基于振动加速度与声音信号融合的轨道交通列车轴箱轴承故障诊断方法
郑则君宋冬利贾晨马超
Fault Diagnosis Method for Rail Transit Train Axle Box Bearing Based on the Fusion of Vibration Acceleration and Acoustic Signal
ZHENG ZejunSONG DongliJIA ChenMA Chao
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作者信息:西南交通大学轨道交通运载系统全国重点实验室，610031，成都
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Affiliation:State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, 610031, Chengdu, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2024.09.007
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中图分类号/CLCN:U279.3
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栏目/Col:学术专论
摘要:
［目的］轴箱轴承是轨道交通列车转向架的关键零部件，其健康状态直接影响列车的运行安全。需建立更为科学、高效的轴箱轴承故障诊断方法，以有效提取强干扰噪声下的轴承故障特征信息。［方法］以振动加速度及声音信号(以下简称“振声信号”)为研究目标，分析了轴箱轴承振声信号的故障特征，提出了一种最优带通卷积滤波的信号降噪方法。该方法将原始信号在频域内划分为多个分段，确定不同分段的带通滤波参数，构建了多通道带通卷积滤波器组。采用时域指标分段峭度来选择最优滤波信号，并对最优滤波信号进行频率加权能量算子解调，以识别轴承的故障部位。［结果及结论］所提故障诊断方法可以在强干扰噪声下实现对振动加速度信号、声音信号故障特征的提取，仿真结果及现场试验结果均验证了该诊断方法的有效性。振动加速度、声音信号的故障诊断结论可相互补充验证，进一步提高轴箱轴承故障诊断的准确率。
Abstracts:
［Objective］ Axle box bearing is a key component of rail transit train bogie, and its health state directly affects the train operation safety. Therefore, it is necessary to establish a more scientific and efficient fault diagnosis method for axle box bearing to effectively extract bearing fault characteristic information under strong noise interference. ［Method］ With the vibration acceleration and acoustic signal (abbreviated as vibration-acoustic signal) as the research object, the fault characteristics of the axle box bearing are analyzed, and an optimal signal noise reduction method with bandpass convolution filtering is proposed. In this method, the original signal is divided into several frequency bands in the frequency domain, different bandpass filtering parameters of each frequency band are determined and a multi-channel bandpass convolution filter bank is constructed. The optimal filtered signal is selected by using time-domain index segmental kurtosis, and demodulated by weighted frequency energy operator to identify the bearing fault spot. ［Result & Conclusion］ With the proposed method, the fault characteristics of the vibration-acoustic signal can be extracted under strong interference noise. Both the simulation and on-site test results verify the validity of the method. The fault diagnosis conclusions of the vibration-acoustic signal can be mutually verified, further improving the accuracy of the axle box bearing fault diagnosis.
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