Identification of Inability States of Rotating Subsystems of Vehicles and Machines

Abstract

Abstract One of the most important subsystems of the vehicles and machines operating currently in industry and transportation are the rotating subsystems. During the subsystems operation, due to the forcing factors influence, the technical state of them is changing and the failure can occur. In order to avoid such a situation the technical state should be identified online. To do this the analysis of the subsystems vibrations is performed. The identified technical state should be considered in a context of the ability and different inability states. Therefore, the first step of the diagnostic procedure is the ability and different inability states identification. In the article, it is proposed to accomplish this goal by the vibrations analysis in time domain. The described research started with the vibration signals acquisition using the experimental stand. In this way, the vibration signals for ability and different inability states were obtained. Afterwards, the signals were divided into learning and testing data sets. For each signal from learning data set, several characteristics were calculated, and they selected the most significant among them. Using the selected characteristics, the signals from the testing data set were analysed. Thanks to it, the testing vibrations signals were counted among the signals collected on the rotating subsystem operating in ability or selected inability state. The result of the performed studies and the accuracy of the technical state of the tested system identification can be found at the end of the article.