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首页> 外文会议>2014 International Conference on Mechatronics and Control >Fault diagnosis based semi-supervised global LSSVM for analog circuit
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Fault diagnosis based semi-supervised global LSSVM for analog circuit

机译：基于故障诊断的半监督全局LSSVM模拟电路

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摘要

Focusing on the issue of fault diagnosis method in existing analog circuit, the nonlinear of circuit and the global and local underlying information of fault should be considered simultaneously. Global and local preserving of fault information is proposed for semi-unsupervised learning algorithms of analog circuit faults diagnosis, the within-class scatter of linear discriminant analysis (LDA) combines the locality preserving projections (LPP) to fully consider the global and local geometric structure between samples and make the method in succession on the basis of the characteristics of the traditional SVM methods in this paper. Experiment takes the pass filter as the diagnosis circle to prove that proposed method in this paper can highly recognize the known and unknown faults comparing with fault diagnosis method based on common SVM.
机译：针对现有模拟电路的故障诊断方法问题，应同时考虑电路的非线性以及故障的全局和局部基础信息。针对模拟电路故障诊断的半无监督学习算法，提出了故障信息的全局和局部保存，线性判别分析（LDA）的类内散布结合了局部保存预测（LPP）以充分考虑全局和局部几何结构本文根据传统支持向量机方法的特点，在样本之间进行选择，并陆续提出方法。实验以通过滤波器为诊断圆，证明了与基于通用支持向量机的故障诊断方法相比，本文提出的方法能够较好地识别已知和未知故障。

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