Aiming at the problems of data fluctuations and false alarms caused by defects such as wire breakage, deformation, wear, and corrosion, as well as external factors such as shaking during the monitoring process of hoist steel wire ropes, this paper constructs a comprehensive evaluation framework for safety performance. This method integrates interquartile range denoising and the entropy weight method for comprehensive evaluation, significantly improving the accuracy of defect identification and safety assessment while maintaining computational efficiency. The proposed method first addresses defects in steel wire ropes and noise interference during monitoring. By employing the interquartile range method combined with horizontal denoising techniques, abnormal data is effectively removed, thereby suppressing noise interference and enhancing data accuracy and reliability. Next, a comprehensive evaluation indicator system is constructed based on key parameters such as the number, severity, and location of defects to thoroughly assess the safety performance of steel wire ropes. Finally, the entropy weight method is introduced to objectively assign weights to each indicator, and a quantitative evaluation model for the safety performance of steel wire ropes is established. Experimental results indicate that this method demonstrates high accuracy and robustness in defect identification and safety performance evaluation. Compared to traditional single‐indicator evaluation methods, the comprehensive evaluation error is reduced by approximately 12%, making it more suitable for practical engineering applications.
Wang et al. (Thu,) studied this question.