Baseline-free damage imaging for metal and composite plate-type structures based on similar paths

When a narrowband tone burst excitation signal is used to generate Lamb waves in the thin composite plates, a suitable frequency of the excitation signal is typically chosen to excite a solitary mode of Lamb wave in the structure. However, if and as the damage severity changes in the structure, it may be possible that the frequency of the excitation signal may influence the response metric. In the present work, the use of a chirp signal as an excitation signal for damage severity assessment is proposed. The use of a chirp signal as an excitation signal may prove suitable for damage severity assessment because the chirp response contains a large frequency bandwidth, and the cumulative effect of all the frequencies with the delamination is reflected in the damage index. The sensitivity of the chirp response to varying delamination sizes is investigated through numerical simulations and experiments. The damage index calculated using the chirp response showed a monotonic trend with an increase in damage severity, in contrast to a bidirectional trend of the damage index when conventional narrow excitation signals are used.

Section: Experimental Validationmentioning

confidence: 99%

Damage severity assessment in composite structures using multi-frequency lamb waves

Nandyala

Darpe

Singh

2022

“…J. Hettler et al 30 proposed a nonlinear damage feature without a reference signal and verified it through impact damage imaging. Qing et al 31 considered the similarity of excitation-receiving paths to calculate the damage factors and estimated the damage location through the probabilistic damage imaging method. However, the requirements for a dense sensor layout in the nonreference method cannot be satisfied in real structures.…”

Section: Introductionmentioning

confidence: 99%

Adaptive guided wave-based damage identification under unknown load conditions

Ding

Wang

et al. 2022

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.

“…Among the SHM methods, the guided wave-based SHM is considered as a promising damage monitoring technique because ultrasonic guided waves can travel over long distances and are sensitive to many types of damage. [2][3][4][5][6][7] In the guided wave-based SHM algorithms, damage diagnostic imaging algorithms have attracted much attention because they can display the damage of the structure in the form of two-dimensional plane, which can intuitively reflect the location of damage. In recent years, some representative algorithms are the tomography technique, 8,9 phased array method, 10 delay-and-sum algorithm, [11][12][13][14] correlation-based imaging technique, 15 model-based damage imaging using sparse reconstruction, 16 and probability-based diagnostic imaging (PDI) algorithm.…”

Section: Introductionmentioning

confidence: 99%

Probability-based diagnostic imaging with corrected weight distribution for damage detection of stiffened composite panel

Liu¹,

Wang²,

Wang³

et al. 2021

Due to no requirement for direct interpretation of the guided wave signal, probability-based diagnostic imaging (PDI) algorithm is especially suitable for damage identification of complex composite structures. However, the weight distribution function of PDI algorithm is relatively inaccurate. It can reduce the damage localization accuracy. In order to improve the damage localization accuracy, an improved PDI algorithm is proposed. In the proposed algorithm, the weight distribution function is corrected by the acquired relative distances from defects to all actuator–sensor pairs and the reduction of the weight distribution areas. The validity of the proposed algorithm is assessed by identifying damages at different locations on a stiffened composite panel. The results show that the proposed algorithm can identify damage of a stiffened composite panel accurately.