Open Access

Fuzzy Identification of The Reliability State of The Mine Detecting Ship Propulsion System


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The study presents the evaluation and comparative analysis of engine shaft line performance in maritime transport ships of the same type. During its operation, a technical system performs functions for which it was designed. It goes through different states. Dynamic state changes of a rotational system can be identified by means of its vibration measurement. For this purpose, a research was carried out which involved recording vibrations of the analysed rotational systems. The recordings were used for calculating selected characteristics in the time-domain, where one of the most unique is the value of the normalized mutual correlation function. On the basis of the concentration values, the characteristics which unambiguously determine the ability state were selected for further studies. Then an identification method for rotational system non-coaxiality was proposed. The method involves using fuzzy clustering. According to this method the values of input signal characteristics were used to formulate fuzzy clusters of system ability and inability states. The method can be used for identifying the current state of the system. The study presents the results of the application of this method in engine turbine shaft lines of minesweepers, with the rotational system selected as an example. It needs to be noted that the efficiency of identifying the operating state of the system with this method is higher than with other methods described in the literature by authors who deal with this issue. The research results have a significant impact on the evaluation of mechanical properties of the studied objects and directly affect operational states of mechanical systems, including those installed in minesweepers, thus determining their reliability.

eISSN:
2083-7429
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Engineering, Introductions and Overviews, other, Geosciences, Atmospheric Science and Climatology, Life Sciences