基于退化数据与失效数据的导弹雷达导引头竞争失效状态预测  

Competition Failure State Prediction of Missile Radar Seeker Based on Degraded Data and Failure Data

作　　者：徐廷学 刘崇屹 朱桂芳 张海军[3] 曲旭 羡崑 XU Ting-xue;LIU Chong-yi;ZHU Gui-fang;ZHANG Hai-jun;QU Xu;XIAN Kun(Naval Aeronautical University,Yantai 264001,China;The PLA Rocket Force Academy,Qingzhou 262500,China;No.92187 Unit of PLA,Changzhi 046000,China;No.91910 Unit of PLA,Dalian 116011,China;No.91183 Unit of PLA,Qingdao 266100,China)

机构地区：[1]海军航空大学 [2]火箭军士官学校 [3]中国人民解放军92187部队 [4]中国人民解放军91910部队 [5]中国人民解放军91183部队

出　　处：《电光与控制》2019年第5期32-38,109,共8页Electronics Optics & Control

基　　金：国家自然科学基金(51605487);中国博士后科学基金(2016M592965)

摘　　要：针对导弹雷达导引头测试数据获取困难、失效机理多样的问题,在分析导弹雷达导引头退化数据和失效数据特点的基础上,提出了一种退化失效与突发失效相关的竞争失效状态预测模型。针对退化数据的小样本、非线性和不确定性的特点,采用相关向量机(RVM)对其分布参数序列进行回归预测,并基于量子粒子化算法(QPSO)和Hannan-Quinn(H-Q)准则分别对核参数和嵌入维数进行寻优;考虑到突发失效与退化失效之间的相关性,引入位置-尺度模型描述突发失效分布参数与退化数据间的相关关系,进而对下一阶段导弹雷达导引头的失效状态进行预测。实例预测结果验证了模型的可行性及合理性。Considering the problems of "difficult acquisition of test data and diverse failure mechanism" of the radar seeker of a missile,we proposed a competition failure state prediction model related to degraded failure and sudden failure based on the analysis to the characteristics of the degraded data and failure data.Aiming at the characteristics of small sample,nonlinearity,and uncertainty of the degraded data,we used Relevance Vector Machine(RVM) to regress and predict the distributed parameter sequence.Then the kernel parameter and embedded dimensions were both optimized via Quantum-Behaved Particle Swarm Optimization(QPSO) and Hannan-Quinn(H-Q) criterion.Taking into account the correlation between the sudden failure and the degraded failure,a position-scale model was introduced to describe the correlation between the sudden failure distribution parameters and the degraded data,thus to predict the failure state of the next stage.Prediction result of an example verified the feasibility and rationality of the model.

关 键 词：导弹雷达导引头 退化数据 失效数据 竞争失效预测 QPSO-RVM 位置-尺度模型 Hannan-Quinn准则 

分 类 号：E927[军事—军事装备学]