中国水利水电科学研究院学报2017，Vol.15Issue(6)：439-443,5.DOI:10.13244/j.cnki.jiwhr.2017.06.005
基于摆度大数据的水轮发电机故障预测方法研究
Study on failure prediction for hydro-generator based on big data of run-out value
段炼达 1刘晓波1
作者信息
- 1. 中国水利水电科学研究院北京中水科水电科技开发有限公司,北京100038
- 折叠
摘要
Abstract
The hydropower plants have accumulated mass production data,which is of great value to failure prediction.In this paper,the Monte Carlo method is applied to analyze the big data of run-out value to predict the failure.The X peak-peak values of the run-out of the lower guide bearing of a hydropower plant are taken as the investigation object.In the treatment of 453,601 sets of the run-out value,three typical operating conditions are selected to study.The normalized weighted average is used as the statistic,and the Monte Carlo method is adopted to analyze it.It is found that the statistic obeys normal distribution.By monitoring the real-time value of the statistic,the working status of the hydro-generator is evaluated qualitatively according to the normal distribution 3σ criterion,and evaluated quantitatively according to the calculated probability P-value.Failure can be predicted by using these evaluations.关键词
大数据/水电厂/机器学习/蒙特卡洛方法/故障预测/摆度Key words
big data/hydropower plant/machine learning/Monte Carlo method/failure prediction/run-out value分类
信息技术与安全科学引用本文复制引用
段炼达,刘晓波..基于摆度大数据的水轮发电机故障预测方法研究[J].中国水利水电科学研究院学报,2017,15(6):439-443,5.
