人工智能背景下机电一体化设备的故障诊断技术优化

Optimization of Fault Diagnosis Technology for Mechatronics Equipment under the Background of Artificial Intelligence

随着工业的自动化与智能化,机电一体化设备复杂性提高,故障诊断难度增加。本文回顾机电一体化故障诊断技术的现状后,从数据处理、系统动态性、新型故障模式识别、整合实施进行分析,重点讨论了人工智能,尤其是机器学习和深度学习在优化故障诊断中的应用,包括数据驱动的诊断方法、预测性维护和算法的实施挑战。通过案例展示人工智能在实际故障诊断中的应用效果和价值。最后,展望该技术的发展,强调智能化和自动化的重要性。

With the development of industrial automation and intelligence,mechatronics equipment becomes more and more complex,which increases the difficulty of fault diagnosis.This paper reviews the development status of fault diagnosis technology,and then analyzes data processing,system dynamics,new fault pattern recognition and combined implementation.The discussion focused on the application of artificial intelligence,especially machine learning and deep learning,to optimized fault diagnosis,including data-driven diagnostic methods,predictive maintenance,and implementation challenges of algorithms.Through a specific case study,the application effect and value of artificial intelligence in practical fault diagnosis are demonstrated.Finally,looking to its future and emphasizing the importance of intelligence and automation.