ENTROPY OF DISCRETE WAVELET TRANSFORM AND RADIAL NEURAL NETWORKS AS A DIAGNOSIS TOOL OF DIESEL ENGINE EXHAUST VALVE FAULT
Journal Title: Scientific Journals of Silesian University of Technology. Series Transport - Year 2011, Vol 2011, Issue 73
Abstract
In case of diagnosing combustion engines by vibration methods, the presence of numerous sources of vibration cannot be neglected, which are the reason for reciprocal interference of symptoms of fault. Owing to the necessity of analyzing non-stationary and impulse signals, a discrete wavelet transform (DWT) has been applied in this study. Based on the signals’ decomposition performed by means of the transform, the value of entropy was determined, which served as a basis in the construction of the states of engine operation intended for teaching neural networks. As results from the research, there is a possibility of using radial neural networks to assess the diesel engine exhaust valve fault.
Authors and Affiliations
Piotr CZECH
Keywords
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