基于最小割集的光学测云系统故障诊断

Fault pattern analysis of optic droplets detection systems based on minimal cut sets

针对光学地面测云系统投入使用时间较短,现场数据较少,无法及时诊断故障等问题,应用Petri网络的矩阵算法求得该系统故障树的最小割集和最小路集,并结合结构重要度系数,提出了基于最小割集的故障树诊断方法.经实例分析表明,该方法缩短了故障诊断时间,提高了设备的维修效率.

Aming at the problem that the faults of optical ground-based droplets detection System is hard to analyse due to its short serving time and insufficient raw data. The MCS and MRS of the systematic fault tree is studied and acquired by using Petri network matrix algorithm. Based on MCS analysis and combined with structure weight factor and fault deduction method, analysis speed for systematic faults is largely increased and the repair effectiveness of new equipements is enhanced.