摘要
为了对机电设备的非线性非平稳状态进行有效的趋势预测,运用混沌预测方法和混沌神经网络的预测原理,建立了基于混沌神经网络的预测模型.以工业现场大型烟气轮机为研究对象,采用混沌神经网络和灰色预测两种方法进行了趋势预测,并对两种方法的预测结果进行了比较.结果表明,针对烟气轮机的非线性非平稳状态,基于混沌神经网络的预测精度更高、更有效.
In order to predict electromechanical equipments'nonlinear and non-stationary condition effectively, the method of chaos prediction and the prediction theory based on chaos-neural networks are introduced, and the model of chaos-neural networks is set up. Aimed at the industrial smokes and gas turbine, the paper finished the prediction based on the chaos-neural networks and gray predicting method, the two prediction results are compared. The compared result shows that the prediction based on the chaos-neural networks has a higher accuracy and it can forecast the fault more effective.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2009年第6期506-509,共4页
Transactions of Beijing Institute of Technology
基金
北京市自然科学基金资助项目(3083019)
北京市人才强教计划资助项目
北京市教委科技计划重点项目(KZ200910772001)
北京市教委科技计划面上项目(KM200910772023)
关键词
机电设备
故障预测
混沌理论
相空间重构
混沌神经网络
electromechanical equipment
faults forecasting
chaos theory
phase-space reconstruction
chaos-neural networks