Fault Diagnosis for Diesel Valve Train Based on S Transform
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Several typical faults of diesel engines valve train were simulated in this paper. The vibration acceleration signals, which were acquired from the cylinder head, were analyzed with S Transform and then a series of timefrequency images were obtained. Eight standard timefrequency images were built from these images. By using some indexes such as Euclid distance, absolute distance and similarity between testing images and standard images, the testing images were classified into eight kinds, which correspond to eight states of valve train. Then the fault diagnosis for valve train was changed to classify timefrequency images. The experimental results show that this method can recognize the state of valve train correctly. Based on the indexes of similarity and Euclid distance, the rate of correct recognition can be as high as 994% when the images are averaged 5 times before classifying.