A GAS REGULATOR FAULT DETECTING METHOD BASED ON ACOUSTIC EMISSION TECHNOLOGY

摘要：

　　In this paper, a new method of gas pressure regulator fault diagnosis is proposed.The wavelet packet decomposition is used for feature extraction of the acoustic emission signal.Then, based on the model obtained in the BP neural network, early regulator fault can be detected.The experimental results prove the feasibility of this method.It can effectively improve the accuracy of the fault diagnosis of the regulator.In addition, the millisecond diagnostic cycle also makes this method have a high engineering value.

关键词： Gas pressure regulator Acoustic emission Wavelet packet BP neural network

作者: Jian-ying JIAO Ya-peng WEI Hong-Lang LI Yao LIU Fei-da CAI Fei JIANG Ming-xin SONG Song-ling TAN

作者单位: Beijing Gas Group Co.Ltd, P.R.China, 100035 Institute of Acoustics Chinese Academy of Sciences, P.R.China, 100190;Beijing Institute of Technolog Institute of Acoustics Chinese Academy of Sciences, P.R.China, 100190 Institute of Acoustics Chinese Academy of Sciences, P.R.China, 100190;University of Chinese Academy

会议类型: 国际会议

会议名称: The 2017 Symposium on Piezoelectricity,Acoustic Waves and Device Applications(2017全国压电和声波理论及器件技术研讨会)

会议地点: 成都

会议语种:英文

页码: 91-94

在线出版日期: 2017-10-27（万方平台首次上网日期，不代表论文的发表时间）