SHAO Yan-jun1, MA Chun-mao2, PAN Hong-xia1
（1. School of Mechanical and Power Engineering, North University of China, Taiyuan 030051, China；2. Northwest Institute of Mechanical and Electrical Engineering, Xianyang 712099, China）
Abstract： Based on modeling principle of GM(1,1) model and linear regression model， a combined prediction model is established to predict equipment fault by the fitting of two models. The new prediction model takes full advantage of prediction information provided by the two models and improves the prediction precision. Finally, this model is introduced to predict the system fault time according to the output voltages of a certain type of radar transmitter.
Key words： grey linear regression model; filtting; radar fault prediction
CLD number： TN956 Document code： A
Article ID： 1674-8042（2016）01-0044-04 doi： 10.3969/j.issn.1674-8042.2016.01.009
References
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基于组合模型的雷达故障预测分析
邵延君1， 马春茂2， 潘宏侠1
（1. 中北大学 机械与动力工程学院， 山西 太原 030051； 2. 西北机电工程研究所， 陕西 咸阳 712099）
摘 要: 基于灰色GM(1，1)模型和回归模型的建模原理， 将两种模型进行拟合， 建立了新的组合模型， 并采用该模型对武器装备的故障进行预测。 该组合模型充分利用了两种预测方法提供的信息， 实现了两种模型之间功能和优势的互补， 有效提高了预测精度。 最后， 以某型雷达发射机的等时距测量的输出电压为例估计系统的故障时间， 并依此推断出该系统的故障发生时间。
关键词: 灰度线性回归模型； 拟合； 雷达故障预测
引用格式： SHAO Yan-jun, MA Chun-mao, PAN Hong-xia. Analysis of radar fault prediction based on combined model. Journal of Measurement Science and Instrumentation, 2016, 7(1)： 44-47. ［doi： 10.3969／j.issn.1674-8042.2016.01.009］
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