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A high-speed D-CART online fault diagnosis algorithm for rotor systems

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Abstract

Intelligent manufacturing poses a challenge for fault diagnosis of rotor systems to meet the three tasks: whether exists faults, faults location and quantitative diagnosis. Traditional methods hardly meet all the three tasks in online fault diagnosis. This paper proposes a modified classification and regression tree (CART) algorithm named D-CART algorithm to provide much faster fault classification by reducing the iteration times in computation while still ensuring accuracy. Experiments are carried on to achieve a comprehensive online fault diagnosis for rotor systems such as faults location, faults types and quantitative analysis of unbalanced mass in this paper. In comparison with the other 4 novel CART-based algorithms, the experimental results indicate that the speed of D-CART algorithm is improved by a factor of 23.92 compared to the fastest improved algorithm (Adaboost-CART) and a model accuracy of up to 96.77%. Thus demonstrating the speed superiority of D-CART algorithm in both diagnosing locations of different faults types and determining the loading masses of unbalanced faults. The proposed method has the potential to realize high-accuracy online fault diagnosis for rotor systems.

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Acknowledgements

The authors appreciate the support of the National Natural Science Foundation of China (Nos. 51575156, 51675156, 51775164, and 51705122) and the Fundamental Research Funds for the Central Universities (Nos. JZ2017HGPA0165, PA2017GDQT0024).

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Authors and Affiliations

  1. School of Instrument Science and Optoelectronics Engineering, Hefei University of Technology, Hefei, Anhui, China

    Huaxia Deng, Yifan Diao, Wei Wu, Jin Zhang, Mengchao Ma & Xiang Zhong

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  1. Huaxia Deng
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  2. Yifan Diao
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  3. Wei Wu
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  4. Jin Zhang
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  5. Mengchao Ma
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  6. Xiang Zhong
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Contributions

Huaxia Deng, Yifan Diao and Wei wu conceived the idea and conducted the experiments. All the authors including Huaxia Deng, Yifan Diao, Wei wu, Jin Zhang, Mengchao Ma and Xiang Zhong contributed to the discussion of the paper and approved the manuscript. Huaxia Deng directed the scientific research of this work.

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Correspondence to Huaxia Deng or Jin Zhang.

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Deng, H., Diao, Y., Wu, W. et al. A high-speed D-CART online fault diagnosis algorithm for rotor systems. Appl Intell 50, 29–41 (2020). https://doi.org/10.1007/s10489-019-01516-2

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  • DOI: https://doi.org/10.1007/s10489-019-01516-2

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