Abstract
This paper has studied the application of wavelet package energy spectrum and frequency energy spectrum analysis in the diesel engine fault diagnosis. Extracting the fault features by wavelet package energy spectrum and frequency energy spectrum analysis of the fault angle of fuel supply decreased 2.5° and plug of air filter, then making those as the input character of neural networks and implementing the fault diagnosis. It is concluded that frequency energy spectrum analysis is more strongly of the practicability than wavelet package energy spectrum analysis by comparing the test results.
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