Delamination Detection in Composites Using Acoustic Signal from Fiber Bragg Grating Sensor: A Comprehensive Review

Abstract

Delamination is an important failure mode of composite materials and can cause structural failure without visible signs. Early and reliable detection is crucial, especially in safety related sectors such as aerospace, automotive or wind energy. Fiber Bragg grating (FBG) sensors have gained widespread popularity for structural health monitoring (SHM), thanks to their high sensitivity, immunity to electromagnetic interference, compactness, and multiplexing ability. This paper reviews the use of FBG sensors for acoustic signal-based delamination detection. The paper categorizes sensor configurations (embedded, surface mounted, hybrid), methods for obtaining signals estimation and extracting features. Time Frequency analysis techniques, including Short Time Fourier Transform (STFT), wavelet transforms, and Fast Fourier Transfer (FFT) are discussed together with machine learning and deep leaning techniques such as support vector machines (SVM), Convolutional Neural Networks (CNNs), long short-term memory models. Their performance of detecting and categorizing delamination events is indeed critically scrutinized. Hybrid systems between FBG and acoustic emission (AE) or piezoelectric sensors are described as a result of their improved detectability. Recent advancements are also discussed including nano enhanced coatings that aid in increasing sensor sensitivity and environmental hardiness. Environmental effects, signal loss and sensor location problems and cost of the system are considered. The review wraps up with discussion on the significant limitations that need to be addressed and suggestions for future directions, such as adaptive signal processing, integration of AI and field ready interrogation units. The extensive evaluation presented here establishes the ground for further development of FBG based SHM methods into real time delamination inspection tools for composite structures.