Diesel engine fault diagnosis based on high-order cumulant image features

Different positions' mechanical fault features of diesel engines are easy to be confused and they are often drowned in other components and color noises, so it is difficult to distinguish and extract them. Here, a fault diagnosis method based on high-order cumulant image features was proposed. Three-order cumulants for six cycles of vibration signals were calculated, respectively and the results were averaged to get three-order cumulant of one cycle. The image texture feature parameters based on three-order cumulant image gray level co-occurrence matrices (GLCM). For different fault states of diesel engines were extracted. The pattern recognition was performed with a support vector machine (SVM). The results showed that this method can inhibit noises and make full use of texture feature information of high-order cumulant image to analyze unsteady signals, the extracted features can be used to distinguish 6 technical states of diesel engines effectively, the fault diagnosis accuracy is improved compared with the traditional feature extraction based on high-order cumulant. ©, 2015, Chinese Vibration Engineering Society. All right reserved.