A Bayesian inference reliability evaluation on the corrosion-affected underground high-voltage power grid

Zhou, H. , Li, F., Le Blanc, M. and Pan, J. (2022) A Bayesian inference reliability evaluation on the corrosion-affected underground high-voltage power grid. International Journal of Reliability, Quality and Safety Engineering, 29(1), 2150042. (doi: 10.1142/s021853932150042x)

Abstract

The underground high-voltage power transmission cables are high value engineering assets that suffer from multiple deteriorations through-out life cycles. Recent studies identified a new failure mode – the pitting corrosion deterioration on the layer of phosphor bronze reinforcing tape, which protects the oil-filled power transmission cables from oil leakage due to deterioration of the leads heath. Two models estimating the phosphor bronze tape life were established separately in this study. The first model, based on mathematical fitting, is generated using a replacement priority model from the power supply industry. This is considered as an empirical-based model. The second model, based on the corrosion fatigue mechanism, utilizes the information of the pit depth distribution and the concept of pit-to-crack transfer probability. The Bayesian inference approach is the conjunction algorithm to update the existing probability of failure (PoF) model with the newly identified failure modes. Through this algorithm, the integrated PoF model contains a more comprehensive background information while maintaining the empirical knowledge on the engineering assets’ performance.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zhou, Dr Hang
• Authors: Zhou, H., Li, F., Le Blanc, M., and Pan, J.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: International Journal of Reliability, Quality and Safety Engineering
• Publisher: World Scientific Publishing
• ISSN: 0218-5393
• ISSN (Online): 1793-6446
• Copyright Holders: Copyright © 2022 World Scientific Publishing
• First Published: First published in International Journal of Reliability, Quality and Safety Engineering 29(1):2150042
• Publisher Policy: Reproduced in accordance with the publisher copyright policy