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| Research of Predicting Machine’s Remaining Useful Life Based on Statistical Pattern Recognition and Auto-regressive and Moving Average Model |
| LIAO Wen-Zhu-1, PAN 尔Shun-2, WANG Ying-2, XI Li-Feng-2 |
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Abstract Considering the important applications of predictive maintenance (PdM) today, it becomes essential to acquire machine’s condition and its deterioration process. A machine’s remaining useful life (RUL) model was proposed in which a statistical pattern recognition (SPR) method is developed to estimate machine’s health index (HI) and an autoregressive and moving average (ARMA) model is used to predict machine’s RUL based on HI information, which greatly supports PdM planning. Through a case study, the computational results show that the proposed model is efficient and practical.
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Received: 28 July 2010
Published: 29 July 2011
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