摘要
针对汽轮发电机组振动振幅受运行参数及随机因素影响的特点 ,提出了用人工神经网络中的递推合成BP网络对汽轮机的振动故障进行多因素预测。通过对仿真数据及机组实际振动数据的预测结果检验 。
Vibration amplitude of steam turbine is affected by operation parameters and random factors,the paper Contributes a Prediction method using multifactor model of recurrent combined BP networks.By means of using simulated data and the operation data of steam turbines,the predictive performance is checked.The prediction results prove that the multi factor prediction model can help to improve the prediction precise.
出处
《东北电力学院学报》
2000年第2期39-43,共5页
Journal of Northeast China Institute of Electric Power Engineering
关键词
汽轮机
振动
故障
预测
BP算法
steam turbo generator set
vibration
neural networks
predivtion
