A Machine Vision Based Approach for Sag Measurement in Power Lines

Subject Areas : Renewable energy

Mohammad Javad Abdollahifard ¹ ( Computer Vision and Remote Sensing Research Lab- Department of Electrical Engineering Department, Tafresh University, Tafresh, Iran )
Mohammad Reaz Mehrdad ² ( Computer Vision and Remote Sensing Research Lab- Department of Electrical Engineering Department, Tafresh University, Tafresh, Iran )

Received: 2022-04-05 Accepted : 2022-06-22 Published : 2023-11-22

Keywords: power line detection, sag measurement, vision-based measurement, surveying,

Abstract :

The supply of permanent electrical energy is of vital importance in modern life and its disruption can cause heavy damage to different areas in industry, commerce, transportation, sanitation and health, education, and management of the society. To prevent the network from short-circuiting to the ground, the amount of sag (drop) of the conductors must be within a standard range. Existing methods for sag measurement often require permanent installation of equipment - such as a camera, GPS receiver, and magnetic field sensor - on the line, the poles/towers, and/or around them. The method presented in this paper performs sag measurement based on a single image recorded from the conductor and poles/tow­ers on its both sides. In addition, the distance between the two ends of the conductor from the camera needs to be measured using a laser rangefinder. First, the position of the two ends of the conductor in three-dimensional space is obtained with the help of rangefinder data. Then, from all the parabolas that pass through these two points, the one that best matches the visual observations and field assumptions is selected, and based on that, the three-dimensional conductor model is generated and the sag is calculated. The proposed measurement method can be done without interruption of the network and dangerous approach to the line and with the help of portable and inexpensive equipment. Evaluation on laboratory and field data showed that the proposed method is not sensitive to the shooting angle, works well in complicated backgrounds, and has an average error of less than 1% of the sag value.

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