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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Intelligent fault diagnosis using rough set method and evidence theory for NC machine tools
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Intelligent fault diagnosis using rough set method and evidence theory for NC machine tools

机译：基于粗糙集和证据理论的数控机床故障智能诊断

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摘要

An intelligent fault diagnostic method was presented to satisfy the development requirements of next-generation intelligent NC machine tools. The framework of fault diagnosis unit was established first, which consisted of signal acquisition, diagnosis rule extraction and fault identification mechanism. The technique of diagnosis rule extraction was then studied and an algorithm for acquisition of decision rules was proposed. The algorithm simplified the analysis of core properties and unnecessary properties, and calculated reduction set by the backwards tracking approach. This algorithm reduced complexity in reductions calculation and improved the efficiency of rule extraction. Finally, to process failure data collected by various sensors, a fault identification mechanism using evidence theory was presented. Feasibility and practicability of the proposed method has been verified by the development and the preliminary application of a prototype system.
机译：提出了一种智能故障诊断方法，以满足下一代智能数控机床的发展需求。首先建立了故障诊断单元的框架，该框架由信号采集，诊断规则提取和故障识别机制组成。研究了诊断规则提取技术，提出了决策规则获取算法。该算法简化了核心属性和不必要属性的分析，并通过向后跟踪方法计算了减少量集。该算法减少了归约计算的复杂度，并提高了规则提取的效率。最后，为了处理各种传感器收集的故障数据，提出了一种基于证据理论的故障识别机制。原型系统的开发和初步应用验证了该方法的可行性和实用性。

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