基于卷积神经网络和格拉姆角差场的四象限脉冲整流器故障诊断方法

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (3550 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract To fully exert the advantages of the convolutional neural network (CNN) in image recognition and classification, a fault diagnosis method for four-quadrant pulse rectifiers based on CNN and Gramian angular difference field (GADF) is proposed. GADF is utilized to transform the one-dimensional time series of rectifier current into a two-dimensional feature map, preserving the temporal dependency of the data and identifying the temporal correlations of the signal over different time intervals. The CNN then extracts and classifies the features of open circuit faults in the rectifier from the generated feature maps. This method is compared with other common fault diagnosis methods. Simulation analysis results indicate that this proposed method achieves higher diagnostic accuracy compared to other fault diagnosis methods.

Key words： four-quadrant pulse rectifiers Gramian angular difference field (GADF) convolutional neural networks (CNN) fault diagnosis

Received: 19 June 2024

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	ZHAI Daoyu
	SUN Yannan

Cite this article:

ZHAI Daoyu,SUN Yannan. Fault diagnosis method for four-quadrant pulse rectifiers based on convolutional neural network and Gramian angular difference field[J]. Electrical Engineering, 2025, 26(1): 23-32.

URL:

https://dqjs.cesmedia.cn/EN/Y2025/V26/I1/23

[1] 王丹. 动车组牵引变流器故障分析及其诊断方法研究[D]. 兰州: 兰州交通大学, 2020.
[2] 杨宝顺, 陈权, 胡存刚. 基于电压偏差的三电平逆变器故障诊断与定位[J]. 电力电子技术, 2022, 56(6): 19-22.
[3] 陈勇, 刘志龙, 陈章勇. 基于电流矢量特征分析的逆变器开路故障快速诊断与定位方法[J]. 电工技术学报, 2018, 33(4): 883-891.
[4] 柯炎, 樊波. 基于电压残差的三相逆变器故障诊断[J]. 空军工程大学学报(自然科学版), 2020, 21(1): 27-31.
[5] 田广强, 乔珊珊, 侯奥, 等. 基于快速傅里叶变换和改进T-S模糊神经网络集成模型的逆变器开路故障诊断方法研究[J]. 电力科学与技术学报, 2023, 38(6): 76-86.
[6] 赵苗苗, 陈小强, 王英, 等. 基于小波包熵及双重优化神经网络的牵引逆变器开路故障诊断[J]. 铁道科学与工程学报, 2022, 19(4): 1101-1110.
[7] 耿俊超, 王天真, 韩金刚, 等. 基于多级特征提取的并网逆变器故障诊断策略[J]. 电源学报, 2022, 20(4): 28-36.
[8] 董懿飞, 舒胜文, 陈诚, 等. 基于红外图像分割与SSA-SVM的复合绝缘子缺陷检测方法[J]. 电气技术, 2021, 22(11): 73-79.
[9] 董志文, 苏晶晶. 基于变分模态分解能量熵混合时域特征和随机森林的故障电弧检测方法[J]. 电气技术, 2024, 25(1): 1-7.
[10] 魏银图, 张旸, 温步瀛, 等. 基于支持向量机的模块化多电平换流器子模块开路故障诊断方法[J]. 电气技术, 2023, 24(10): 1-7.
[11] 钱存元, 吴昊, 陈昊然. 基于EMD-BPNN的逆变器IGBT开路故障诊断方法[J]. 电气工程学报, 2024, 19(3): 432-442.
[12] 李宇昂, 岳朋朋, 李豪. 基于CNN的Buck-Boost变流器开路故障诊断[J]. 电力电子技术, 2023, 57(7): 24-27.
[13] 丁伟, 宋俊材, 陆思良, 等. 基于多通道信号二维递归融合和ECA-ConvNeXt的永磁同步电机高阻接触故障诊断[J]. 电工技术学报, 2024, 39(20): 6397-6408.
[14] 刘伟, 杨东风, 王洪志, 等. 基于格拉姆角场-改进残差网络的小电流接地系统故障选线[J]. 电气技术, 2023, 24(12): 14-19.
[15] KIM B, KANG J W, KIM C S, et al.Hybrid transformer for anomaly detection on railway HVAC systems through feature ensemble of spatial-temporal with multi-channel GADF images[J]. Journal of Elec- trical Engineering Technology, 2024, 19(4): 2803-2815.
[16] 张辉, 戈宝军, 韩斌, 等. 基于GAF-CapsNet的电机轴承故障诊断方法[J]. 电工技术学报, 2023, 38(10): 2675-2685.
[17] 孙曙光, 张婷婷, 王景芹, 等. 基于连续小波变换和MTL-SEResNet的断路器故障程度评估[J]. 仪器仪表学报, 2022, 43(6): 162-173.