[1]陆 晓,高 超,蒋承伶,等.基于双注意力机制和级联检测框架的金具螺栓缺陷检测研究[J].机械与电子,2024,42(01):63-70.
 LU Xiao,GAO Chao,JIANG Chengling,et al.Research on Bolt Defect Detection Based on Dual-attention Mechanism and Cascade Detection Framework[J].Machinery & Electronics,2024,42(01):63-70.
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基于双注意力机制和级联检测框架的金具螺栓缺陷检测研究()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
42
期数:
2024年01期
页码:
63-70
栏目:
机电一体化
出版日期:
2024-01-25

文章信息/Info

Title:
Research on Bolt Defect Detection Based on Dual-attention Mechanism and Cascade Detection Framework
文章编号:
1001-2257 ( 2024 ) 01-0063-08
作者:
陆 晓 1 高 超 1 蒋承伶 1 王茂飞 2
1. 国网江苏省电力有限公司,江苏 南京 210024 ;
2. 国网江苏泰州供电公司,江苏 泰州 225300
Author(s):
LU Xiao1 GAO Chao1 JIANG Chengling1 WANG Maofei2
( 1.State Grid Jiangsu Electric Power Co. , Ltd. , Nanjing 210024 , China ;
2.State Grid Jiangsu Taizhou Power Supply Company , Taizhou 225300 , China )
关键词:
金具螺栓缺陷检测多尺度注意力级联知识引导图像增广
Keywords:
gauge bolts defect detection multi-scale attention cascade knowledge guiding image augmentation
分类号:
TP391.41 ; TM75
文献标志码:
A
摘要:
针对传统输电线路金具上的螺栓缺陷检测存在精度低和效率低的问题,提出一种基于双注意力机制和级联检测框架的螺栓缺陷检测模型。首先,构建了螺栓缺陷检测的级联框架并通过基于 GridMask 图像增广方法实现数据集的扩充;其次,为了提高螺栓缺陷检测精度,提出了基于知识引导的输电线金具检测模型,通过隐式和显示模块的构建,实现第 1 级金具的检测;然后,将金具检测结果输入到第 2 级螺栓的缺陷检测网络中,同时提出一种基于双注意力机制的螺栓缺陷检测模型来进行螺栓缺陷检测,通过多尺度注意力模块的设计,融合空间注意力图,实现螺栓全局视野上的特征增强,提高检测的精度;最后,通过实验进行验证,实验结果表明,所提模型的螺栓缺陷检测平均准确度高、检测速度快,具有良好的实用性和鲁棒性,有一定的应用前景。
Abstract:
The traditional bolt defect detection on transmission lines suffers from low accuracy and efficiency , and this paper proposes a bolt defect detection model based on dual-attention mechanism and cascade detection framework.Firstly , a cascade framework for bolt defect detection is constructed and the dataset is expanded by an image augmentation method based on the GridMask ; secondly , in order to improve the accuracy of bolt defect detection , a knowledge-guided detection model for power line fittings is proposed , the detection of the first level of gold fixtures is realized through the construction of implicit and display modules ; then , the results of the gold fixture detection are inputted into the defect detection network for bolts at the second level , while a bolt defect detection model based on dual-attention mechanism is proposed for bolt defect detection , through the design of the multi-scale attention module , the spatial attention map is fused to realize the feature enhancement on the global field of view of the bolt and improve the accuracy of detection ; finally , it is validated by experiments , which show that the average accuracy of bolt defect detection of the model proposed in this paper is high and the detection speed is fast.The model has good practicality , robustness and certain application prospects.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2023-07-21
基金项目:国网江苏电力有限公司科技项目资助( J2022004 )
作者简介:陆 晓 ( 1968- ),男,江苏南京人,博士,高级工程师,研究方向为电力系统调度运行及数字化建设管理;高 超 ( 1983- ),男,河南洛阳人,博士,高级工程师,研究方向为输电线路巡检;蒋承伶 ( 1986- ),男,重庆人,博士,高级工程师,研究方向为电气自动化、计算机通信;王茂飞 ( 1991- ),男,江苏泰州人,硕士,工程师,研究方向为智能运检技术,通信作者。
更新日期/Last Update: 2024-01-16