LOCAL DAMAGE ASSESSMENT OF COMPOSITE LAMINATES USING GLOBAL STRUCTURAL VIBRATION RESPONSE

Abstract

Laminated composites are widely used in aerospace, automotive, and marine industries due to their exceptional strength-to-weight ratio and stiffness. The orthotropic characteristics of these materials allow for tailored mechanical properties. However, this also results in intricate failure modes that complicate damage assessment. Traditional non-destructive evaluation (NDE) techniques and structural health monitoring (SHM) strategies, such as surface acoustic wave (SAW) methods, encounter significant challenges in the real-time detection of damage within composite structures. Although real-time vibration data from composite structures can be easily acquired, the global response characteristics of this data often hinder the accurate identification of localized damage. Recently, advancements in artificial intelligence (AI)-based damage detection methodologies have facilitated the ability to infer local damage status from global sensor data. This paper presents a novel approach for the assessment of local damage in composite structures through the analysis of global structural vibration data.