计算机工程与应用Issue(12)：263-265,270,4.DOI:10.3778/j.issn.1002-8331.1207-0445
基于小波分析的汽轮机振动预测研究
Steam turbine vibration prediction research based on wavelet analysis
李慧君 1杨继明 1邓彤天 2钟晶亮2
作者信息
- 1. 华北电力大学 能源动力与机械工程学院，河北 保定 071003
- 2. 贵州电力试验研究院，贵阳 550000
- 折叠
摘要
Abstract
As the power plant prediction of steam turbine rotor vibration time series is difficult, the wavelet decomposi-tion to realize trend prediction is proposed. Some non-stationary time series can be decomposed into several approximate stationary time series with wavelet decomposition. Decomposed time series are forecasted with auto-regression model, to obtain forecasting results of the original time series. Experiments with a power plant vibration signal show that the local and overall effect of the algorithm is better than neural network approaches. The result shows rotor vibration time series forecasting accuracy of this model.关键词
小波分析/时间序列/动态神经网络/故障/预测Key words
wavelet analysis/time series/dynamic neural network/fault/predict分类
信息技术与安全科学引用本文复制引用
李慧君,杨继明,邓彤天,钟晶亮..基于小波分析的汽轮机振动预测研究[J].计算机工程与应用,2014,(12):263-265,270,4.
