[01] Wael A. Altabey, Southeast University, International Institute for Urban Systems Engineering, Nanjing, China； Department of Mechanical Engineering, Faculty of Engineering, Alexandria University, Alexandria, Egypt. [02] Mohammad Noori, Southeast University, International Institute for Urban Systems Engineering, Nanjing, China； Department of Mechanical Engineering, California Polytechnic State University, San Luis Obispo, California, USA.

Lamb waves are guided waves and have many useful properties that can be exploited for non-destructive testing (NDT) and structural health monitoring (SHM) applications. Utilization of Lamb waves for these purposes have led to the development of some of the most promising methods and have resulted in numerous useful and practical applications over the past two decades. The major advantage of using Lamb waves has been their capability of propagating a relatively long distance in plate or shell structures, the ability to follow curvature and penetrate into hidden and buried parts, allowing the detection of faults between the layers of composite laminate structures. The wave structure depends on the frequency and phase velocity. Lamb waves are on the verge of maturity for diverse engineering applications. This emerging technique serves as an encouraging candidate for facilitating continuous and automated surveillance of the integrity of engineering structures in a cost-effective manner. Numerous studies of lamb wave based methodologies have been developed for damage detection in composite structures. In this paper we present an overview of lamb waves behavior, modeling and applications as well as their limitations for fatigue damage detection of composite structures. The focus of this study is on the application of Lamb waves combined with Artificial Neural Networks. Over the last decade, ANNs have been used as one of the most desirable methods for fatigue damage prediction of composite structures. A well-trained ANN can predict outcomes under an unknown stimulus based on pre-accumulated knowledge from a lamb waves sensing system, while avoiding interrogating intricate constitutive relations and save the time needed for this interrogation. An overview of some new developments in this regard is presented.

Lamb Wave Technique, Piezoelectric Transducers (PZTs), Fatigue Damage Detection, Composite Structures, Artificial Neural Networks (ANNs)

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