点击次数：

论文类型：会议论文

发表时间：2016-06-13

收录刊物：EI、CPCI-S

卷号：2D-2016

摘要：Centrifugal compressor is a piece of key equipment for factories. Among the components of a centrifugal compressor, impeller is a pivotal part as it is used to transform kinetic energy to pressure energy. The blades are exposed to centrifugal forces, gas pressure, and the friction force which usually lead to cracks.
   Therefore, early crack feature extraction and pattern recognition are important to prevent it from failure. Although time series analysis for monitored signals can be used on feature extraction, it is not enough. So the incipient weak feature extraction method should be investigated. In this research, pressure pulsation sensors arranged close to crack area are used to monitor the blade crack signal and extract the feature information. As the different kinds of interference of flow, the pressure pulsation signals for a centrifugal compressor are full of nonlinear characteristics. Therefore, how to obtain the weak information from monitored signals effectively should be investigated. A method on blade crack classification is present by continuous wavelet transform (CWT) and envelope spectrum in this research. Simulation signal analysis and experimental investigation on blade crack classification are carried out to verb the effectiveness of this method The results show that it is an effective tool for blade incipient crack classification for a centrifugal compressor