Damage assessment of CFRP composites using a time–frequency approach

Abstract

A damage assessment methodology using a time–frequency signal processing technique is presented in this article. Delaminations are detected in composite structures with multiple stiffeners. Because Lamb waves are complex in nature, due to wave dispersion and scattering, a robust signal processing technique is required to extract features from Lamb wave signals. In this article, the matching pursuit decomposition algorithm is used for extracting wavelets from the Lamb wave signals in the time–frequency domain. A small time–frequency atom dictionary is defined to avoid the exhaustive search over the time–frequency domain and to reduce the computation costs. The propagation characteristics of Lamb waves in stiffened composite panels are investigated. The delaminations are detected by identifying the converted Lamb wave modes introduced by the structural imperfection. A two-step damage detection approach, which uses both pulse-echo and pitch-catch active sensing schemes, is developed for the identification of delaminations. The delamination is quantified using a signal energy-based damage index. The matching pursuit decomposition algorithm is further used to localize the delamination position by solving a set of nonlinear equations. The results show that the matching pursuit decomposition algorithm can be used to identify and localize the seeded delaminations in composite structures with complex geometries and material properties.

Multiscale Modeling of Advanced Materials for Damage Prediction and Structural Health Monitoring

“…(Guo and Cawley, 1993;Liu et al, 2012). In the case of a low velocity impact, matrix cracking is often present surrounding the delaminations (Hiche et al, 2009;Liu and Chattopadhyay, 2013), as seen in Figure 5.5.…”

A New Structural Damage Identification Method Based on Wavelet Packet Energy Entropy of Impulse Response

“…Therefore, structural damage identification has become an important research topic in the engineering protection field [2]. In the past few years, many technologies have been developed to achieve structural damage identification, such as: identification methods based on time domain analysis [3,4], identification methods based on modal parameters [5,6] and identification methods based on time-frequency domain analysis [7,8]. Among these methods, because of low entropy and multi-resolution, wavelet transform has become a popular technology in the field of structural damage identification.…”

A self-sensing fiber reinforced polymer composite using mechanophore-based smart polymer

“…Although these techniques have been well validated in laboratory environments, in-field applications, especially real-time NDE (also referred to as SHM), are still difficult due to the bulky size of NDE equipment and the time-consuming data post-processing and decision making procedures. SHM techniques combining sensors and complex feature extraction algorithms have been well studied [5][6][7][8]. Piezoelectric ceramic sensors have been employed to record guided waves or impedance data for local and global damage awareness [9,10].…”