基于逆变器多模态输出电压的IGBT微小故障特征提取

TM46; 针对逆变器IGBT模块发生微小故障引起特征信号变化,相较于电路正常运行信号十分微弱、难以检测的问题,提出一种通过采样逆变器端口输出电压来提取IGBT微小故障特征参数的方法.方波控制策略下,逆变器输出电压包含稳态和暂态两种工作模态,可进一步划分为6个暂态模态和6个稳态模态,因此利用Elman神经网络完成工作模态划分.暂态工作模态中,通过将开关状态下的逆变器等效成二阶系统,完成系统的参数辨识;基于此提出一种输出电压原始数据和系统辨识参数相融合的方法,提取二阶系统的超调量、峰值时间以及暂态电压斜率作为暂态故障特征参数,既降低了实际系统原始数据噪声的干扰,又避免了等效二阶系统参数辨识误差对...

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Published in电机与控制学报 Vol. 27; no. 1; pp. 65 - 79
Main Authors 朱琴跃, 李姚霖, 谭喜堂, 魏伟, 李爱华
Format Journal Article
LanguageChinese
Published 同济大学 电子与信息工程学院,上海201804 2023
Subjects
两电平逆变器
模态划分
IGBT微小故障
Elman神经网络
特征参数提取
原始数据与辨识参数融合
Online AccessGet full text
ISSN1007-449X
DOI10.15938/j.emc.2023.01.007

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Abstract TM46; 针对逆变器IGBT模块发生微小故障引起特征信号变化,相较于电路正常运行信号十分微弱、难以检测的问题,提出一种通过采样逆变器端口输出电压来提取IGBT微小故障特征参数的方法.方波控制策略下,逆变器输出电压包含稳态和暂态两种工作模态,可进一步划分为6个暂态模态和6个稳态模态,因此利用Elman神经网络完成工作模态划分.暂态工作模态中,通过将开关状态下的逆变器等效成二阶系统,完成系统的参数辨识;基于此提出一种输出电压原始数据和系统辨识参数相融合的方法,提取二阶系统的超调量、峰值时间以及暂态电压斜率作为暂态故障特征参数,既降低了实际系统原始数据噪声的干扰,又避免了等效二阶系统参数辨识误差对故障特征提取效果的影响.仿真和实验验证了所提方法的有效性.
AbstractList TM46; 针对逆变器IGBT模块发生微小故障引起特征信号变化,相较于电路正常运行信号十分微弱、难以检测的问题,提出一种通过采样逆变器端口输出电压来提取IGBT微小故障特征参数的方法.方波控制策略下,逆变器输出电压包含稳态和暂态两种工作模态,可进一步划分为6个暂态模态和6个稳态模态,因此利用Elman神经网络完成工作模态划分.暂态工作模态中,通过将开关状态下的逆变器等效成二阶系统,完成系统的参数辨识;基于此提出一种输出电压原始数据和系统辨识参数相融合的方法,提取二阶系统的超调量、峰值时间以及暂态电压斜率作为暂态故障特征参数,既降低了实际系统原始数据噪声的干扰,又避免了等效二阶系统参数辨识误差对故障特征提取效果的影响.仿真和实验验证了所提方法的有效性.
Author 朱琴跃
李爱华
魏伟
谭喜堂
李姚霖
AuthorAffiliation 同济大学 电子与信息工程学院,上海201804
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TAN Xi-tang
LI Ai-hua
ZHU Qin-yue
WEI Wei
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DocumentTitle_FL Extraction method for incipient fault characteristic parameters of IGBT based on multi-mode output voltage of inverter
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Keywords 两电平逆变器
模态划分
IGBT微小故障
Elman神经网络
特征参数提取
原始数据与辨识参数融合
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Snippet TM46; 针对逆变器IGBT模块发生微小故障引起特征信号变化,相较于电路正常运行信号十分微弱、难以检测的问题,提出一种通过采样逆变器端口输出电压来提取IGBT微小故障特征参数...
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Title 基于逆变器多模态输出电压的IGBT微小故障特征提取
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