基于生产大数据的水轮发电机组故障检修技术研究
Research on Fault Maintenance Technology for Hydroelectric Generating Set Based on Production Big Data
董佩宇 1张文杰1
作者信息
- 1. 国网甘肃省电力公司刘家峡水电厂,临夏回族自治州 731600
- 折叠
摘要
文章阐述水轮发电机组的常见故障类型,分析传统检修技术存在诊断精度低、人力依赖强等局限性,并提出一套基于生产大数据的水轮发电机组故障检修技术.通过搭建实验平台,对比传统检修技术和基于生产大数据的故障检修技术的故障检修性能.实验结果表明,基于生产大数据的故障检修技术可以显著提高故障检出率,降低误报率,缩短平均检修时间,节约检修成本.
Abstract
This paper describes the common fault types of hydroelectric generating set,analyzes the limitations of traditional maintenance technology such as low diagnostic accuracy and strong manpower dependence,and puts forward a set of fault maintenance technology of hydroelectric generating set based on production big data.By setting up an experimental platform,the performance of the traditional maintenance technology and the fault maintenance technology based on production big data is compared.The experimental results show that the fault inspection technology based on production big data can significantly improve the fault detection rate,reduce the false positive rate,shorten the average inspection time and save the inspection cost.
关键词
水轮发电机组/故障/检修技术/生产大数据Key words
hydroelectric generating set/malfunction/maintenance technology/production big data引用本文复制引用
出版年
2024
NETL
NSTL
万方数据