模拟万用表逻辑电平测量电路故障维修仿真

摘要

A fault diagnosis method of analog multimeter logic level measurement circuit based on VRC technology is proposed.Based on the tolerance effect,the threshold function and criterion of the circuit fault are established.After the measurement of voltage and circuit gain of the measuring point is judged,the neural network feature layer is fused and the neural network algorithm is used to locate the fault characteristic data of the circuit.Based on the results of fault location and VRC simulation,a circuit model that can be used for fault maintenance is simulated.The genetic algorithm is used to generate the individual fitness function of the circuit model to reconfigure the VRC to avoid the logic gate of the fault and realize the self-repair of the fault.The simulation results show that the proposed method can improve the fault location accuracy of the circuit to more than 96％,and can repair more types of faults,shortening the circuit simulation time and meeting the design requirements of the fault maintenance of the analog multimeter logic level measurement circuit.%现行基于仿生自修复技术的电路故障维修方法以设计的逻辑单元自行发现故障、维修故障,故障维修方式简单,故障维修类型有限,导致故障定位及维修能力受到了很大程度上的限制.提出一种基于VRC技术的模拟万用表逻辑电平测量电路故障维修方法.在考虑容差效应的基础上,建立电路故障阈值函数及判据,对测量点电压与电路增益两种测量数据判决后,经神经网络特征层融合,运用神经网络算法对电路故障特征数据定位,以故障定位结果为基础,结合VRC技术模拟可用于故障维修的电路模型,采用遗传算法生成电路模型的个体适应度函数对VRC重配置,可避开电路故障逻辑门,实现电路故障的自修复.实验结果表明,所提方法可将电路故障定位精度提高到96％以上,且可维修的故障类型较多,缩短了电路模拟时间,满足模拟万用表逻辑电平测量电路故障维修的设计需求.