人工智能在机械状态监测与故障诊断中的应用

Y. Ali
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引用次数: 17

摘要

机器状态监测和故障诊断作为系统维护的一部分,由于可以从减少维护预算、提高生产率和改善机器可用性中获得潜在的好处,因此受到了广泛的关注。人工智能(AI)是机器状态监测和故障诊断的成功方法,因为这些技术被用作日常维护的工具。本章试图总结和回顾人工智能信号分析在机械状态监测和故障诊断领域的最新研究进展。人工神经网络(ANN)、模糊逻辑系统(FLS)、遗传算法(GA)和支持向量机(SVM)等智能系统此前已经开发了许多不同的方法。然而,利用声发射(AE)信号分析和人工智能技术进行机器状态监测和故障诊断仍然很少。在未来,由于文献的空白,人工智能在机器状态监测和故障诊断方面的应用还需要更多的鼓励和关注。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence Application in Machine Condition Monitoring and Fault Diagnosis
The subject of machine condition monitoring and fault diagnosis as a part of system maintenance has gained a lot of interest due to the potential benefits to be learned from reduced maintenance budgets, enhanced productivity and improved machine availabil- ity. Artificial intelligence (AI) is a successful method of machine condition monitoring and fault diagnosis since these techniques are used as tools for routine maintenance. This chapter attempts to summarize and review the recent research and developments in the field of signal analysis through artificial intelligence in machine condition monitoring and fault diagnosis. Intelligent systems such as artificial neural network (ANN), fuzzy logic system (FLS), genetic algorithms (GA) and support vector machine (SVM) have pre - viously developed many different methods. However, the use of acoustic emission (AE) signal analysis and AI techniques for machine condition monitoring and fault diagnosis is still rare. In the future, the applications of AI in machine condition monitoring and fault diagnosis still need more encouragement and attention due to the gap in the literature.
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