FAULT DIAGNOSE METHOD OF OPEN-CIRCUIT OF PV INVERTERS BASED ON IMPROVED GAF-SE-RESNET

Han Sumin; Yu Yuewei; Guo Yu

doi:10.19912/j.0254-0096.tynxb.2023-0987

PDF(4302 KB)

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (10) : 336-344. DOI: 10.19912/j.0254-0096.tynxb.2023-0987

FAULT DIAGNOSE METHOD OF OPEN-CIRCUIT OF PV INVERTERS BASED ON IMPROVED GAF-SE-RESNET

Han Sumin, Yu Yuewei, Guo Yu

Author information +

History +

Abstract

Aiming at the problem that the one-dimensional time series signals of PV inverters cannot adequately capture the temporal and local features when they are input into the convolutional neural network, a PV inverter open-circuit fault diagnosis model based on the combination of Gramain angular fields （GAF） and improved deep residual network （ResNet） is proposed. Utilizing GAF encoding method with two channels, the one-dimensional current signal is mapped into a two-dimensional fault feature image with distinct pixel distributions. Using the feature images as the input to ResNet preserves the temporal correlation of the data. ResNet incorporates residual modules in convolutional neural networks to mitigate overfitting. An improved version of the residual module includes compression and squeeze-and-excitation （SE） attention mechanisms for image compression and feature reuse, enhancing important feature information. These enhancements enable ResNet to delve deeper into image information and fully capture local features. Combining the Swish function and Ranger optimizer to optimize ResNet, the training difficulty of the model is significantly reduced. The experimental results show that the method has an accuracy of 99.41% for diagnosing open circuit faults in PV inverters, and has better feature extraction effect and diagnosis speed compared with other models.

Key words

photovoltaic inverter / fault detection / feature extraction / Gramian angular field / residual network

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Han Sumin, Yu Yuewei, Guo Yu. FAULT DIAGNOSE METHOD OF OPEN-CIRCUIT OF PV INVERTERS BASED ON IMPROVED GAF-SE-RESNET[J]. Acta Energiae Solaris Sinica. 2024, 45(10): 336-344 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0987

References

[1] 赵铁英, 高宁, 杨杰, 等. 基于PI控制器有源阻尼的并网逆变器自适应改进策略[J]. 太阳能学报, 2023, 44(5): 152-161.
ZHAO T Y, GAO N, YANG J, et al.Adaptive improvement strategy for grid-connected inverter based on active damping of PI controllers[J]. Acta energiae solaris sinica, 2023, 44(5): 152-161.
[2] 安文杰, 陈长征, 田淼, 等. 基于迁移学习的风电机组轴承故障诊断研究[J]. 太阳能学报, 2023, 44(6): 367-373.
AN W J, CHEN C Z, TIAN M, et al.Research on bearing fault diagnosis of wind turbines based on transfer learning[J]. Acta energiae solaris sinica, 2023, 44(6): 367-373.
[3] 韩艳, 帕孜来·马合木提. 闭环状态下并网逆变器故障诊断[J]. 电子技术应用, 2019, 45(1): 122-126.
HAN Y, PAZILAI M.Grid-connected inverter fault diagnosis in closed loop[J]. Application of electronic technique, 2019, 45(1): 122-126.
[4] 任惠, 夏静, 卢锦玲, 等. 基于红外图像和改进MobileNet-V3的光伏组件故障诊断方法[J]. 太阳能学报, 2023, 44(8): 238-245.
REN H, XIA J, LU J L, et al.Research on fault diagnosis of photovoltaic modules based on infrared images and improved MobileNet-V3[J]. Acta energiae solaris sinica, 2023, 44(8): 238-245.
[5] 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.
KE Y, FAN B.A three-phase inverter fault diagnosis based on voltage residual[J]. Journal of Air Force Engineering University (natural science edition), 2020, 21(1): 27-31.
[6] 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.
CHEN Y, LIU Z L, CHEN Z Y.Fast diagnosis and location method for open-circuit fault in inverter based on current vector character analysis[J]. Transactions of China Electrotechnical Society, 2018, 33(4): 883-891.
[7] 伍珣, 陈特放, 成庶, 等. 基于输出电流轨迹的机车逆变器开路故障在线诊断方法[J]. 电工技术学报, 2017, 32(增刊2): 87-95.
WU X, CHEN T F, CHENG S, et al.On-line diagnosis method of locomotive inverter open circuit fault based on output current trajectory[J]. Transactions of China Electrotechnical Society, 2017, 32(Sup 2): 87-95.
[8] 陈勇, 张建建, 陈章勇. 基于电流观测器的三相逆变电路开路故障在线诊断[J]. 电工技术学报, 2019, 34(S2): 609-617.
CHEN Y, ZHANG J J, CHEN Z Y.On-line diagnosis of open circuit fault of three-phase inverter circuit based on current observer[J]. Transactions of China Electrotechnical Society, 2019, 34(Sup 2): 609-617.
[9] WU X, CHEN C Y, CHEN T F, et al.A fast and robust diagnostic method for multiple open-circuit faults of voltage-source inverters through line voltage magnitudes analysis[J]. IEEE transactions on power electronics, 2020, 35(5): 5205-5220.
[10] YUAN W B, LI Z G, HE Y G, et al.Open-circuit fault diagnosis of NPC inverter based on improved 1-D CNN network[J]. IEEE transactions on instrumentation and measurement, 2022, 71: 3510711.
[11] 韩素敏, 郑书晴, 何永盛. 基于粗糙集贪心算法的逆变器开路故障诊断[J]. 电力系统保护与控制, 2020, 48(17): 122-130.
HAN S M, ZHENG S Q, HE Y S.Open circuit fault diagnosis for inverters based on a greedy algorithm of a rough set[J]. Power system protection and control, 2020, 48(17): 122-130.
[12] CUI Y B, WANG R J, SI Y P, et al.T-type inverter fault diagnosis based on GASF and improved AlexNet[J]. Energy reports, 2023, 9: 2718-2731.
[13] HE K M, ZHANG X Y, REN S Q, et al.Deep residual learning for image recognition[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV, USA, 2016: 770-778.
[14] 姚芳, 姜涛, 刘明宇, 等. 基于GWO-ELM的逆变器开路故障诊断[J]. 电源学报, 2020, 18(1): 45-53.
YAO F, JIANG T, LIU M Y, et al.Open-circuit fault diagnosis of inverter based on GWO-ELM[J]. Journal of power supply, 2020, 18(1): 45-53.