Artificial Intelligence Methods for Improving Mechanical Fault Monitoring and Maintenance
In the era of Industry 4.0,traditional maintenance methods are difficult to meet the efficient and accurate requirements of mechanical fault monitoring.This study focuses on predictive maintenance(PdM)and utilizes industrial Internet of Things(IIoT)technology to automatically collect data,constructs an artificial neural network(ANN)model,analyzes the S-shaped activation function,and evaluates performance using mean square error(MSE)and other metrics.Data imbalance is analyzed combined with expert knowledge.The experiment shows that the ANN model has an accuracy of 87%,improving maintenance efficiency and accuracy.The PdM strategy has significant advantages,providing efficient and low-cost maintenance solutions for the manufacturing industry,laying a scientific evaluation foundation.And it is expected to promote progress in the field of mechanical fault monitoring and maintenance.
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