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智能诊断是当前故障诊断领域的一个重要发展方向。智能诊断发展的瓶颈是知识获取。近年来,数据挖掘技术作为知识获取强有力的工具日渐发展起来。它综合运用人工智能、模式识别、数理统计等先进技术,从大量数据中挖掘和发现有价值和隐含的知识。本文在分析故障诊断专家系统存在问题的基础上,结合数据挖掘技术,提出了基于数据挖掘的故障诊断模型框架DMFD,并给出了具体实现技术。最后,指出了机械设备故障诊断中数据挖掘技术的应用和发展方向。
Intelligent diagnosis is an important development direction in the field of fault diagnosis. The bottleneck of the development of intelligent diagnosis is knowledge acquisition. In recent years, data mining technology is increasingly developed as a powerful tool for knowledge acquisition. It integrates advanced technologies such as artificial intelligence, pattern recognition and mathematical statistics to discover valuable and implicit knowledge from a large amount of data. Based on the analysis of the existing problems of fault diagnosis expert system, combined with data mining technology, this paper proposes DMFD, a fault diagnosis model framework based on data mining, and gives the concrete realization technology. Finally, the application and development of data mining technology in the fault diagnosis of mechanical equipment are pointed out.