摘要
故障预测对制定雷达精确维修保障计划,降低维修保障费用,提高战备完好率和任务成功率以及避免因故障造成巨大损失等方面具有重大意义。针对现代雷达装备系统组成复杂、结构关系模糊、特征参数获取不完整和不确定,造成故障预测实现困难的问题,采用灰色预测理论,从优化背景值构造和提高模型的预测精度出发,采用背景值加权和新陈代谢思想相结合的方式,提出一种多因素的新陈代谢不等时距加权灰色预测模型(MUGM(1,m,w)),并通过雷达故障预测实例仿真及比较分析,检验了模型的有效性。
Radar fault prediction is very important to establish accurate maintenance support plan,reduce maintenance support cost,improve operational readiness probability and mission readiness probability,even avoid the huge loss by radar fault;In order to overcome the difficulty of modern radar fault prediction,which induced by the complexity of system compose,fuzziness of configuration connection and incompletely and uncertainty of character parameters,a new multi-variables metabolism unequal interval weight grey model（MUGM（1,m,w）） was advanced by combining the background value weight and metabolism idea.The result of simulating a practical radar fault forecast and comparatively analyzing the models,shown that the MUGM（1,m,w） model had higher accuracy.
出处
《现代雷达》
CSCD
北大核心
2011年第8期25-28,共4页
Modern Radar
关键词
多因素
灰色预测模型
MUGM(1
m
w)模型
新陈代谢
multi-variables
grey forecast model
multi-variables metabolism unequal interval weight grey model
metabolism
