EMB-YOLO: Dataset, method and benchmark for electric meter box defect detection
The electric meter box is a terminal device with a large number in the power grid. It may cause electrical hazards and property loss if damaged. Inspection of electricity meter boxes still relies on manual inspection with low efficiency and low automation. But image-based automated inspection is als...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-02-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157824000259 |
| _version_ | 1797272576941096960 |
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| author | Zhiyong Liu Yong Li Feng Shuang Zhongmou Huang Ruichen Wang |
| author_facet | Zhiyong Liu Yong Li Feng Shuang Zhongmou Huang Ruichen Wang |
| author_sort | Zhiyong Liu |
| collection | DOAJ |
| description | The electric meter box is a terminal device with a large number in the power grid. It may cause electrical hazards and property loss if damaged. Inspection of electricity meter boxes still relies on manual inspection with low efficiency and low automation. But image-based automated inspection is also limited by equipment battery and insufficient computing power, which makes the inspection system in urgent need of efficient model. However, lightweight model may reduce model robustness and be susceptible to interference from complex backgrounds due to insufficient feature extraction. Meanwhile, there are no publicly available datasets for electric meter boxes at present. To address the above issues, we firstly constructed a dataset, named EMB-11. After that, we improved the YOLOv7-tiny to design a novel model for electric meter box defect detection, named EMB-YOLO. In EMB-YOLO, we proposed the Big Kernel ShuffleBlock which can increase the effective receptive field and reduce the model parameters. Additionally, we proposed ELAN-CBAM to enhance the robustness of the model and reduce the interference of background noise. Finally, we constructed RepBSB based on the idea of structural reparameterization to reduce the size of the trained model. Compared to YOLOv7-tiny, the size of EMB-YOLO is only 4.82 Mb, which is reduced by 20.3 %. The detection speed is 343 frames/s, which is increased by 14.3 %. Most importantly, mAP can reach 82.8 %, which is increased by 3.5 %, reaching the SOTA level. |
| first_indexed | 2024-03-07T14:30:22Z |
| format | Article |
| id | doaj.art-bcc67da61fb54f1796a7afbd03270608 |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-03-07T14:30:22Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-bcc67da61fb54f1796a7afbd032706082024-03-06T05:25:40ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782024-02-01362101936EMB-YOLO: Dataset, method and benchmark for electric meter box defect detectionZhiyong Liu0Yong Li1Feng Shuang2Zhongmou Huang3Ruichen Wang4Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, Nanning 530004, ChinaGuangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, Nanning 530004, China; Corresponding author.Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, Nanning 530004, ChinaChongzuo Power Supply Bureau of Guangxi Power Grid Co., Ltd, Chongzuo, ChinaGuangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, Nanning 530004, ChinaThe electric meter box is a terminal device with a large number in the power grid. It may cause electrical hazards and property loss if damaged. Inspection of electricity meter boxes still relies on manual inspection with low efficiency and low automation. But image-based automated inspection is also limited by equipment battery and insufficient computing power, which makes the inspection system in urgent need of efficient model. However, lightweight model may reduce model robustness and be susceptible to interference from complex backgrounds due to insufficient feature extraction. Meanwhile, there are no publicly available datasets for electric meter boxes at present. To address the above issues, we firstly constructed a dataset, named EMB-11. After that, we improved the YOLOv7-tiny to design a novel model for electric meter box defect detection, named EMB-YOLO. In EMB-YOLO, we proposed the Big Kernel ShuffleBlock which can increase the effective receptive field and reduce the model parameters. Additionally, we proposed ELAN-CBAM to enhance the robustness of the model and reduce the interference of background noise. Finally, we constructed RepBSB based on the idea of structural reparameterization to reduce the size of the trained model. Compared to YOLOv7-tiny, the size of EMB-YOLO is only 4.82 Mb, which is reduced by 20.3 %. The detection speed is 343 frames/s, which is increased by 14.3 %. Most importantly, mAP can reach 82.8 %, which is increased by 3.5 %, reaching the SOTA level.http://www.sciencedirect.com/science/article/pii/S1319157824000259Defect detectionYOLOPower inspectionMeter Box |
| spellingShingle | Zhiyong Liu Yong Li Feng Shuang Zhongmou Huang Ruichen Wang EMB-YOLO: Dataset, method and benchmark for electric meter box defect detection Journal of King Saud University: Computer and Information Sciences Defect detection YOLO Power inspection Meter Box |
| title | EMB-YOLO: Dataset, method and benchmark for electric meter box defect detection |
| title_full | EMB-YOLO: Dataset, method and benchmark for electric meter box defect detection |
| title_fullStr | EMB-YOLO: Dataset, method and benchmark for electric meter box defect detection |
| title_full_unstemmed | EMB-YOLO: Dataset, method and benchmark for electric meter box defect detection |
| title_short | EMB-YOLO: Dataset, method and benchmark for electric meter box defect detection |
| title_sort | emb yolo dataset method and benchmark for electric meter box defect detection |
| topic | Defect detection YOLO Power inspection Meter Box |
| url | http://www.sciencedirect.com/science/article/pii/S1319157824000259 |
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