Online sensing method for transmission line conductor ice cover based on fiber optic sensing information fusion and continuous wavelet decomposition

• Published in: Optical and quantum electronics Vol. 56; no. 9
• Main Authors: Jia, Boyan, Xia, Yanwei, Liu, Hongliang, Xu, Yabing, Yi, Xiaoyu
• Format: Journal Article
• Language: English
• Published: New York Springer US 18.08.2024; Springer Nature B.V
• Subjects: Characterization and Evaluation of Materials; Computer Communication Networks; Conductors; Continuous fibers; Data integration; Decomposition; Electrical Engineering; Feature extraction; Fiber optics; Ice cover; Ice formation; Lasers; Line spectra; Neural networks; Optical Devices; Optical fibers; Optics; Photonics; Physics; Physics and Astronomy; Regression models; Signal classification; Transmission lines; Vibration; Vibration perception; Wavelet transforms; Continuous wavelet decomposition; Fiber optic sensing; Transmission line; Online sensing; Information fusion; Conductor ice cover
• DOI: 10.1007/s11082-024-07308-4
• ISSN: 1572-817X; 0306-8919

At present, the identification of icing status of transmission line conductors is mainly manual. Although the mainstream method based on intelligent vision and UAV can solve the manual problem, the specific situation of conductor icing cannot be further mastered. Based on the information fusion of optical fiber sensor and continuous wavelet decomposition, the online sensing method of transmission line icing is studied. This method uses the transmission line conductor vibration and stress signal acquisition method based on distributed optical sensing technology. After the transmission line conductor vibration and stress signals are collected online by multiple optical fiber sensors, the fusion model based on Elman neural network is used to fuse the multiple optical fiber sensing information, and then the spectrum feature extraction method of optical fiber sensing signal based on continuous wavelet decomposition is used. The spectral characteristics of fused optical fiber sensing signals are extracted as diagnostic samples of the online perception method of conductor icing based on improved logical regression, and the binary classification method is used to identify whether there is icing problem on transmission line conductors online. In the experiment, this method can accurately perceive the online perception results of rime type icing, mixed rime type icing, wet snow type icing, and has the function of accurately sensing the icing status of transmission line conductors.