State-of-the-art review of computer vision for the management of power transmission lines

Mirallès, François; Pouliot, Nicolas; Montambault, Serge

doi:10.1109/carpi.2014.7030068

Cited by 40 publications

(20 citation statements)

References 28 publications

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“…ROWs are vulnerable to potential hazards (e.g., icing), resulting in short-or long-term power outages [1,2]. It is critical for the safe operation of power transmission grids to monitor the ROW to find potential threats on the power line networks in an efficient and reliable way [3,4]. The inspection of the ROWs incorporates two aspects: electrical facilities and surrounding objects [5].…”

Section: Introductionmentioning

confidence: 99%

Automatic Clearance Anomaly Detection for Transmission Line Corridors Utilizing UAV-Borne LIDAR Data

et al. 2018

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Transmission line corridor (i.e., Right-of-Ways (ROW)) clearance management plays a critically important role in power line risk management and is an important task of the routine power line inspection of the grid company. The clearance anomaly detection measures the distance between the power lines and the surrounding non-power-facility objects in the corridor such as trees, and buildings, to judge whether the clearance is within the safe range. To find the clearance hazards efficiently and flexibly, this study thus proposed an automatic clearance anomaly detection method utilizing LiDAR point clouds collected by unmanned aerial vehicle (UAV). Firstly, the terrain points were filtered out using two-step adaptive terrain filter and the pylons were detected in the non-terrain points following a feature map method. After dividing the ROW point clouds into spans based on the pylon detection results, the power line point clouds were extracted according to their geometric distribution in local span point clouds slices, and were further segmented into clusters by applying conditional Euclidean clustering with linear feature constraints. Secondly, the power line point clouds segments were iteratively fitted with 3D catenary curve model that is represented by a horizontal line and a vertical catenary curve defined by a hyperbolic cosine function, resulting in a continuous mathematical model of the discretely sampled points of the power line. Finally, a piecewise clearance calculation method which converts the point-to-catenary curve distance measurements to minimal distance calculation based on differential geometry was used to calculate the distance between the power line and the non-power-facility objects in the ROW. The clearance measurements were compared with the standard safe threshold to find the clearance anomalies in the ROWs. Multiple LiDAR point clouds datasets collected by a large-scale UAV power line inspection system were used to validate the effectiveness and accuracy of the proposed method. The detected results were validated through qualitatively visual inspection, quantitatively manual measurements in raw point clouds and on-site field survey. The experiments show that the automatic clearance anomaly detection method proposed in this paper effectively detects the clearance hazards such as tree encroachment, and the clearance measurement accuracy is decimeter level for the LiDAR point clouds collected by our UAV inspection system.

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Section: Introductionmentioning

confidence: 99%

Automatic Clearance Anomaly Detection for Transmission Line Corridors Utilizing UAV-Borne LIDAR Data

et al. 2018

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“…The gray value sum of the three windows is calculated and marked as g i , i ∈ (l, c, r), after which the gray ratio is calculated for the area between the center window w c and the windows w l and w r . Windows w l and w r are shown as the windows on the left and right, respectively, according to Equation (1). If the ratio r is greater than a threshold ε, the power line feature is detected, and the gray value of the central pixel in w c is marked as 255; otherwise, the gray value is marked as 0.…”

Section: Power Line Automatic Measurement Methods Based On Epipolar Comentioning

confidence: 99%

“…To achieve sub-pixel accuracy, we calculate the intersection between the epipolar line and the power line. The gray ratio coefficient r between the intersection point and the adjacent pixels on the left and right sides are calculated according to Equation (1). We adopt a parabolic fitting algorithm [24] to acquire the coordinates for the maximum value of the coefficients, which are used as the true intersection between the epipolar line and the power line 2D vector.…”

Section: Automatic Generation Of Power Line 3d Vectorsmentioning

confidence: 99%

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Automatic Power Line Inspection Using UAV Images

et al. 2017

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Power line inspection ensures the safe operation of a power transmission grid. Using unmanned aerial vehicle (UAV) images of power line corridors is an effective way to carry out these vital inspections. In this paper, we propose an automatic inspection method for power lines using UAV images. This method, known as the power line automatic measurement method based on epipolar constraints (PLAMEC), acquires the spatial position of the power lines. Then, the semi patch matching based on epipolar constraints (SPMEC) dense matching method is applied to automatically extract dense point clouds within the power line corridor. Obstacles can then be automatically detected by calculating the spatial distance between a power line and the point cloud representing the ground. Experimental results show that the PLAMEC automatically measures power lines effectively with a measurement accuracy consistent with that of manual stereo measurements. The height root mean square (RMS) error of the point cloud was 0.233 m, and the RMS error of the power line was 0.205 m. In addition, we verified the detected obstacles in the field and measured the distance between the canopy and power line using a laser range finder. The results show that the difference of these two distances was within ±0.5 m.

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“…UAV systems are flexible; digital cameras as well as video cameras are carried as UAV sensors [7]. Paper [8] comprehensively analyzed how computer vision technology is used in the operation and maintenance of transmission lines.…”

Section: Introductionmentioning

confidence: 99%

UAV Low Altitude Photogrammetry for Power Line Inspection

Zhang

Yuan

Fang

et al. 2017

IJGI

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When the distance between an obstacle and a power line is less than the discharge distance, a discharge arc can be generated, resulting in the interruption of power supplies. Therefore, regular safety inspections are necessary to ensure the safe operation of power grids. Tall vegetation and buildings are the key factors threatening the safe operation of extra high voltage transmission lines within a power line corridor. Manual or laser intensity direction and ranging (LiDAR) based inspections are time consuming and expensive. To make safety inspections more efficient and flexible, a low-altitude unmanned aerial vehicle (UAV) remote-sensing platform, equipped with an optical digital camera, was used to inspect power line corridors. We propose a semi-patch matching algorithm based on epipolar constraints, using both the correlation coefficient (CC) and the shape of its curve to extract three dimensional (3D) point clouds for a power line corridor. We use a stereo image pair from inter-strip to improve power line measurement accuracy by transforming the power line direction to an approximately perpendicular to epipolar line. The distance between the power lines and the 3D point cloud is taken as a criterion for locating obstacles within the power line corridor automatically. Experimental results show that our proposed method is a reliable, cost effective, and applicable way for practical power line inspection and can locate obstacles within the power line corridor with accuracy better than ±0.5 m.

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State-of-the-art review of computer vision for the management of power transmission lines

Cited by 40 publications

References 28 publications

Automatic Clearance Anomaly Detection for Transmission Line Corridors Utilizing UAV-Borne LIDAR Data

Automatic Clearance Anomaly Detection for Transmission Line Corridors Utilizing UAV-Borne LIDAR Data

Automatic Power Line Inspection Using UAV Images

UAV Low Altitude Photogrammetry for Power Line Inspection

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