Lamb wave-based damage assessment for CFRP composite structures using a CHMM-based damage localization algorithm and a damage quantitative expression

Abstract

Accurately and quantitatively monitoring the damages in composite structures is very challenging, but important for assessing their integrity. In this paper, an innovative damage location identification and size quantification assessment method based on Lamb wave is proposed for composite laminates. A continuous hidden Markov model (CHMM)-based damage scaling factor together with a weighted average imaging algorithm is adopted in damage location identification. To quantify the degree of structural deviation from the healthy state, the inconspicuous change of guided wave (GW) signal is converted to a CHMM-based damage scaling factor with significant change. Based on the damage scaling factors of all GW sensing paths, a weighted average imaging algorithm is performed to identify the most probable damage location. In addition, a damage quantitative mathematical expression is proposed to approximately estimate the size of circular-shaped damage founded on several different damage-related characterizations. The implementation of the proposed quantitative methodology is comparatively simple and straightforward for damage detection. Experiments on three composite panels with multiple damage cases are conducted to substantiate the proposed method. The sensor layers with embedded piezoelectric transducer (PZT) sensor networks surf-mounted on the structures are employed to excite and receive Lamb wave signals since their superiority of flexibility, electrical stability and apt for complex structures. The results demonstrate that the proposed algorithm is capable of pinpointing both the location and size of the circular-hole damage in composite structures.