现代信息科技2024，Vol.8Issue(12)：121-124,4.DOI:10.19850/j.cnki.2096-4706.2024.12.026
基于时间序列的发电机设备异常分析
Abnormal Analysis of Generator Equipment Based on Time Series
摘要
Abstract
To improve the level of maintenance and management of power generation equipment operation,a fault prediction technology for power generation equipment based on PCA-Informer method is proposed.Firstly,it uses Principal Component Analysis(PCA)algorithm to reduce the feature dimension of time series data.Secondly,the data is inputted into the Encoder in batches,and the Encoder performs distillation operations to extract Long-Range dependencies between long time series inputs.The important features are given higher weights through distillation operation,and a focused Self-Attention Feature Map is generated in the next layer.Finally,the Decoder generates a long sequence output by one-step reaction through a forward process.Experimental results show this method can effectively predict the faults of power generation equipment.关键词
发电机设备/主成分分析/Informer/故障预测Key words
generator equipment/PCA/Informer/fault prediction分类
信息技术与安全科学引用本文复制引用
陆钊,龙法宁,陈国年..基于时间序列的发电机设备异常分析[J].现代信息科技,2024,8(12):121-124,4.基金项目
玉林市科学研究与开发计划项目(玉市科20202925) （玉市科20202925）
