一种遥测数据短期预测方法
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摘要
为实现遥测数据的快速和高精度预测,针对遥测数据的非平稳性特点,提出一种基于小波分析和自适应指数平滑法的建模方法.该方法引入小波分析技术对遥测数据非平稳序列进行分解和重构,将原始非平稳遥测数据序列分解为较平稳的序列.利用对传统的指数平滑法改进后的自适应指数平滑法和周期自回归模型(PAR模型)建立短期预测模型,并对太阳翼输出功率数据的未来趋势进行预测分析.实验结果表明预测曲线与实际曲线吻合效果理想,该方法能够有效的解决遥测数据的短期预测问题.
In order to achieve fast and high-precision prediction for telemetry data,according to the non-stationary of telemetry data,a forecast method based on wavelet analysis and adaptive exponential smoothing is proposed. Wavelet analysis technology is used to make decomposition and reconstruction for non-stationary sequence and steady sequence is obtained. Then adaptive exponential smoothing that is improved from traditional exponential smoothing and periodic autoregressive model( PAR model) are used to build shortterm prediction model,and the model is used to analyze the data of solar array output power. Simulation results showthat predict curve and practical curve are almost coincide,the method is effective to solve the short-term forecasting problem of telemetry data.
In order to achieve fast and high-precision prediction for telemetry data,according to the non-stationary of telemetry data,a forecast method based on wavelet analysis and adaptive exponential smoothing is proposed. Wavelet analysis technology is used to make decomposition and reconstruction for non-stationary sequence and steady sequence is obtained. Then adaptive exponential smoothing that is improved from traditional exponential smoothing and periodic autoregressive model( PAR model) are used to build shortterm prediction model,and the model is used to analyze the data of solar array output power. Simulation results showthat predict curve and practical curve are almost coincide,the method is effective to solve the short-term forecasting problem of telemetry data.
引文
[1]Lu Ming Recognition of information from satellite data[D].Harbin:Harbin Institute of Technology,2006.
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[11]Catalao J P S,Pousinho H M I,Mendes V M F.Short-term wind pow er forecasting in Portugal by neural netw orks and w avelet transform[J].Renew able energy,2011,36(4):1245-1251.
[12]Tang Jian,Luan Jia-hui,Liu Ya-long,et al.A novel design of prediction interval for telemetry data[C].Reliability and maintainability symposium(RAM S),Lake Buena Vista,FL,2011:1-5.
[13]Han Liang-xiu,Cong Suo,Yan Hua,et al.Characterizing network traffic based on the w avelet technique[J].Journal of Chinese Computer Systems,2001,22(9):1110-1113.
[14]Cheng Guang,Gong Jian,Ding Wei.Traffic decomposed model on w avelet in a large-scale netw ork[J].Journal of Chinese Computer Systems,2005,26(3):400-403.
[15]Xu Jun-hua.Research on power system short-term load forecasting model and optimum selsction[D].Chengdu:Sichuan University,2004.
[16]Shi Yi,Zhang Li-li,Zhu Li-chun,et al.Routing protocol based on dynamic exponential smoothing prediction in Ad Hoc netw ork[J].Journal of Chinese Computer Systems,2012,33(3):462-465.
[1]鲁明.卫星数据的信息识别[D].哈尔滨工业大学,2006.
[4]孙振明,姜兴渭,王晓锋,等.àTrous小波在卫星遥测数据递归预测中的应用[J].南京理工大学学报,2004,28(6):606-611.
[5]唐建,栾家辉,吕琛.小卫星电源系统遥测数据的区间预测技术[J].华中科技大学学报(自然科学版),2009,37(1):209-212.
[6]郭小红,徐小辉,赵树强,等.基于新息灰预测的卫星遥测参数状态预测及应用[J].宇航学报,2010,31(8):1939-1943.
[8]房红征,史慧,韩立明,等.基于粒子群优化神经网络的卫星故障预测方法[J].计算机测量与控制,2013,21(7):1730-1733.
[13]韩良秀,丛锁,阎华,等.基于小波技术的网络流量特性刻画[J].小型微型计算机系统,2001,22(9):1110-1113.
[14]程光,龚俭,丁伟.基于小波的网络流量分解模型[J].小型微型计算机系统,2005,26(3):400-403.
[15]徐军华.电力系统短期负荷预测模型与优选的研究[D].四川大学,2004.
[16]沙毅,张立立,朱丽春,等.基于指数平滑预测的Ad Hoc网络路由协议[J].小型微型计算机系统,2012,33(3):462-465.
[2]Skander Soltani.On the use of the wavelet decomposition for time series prediction[J].Neurocomptuing,2002,48(3):267-277.
[3]Ali Deihimi,Omid Orang,Hemen Showkati.Short-term electric load and temperature forecasting using w avelet echo state netw orks w ith neural reconstruction[J].Energy,2013,57:382-401.
[4]Sun Zhen-ming,Jiang Xing-wei,Wang Xiao-feng,et al.Application of trous w avelet to satellite telemetry data recursive prediction[J].Journal of Nanjing University of Science and Techonlogy,2004,28(6):606-611.
[5]Tang Jian,Luan Jia-hui,Lv Chen.Prediction interval technique for small satellite pow er system telemetry data[J].Journal of Huazhong University of Science and Technology(Nature Science Edition),2009,37(1):209-212.
[6]Guo Xiao-hong,Xu Xiao-hui,Zhao Shu-qiang,et al.Satellite telemetry parameter trend forecast algorithm based on new information and application[J].Journal of Astronautics,2010,31(8):1939-1943.
[7]Fang H Z,Zou K X,Yi D W,et al.The study of spacecraft telemetry data prediction based on SERTS model[A]Prongnostics&System Helath M angement Conference,PHM2011[C].Shenzhen,2011:1-5.
[8]Fang Hong-zheng,Shi Hui,Han Li-ming,et al.Method of prognostics for satellite based on particle sw arm optimized neural netw ork[J].Computer Measurement&Control,2013,21(7):1730-1733.
[9]Sary C,Peterson C,Rower J,et al.Trend analysis for spacecraft systems using multimodal reasoning[R].AAAI Spring Symp Tech Report SS-98-04:157-161.
[10]Len Losik L.Stopping launch pad delays,launch failures,satellite infant mortalities and on-orbit satellite failures using telemetry prognostic technology[A].Annual International Telemetring Conference and Technical Exhibition[C].Las Vegas,NV,USA,2007.
[11]Catalao J P S,Pousinho H M I,Mendes V M F.Short-term wind pow er forecasting in Portugal by neural netw orks and w avelet transform[J].Renew able energy,2011,36(4):1245-1251.
[12]Tang Jian,Luan Jia-hui,Liu Ya-long,et al.A novel design of prediction interval for telemetry data[C].Reliability and maintainability symposium(RAM S),Lake Buena Vista,FL,2011:1-5.
[13]Han Liang-xiu,Cong Suo,Yan Hua,et al.Characterizing network traffic based on the w avelet technique[J].Journal of Chinese Computer Systems,2001,22(9):1110-1113.
[14]Cheng Guang,Gong Jian,Ding Wei.Traffic decomposed model on w avelet in a large-scale netw ork[J].Journal of Chinese Computer Systems,2005,26(3):400-403.
[15]Xu Jun-hua.Research on power system short-term load forecasting model and optimum selsction[D].Chengdu:Sichuan University,2004.
[16]Shi Yi,Zhang Li-li,Zhu Li-chun,et al.Routing protocol based on dynamic exponential smoothing prediction in Ad Hoc netw ork[J].Journal of Chinese Computer Systems,2012,33(3):462-465.
[1]鲁明.卫星数据的信息识别[D].哈尔滨工业大学,2006.
[4]孙振明,姜兴渭,王晓锋,等.àTrous小波在卫星遥测数据递归预测中的应用[J].南京理工大学学报,2004,28(6):606-611.
[5]唐建,栾家辉,吕琛.小卫星电源系统遥测数据的区间预测技术[J].华中科技大学学报(自然科学版),2009,37(1):209-212.
[6]郭小红,徐小辉,赵树强,等.基于新息灰预测的卫星遥测参数状态预测及应用[J].宇航学报,2010,31(8):1939-1943.
[8]房红征,史慧,韩立明,等.基于粒子群优化神经网络的卫星故障预测方法[J].计算机测量与控制,2013,21(7):1730-1733.
[13]韩良秀,丛锁,阎华,等.基于小波技术的网络流量特性刻画[J].小型微型计算机系统,2001,22(9):1110-1113.
[14]程光,龚俭,丁伟.基于小波的网络流量分解模型[J].小型微型计算机系统,2005,26(3):400-403.
[15]徐军华.电力系统短期负荷预测模型与优选的研究[D].四川大学,2004.
[16]沙毅,张立立,朱丽春,等.基于指数平滑预测的Ad Hoc网络路由协议[J].小型微型计算机系统,2012,33(3):462-465.