基于改进粒子群算法的模拟电路测试点选择

Test point selection of analog circuits using enhanced particle swarm optimization algorithm

针对模拟电路测试点选择的特点,对粒子群算法进行改进,提出利用粒子群算法与整数编码故障字典相结合的方法进行测试点选择,给出了该算法的模型和应用于模拟电路测试点选择的一般规律.首先根据各测试点的数据建立整数编码故障字典,然后利用改进的粒子群算法选取最优测试点.将该方法应用于实际模拟滤波器的测试点选择,并通过统计实验的方法与已有的测试点选择方法进行比较,结果表明:利用该方法很容易求出模拟电路的全局最优测试点,且需要设置的参数较少.

A method based on particle swarm optimization algorithm and integer-coded fault dictionary was proposed for selecting the optimum test points of analog circuits. The traditional particle swarm optimization algorithm was updated. The basic model was given and the general rule to use this method to select the optimum test points of analog circuits was described in detail. Firstly, the integer-coded fault dictionary was constructed based on the original data of test points. Then, the enhanced particle swarm optimization algorithm was used to find the optimum test points. The proposed method was used to select the test points of an analog filter and compared with other methods by statistical experiments. The results show that this method is easy to find the global optimum test points and few parameters need to be set.