摘要
应用小波变换和混沌理论对复杂系统状态预测方法进行了研究.首先,应用小波变换对系统的特征参数序列进行分解,得到低频部分和高频部分.然后,对低频部分和高频部分做进一步分析,以确认低频部分和高频部分都存在混沌特性.再应用混沌理论分别建立低频部分和高频部分的预测模型,对低频部分和高频部分进行预测.最后,应用小波理论对混沌模型预测的结果予以重构,实现对系统特征参数序列的预测.实例研究表明,此方法具有较高的预测精度,可有效地应用于复杂系统的状态预测和故障趋势预测分析.
Based on wavelet transformation and chaos theory, this paper presents a condition forecasting method for complex systems. Firstly, using wavelet decomposition theory, the system feature reference data series are decom- posed into two parts ： low frequency part and high frequency part. Further analysis on the two parts indicates that there exists a chaos feature in the both parts. Then, by using chaos theory, chaotic forecasting models are established to forecast the low frequency and high frequency parts respectively. Finally, forecasting results of the chaotic models are reconstructed based on wavelet theory so as to forecast the system feature reference data series. Case study shows that the proposed method is of high precision, and can be effectively applied to condition forecasting and fault trend fore- cast analysis of complex systems.
出处
《信息与控制》
CSCD
北大核心
2007年第1期6-9,共4页
Information and Control
关键词
状态预测
小波变换
复杂系统
混沌
condition forecasting
wavelet transformation
complex system
chaos
