An Approach for the Construction of Entropy Measure and Energy Map in Machine Fault Diagnosis

Abstract

This paper presents a novel wavelet-based methodology for feature extraction and classification. To compare the performance of the proposed approach with major existing methods, a number of sets of real-world machine data acquired by mounting accelerometer sensors on the cylinder head of an engine have been extensively tested. The developed method not only bypasses the demerits of the previous techniques but also demonstrates superior performance.