ReviewSensors (Basel, Switzerland)2026
Ultrasonic Assessment of Precursor Fatigue Damage in CFRP Composites: A Synthesis of Coda Waves, Nonlinear Indicators, Stress Relaxation, and Validation.
Review in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Carbon fiber-reinforced polymer composites can accumulate distributed microstructural damage before visible delamination or substantial stiffness loss becomes apparent. This article presents a program-based synthesis of six publications that examined precursor fatigue damage using guided coda waves, nonlinear guided waves, high-frequency pulse-echo ultrasonics, and scanning acoustic microscopy. The evidence comprises a separate incremental coda-wave campaign to 300,000 cycles and a coordinated fatigue-relaxation program conducted in three 75,000-cycle stages. Coda-wave interferometry detected progressive propagation changes while the first-arriving guided-wave packets remained largely unchanged. Nonlinear measurements showed changes in second- and third-order parameters and sideband peak counts, while the guided-wave nonlinear response decreased by as much as 26.8% during the 8 h unloaded period. This result demonstrates that post-loading measurement time must be controlled when transient stress-related and persistent damage-related responses are compared. Within the specific Route II material system and loading protocol, the 5 Hz specimens exhibited greater degradation than the 2 and 10 Hz specimens. This frequency ranking is not proposed as a general relationship for CFRP composites. Residual-strength testing, microscopy, and SAM provided convergent supporting evidence, but the overlapping datasets and small specimen groups do not constitute independent statistical replication. The proposed framework therefore demonstrates laboratory-scale sensitivity to precursor material-state changes but does not yet provide reliable prediction of residual strength, remaining fatigue life, or probability of failure. Field implementation will require larger independent datasets, uncertainty estimation, environmental compensation, repeated sensor installations, and validation on representative structural components.
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