Abstract
The paper presents a method of classification of locomotive Diesel engine states basing on vibration signals taken from an engine body and using chosen statistical parameters calculated for the original signal and it wavelet multiresolution components. The researches presented in the paper concern estimation of an engine states before and after a general repair. The target application of the presented researches is an on-line diagnostic system which can complement standard OBD systems. To this purpose the applied methods should not base on complex analysis of some spectral, time-frequency or scalogram plots but rather on choosing single diagnostic parameters which are suitable for the fast on-line diagnostic. The results have showed the significant difference in distinguishing of engine work before and after a general repair using some chosen statistical parameters applied to vibration signals.
Highlights
A combustion engine is an example of a mechanical device which can run down
It is this imminent perspective that gives an impulse to research new detection methods that would be applicable in diesel locomotives and which base on vibration analysis [1]
The results presented in the paper covers the application of multiresolution wavelet analysis into diagnostic of rail vehicle combustion engine with application of some chosen statistical parameters applied to the original signal and it wavelet multiresolution components
Summary
A combustion engine is an example of a mechanical device which can run down. The engine diagnosis needs estimation of the technical state of an engine during it exploitation. The proposition of engine diagnostic presented in the paper bases on the indication of some diagnostic parameters which can be useful to distinguish engine different states by signal processing methods without considering details of mechanical engine processes. In this on-line analysis the applied methods cannot base on complex analysis of spectral, time-frequency or scalogram plots but they need choosing single diagnostic parameter which can be applied in a fast on-line diagnostic. The results presented in the paper showed the significant difference in distinguishing of engine work before and after a repair using some of chosen shape parameters applied to vibration signals taken from an engine
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