Novel Feature Fusion Module-Based Detector for Small Insulator Defect Detection
文献类型：期刊论文
| 作者 | Gao, Zishu1,2 ; Yang, Guodong1,2; Li, En1,2; Liang, Zize1,2
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| 刊名 | IEEE SENSORS JOURNAL
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| 出版日期 | 2021-08-01 |
| 卷号 | 21期号:15页码:16807-16814 |
| 关键词 | Feature extraction Insulators Sensors Image segmentation Inspection Fuses Support vector machines Insulator defect detection anchor-free object detection data augmentation aerial image |
| ISSN号 | 1530-437X |
| DOI | 10.1109/JSEN.2021.3073422 |
| 通讯作者 | Yang, Guodong(guodong.yang@ia.ac.cn) |
| 英文摘要 | The failure of an insulator may compromise the safety of the entire power transmission system. Therefore, insulator defect detection is vital for the safe operation of power systems. However, insulator defects in an insulator image may have varying sizes, and several currently available methods do not have satisfactory detection accuracy for small defects. To address this issue, we propose an improved detection network for small insulator defects with a batch normalization convolutional block attention module (BN-CBAM) and a feature fusion module. The BN-CBAM is designed to better exploit channel information and enhance the effect of different channels on the feature map. In addition, we propose a feature fusion module that fuses multi-scale features from different layers to improve small object detection performance. Moreover, to address the scarcity of aerial images, a data augmentation method based on the fusion of the target segment and background is introduced. Experiments demonstrate that the proposed method achieves better small insulator defect detection performance than other state-of-the-art approaches. In addition, data augmentation methods enrich sample diversity and enhance the generalizability of the network. |
| 资助项目 | National Key Research and Development Program of China[2018YFB1307400] ; National Natural Science Foundation[U1713224] ; National Natural Science Foundation[61973300] |
| WOS研究方向 | Engineering ; Instruments & Instrumentation ; Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:000679541000045 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/45554]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 通讯作者 | Yang, Guodong |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Gao, Zishu,Yang, Guodong,Li, En,et al. Novel Feature Fusion Module-Based Detector for Small Insulator Defect Detection[J]. IEEE SENSORS JOURNAL,2021,21(15):16807-16814. |
| APA | Gao, Zishu,Yang, Guodong,Li, En,&Liang, Zize.(2021).Novel Feature Fusion Module-Based Detector for Small Insulator Defect Detection.IEEE SENSORS JOURNAL,21(15),16807-16814. |
| MLA | Gao, Zishu,et al."Novel Feature Fusion Module-Based Detector for Small Insulator Defect Detection".IEEE SENSORS JOURNAL 21.15(2021):16807-16814. |
入库方式： OAI收割
来源：自动化研究所
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