Open Access
ARTICLE
Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-Speed Wire Rod Finishing Mills
Cunsong Wang1, Ningze Tang1, Quanling Zhang1,*, Lixin Gao2, Haichen Yin3, Hao Peng4
1 Institute of Intelligent Manufacturing, Nanjing Tech University, Nanjing, 210009, China
2 Beijing Gaohuahan Intelligent Technology Co., Ltd., Beijing, 100084, China
3 Beijing Wavelet Rhythm Technology Co., Ltd., Beijing, 100020, China
4 College of Mechanical and Power Engineering, Nanjing Tech University, Nanjing, 211816, China
* Corresponding Author: Quanling Zhang. Email:
(This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
Computer Modeling in Engineering & Sciences 2024, 138(2), 1827-1847. https://doi.org/10.32604/cmes.2023.030970
Received 06 May 2023; Accepted 29 June 2023; Issue published 17 November 2023
Abstract
The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise. As complex system-level equipment, it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring. To solve the above problems, an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper. First, based on its mechanical structure, time and frequency domain analysis are improved in fault feature extraction. The approach of combining virtual value, peak value with kurtosis value index, is adopted in time domain analysis. Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband. Then, according to time and frequency domain characteristics, fault location based on expert experience is proposed to get an accurate fault result. Finally, the proposed method is implemented in the equipment intelligent diagnosis system. By taking an equipment fault on site, for example, the effectiveness of the proposed method is illustrated in the system.
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Cite This Article
APA Style
Wang, C., Tang, N., Zhang, Q., Gao, L., Yin, H. et al. (2024). Expert experience and data-driven based hybrid fault diagnosis for high-speed wire rod finishing mills. Computer Modeling in Engineering & Sciences, 138(2), 1827-1847. https://doi.org/10.32604/cmes.2023.030970
Vancouver Style
Wang C, Tang N, Zhang Q, Gao L, Yin H, Peng H. Expert experience and data-driven based hybrid fault diagnosis for high-speed wire rod finishing mills. Comput Model Eng Sci. 2024;138(2):1827-1847 https://doi.org/10.32604/cmes.2023.030970
IEEE Style
C. Wang, N. Tang, Q. Zhang, L. Gao, H. Yin, and H. Peng "Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-Speed Wire Rod Finishing Mills," Comput. Model. Eng. Sci., vol. 138, no. 2, pp. 1827-1847. 2024. https://doi.org/10.32604/cmes.2023.030970