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A non-destructive fault diagnosis method for a diaphragm compressor in the hydrogen refueling station

机译:加氢站隔膜压缩机的无损诊断方法

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Costly and time-consuming maintenance of the hydrogen compressors due to their frequent breakdown severely hinders the deployment and promotion of hydrogen refueling station (HRS), and effective condition monitoring and fault diagnosis is the key to reduce the unscheduled downtime of the compressor. This paper proposes a nondestructive method for fault diagnosis of diaphragm compressors for HRSs based on the acoustic emission (AE) signal. The AE signals in the time domain are segmented into angle domain signals correspond to a working cycle. The feature events of the moving components are determined through the measured AE signal in both angle-domain and angle frequency domain based on short-term Fourier transform (STFT). Those feature events signals are innovatively applied to identify the typical abnormal conditions of excessively high oil pressure, slightly inadequate oil pressure and seriously inadequate oil pressure, replacing the traditional and destructive pressure measuring method. The results show that this method can be used to effectively diagnose abnormal working conditions and indicate that this method can be utilized as a powerful tool in the non-destructive condition monitoring and fault diagnosis of the diaphragm compressors. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
机译:由于氢压缩机频繁故障而导致的昂贵且费时的维护工作严重阻碍了氢加油站(HRS)的部署和推广,有效的状态监测和故障诊断是减少压缩机意外停机的关键。本文提出了一种基于声发射(AE)信号的HRS隔膜压缩机故障诊断的非破坏性方法。时域中的AE信号被分割成与工作周期相对应的角域信号。通过基于短期傅立叶变换(STFT)的角度域和角度频域中的AE信号确定运动分量的特征事件。这些特征事件信号被创新地应用于识别油压过高,油压略有不足以及油压严重不足的典型异常情况,从而取代了传统的破坏性压力测量方法。结果表明,该方法可有效地诊断异常工况,表明该方法可作为隔膜压缩机无损状态监测和故障诊断的有力工具。 (C)2019氢能出版物有限公司。由Elsevier Ltd.出版。保留所有权利。

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