A Classification and Regression Trees (CART) Model of Parallel Structure and Long-term Prediction Prognosis of Machine Condition
Author(s): |
Van Tung Tran
Bo-Suk Yang Andy Chit Chiow Tan |
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Medium: | journal article |
Language(s): | English |
Published in: | Structural Health Monitoring, September 2009, n. 2, v. 9 |
Page(s): | 121-132 |
DOI: | 10.1177/1475921709352148 |
Abstract: |
This article presents a combined prediction model involving the parallel of classification and regression trees (CART) model, namely p-CART, and a long-term direct prediction methodology of time series techniques to predict the future stages of the machine’s operating conditions. p-CART model consists of multiple CART models which are connected in parallel. Each sub-model in the p-CART is trained independently. Based on the observations, these sub-models are subsequently used to predict the future values of the machine’s operating conditions separately with the same embedding dimension but different observations’ indices. Finally, the predicted results of sub-models are combined to produce the final results of the predicting process. Real trending data acquired from condition monitoring routine of compressor are employed to evaluate the proposed method. A comparative study of the predicted results obtained from traditional CART and p-CART models is also carried out to appraise the prediction capability of the proposed model. |
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10561663 - Published on:
11/02/2021 - Last updated on:
19/02/2021