Assessment of the Supporting Structures on the Basis of Images

Zator, S.; Gasz, Rafał

doi:10.14313/par_222/23

Cited by 2 publications

(1 citation statement)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recognising the condition of electricity infrastructure objects in digital images creates a wide range of potential applications. These may include [ 29 , 31 , 32 , 33 ]: precise measurements of the position of line structural elements, monitoring to support early warning systems, condition monitoring, and fault localisation in high-voltage networks, identification of line hazards arising from the immediate environment. The data collected during a ground inspection are usually images obtained using various cameras.…”

Section: Introductionmentioning

confidence: 99%

Detection of Power Line Insulators in Digital Images Based on the Transformed Colour Intensity Profiles

Tomaszewski

Gasz

Osuchowski

2023

Sensors

View full text Add to dashboard Cite

Proper maintenance of the electricity infrastructure requires periodic condition inspections of power line insulators, which can be subjected to various damages such as burns or fractures. The article includes an introduction to the problem of insulator detection and a description of various currently used methods. Afterwards, the authors proposed a new method for the detection of the power line insulators in digital images by applying selected signal analysis and machine learning algorithms. The insulators detected in the images can be further assessed in depth. The data set used in the study consists of images acquired by an Unmanned Aerial Vehicle (UAV) during its overflight along a high-voltage line located on the outskirts of the city of Opole, Opolskie Voivodeship, Poland. In the digital images, the insulators were placed against different backgrounds, for example, sky, clouds, tree branches, elements of power infrastructure (wires, trusses), farmland, bushes, etc. The proposed method is based on colour intensity profile classification on digital images. Firstly, the set of points located on digital images of power line insulators is determined. Subsequently, those points are connected using lines that depict colour intensity profiles. These profiles were transformed using the Periodogram method or Welch method and then classified with Decision Tree, Random Forest or XGBoost algorithms. In the article, the authors described the computational experiments, the obtained results and possible directions for further research. In the best case, the proposed solution achieved satisfactory efficiency (F1 score = 0.99). Promising classification results indicate the possibility of the practical application of the presented method.

show abstract

Section: Introductionmentioning

confidence: 99%