摘要
将传统意义上测点的概念推广为电路中能够携带故障信息的任何可测量变量。用香农信息熵对在一定测点上测量前后电路故障状态的不确定性进行了定量描述,在此基础上提出了测点集合诊断信息量的概念并给出了其估计方法。将测点选择问题建模为在全体可达测点集合中选取具有最大诊断信息量的测点子集问题,用遗传算法对最优子集进行搜索。讨论了遗传算法中染色体的编码方式、适应度函数的选择以及遗传算子的设计方法。将本文提出的方法用于一个线性模拟电路的测点选择中,实验结果表明,所获得的测点子集能充分反映电路的故障状态信息。
The conventional concept of test point is replaced by a more extensive one which means any testable variable of the analog circuit carrying fault information. The pre - and post - test unceaainty of the circuit fault state is described by Shannon entropy. Based on this description the concept of diagnostic information of test point set is proposed and the method for its estimation is given. The problem of test point selection is modeled as searching for the test point subset with the maximum diagnostic information in the set of all accessible test points of the circuit. Genetic algorithm is used for the optimal subset searching and the strategy for chromosome coding, the choice of fitness function and genetic operator is discussed. The proposed method is used for test point selection of a linear analog circuit and satisfying results have been achieved.
出处
《电子测量与仪器学报》
CSCD
2005年第5期1-5,共5页
Journal of Electronic Measurement and Instrumentation
关键词
测点集合
诊断信息量
遗传算法
test points set
diagnostic information
genetic algorithm
