Fault Diagnosis for IC Engines Using Wavelet Packet and Image Processing

摘要

There are few applications of image processing technology for diagnosing and state monitoring for internal combustion (IC) engines, which is discussed in detail in this paper. The time-frequency distribution images of cylinder head vibration signals are obtained by decomposing them with a wavelet packet algorithm. It is the first time that we look at time-frequency distribution images from the point of images. Based on this, a new method for applying image processing technology for diagnosing and state monitoring for internal combustion engines is presented in this paper. A valve fault diagnosis model is set up by image matching, which is realized on a four-stroke, six-cylinder diesel engine. At the same time, some notes are presented in this paper. It has been proved that it is of no good effect to diagnose with histograms of time-frequency images generated by cylinder head vibration signals that have been processed with a wavelet packet algorithm. The reason is given in this paper. Comparisons of diagnosing effect are carried out between noise-added signals and original signals. It has little effect on diagnosing results after signals have been added with noise. The results show that this method has a clear physical meaning and is of good engineering practicability, feasibility, good precision and high speed.