Failure Prediction of Circular Sawing Machines Based on Condition Evaluation and ARIMA Model

Abstract

As the starting point of cutting, sawing is an important link in the production process. Circular saws have high precision and high sawing efficiency. Once a failure occurs, it will bring considerable losses. This paper presents a fault prediction method for circular saw based on state evaluation and ARIMA model. According to the mechanism of failure analysis, considering different parameter indicators for different failures, we first find out the components of the equipment involved in these parameters, and adopt the entropy weight method and trapezoid-triangular membership function model to determine the health status. The key mechanism of the components in poor condition is predicted using the ARIMA model, and the weighted method is used to predict the failure time.