We propose a peak seeking algorithm to extract the damage characteristic-variation of central wavelength to monitor the crack damage status in aluminum alloy plates using surface bonded fiber Bragg grating (FBG) sensors. The FBG sensors are sensitive to the uniform and non-uniform strain distribution along their longitudinal direction, and the effect appears in the power spectrum of the reflected light from the gauge section. In this paper, we propose a fast-self-adaptive multi-peak seeking algorithm to detect the central wavelength shifting of the FBG reflection spectrum with the crack propagation. The proposed peak searching algorithm results point to a significant improvement compared to other conventional methods. Then the central wavelength shifting is applied to explain the crack propagation behavior of the aluminum plates under quasi-static tensile test conditions. The different damages feature changing intervals which are associated with the crack position and the FBGs location, demonstrating that central wavelength shifting performs as an indicator to detect structural crack damage.

This study presents a novel monitoring method for hole-edge corrosion damage in plate structures based on Lamb wave tomographic imaging techniques. An experimental procedure with a cross-hole layout using 16 piezoelectric transducers (PZTs) was designed. The A0 mode of the Lamb wave was selected, which is sensitive to thickness-loss damage. The iterative algebraic reconstruction technique (ART) method was used to locate and quantify the corrosion damage at the edge of the hole. Hydrofluoric acid with a concentration of 20% was used to corrode the specimen artificially. To estimate the effectiveness of the proposed method, the real corrosion damage was compared with the predicted corrosion damage based on the tomographic method. The results show that the Lamb-wave-based tomographic method can be used to monitor the hole-edge corrosion damage accurately.

Piezoelectric (PZT) ceramic elements are often subjected to complex loads during in- service lifetime in structural health monitoring (SHM) systems, and debonding of both excitation actuators and receiving sensors have a negative effect on the monitoring signals. A first systematic investigation of debonding behaviors by considering actuators and sensors simultaneously was performed in this paper. The debonding areas of actuators were set in different percentage range from 0% to 70%, and sensors in 0%, 20%, 40% and 60%. The signal-based monitoring method was used to extract the characteristic parameters of both the amplitudes and phases of received signals. Experimental results revealed that as the debonding areas of the actuators increase, the normalized amplitude appears a quick decrease before 35% debonding area of actuators and then a slow rise until 60% of debonding reached. This may be explained that the 35% debonding turning point correspond to the coincidence of the excitation frequencies of peripheral actuators with the inherent frequency of the central piezoelectric sensor, and the 60% be the result of the maximum ability of piezoelectric sensor. The degrees of debonding of actuators and sensors also have significant influence on the phase angle offset, with large debonding of actuators increases the phase offset sharply. The research work may provide useful information for practical monitoring of SHM systems.

Adhesive and its aging can have influence on the Piezoelectric (PZT) elements in structural health monitoring (SHM) systems. However, the current research pays little attention to the effect of adhesives in SHM systems, and the mechanism of adhesive aging on monitoring signals is still unclear. In the present study, the relationship between types of adhesives, adhesive thickness, accelerated aging, and monitoring signal was analyzed in detail. The study was carried out with three kinds of epoxy resin AB adhesive (AW106, E-30CL, and E-120HP) and bonding thicknesses (0.01, 0.05, and 0.12 mm), and the elevated temperature was 100 °C for 45 days. The signal-based monitoring method was used to extract the characteristic parameters. The experimental results indicated that the standard shear strength and thickness of the adhesive may have a combined effect on the monitoring signal. Increasing the thickness may enhance the shear strength between PZT and the matrix. For the effectiveness of monitoring the signal propagation, however, increase in thickness may have a negative influence. Moreover, the elevated temperature will bring the signal amplitude to a peak in the first period of aging, and the highest point appears in 10 to 15 days. Nevertheless, with the increase of aging time, the adhesive will finally be degraded, resulting in the decrease of the signal amplitude. The experimental results may provide useful information for practical monitoring in the SHM field.

Corrosion damage to the aircraft structure can significantly reduce the safety performance and endanger flight safety. Especially when the corrosion occurs in a stress concentration region, such as hole edges, it can easily threaten the entire structure. In this paper, an on-line imaging qualitative monitoring algorithm based on piezoelectric sensors is proposed for detecting hole edge corrosion damage of porous aluminum alloy structures. The normalized amplitude is used to characterize the correlation between the initial Lamb wave signal and the damage signal, which is as an image reconstruction parameter in the algebraic iterative probability reconstruction algorithm. Moreover, a homogenization algorithm is proposed to process the reconstruction results. The experimental results of single hole and double hole corrosion for porous aluminum alloy plate show that the method can effectively achieve the location and quantification of corrosion damage to one and two holes of the porous structure.

Corrosion is a critical issue for engineered metallic components in mechanical and aerospace industries. Due to the complexity of aerospace aluminum alloy structure, corrosion is particularly tend to occur and expand in stress concentration areas, such as the edge of a hole, which causes the overall structure to be more likely to fail. In this paper, a Lamb wave-based active sensing method with improved sensors network was used to detect the hole-edge corrosion expansion. A0 wave packet of Lamb wave is extracted from signals, and two damage factors are used as characteristics of the signals. Probabilistic imaging algorithm is used to imaging and quantify the hole-edge corrosion area. Five corrosion extension tests show that the proposed method can effectively locate and quantify the hole-edge corrosion damage expansion of a single-hole structure; furthermore, the normalized amplitude damage index and phase change damage index can be used to predict hole-edge corrosion expansion effectively.