Abstract:In order to solve the problem that the response speed of CCD camera is very high when measuring high-speed projectile, but the response delay of camera is difficult to measure accurately, a method of CCD camera response delay detection based on FPGA is proposed.In this method, the trigger signal is divided into two channels: one is to trigger the high-speed camera directly; the other is to trigger the pulse laser light source by delaying the signal through FPGA module. The response delay of the camera is determined by changing the delay time and continuously judging whether the camera has captured the pulse laser.In this paper, the detection performance model of CCD camera is established, and the detection performance of the camera is analyzed. Finally, an experimental platform is built to verify the test method.The results show that the response delay of the camera is 0.5s.The response delay precision of the test is 0.1s, the detection speed is fast, the work efficiency is high, the operation is simple, and the result is accurate and stable.

Abstract:The system error of the observation data is the main factor that affects the accuracy of satellite orbit determination. The delay of the satellite transponder is difficult to obtain directly from the orbit measurement, so it has become one of the main sources of the system error of the FY-4A stationary meteorological satellite observation data. In response to this problem, this article first introduces and analyzes the original FY-4A geostationary meteorological satellite transponder time delay calibration scheme, which was found that the solution was unable to obtain satellite transponder delay due to too many parameters to be estimated. Subsequently, a new on-orbit calibration method was proposed that the difference between the time delay of the FY-4A meteorological satellite transponder and the ground correction value was about 2m by using the dynamic precision orbit determination analysis. The results show that the method can effectively retrieve the on-orbit variation of the FY-4A weather satellite transponder.

Abstract:According to the mechanical and electrical structure of intercooler control system, this paper expounds the working principle of intercooler heat exchange and the necessity of Fieldbus design. Combined with the hardware characteristics and drive characteristics of the intercooling control system, the controller module including basic functions, auxiliary functions and additional functions is completed according to its application situation. According to the design scheme, with the industrial PLC as the center, and with the help of environmental control system and PROFIBUS DP industrial field bus, the control of the central measurement and control system can be extended to every corner of the engine laboratory. The hardware architecture of intercooler controller based on DSP and PROFIBUS DP communication function is designed. Results the controller can not only control the air temperature after turbocharging, but also provide feasibility for industrial control interconnection and remote control. At the same time, it provides solutions for the design of other intelligent controllers in the engine laboratory environment control system.

Abstract:Objective to verify the influence of graphite based flexible grounding body on Corrosion Behavior of metal down lead in graphite based flexible grounding device. Methods three kinds of accelerated corrosion tests were carried out to simulate soil coating, strong electrolyte soil current and other types of accelerated corrosion tests after connecting galvanized sheet, copper metal and 304 stainless steel with graphite material. The influence of different accelerated corrosion test types on Corrosion Behavior of galvanized sheet, copper and stainless steel was studied by weight loss method, XRD and polarization curve. Results the order of corrosion resistance was 304 stainless steel > copper metal > galvanized steel. The increase of sulfate ion concentration would accelerate the corrosion of graphite grounding materials to metal grounding materials. Conclusion 304 stainless steel or 304 stainless steel and graphite composite material is preferred for down lead of graphite based flexible grounding device, the corrosion products on the surface of galvanized steel have obvious layered structure, the main corrosion products of inner layer are Zn5(OH)8Cl2H2O, Fe4(OH)10SO4, and The outer corrosion products have high oxygen content and loose texture, mainly SiO4 and Zn.

Abstract:The detection of mechanical products based on machine vision technology is a development trend in the measurement field. By consulting domestic and foreign machine vision dimensional measurement technology related research literature, review the current research progress on machine vision-based geometric measurement technology. After analysis, it is concluded that the current detection technology lacks the research and development of general geometric measurement systems, the image processing system has obvious time lag, and the accuracy of geometric measurement based on machine vision is not very high. The development strategy of geometric measurement technology for machine vision mechanical products is proposed: follow-up research will increase the development of parts image recognition and classification modules, optimize algorithms, and achieve a higher level of automation and intelligent machine vision measurement; effectively combine other sensors The advantages of complementary performance, through the fusion of multi-sensor to establish a more stable transfer model to eliminate uncertainty; use the results of active vision and other development strategies. Provide a theoretical reference for related research on machine vision mechanical product inspection technology.

Abstract:In view of the situation of data error and number loss in high-speed long-distance transmission in bad test environment, this design adopts a BCH code which can self-correct error and a 8B/10B code which can realize the DC balance in the transmission process. In this scheme, the long-distance data transmission is realized by using the high-speed serial Hotlink transmission and receiving chip CY7B923/933, and the reliability of the transmission process is improved by designing the hardware circuit of data receiving and sending and using the software logic design with error correction technology. After the high temperature test with external signal excitation and interference, it can realize the correct transmission of Hotlink data on the 100M coaxial cable at the rate of 400Mbit/s without error code.

Abstract:Aiming at the problem of battery inconsistency in photovoltaic energy storage power station, a hierarchical active equalization system based on flyback transformer and inductance is designed. The system adopts hierarchical equalization strategy. The first layer is the internal group equalization of battery packs, and the energy transfer between adjacent batteries is realized by the inductance; the second layer is the equalization of different battery packs, which is realized by the equalization circuit based on flyback transformer. Taking the state of charge (SOC) of the battery as the equilibrium index, a simulation model of six series lithium batteries was built in Matlab / Simulink. The experimental results show that after a period of internal group equalization and different groups equalization, the SOC of each cell in the series lithium batteries reaches 100% without causing overcharge. The equalization time is short, and the effects is perfect.

Abstract:The traditional binocular distance measurement is to calculate the coordinate information of the object in the three-dimensional space through the parallax of the object to be measured in the binocular camera, which needs to be combined with the ideal binocular distance measurement model. However, the cameras used in actual engineering applications are often monocular cameras, which cannot meet the requirements of binocular distance measurement. Aiming at the above problems, a pseudo-binocular dynamic ranging method based on monocular video is proposed, and the target object is ranging from the video taken by a camera moving on a predetermined track. Calibrate the monocular camera used to obtain the camera's focal length, principal point coordinates and other internal parameters. Intercept two frames of images at different positions in the video taken by the camera, calculate the pose relationship of the camera at different positions through the track parameters, and use the normalized template matching algorithm to obtain the best pixel matching point, combined with pseudo The binocular ranging model calculates the distance of the object to be measured, and compares it with traditional binocular ranging and monocular ranging. The experimental results show that when the camera is within 5m of the object to be measured, the error can be maintained within 4% when measuring objects within the camera's field of view.

Abstract:V-type electro-thermal actuator is widely used in MEMS system because of its simple structure,large execution force and linear displacement. The thermoelectric effect is used to discuss the V-beam electro-thermal actuator, the theoretical analysis values of temperature distribution, maximum displacement and step response time are obtained, and the simulation results are verified by ANSYS. The result shows that the simulation results are consistent with the theoretical results. And the influence of the geometric parameters on the performance of the device is researched.

Abstract:In view of the uncertainty and nonlinearity existing in the wind pendulum device, combining the traditional PID control theory with fuzzy control thought, a multi-mode controller based on fuzzy switching to solve the stability problem is proposed since the traditional PID method is difficult to control pendulum device accurately and effectively in this paper. The multi-mode controller is obtained to deal with the angle error and the error change rate of the feedback input of the wind pendulum device.The control intensity of each controller is adjusted automatically by using the fuzzy switch so as to improve the adaptive ability of the wind pendulum device. Finally, by using the MATLAB simulation tool, the multi-mode controller with the conventional PID controller and the fuzzy controller are simulated and compared respectively. The effectiveness and superiority of the proposed method are illustrated which further proves that the multi-mode controller has the advantages of high anti-interference and high precision in this paper.

Abstract:The indoor environment has the characteristics of complexity and variability. In order to achieve accurate indoor positioning, it is necessary to model the indoor environment to estimate the target's positioning. Aiming at the problem of low positioning accuracy of the existing indoor positioning algorithms, this paper adopts the lognormal distribution model according to the characteristics of the indoor environment, and uses Taylor formula to improve the traditional least squares algorithm to achieve more accurate indoor target positioning. In this algorithm, the average Kalman filter (Kalman Filter) is first used to model the indoor environment to eliminate the interference of random noise. Then the estimated coordinates obtained by the least squares algorithm are expanded with Taylor's formula to construct a loop iteration to gradually approach the real target position. The experimental results show that the improved algorithm better improves the positioning accuracy, obtains a more accurate estimated coordinate position, and ensures the stability of the positioning deviation.

Abstract:In the application of rotating machinery, rolling bearing is the key precision equipment to reduce the friction loss between shaft and shaft seat. In order to effectively monitor the damage of rolling bearing caused by wear, corrosion and overload, the characterization of rolling bearing vibration signal for rolling bearing fault is designed and verified. This experimental design method is to start from the vibration signal of the rolling bearing collected during the mechanical rotation process, and to extract and analyze the fault characteristics of the rolling bearing in Matlab. Through empirical mode decomposition to obtain the inherent modal function of the vibration signal, the envelope spectrum of each component is obtained after the Hilbert-Huang transformation, and the fault characteristic value calculated by the theory is compared and matched to achieve the rolling bearing fault diagnosis and analysis. The experimental results show that the theoretical calculation of the outer ring fault frequency of rolling bearing is about 49 Hz, and the experimental measurement of the fault frequency is 50 Hz, which is consistent with the outer ring fault frequency characteristics. Therefore, this method can accurately characterize the fault frequency of rolling bearing, and can realize the effective monitoring of rolling bearing fault.

Abstract:In the mobile wireless sensor network(MWSN) of underguound coal mine, as the mobile node of the network, the determination of the spatial position of the mobile robot plays an important role in the normal operation of the network. Aiming at the problem that the accuracy and complexity of the three-dimensional positioning algorithm in wireless sensor networks are difficult to balance, this paper extends a probabilistic centroid localization algorithm based on received signal strength indication (RSSI) ranging in a two-dimensional plane to a long and narrow space in coal mines for three-dimensional positioning application of mobile robot nodes. The algorithm adopted the overlapping area,which should be locating spherical shell of anchor node under a certain outstanding degree, replacing the whole distribution area of the robot node estimated position.Then the probability-density-centroid of overlapping area was figured out as the estimated value of the robot node. The position algorithm have been verified by a simulation experiment. The result manifest that the Positioning accuracy can reach 0.13 in long and narrow space.

Abstract:In order to improve the modeling accuracy of automobile brake disc, three kinds of elements were used to establish the finite element model of brake disc. The first six order natural frequencies of the brake disc were obtained by calculation and test. It is found that the errors of the first six order natural frequencies between the finite element model established by using tetrahedral, 1-order and 2-order hexahedron elements are less than 9%, 2% and 7% respectively. Then, the mode shapes of the first order hexahedron finite element model were compared, and the constrained modal analysis was carried out. The results show that: the first six modes shapes of brake disc obtained by calculation and test are basically consistent, and the finite element model is accurate and reliable; the modeling accuracy of three different elements from high to low are 1-order hexahedron, 2-order hexahedron and tetrahedron respectively; three pairs of complex modes exist in the brake disc restraint boundary condition and attention should be paid to the design of brake system. The research method has certain reference significance to improve the accuracy of brake disc finite element.

Abstract:In order to provide campus service and off-campus service simultaneously, and help teachers and students to understand campus layout and resource distribution macroscopically , the paper designs an universities three-dimensional positioning AR navigation system. It uses 3DsMax, Vuforia SDK, Intent, ListView and other tools to make 3D model, identify target location ‘s flat image, switch mode and other functions. The tests show that system can meet function needs, it can enhance the rendering of scene regional goals, and achieves virtual-real fusion effect. At the same time, the system’s position error are all less than 0.6m, minimum error is 0.2m, its time is 13s, the performance can also meet students and teachers’ basic needs, the user experience is good.

Abstract:Text emotion analysis based on deep learning is an important direction of natural language processing research at present. Based on CNN and Bi-LSTM this paper proposes a emotion analysis algorithm with better performance than the previous two algorithms.The improved emotion analysis algorithm combines the traditional deep learning structure and combines the Bi-LSTM,CNN and Attention mechanism. The part combining the Bi-LSTM and Attention mechanism is mainly used to extract global features and focus on target words.The part of CNN and Attention mechanism is mainly used to extract local important features.Finally, the characteristics of the two parts are integrated and then classified. The results of the experiment showed that when analyzing the emotions of online comments , The F1 of CNN model was 0.7939, the F1 of BI-LSTM was 0.7959, the F1 of BI-LSTM-Attention was 0.7998,and the F1 of BI-LSTMA-CNNA was 0.8028.Therefore, the performance of the improved model is better than the other three models.

Abstract:In order to solve the problem of automatic generation control of traditional hybrid unified power system, a cascade PD-fuzzy PID controller was proposed.The scaling parameters of the cascade PD-fuzzy PID controller were optimized by using gray Wolf optimization and hybrid optimization based on teaching and learning optimization algorithm (GWO-TLBO).In the optimization process, the burst load interference of 0.01pu was added into region 1, and the absolute error of integral time was taken as the evaluation function.In the analysis of the dynamic performance of the system, the AC link and AC-DC link are considered.The robustness and sensitivity of the cascade PD-fuzzy PID controller are further verified in the case of random load variation and nominal parameter variation. The dynamic characteristics of the system are analyzed by using the time response index. By comparing the optimal parameters obtained by the proposed method with the existing results, it is concluded that the settling time of △f1, △f2and △Ptieusing the cascade PD-fuzzy PID controller is increased by 93.36%, 84.46% and 91.13% respectively compared with PID, and by 82.59%, 56.15% and 65.06% respectively compared with the fuzzy PID.The simulation results show that.The cascade PD-fuzzy PID controller is superior to other controllers, and solves the problem of automatic generation control of traditional hybrid power system, which can provide reference for automatic generation control of power system.

Abstract:The setting value of the coal injection rate in the blast furnace ironmaking process is usually derived from the experience of the furnace manager, which has certain blindness and ambiguity. In order to increase the rationality of the coal injection rate setting, this paper proposes an improved particle swarm Optimize the prediction model of blast furnace coal injection rate based on extreme learning machine. Based on the actual operating data of a blast furnace, this paper uses chaotic inertia weights and adaptive learning factors to improve the convergence of the particle swarm optimization (PSO) algorithm, and introduces the cross-mutation operation of genetic algorithms to improve the global optimality of the algorithm, and then uses the improvement The particle swarm algorithm optimized extreme learning machine (ELM) builds an extreme learning machine prediction model (IPSO-ELM) based on the improved particle swarm algorithm. Finally, based on the operating data of a certain blast furnace, the IPSO-ELM prediction model proposed in this paper is compared with the traditional particle swarm optimization extreme learning machine prediction model (PSO-ELM) and the extreme learning machine prediction model. The results show that the IPSO-ELM prediction model has higher prediction accuracy, can achieve accurate prediction of the change of the blast furnace coal injection rate, and has high industrial application value.

Abstract:In view of the nonlinearity and time variability of industrial control systems, as well as the poor transient response in traditional adaptive control, this paper presents a neural network multi-model switching adaptive control method basing on particle swarm optimization. Firstly, the PSO algorithm was used to adjust the neural network weights to achieve the optimal value. Then an adaptive control strategy was designed basing on the BPNN and multiple models. The optimal controller can be selected to control the system through the constructed rational switching rules. The good approximation ability of neural network can improve the performance of adaptive control. The performance through PSO optimization are studied through simulation methods using Matlab, which verifies that the proposed method can significantly improve the overall performance of the system：fast convergence, high precision, good network generalization and approximation ability, and can precisely track the output of the control system.

Abstract:In the Internet of Things(IoTs), the information is required to be fresh becomes, and transmitting of real-time information becomes more and more important. The Age of Information (AoI) is a metric proposed to evaluate the freshness of specific pieces of information, which has certain advantages in improving the timeliness of information in IoTs. The throughput and latency have been studied extensively in the IoTs, but research on the AoI of IoTs is quite novel. Aiming at improving the freshness of the information, this paper proposes a polling mechanism to reduce the access delay of packets and to improve the AoI of packets, such that the receiver can receive the latest messages. The simulation results show that this method has significant advantages in congested IEEE 802.11ah wireless LAN, such that it can reduce AoI of messages and increase the network throughput as well.

Abstract:Aiming at the problem of poor visibility of single system satellite signal due to the shielding of surrounding buildings in complex urban environment or indoor environment, a joint positioning system was designed to locate single point, and Kalman filter algorithm and federal Kalman filter algorithm were used to process the positioning results respectively. In order to verify this conclusion, we used the GPS/BDS dual-mode positioning receiving module in MC20 to collect positioning data, and the data collected by Jisubo UG905 was used as the reference data of the anchor point. The results show that compared with the reference data, the error of the federated Kalman filter is reduced by 9.54% in the linear distance and 53.43% in the elevation. The results show that the positioning data processed by federated Kalman filter has good reliability and high precision, which can improve the accuracy and accuracy of positioning more effectively.

Abstract:Vehicle to Everything (V2X) communication is an effective solution to improve traffic safety and mobility. In order to solve the problems of deep learning that requires a large amount of training data and generalization in power allocation, this paper proposes a power distribution framework that based on Graph Convolutional Network (GCN) under the three criteria of maximizing the total user rate, maximizing the total user energy efficiency. The proposed framework first converts the wireless interference channel into a graph data structure, which proves the disorder of the interference channel. Secondly, according to the characteristics of different power distribution, the GCN network structure is constructed, and the corresponding loss function is proposed. Compared with the Multilayer Perceptron (MLP) network trained based on the weighted minimum mean square error (WMMSE) algorithm， the simulation data shows that the proposed scheme is better than the comparison algorithm in terms of small sample training, scalability, and generalizability.

Abstract:With the development of technologies such as machine vision, depth cameras are becoming more and more widely used in 3D modeling. For the phenotypic surface reconstruction of plants, this paper designed a method to obtain the point cloud data of the plant phenotype by Kinect, and collected images at a certain angle interval and stitched into a complete point cloud image by rotating the point cloud coordinates.Then used straight-through filtering and statistical filtering to complete the filtering of the plant point cloud image.Then used the greedy projection triangulation method to reconstruct the surface of the plant point cloud. Finally, the 3D reproduction of the obtained surface model was implement with the help of MeshLab software as well as the measurement of blade length parameters. Experimental results show that there is no significant difference between the phenotypic parameters of the reconstructed plant surface model and the measured values, and the relative error is kept within 5%, this method can meet the needs of 3D reconstruction of plant phenotype.

Abstract:Water body extraction based on SAR images is widely used in flood monitoring and other fields. The water body extraction method based on threshold segmentation is easy to classify mountain shadows as water bodies for wrong extraction. Traditional machine learning classification methods require manual extraction of effective features, which is inefficient and time-consuming. This paper proposes a SAR image water extraction method based on convolutional neural network. First, the SAR image is divided into blocks, and the SAR image features are automatically learned through multi-layer convolution and pooling operations based on image blocks. Finally, the Sigmoid classifier is used to classify the pixels into water and non-water to realize the extraction of water body. Experiments based on SAR data obtained by Sentinel-1A verify the effectiveness of this method. The recall rate and accuracy rate of water extraction can reach 99%, and the performance is better than the OTSU threshold method and the SVM method based on texture features. This method overcomes the influence of mountain shadows on water body extraction, and its ability to automatically learn features can achieve efficient water body extraction.

Abstract:In view of the practical problems of small proportion and close interval and difficult to identify accurately of ground wire area in the images obtained by handheld devices when the temporary ground wire is attached to the transmission line, this paper proposes an improved Faster R-CNN method to realize ground wire target recognition. the low- and high-level feature maps of the convolutional network are fed into the RPN on the basis of the original Faster R-CNN method to achieve multi-scale target detection, and the non-maximum suppression is improved. The improved model is transplanted to the handheld data acquisition device. Through simulation and field test, the detection accuracy of grounding wire is 94.8%, which is 7.5% higher than the original method. It shows that the proposed method can effectively improve the overall performance of target recognition.

Abstract:Strip steel surface defect detection based on machine vision is an important quality inspection method in the strip rolling process.In order to improve the efficiency and accuracy of strip surface defect detection, this paper proposes a new strip steel surface defect image edge detection algorithm.The algorithm first uses bilateral filtering to remove image noise to achieve the purpose of edge preservation and denoising, then uses an improved four-direction Sobel operator to detect the edges of defective images, and uses adaptive dynamic thresholds to select the best threshold for binarization.The valued image is processed by edge thinning based on Hilditch algorithm to obtain the final detection image.The algorithm is simulated on the Matlab platform, and the experimental results obtained are compared with the traditional Sobel operator. Experimental results show that the average segmentation accuracy of the algorithm in this paper reaches 93.5%.Compared with the traditional Sobel operator edge detection method, the algorithm in this paper can obtain better edge detection results.

Abstract:The binary hash code generated by the traditional deep hash image retrieval method has information redundancy and cannot reflect the local semantic information of the image well. This paper proposes a deep hash image retrieval method that combines a convolutional neural network with an attention model. It uses the VGG16 network as the image feature extractor, and then adds an attention module after the convolutional layer of the model to refine the feature map, and finally output the binary hash code as the feature of the image in the fully connected layer of the model, thereby improving the accuracy of the image retrieval task. Experiments on the CIFAR-10 and NUS-WIDE datasets show that after the attention mechanism is added, the model uses different digit binary hash codes in the two datasets to achieve the highest retrieval accuracy of 85.3% and 78.1%, higher than the case where the attention mechanism is not used, verifying the effectiveness of attention model.

Abstract:In order to recover the projectile borne recorder, it is necessary to accurately find the position of the projectile impact point, and ensure that it can still accurately find the location of the impact point when the impact point is in the shielding environment and poor wireless transmission environment. A multi positioning beacon machine is designed. Firstly, the target position is reduced by using the final received GPS positioning signal, and then the projectile impact point is found by detecting the target signal strength. This design is composed of GPS module of transmitter, decoding module controlled by FPGA, Lora remote wireless module, data processing and display module of receiver, directional antenna, etc. The experiment is a fixed-point test experiment, which is conducted in three different locations of the school. The test results are as follows: the positioning parameters of GPS signal are: 112.44571 e, 38.01395 n. the signal strength of the strongest direction at the three observation points are - 49dbm, - 58.5dbm and - 65dbm respectively. Through the final received positioning information and the signal strength information received in the later stage, the impact position of the projectile can be found effectively, which proves the feasibility of the search device and improves the effective search means for the recovery of the missile borne recorder.

Abstract:The current resistance measurement devices use mechanical rotary shifting.It does not support automatic shift measurement and resistance screening functions.The paper develops a capacitive touch automatic resistance measurement device. The device is based on STC12C5A60S2 single-chip microcomputer as the main control platform. It uses GM3400 NMOS field effect tube and standard precision resistance to form a gear switching circuit. CR302A capacitive touch control circuit realizes the setting of system working mode and measurement parameters.LCD 12864 screen displays resistance measurement and resistance screening result. In order to improve the accuracy of resistance measurement, an ADC software compensation algorithm is proposed. The test results show that the device realizes the resistance automatic shift measurement and resistance screening function in the range of 0～10MΩ. The error rate is less than 0.41%.The resistance screening function is stable, and the accuracy is high.

Abstract:Aiming at the problem of classroom ambient air quality, a fuzzy AQI monitoring management system for classrooms based on the IoT technology is designed. A monitoring platform integrating multiple air quality sensors and a fresh air conditioning system is constructed based on STM32, and the air quality data transmission is completed through TCP/IP、MQTT and HTTP protocols; by selecting five indicators of CO2, VOC, formaldehyde, PM2.5 and PM10 in classroom air quality, a Fuzzy Air Quality Index (FAQI) evaluation method is designed based on Fuzzy inference system; on this basis, Java Web/database technology and Vue.js framework are used to design background management system and APP, respectively, which realizes the real-time display of classroom air quality and stable control of the fresh air system. Practical test results show that the system runs stably, can effectively monitor and control the air quality in classrooms in real time, thus has certain promotion value.

Abstract:For the requirements of low cost, high reliability and chip localization in flight control system, a design of RT terminal based on DSP EMIF + LHB155304 is proposed. Using DSP chip as the main controller，the EMIF interface of DSP is used to connect with domestic 4Mbps 1553B bus protocol chip LHB155304，simplify the traditional "DSP + FPGA + protocol chip architecture". To solve the problem of asynchronous data reading between the front-end data sending system and the back-end control system, LHB155304 protocol chip is configured as the RT double buffer mechanism to avoid conflicts and ensure the correctness of data transmission. Finally， the online debugging tool of CCS software is used to observe the receiving and receiving data.It has been proved that the receiving and receiving data are consistent，and the design is stable and reliable，It provides practical experience for the localization of 1553B bus。

Abstract:In order to meet the current demand for online real-time detection of dangerous goods in public places, a handheld raman spectrometer data acquisition system is designed. The system consists of a laser module, a micro spectrometer module, a power supply module and an ARM main control module.After many tests and verification experiments, the results show that the prototype is 18.7cm long, 9.2cm wide, 4.4cm high, weighs about 0.42kg, and has an optical resolution of up to 1.5nm. The test samples—absolute ethanol, methanol, and ethyl acetate are tested and their raman response curves are analyzed. It is concluded that the instrument can make the output raman spectrum characteristic peaks match 98.7% within 6s.The instrument is small in size, light in weight, and high in resolution. It can quickly and accurately detect the properties of the object to be tested, which has extremely high application value and broad market prospects.

Abstract:In view of the shortcomings of the existing underground power cable positioning system, combined with the requirements of the market and the detection site, this paper introduces the principle and implementation method of the coil arrangement of the underground cable positioning system. Based on the principle of electromagnetic induction, a signal receiver with six induction coils is designed. In view of the unknown working state of the field power cable to be tested, the power frequency magnetic field signal can be directly detected without affecting the normal operation of the power cable, for the power cable without operation, the magnetic field signal generated by the current injected by the transmitter at a specific frequency is detected, and the induced electromotive force of each coil is compared and calculated to determine the distribution direction of the cable and calculate the buried depth and current of the cable. Finally, the path direction of the underground cable is determined, and the compass function can accurately determine the actual direction of the cable, avoid the wrong judgment of the cross cable, and realize the detection of the buried depth of the cable, the relative error of the detection depth of the underground cable is only 3.469%.