[1]冯晗,姜勇.使用改进Yolov5的变电站绝缘子串检测方法[J].智能系统学报,2023,18(2):325-332.[doi:10.11992/tis.202201027]
FENG Han,JIANG Yong.A substation insulator string detection method based on an improved Yolov5[J].CAAI Transactions on Intelligent Systems,2023,18(2):325-332.[doi:10.11992/tis.202201027]
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FENG Han,JIANG Yong.A substation insulator string detection method based on an improved Yolov5[J].CAAI Transactions on Intelligent Systems,2023,18(2):325-332.[doi:10.11992/tis.202201027]
使用改进Yolov5的变电站绝缘子串检测方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
18
期数:
2023年第2期
页码:
325-332
栏目:
学术论文—机器感知与模式识别
出版日期:
2023-03-05
- Title:
- A substation insulator string detection method based on an improved Yolov5
- Keywords:
- Yolov5; insulator; attention mechanism; backlighting environment; computer vision; deep learning; artificial intelligence; target detection
- 分类号:
- TP391.4
- 摘要:
- 针对变电站绝缘子串水冲洗机器人在复杂光照环境下无法准确识别绝缘子的问题，提出了一种基于改进Yolov5的绝缘子检测方法。首先针对逆光环境下图像质量差导致算法失效的问题，提出了一种模拟过曝增强算法，并应用到数据增强过程中；此外，针对变电站绝缘子检测任务，对网络的Neck进行了优化裁剪，使推理速度获得了提升；最后，使用注意力机制改善了裁剪后网络检测精度下降的问题。实验表明，改进后的Yolov5在检测精度基本不变的情况下推理速度提高了25%，并且对于逆光下图像的检测精度获得了大幅提升。
- Abstract:
- An improved method for detecting insulators, based on Yolov5, is proposed to address the challenge faced by substation insulator string water rinsing robots in accurately identifying insulators in complex lighting conditions. To overcome the issue of poor image quality in backlight environments causing algorithm failure, the data enhancement process includes the use of a simulated overexposure enhancement algorithm. The network’s Neck is optimally cropped to improve the inference speed for the substation insulator detection task, and the attention mechanism is utilized to address the accuracy degradation after cropping. Results show that the improved Yolov5 has improved the inference speed by 25% while maintaining the same detection accuracy and achieved significant improvement in the detection accuracy for images under backlighting.
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- 相似文献/References:
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[1]赵文清,程幸福,赵振兵,等.注意力机制和Faster RCNN相结合的绝缘子识别[J].智能系统学报,2020,15(1):92.[doi:10.11992/tis.201907023]
ZHAO Wenqing,CHENG Xingfu,ZHAO Zhenbing,et al.Insulator recognition based on attention mechanism and Faster RCNN[J].CAAI Transactions on Intelligent Systems,2020,15():92.[doi:10.11992/tis.201907023]
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备注/Memo
收稿日期:2022-01-17。
基金项目:国家自然科学基金项目(52075531)
作者简介:冯晗,硕士研究生,主要研究方向为目标检测;姜勇,研究员,博士,主要研究方向为机器人智能控制、多传感器融合、特种机器人控制系统设计与集成。负责及参加完成了国家高技术研究发展计划重点项目、国家自然科学基金青年及面上项目、中科院知识创新工程重大项目、辽宁省自然科学基金项目、机器人学重点实验室项目、国网及南网重点项目等20余项。获国家发明专利授权3项、实用新型专利4项。登记软件著作权2项,参编专著2部,发表学术论文20余篇
通讯作者:姜勇. E-mail：jiangyong@sia.com
更新日期/Last Update:
1900-01-01