The tomography technique is an effective way to quantitatively evaluate damage from reconstruction imaging in structure health monitoring (SHM). The reconstruction algorithm for the probabilistic inspection of damage (RAPID) algorithm based on the signal difference coefficient (SDC) feature is a promising approach due to its superior performance. This paper focuses on the influence of different patterns of PZT (Lead Zirconate Titanate) sensor array configurations, i.e., the circular, square, and parallel array, on reconstruction image qualities for evaluating hole and crack damage. Variable shape parameters are applied to account for the unequal damage distances of different actuator-sensor pairs. Considering the directionality scattering fields of cracks, the angular scattering pattern of the SDC values are studied by simulation. The SDC variations for different groups of sensing paths at the same actuator are applied to predict the crack orientation. An improved RAPID algorithm is proposed by defining an additional SDC value of 1 in the path along the predicted crack orientation, which is determined by the point of the actuator causing the minimal SDC variation and the center point of the initial reconstruction image of the crack. The results show that the improved RAPID algorithm is effective for the evaluation of crack damage. Reconstruction image qualities with three PZT sensor array configurations for both holes and cracks are compared. The research is significant for selecting the PZT sensor array configuration in SHM.

Piezoelectric fiber rosettes respond to the directivity characteristics of Lamb waves, and therefore, are useful in detecting the Lamb wave propagation direction. Considering material damage as a secondary wave source, two piezoelectric fiber rosettes are arranged to measure the scattered wave propagation directions for damage localization. The influences of various rosette configurations, i.e., 45°‐rectangular, 135°‐rectangular, 60°‐delta, and 120°‐delta, on the estimation accuracy of the propagation direction are investigated in this paper. The response of the piezoelectric fiber to the A₀ mode Lamb wave under narrowband tone‐burst excitation is theoretically derived. Experimental tests and piezoelectric coupling simulations are performed to obtain the Lamb wave signal of each fiber. The matching pursuit (MP) algorithm is applied to extract the weak damage‐related wave packet by using Hann‐windowed narrowband excitation as an atom. The Lamb wave propagation directions are estimated based on the error function. The accuracies of the directions with 4 types of rosette configurations are compared, and their error sources are discussed. The results show that the accuracy of the 135°‐rectangular configuration is relatively satisfactory, and the errors depend on the size and location of each fiber in the rosette. The proposed damage localization method is validated by experimental tests. The predicted locations are close to the actual damage location. The research results are significant for piezoelectric fiber rosette design and optimization and damage location without wave speed or time‐of‐flight information in complex or irregular structures.

Impact damage localization is crucial in aircraft structural health monitoring. The integration of ultrasonic guided waves (UGW) and piezoelectric sensors offers a promising solution for monitoring aircraft structures. However, the challenge lies in the UGW signals generated by external impacts on plate structures, characterized by significant background noise, wide frequency bandwidth, multimodal interference, and inherent frequency dispersion. These complexities hinder the direct extraction of characteristic signals for impact localization in both time and frequency domains. Impact-induced UGW signals typically exhibit Gaussian amplitude-modulated and frequency-modulated (AM-FM) characteristics. Addressing this challenge, this paper introduces the Gaussian Reconstructed Symplectic Geometry Mode Decomposition (GRSGMD) method. GRSGMD combines power spectral density analysis and the Gaussian mixed-model clustering algorithm, to improve the discriminant function of the Symmetric Geometry Component (SGC). This study investigates the decomposition performance and noise robustness of GRSGMD through simulated impact-induced UGW signals. Based on the adaptively extracted dominant energy narrowband of impact-induced UGW using GRSGMD, an impact source localization method is proposed, and verification experiments on aluminum plate impact localization are conducted. The results show that the GRSGMD method can effectively and adaptively extract the dominant energy narrowband of impact-induced UGW. The dominant energy narrowband of low-speed impact-induced UGW corresponds to the A ₀ mode Lamb wave. Experimental results for impact source localization using GRSGMD align well with actual positions. The research findings contribute to providing an efficient and feasible signal processing method for impact monitoring based on UGW.