Research on Quality Detection Methods for Automotive Transmission

Given the problems in intelligent diagnosis methods for automotive transmission, it is difficult to obtain the fault signal features and a large enough sample size to study. To solve these problems, a method integrating order tracking, cepstrum, support vector machine (SVM) and extremal curve is proposed in this paper. Order tracking and cepstrum are combined for processing the non-stationary vibration signal emitted by automotive transmission. As conventional intelligent methods cannot produce true results for insufficient samples, a method that combines SVM and extremal curve is presented. Input the vector acquired from the feature signals into the SVM model for the first detection, and then do the second detection by means of extremal curve which in turn can enrich the training samples in SVM model thus making the SVM model be more perfect. Analytical description and experimental studies are presented for the methods of signal processing and quality detection. The experimental results demonstrate the effectiveness and practicability of the proposed method. Copyright © 2014 IFSA Publishing, S. L.