Robust deep Gaussian process-based trustworthy fog-haze-caused pollution flashover prediction approach for overhead contact lines

Jian Wang, Huiyuan Liu, Shibin Gao, Long Yu, Xingyang Liu, Dongkai Zhang and Lei Kou

Reliability Engineering and System Safety, 2024, vol. 243, issue C

Abstract: Due to completely open-air operation, fog-haze has become the main cause of contamination on the insulator surface of overhead contact lines (OCLs), further leading to pollution flashover and a series of serious risk consequences. To perceive the fog-haze-caused pollution flashover (FHPF) risk of OCL insulator, a robust deep Gaussian process (DGP)-based uncertainty-aware trustworthy prediction approach is proposed, incorporating epistemic and aleatoric uncertainties. In particular, aiming at the imbalanced dataset with limited fault samples, the prediction of FHPF risk is cast as a classification problem, and solved by DGP using stochastic gradient Hamiltonian Monte Carlo (SGHMC) inference. The key parameters are identified investigating the influences of fog-haze on insulator surface contamination. Furthermore, the SGHMC sampling-based inference is utilized to efficiently capture the intractable posterior distribution, dealing with uncertainty and enhancing the flexibility of the prediction approach. Finally, extensive experiments on high-speed railway line validate the effectiveness and superior of the proposed approach, compared to other advanced predictive classification methods. In addition, it cannot only capture the prediction uncertainty over a limited number of fault samples, but also achieve favorable prediction performance under unseen noisy environments, ultimately ensuring robust and trustworthy FHPF risk predictions for OCLs.

Keywords: Overhead contact lines; Fog-haze; Insulator; Deep Gaussian process; Limited fault sample; Probabilistic pollution flashover prediction; Uncertainty (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832023007433
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:243:y:2024:i:c:s0951832023007433

DOI: 10.1016/j.ress.2023.109829

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().