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作 者:马共立 MA Gongli(Harbin Railway Research Institute Technology Co.,Ltd.,Harbin 150006,China)
机构地区:[1]哈尔滨铁路科研所科技有限公司,黑龙江哈尔滨150006
出 处:《铁道车辆》2021年第4期94-97,共4页Rolling Stock
摘 要:以铁路车辆滚动轴承故障和车轮故障为例,分析了不同故障导致的冲击噪声特征,并结合多年TADS采集的噪声数据,利用时域声强计算、谱分析和小波变换方法建立了异音判别模型。经过实际运用证明,利用异音判别模型升级软件后的TADS设备在用于铁路车辆滚动轴承故障预报的同时,也可用于对轴承附近其他部件故障的异音进行检测和报警。In the case of faults of rolling bearing and wheel for railway vehicles,the features of impulse noise caused by different faults are analyzed,and combined with the noise data collected by TADS in recent years,the abnormal sound discrimination model is established with method of time-domain sound intensity calculation,spectral analysis and wavelet transform.The practical application proves that TADS with software upgraded by abnormal sound discrimination model can not only be used for the fault prediction of rolling bearings for railway vehicles,but also be used to detect and alarm the abnormal sound of other parts near the bearing.
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