| 基于神经网络的非线性时间序列故障预报 |
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| 引用本文： | 胡寿松,张正道.基于神经网络的非线性时间序列故障预报[J].自动化学报,2007,33(7):744-748. |
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| 作者姓名： | 胡寿松 张正道 |
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| 作者单位： | 1.南京航空航天大学自动化学院 南京 210016 |
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| 基金项目： | 国家自然科学基金;国防科技应用基础研究基金;航空基础科学基金 |
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| 摘 要： | 对模型未知非线性系统, 将系统输出组成时间序列并通过空间嵌入的方法转化为一个离散动态系统. 利用线性 AR 模型拟合时间序列的线性部分, 用神经网络拟合时间序列的非线性部分并补偿外界未知的扰动, 提出了通过对状态的观测实现时间序列一步预测的方法. 利用滚动优化的思想将一步预测推广, 提出了时间序列的 N 步预测方法, 证明了时间序列预测误差有界. 通过对预测误差进行概率密度估计和检验, 提出了故障的预报方法. 对 F-16 歼击机的结构故障预报结果表明了方法的有效性.
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| 关 键 词： | 非线性时间序列 神经网络 滚动预测 概率密度估计 故障预报 |
| 收稿时间： | 2005-12-26 |
| 修稿时间： | 2005-12-262006-04-27 |
Fault Prediction for Nonlinear Time Series Based on Neural Network |
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| HU Shou-Song,ZHANG Zheng-Dao.Fault Prediction for Nonlinear Time Series Based on Neural Network[J].Acta Automatica Sinica,2007,33(7):744-748. |
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| Authors: | HU Shou-Song ZHANG Zheng-Dao |
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| Affiliation: | 1.College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016;2.College of Communication and Control Engineering, Jiangnan University, Wuxi 214122 |
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| Abstract: | According to the Takens embedding theorem, the nonlinear time series combined with system output is converted into discrete dynamic system. An autoregressive model is used to fit the linear part of series; the neural network is used to fit the nonlinear part of series and to compensate for the unknown disturbance. The prediction of time series is achieved by the observation of system states. So a one-step prediction method is proposed. Using the so-called moving horizon optimization method, one-step prediction is extended to N-steps prediction. The boundedness of prediction error is proved. The fault is predicted by the prediction error through density function estimation and hypothesis test. The simulation of the structure fault prediction of a fighter F-16 proved the efficiency of the model. |
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| Keywords: | Nonlinear time series neural network moving horizon prediction density estimation fault prediction |
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