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Machine condition prognosis based on regression trees and one-step-ahead prediction

Tran, Van Tung, Yang, Bo-Suk, Oh, Myung-Suck and Tan, Andy Chit Chiow (2008) Machine condition prognosis based on regression trees and one-step-ahead prediction. Mechanical Systems and Signal Processing, 22 (5). pp. 1179-1193. ISSN 0888-3270

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Predicting the degradation of working conditions of machinery and trending of fault propagation before they reach the alarm or failure threshold is extremely important in industry to fully utilize the machine production capacity. This paper proposes a method to predict the future conditions of machines based on one-step-ahead prediction of time-series forecasting techniques and regression trees. In this study, the embedding dimension is firstly estimated in order to determine the necessarily available observations for predicting the next value in the future. This value is subsequently utilized for the predictor which is generated by using regression tree technique. Real trending data of low methane compressor acquired from condition monitoring routine are employed for evaluating the proposed method. The results indicate that the proposed method offers a potential for machine condition prognosis.

Item Type: Article
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering
Depositing User: Van Tran
Date Deposited: 31 Jan 2013 12:41
Last Modified: 28 Aug 2021 20:13


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