基于免疫粒子群文化算法的数字电路故障诊断

为改善粒子群算法摆脱局部极值点的能力,提升种群进化的多样性,将免疫算法中免疫机制引入到粒子群算法中形成免疫粒子群算法;为有效提高故障覆盖率和缩短测试生成时间,将免疫粒子群算法引入文化算法框架中形成免疫粒子群的文化算法。将其应用于数字电路故障模型仿真实验并与其他测试生成算法进行对比,结果表明该算法能够有效提高故障覆盖率,缩短测试生成时间,在大规模电路测试生成与故障诊断中更具优势。

Test Pattern Generation for Digital Integrated Circuits Based on CA-IA-PSO Algorithm

In order to improve the ability to get rid of partial extreme spot and the diversity in evolution,IA algorithm is imported into PSO algorithm to form IA-PSO algorithm. For the purpose of raising fault rate and shortening test pattern generation time,CA algorithm into is imported IA-PSO algorithm to form CA-IA-PSO algorithm. Finally, single stuck-at fault is adopted and different algorithms is used to the simulation experiment of test pattern generation,the result is that CA-IA-PSO algorithm can solve the problem of test pattern generation more practically and efficiently, especially in large digital circuits.