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题名: 基于无人机的输电线路设备识别方法研究
其他题名: Research of power transmission line equipments recognition method based on UAV
作者: 何思远 ; 刘刚 ; 王玲 ; 唐延东
作者部门: 机器人学研究室
关键词: 目标识别 ; 小波特征 ; AP聚类 ; 无人机
刊名: 红外与激光工程
ISSN号: 1007-2276
出版日期: 2013
卷号: 42, 期号:7, 页码:1940-1944
收录类别: EI ; CSCD
产权排序: 1
摘要: 利用无人机进行输电线路巡检是近几年国内外研究的热点技术之一,其优点是在无需拉闸断电的情况下,即可对输电线路进行检测,对其故障进行判别。根据输电线路设备的特征,应用图像处理与模式识别技术,提出了一种识别绝缘子、防震锤和输电塔的方法。该方法先采用中值滤波、膨胀和腐蚀等方法对灰度化后的航拍图像进行预处理,然后提取预处理后图像的小波特征值,最后采用AP(Affinity Propagation)聚类方法对目标图像进行分类与识别。实验结果表明,所提出的方法能够有效的识别绝缘子、防震锤和输电塔等目标,具有较好的鲁棒性和准确性。
英文摘要: In recent years, the use of unmanned aerial vehicle(UAV) for power transmission line detection is a hot technology, and it can detect the transmission line and discriminate the failure without power off. According to the features of power transmission line equipments, a method of equipments recognition based on image processing and pattern recognition was put forward. It preprocessed the aerial images by median filtering, dilating and eroding. Then, wavelet eigenvalues of preprocessed images were calculated. Finally, the objects, such as insulator, vibration damper and transmission tower, were classified and recognized by affinity propagation (AP) clustering algorithm. The results of experiments show that this method can recognize the insulator, vibration damper and transmission tower, and it has better robustness, accuracy and validity.
语种: 中文
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/14039
Appears in Collections:机器人学研究室_期刊论文

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