基于STM32与FPGA自适应谱线增强轴承故障检测系统
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北京建筑大学机电与车辆工程学院 北京 100044

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TN98

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国家自然科学基金(52275079)、广西科技重大专项(桂科AA23062031)、北京市西城区优秀人才培养项目(06268321001)、青年北京学者项目(21147523014)、北京建筑大学研究生创新项目(PG2024143)资助


Adaptive spectral line enhanced bearing fault detection system based on STM32 and FPGA
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School of MechanicalElectronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture,Beijing 100044, China

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    摘要:

    滚动轴承在运行过程中出现故障可能会造成严重的后果,对轴承进行在线检测具有重要意义。针对滚动轴承在线检测难题,设计一套基于STM32与FPGA的便携式轴承故障在线检测系统。在硬件方面,采用FPGA芯片作为数据处理单元,实现轴承振动信号A/D转换与在线采集,并对采集信号进行降噪、包络谱分析以及故障频率提取,利用LCD屏实时显示轴承振动信号时域波形与故障频谱。通过STM32单片机设计系统UI控制界面,对采样率、波形显示进行控制并显示诊断结果,实现人机友好交互。在算法方面,利用FPGA实现自适应谱线增强技术对采集信号进行降噪,通过包络谱分析获得故障频谱并提取故障特征频率。最后利用自建机械综合故障模拟试验台对该系统进行测试,实验结果表明系统可以有效提取轴承故障频率,对比软件检测方案速度提升约30倍,满足在线检测需求。

    Abstract:

    The failure of rolling bearing in the running process may cause serious consequences, so it is of great significance to carry out on-line detection of bearings. A portable bearing fault online detection system based on STM32 and FPGA is designed to solve the problem of on-line detection of rolling bearings. In terms of hardware, the FPGA chip is used as the data processing unit to realize the A/D conversion and on-line acquisition of bearing vibration signal, and the signal noise reduction, envelope spectrum analysis and fault frequency extraction are carried out. The bearing vibration signal time domain waveform and fault spectrum are displayed in real time by LCD screen. The STM32 single chip microcomputer is used to design the system UI control interface, control the sampling rate, waveform display and display the diagnosis result, and realize human-computer friendly interaction. In the aspect of algorithms, adaptive line enhancement technology is implemented by FPGA to reduce the noise of the collected signals, and the fault spectrum is obtained by envelope spectrum analysis and the fault characteristic frequency is extracted. Finally, the system is tested by the self-built mechanical integrated fault simulation test bench. The experimental results show that the system can effectively extract the bearing fault frequency, and the speed is improved by about 30 times compared with the software detection scheme, which can meet the requirements of online detection.

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祝克辉,王衍学,戴伟杰.基于STM32与FPGA自适应谱线增强轴承故障检测系统[J].电子测量技术,2024,47(15):161-168

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  • 在线发布日期: 2024-11-28
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