| For all petrochemical enterprises, it is the most considerable work to maintain the stable operation of reciprocating compressors which play a very important role in petrochemical production. Therefore, the condition monitoring and fault diagnosis for reciprocating compressors are of great practical significance and economic value. Some effective work for condition monitoring and fault diagnosis of reciprocating compressor is carried out. The main work of this dissertation is listed as follows:1. The mechanism and the common fault of reciprocating compressors are analyzed. Then the fault phenomena and mechanism of the key parts are researched.2. According to the monitoring parameters, the fault diagnosis methods are presented, such as parametric method, P-V method, vibration analysis method. On discussing the main fault source in the construction,the character of the vibration signal are studied. Compared with the time-frequency analysis algorithm such as FFT, Winger-Ville, EMD,we propose Local-wave method based on EMD for the analysis of nonlinear and non-stationary signal.3. According to the type of monitoring parameters and the characteristics of reciprocating compressor, the type of sensors and the location of the measurement points are determined.4. Research the influence of the noise and defect of EMD on the accuracy of the analysis. This paper uses the improved wavelet de-noising method to pretreat the rolling bearing vibration signal, and the main idea of this method is to improve the threshold selection principle and the threshold function. The empirical mode decomposition method is improved by using EMD. The method can distinguish whether the intrinsic mode function is the pseudo component.5. This paper combines the EMD with the Hilbert transform, and applies the method to extract the rolling bearing fault diagnosis feature.6. Reciprocating compressor condition monitoring and fault diagnosis system interface program is developed. |
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