基于改进离散粒子群算法的传感器布局优化设计

Optimal Sensor Placement Design Based on Improved Discrete PSO Algorithm

传感器布局优化是复杂系统测试性设计的重要内容,属于典型的组合优化问题.通过改进系统的故障-传感器相关性矩阵,建立了考虑传感器故障检测能力的约束优化模型.利用混沌的遍历性初始化粒子群的参数,惯性权重则根据粒子群的早熟收敛程度自适应调整,并对粒子的位置更新方式进行了重新定义,用改进后的离散粒子群算法求解建立的优化模型.仿真实例验证了本文方法的有效性,优化结果能满足系统的各项指标要求。

Optimal sensor placement is important content of testability design for complicated systems, which belongs to the typical combinatorial optimization problem. Based on the improvement of the fault-sensor correlation matrix, the constraint optimiza- tion model is set up which considers the fault detection abilities of the sensors. The ergodic of chaos has been used to initialize the parameters of the particles,and the inertia weight is adjusted adaptively according to the swarm＇ s premature convergence degree. Besides,the update of the particle＇s position has been redefmed, then the improved discrete PSO algorithm is used to solve the opti- mization model. The simulation examples demonstrate that the proposed method is effective, and the optimization results can satisfy all the requests of the system, and it is a feasible approach for opfin~ sensor placement for complicated systems.