Feature extraction based on teager-kaiser energy operation and envelope spectra for fault detection of a reciprocating compressor

In this paper, signal analysis techniques based on Teager- Kaiser energy operation and envelope spectra for fault detection of the discharge valve of a reciprocating compressor is proposed. The method can accurately identify the existing fault of vibration signal features that it simulated by the synthetic signals. A twophase study was designed to explore the signals simulation and the experimental validation. Signals simulation, which is based on the operation of a reciprocating compressor, and experiment design, which uses three conditions. The first stage is to simulate the operation of the reciprocating compressor, which is to simulate a synthetic signal for the cycle and impact. The synthetic signal is composed of a noise, square wave, and pulse wave. In this study, the synthetic signal is signal-processed by the Teager-Kaiser energy operator and the envelope spectrum that they can effectively extract feature signal and the noise almost is eliminated. The second stage is applied to the signal processing technique proposed in the first stage. Experimental verification of experiment design by the different operating conditions of reciprocating compressor valves. Through the above analysis technology, it is proved that the synthetic signal can be eliminated the background noise to obtain the feature signal. The feasibility of the proposed approach is verified by simulation results, the experiment is to validate with the measurement signals from a six-cylinder reciprocating compressor under different valve conditions. Simulations and experimental results support the proposed technology positively.