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容差条件下PSO算法诊断模拟电路单软故障方法

PSO Method for Diagnosis of Single Soft Fault in Analog Circuit with Tolerance

  • 摘要: 为了定量地诊断模拟电路中的单个软故障,提出一种容差条件下基于微粒群优化理论的诊断方法.首先通过灵敏度分析建立电路测试节点电压增量方程,以及模拟电路故障诊断的约束线性规划方程组;然后引入罚函数,把微粒群算法应用到方程的求解中;最后估计出电路各元件参数的最小变化量,并与各元件容差范围相比较来定位故障元件.仿真实验结果表明,该方法兼顾故障元件的定位和故障元件参数变化量的估计,可以有效地实现模拟电路在容差条件下的软故障定量诊断.

     

    Abstract: In order to diagnose the single soft fault in analog circuit quantitatively,a method based on particle swarm optimization (PSO) for analog circuit with parameter tolerance is proposed. Firstly,node-voltage incremental equations based on the sensitivity analysis are built as constraints of linear programming (LP) equation. Then,through inducing the penalty function,the theory of PSO is introduced into the solution of the LP equation. In the end,after evaluating the parameters deviations,it enables us to state whether the actual parameters are within tolerance ranges or someone is faulty. Simulation results on examples illustrated that the proposed method can locate the faulty element and present its parameter deviation. The simulation results also show the effectiveness of the method in soft-fault diagnosis with tolerance in analog circuit.

     

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