摘要
针对舰员对装备维修能力不足的情况,论文提出了一种能够应用于便携式故障诊断仪中的故障树诊断算法。首先通过对混沌自适应粒子群算法的参数选择进行优化,使粒子能够在全局范围内进行搜索,克服了其易陷入局部最优的缺点,其次将其应用于故障树诊断算法中,并通过仿真试验证明了该方法的有效性。
Aiming at the lack of maintenance ability of warship crews, a fault tree diagnosis algorithm(TFA) is presen- ted which is used in portable fault diagnosis instrument. First, the paramelers of chaos adaptive particle swarm optimization (PSO) algorithm are optimized, so the particles can search the optimal solution in whole situation, which overcomes the drawback of easy to fall into local optimum. Secondly, the PSO is used in to TFA, and a simulation test shows the effective ness of this method.
出处
《计算机与数字工程》
2014年第3期407-411,共5页
Computer & Digital Engineering
关键词
便携式故障诊断仪
故障树诊断
混沌自适应粒子群算法
参数优化
portable fault diagnosis instrument, fault tree diagnosis algorithm, chaos adaptive particle swarm optimi-zation algorithm, parameter optimization