This research presents ultrasonic guided wave (UGW) propagation-based nondestructive testing (NDT) of an adhesively bonded composite structure (ACS).

 In the process, a series of scanning laser Doppler vibrometry (SLDV)-based laboratory experiments and time-domain spectral element method (SEM)-based numerical simulations were carried out on an ACS with barely visible impact damage (BVID) and a hole.

Finally, a full-field and elliptical signal processing method-based NDT strategy was proposed that uses differential damage features of the registered UGW signals to identify different types of BVIDs in the ACS. 

This study aimed to identify, visualize, localize, and verify multiple barely visible impact damage (BVID) in a GFRPS using a combination of guided waves (GW)-based online structural health monitoring (SHM) and thermal strain-based non-destructive testing (NDT) approaches. 

A threshold-based baseline-free SHM approach to effectively localize the damages was proposed along with quick DIC verification of composite structure with thermal loading based on short-pulse heating as an excitation source. 

The proposed methodology consists of two steps. Step 1 using the full wavefield root mean square energy map-based approach to check the presence of debond. 

Step 2 using point-wise measurements to study debond localization and size estimation using a baseline free signal coefficient difference algorithm (SCDA). The proposed processing approaches are applied for an in-depth analysis of the experimental signals that provide information about the interaction of GWs with stiffener and debond. 

The mentioned approaches take advantage of the asymmetry caused by the damage. For the applied SCDA methodology there is no need for full-wavefield measurements, healthy case measurements, as only a few measurement points can be enough for the assessment of stiffener debond in such structures 

The research presents multiple impact damage detections and characterization in a multi-layered carbon fiber reinforced polymer structure using a multi-step combination of the global area and local area damage detection methods. 

The experimental results were cross-verified numerically using the spectral element method (SEM). The implemented structural health monitoring (SHM) based sectorial elliptical code (SEC) reduced the overall calculation time in damage localization and accurately identified the damage from experimental and numerical data. An infrared thermography (IRT)-based crack identification algorithm was developed in pinpointing the ICD shape. 

The automatic method removes the influence of high heat sources and highlights the damage zones easily. The accuracy of the localization strategy was successfully verified with non-contact active IRT analysis. 

The crack size and damage severity were quantified using the ultraviolet radiation (UVR) method with a solution mixture based organic dye. 

The SHM approach uses a proposed quick damage identification matrix maps and an improved elliptical wave processing (EWP) strategy of the registered GW signals to detect the locations of debonding and other damages in the SCS. The benefit of the proposed damage identification map is to locate the damaged area (sectors) quickly. 

This identification step is followed by applying the damage localization step using the improved EWP only on the previously identified damage sector region. The proposed EWP has shown the potential to effectively locate the hidden multiple debonding regions and damages in the SCS with a reduced number of calculations using a step-wise approach that uses only a selected number of grid points.

The research presents a proof-of-study to use a global-local approach in damage localization and quantification. The main novelties in this are the implementation of an improved SHM GW algorithm to localize the damages, a new pixel-based confusion matrix to quantify the size of the damage threshold, and a newly developed IRT-ANN algorithm to validate the damage quantification. 

From the SHM methodology, it is realized that only three sensors are sufficient to localize the damage, and an ANN- IRT imaging algorithm with only five hidden neurons in quantifying the damage. The robust SHM methods effectively identified, localized, and quantified the different damage dimensions against the non-destructive testing-IRT method in different composite structures. 

The novelty of this study lies in the development of a proof-of-study damage mapping method that uses an improved cosine distance (CD) formulation to detect damage paths while accounting for the directional sensitivity of FBG sensors. Additionally, a sectorial elliptical code (SEC) based on CD was used to localize damages in a hybrid FBG-PZT network. This approach was validated with numerical simulations, demonstrating its effectiveness in accurately detecting and localizing damages in structures. 

The damage detection with the CD method located all the damage paths which help to identify the probable damage region. The SEC method localized damages not only in the inner sensor zone but also in the outer zone. The CD method successfully predicted the probable damage zones overcoming the directional sensitivity issue. The error predicted with the SEC method was as low as 0.7 cm in the experimental and 0.1 cm in numerical studies.