A two-step method for delamination detection in composite laminates using experience-based learning algorithm

Abstract

Delamination in composite laminates reduces the structural stiffness and thus causes changes in the vibration responses of the laminates. Therefore, it is feasible to employ dynamic characteristics (such as natural frequencies and mode shapes) for delamination detection by using an optimization method. In the present study, a two-step method is proposed for the delamination detection in composite laminates using an experience-based learning algorithm. In the first step, one-dimensional equivalent through-thickness beam elements are employed to model the composite laminated beam and potential delamination locations are identified. In the second step, a typical three-dimensional finite mesh is utilized for the beam’s modeling and the detailed delamination information (including the delamination location, size, and interface layer) is detected. This two-step method combines the advantages of the two different modeling techniques and is able to significantly reduce the computational cost without reducing detection accuracy. The proposed method is applied for an eight-layer quasi-isotropic symmetric (0/-45/45/90)s composited beam with different delamination situations to verify its effectiveness and robustness. The performance of the two-step method is demonstrated by comparing with the one-step method and other three state-of-the-art algorithms (CMFOA, PSO, and SSA). Moreover, the influence of artificial noise on the accuracy of the detection performance is also investigated. Both numerical and experimental results confirm the superiority of the proposed method for delamination detection in composite laminates especially for the prediction of delamination interface.

Comparative study of dynamic parameters for damage identification of carbon fiber reinforced polymer tube

“…14,15 In recent years, there has been an increasing trend among scholars to utilize vibration-based methods for damage identification. 16,17 It is widely recognized that structural damage affects the mass, stiffness, and damping properties of a structure, consequently altering its vibrational response. 18,19 Based on the extracted damage identification features, the dynamic parameters are classified into four categories: natural frequency-based methods, mode shape-based methods, curvature/strain mode shapebased methods, and methods based on the combination of mode shape and frequency.…”

“…The dynamic characteristics of composite tube components play a crucial role in the analysis of their dynamic responses and are of great importance in vibration control 14,15 . In recent years, there has been an increasing trend among scholars to utilize vibration‐based methods for damage identification 16,17 . It is widely recognized that structural damage affects the mass, stiffness, and damping properties of a structure, consequently altering its vibrational response 18,19 .…”

A novel index for vibration-based damage detection technique in laminated composite plates under forced vibrations: experimental study

“…12,13 Damage detection algorithm developed by Sahin and Shenoi 14 was combined with local (curvature MSs) and global (changes in natural frequencies) vibrationbased analysis data as supplied to artificial neural network to assess the severity and location of damage in beam structure. Zheng, et al 15 conducted an optimization method for detection of different delamination situations in laminated composite structures by using experimental and numerical study. They stated that the dynamic characteristics (MSs and natural frequencies) can be used for delamination detection by applying an experience-based learning algorithm.…”

Delamination Localization in the Composite Thin Plates Using Ensemble Learning: Bagging and Boosting Techniques

“…Their analysis results indicated that the proposed method is in good agreement with the Hashin model. Zheng et al [30] proposed a twostep technique experience-based learning algorithm to identify delamination in composite beams. They used one-dimensional equivalent through-thickness beam elements to model the composite beam and to identify the potential delamination locations.…”