首页|基于多普勒信号校正和短步长波束形成的列车轴承故障检测

基于多普勒信号校正和短步长波束形成的列车轴承故障检测

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针对受多普勒调制的移动声源信号时域幅值畸变、频域频带展宽,且在强背景噪声下信噪比(SNR)低,难以提取其故障特征等问题,提出了一种基于多普勒信号校正和短步长波束形成的列车轴承故障检测方法.首先,由声源和麦克风的相对运动关系和莫尔斯声学理论,得到了插值时间序列和幅值还原公式,对受多普勒调制的畸变信号进行了恢复;然后,提出了基于麦克风阵列的短步长波束形成方法,分段截断了信号,并对每段信号在其期望方向上进行了增强;最后,通过仿真研究了不同信噪比情况下该方法的有效性,设计了轨边故障检测实验,对产生内圈裂纹缺陷的滚动轴承进行了实验分析,并结合仿真与实验,对该方法的有效性进行了验证.研究结果表明:相较于8 个麦克风收集的原始信号,信号时域、频域均被校正,且信噪比增加了 11.5 dB,在强噪声背景下,采用该方法能够恢复多普勒畸变信号,并有效提取移动声源的故障特征.
Fault detection of train bearings based on Doppler signal correction and short-step long-wave beam formation
Aiming at the problem of difficulty in detecting the faults of sound source during driving,the received signal was affected by Doppler effect,which caused the problem of frequency shift,frequency band spread and amplitude modulation,and in addition,signal was in a low signal-noise ratio(SNR)which caused by strong environmental noise,which seriously affectd the extraction of the target sound signal,a fault detection method for train bearings based on Doppler signal correction and short-step long-wave beamforming was proposed.Firstly,based on the relative motion relationship between sound source and microphone and Morse acoustic theory,the interpolation time series and amplitude reduction formulas were obtained to recover the distorted signal modulated by Doppler effect.Then,a short-step beamforming method based on microphone array was proposed,which intercepted the signal in segments and enhanced each segment in its expected direction.Finally,the effectiveness of this method under different signal-to-noise ratio was studied by simulation.The rail edge fault detection experiment was designed,and the rolling bearing with inner ring crack defect was analyzed experimentally.Combining with simulation and experiment,the effectiveness of this method was verified.The research result shows that comparing with the original low SNR signal collected by 8 microphones,the signal is corrected in both time domain and frequency domain,and the SNR is increased by 11.5 dB.The proposed method can recover the Doppler distortion signal and effectively extract the fault characteristics of mobile sound sources under strong interference environment.

mobile sound sourceDoppler effectrolling bearingfault diagnosisDoppler signal correctionshort-step long wave beamforming methodsignal-noise ratio(SNR)

蔺秋雨、纪爱敏、杜占涛、陈曦晖、林新海

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河海大学 机电工程学院,江苏 常州 213000

中车戚墅堰机车车辆工艺研究所有限公司,江苏 常州 213000

移动声源 多普勒效应 滚动轴承 故障诊断 多普勒信号校正 短步长波束形成方法 信噪比

国家自然科学基金资助项目江苏省自然科学基金资助项目江苏省科技成果转化专项资金项目常州市科技计划项目

51905147BK20201163BA2019020CM20223014

2024

10.3969/j.issn.1001-4551.2024.09.002

机电工程
浙江大学　浙江省机电集团有限公司

机电工程

CSTPCD北大核心
影响因子：0.785
ISSN：1001-4551
年,卷(期)：2024.41(9)
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