Detecting broken strands in transmission line — Part 2: Quantitative identification based on S-transform and SVM
作者： Yunfeng Xia , Xingliang Jiang , Jianlin Hu , Zhijin Zhang , Lichun Shu
DOI: 10.1002/ETEP.1668
关键词:
摘要: SUMMARY Strikes of lightning, corrosion chemical contaminants, ice shedding, wind vibration conductors, lines galloping and damage due to external forces may induce some fatal accidents such as broken transmission lines. The common means be used for latent faults inspection in is manually periodically examined by workers from commercial electrical power company. With the development both artificial intelligence technologies smart grid, method detecting strands line robot with detectors a good prospect. In this paper, eddy current transducer carried developed identification approach based on S-transform proposed. proposed utilizes extract module phase information at each frequency point detection signals. Through comparison, characteristic points are ascertained, fault signal constructed. confidence degree defined Shannon fuzzy entropy (SFE-BSICD). combines while utilizing information, SFE-BSICD energy, so reliability greatly improved. These qualities input support vector machine multi-classification, then number can determined. field experimental verification, it concluded that shows high accuracy reasonably. Copyright © 2012 John Wiley & Sons, Ltd.
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