Abstract
One of the most important subsystems of the vehicles and machines operating currently in industry and transportation are the rotating subsystems. Monitoring of its technical state is an important issue of the engineering and academic research. As a result of the research a lot of new diagnostic methods have been formulated but one of the most important characteristic of them is the ability to industrial implementation. It depends on the insensitivity to disturbance which can arise in real operational environment. In the paper the method formulated by the authors is analysed. This is the method of the identification of inability states of rotating subsystems based on the vibrations analyses in the time domain. It constitutes the system approach to the considered issue. There are three applications of the method described - research on simulation laboratory stand, research on a real technical object conducted in the laboratory and research carried out on a real technical object under the real operation conditions. In each case different accuracy of the ability and inability states identification is achieved. Analysing the differences in accuracy of the method applications the conclusion of its sensitivity to the conditions of the experiment were formulated which are presented in the end of the paper.
Highlights
The analysed method is used to identify the reliability states of the rotating subsystems in different kind of vehicles and machines
This is the method of the identification of inability states of rotating subsystems based on the vibrations analyses in the time domain
There are three applications of the method described - research on simulation laboratory stand, research on a real technical object conducted in the laboratory and research carried out on a real technical object under the real operation conditions
Summary
The analysed method is used to identify the reliability states of the rotating subsystems in different kind of vehicles and machines. The mean values of the characteristics of learning groups define points in the space In this way for ability group of learning signals in RSS space the point of the ability states is defined. In ISS space, the mean values of the characteristics - the dimensions of this space for specified types of failures groups of learning signals determine the points of specific types of inability states. In the final step of the method, in each space, the distances between the points enumerated above and the points determined for each vibration signal from testing groups are calculated. The signal was identified as a signal recorded on rotating subsystem remaining in specified inability state if the distance between the point of ISS space determined for analysed vibration signal and the point of ISS space determined for one of the considered inability states is the smallest one
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