Enhanced permanently installed Magnetic Sensing for Condition Monitoring

Afnan Islam, Afnan Islam

Research output: Types of ThesisPhD

Abstract

Corrosion-induced structural degradation remains a paramount concern in the integrity management of oil and gas infrastructures, encompassing pipelines and pressure vessels. Traditional monitoring methods, such as sporadic ultrasonic thickness measurements, often prove inadequate under severe operational conditions. Furthermore, the nascent practise of using permanently affixed ultrasonic sensors introduces challenges associated with mechanical fatigue, thus undermining long-term reliability. TWI’s trailblazing work has introduced a magnetically coupled device designed for noninvasive thickness gauging in ferromagnetic structures. Although innovative, the prototype has shown limitations, particularly a confined measurement range of up to 4 mm in cast steel plates. This research significantly enhances the foundational concept of TWI by engineering an advanced magnetic sensor system that highly precise. Employing permanent magnets as the core sensing elements, the newly designed sensor is optimised for real-time condition monitoring and predictive analytics of ferromagnetic structures. Rigorous advancements have been made in the magnetic circuitry, including both the magnet and its yoke, corroborated through computational simulations and empirical validations. Additionally, the integration of graphene-based Hall sensors with nanotesla-level resolution as a tool has facilitated the accurate detection and categorisation of leakage flux patterns emanating from material defects and corrosion phenomena. The empirical results demonstrate a considerable improvement in system performance, most notably surpassing the previous 4 mm thickness measurement limitation. These advances underscore the transformative potential of developed magnetic sensor technology for robust and reliable structural health monitoring.
Original languageEnglish
Supervisors/Advisors
  • Tokhi, Mohammad, Supervisor, External person
  • duan, fang, Supervisor, External person
  • Zhao, Zhanfang, Supervisor
DOIs
Publication statusPublished - 2 Nov 2023

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