摘要
机械振动信号能反映有载分接开关的运行状态。为提高有载分接开关机械故障的诊断准确率,提出了一种基于参数自适应变分模态分解(VMD)和模拟退火优化极限学习机(SA-ELM)的故障诊断方法。首先对振动信号进行VMD分解,根据能量准则自适应确定模态数的取值,得到一组窄带、区分度较好的模态分量。然后求取各模态的能量值,形成特征向量组,不同故障状态的模态特征区分明显。最后将特征向量组输入SA-ELM,实现振动信号的识别和诊断。在模拟试验平台上进行试验并对采集的信号进行分析,结果表明文中故障诊断方法可有效提高有载分接开关机械故障的诊断准确率。
Mechanical vibration signal can reflect the running state of on-load tap-changer.In order to realize effective mechanical fault diagnosis for on-load tap-changer,a fault diagnosis method based on the parameter-adapted variational mode decomposition(VMD)and extreme learning machine optimized by simulated anneal(SA-ELM)is proposed.Firstly,the signal is decomposed by VMD method,and the number of modals is selected based on energy criterion.A group of modal components with narrow band and great discrimination is obtained.Then the energy features of each modal component are calculated,which form the feature vector group,and the modal features of different fault states are clearly distinguished.Finally,the feature vector group is input to the extreme learning machine(ELM)optimized by simulated annealing algorithm to realize the recognition and fault diagnosis of the vibration signals.An experiment is carried out on the simulation experiment platform and the collected signals are processed.Compared with the method based on VMD and ELM,the fault diagnosis method proposed can effectively improve the diagnostic accuracy of mechanical fault of on-load tap-changer.
作者
钱国超
彭庆军
程志万
古洪瑞
于虹
QIAN Guochao;PENG Qingjun;CHENG Zhiwan;GU Hongrui;YU Hong(School of Electrical Engineering,Chongqing University,Chongqing 400030,China;Electric Power Research Institute of Yunnan Power Grid Co.,Ltd.,Kunming 650200,China)
出处
《电力工程技术》
2020年第1期157-164,共8页
Electric Power Engineering Technology
基金
国家自然科学基金资助项目(U1766217)
关键词
有载分接开关
变分模态分解
模态能量
极限学习机
故障诊断
on-load tap-changer
variational mode decomposition
modal energy
extreme learning machine
fault diagnosis