Cited by 1Structural Health Monitoring TechniquesAeroelasticity and Vibration ControlControl Systems and Identification

DAMAGE LOCALIZATION AND MAGNITUDE ESTIMATION ON A COMPOSITE UAV WING VIA STOCHASTIC FUNCTIONALLY POOLED MODELS

ZHOU, PEIYUAN, KOPSAFTOPOULOS, OTIS·2022·Proceedings of the 13th International Workshop on Structural Health Monitoring

Abstract

A vibration-based active-sensing global SHM method is proposed and evaluated for its damage localization and quantification accuracy on complex wing structure. In the process, the wing structure is actuated by a white noise vibration and the response signals are collected by a distributed sensor network. The proposed SHM method first utilize auto-regressive exogenous (ARX) model [1] for representing the time-domain response at each sensor location under various damage conditions, where stochasticity contained in structural response is minimized and identified. ARX models are then mapped to damage parameter space via vector-dependent functionally pooled (VFP) method [2]. Then, a damage estimation algorithm based on minimizing VFP-ARX model prediction error is developed. Finally, the damage estimation results are evaluated as the possibility of leveraging multiple senor signal in SHM process is implicated.

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Crossref · 10.12783/shm2021/36240

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Cited by 1

Authors
ZHOU, P., & KOPSAFTOPOULOS, O.
Venue
Proceedings of the 13th International Workshop on Structural Health Monitoring
Published
2022-03-15
OpenAlex
W4312892798
Cited by
1
References
0
Citations by year
2023: 1
FWCI
0.86
Type
conference paper
Language
en
Open access
closed
Locations
International Workshop on Structural Health Monitoring (IWSHM) (publishedVersion)
Topics
  • Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
  • Physical Sciences › Engineering › Aerospace Engineering › Aeroelasticity and Vibration Control
  • Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
Keywords
damage localization, vibration-based structural health monitoring, active sensing, white noise excitation, sensor networks, ARX model, damage parameter identification, prediction error minimization

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