Picture of a sphere with binary code

Making Strathclyde research discoverable to the world...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs. It exposes Strathclyde's world leading Open Access research to many of the world's leading resource discovery tools, and from there onto the screens of researchers around the world.

Explore Strathclyde Open Access research content

Pattern recognition on diesel engine working conditions by Wavelet Kullback-Leibler distance method

Zhou, P. and Li, H. and Clelland, D. (2005) Pattern recognition on diesel engine working conditions by Wavelet Kullback-Leibler distance method. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 219 (9). pp. 879-887. ISSN 0954-4062

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

This article introduces a novel pattern recognition and fault diagnosis method for diesel engines. The method is developed from engine vibration signal analysis in combination with wavelet and Kullback-Leibler distance (KLD) approaches. The new approach is termed wavelet Kullback-Leibler distance (WKLD). Experimental data relating to piston and cylinder liner wear obtained from a production diesel engine are used to evaluate the newly developed method. A good agreement between the experimental data and the WKLD estimation is found. The results of this article suggest that WKLD is an advancement on the methods which have been currently developed for pattern recognition and fault diagnosis of diesel engines.