Browse by author
Lookup NU author(s): Anthony Simm
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© 2026 Informa UK Limited, trading as Taylor & Francis Group. Accurate stress measurement in metallic structures is essential for structural health monitoring. However, conventional strain-gauge-based methods require direct contact and complex installation, limiting long-term and large-scale deployment. This study presents a non-contact stress sensing system based on an LC resonant circuit and a low-cost inductance-to-digital converter (LDC). Mechanical stress in ferromagnetic materials alters magnetic permeability and electrical conductivity, modifying the coil–material electromagnetic coupling and causing variations in resonant frequency fr and equivalent parallel resistance Rp. A planar PCB coil operating at approximately 2 MHz was integrated with an LDC1101-based acquisition system. The sensor was experimentally validated using industrial boiler water-wall tubes under tensile stresses from 83.3 to 333.3 MPa. Both fr and Rp exhibited monotonic responses to applied stress. Noise characteristics were quantitatively evaluated using power spectral density and Allan deviation analysis. With an optimized averaging time of 6.0 s, the minimum detectable stress reached 2.49 MPa under the 2σ criterion. The proposed approach combines dual-parameter extraction, quantitative noise evaluation, and resolution–latency optimization, providing a compact and cost-effective solution for non-contact static stress monitoring.
Author(s): Chen Z, Li J, Liu C, Liu D, Ooi PC, Zhang H, Guan K, Simm A, Peng Y
Publication type: Article
Publication status: Published
Journal: Nondestructive Testing and Evaluation
Year: 2026
Pages: Epub ahead of print
Online publication date: 16/08/2026
Acceptance date: 06/08/2026
ISSN (print): 1058-9759
ISSN (electronic): 1477-2671
Publisher: Taylor and Francis Ltd
URL: https://doi.org/10.1080/10589759.2026.2717411
DOI: 10.1080/10589759.2026.2717411
Altmetrics provided by Altmetric