@Article{cmes.2023.030970,
AUTHOR = {Cunsong Wang, Ningze Tang, Quanling Zhang, Lixin Gao, Haichen Yin, Hao Peng},
TITLE = {Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-Speed Wire Rod Finishing Mills},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {138},
YEAR = {2024},
NUMBER = {2},
PAGES = {1827--1847},
URL = {http://www.techscience.com/CMES/v138n2/54625},
ISSN = {1526-1506},
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.},
DOI = {10.32604/cmes.2023.030970}
}