|本期目录/Table of Contents|

[1]张丽萍,石敦义,缪希仁.低压断路器振动特性分析及其故障诊断研究[J].电机与控制学报,2016,20(10):82-87.[doi:10. 15938 /j. emc. 2016. 10. 011]
 ZHANG Li-ping,SHI Dun-yi,MIAO Xi-ren.Research on vibration signal feature analysis and its fault diagnosis [J].,2016,20(10):82-87.[doi:10. 15938 /j. emc. 2016. 10. 011]
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低压断路器振动特性分析及其故障诊断研究(PDF)
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
20
期数:
2016年10
页码:
82-87
栏目:
出版日期:
2016-10-01

文章信息/Info

Title:
Research on vibration signal feature analysis and its fault diagnosis
作者:
张丽萍1 石敦义2 缪希仁1
(1.福州大学 电气工程与自动化学院,福建 福州 350116; 2.华能罗源发电有限责任公司,福建 福州 350600)
Author(s):
ZHANG Li-ping1 SHI Dun-yi2 MIAO Xi-ren1
 ( 1. College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350116,China; 2. Hua Neng Luoyuan Power Generation Co.,Ltd,Fuzhou 350600,China)

关键词:
低压断路器 振动信号 经验模态分解 分形理论 极端学习机 故障诊断
Keywords:
low voltage circuit breaker vibration signal empirical mode decomposition fractal theory extreme learning machine fault diagnosis
分类号:
TM 51
DOI:
10. 15938 /j. emc. 2016. 10. 011
文献标志码:
A
摘要:
以低压断路器三相不同期故障为对象,首先,利用经验模态分解( EMD) 方法,将振动信号 分解为若干本征模态函数( IMF) ,经频谱分析确定前四阶 IMF 分量作为振动信号特性,并起到振动 信号消噪作用; 其次,利用分形理论对前四阶 IMF 分量求取关联维数,以表征低压断路器三相合闸 不同期的故障特征; 最后,引入极端学习机( ELM) 建立三相合闸不同期故障识别模型。试验与仿 真结果表明,基于 EMD 及分形理论的 ELM 模型可有效区分三相不同期故障。根据上述故障诊断 原理,该方法对低压断路器其他故障类型的诊断具有适用性。
Abstract:
A method for fault diagnosis of three-phasesasynchronism switching for a low voltage circuit breaker( LVCB) is concerned. Firstly,the vibration signal is decomposed into several intrinsic mode functions ( IMF) by empirical mode decomposition ( EMD) . By analyzing the vibration signal spectrum of a LVCB,the front four IMF components were determined as the vibration signal characteristic so that noise of vibration signal was eliminated. Secondly,the correlation dimension of front four IMF components was calculated by fractal theory,that is the fault characteristic of three-phases switching asynchronism of a LVCB. Finally,extreme learning machine was introduced to build the fault identification model of three-phases switching asynchronism.Results of experiment and simulation showing that it is effective to identify switching synchronism with ELM model based on EMD and fractal theory. In addition,the method also has the feasibility to diagnose other faults of a LVCB,based on above fault diagnosis principle.

参考文献/References:

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[2]杨秋玉,阮江军,黄道春,等. 基于振动信号的高压断路器触头超程状态识别[J].电机与控制学报,2019,23(06):27.[doi:10.15938/j.emc.2019.06.004]
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备注/Memo

备注/Memo:
收稿日期: 2014 - 09 - 02
基金项目: 国家自然科学基金( 51377023) ; 福建省高校产学合作科技重大项目( 2011H6013)
作者简介: 张丽萍( 1977—) ,女,博士研究生,讲师,研究方向为电气设备在线监测与故障诊断技术;
石敦义( 1989—) ,男,工程师,硕士,主要从事电气设备在线监测工作; 缪希仁( 1965—) ,男,教授,博士生导师,研究方向为电器及其系统智能化技术。
更新日期/Last Update: 2016-12-09