中点钳位(neutral point clamped,NPC)型三电平逆变器并网工作环境恶劣,IGBT面临单管与双管同时故障的挑战,这使得故障特征之间的差异变得非常微弱,进而导致双管故障的识别精度难以有效提升。为此,提出了一种新的故障诊断方法,该方法结...中点钳位(neutral point clamped,NPC)型三电平逆变器并网工作环境恶劣,IGBT面临单管与双管同时故障的挑战,这使得故障特征之间的差异变得非常微弱,进而导致双管故障的识别精度难以有效提升。为此,提出了一种新的故障诊断方法,该方法结合了多通道的二维递归融合图和轻量化多尺度残差(lightweightmultiscale convolutional residuals,LMCR)网络。首先,通过仿真获取三相电流信号作为故障信号;再利用递归图(recurrence plot,RP)将三相电流信号分别转化为二维图并进行多通道融合,以捕捉时间序列中的周期性、突变点和趋势等特征;最后,将递归融合图作为输入,输入到LMCR模型中进行故障识别,LMCR模型整合多级Inception结构和残差网络,用于提取不同尺度的特征并融合这些特征,从而保证网络的梯度消失和爆炸。实验结果显示,该方法在IGBT故障识别中表现出色,无噪声环境下平均识别准确率达100%,噪声环境中也达到了92.53%,充分证明了该方法具有较强的特征提取能力和优异的抗噪性能。展开更多
针对常规虚拟空间矢量脉宽调制VSVPWM(virtual space vector pulse-width modulation)在高调制深度下,母线中点电位存在不可控区域问题,提出1种可在整个线性调制区实现中点电位快速均衡的优化型VSVPWM算法。基于VSVPWM母线中点电位均衡...针对常规虚拟空间矢量脉宽调制VSVPWM(virtual space vector pulse-width modulation)在高调制深度下,母线中点电位存在不可控区域问题,提出1种可在整个线性调制区实现中点电位快速均衡的优化型VSVPWM算法。基于VSVPWM母线中点电位均衡原理重构虚拟中矢量,为保证重构后虚拟中矢量的均压性能,同时提高算法对系统参数摄动的适应性,设计用于中点电压闭环控制的模糊推理确定重构因子对VSVPWM进行优化。即使在直流母线电容不对称情况下,优化型VSVPWM仍可实现线性调制区全范围的快速均压控制。进一步在60°坐标系内对算法简化,参考电压矢量子区域的判断条件、伏秒平衡方程组从30个减少至5个。实验结果表明,该控制策略具有良好性能,均压调节时间显著降低,直流母线中点电位稳态偏差可控制在1.14%内,相较于传统VSVPWM,并网电流总谐波含量更低。展开更多
With the increasing demand for high reliability and availability in power conversion equipment within power electronics systems,the fault diagnosis of neutral-point-clamped(NPC) three-level inverters has garnered wide...With the increasing demand for high reliability and availability in power conversion equipment within power electronics systems,the fault diagnosis of neutral-point-clamped(NPC) three-level inverters has garnered widespread attention.To address the challenges of fault feature extraction,this article proposes an end-to-end diagnostic approach based on a wavelet kernel convolutional neural network (WKCNN),capable of extracting multi-scale features from current signals to significantly enhance diagnostic accuracy.This method directly uses raw three-phase current signals as input,applying wavelet kernel convolution to automatically capture frequency-domain fault features,combined with a Softmax classifier optimized by the Adam algorithm to achieve fault diagnosis for NPC threelevel inverters.Experimental results under various operating conditions demonstrate that this approach maintains robust diagnostic accuracy across multiple fault scenarios,with comparative analysis further confirming its advantages in diagnostic efficiency and performance over traditional machine learning and other deep learning methods.展开更多
Editor's Note:The“two ssions”,the annual ssions of China's national lgislature and political advisory body,kicked of in early March in Beiing.As a highly anticipated event on the country's political cale...Editor's Note:The“two ssions”,the annual ssions of China's national lgislature and political advisory body,kicked of in early March in Beiing.As a highly anticipated event on the country's political calendar,it attracted both domestic and international attentions,ofering a critical window for the world at large into China's achievements in 2024 and is roadmap towards high-quality development and Chinese modernization in 2025-the final year of China's 14th Five Year Plan(2021-2025).展开更多
文摘针对常规虚拟空间矢量脉宽调制VSVPWM(virtual space vector pulse-width modulation)在高调制深度下,母线中点电位存在不可控区域问题,提出1种可在整个线性调制区实现中点电位快速均衡的优化型VSVPWM算法。基于VSVPWM母线中点电位均衡原理重构虚拟中矢量,为保证重构后虚拟中矢量的均压性能,同时提高算法对系统参数摄动的适应性,设计用于中点电压闭环控制的模糊推理确定重构因子对VSVPWM进行优化。即使在直流母线电容不对称情况下,优化型VSVPWM仍可实现线性调制区全范围的快速均压控制。进一步在60°坐标系内对算法简化,参考电压矢量子区域的判断条件、伏秒平衡方程组从30个减少至5个。实验结果表明,该控制策略具有良好性能,均压调节时间显著降低,直流母线中点电位稳态偏差可控制在1.14%内,相较于传统VSVPWM,并网电流总谐波含量更低。
基金supported in part by Zhejiang Provincial“Pioneer”and“Leading Goose”R&D Program of China under Grant 2024C01014the National Natural Science Foundation of China under Grant52177055。
文摘With the increasing demand for high reliability and availability in power conversion equipment within power electronics systems,the fault diagnosis of neutral-point-clamped(NPC) three-level inverters has garnered widespread attention.To address the challenges of fault feature extraction,this article proposes an end-to-end diagnostic approach based on a wavelet kernel convolutional neural network (WKCNN),capable of extracting multi-scale features from current signals to significantly enhance diagnostic accuracy.This method directly uses raw three-phase current signals as input,applying wavelet kernel convolution to automatically capture frequency-domain fault features,combined with a Softmax classifier optimized by the Adam algorithm to achieve fault diagnosis for NPC threelevel inverters.Experimental results under various operating conditions demonstrate that this approach maintains robust diagnostic accuracy across multiple fault scenarios,with comparative analysis further confirming its advantages in diagnostic efficiency and performance over traditional machine learning and other deep learning methods.
文摘Editor's Note:The“two ssions”,the annual ssions of China's national lgislature and political advisory body,kicked of in early March in Beiing.As a highly anticipated event on the country's political calendar,it attracted both domestic and international attentions,ofering a critical window for the world at large into China's achievements in 2024 and is roadmap towards high-quality development and Chinese modernization in 2025-the final year of China's 14th Five Year Plan(2021-2025).
