A Novel Approach for Analog Circuit Fault Prognostics Based on Improved RVM

A Novel Approach for Analog Circuit Fault Prognostics Based on Improved RVM
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基于改进RVM的模拟电路故障预测新方法

DOI:
10.1007/s10836-014-5454-8
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发表时间:
2014-06
影响因子:
0.9
通讯作者:
邓芳明
邓芳明
中科院分区:
工程技术4区
文献类型:
--
作者:
张朝龙;何怡刚;袁莉芬;邓芳明

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为了实时准确地估计模拟电路的剩余有用性能(RUP),提出了一种模拟电路故障预测框架。从电路响应中提取输出电压作为特征,计算出能够反映模拟电路健康状况的余弦距离。采用粒子群算法改进的相关向量机(RVM)对RUP进行估计。通过对带通滤波器、高通滤波器和非线性电路等12个实例的研究,验证了该方法的预测性能。仿真结果表明,该方法具有较高的预测精度。
In order to estimate the remaining useful performance (RUP) of analog circuits precisely in real time, an analog circuit fault prognostics framework is proposed in the paper. Output voltages are extracted from circuit responses as features to calculate cosine distance which can reflect the health condition of analog circuits. Relevance vector machine (RVM) which has been improved by particle swarm optimization (PSO) algorithm is applied to estimate the RUP. Twelve case studies involving bandpass filter, highpass filter and nonlinear circuit have validated the predict performance of the approach. Simulation results demonstrate that the proposed approach has higher prediction precision.
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