Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 22, Issue 5, Pages 1179-1193Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2007.11.012
Keywords
embedding dimension; regression trees; prognosis; time-series forecasting
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Funding
- Korea Institute of Industrial Technology(KITECH) [10029130] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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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. (c) 2007 Elsevier Ltd. All rights reserved.
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