基于GWO-VMD的IGBT老化状态应力波分析

Stress Wave Analysis of IGBT Aging State Based on GWO-VMD

中文关键词:  绝缘栅双极晶体管  应力波  状态评估  变分模态分解

英文关键词:IGBT  stress waves  state assessment  VMD

中文摘要:

      针对绝缘栅双极晶体管（Insulated Gate Bipolar Transistor，IGBT）的老化失效问题，提出了利用一种灰狼优化（Grey Wolf Optimizer，GWO）算法优化变分模态分解（Variational Mode Decomposition，VMD）算法的IGBT老化状态评估方法。首先，利用GWO算法以最小包络熵为适应度函数来确定VMD算法的模态分解数K和惩罚因子α的最佳组合；然后，利用最佳参数组合［K，α］将IGBT应力波信号通过VMD算法分解成若干本征模态函数（Intrinsic Mode Function，IMF）分量；最后，对信号分解的各模态分量进行特征提取和分析。基于IGBT功率循环平台的应力波试验结果表明，该方法能够有效提取IGBT老化特征，同时IGBT应力波的峭度特征变化明显，可以表征IGBT的老化程度。

英文摘要:

      Based on the aging failure problem of insulated gate bipolar transistor(IGBT) devices,an IGBT aging status evaluation method using grey wolf optimizer(GWO) algorithm to optimize variational mode decomposition(VMD) algorithm is proposed.Firstly,the GWO algorithm is used to determine the optimal combination of modal decomposition number K and penalty factor α of the VMD algorithm with the minimum envelope entropy as the fitness function.Then,the IGBT stress wave signal is decomposed into several intrinsic mode function (IMF) components by the VMD algorithm based on the optimal parameter combination［K,α］.Finally,the feature extraction and analysis of each modal component of signal decomposition are carried out.The results of stress wave test based on IGBT power cycling platform shows that the proposed method can effectively extract the IGBT aging characteristics,and the kurtosis characteristics of the IGBT stress wave change significantly,which can characterize the aging degree of IGBT.