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Fault Prediction and Maintenance of Non‐Periodic Incipient Fault for Hydraulic Tube Tester
Author(s) -
Zhao Zhen,
Zhang Jun,
Wang Shu,
Chang Yuqing,
Jia Mingxing
Publication year - 2014
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.836
Subject(s) - fault (geology) , probabilistic logic , engineering , reliability engineering , process (computing) , component (thermodynamics) , control theory (sociology) , computer science , artificial intelligence , geology , seismology , physics , control (management) , thermodynamics , operating system
This paper is concerned with fault prediction and maintenance for the hydraulic tube tester according to the process variables. For the two types of incipient faults of this machine, it is more difficult to predict the non‐periodic incipient fault and make a predictive maintenance decision in comparison with the periodic incipient fault. For the non‐periodic incipient fault, a new probabilistic fault prediction method is proposed using a multivariate principle component analysis and B ayesian auto‐regression model. Then, a new predictive maintenance policy is developed, based on the results of the probabilistic fault prediction approach, which implies the evolvement of system deterioration caused by the non‐periodic incipient fault. Simulation results demonstrate the effectiveness of the method proposed in this paper.