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Fault Diagnosis Of Turbine Based On Fuzzy Cross Entropy Of Vague Sets

机译:基于Vague集模糊交叉熵的汽轮机故障诊断。

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摘要

The fuzzy cross entropy of vague sets, so-called vague cross entropy, is introduced by analogy with the cross entropy of probability distributions. And then a new method of the fault diagnosis is proposed on the basis of the vague cross entropy and is applied to the fault diagnosis of turbine. The vague cross entropy between a testing sample and the knowledge of system faults is evaluated in the fault diagnosis of the turbine vibration. If the cross-entropy value is small, the testing sample is near to a type of fault knowledge. Then, the type of vibration fault is determined according to the minimum cross-entropy value. The fault-diagnosis example of the turbine demonstrates that the proposed method cannot only diagnose the main fault types of the turbine, it can also detect useful information for future trends and multi-fault analysis.
机译:Vague集的模糊交叉熵,即所谓的Vague交叉熵,是通过与概率分布的交叉熵进行类比引入的。在此基础上,提出了一种基于模糊交叉熵的故障诊断方法,并将其应用于汽轮机故障诊断中。在涡轮振动的故障诊断中,评估了测试样本与系统故障知识之间的模糊交叉熵。如果交叉熵值很小,则测试样本接近于一种故障知识。然后,根据最小交叉熵值确定振动故障的类型。涡轮机的故障诊断实例表明,该方法不仅可以诊断涡轮机的主要故障类型,还可以检测出有用的信息,以备将来趋势和多故障分析之用。

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