满足故障隔离率指标的测试序列优化差分进化算法
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Sequential Fault Diagnosis with Isolation Rate Requirement Using Differential Evolution Algorithm
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    摘要:

    最优测试序列的设计是故障诊断过程中必须解决的非确定多项式(Non-deterministic polynomial,NP)完全问题。基于自适应差分进化算法,提出一种惯性速度差分进化(Inertial velocity differential evolution,IVDE)算法,通过增加额外的惯性速度项求解复杂电子系统最优测试序列问题(Optimal test sequence problem,OTP)。为求解该优化问题设计了个体的状态与测试序列编码方式,构建了包含故障隔离率(Fault isolation rate,FIR)等指标的个体适应度函数,通过优化生成诊断决策树来减少测试设备和测试成本。仿真结果表明,IVDE算法可以求得既满足FIR要求,又减少测试成本的测试序列。与粒子群优化算法(Particle swarm optimizer,PSO)、遗传算法(Genetic algorithm,GA)等其他算法相比,IVDE可以求解OTP,得到更好的解。

    Abstract:

    The optimal test sequence design for fault diagnosis is critical to NP-complete problem. An improved differential evolution (DE) algorithm with additional inertial velocity item is proposed to solve the optimal test sequence problem (OTP) in complicated electronic system. The proposed inertial velocity differential evolution (IVDE) algorithm is constructed based on adaptive differential evolution algorithm. IVDE, combined with a new individual fitness function, optimizes the test sequence sets with the index fault isolation rate(FIR)satisfied in top-down to generate diagnostic decision tree and decrease the test sets and the cost test. Simulation results show that IVDE algorithm can cut down the test cost with the satisfied FIR. Compared with the other algorithm such as particle swarm optimizer(PSO)and genetic algorithm(GA), IVDE can get better solution to OTP.

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邱晓红 李渤 李靖.满足故障隔离率指标的测试序列优化差分进化算法[J].数据采集与处理,2016,31(6):1132-1140

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  • 在线发布日期: 2018-04-09