Power Line Detection Research Articles

Crack Detection of Power Line Based on Metal Magnetic Memory Non-destructive

Visual inspection method using helicopter equipped with infrared and ultraviolet camera is often employed to check the transmission status of power line, but it is so expensive and unsafe relative to using power line robot to implement crack detection of power line. In this paper a new measuring method is proposed using metal magnetic memory non-destructive (MMMNDT) to to automatically detect defects or abnormal conditions based on a completely autonomous mobile platform capable of a meaningful payload for signal data processing. In this work one kind of brand-new mechanical structure has been designed for inspection robot, and some important parts of the mechanical structure have been fully explained. At the same time, a detection system of the robot has been designed based on MMMNDT. The results of experiments about the crack detection of power line show that the robot can satisfactorily span obstacles automatically and fulfill the specified inspection tasks, experiment results of the detection system verified that this diagnosis system is feasible and can be applied to power line detection.

Underground Power Cable Detection and Inspection Technology Based on Magnetic Field Sensing at Ground Surface Level

In this paper, a novel technique based on magnetic field sensing is proposed for underground power cable detection and inspection. In this technique, the current sources of the underground power cables are reconstructed based on a set of measured magnetic field values at the ground surface level emanated by the electric currents carried by the underground power cables. The stochastic optimization technique developed with an artificial immune system algorithm is applied to realize the reconstruction. The principle of this method was proved and verified experimentally by our laboratory setup. Application of this method was demonstrated on the simulation models of 11- and 132-kV underground power cables. The reconstruction results of the electrical and spatial parameters of the cables match accurately with the actual source parameters of the cables in the models. This paper shows that the proposed method is able to remotely detect the horizontal locations and vertical depths of underground power cables with high accuracy at the ground surface level requiring no prior knowledge about the exact locations of the cables. Thus, it can be potentially used to develop a portable locator for providing a map of the underground electrical cables by simultaneous detection of multiple power lines. This method can also enable engineers to correctly inspect the operation states of the target cables during onsite maintenance. This technique is applicable to various laying conditions and cable configurations (three core or single core) of the underground power cables. In addition, this is an entirely passive method and does not need any signal injection into the cables.

Object-aware power line detection using color and near-infrared images

Vision-based power line detection (PLD) is an important yet challenging problem in low-altitude flight. Different from the traditional PLD methods, which only aim at line information, we propose a novel object-aware PLD method to obtain better detection performance. A new definition of power line is first proposed to present its object-aware properties; and then a cascaded PLD scheme is devised with line detection, region filtration, and object validation based on corresponding image cues in joint color (RGB) and near-infrared (NIR) images. Considering that the primary goal of PLD is to capture all potential information and decrease the false negatives, we first treat the universal line shape in pixel from joint RGB-NIR images as a basic feature to explore general line candidates. To further pick out the accurate regions occupied by power lines, on the one hand we filter the false candidates based on the region-based intensity of special material characteristics in NIR, and on the other hand we validate the power lines according to the color features in RGB. The experiments demonstrate the advantages of our proposed method in three aspects: good detection accuracy, high true detection rate, and low false detection rate.

A novel design of inspection robot for high-voltage power lines

Purpose – In this article, a detailed design of a novel power line inspection robot is studied. This robot can be used to move on ground wires for special purposes such as inspection and fault detection of electric power lines. The paper aims to discuss these issues. Design/methodology/approach – Designed active and passive mechanisms in the proposed robot enable it to move over various obstacles on ground wires, such as clamps, warning balls and mast tips. Indeed, this robot is the first designed robot with the capability of moving over all ground wire obstacles. The active mechanisms contain seven rubber-coated rollers (i.e. four vertical rollers and three horizontal rollers) as well as three mechanisms in order to make horizontal rollers move vertically. The passive mechanisms also include a set of spring-dampers installed in each joint of robot arms. Findings – The simulation results in the ADAMS software revealed a desirable stability of performance when moving on the ground wires with a maximum slope of 30-degree. Also, the robot showed a suitable performance when passing over the warning balls (with a maximum diameter of 700 mm), rectangular mast tips (170×170 mm) and mast tips with a 30-degree twist in the horizontal plane. Practical implications – The feasibility of these maneuvers is proved with a prototype implementation and successful test results. This robot is approximately 60 kg weight and can move in ground wires with maximum speed of 20 m/min. Originality/value – The proposed robot is able to move on ground cable and pass over different kinds of obstacles like warning balls and mast tips (straight and angular) with maximum speed of 20 m/min.

비행장애물 회피를 위한 라이다 기반 송전선 고속탐지 및 적용가능성 분석

Abstract Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a f iltering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.Keywords : LIDAR, Flight Obstacle, Power Line, Avoidance, Detection, Realtime, Fast

Power line detection from optical images

Image-based power line detection is highly important for threat avoidance when the aerial vehicles fly in low altitude. However, it is very challenging for the requirements of high detection rates, low false alarms and real-time application. In this paper, a sequential local-to-global power line detection algorithm is proposed. In the local criterion, a line segment pool is detected by morphological filtering an edge map image, which is computed based on matched filter (MF) and first-order derivative of Gaussian (FDOG). It results in over detection to guarantee high detection rates. In the next global criterion, grouping the line segments into whole power lines is formulated as a graph-cut model based on graph theory. The principal advantage of the proposed algorithm is that it can detect not only the straight power lines but also the curve ones. Experimental results demonstrate that the algorithm has good performances both in detection accuracy and in processing time.

LiDAR 데이터와 RANSAC 알고리즘을 이용한 철도 전력선 자동탐지에 관한 연구

LiDAR 측량은 고밀도로 정확하게 거리를 측정하는 장점 때문에 지표면과 지표면 위의 객체를 3D 모델링하는데 사용되는 주요기술 중의 하나이다. 본 연구의 목적은 고밀도 LiDAR 데이터와 RANSAC 알고리즘을 이용하여 자동으로 철도전력선을 탐지하고 모델링하는 방법을 개발하는데 있다. 철도전력선을 탐지하기 위하여 레이저 데이터의 다중반사 특성과 철도전력선에 대한 형상정보를 이용한다. 이를 위한 프로세스는 최초 단위라인을 찾기 위한 직육면체 분석과 라인 추적, 연결 그리고 색인 작업으로 구성되며, 반복 RANSAC과 라인 파라미터를 구하기 위한 최소제곱법이 모델링을 위하여 사용된다. 철도전력선의 경우에는 정확도 확인을 위한 실측자료를 구하는 것이 매우 힘들어서 정량적인 정확도 평가가 어려우나 모델에 대한 레이저점군의 표준편차는 x-y 및 z 좌표 각각 8cm와 5cm로 양호하였고, 육안 검사에 의한 완성도면에서도 원 데이터와 비교할 때 모든 철도전력선 라인이 탐지 및 모델링된 것을 알 수 있었다. 본 연구에서 제시하는 방법의 모든 과정은 완전히 자동화하였으며, 특히 다수의 전력선이 복잡하게 설치된 지역에서도 적용될 수 있도록 개발하였다. LiDAR has been one of the widely used and important technologies for 3D modeling of ground surface and objects because of its ability to provide dense and accurate range measurement. The objective of this research is to develop a method for automatic detection and modeling of railroad power lines using high density LiDAR data and RANSAC algorithms. For detecting railroad power lines, multi-echoes properties of laser data and shape knowledge of railroad power lines were employed. Cuboid analysis for detecting seed line segments, tracking lines, connecting and labeling are the main processes. For modeling railroad power lines, iterative RANSAC and least square adjustment were carried out to estimate the lines parameters. The validation of the result is very challenging due to the difficulties in determining the actual references on the ground surface. Standard deviations of 8cm and 5cm for x-y and z coordinates, respectively are satisfactory outcomes. In case of completeness, the result of visual inspection shows that all the lines are detected and modeled well as compare with the original point clouds. The overall processes are fully automated and the methods manage any state of railroad wires efficiently.

Power line detection from synthetic aperture radar imagery using coherence of co-polarisation and cross-polarisation estimated in the Hough domain

Power lines are an important target type in topographic mapping, as well as in post-disaster and post-strike damage detection. A method of detecting power lines from polarimetric synthetic aperture radar (POLSAR) data using the coherence between the co- and cross-polarisation is proposed based on the azimuth symmetry of the clutter. First, the scattering of power lines is analysed from the aspects of radar cross-section and polarimetric response. Next, the covariance and coherence between the co- and cross-polarisation of power lines and clutter are characterised, and a constant false-alarm rate detector based on the coherence statistics is proposed. In order to obtain a high accuracy, the coherence is estimated in the Hough domain, and the proposed method is improved by considering the sign of the polarimetric orientation angle and using only the real part of the coherence. In addition, the coherence in the special case of azimuth symmetrical power lines is estimated using rotated scattering matrix. Finally, the proposed detector is demonstrated using both simulated and real P-band POLSAR data.

FAST POWER LINE DETECTION AND LOCALIZATION USING STEERABLE FILTER FOR ACTIVE UAV GUIDANCE

Abstract. In this paper we present a fast power line detection and localisation algorithm as well as propose a high-level guidance architecture for active vision-based Unmanned Aerial Vehicle (UAV) guidance. The detection stage is based on steerable filters for edge ridge detection, followed by a line fitting algorithm to refine candidate power lines in images. The guidance architecture assumes an UAV with an onboard Gimbal camera. We first control the position of the Gimbal such that the power line is in the field of view of the camera. Then its pose is used to generate the appropriate control commands such that the aircraft moves and flies above the lines. We present initial experimental results for the detection stage which shows that the proposed algorithm outperforms two state-of-the-art line detection algorithms for power line detection from aerial imagery.

An Algorithm for Power Line Detection and Warning Based on a Millimeter-Wave Radar Video

Power-line-strike accident is a major safety threat for low-flying aircrafts such as helicopters, thus an automatic warning system to power lines is highly desirable. In this paper we propose an algorithm for detecting power lines from radar videos from an active millimeter-wave sensor. Hough Transform is employed to detect candidate lines. The major challenge is that the radar videos are very noisy due to ground return. The noise points could fall on the same line which results in signal peaks after Hough Transform similar to the actual cable lines. To differentiate the cable lines from the noise lines, we train a Support Vector Machine to perform the classification. We exploit the Bragg pattern, which is due to the diffraction of electromagnetic wave on the periodic surface of power lines. We propose a set of features to represent the Bragg pattern for the classifier. We also propose a slice-processing algorithm which supports parallel processing, and improves the detection of cables in a cluttered background. Lastly, an adaptive algorithm is proposed to integrate the detection results from individual frames into a reliable video detection decision, in which temporal correlation of the cable pattern across frames is used to make the detection more robust. Extensive experiments with real-world data validated the effectiveness of our cable detection algorithm.

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.

94 GHz Folded Fresnel Reflector Using C-Patch Elements

A 94 GHz folded Fresnel reflector (FFR) for helicopter collision avoidance Radar is presented. The antenna system consists of a primary source illuminating a semi-reflecting grid that reflects the primary source polarization toward the main reflector opposite the grid. The main reflector has two functions. It focuses the field in the desired direction and rotates the incident polarization by 90 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">deg</sup> to enable it to pass through the grid and radiate. Specific patch elements having a C-shape have been designed for this purpose. In order to increase overall efficiency, the reflector combines 8 correcting zones in its center and 4 at the periphery. The reflector is manufactured using standard photolithographic techniques. The primary source consists of a metal waveguide covered with a small frequency selective surface (FSS) for matching purposes. The maximum measured gain is 36.5 dBi at 94 GHz. The maximum side lobe level is -18 dB. The return loss value does not exceed -25 dB. The frequency bandwidth -3 dB in gain and return loss is 10%. In-flight measurements were conducted demonstrating the ability to detect power lines at distances up to 680 m.

Processing of laser scanner data—algorithms and applications

Airborne laser scanning systems are opening new possibilities for surveys and documentation of difficult areas and objects, such as dense city areas, forest areas and electrical power lines. Laser scanner systems available on the market are presently in a fairly mature state of art while the processing of airborne laser scanner data still is in an early phase of development. To come from irregular 3D point clouds to useful representations and formats for an end-user requires continued research and development of methods and algorithms for interpretation and modelling. This paper presents some methods and algorithms concerning filtering for determining the ground surface, DEM, classification of buildings for 3D City Models and the detection of electrical power lines. The classification algorithms are based on the Minimum Description Length criterion. The use of reflectance data and multiple echoes from the laser scanner is examined and found to be useful in many applications.

Millimeter-wave radar phenomenology of power lines and a polarimetric detection algorithm

The radar phenomenology of high-voltage power lines and cables is studied for examining the feasibility of detecting power lines along the path of a low-flying aircraft using a millimeter-wave radar system. For this purpose, polarimetric backscatter measurements of power line samples of different diameters and strand arrangements were performed over a wide range of incidence angles with very fine increments at 94 GHz. Also, similar polarimetric backscatter measurements were conducted for cylinders of the same radii and lengths as the power line samples for identifying the scattering features caused by the braiding structure of the power lines. In addition, the effects of a thin layer of water and a layer of ice over the power line surface on its polarimetric scattering behavior are studied by repeating the polarimetric backscatter measurements. Based on this phenomenological study, a polarimetric detection algorithm that makes use of the scattering features caused by the braided structure of power lines is proposed. It is shown that the proposed algorithm is capable of detecting power lines in a relatively strong clutter background with a poor signal-to-clutter ratio. The performance of the algorithm is demonstrated experimentally using a rough asphalt surface and a vegetation foliage as sample clutter backgrounds.