PSI - Issue 80

Available online at www.sciencedirect.com Available online at www.sciencedirect.com Available online at www.sciencedirect.com

ScienceDirect

Procedia Structural Integrity 80 (2026) 43–52 Structural Integrity Procedia 00 (2023) 000–000 Structural Integrity Procedia 00 (2023) 000–000

www.elsevier.com / locate / procedia www.elsevier.com / locate / procedia

© 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Ferri Aliabadi Abstract Fatigue crack initiation and propagation pose critical challenges to structural integrity assessment, particularly in safety-critical applications where reliable in-service monitoring is essential. Previous studies have demonstrated the feasibility of baseline-free crack detection using higher-order harmonic parameters, specifically the second harmonic parameter ( β ′ ) and the third harmonic parameter ( γ ′ ). While these parameters showed the potential for online in-service crack detection, their fluctuations and the dependence of the first stage on sensor bonding conditions, thereby limiting ro bustness and interpretability. To address these limitations, the present study introduces an alternative feature based on the root mean square (RMS) value of time-domain signals for baseline-free in-service crack monitoring. owing to its direct reflection of the signal content, the RMS features demonstrates greater stability and reliability compared with harmonic based parameters. The Dynamic Piecewise Linear (DPL) method was employed to analyze RMS data obtained from fatigue experiments conducted on multiple specimens. Results reveal that the RMS change can be clearly divided into two stages, with the critical transition point closely coinciding with the experimentally observed crack initiation. Further more, the proposed approach successfully identified cracks smaller than 2 mm, yielding consistent detection outcomes across di ff erent specimens and sensor configurations. Most importantly, the RMS-based method exhibited insensitivity to sensor bonding conditions, thereby addressing one of the primary shortcomings of harmonic-based approaches. This study confirms the feasibility of using RMS as a robust and interpretable feature for baseline-free online crack detec tion. The observed two-stage evolution and the consistency of detection across varying test conditions provide a solid foundation for the practical implementation of structural health monitoring (SHM) systems in engineering applications. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of Professor Ferri Aliabadi. Keywords: Baseline free; In-service crack detection; Harmonic parameter; Root mean square (RMS); Dynamic Piecewise Linear (DPL); Structural health monitoring (SHM) Abstract Fatigue crack initiation and propagation pose critical challenges to structural integrity assessment, particularly in safety-critical applications where reliable in-service monitoring is essential. Previous studies have demonstrated the feasibility of baseline-free crack detection using higher-order harmonic parameters, specifically the second harmonic parameter ( β ′ ) and the third harmonic parameter ( γ ′ ). While these parameters showed the potential for online in-service crack detection, their fluctuations and the dependence of the first stage on sensor bonding conditions, thereby limiting ro bustness and interpretability. To address these limitations, the present study introduces an alternative feature based on the root mean square (RMS) value of time-domain signals for baseline-free in-service crack monitoring. owing to its direct reflection of the signal content, the RMS features demonstrates greater stability and reliability compared with harmonic based parameters. The Dynamic Piecewise Linear (DPL) method was employed to analyze RMS data obtained from fatigue experiments conducted on multiple specimens. Results reveal that the RMS change can be clearly divided into two stages, with the critical transition point closely coinciding with the experimentally observed crack initiation. Further more, the proposed approach successfully identified cracks smaller than 2 mm, yielding consistent detection outcomes across di ff erent specimens and sensor configurations. Most importantly, the RMS-based method exhibited insensitivity to sensor bonding conditions, thereby addressing one of the primary shortcomings of harmonic-based approaches. This study confirms the feasibility of using RMS as a robust and interpretable feature for baseline-free online crack detec tion. The observed two-stage evolution and the consistency of detection across varying test conditions provide a solid foundation for the practical implementation of structural health monitoring (SHM) systems in engineering applications. 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of Professor Ferri Aliabadi. Keywords: Baseline free; In-service crack detection; Harmonic parameter; Root mean square (RMS); Dynamic Piecewise Linear (DPL); Structural health monitoring (SHM) Fracture, Damage and Structural Health Monitoring A baseline-free method for in-service crack detection under complex loading conditions YuhangPan a, ∗ , Zahra Sharif Khodaei 1 , Ferri M.H. Aliabadi a a Department of Aeronautics, Imperial College London, South Kensington Campus, City and Guilds Building, Exhibition Road, SW7 2AZ, London, UK Fracture, Damage and Structural Health Monitoring a, ∗ , Zahra Sharif Khodaei 1 , Ferri M.H. Aliabadi a a Department of Aeronautics, Imperial College London, South Kensington Campus, City and Guilds Building, Exhibition Road, SW7 2AZ, London, UK

∗ Corresponding author. Tel.: + 44 (0) 771-392-0325. E-mail address: y.pan21@imperial.ac.uk ∗ Corresponding author. Tel.: + 44 (0) 771-392-0325. E-mail address: y.pan21@imperial.ac.uk

2452-3216 © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Ferri Aliabadi 10.1016/j.prostr.2026.02.005 2210-7843 © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of Professor Ferri Aliabadi. 2210-7843 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of Professor Ferri Aliabadi.