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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 parameters 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 obtained results and observation of the multidimensional parameter space seem quite promising. They show the possibility of distinguishing different cluster centers within the parameter space which can be assign to different engine states represented e.g. the states before and after a general repair. However the general conclusion are not fully clear because of the great complexity and variety of possible measurement schemes.