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Similarity-based prediction method for machinery remaining useful life: A review

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Abstract

Determining the remaining useful life (RUL) of increasingly complex machines provides the decision basis for the predictive maintenance process, which effectively ensures equipment safety, improves the utilization rate, and reduces the maintenance cost. Similarity-based prediction (SBP) methods are one type of RUL prediction technique, generally divided into four steps: condition monitoring data collection, degradation information fusion, similarity evaluation, and model prediction aggregation. SBP methods have advantages which include strong interpretability and a simple implementation process. Intensive studies and wide applications based on the SBP methods exist in both academia and industry. SBP methods have been included in numerous reviews, but they mainly focus on the first two steps or just one of the steps. Existing reviews lack recent advances of SBP methods and discussions of the four steps in detail. To fill the above gaps, this paper reviewed the whole procedure of SBP methods. Firstly, the prognostics industrial scenarios with limited failure data and sufficient failure data are introduced. Then, the degradation indicators (DIs) of the machines are constructed through a fusion of degradation information. Later, similarity calculation and similarity matching rule are utilized to evaluate the similarity of the DIs segments. After that, point estimation and uncertainty management are acquired by integrating the referential DIs segments. Finally, the effectiveness of the SBP methods in different industrial scenarios, the limitations, and future challenges are discussed.

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Acknowledgements

The authors are thankful for the fruitful discussions with Prof. Hongshuang Li, Prof. Demetrio Cristiani, and Prof. Wennian Yu. The authors also thank the publisher for providing the publicly available datasets for benchmark problems.

Funding

This work was supported by National Natural Science Foundation of China (No. 52073247), Institute of Robotics at Zhejiang University under (Grant K12105), and Special Innovation Fund of Zhejiang University, Ningbo (No. 702002J20211109).

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Authors and Affiliations

  1. Institute of Process Equipment, College of Energy Engineering, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, Zhejiang, China

    Bin Xue, Huangyang Xu & Zhongbin Xu

  2. John A. Paulson School of Engineering and Applied Sciences, Harvard University, 8 Garden Street, Cambridge, 02138, Massachusetts, USA

    Xing Huang & Hao Pei

  3. Wenzhou Institute, University of Chinese Academy of Sciences, 1 Jinlian Road, Wenzhou, 325000, Zhejiang, China

    Xing Huang

  4. Institute of Robotics, Ningbo Research Institute, Zhejiang University, 1 Qianhu South Road, Ningbo, 315100, Zhejiang, China

    Ke Zhu & Zhongbin Xu

  5. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, Zhejiang, China

    Zhongbin Xu

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  1. Bin Xue
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  3. Xing Huang
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  4. Ke Zhu
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Contributions

All authors contributed to this review study. Material preparation, data collection and analysis were performed by Bin Xue, Huangyang Xu, and Ke Zhu. The first draft of the manuscript was written by Bin Xue and revised by Xing Huang and Hao Pei. Zhongbin Xu was responsible for the supervision and funding acquisition. All authors read and approved the final manuscript.

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Correspondence to Zhongbin Xu.

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Xue, B., Xu, H., Huang, X. et al. Similarity-based prediction method for machinery remaining useful life: A review. Int J Adv Manuf Technol 121, 1501–1531 (2022). https://doi.org/10.1007/s00170-022-09280-3

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