基于大数据的风电机组发电机定子槽楔脱落在线监测系统研究  

Research on Online Monitoring System for Stator Wedge Shedding of Wind Turbine Generator Based on Big Data

作　　者：荣必贤 成伟 莫堃 王兵 邓超 RONG Bixian;CHENG Wei;MO Kun;WANG Bin;DENG Chao(DEC Academy of Science and Technology Co.,Ltd.,Chengdu 611731;Dongfang Electric Wind Power Co.,Ltd.,Deyang 618000)

机构地区：[1]东方电气集团科学技术研究院有限公司,成都610027 [2]东方电气风电有限公司,德阳618000

出　　处：《现代制造技术与装备》2021年第10期80-83,共4页Modern Manufacturing Technology and Equipment

摘　　要：发电机定子槽楔脱落会对风电机组的安全平稳运行带来严重影响,以往的工作中,只能依靠人工凭借工作经验判断槽楔的脱落状态,这种方式主观性强,容易失误。因此,提供了一种基于大数据的风电机组发电机定子槽楔脱落在线监测系统,该系统以声波频率与振幅为检测手段,具备感知层、网络层和应用层等3层系统框架,可以将专家知识库与大数据分析相结合,实时分析槽楔的在线监测数据,从而判断槽楔松动的状态,并且可以根据以往的运行数据,提前预警槽楔的松动状态以及其他故障。The shedding of the stator slot wedge of the generator will bring great challenges to the safe and stable operation of the wind turbine.In the past,the fall-off state of the slot wedges could only be judged manually based on historical experience,which was subjective and easy to make mistakes.This article provides an online monitoring system for wind turbine generator stator slot wedge shedding based on big data.Using sound wave frequency and amplitude as detection means,it has a three-layer system framework including perception layer,network layer and application layer.The system combines expert knowledge base with big data analysis,which can analyze the online monitoring data of slot wedge in real time and judge the state of slot wedge loosening.And based on past operating data,early warning of slot wedge looseness and other faults can be given.

关 键 词：槽楔脱落 大数据 在线监测 预警 

分 类 号：TM315[电气工程—电机] TP311.13[自动化与计算机技术—计算机软件与理论]