基于空-频域联合滤波的列车轴承轨旁声学诊断

doi:10.16180/j.cnki.issn1007-7820.2024.01.008

电子科技 ›› 2024, Vol. 37 ›› Issue (1): 55-60.doi: 10.16180/j.cnki.issn1007-7820.2024.01.008

基于空-频域联合滤波的列车轴承轨旁声学诊断

张彦喆¹,胡定玉^1,²,师蔚^1,²,廖爱华^1,²

1.上海工程技术大学城市轨道交通学院,上海 201620
2.上海市轨道交通振动与噪声控制技术工程研究中心,上海 201620

收稿日期:2022-09-12 出版日期:2024-01-15 发布日期:2024-01-11
作者简介:张彦喆(1996-),男,硕士研究生。研究方向:声学故障诊断。|胡定玉(1987-),男,博士,副教授。研究方向:传声器阵列信号处理、声学检测与诊断等。
基金资助:
上海市地方院校能力建设项目(20030501000)

Train Bearings Diagnosis Method for Wayside Acoustic Signal Based on Spatial-Frequency Joint Filtering

ZHANG Yanzhe¹,HU Dingyu^1,²,SHI Wei^1,²,LIAO Aihua^1,²

1. School of Urban Railway Transportation,Shanghai University of Engineering Science,Shanghai 201620,China
2. Shanghai Engineering Research Center of Railway Noise and Vibration Control,Shanghai 201620,China

Received:2022-09-12 Online:2024-01-15 Published:2024-01-11
Supported by:
Shanghai Local College Capacity Building Project(20030501000)

摘要/Abstract

摘要：

现有的列车轴承轨旁声学诊断方法多集中在多普勒效应去除、空间滤波器优化等方面,忽视了轨旁环境中存在的大量冲击性噪声及循环平稳性噪声的影响。针对此问题,文中提出了一种波束形成和目标频带选择结合的列车轴箱轴承轨旁声学诊断方法。该方法采用传声器阵列采集列车轴承阵列声信号,通过时域插值重采样方法校正信号畸变,使用波束形成空间域滤波器提取目标轴承方向信号,利用ICS2gram选取最优解调频带并提取带通信号,对带通信号进行包络分析实现轴承诊断。实验结果表明,该方法能够在轨旁声场环境下有效避免冲击性噪声和循环平稳性噪声带来的影响,准确提取目标轴承信号并诊断出轴承故障,相较于现有方法表现出了更好的效果。

关键词: 轴承故障诊断, 声学诊断, 最优频带选择, 波束形成, 轨旁诊断, 循环平稳, 包络分析, 多普勒效应

Abstract:

Existing train bearing trackside acoustic diagnosis methods mostly focus on doppler effect removal and spatial filter optimization, while ignoring the impact noise and cyclostationary noise in the trackside environment. To address this problem, a trackside acoustic diagnosis method combining beamforming and target band selection for train axlebox is proposed in this study. The proposed method acquires train bearing array acoustic signals by microphone array, corrects the signal distortion by time domain interpolation resampling method, extracts the target bearing direction signal using beamforming spatial domain filter, selects the optimal demodulation band and extracts the band-pass signal using ICS2gram, and the envelope analysis of the band-pass signal is carried out to realize bearing diagnosis. The experimental results show that the proposed method can effectively avoid the influence of impact noise and cyclostationary noise in the trackside sound field environment, accurately extract the target bearing signals and diagnose the bearing faults, showing better effect when compared with the existing methods.

Key words: bearing fault diagnosis, acoustic diagnosis, optimal frequency band selection, beam forming, track side diagnosis, cyclostationary, envelope analysis, Doppler effect

中图分类号:

TP206

张彦喆,胡定玉,师蔚,廖爱华. 基于空-频域联合滤波的列车轴承轨旁声学诊断[J]. 电子科技, 2024, 37(1): 55-60.

ZHANG Yanzhe,HU Dingyu,SHI Wei,LIAO Aihua. Train Bearings Diagnosis Method for Wayside Acoustic Signal Based on Spatial-Frequency Joint Filtering[J]. Electronic Science and Technology, 2024, 37(1): 55-60.

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轴承型号	NSK N212
轴承孔径d/mm	60
轴承外径D/mm	110
轴承宽度B/mm	22
滚动体个数Z	16
外圈故障特征频率f_i/Hz	13

基于空-频域联合滤波的列车轴承轨旁声学诊断

Train Bearings Diagnosis Method for Wayside Acoustic Signal Based on Spatial-Frequency Joint Filtering

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