Malfunction Detection in Multi-cylinder Engines Using Wavelet Packet Dictionary
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In this paper, wavelets as signal processing tools are used to analyze the acceleration data acquired at the cylinder head for the detection and characterization of combustion malfunctions in multi-cylinder industrial engines. The objectives were to collect data on 1) normal operations, and 2) operations with a deactivated cylinder to simulate a faulty condition. Wavelet packet and local discriminatory basis algorithm are used to select wavelets that can recognize different conditions. It is shown that the wavelet packet provides a useful data analysis structure for extracting features that are capable of detecting the combustion malfunction of one cylinder in a 12-cylinder engine. Feature extraction is followed by a classification that uses a neural network for the fault identification phase. Copyright © 2005 SAE International.
author list (cited authors)
Tafreshi, R., Sassani, F., Ahmadi, H., & Dumont, G.