基于改进离散粒子群算法优化故障等级的传感器布局

Optimized Sensor Layout Considering Fault Level Based on Improved Discrete Particle Swarm Algorithm

文章提出一种基于改进离散粒子群算法优化故障等级的传感器布局方法用于解决传感器检测故障的布局问题,通过故障模式影响和危害性分析得到系统的故障模式,对系统故障模式进行故障等级划分;然后依据故障等级漏检率构造约束条件,传感器成本构造适应度函数;并构造出非线性优化学习因子的动态调整策略;利用改进的离散粒子群算法求解故障漏检率约束条件下适应度函数最优的传感器布局离散序列,仿真实验表明应用文章方法布局具有在满足不同故障等级的漏检率条件下的成本低优越性。

A sensor layout method based on improved discrete particle swarm algorithm to optimize the fault level is proposed to solve the layout problem of sensor detection faults.The system failure mode is obtained through failure mode impact and criticality analysis,and the system failure mode is divided into fault levels.Then constraint conditions are constructed based on the failure rate missed detection rate,the fitness function is constructed for the sensor cost.A dynamic adjustment strategy is constructed for nonlin-ear optimization learning factors.The improved discrete particle swarm algorithm is used to solve the optimal fitness function under the constraint condition of the fault missed detection rate.The simulation experiment shows the superiority of the application of this paper to get a lower cost with satisfaction of different fault level.