小卫星多级故障诊断系统设计

提出一种基于模糊神经网络的小卫星多级故障诊断系统,利用多级的方式对小卫星的故障进行诊断。其中第一级采用模糊聚类的方法,将故障定位于模块级;第二级采用模糊径向基神经网络,完成故障的部件级定位。最后用该故障诊断方法针对卫星故障仿真系统做了实验,对其预设故障进行了诊断,诊断结果与仿真系统预设故障完全一致。实验表明:多级故障诊断结构提高了故障诊断的系统性、准确性并大大降低了故障诊断中的计算量。

Multi-Grade Faulty Diagnosis Design of Small Satellite

A faulty diagnosis system based on multi-grade fuzzy neural network was presented which uses a multi-grade method to diagnose the fault of small satellite.In this multi-grade diagnosis a fuzzy clustering method was used in the first grade to estimate which module works abnormally.In the second grade fuzzy radial basis function neural network(RBFNN) was used to confirm which component or part was error.At last an experiment was done with this faulty diagnosis method according to a small satellite faulty simulation system .An experiment was done with this faulty diagnosis method according to a small satellite faulty simulation system at last.The result of the diagnosis shows no difference with the fault set beforehand in the simulation system.The result indicates that in a small satellite faulty diagnosis system,this multi-grade method can improve the integration and accuracy of the system,and greatly reduce the complexity of calculation in the process of the diagnosis.