Operation Status Monitoring of Transmission Tower in Power System based on Data Fusion

Abstract

This paper studies the application of data fusion technology in power system to solve some difficult problems in this complex energy system. A transmission tower identification and bird nest detection method based on corner, line, color and shape features is proposed. Through LSD (Line Segment Detection) and Harris corner detection method, the straight line segment and corner point in the image are extracted respectively. Combined with triangle method, the actual tilt angle of tower is measured; According to the nesting rule of birds in transmission towers, the basic unit segmentation algorithm of transmission towers is proposed, and the basic unit segmentation of transmission towers is realized by using the local maximum of the target pixel row statistical histogram. The algorithm proposed in this paper can effectively solve the problems of on-line measurement of tilt angle of transmission tower and on-line detection of bird's nest, which will lay a theoretical foundation for on-line monitoring of transmission tower status.

Research on Tower Mechanical Fault Classification Method Based on Multiclass Central Segmentation Hyperplane Support Vector Machine Improvement Algorithm

“…Adjusting the parameter C controls the proportion of each class in the new dataset processed with the SMOTE algorithm. In this paper, the ratio of positive class to negative class samples should be controlled as 1:1, thus the parameter C should take the value of [1,1]. The introduced KNN algorithm must introduce the parameter k, which indicates that the value is taken for the k proximity sample points around each known sample point.…”

“…Severe weather and extreme terrain bring great challenges to long-distance transmission lines, and mechanical failures of transmission towers will lead to serious economic losses and even threaten personal safety. The excessive stress on the towers of transmission lines is the root cause of tower overturning and tower collapse [1]. To obtain the size of the tower strain, Huang et al of Xi'an Engineering University proposed a method based on a fiber optic grating sensor for tower stress monitoring of transmission lines, which mainly uses a grating fiber sensor attached to the surface of the measured pole and determines the size of the stress change by measuring the grating reflection wavelength or transmission wavelength.…”