运载火箭故障检测序列优化

摘要

An algorithm based on discrete particle swarm optimization (DPSO) is proposed in this paper for the optimal test-sequencing for the fault detection of a launch vehicle.This algorithm optimizes the original test set first to obtain the optimal test set,and then optimizes the test sequence based on the optimal test set.A timing sequencing control system is taken as an example for modeling.The result shows that this algorithm not only reduces the quantity of the test sets and the test cost,but also performs much better than the genetic algorithm (GA) in the optimization results and computational efficiency.%针对运载火箭故障检测序列优化这一新问题,建立数学模型并提出基于离散粒子群算法的故障检测序列优化方法.该算法通过测试集优化获得优选测试集,再通过检测序列优化对优选测试集中测试进行排序,获得优化的故障检测序列.最后以运载火箭时序控制系统为对象进行了验证,结果证明,基于离散粒子群算法的故障检测序列优化方法能够在保证故障状态全覆盖的前提下减少测试数量及成本,大大提高测试效率,且相较于遗传算法具有更好的优化性能和计算效率,适用于运载火箭故障检测序列优化.