A novel scheme for fault detection of reciprocating compressor valves based on basis pursuit, wave matching and support vector machine

A scheme for fault detection of compressor valves based on basis pursuit (BP), wave matching and support vector machine (SVM) is presented. BP is applied to extract the main vibration component in the signal and suppress background noise. Wave matching is a new feature extraction method proposed in this paper. Instead of extracting features through commonly used indicators such as statistic measures or information entropy, wave matching extracts features by matching the vibration signal with parameterized waveform optimized by differential evolution (DE) algorithm. It only produces a small number of features and the features have clear physical meaning. SVM is employed in the fault classification because of its superiority in dealing with small sample problems. The results of real compressor valve signal analysis confirm that the proposed scheme can differentiate compressor valve faults with high accuracy and reliability.

► Wave matching is a novel feature extraction method. ► Wave matching is able to extract features with physical meanings. ► Basis pursuit shows a good performance in de-noising valve vibration signals. ► The scheme can identify three types of valve faults with high accuracy.