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Fault diagnosis based on ant colony algorithms

机译:基于蚁群算法的故障诊断

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For concluding the difficulty of classing fault sign of equipment automatically in fault diagnosis, this paper presents a new excellent clustering algorithm based on Ant Colony Algorithms (ACA). It is discovered the diagnosis earlier, it is classified fault sign of equipment automatically, and obtain diagnosis knowledge, conclude diagnosis rule, find the reason of fault. All these are in favor of fast, automatic and exact decision-making and dealing with the fault. ACA is applied in the fault diagnosis and recognition, and does pattern recognition for a chemical reactor. Result and the actual operation state are consistent. That can reflect the algorithm accuracy.
机译:对于在故障诊断中自动占用设备的故障标志的难度结论,本文介绍了一种基于蚁群算法(ACA)的新型优秀聚类算法。它被发现前面的诊断,它是自动的分类故障标志,并获得诊断知识,结束诊断规则,找到了错误的原因。所有这些都赞成快速,自动和精确的决策和处理故障。 ACA应用于故障诊断和识别,并对化学反应器进行模式识别。结果和实际操作状态是一致的。这可以反映算法精度。

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