|
| 基于混沌时间序列的水电机组状态短期预测 |
| Short-term Prediction of Hydroturbine Generating Unit Condition Based on Chaotic Time Series |
| |
| DOI：10.3969/j.issn.1671-5322.2010.02.006 |
| 中文关键词: 水电机组 混沌时间序列 相空间重构 状态预测 |
| 英文关键词: hydroturbine generating units chaotic time series phase space reconstruction condition prediction |
| 基金项目: |
|
| 摘要点击次数: 4649 |
| 全文下载次数: 3897 |
| 中文摘要: |
| 基于混沌时间序列短期可以预测的特点,构建水电机组状态短期预测.用采样周期确定相空间时延τ,G-P算法确定关联维数从而确定相空间的嵌入维数m,小数据量法证明水电机组振动状态的混沌特性.在重构相空间中,运用加权一阶局域法构建水电机组状态短期预测模型.结果表明:混沌特性指数λ=0.260 5的水电机组振动状态具有混沌特性,可以在最佳嵌入维数m=4的情况下进行预测,实例结果表明采用混沌理论进行水电机组状态短期预测是可行的. |
| 英文摘要: |
| Based on the characteristic of chaotic time series,a model was built to predict hydroturbine generating unit condition.The time delayτ was determined by sampling period,and the embedding dimension m was chosen according to correlation dimension,which was calculated by G-P algorithm.Chaotic characteristic of vibration signal series of hydroturbine generating unit was proved by small data sets arithmetic.The prediction model of hydroturbine generating unit condition was constructed by an adding-weight one-rank local-region method after the phase space was reconstructed.The results show that vibration signal series has a chaotic characteristic while the chaotic property exponent λ=0.2605.Therefore,a prediction model can be carried out while the best embedding dimension m is 4.The results demonstrate that the prediction method is feasible. |
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |