Infrared Image Fault Detection of Photovoltaic Modules Based on Residual Photovoltaic Network

Fig. 8. Feature layer visualization information of underlying feature information enhancement module. (a) Feature maps information of ResNet-50; (b) feature maps information of ResPNet[D]

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Fig. 9. Feature layer visualization information of Respblock module. (a) Feature maps information of ResPNet[D]; (b) feature maps information of ResPNet[P]

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Fig. 10. Feature layer visualization information of Gblock module. (a) Feature maps information of ResPNet[P]; (b) feature maps information of ResPNet[G]

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Fig. 11. Test results of different photovoltaic module fault detection models. (a) ResNet; (b) ResPNet

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Fig. 12. Test results of cascaded photovoltaic module fault detection

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Table 1. Description of photovoltaic module and dataset partitioning

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Table 1. Description of photovoltaic module and dataset partitioning

Fault name	Fault description	Number of images	Number of images in train and validation dataset	Number of images in test dataset
Cell	There is a single square hot spot in the photovoltaic module	1877	1689	188
Cell-multi	There are multiple square hot spots in the photovoltaic module	1288	1160	128
Cracking	Cracks exist on the surface of the photovoltaic module	940	845	95
Hot-spot	A single hot spot exists on the surface of the photovoltaic module	249	224	25
Hot-spot-multi	There are multiple hot spots on the surface of the photovoltaic module	246	222	24
Shadowing	Shadows created by plants，artifacts between adjacent rows	1056	950	106
Diode	Bypass diode short circuit causes that 1/3 photovoltaic module cannot operate normally	1499	1349	150
Diode-multi	The short circuit of the bypass diode causes that 2/3 of the photovoltaic module cannot operate normally	175	158	17
Vegetation	The plants shade the photovoltaic module	1639	1476	163
Soiling	Dust and garbage may block the surface of the photovoltaic module	204	183	21
Offline-module	The entire photovoltaic module fails to operate properly	827	744	83
No-anomaly	Trouble-free	10000	9000	1000

Table 2. Type of photovoltaic module images
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Table 2. Type of photovoltaic module images
Fault name Image data
Cell
Cell-multi
Cracking
Hot-spot
Hot-spot-multi
Shadowing
Diode
Diode-multi
Vegetation
Soiling
Offline-module
No-anomaly

Table 3. Ablation experiment results of infrared image classification accuracy of photovoltaic modules
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Table 3. Ablation experiment results of infrared image classification accuracy of photovoltaic modules
Dataset Model $A_{c}$ /%
Infrared Solar Modules ResNet-50 83.2
ResPNet［D］ 83.8
ResPNet［P］ 84.4
ResPNet［G］ 84.6

Table 4. Model accuracy of infrared image classification in photovoltaic modules

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Table 4. Model accuracy of infrared image classification in photovoltaic modules

Model	$A_{c}$ /%	$A_{p}$ /%	$A_{r}$ /%	$F_{F 1 - S c o r e}$ /%	Speed /ms
ShuffleNetV2^［19］	76.8	59.8	54.1	56.8	4.9
MobileNetV2^［20］	78.3	63.0	57.2	59.9	4.0
ResNet-50^［14］	83.2	74.2	67.9	70.9	5.1
ResNet-101^［14］	83.5	74.3	67.0	70.4	12.3
EfficientNetV7^［21］	81.4	68.7	63.6	66.1	26.9
Alves et al.模型^［11］	78.8	—	—	—	—
CNN-SVM^［12］	82.9	—	—	—	—
Le et al.模型^［13］	84.1	—	—	—	—
ResPNet［G］	84.6	75.8	67.6	71.5	30.8

Table 5. Integrated models for infrared image classification accuracy of photovoltaic module
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Table 5. Integrated models for infrared image classification accuracy of photovoltaic module
Model No. of model A_c /%
Proposed by Le et al. ^［13］ 15 85.9
ResPNet［G］ 3 85.9

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Mingzheng Sun, Hao Li. Infrared Image Fault Detection of Photovoltaic Modules Based on Residual Photovoltaic Network[J]. Laser & Optoelectronics Progress, 2023, 60(24): 2412005

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Paper Information

Category: Instrumentation, Measurement and Metrology

Received: Mar. 22, 2023

Accepted: Apr. 20, 2023

Published Online: Nov. 27, 2023

The Author Email: Li Hao (lihao@hhu.edu.cn)

DOI:10.3788/LOP230912

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Description of photovoltaic module and dataset partitioning

Table 1. Description of photovoltaic module and dataset partitioning

Table 2. Type of photovoltaic module images

Table 2. Type of photovoltaic module images

Table 3. Ablation experiment results of infrared image classification accuracy of photovoltaic modules

Table 3. Ablation experiment results of infrared image classification accuracy of photovoltaic modules

Table 4. Model accuracy of infrared image classification in photovoltaic modules

Table 4. Model accuracy of infrared image classification in photovoltaic modules

Table 5. Integrated models for infrared image classification accuracy of photovoltaic module

Table 5. Integrated models for infrared image classification accuracy of photovoltaic module