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基于Bandler（1982）故障诊断L1范数法，提出模拟电路故障诊断的遗传优化技术，采用直接对网络节点电压增量直接编码的方法，避免了因将连续量，人为转化为离散量而引起的编码误差；为保证算法的全局收敛特性，本文的选择算子采用了最佳个体保留方法（ElitistModel）；在交叉和变异操作中引入自适应策略后，改善了算法的局部寻优能力和程序的收敛时间。实例仿真表明本文算法能够快速准确地将模拟电路故障定位到元件级。
Based on Bandler (1982) fault diagnosis L1 norm method, a genetic optimization technique for fault diagnosis of analog circuits is proposed. By directly encoding the network node voltage increment directly, this method avoids the problem that the continuous quantities are converted into discrete quantities In order to ensure the global convergence of the algorithm, the selection operator in this paper adopts the best individual retention method (ElitistModel). After the adaptive strategy is introduced in the crossover and mutation operations, the algorithm improves the local optimization ability and the process of Convergence time. Simulation results show that our algorithm can quickly and accurately locate the analog circuit fault to the component level.