Research on Dynamic Performance Prediction Model Using Intelligent Algorithm in Mechanical Principle

The purpose of this study is to explore the application of intelligent algorithms in the dynamic performance prediction model of mechanical principles. With the complexity of mechanical engineering and the increasing pursuit of efficient performance, traditional performance prediction methods have been difficult to meet the needs of modern engineering. In this paper, the key factors affecting the dynamic performance of mechanical systems are analyzed first, and then a variety of intelligent algorithms (including genetic algorithm, particle swarm optimization algorithm and deep learning model) are used to mine and analyze the performance data. By constructing a dynamic performance prediction model and using real data set to verify, the results show that the intelligent algorithm significantly improves the prediction accuracy and computational efficiency. Finally, the potential application of this research in mechanical design optimization and fault diagnosis is discussed in order to provide theoretical support and practical guidance for the intelligent development of mechanical systems.