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Analysis of vibration signals using short-time analysis and clustering in parameter space for detection of combustion engine state

Boguś Piotr, Merkisz Jerzy

Combustion Engines

2019

R. 58, nr 2

83--87

The paper presents a short-time analysis of the vibration signals for the diagnosis of Diesel engine of combustion locomotive by recognition of different engine states using the clustering technique. The main aim of the researches was to distinguish between different engine states represent different wear extends. The proposed method of vibration signal analysis consists on sliding a time window along signal in time and observing the changes of some given statistical parameters. The set of this parameter values creates a multidimensional parameter space where the time evolution can be observed. For recognition and detection of different engine system states some clustering techniques in the parameter space were performed. The results show the possibility of distinguishing different cluster centers within the parameter space which can be assigning to different engine states represented the states before and after a general repair.

Multiresolution analysis of vibration signals acquired from locomotive Diesel engine for classification of engine states basing on signal statistical parameters

Boguś P., Cieszyński M., Merkisz J.

Combustion Engines

2017

R. 56, nr 1

68--72

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.