地铁车辆轴箱轴承故障智能检测系统
周鸣语1金健1石鹏鹏1李冬方2张军2
Intelligent Detection System of Metro Vehicle Axle Box Bearing Fault
ZHOU MingyuJIN JianSHI PengpengLI DongfangZHANG Jun
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作者信息:1.1.南京地铁建设有限责任公司，210017，南京；
2.2.哈尔滨国铁科技集团股份有限公司，150001，哈尔滨
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Affiliation:Nanjing Metro Construction Co., Ltd., 210017, Nanjing, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2023.01.046
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中图分类号/CLCN:U270.331.+2;U279.3+23
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栏目/Col:应用技术
摘要:
针对地铁车辆轴箱轴承故障诊断过程中隧道内强反射噪声干扰的问题，提出了一种基于小波包分解与大数据神经网络算法的故障智能检测系统。通过轨边非接触式声学传感器阵列，实现车辆走行部轴箱轴承声音信号采集；结合峭度计算方法，利用小波包分解进行特征提取；基于大数据神经网络算法进行故障分析识别，并完成智能诊断。实测验证了该系统对地铁车辆轴箱轴承故障检测的可靠性。
Abstracts:
Aiming at the problem of strong tunnel reflection noise interference in the process of metro vehicle axle box bearing fault diagnosis, a fault intelligent detection system based on wavelet packet decomposition and big data neural network algorithm is proposed. Through wayside non-contact acoustic sensor array, the sound signal acquisition of axle box bearing in vehicle running part is realized. Wavelet packet decomposition combined with kurtosis calculation method is used for feature extraction. Fault analysis and identification is carried out based on big data neural network algorithm, and intelligent diagnosis is completed. The reliability of the promoted system for metro vehicle axle box bearing fault detection is verified by field measurement.
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