融合数据权重的雷达发射机健康状态评估方法  

Evaluation Method of Radar Transmitter Health State Based on Data Weight Fusion

作　　者：赵丽琴[1] 刘家铭 刘昶[1] 邓丞君 ZHAO Liqin;LIU Jiaming;LIU Chang;DENG Chengjun(College of Computer Science,Chengdu University,Chengdu 610106,China;State-owned 784th Factory,Chengdu 610051,China)

机构地区：[1]成都大学计算机学院,成都610106 [2]国营第七八四厂,成都610051

出　　处：《现代雷达》2021年第1期58-64,共7页Modern Radar

基　　金：国家自然科学基金青年基金资助项目(61502059);国营第784厂科技研究开发课题资助项目(1082082)。

摘　　要：针对雷达发射机的健康状态评估中状态数据值大小不同对健康状态影响程度不同,提出了用指数函数对样本数据进行加权处理的方法;然后用支持向量机(SVM)作为判别算法构建了健康状态评估模型。该方法通过权重因子的调节,可有效突出个别状态数据恶化对整个健康状态的影响程度。在少量样本训练情况下,能显著提高健康状态评估的准确性。实际测试表明,该方法在雷达发射机健康状态准确评估方面具有实用价值。Considering the influence of different values of collected data on health status for radar transmitter,the method of weighting sample data with exponential function is proposed,and then the health status evaluation model is constructed with support vector machine(SVM)as the discrimination algorithm.This method can effectively highlight the influence of individual state data deterioration on the whole health state by adjusting the weight factor.In the case of a small number of sample training,it can significantly improve the accuracy of health assessment.The practical test shows that this method has practical value in the accurate evaluation of radar transmitter health.

关 键 词：健康管理 健康状态评估 支持向量机 雷达发射机 

分 类 号：TN957.3[电子电信—信号与信息处理]