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An Assembled Detector Based on Geometrical Constraint for Power Component Recognition.

TitleAn Assembled Detector Based on Geometrical Constraint for Power Component Recognition.
Publication TypeJournal Article
Year of Publication2019
AuthorsJi Z, Liao Y, Zheng L, Wu L, Yu M, Feng Y
JournalSensors (Basel)
Date Published2019 Aug 11

The intelligent inspection of power lines and other difficult-to-access structures and facilities has been greatly enhanced by the use of Unmanned Aerial Vehicles (UAVs), which allow inspection in a safe, efficient, and high-quality fashion. This paper analyzes the characteristics of a scene containing power equipment and the operation mode of UAVs. A low-cost virtual scene is created, and a training sample for the power-line components is generated quickly. Taking a vibration-damper as the main object, an assembled detector based on geometrical constraint (ADGC) is proposed and is used to analyze the virtual dataset. The geometric positional relationship is used as the constraint, and the Faster R-CNN, Deformable Part Model (DPM), and Haar cascade classifiers are combined, which allows the features of different classifiers, such as contour, shape, and texture to be fully used. By combining the characteristics of virtual data and real data using UAV images, the power components are detected by the ADGC. The result produced by the detector with relatively good performance can help expand the training set and achieve a better detection model. Moreover, this method can be smoothly transferred to other power-line facilities and other power-line scenarios.

Pubmed Link
Alternate JournalSensors (Basel)
PubMed ID31405244
PubMed Central IDPMC6719115
Grant List2018YFB0505003 / / The National Key Research and Development Program of China /

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