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基于故障区分度DAGSVM的模拟电路故障诊断
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TP277.3

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航空科学基金(201428960220)


A Novel Fault Diagnosis Approach in Analog Circuits
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    摘要:

    为了提高模拟电路故障诊断的精度,针对现有DAGSVM用于解决多类分类问题固有的不稳定性结构以及“误差累积”的特点,提出了一种基于故障区分度构建DAGSVM的新方法。根据从不同测试点获取的故障数据信息,定义故障区分度,并以此为依据优化DAGSVM的拓扑结构,从而消除DAGSVM结构固有的不稳定性,获得稳定而较高的诊断精度。实验结果表明,与现有的“1 vs 1”SVM、DAGSVM及其改进方法相比,该方法在诊断精度上有明显提高,对于模拟电路的故障诊断具有很好的借鉴意义。

    Abstract:

    In order to improve the accuracy of fault diagnosis in analog circuits, aimed at the instability structure and error transferring of the existing directed acyclic graph support vector machine (DAGSVM), a novel approach based on fault distinguish degree to construct DAGSVM is proposed. According to the fault information acquired from all of the testable points, this paper defines the concept of fault distinguish degree, and takes this as a basis to optimize the topology of the DAGSVM to eliminate the inherent instability of DAGSVM structure. For this reason, there is a stable and quite good accuracy of diagnosis. The experimental results show that this method improves obviously diagnosis accuracy compared with "1 vs 1",SVM, and traditional DAGSVM, and simultaneously the method can be used for reference in analog circuit fault diagnosis.

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孙贤明,樊晓光,禚真福,黄雷,陈少华.基于故障区分度DAGSVM的模拟电路故障诊断[J].空军工程大学学报,2016,17(4):64-69

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  • 在线发布日期: 2016-07-30
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