- Current Issue
- Online First
- Adopt
- Most Downloaded Archive
-
Xue Xianbin, Tan Beihai, Yu Rong, Zhong Wuchang
2024,47(6):1-7, DOI:
Abstract:
Urban intersections are accident-prone sections. For intelligent networked vehicles, it is very important to carry out risk detection and collision warning during driving to ensure the safety of driving. This paper proposes a traffic risk field model considering traffic signal constraints for urban intersections with traffic lights, and designs a three-level collision warning method based on this model. Firstly, a functional scenario is constructed according to the potential conflict risk points of urban intersections, and the vehicle risk field model is carried out considering the constraint effect of traffic signal. In order to solve the problem of collision warning, a three-level conflict area is proposed to be divided by the index, and the collision risk of the main vehicle is measured according to the position of the potential energy field around the main vehicle by calculating the corresponding field strength around the main vehicle. The experimental results show that the designed model can accurately warn the interfering vehicles entering the potential energy field of the main vehicle, the warning success rate can reach 100%, and the false alarm rate is only 3.4%, which proves the reliability and effectiveness of the proposed method.
-
Wei Jinwen, Tan Longming, Guo Zhijun, Tan Jingyuan, Hou Yanchen
2024,47(6):8-13, DOI:
Abstract:
To address the issue of low accuracy in indoor static target positioning with existing single-antenna ultra-high frequency RFID technology, this paper proposes a new RFID localization method based on an antenna boresight signal propagation model. The method first determines the height position of the target through vertical antenna scanning; secondly, it adjusts the antenna height to match that of the target and then performs stepwise rotational scanning to identify the target′s azimuth angle; furthermore, it utilizes a Sparrow Search Algorithm optimized back propagation neural network to establish a path loss model for ranging purposes; finally, it integrates the height, azimuth angle, and distance data to complete the target positioning. Experimental results show that in indoor environment testing, the proposed method has an average positioning error of 7.2 cm, which meets the positioning requirements for items in general indoor scenarios.
-
Wang Huiquan, Wei Zhipeng, Ma Xin, Xing Haiying
2024,47(6):14-19, DOI:
Abstract:
To solve the problem of low control accuracy of the tidal volume emergency ventilation for lower air pressure at high altitudes, we propose a dual-loop PID tidal volume control system, which utilizes a pressure-compensated PID controller to adjust fan speed, supplemented by an integral-separate PID controller in order to achieve precise control of airflow velocity.Compared with single-loop PID control, the rapid response and no overshooting are observed in the performance tests of the dual-loop control system at an altitude of 4 370 m and atmospheric pressure of 59 kPa, in addition, the output error of the average airflow velocity decrease to 3.19% (the maximum error is 4.1%), which is superior to that of current clinical equipment. Our work offers an effective solution for high-altitude emergency ventilator tidal volume control, and contributes important insights to the development of ventilation control technology in special environments.
-
Fang Xin, Shen Lan, Li Fei, Lyu Fangxing
2024,47(6):20-27, DOI:
Abstract:
The high-frequency measurement data of underground vibration signals can record more specific details about the dynamic response of drilling tools, which is helpful for analyzing and diagnosing abnormal vibrations underground. However, the high-frequency measurement generates a large amount of measurement data, resulting in significant storage pressure for underground vibration measurement equipment. The proposed method uses compressed sensing technology to selectively collect and store sparse underground vibration data and then recover high-frequency measurement results through a signal reconstruction algorithm. In the process of realizing this method, an innovative method of constructing a layered Fourier dictionary against spectrum leakage is proposed, and an improved OMP signal reconstruction algorithm based on layered tracking is researched and realized, which greatly reduces the time required for signal recovery. Simulation and experimental test results demonstrate the method′s effectiveness, achieving a system compression ratio of 18.9 and a reconstruction error of 52.1 dB. The proposed method may greatly reduce the data storage pressure of the measuring equipment in the underground, and provides a new way to obtain high-frequency measurement data of underground vibration.
-
2024,47(6):28-33, DOI:
Abstract:
With the increasing demand for satellite network, vehicle-connected network, industrial network and other service simulation, this paper proposes a multi-session delay damage simulation method based on delay range strategy to build flexible software network damage simulation, aiming at the problems of small number of analog links, low flexibility and high resource occupation of traditional dedicated channel damage instruments. In this method, the delay damage of each session flow is identified and controlled independently, and the multi-queue merging architecture based on time delay strategy is adopted to reduce the resource consumption. The experimental results show that compared with the traditional dedicated device and simulation software NetEm, the proposed method supports the independent delay configuration of million-level links, increases the number of session streams from ten to one million, and reduces the memory consumption by at least 85% under each bandwidth, which meets the requirements of large scale and accuracy, and greatly reduces the system cost.
-
Feng Zhibo, Zhu Yanming, Liu Wenzhong, Zhang Junjie, Li Yingchun
2024,47(6):34-40, DOI:
Abstract:
The data bits and spread spectrum codes of the spaceborne spread-spectrum transponder are asynchronous. Due to the influence of transmission system noise and Doppler frequency shift, it can cause attenuation of peak values related to receiving and transmitting spread spectrum codes, leading to a decrease in capture performance. Traditional capture techniques often have problems such as high algorithm complexity, slow capture speed, and difficulty adapting to the requirements of large frequency offsets of hundreds of kilohertz. This article proposes a spread spectrum sequence search method that truncates the spread spectrum sequence into two segments for correlation operations, and combines the signal squared sum FFT loop for a large frequency offset locking, effectively suppressing the attenuation of correlation peaks and improving pseudocode capture performance. MATLAB simulation and FPGA board level testing show that the proposed spread spectrum signal capture scheme can resist Doppler frequency shifts of up to ±300 kHz, with an average capture time of about 95 ms. In addition, the FPGA implementation of this algorithm saves about 47% of LUT, 43% of Register, and more than half of DSP and BRAM resources compared to traditional structures, making it of great application value in resource limited real-time communication systems.
-
Yang Yi, Aimen Malik, Yuan Ruifu, Wang Keping
2024,47(6):41-49, DOI:
Abstract:
Hydraulic support pillar pressure prediction has been a pivotal basis for decision-making in the mining process. It has been one of the fundamental pieces of information for ensuring the stability of the surrounding rock. However, although the pressure of hydraulic support pillars followed certain patterns, it couldn’t be predicted using simple mathematical models. Additionally, during the mining process, issues such as the support detaching the roof, roof fragmentation, and sensor detection errors introduced a significant amount of random noise, turning the pressure data into a non-stationary time series. This significantly complicated the pressure prediction. Based on the Transformer model, this paper proposed a differencing non-stationary Transformer model, which introduced differencing normalization and de-normalization operations in the Transformer′s Encoder and Decoder, respectively, to enhance the stationarity of the series. At the same time, a de-stationary attention mechanism was deployed within the Transformer to calculate the correlations between sequence elements, which thereby enhanced the model′s predictive capabilities. Comparative experiments on a real coal mine support pillar dataset showed that the differencing non-stationary Transformer model proposed in this paper achieved a prediction performance of 0.674, which was significantly better than LSTM, Transformer, and non stationary Transformer models.
-
Peng Duo, Luo Bei, Chen Jiangxu
2024,47(6):50-57, DOI:
Abstract:
Aiming at the non-range-ranging location problem of multi-storey WSN structures, a three-dimensional indoor multi-storey structure location algorithm IAODV-HOP algorithm based on improved Tianying is proposed in the field of large-scale indoor multi-storey structure location for some large commercial supermarkets, hospitals, teaching buildings and so on. Firstly, the nodes are divided into three types of communication radius to refine the number of hops, and the average hop distance of the nodes is modified by using the minimum mean square error and the weight factor. Secondly, the IAO algorithm is used to optimize the coordinates of unknown nodes, and the population is initialized by the best point set strategy, which solves the problem that the quality and diversity of the population are difficult to guarantee due to the random distribution of the initial population in the Tianying algorithm. In addition, the golden sine search strategy is added to the local search to improve the position update mode of the population, and enhance the local search ability of the algorithm. Through simulation experiments, compared with traditional 3D-DV-Hop, PSO-3DDV-Hop, N3-3DDV-Hop and N3-ACO-3DDV-Hop, the normalized average positioning error of the proposed algorithm IAODV-HOP is reduced by 70.33%, 62.67%, 64% and 53.67%, respectively. It has better performance, better stability and higher positioning accuracy.
-
Ma Dongyin, Wang Xinping, Li Weidong
2024,47(6):58-63, DOI:
Abstract:
Aiming at the Automatic Train Operation of high-speed train,an algorithm based on BAS-PSO optimized auto disturbance rejection control (ADRC) is used to design speed tracking controller.The ADRC is designed based on the train dynamics model,ITAE is used as the objective function,and the parameters are tuned by BAS-PSO.CRH380A train parameters are selected, The tracking effect of BAS-PSO, PSO and improved shark optimized ADRC algorithm on the target speed curve of the train is compared by MATLAB simulation,The tracking error of the train target speed curve based on the BAS-PSO optimized ADRC algorithm is kept in the range of ±0.4 km/h,which is closer to the target speed curve than the other two algorithms.The results show that the ADRC based on BAS-PSO optimization has the advantages of small tracking error and strong anti-interference ability.
-
Li Ya, Wang Weigang, Zhang Yuan, Liu Ruipeng
2024,47(6):64-70, DOI:
Abstract:
A task offloading strategy based on Vehicle Edge Computing (VEC) is designed to meet the requirements of complex vehicular tasks in terms of latency, energy consumption, and computational performance, while reducing network resource competition and consumption. The goal is to minimize the long-term cost balancing between task processing latency and energy consumption. The task offloading problem in vehicular networks is modeled as a Markov Decision Process (MDP). An improved algorithm, named LN-TD3, is proposed building upon the traditional Twin Delayed Deep Deterministic Policy Gradient (TD3). This improvement incorporates Long Short-Term Memory (LSTM) networks to approximate the policy and value functions. The system state is normalized to accelerate network convergence and enhance training stability. Simulation results demonstrate that LN-TD3 outperforms both fully local computation and fully offloaded computation by more than two times. In terms of convergence speed, LN-TD3 exhibits approximately a 20% improvement compared to DDPG and TD3.
-
Fan Shuaixin, Gu Yuhai, Zou Zhi, Cui Yue
2024,47(6):71-78, DOI:
Abstract:
Feature matching is often used to calculate pose information in visual measurement, but there is no available algorithm for designing feature matching for infrared active targets. In order to achieve matching of infrared active targets with different distributions, this paper proposes a general two-stage feature Point matching method. The first stage is coarse registration. First, the convex hull of the image feature point set is detected to obtain the outermost points. Fast coarse registration is achieved by constructing a triangle feature set and using Mahalanobis distance to calculate and search for similar triangles. The second stage is precise matching. First, the Euler angle is calculated through coarse matching features to avoid the 180° rotational symmetry of the matching results. In order to solve the problem of possible missing feature points after coarse registration, the epipolar constraint fine matching strategy is adopted to make full use of the existing features. Match the geometric information of feature points to effectively achieve accurate matching of remaining points. Theoretical analysis and experiments show that under the rotational symmetry point set and the non-rotation symmetry point set composed of 13 infrared luminescent points, this method can efficiently match within the absolute rotation range of 0°~40°, and the experimental test limit performance can reach 50°, and has good robustness to the occlusion of feature points in actual scenes. The experimental results verify its adaptability and stability, and has high practical value.
-
Zhou Jianxin, Zhang Lihong, Sun Tenghao
2024,47(6):79-85, DOI:
Abstract:
Aiming at the problems that the standard honey badger algorithm (HBA) is easy to fall into local optimum, low search accuracy and slow convergence speed, a honey badger algorithm based on elite differential mutation (EDVHBA) is proposed. The elite solution searched by the two optimization strategies in the standard HBA is combined with differential mutation to generate a new elite solution. The use of three elite solutions to guide the next iteration of the population can increase the diversity of the algorithm solution and prevent the algorithm from falling into premature convergence. At the same time, the nonlinear density factor is improved and a new position update strategy is introduced to improve the convergence speed and optimization accuracy of the algorithm. In order to verify the performance of the algorithm, simulation experiments are carried out on eight classical test functions. The results show that compared with other swarm intelligence algorithms and improved HBA, EDVHBA can find the optimal value 0 in the unimodal function, and converge to the ideal optimal value in the multimodal function after about 50 iterations, which verifies that EDVHBA has better optimization performance.
-
Zhang Huimin, Li Feng, Huang Weijia, Peng Shanshan
2024,47(6):86-93, DOI:
Abstract:
A lightweight improved model CAM-YOLOX is designed based on YOLOX to address the issues of false alarms of land targets and missed detections of shore targets encountered in ship target detection in large scene Synthetic Aperture Radar(SAR)images in near-shore scenes. Firstly, embed Coordinate Attention Mechanism in the backbone to enhance ship feature extraction and maintain high detection performance; Secondly, add a shallow branch to the Feature Pyramid Network structure to enhance the ability to extract small target features; Finally, in the feature fusion network, Shuffle unit was used to replace CBS and stacked Bottleneck structures in CSPLayer, achieving model compression. Experiments are carried out on the LS-SSDD-v1.0 remote sensing dataset. The experimental results show that compared with the original algorithm, the improved algorithm in this paper has the precision increased by 5.51%, the recall increased by 3.68%, and the number of model parameters decreased by 16.33% in the near-shore scene ship detection. The proposed algorithm can effectively suppress false alarms on land and reduce the missed detection rate of ships on shore without increasing the number of model parameters.
-
Ma Zhewei, Zhou Fuqiang, Wang Shaohong
2024,47(6):94-99, DOI:
Abstract:
A feature point extraction algorithm based on adaptive threshold and an improved quadtree homogenization strategy are proposed to address the issue of low positioning accuracy or low matching logarithms of the SLAM system caused by the ORB-SLAM2 algorithm extracting fewer feature points in dark environments or environments with fewer textures, resulting in system crashes. Firstly, based on the brightness of the image, FAST (Features from Accelerated Seed Test) feature points are extracted using adaptive thresholds. Then, an improved quadtree homogenization strategy is used to eliminate and compensate the feature points of the image, completing feature point selection. The experimental results show that the improved feature point extraction algorithm increases the number of matching pairs by 17.6% and SLAM trajectory accuracy by 49.8% compared to the original algorithm in dark and textured environments, effectively improving the robustness and accuracy of the SLAM system.
-
Zhang Fubao, Wu Ting, Zhao Chunfeng, Wei Xianliang, Liu Susu
2024,47(6):100-108, DOI:
Abstract:
In real-time detection of saw chain defects based on machine vision, factors like oil contamination and dust impact image brightness and quality, leading to a decrease in the feature extraction capability of the object detection network. In this paper, an automated saw chain defect detection method that combines low-light enhancement and the YOLOv3 algorithm is proposed to ensure the accuracy of saw chain defect detection in complex environments. In the system, the RRDNet network is used to adaptively enhance the brightness of the saw chain image and restore the detailed features in the dark areas of the image. The improved YOLOv3 algorithm is used for defect detection. FPN structure is added with a feature output layer, the a priori bounding box parameters are re-clustered using the K-means clustering algorithm, and the GIoU loss function is introduced to improve the object defect detection accuracy. Experimental results demonstrate that this approach significantly improve image illumination and recover image details. The mAP value of the improved YOLOv3 algorithm is 92.88%, which is a 14% improvement over the original YOLOv3. The overall leakage rate of the system eventually reduces to 3.2%, and the over-detection rate also reduces to 9.1%. The method proposed in this paper enables online detection of saw chain defects in low-light scenarios and exhibits high detection accuracy for various defects.
-
Zhang Bian, Tian Ruyun, Han Weiru, Peng Yuxin
2024,47(6):109-115, DOI:
Abstract:
In order to solve the problems that the traditional SPD life alarm characterization method can not clearly correspond to the real life state of SPD, and the remaining life model characterized by a single degradation related parameter has poor predictability, a multi-parameter SPD life remote monitoring system based on STM32 is designed. With STM32 as the main controller, the important parameters such as surge current, leakage current, surface temperature and tripping status of SPD are collected in real time, and the status information is uploaded to the One net cloud platform through the BC20 wireless communication module. The One net cloud platform displays and stores the multi-parameter data of SPD in real time, and provides data management and analysis. The SVM classification model is used to judge whether SPD is damaged and the BO-LSTM prediction model is used to predict the remaining life of SPD. Based on the positioning function of BC20, the real-time geographic location of SPD can be viewed on the host computer. The results show that the root mean square error and average absolute error of the BO-LSTM prediction model are 0.001 3 and 0.001 8, and the system can monitor the SPD status in real time, effectively predict the remaining life value of SPD, and give early warning in time.
-
Shi Shujie, Zhao Fengqiang, Wang Bo, Yang Chenhao, Zhou Shuai
2024,47(6):116-122, DOI:
Abstract:
Rolling bearings play an important role in rotating machinery. If a fault occurs, it can cause equipment shutdown, and in severe cases, endanger the safety of on-site personnel. Therefore, it is necessary to diagnose the fault. In response to the difficulty in extracting fault features of rolling bearings and the low accuracy of traditional classification methods, this paper proposes a fault diagnosis method based on Set Empirical Mode Decomposition (EEMD) energy entropy and Golden Jackal Optimization Algorithm (GJO) optimized Kernel Extreme Learning Machine (KELM), achieving the goal of extracting fault features of rolling bearings and correctly classifying them. Through experimental data validation, this method can extract the fault information features hidden in the original signal of rolling bearings, with a diagnostic accuracy of up to 98.47%.
-
Zhan Huiqiang, Zhang Qi, Mei Jianing, Sun Xiaoyu, Lin Mu, Yao Shunyu
2024,47(6):123-130, DOI:
Abstract:
Aiming at the force test in low-speed pressurized wind tunnel, the original data source of aerodynamic characteristic curve is analyzed. With the balance signal, flow field state and model attitude as the main objects, combined with the test control process, the abnormal detection methods and strategies of the test data are studied from the dimensions of single point data vector, single test data matrix and multi-test data set in the same period, and an expert system for abnormal data detection is designed and developed based on this core knowledge base. The system inference engine automatically detects online during the test, and realizes the pre-detection and pre-diagnosis of the original data through data identification, rule reasoning, logical reasoning and knowledge iteration. The experimental application results show that the expert system is highly sensitive to the detection of abnormal types such as abnormal bridge pressure, linear segment jump point and zero point detection, which guides the direction of abnormal data analysis and improves the efficiency of problem data investigation.
-
Xu Lijie, Wang Yanlin, Chen Qingshan
2024,47(6):131-136, DOI:
Abstract:
In order to realize high-precision real-time detection of large-stroke precision optical focusing components In order to realize high-precision real-time detection of large-stroke precision optical focusing components, high-precision long-displacement sensors based on axial eddy current effect are studied. A long-displacement eddy current probe simulation model is established for linearity testing, an eddy current sensor test system is built for accuracy experiments, and the long-displacement eddy current sensor is connected to the precision optical focusing assembly. The experimental results show that while the measurable displacement reaches 24 mm, the linearity is better than 1%, the resolution is better than 0.5 μm, the accuracy is better than 1 μm, and the high-precision long-displacement eddy current sensor meets the requirements of the precision optical focusing assembly.
-
Cheng Dongxu, Wang Ruizhen, Zhou Junyang, Zhang Kai, Zhang Pengfei
2024,47(6):137-142, DOI:
Abstract:
For the tobacco industry, there is currently no detection device and method for detecting the heating temperature and temperature uniformity of heated cigarette smoking sets. In order to solve the temperature measurement needs of micro rod-shaped heating sheets in a narrow space, this article developed a cigarette heating rod thermometer, and designed a new structure suitable for temperature measurement of cigarette heating rods. In order to verify the accuracy and reliability of the measurement results of the cigarette heating rod thermometer, uncertainty analysis of the thermometer was performed. The analysis results are based on the "GB/T 13283-2008 Accuracy Level of Detection Instruments and Display Instruments for Industrial Process Measurement and Control" standard. The measurement range is 100 ℃~400 ℃, meeting the requirements of level 0.1. The final experiment verified that the heating temperature field of different cigarettes can be effectively measured.
-
Xu Ziqiang, Li Cheng, Mu Lianbo, Wang Suilin, Liu Jianjun
2024,47(6):143-150, DOI:
Abstract:
To improve the positioning accuracy of the leakage application of the direct buried hot water heating pipe network by acoustic method, based on the analysis of the applicability of various wavelet threshold functions, an improved threshold function noise reduction method is proposed. This method can theoretically overcome the constant deviation of the soft threshold function and the shortcomings of the hard threshold function signal oscillation. Through setting adjustment parameters, improving the noise reduction ability, and retaining the signal of the region less than the threshold point to avoid effective signal loss. The experiment was carried out in a large direct buried hot water circulation pipe network. The research showed that the leakage positioning error was within ±1 m and the positioning accuracy reached 0.11%~3.49%. Finally, the acoustic leakage detection method was adopted in a practical engineering case of a Beijing heating system. The leakage location error is 0.37%~0.66%, and the positioning accuracy has efficiently is improved.
-
Zhang Xinyu, Fan Ximei, Li Zhonghu, Li Jing, Wang Jinming
2024,47(6):151-156, DOI:
Abstract:
Ultrasonic phased array theory and Total Focusing Method are introduced to identify internal defects of thick-walled pipelines，the image is reconstructed. Sparse Matrix Capture technology is used to reduce data volume and improve imaging efficiency, it simulated the ultrasonic phased array total focus imaging of thick-walled pipelines with the outer diameter of 550mm and the wall thickness of 65 mm by the finite element method. The results show that when the excitation center frequency is 5 MHz, the element width is 0.5 mm, the element spacing is 1 mm, the number of array elements is 32. the effectively of the image of Sparse Matrix Capture-Total Focusing Method is 74.81% higher than that of Full Matrix Capture-Total Focusing Method, which is improves the imaging speed and meets the requirements of rapid imaging.
-
Long Biao, Yang Jun, Chen Huiping, Chen Guangrun, Zhao Peiyang
2024,47(6):157-163, DOI:
Abstract:
In order to solve the problem that the audio signal processing in the voice communication system has a large amount of data, a lot of stray signals, and the received audio signals of the frequency modulation receiver are large and small, a lightweight audio signal processing algorithm is proposed, and based on this algorithm, the audio signal receiving and automatic gain control are realized on the field programmable gate array(FPGA) platform. The algorithm combines digital down conversion technology, multistage extraction filtering technology and automatic gain control technology (AGC) technology, and is applied to the audio signal processing system. The RF analog signal received from the upper antenna is converted into baseband audio signal through analog-to-digital conversion and digital down-conversion, and the stray signal in the baseband signal is filtered through four-stage extraction filtering, reducing the complexity and power consumption of the system. At the same time, the digital AGC controls and adjusts the baseband audio signal to output a more stable audio signal. The experimental results show that the algorithm can effectively reduce the information rate from 102.4 MHz to 32 kHz, reduce the computation burden, improve the signal quality, and reduce the resource utilization of FPGA. And the automatic gain control adjustment of audio signal is realized, and the adjustment time is only 12.8 μs, which meets the power stability time of the receiver.
-
Li Hui, Hu Dengfeng, Zhang Kai, Zou Borong, Liu Wei
2024,47(6):164-172, DOI:
Abstract:
In signal generation algorithms, a large number of labeled signal samples are needed for network training, but it is usually difficult to obtain signals carrying message information markers in bulk. To address this problem, this paper proposes a method based on CycleGAN and transfer learning, which realizes the generation of Enhanced LORAN signals without the need for a large number of signals and the corresponding messages as markers and uses migration learning to generate them quickly with a small number of measured signals. The structure of the CycleGAN includes two generators and two discriminators, using the Enhanced LORAN signals and message data sets that do not need to be one-to-one correspondence, so that the generator learns the interconversion relationship between the two data sets, and realises that the input message data can generate the Enhanced LORAN signals corresponding to it, for the characteristics of the Enhanced LORAN signal, the network model is improved using a one-dimensional convolution, residual network, and self-attention mechanism. Experimentally confirmed, it is confirmed that the mean square error of the signal generated by this paper with the measured data is 0.015 3, the average Pearson correlation coefficient is 0.984 3, and the accuracy of the contained message information is 99.02%. To verify the universality of the algorithm, this paper validates the algorithm on PSK, ASK, and FSK datasets, and the experimental results show that the generated signals satisfy the expectations and provide a new idea for signal modulation and demodulation with unknown parameters.
-
Qiu Yanbo, Chu Kaibin, Zhang Ji, Feng Chengtao
2024,47(6):173-181, DOI:
Abstract:
In order to improve the image quality of font generation and reduce the labour cost of font design, a method for few-shot font generation based on multilevel channel attention network is proposed. Firstly, the method acquires important local features through the style-aware attention module; then a multilevel attention mechanism is designed, where shallower layers can only observe the local features of the image, while deeper layers can observe all the features of the image, and new stylistic features are constructed by aggregating the local features of different levels. Finally, a content loss function, a style loss function and a L1 loss function are used to optimise the parameters of the model and stabilise the training of the network so that the generated images are consistent with the target font in terms of content and style. The experimental results show that the method has a strong generalisation to fonts of unknown style and fonts of unknown content. Compared to other methods, the proposed method shows better experimental results that maintain the integrity of the content structure and the accuracy of the font style.
-
Chen Haoan, Li Hui, Huang Rui, Fu Pingbo, Zhang Jian
2024,47(6):182-189, DOI:
Abstract:
Facing the challenges of regulating unmanned aerial vehicles (UAV), and based on an YOLOv5-Lite improved model, this paper incorporates an exponential moving sample weight function that dynamically allocates loss function weights to the model during the training iteration. Through model computations, we achieve real-time UAV tracking using a two-degree-of-freedom servo platform. Furthermore, video capture, model calculations, and servo control are all performed locally on a Raspberry Pi 4B.The optimized model maintains the original model's parameter count while achieving a mAP@.5:.95 score of 70.2%, representing a 1.5% improvement over the baseline model. Real-time inference on the Raspberry Pi yields an average speed of 2.1 frames per second (FPS), demonstrating increased processing efficiency. Simultaneously, the Raspberry Pi controls a servo platform via the I2C protocol to track UAV targets, ensuring real-time dynamic monitoring of UAVs. This optimization enhances system reliability and offers superior practical value.
-
Zhou Guoliang, Zhang Daohui, Guo Xiaoping
2024,47(6):190-196, DOI:
Abstract:
The gesture recognition method based on surface electromyography and pattern recognition has a broad application prospect in the field of rehabilitation hand. In this paper, a hand gesture recognition method based on surface electromyography (sEMG) is proposed to predict 52 hand movements. In order to solve the problem that surface EMG signals are easily disturbed and improve the classification effect of surface EMG signals, TiCNN-DRSN network is proposed, whose main function is to better identify the noise and reduce the time for filtering the noise. Ti is a TiCNN network, in which convolutional kernel Dropout and minimal batch training are used to introduce training interference to the convolutional neural network and increase the generalization of the model; DRSN is a deep residual shrinkage network, which can effectively eliminate redundant signals in sEMG signals and reduce signal noise interference. TiCNN-DRSN has achieved high anti-noise and adaptive performance without any noise reduction pretreatment. The recognition rate of this model on Ninapro database reaches 97.43% 0.8%.
Volume 47, 2024 Issue 6
Research&Design
Theory and Algorithms
Information Technology & Image Processing
Online Testing and Fault Diagnosis
Data Acquisition
-
Heating data detection and cleaning based on CEEMDAN-CNN-LSTM
梁晓龙, 李金刚, 徐平平, 王佳龙, 马雅楠, 陈涛, 孟现阳
Abstract:
Using the accurate parameters of the heating system has guiding significance for monitoring system status and identifying abnormal conditions. However, a large amount of terminal data may have distortion problems. To address this, this paper proposed a method for detecting and cleaning abnormal data. Signal modal decomposition combined with deep learning was used to construct a detection and cleaning model. The first step involves conducting CEEMDAN mode decomposition of the heating load obtained by DeST. Subsequently, the intrinsic mode functions and residual quantities generated from the decomposition are input into the CNN-LSTM deep learning prediction model to achieve high-precision prediction results. Finally, based on the deviation between predicted values and data to be cleaned, abnormal detection and data cleaning are completed. The CEEEMDAN-CNN-LSTM combined model in this paper achieves superior accuracy and F1 scores of 91.36% and 86.21%, respectively, outperforming the other three models. Moreover, the predicted values can be used to replace abnormal values, ensuring the integrity and accuracy of the final data set.
- 1
-
Research on dynamic weighing algorithm based on CSSA-LSTM neural network
Abstract:
In order to improve the measurement accuracy of dynamic weighing and realize real-time monitoring and fine management of intelligent pasture, a dynamic weighing algorithm based on chaotic sparrow search algorithm (CSSA) to optimize LSTM neural network is proposed. The data is collected by the dynamic weighing platform, and the Kalman filter algorithm is used to process the interference data. The CSSA-LSTM neural network model is established by using the Tent mapping strategy and the sparrow search algorithm after Gaussian mutation to optimize the parameters of the LSTM neural network. The results show that the average absolute percentage error of CSSA-LSTM neural network is within 1.5%, the average absolute error is reduced by 0.874, and the root mean square error is reduced by 1.1153. The comparative experiments show that the hybrid algorithm has the smallest prediction error and effectively improves the measurement accuracy of dynamic weighing.
- 1
-
Modulation and recognition algorithm of UFMC system based on feature fusion
Abstract:
The modulation recognition problem of subcarriers in the Universal Filter Multi-Carrier (UFMC) system for non-cooperative communication needs to be addressed. Therefore, a modulation recognition algorithm based on feature fusion is proposed for the UFMC system. Firstly, the receiver signal of the UFMC system is obtained and input features such as in-phase and quadrature sequence and amplitude phase sequence are extracted. Subsequently, a neural network module is constructed by connecting a convolutional neural network with a long short-term memory network in series, while also incorporating a gated recurrent unit in parallel. Finally, modulation recognition of UFMC system subcarriers is performed. The experimental results demonstrate that the constructed neural network effectively identifies five signals (BPSK, 4QAM, 8QAM, 16QAM, 64QAM) with a recognition accuracy reaching 100% when SNR is greater than or equal to 6 dB.
- 1
-
Data fusion of GNSS common-view multi-reference stations based on robust estimation
Abstract:
In order to meet the needs of remote time users for standard time UTC (NTSC) nanosecond distribution, a standard time remote reproduction system has been established. The single-reference terminal service model currently used in the system has certain risks. If the single receiver fails, it will affect the accuracy of the resulting deviation between local time and satellite clock (i.e., the time difference between satellite time and local time).To solve the above problems, this paper proposes a method based on robust estimation for GNSS common-view multi-reference stations to fuse the time difference between satellite time and local time. In this method, the median absolute deviation (MAD) is used to detect the outliers of the time difference between satellite time and local time data, and the robust estimation method of IGG III. equivalent weight function is used to fuse the above data of multiple stations, to output a set of stable reference station reference values. Comparing the outlier detection performance of the MAD method and the 3-Sigma method through the Matlab simulation, the MAD method is more applicable for the time difference between satellite time and local time data of the reference stations. At the same time, the fusion method based on robust estimation is compared with the equal-weight fusion method, the standard deviation of the fusion data of the former is 0.11 ns-6.65 ns lower than that of the latter, which improves the stability of the system.
- 1
-
A Precision Measurement Unit Circuit Design for Integrated Circuit Testing
Abstract:
With the rapid development of the integrated circuit industry, higher requirements are put forward for integrated circuit testing, and the Precision Measurement Unit (PMU) is the core unit for integrated circuit DC parameter testing. A PMU circuit for integrated circuit testing is designed in this paper, which uses a Field-Programmable Gate Array (FPGA) to control the DAC module to apply voltage excitation. The excitation signal after the PI regulator and power amplification is applied to the Device Under Test (DUT) through the resistor matching network, Then, the ADC module reads back the test response data to realize the parameter testing functions such as applying voltage to measure current and applying current to measure voltage. The designed PMU circuit has the advantages of wide test range and high measurement accuracy, with an applied or measured voltage range of -10V to +15V and a maximum current of ±1.838A. The system performance in different test modes was calibrated and functionally verified with high-precision resistive loads, and the experimental results show that the system calibrated test error is better than 0.05%, which is able to meet the requirements of DC parameter testing of general-purpose integrated circuits.
- 1
-
Design of multi-channel communication system based on out-of-band real-time calibration
Abstract:
To meet the application requirements of multi-antenna beamforming in 5G mobile communications, this paper designs and implements a multi-channel Software Defined Radio (SDR) communication system, and based on this system, achieves broadband multi-channel multi-frequency point synchronization calibration. To address the issue of multi-channel synchronization drift due to environmental factors such as temperature, this paper innovatively proposes a real-time synchronization scheme based on out-of-band calibration signals. This scheme inserts calibration signals into the redundant bandwidth of OFDM communications to track the drift of multi-channel response errors over time and compensates for the in-band effective signals. At the 1GHz frequency point, the system effectively compensates for the phase response error drift of 2.8 degrees and amplitude response error drift of 0.2dB caused by temperature variations through real-time calibration. After initialization calibration and real-time calibration, the phase error is controlled within 0.4 degrees, and the amplitude response error is controlled within 0.05dB in the temperature range of 40 to 80 degrees. This scheme not only achieves higher precision but is also completely transparent to the end user, allowing calibration without interrupting communication operations, making it highly significant for the design of 5G multi-channel synchronization.
- 1
-
Research on the control of fuel cell gas supply system with tandem sliding mode structure
Abstract:
Aiming at the problem that the dynamic performance of the fuel cell air supply system is susceptible to load changes and external environmental factors, a tandem-type control strategy combining super-helical sliding mode control and terminal sliding mode control is designed. A control-oriented fifth-order dynamic model is established, and the control problem of tracking the optimal oxygen excess ratio , maximum net output power and cathode pressure measurement of the air supply system during load change is proposed; the optimal expectation value is extracted and the controller is designed, and the closed-loop stability is verified using the Lyapunov method. Simulation analysis shows that the constructed observer perturbation estimate is within 0.01% error from the theoretical actual value. Compared with PID control, the response time of tracking the optimal expected value of the oxygen excess ratio is improved by 6.9%, the maximum net power output is increased by 0.2%, and the response time of cathode pressure is improved by 60%. From the results, it can be concluded that the strategy of this paper can effectively control the oxygen excess ratio of the gas supply system to track the optimal desired value and output the maximum net power when the load changes, can accurately and rapidly estimate the cathode pressure, can better estimate the perturbation, and has a strong anti-disturbance ability.
- 1
-
Research on the prediction of the remaining life of internal corrosion in oilfield water injection pipelines
Abstract:
In order to estimate the remaining safe service life of the pipeline, the extreme gradient boosting algorithm model besed on grey correlating analysis was proposed. Grey Relational Analysis (GRA) was used to calculate and rank the correlation values between each influencing factor and the remaining life, and the data of the influencing factors with high correlation were preferably input into the eXtreme Gradient Boosting (XGBoost) algorithm for the prediction of the remaining life of corroded pipelines. Taking an oilfield water injection pipeline as an example, the results showed that the Root Mean Square Error (RMSE) was 0.012, the Mean Absolute Error (MAE) was 0.068, and the goodness of fit (R2) was 0.999, compared with the other three prediction models, the results showed that the prediction accuracy and generalization performance of the model constructed in this paper were better.
- 1
-
Traffic sign mounting angle measurement based on object detection and binocular ranging
Abstract:
Aiming at the problems such as the difficulty of measuring the angle of traffic sign installation and the single measurement method. Through YOLOv8 object detection accuracy experiments, the model is made to have an accurate object detection frame to ensure the accuracy of signage pixel coordinates. In this paper, iterative geometric encoder stereo matching model (IGEV) is introduced to improve the binocular ranging model using migration learning. Ranging experiments were set up in 1.5m, 2.0m, 2.5m and 3m four distance variables, after the experiments to verify the accuracy of the ranging model, and the true distance value compared with the ranging error rate of 0.67%; sign installation angle experiments proved that all the error rate of the angular measurement is less than 7.62%. This paper method sign installation angle measurement method intelligent.
- 1
-
Research on Improved Dijkstra Algorithm Based on Time Window
Abstract:
Aiming at the problem that Dijkstra algorithm can not plan conflict free path in multi AGV system, an improved Dijkstra algorithm based on time window is proposed after analyzing the implementation principle and limitations of Dijkstra algorithm. In the process of Dijkstra algorithm traversing from the starting node to other nodes step by step, the time window conflict judgment of each path node is introduced. By changing the backtracking vector, a shortest path without conflict with other AGV paths is obtained. Finally, the MATLAB software is used to design the corresponding program to verify the algorithm. The simulation results show that the improved Dijkstra algorithm with time windows can effectively plan the shortest path without conflict among the AGVs when planning the multi AGV task path.
- 1
-
Research on direction finding algorithm of ultra-short baseline phase interferometer
Abstract:
There are many solutions to the direction finding problem of the radar radiation source on a single platform, but the high-speed and high-precision direction finding method needs further research. In order to obtain the accurate estimation value of the phase difference of the radar emitter and solve the signal arrival azimuth angle, this paper combines the theoretical ideas of the long and short baseline method and the virtual baseline method, and proposes a virtual ultra-short baseline phase interferometer defuzzification algorithm. Under the condition of poor signal-to-noise ratio, as the phase error increases, the correct rate of defuzzification can be maintained above 70%; the root mean square error of the azimuth angle can reach 0.05°. It is verified by simulation that the defuzzification algorithm used in this paper has high-precision characteristics, and has theoretical and practical significance for measuring the azimuth angle of the radar radiation source.
- 1
-
Logistics IOT intelligent decision support platform for differentiated access of multiple ubiquitous intelligent devices
Abstract:
Aiming at the problems such as administrative confusion, poor data processing efficiency and slow decision-making speed of logistics IOT. A logistics IOT intelligent decision support platform for differentiated access of various ubiquitous intelligent devices is designed. According to the data generated by a variety of ubiquitous intelligent devices, 5G non orthogonal code access method is adopted to realize the equipment differential access. Thrift data acquisition technology is used to complete data collection. Intelligent fair scheduling algorithm is used for data processing and data transportation scheduling, and then the high-speed data acquisition is adopted An intelligent decision support platform is designed by using hybrid cloud storage algorithm to store and classify data. Through the comparative analysis of three different types of platform simulation diagrams, it is proved that the intelligent decision-making platform designed in this study has the largest increase in data transmission gradient and less waiting delay time, which can effectively solve the problems such as poor decision-making efficiency and data confusion of logistics IOT.
- 1
-
Logistics business data collection, fusion and analysis method based on multi-source and heterogeneous
Abstract:
Aiming at the problems of low efficiency and poor expansibility in the traditional logistics business data processing method with multi-source and heterogeneous structure, this paper studies a set of practical solutions. The acquisition system of the scheme uses the multi port adaptive method to collect, which solves the problem of low scalability of the traditional acquisition system. The acquisition and processing dual thread mode is adopted to improve the collection efficiency. This paper also studies a combination algorithm of multi-source heterogeneous data fusion. Through fuzzy reasoning algorithm, the two data fusion algorithms are combined skillfully to optimize and complement each other to improve the multi-source heterogeneous logistics business data fusion. The experimental results show that the acquisition system has high accuracy and efficiency, and the loss value of logistics business data fusion is less than 0.07.
- 1
-
Construction of desired response of LMS adaptive filter based on autocorrelation*
Abstract:
Aiming at the problem that the desired response error of the least mean square (LMS) adaptive filter constructed by spectral subtraction and spectrum method was large under the condition of low signal-to-noise ratio (SNR), based on the analysis of LMS adaptive filtering principle, an autocorrelation method is proposed to construct the desired response of LMS adaptive filter. Firstly, according to the characteristic that the noise was uncorrelated at different times, the input signal was delayed; then, in order to detect the periodic signal from the low signal-to-noise ratio environment, the autocorrelation of the delayed signal was calculated; finally, the autocorrelation signal was taken as the expected response. Simulation results show that the proposed method is effective and can accurately construct the desired response for LMS adaptive filtering under the condition of low SNR.
- 1
-
Wireless passive saw temperature sensor measurement system
Abstract:
At present, saw temperature sensor is widely used in various fields due to its advantages of high Q value, small volume and long-distance transmission. A general temperature measurement system is designed for this kind of sensor, which has good effect in the temperature range of 20 ℃ to 110 ℃. The system realizes the functions of excitation source transmitting, echo signal receiving and processing, temperature calculation, etc. The time-domain gate extraction algorithm is used to effectively solve the problem of jamming source submerging echo signal in the measurement process and improve the detection accuracy. The temperature rise experiment is designed to explore the relationship between the ambient temperature and the resonance frequency of the sensor. The measurement error is controlled below 5%. Compared with the traditional wired measurement device, it has low cost, high flexibility and can meet the special environmental measurement requirements.
- 1
-
Lithium-ion battery parameter identification based on model and dual Kalman filter
Abstract:
Reliable model parameter identification is a key index for battery management systems. To ensure the sustainability of lithium-ion battery under unknown measurement noise, an effective lithium-ion battery model with updated parameters should be developed. To soften the impact of measurement noise from the transducer, an improved equivalent circuit model using current noise as the compensation factor is introduced into the lithium-ion battery. Based on the suppression of parameter disturbances in the equivalent circuit model, a double extended Kalman filter algorithm is used to recursively identify model parameters. Finally, the federal urban driving schedule (FUDS) is loaded on the lithium-ion battery to test the effectiveness of the improved method. The experimental results demonstrate the effectiveness of the model and identification method in the identification of lithium-ion battery parameters.
- 1
-
Daily Peak Load Forecasting based on Gating Recurrent Neural Network
Abstract:
As a non-linear, non-stationary and fluctuating time series, daily peak load is difficult to predict accurately. In this paper, a gated recurrent neural network (GRNN) combined with dynamic time warping (DTW) is proposed to predict daily peak load accurately. DTW distance is used to match the most similar load curve, which can capture the trend of load change. The thermal coding scheme is used to encode the discrete variables and extend their characteristics to represent the influence on the load curve. A dtw-gru algorithm based on DTW is proposed for daily peak load forecasting, and it is tested on the European Intelligent Technology Network (EUNITE) dataset. Simulation results show that the MAPE of this algorithm is only 1.01% compared with other algorithms.
- 1
-
Small sample surface defect detection based on convolutional neural network
Abstract:
At present, the detection of surface defects on the market often relies on human visual recognition. This traditional method consumes a lot of human and material resources, which hinders the development of the market to a certain extent. At the same time, in recent years, deep learning technology has been used in image recognition. In the development of classification, more and more fields are using deep learning for object detection. In order to solve the problem of high miss rate of surface crack defects in traditional manual detection methods, a method based on deep convolution neural network DenseNet (Densely Networks) to detect crack surface defect data was proposed, and two tests were performed on the network The improvement is that one is to add a coding-decoding structure so that the network input and output are graphs, and the second is to increase the number of network convolution kernels and increase the receptive field size of the network feature extraction, so that the improved DeepDenseNet (Deep Densely Networks) The network converges faster, the ability to learn features is stronger, the detection effect is better, and the detection results are compared with the deep convolutional neural network VGGNet model. Experimental results show that the proposed method is effective for small sample surface crack defect data Set has a good detection effect.
- 1
-
Research on multi-mode protocol adaptation and heterogeneous network fusion technology#$NL
Abstract:
In the current method, the evaluation of multi-mode protocol adaptation is poor. When dealing with multi-mode protocol adaptation and heterogeneous network fusion, the problems of low reliability, high blocking rate, and high packet loss rate are addressed. A new multi-mode protocol adaptation and heterogeneous network fusion method is proposed. The method consists of two steps: multi-mode protocol adaptation and heterogeneous network fusion. First, the multi-mode protocol adaptation model is used to implement the heterogeneous network multi-mode protocol differential format conversion, and the heterogeneous network data in the multi-mode protocol is uniformly converted to the same Format; and then for the converted data, through a new heterogeneous data fusion algorithm, to achieve heterogeneous network communication data fusion. Finally, the UMTS + WLAN multi-mode protocol adaptation and heterogeneous network fusion problems are used as examples to implement the fusion effect test. The test results show that the method has minimal delay, availability, and reliability when dealing with heterogeneous network fusion problems. The test results of blocking rate and packet loss rate are better than the comparison method.
- 1
-
Design of a broadband slot antenna fed by microstrip
Abstract:
In order to meet the needs of millimeter wave radar system, a design method of microstrip broadband slot antenna suitable for millimeter wave band is researched. By using the structure of defected ground and "windowing" on the ground plate, good impedance characteristic is obtained at the expense of partial gain, which solves the problem of narrow band of traditional microstrip antenna. An ellipsoidal dielectric lens is designed to improve the gain characteristics of a microstrip slot antenna. Through simulation and measurement, the passband S11 is less than-10db in the 75GHz-90GHz frequency band, and the impedance bandwidth is greater than 30%. The 3dB beam width of the two main planes is 10 ° and 11 ° at center frequency of 80GHz. The characteristics of far field pattern are in good agreement. Dielectric lens increases antenna gain from 3.5db to 19.69db. The antenna has the characteristics of wide bandwidth and high gain, which can be used for long-distance millimeter wave radar detection.
- 1
-
2016,39(11):183-186, DOI:
Abstract:
For the problem that temperature sensors of mine belt transport system can’t be inspected in real time and on site, design a based on Smith estimated compensation control for portable underground conveyer temperature sensor detection device. The working principle of the device is introduced in detail, the hardware design of thermostat, intrinsically safe power supply circuit and the drive system based on the Smith prediction control is expounded and the flow chart of main program software is given in this paper. The experimental result and field operation results show that the device has the characteristics of convenient carrying, accurate measurement, real time and on site detection and so on.
-
Gu Youyi, Jiang Lixing, Sun Zhenxiong, Wang Li, Wang Ancheng
2019,42(10):1-5, DOI:
Abstract:
Outdoor baseline is the special length standard in the field of surveying and mapping, it can be used to verify the addition and multiplication constants of the total station and other photoelectric rangefinders. In order to ensure the authenticity, accuracy and reliability of verification results, conducting outdoor baseline traceability periodically is essential. At present, direct measurement by 24 m invar tape or high precision electro-optical measurement is mainly used to achieve the traceability of outdoor baseline in China, a large number of experimental facts have shown that there are still system errors between the quantity transfer of baselines in China and abroad. With the rapid development of China′s manufacturing industry and the proposal of “made in China 2025”, the traditional traceability technology of outdoor baseline is difficult to meet the increasingly high precision requirements, and it is urgent to achieve the outdoor baseline precision ranging. Combined with the current research situation at home and abroad, optical interferometry by Vaisala interference comparator, direct measurement by 24 m invar tape and high precision electro-optical measurement are summarized，the advantages and disadvantages of the three methods are deeply analyzed. Last but not least, some thoughts and suggestions are put forward for the future outdoor baseline field construction in China.
-
Li Songsong, Ping Dongyue, Zhang Chenchen, Xia Wenze, Guo Zhonghui
2019,42(10):6-11, DOI:
Abstract:
Electromagnetic acoustic transducer（EMAT）sensors are widely concerned because they do not need couplers and can be used in high-temperature environments. However, there are problems such as low energy conversion efficiency, small amplitude of ultrasonic echo signal, and easy to be disturbed by noise, which need to be further studied. According to the working mechanism of the EMAT, through analyzing the characteristics of the echo signal of ultrasonic Lamb determines the index of receiving circuit, design and optimize the impedance matching circuit, preamplifier circuit and low-pass filter circuit, and design the digital bandpass filter for further signal processing. Firstly, the preamplifier circuit is simulated to make it capable of receiving small signals. Then a three-stage MFB low pass filter circuit is adopted to eliminate the spatial coupling noise. The EMAT flaw detection test of aluminum plate was made and built by circuit hardware. The results show that the designed receiver circuit can detect lamb wave well, which provides a foundation for the development of the testing system.
-
Yang Xunyong, Yang Fashun, Hu Rui, Chen Xiao, Ma Kui
2019,42(10):43-47, DOI:
Abstract:
Take the high-voltage high-power chip TO-3 package structure with operating voltage of 70V and output current of 9A as an example, the three-dimensional package model is first established based on the thermal analysis software Flo THERM, and the thermal characteristics of the package model is simulated and analyzed. Secondly, comparative analysis is carried out for the presence/absence of substrates, different substrate materials, and different package materials. Finally, the temperature of the package is studied according to the thickness of the bonding layer, the power and the thickness of the substrate, and a package with optimized heat dissipation is obtained. The simulation results show that The higher the thermal conductivity of the substrate material and the package casing, the better the heat dissipation effect. As the thickness of the bonding layer and the power of the chip increase, the temperature of the chip gradually increases. As the thickness of the substrate increases, the temperature of the chip decreases. The heat dissipation effect is optimal when the substrate material is copper, the package casing is BeO, and the bonding layer is AuSn20.
-
2019,42(10):82-85, DOI:
Abstract:
The near-drilling tool can effectively overcome the shortcomings of the conventional measurement while drilling system, which is very suitable for use in complex formations or thin reservoirs, and has the advantages of convenient field assembly and low operating cost. Near-bit azimuth gamma measurement system is the core of its geological steering control. In this paper, two important modules of near-bit azimuth gamma ray measurement system are introduced in detail: sector measurement module and gamma counting processing module. Field experiments show that the system can quickly indicate the direction of the tool crossing the horizon, meet the requirements of field operation, and has a certain market value.
-
Tao Hongbo, Fang Yong, Xu Guanghong, Bu Dongyao, Jin Yanliang
2016,39(11):126-130, DOI:
Abstract:
In this paper, a remote monitoring system for air quality in vehicle is designed based on Kalman filter. The microprocessor Exynos 4412 is used as the controller and signal processer in this system. The data of PM2.5, PM10, formaldehyde, temperature and humidity are obtained by gas sensors.The mean filteringis used to eliminate pulse noiseof data and the Kalman filtering is used to calculatethe optimal estimation values. Thesedatadrawgraphics are displayed on theAndroid boardand sentto mobile terminal for remote real time monitoring.When the data is more than the normal threshold, the mobile terminal is able to give the acousto optic alarm and control the car air system. The experimental results show that the system can effectively improve the accuracy of pollution monitoring and mobility.
-
2019,42(10):12-15, DOI:
Abstract:
The on-line monitoring device of transmission line in Xinjiang Province cannot work normally in the extremely cold environment, which brings some difficulties to the operation and maintenance of transmission line. In this paper, the implementation scheme of power tapping from OPGW was put forward. Based on EMTP simulation platform, 500 kV ac transmission line model was established, which simulated the induced voltage and current, and the dual insulation mode is proposed. The results prove that the induced voltage and current of ground wire are positively correlated with the spacing and load power, and are basically unaffected by the soil resistivity; when the span is 300 m and the load power is 500 MW, the output power of the ground wire energy-collecting device is 137.8 W, fully meeting the power supply demand of on-line monitoring device in the transmission line; under the condition of long-term extremely cold temperature -45 ℃, by using nano porous silica insulation membrane and infrared radiation heating, it still can ensure ideal temperature conditions,which is not less than -30 ℃; after the insulation measures are adopted for the power supply, the mean rate of no failure in online monitoring device is increased from 85.9 to 99.6%, and the reliability is significantly increased. The research results provide a design idea of stable power supply for on-line monitoring devices in extremely cold regions.
-
2019,42(10):38-42, DOI:
Abstract:
Wireless power transmission technology is the key technology that enables special robots to achieve lightweight sustainable work. The magnetic coupling resonant wireless charging, must consider the impact of metal obstacles on the transmission system. The metal eddy current effect is equivalent to mutual inductance coupling circuit, and the transmission system is modeled by coupling circuit theory. The transmission equation of voltage gain coefficient and the expression of energy loss of metal obstacles to transmission system are derived. With the change of coupling coefficient, the transmission system still has frequency splitting, critical coupling, over-coupling and under-coupling. Given the parameters of the transmission system, the critical coupling coefficient Kc=1.54×10-4. When there are metal obstacles, K′c=1.09×10-2. which lead to the reduction of voltage gain, the shift of resonance frequency, the increase of coupling coefficient and the decrease of coupling performance in wireless transmission system. The change of output voltage in the presence of metal barrier is obtained by simulation.
-
2019,42(10):16-21, DOI:
Abstract:
In order to solve the problem that the surplus torque′s strong interference to the electric load simulator and affects the tracking accuracy, the fuzzy PID control method based on particle swarm optimization is applied to the design of motor controller. Firstly, the mathematical model of the electric loading system is established based on the analysis of the structure and working principle of the loading motor, and feedforward compensation is deduced by the principle of structural invariability; Secondly, because of conventional PID controller cannot deal with the complex nonlinear environment by changing parameters, and the fuzzy PID quantization factor scale factor is difficult to adjust by experience, a compound control strategy based on fuzzy PID and particle swarm optimization algorithm is proposed. Finally, the simulation result shows that the proposed control strategy is superior to the conventional fuzzy PID controller.
-
Zheng Ying, Zheng Xianfeng, Cheng Jingjie
2019,42(10):48-51, DOI:
Abstract:
The engine mount system is an important part of the vehicle, Play the role of supporting engine, blocking vibration and improving ride comfort in the process of driving This paper studies the relationship between the stiffness of the suspension element and the inherent characteristics of the suspension system by modeling and simulation of the automobile engine. In Adams software, a three-dimensional model of the engine suspension system is established, simulation analysis is conducted, and the intrinsic frequency and vibration modal energy decoupling distribution of the suspension system is obtained in the Vibration vibration module. The analysis shows that the vibration isolation effect is poor. With the stiffness of suspended rubber pad as the optimized parameter, a new energy decoupling distribution is obtained, and the decoupling rate in the main vibration direction reaches more than 80%. Compared with the initial data, the decoupling degree is greatly improved, which shows that the optimized data has obvious effect on the vibration isolation of the engine, and verifies the feasibility of the optimized design method.
-
Zhao Hongliang, Guo Youmin, Wang Jianxin, Yang Jun
2024,47(1):130-135, DOI:
Abstract:
In order to solve the problems of low accuracy and slow detection speed of obstacle detection in the complex rail transit background, an improved object detection network model of YOLOv5 was proposed. Firstly, a lightweight Transformer backbone EMO based on attention mechanism was used to replace some modules in the original backbone of YOLOv5, which not only ensured the lightweight, but also improved the accuracy and stability of the model. Secondly, Focal-EIoU is used to replace the CIoU loss function in YOLOv5 to solve the problems of low training efficiency and slow convergence speed caused by CIoU. Finally, the lightweight upsampling operator CARAFE is used to replace the original upsampling layer in the YOLOv5 algorithm, which has a larger receptive field without introducing too many parameters and computational cost, and improves the detection accuracy and detection speed. Experimental results show that compared with the original YOLOv5 network model, the mean average precision of the proposed method is improved by 11.1%, the precision is improved by 13%, the recall is improved by 11.4%, and the detection speed reaches 60.7 frames per second. The proposed method shows good performance in the target detection task, and effectively enhances the detection performance of the target detection model in the context of rail transit.
-
2019,42(10):33-37, DOI:
Abstract:
In order to improve the real-time control ability of biped robot, a real-time obstacle avoidance position control method for biped robot based on reinforcement learning is proposed. Taking the stability of biped walking as the control objective function, the real-time path dynamics model of biped robot is constructed. The acceleration and inertia moment of the robot′s centroid motion are taken as the controlled object. The effective collision sub-model is used to plan the real-time obstacle avoidance path of biped robot, and the collision sub-model and swing sub-model are combined to adjust the error correction parameters of biped robot. The fuzzy reinforcement learning tracking method is used to control the error gain of biped robot, and the real time obstacle avoidance position control of biped robot is realized. The simulation results show that the proposed method can avoid obstacles in real time and improve the adaptive control ability of biped robot.
-
Wu Shaolei, Xiao Jianhong, Feng Yu, Shi Liang, Zhang Liang
2019,42(10):22-27, DOI:
Abstract:
Due to the high level penetration of several types of distributed energy source, storage system needs to be added in modern power system to suppress power flow fluctuation. In order to realize high efficiency bidirectional power conversion under the circumstance of wide input and output voltage range in energy storage system, a bidirectional buck-boost DC/DC converter based on multi-mode control is studied in this paper. When the input voltage exceeds the output voltage above a certain threshold, valley current mode control is employed and the converter operates as buck region. When the output voltage exceeds the input voltage above a certain threshold, peak current mode control is used and the converter operates as boost region. Furthermore, when the intput voltage is similar to the output voltage, phase-shift mode control is adopted to obtain seamless transition and the converter operates in a manner of buck and boost combination. In order to realize high accurary output and fast dynamics, Type II compensator is employed. By the approach of small portion overlaping between Buck region and Boost region, the discontinuity happened at region transition in traditional Buck-Boost converter is eliminated. 97.5% peak efficiency is achieved in the 1 kW hardware prototype and the transition between Buck region and Boost region is smooth.
-
Wang Xuejun, Gu Jinliang, Luo Hong′e, Xia Yan, Li Baoming
2019,42(10):110-114, DOI:
Abstract:
In order to measure and study the contact impedance of the contact interface between the central rail and the electromagnetic launching system, a low impedance measurement system at low frequency is developed. The system measures the vector voltage at both ends of the impedance to be measured and the standard impedance separately by impedance transformation method. The real and imaginary parts of the vector voltage are separated by phase sensitive detection method based on free axis. The magnitude of the impedance to be measured is calculated according to the relationship between the standard impedance voltage and the impedance voltage to be measured. The system uses STM32 controller as signal generator and controller, adopts Kelvin four-wire method to reduce the influence of lead resistance and contact resistance, and uses software compensation method to reduce measurement error. The measurement results show that the measuring system can work normally within 10 kHz and has high accuracy in measuring resistance within 100 Ω.
-
Liu Baohang, Wang Bingsen, Li Ziqi
2019,42(10):28-32, DOI:
Abstract:
Wireless power transmission (WPT) based on the magnetically-coupled resonant is a hot topic in the research and development in modern electrical technology. It is the most likely to be a technology to provide solutions for wireless power supply of electrical equipment, such as household appliances, various consumer electronic products, smart wearable devices and embedded medical devices. The WPT is a flexible access and transmission for real-time power supply. In order to get rid of the shackles of the traditional power cord, the limitation of the space and distance of the power supply mode is solved. Using coupled-mode theory, the two identical helical coils are built with the height of 20 cm, the diameter of 60 cm and the number of turns of 5.25. Both coils are made of hollow copper wire. The expected resonant frequency given is 7.65 MHz, which is about 4.5% off from the measured resonance at 8 MHz. Control the class E power amplifier(PA) gate with an 8 MHz square wave signal, The effects of the nonlinear and linear shut capacitance have been considered in the drain of PA, it is important to predict the performance when an external capacitor is necessary to add for the optimal Class-E mode. Impedance matching is designed to maximum the power transfer from the drain of PA to the transmission coil. The system achieves the maximum transmission distance of 6 meters on the theoretical basis of the transmitting coil of diameter of 60 cm. According to experimental analysis, the system has a great improvement in transmission distance.
-
2019,42(10):120-125, DOI:
Abstract:
The bus-based distributed structure has been applied to the field of drones because of its simple structure, easy expansion, and maintainability. The research group takes unmanned helicopter as the research object, and carries on the technical upgrade on the basis of the original centralized flight control system. A design scheme of distributed flight control system based on CAN bus is proposed. It describes the overall design scheme, hardware design, communication mechanism, software development and implementation of distributed system based on CAN bus, and carries out semi-physical simulation verification. The test results show that the actual bandwidth occupied by CAN bus is 10.5%, and there is no frame loss. The synchronization accuracy of communication reference clock is less than 150 μs, which can fully meet the requirements of flight control system. Through the whole process of flight semi physical simulation, it is proved that the distributed flight control system based on CAN bus can meet the real-time, reliability and other control requirements of unmanned helicopter flight control system, and the design meets the engineering requirements.
-
Zhu Jiangbo, Zhao Zhiheng, Liu Yang, Ma Jiayi, Sun Lei
2019,42(10):52-57, DOI:
Abstract:
A new black and white color selection system based on ZYNQ-7000 series fully-programmable SoC is designed to solve the problem of slow detection speed and low integration of traditional black and white color selection system. Using hardware and software co-design methods, firstly linear CCD image acquisition, grayscale correction, threshold comparison and valve output are implemented on the PL side. Then using the AXI interface to cache the compensated grayscale value, valve output signal, and setup parameters to the DDR3 SDRAM memory, and finally The PS side is ported to an embedded Linux operating system for real-time display and human-computer interaction. The experimental results show that the system can effectively measure the eigenvalue parameters of the materials with screening, and carry out the selection, the operation is stable and reliable, and meets the requirements of industrial applications.
-
Li Zicong, Zeng Yuhang, Xiong Xiaoming
2019,42(10):126-131, DOI:
Abstract:
In recent years, convolutional neural networks have done a great job in many machine vision tasks. However, existing software implementations are not well implemented in portable devices. A convolutional neural network system based on Xilinx all-programmable SoC is designed to accelerate the convolutional operation in parallel, which only need few design resource and implement fast detection system. The system uses multi-stage pipeline technology and input data reuse to improve calculation efficiency. The hardware part completes convolutional network calculation, and the software part finish the image preprocessing and post-image detection preprocessing, thereby improving operation efficiency. The system can implements the convolution operation with different size, mean pooling operation and the non-maximum suppression algorithm, which achieves accurate positioning of multiple faces in the picture. The experimental results show that the average calculation rate of the system is 0.19 Gops/s at the operating frequency of 100 MHz，and the power consumption is only 4.07% of the general purpose CPU.
-
Bi Lige, Tong Xiaolin, Li Hanchao
2017,40(6):1-4, DOI:
Abstract:
When projectile launched by ground operations for weather modification did not burst in the air and land, it would damage to the ground personnel or important facilities. In order to avoid the damage, using remote sensing image, global positioning system and geographic information technology, this paper designed and developed an analysis system for safe firing area of antiaircraft guns and rocket. The system extracts the object information from the high resolution remote sensing image of Spot in the system database and the GPS positioning information of the operation terminal system. Combined with the trajectory parameters of different types of rocket and antiaircraft guns, this article analyzed the safe firing area. The results of firing area analysis are intuitive, reliable, convenient and quick operation, providing a scientific basis for safety of ground operations for weather modification.
-
2019,42(10):58-62, DOI:
Abstract:
In order to improve the working efficiency of the parallel H-bridge active filter, when the power supply voltage is distorted, a more accurate harmonic compensation current is calculated in a shorter time, and an accurate compensation command is provided for the deadbeat control. A control strategy combining adaptive harmonic detection algorithm with carrier phase shift sinusoidal pulse width modulation (CPS-SPWM). Firstly, the reference compensation current is calculated quickly and accurately by the adaptive harmonic detection algorithm. Then, the bridge voltage stability is realized by the outer loop voltage PI control, and the internal loop equalization proportional control is used to realize the same capacitor voltage of the sub-module on the bridge arm. CPS-SPWM provides a more accurate modulated wave signal for active filters. Through simulation experiments, it is verified that the control strategy has higher stability and accuracy than traditional methods.
