Integrated multimodal structural health monitoring and feature fusion for fatigue damage assessment in open-hole woven composites

Woven composites are extensively used in aerospace, marine, and energy infrastructure systems. In these systems, the early-stage evolution and characterization of fatigue damage remain challenging due to inherent material heterogeneity. Although the evolution of such damage has been widely studied using various structural health monitoring (SHM) techniques, an unified, robust quantification using multiple SHM modalities remains limited. This study addresses these specific challenges by proposing a novel synergistic monitoring framework that combines X-ray microtomography, digital image correlation (DIC), acoustic emission (AE), guided waves (GW), and electromechanical impedance (EMI) for fatigue damage assessment in open-hole woven composite laminates. The results show that individual SHM techniques exhibit varying sensitivities to different fatigue stages, including damage initiation, progression, and pre-failure. The trend of AE-based parameters, characterizes different damage stages. Furthermore, EMI and GW are found to be more sensitive to incipient stiffness degradation and damage progression. The study also proposes incorporating an in-service baseline to improve field feasibility and more effectively detect damage. Microtomography and DIC analyses have been performed to interpret surface features, damage morphology, and micro-crack evolution. Further, a novel feature-fusion approach based on physically-constrained Bayesian-tuned particle swarm optimization (PcB-PSO) has been proposed to enhance sensitivity and improve damage quantification. The PcB-PSO-based fused damage indicators achieved a strain correlation magnitude of 92.09% and demonstrated high sensitivity in detecting incipient and severe damage scenarios. The practical implications of this study are essential for next-generation fused SHM systems and for selecting suitable monitoring strategies for predictive maintenance of structures.