摘要
模拟电路随工作时长的增加,其健康状态也在不断下降。及时对早期故障状态的元件进行参数估计,可以准确地评估设备健康状态,为故障预测提供参考。基于被测电路的传递函数和实测的故障响应,可反推出可能的故障参数。由于容差的影响,有很多参数组合可以产生相同的故障响应。本文通过数学分析,将故障参数估计问题转化为多目标优化问题,并针对优化目标量级相差巨大、难以合理生成权重向量进行环境选择等问题,提出基于对数分布参考点来指导种群进化,并提出了一种基于对数分布参考点的分解多目标进化算法,该.法能够准确且稳定地找到故障参数估计问题的最优解,通过仿真跳藕滤波电路,验证了随容差的增.,参数范围越来越宽,且所有标准偏差最大仅18.616Ω,在时间效率上,具有3种不同容差的12个故障实例的运行时间没有显著差异,平均运行时间为0.7 s,和实际电路实验证明了该算法的正确性和鲁棒性,并通过对比该方向前沿研究的其他多种算法,验证了本文的方法在精度上优于双目标进化算法2~3个数量级,对比Tadeusiewicz提出的方法具有更宽的故障区间等,验证了本文的方法具备更高的准确性和有效性,体现了本文方法的优越可靠。
With the increase of working time,the health status of analog circuit declines.The faulty parameter estimation in early fault state can accurately evaluate equipment health state and provide reference for fault prediction.Based on the transfer function of the circuit and the measured fault response,the possible fault parameters can be inversely derived.Due to the influence of tolerance,the same fault response can be generated by many parameter combinations.This article transforms the fault parameter estimation problem into a multi-objective optimization problem through mathematical analysis.In view of the problems of the huge difference in the optimization objective scale and the difficulty in generating a reasonable weight vector,it proposes to guide the population evolution based on the logarithmic distribution reference point and proposes a logarithmic distribution reference point-based decomposition multi-objective evolution algorithm.This method can accurately and stably find the optimal solution of the fault parameter estimation problem.Through simulation of the jump filter circuit,it is verified that as the tolerance increases,the parameter range becomes wider,and the maximum standard deviation is only 18.616Ω.In terms of time efficiency,there is no significant difference in the running time of 12 fault instances with three different tolerances,and the average running time is 0.7 s.The correctness and robustness of the algorithm are verified by experiments,and compared with other multi-objective evolution algorithms in the forefront of this direction,the method proposed in this article is more accurate than the bi-objective evolution algorithm by 2~3 orders of magnitude in terms of accuracy,and has a wider fault interval than the method proposed by Tadeusiewicz,which verifies the higher accuracy and effectiveness of the method proposed in this article,reflecting the superiority and reliability of the method proposed in this article.
作者
杨成林
张棋皓
王浩
Yang Chenglin;Zhang Qihao;Wang Hao(University of Electronic Science and Technology of China,Chengdu 611731,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2023年第2期119-128,共10页
Chinese Journal of Scientific Instrument
基金
国家自然基金(61871100)
中央高效基本业务费(ZYGX2020J012)项目资助
关键词
参数估计
容差
参考点
LDRP
多目标优化
parameter estimation
tolerance
LDRP
reference points
multi-objective optimization
作者简介
杨成林,2011年于电子科技大学获得博士学位,现为电子科技大学副教授,主要研究方向为模拟电路测试性设计,故障诊断,多目标优化智能算法。E-mail:yangclin@uestc.edu.cn;通信作者:张棋皓,2021年于江苏科技大学获得学士学位,现就读于电子科技大学攻读硕士学位,研究方向为大型集成电路和芯片的故障诊断。E-mail:693731052@qq.com;王浩,2020年于河北工业大学获得学士学位,现于电子科技大学攻读硕士学位,现研究方向为故障诊断。E-mail:935570133@qq.com
