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Summary The long‐term service of composite structures and the difficulty of controlling the load environment can cause unavoidable damage and make online damage identification imperative. In this paper, a two‐step damage identification method for small penetrating damage in a fiber‐reinforced composite laminate based on combined active and passive monitoring concepts by using distributed piezoelectric and strain sensors is proposed. First, based on the lamb wave generated via active excitation, the alternating time‐reversal phase synthesis (ATRPS) method with an alternating excitation of each piezoelectric sensor is developed. By reversing the received signals in the time domain, thereby modulating the phase and superposition of all signals, the energy focus of the suspicious damage area is achieved. Second, the gradients between the strain measurements and the damage variables are derived. An optimization method based on the modified quasi‐Newton search (MQNS) method is adopted to identify the damage extent of the suspicious elements by minimizing the error of the strain information between the reference model and the damage model. Numerical and experimental cases are then presented to demonstrate the validity, accuracy, and efficiency of the proposed methodology. The robustness is assessed in detail through a discussion of important parameters and noisy interference.

Damage identification methods based on guided waves (GWs) have been widely researched in the field of aircraft structural health monitoring. Notably, the existing research has not extensively considered the realization of accurate damage localization in an unknown load environment, although this aspect is of significance to the real-time safety assessment of aircraft structures. To address this issue, we propose an adaptive damage imaging method based on GW signals for typical aircraft structures subjected to unknown workloads. First, through the GW signals and load data sampled in the working load range, a mathematical model between the characteristics of the GW signal and load is established. Second, the active GW signal is adaptively compensated by the real-time identified load through the passive strain signal during the service process of the structure. Finally, the alternating time-reversal phase synthesis (ATRPS) method is used to accurately locate the damage in the monitoring area. The feasibility, applicability, and accuracy of the proposed methodology are validated by three levels of experimental cases. All results consistently indicate that reliable damage localization can be achieved under an unknown load environment.

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