Prediction of the Service Life and Wear of Electric Hoist Wheels using the GM (1,1) Grey Model

Abstract

As one of the core components of electric hoists, the wheels of the traveling mechanism directly affect the working efficiency and operational safety of the equipment through their wear degree. To address the need for accurate service life assessment of the wheels in the electric hoist traveling mechanism, this study aims to predict the wheel wear amount and remaining service life. Based on the collected wheel wear life test data, the grey GM (1,1) prediction model was adopted for modeling and life prediction. The results show that the model has high prediction accuracy: the average relative error between the predicted values and actual values is 2.03%, with a maximum relative error of 3.08%. This provides a feasible method for the wear amount prediction and life analysis of the electric hoist traveling mechanism wheels during actual operation. This method is applicable to standard operating conditions with limited sample data in the early stage of equipment operation. It does not consider complex operating conditions and the coupling effect of multiple factors, and further optimization is required for relevant scenarios.

Affiliated Institutions

• PowerChina (China) CN
• Shandong Special Equipment Inspection Institute CN
• North China University of Water Resources and Electric Power CN

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