导弹遥测故障的GM-Verhulst-SCGM预测算法  

Research on Missile Telemetry Fault Forecast Algorithm Based on GM-Verhulst-SCGM Method

作　　者：张峰[1] 殷秀清[1] 董会忠[1] 万里洋 毕砚昭 

机构地区：[1]山东理工大学商学院,山东淄博255012

出　　处：《火力与指挥控制》2016年第6期108-112,116,共6页Fire Control & Command Control

基　　金：国家自然科学基金(71371112);山东省自然科学基金资助项目(ZR2012GM020)

摘　　要：遥测故障预测是保障导弹遥测系统可靠性的基础。根据导弹遥测故障的历史数据,结合GM(1,1)模型、Verhucst模型和SCGM(1,1)c模型构建了导弹遥测故障的GM-Verhulst-SCGM组合灰色预测模型,按照预测有效度算法取得组合预测模型的权重系数。选用导弹遥测故障的训练组实际值作为原始数据,分别利用各预测模型估算对比组导弹遥测故障数据。预测结果表明,相比单一预测模型,组合灰色预测模型具备更高的故障预测精度。在验证组合灰色预测模型可行性的基础上,进一步估算了同一型号导弹未来时序的遥测故障数据,为相关部门及时改善导弹遥测技术及避免导弹故障提供理论及方法借鉴。The reliability of the missile telemetry system is based on the forecast and analysis of fault. So the GM-Verhulst-SCGM combined grey forecasting model of missile telemetry fault is constructed according to GM （1,1） model,Verhulst model and SCGM （1,1） c model. The weight coefficients of combination forecasting model was calculated based on predict effective algorithm and the history data of missile telemetry fault. Missile telemetry fault of the real value of exercise group is used as a raw data,and control group of missile telemetry failure data are analyzed through each forecast model. The prediction results show that GM-Verhulst-SCGM forecasting model have higher forecasting precision compared with single forecast model. The future time-series model missile telemetry failure data is estimated on the basis of the feasibility of grey forecasting model is validated. So it can provide theory and method for related department with the reference of improving the remote sensing technology and avoiding missiles fault in timely.

关 键 词：导弹遥测 灰色模型 故障预测 

分 类 号：V557.3[航空宇航科学与技术—人机与环境工程]