基于DKPCA的气象卫星遥测故障检测方法  

Fault Detection of Meteorological Satellite Telemetry Based on DNMFSC

作　　者：彭艺[1] 贾树泽[1] 韩琦[1] 康宁[1] 陈秀娟[1] Peng Yi;Jia Shuze;Han Qi;Kang Ning;Chen Xiujuan(National Satellite Meteorological Center,Beijing 100081)

机构地区：[1]国家卫星气象中心,北京100081

出　　处：《气象科技》2018年第5期886-891,共6页Meteorological Science and Technology

摘　　要：针对气象卫星遥测数据在阈值范围内变化发生异常,简单的阈值法无法检测出来的问题,本文提出基于动态核主元分析法(DKPCA)对气象卫星遥测数据进行故障检测。首先采集卫星正常运行的遥测数据,建立DKPCA模型求得统计量的控制限,然后对当前的遥测数据进行检测,判断是否有故障发生。该方法通过初始数据的动态化表示解决了观测值间存在序列相关性的问题,引入的核主元分析法能够将复杂的遥测数据的非线性问题转化为线性问题。通过在轨运行的气象卫星FY3C的实际数据进行效果验证,结果表明利用正常状况下的观测数据,可以实时检测卫星遥测数据出现的异常,有效避免故障漏报。Due to the problem that the abnormal telemetry data of meteorological satellites in the threshold rang cannot be detected,this paper proposes the Dynamic Kernel Principal Component Analysis（DKPCA）method to detect the abnormity of satellite telemetry.The telemetry data during the normal operation are collected,and the DKPCA model is established to obtain the control limit of the variable.Then the current telemetry data are detected to determine whether there is a fault.The method solves the problem of sequence correlation between observed data by the dynamic representation of initial data.The introduced DKPCA can transform the nonlinear problem of complex telemetry data into linear problems.The effect is verified by the data of the meteorological satellite FY3 Cin orbit.The results show that the observed data under normal conditions can be used to detect abnormal satellite telemetry,and the fault omission can be avoided effectively.

关 键 词：气象卫星遥测 故障检测 动态核主元分析 

分 类 号：P407[天文地球—大气科学及气象学]