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首页> 外文期刊>Advances in Mechanical Engineering >Wayside acoustic fault diagnosis of train wheel bearing based on Doppler effect correction and fault-relevant information enhancement:
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Wayside acoustic fault diagnosis of train wheel bearing based on Doppler effect correction and fault-relevant information enhancement:

机译：基于多普勒效应校正和故障相关信息增强的火车轮轴承路边声学故障诊断：

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Health monitoring of train bearing is crucial to railway transport safety. More and more attention has elicited by the wayside acoustic monitoring technique in recent years than other defect detection techniques. However, wayside acoustic signal contains serious Doppler distortion and heavy background noise because of the high speed of trains. Thus, extracting fault-relevant information is difficult. A novel method for Doppler effect correction is proposed in this study by incorporating the traditional time-domain interpolation resampling with a novel kinematic parameters estimation method. In this kinematic parameters estimation method, an iterative algorithm based on least squares theory is proposed to improve the parameters estimation accuracy. After the Doppler effect correction, the ensemble empirical mode decomposition is employed to further enhance the fault-relevant information. The proposed iteration algorithm can improve the accuracy of kinematic parameters estimation significantly; thus the Dop...
机译：火车轴承的健康监测对铁路运输安全至关重要。近几年除其他缺陷检测技术的路边声学监测技术越来越多地引起了越来越多的关注。然而，由于高速列车，路边声信号包含严重的多普勒失真和重型背景噪声。因此，提取故障相关信息很难。本研究提出了一种新的多普勒效应校正方法，通过结合具有新型运动参数估计方法的传统时域插值重采样。在这种运动学参数估计方法中，提出了一种基于最小二乘理论的迭代算法来提高参数估计精度。在多普勒效应校正之后，采用集合经验模式分解来进一步增强故障相关信息。建议的迭代算法可以显着提高运动学参数估计的准确性;因此dop ......

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