A non-destructive fault diagnosis method for a diaphragm compressor in the hydrogen refueling station
A non-destructive fault diagnosis method for a diaphragm compressor in the hydrogen refueling station
复制标题
加氢站隔膜压缩机无损故障诊断方法
DOI：
10.1016/j.ijhydene.2019.07.147
复制
发表时间：
2019-09
影响因子：
7.2
通讯作者：
Xueyuan Peng
中科院分区：
文献类型：
--
作者：
Li Xueying;Chen Jiahao;Zhizhong Wang;Xiaohan Jia;Xueyuan Peng
摘要加氢站氢气压缩机故障频繁，维护费用高、耗时长，严重阻碍了加氢站的部署和推广，有效的状态监测和故障诊断是减少压缩机非计划停机的关键。本文提出了一种基于声发射信号的高分辨率压缩机故障无损诊断方法。声发射信号在时域上被分割成对应于一个工作循环的角域信号。基于短时傅立叶变换（STFT），通过测量的声发射信号在角域和角频域确定运动部件的特征事件。创新性地应用这些特征事件信号识别油压过高、油压轻微不足和油压严重不足等典型异常情况，取代了传统的破坏性压力测量方法。结果表明，该方法能有效地诊断出异常工况，为隔膜压缩机的无损状态监测和故障诊断提供了有力的工具。
Abstract 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 non-destructive 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.
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DOI：
--
发表时间：
1990
期刊：
--
影响因子：
--
作者：
K. Haugland
通讯作者：
K. Haugland
影响因子：
3.5
作者：
F. Elamin;F. Gu;A. Ball
通讯作者：
F. Elamin;F. Gu;A. Ball
影响因子：
8.4
作者：
Zhike Peng;F. Chu;P. Tse
通讯作者：
Zhike Peng;F. Chu;P. Tse
影响因子：
4.7
作者：
Charles, P.;Sinha, Jyoti K.;Ball, A. D.
通讯作者：
Ball, A. D.
70 MPa IV型氢复合压力容器水压试验损伤声发射表征
影响因子：
7.2
作者：
Liao B. B.;Wang D. L.;Hamdi M.;Zheng J. Y.;Jiang P.;Gu C. H.;Hong W. R.
通讯作者：
Hong W. R.