Design of Mechanical Automation Control System Based on Artiicial Intelligence

Aiming at the problems of poor adaptability and insufficient fault prediction of traditional mechanical automation control systems in complex working conditions, a mechanical automation control system based on artificial intelligence is designed. This design integrates expert control, fuzzy control, and neural network control technologies, and builds a hierarchical distributed architecture. Fault warning adopts threshold judgment and dynamic time warping pattern recognition technologies, and state monitoring realizes accurate analysis through multi-source data fusion and Kalman filtering algorithm. Practical applications show that this system can reduce the equipment failure rate by more than 30%. With the help of intelligent scheduling optimization, it can significantly improve production efficiency and reduce energy consumption, providing a reliable technical solution and practical path for the intelligent upgrade of the mechanical automation field.