Damage growth and failure detection in hybrid fiber composites using experimental in-situ optical strain measurements and smoothing element analysis

Abstract

In previous study the failure initiation and development in hybrid fiber laminates was successfully monitored and determined. In current investigation a novel damage monitoring approach is proposed for hybrid laminates by combining different optical strain measurement techniques namely digital image correlation (DIC), fiber Bragg grating sensors (FBG) and infrared thermography (IRT) with smoothing element analysis (SEA). This viable experimental procedure eliminates the effects of global/local nature of optical strain measurement systems on heterogeneous damage accumulation and is a two-step approach. First, all optical sensing systems together with conventional strain gauges are utilized concurrently to indicate the differences in the measured strains and monitor damage accumulation under tensile loading. This demonstrates how failure events disturb the measurement capabilities of optical systems, which can cause a miscalculation of hybrid effect in hybrid-fiber laminates. The second step involves the utilization of SEA algorithm for discretely measured DIC displacements to predict a realistic continuous displacement/strain map and rigorously mitigate the inherent noise of the full field optical system. Remarkably, for large deformation states in hybrid composites, the combination of SEA/DIC enables early prediction of susceptible damage zones at stress levels 30% below material strength.

Experiments and Modelling of Composite–Aluminium Bolted Joints

“…Smoothing element analysis (SEA), introduced by Tessler et al [42], is another technique for smoothing noisy displacement fields. Originally applied to post-processing of FE solutions, where nodal displacements are used to calculate strains in the solution domain, it was applied to DIC measurements by de Sá Rodriguez et al [43] and Tabrizi et al [44].…”

Sensor Placement Optimization for Shape Sensing of Plates and Shells Using Genetic Algorithm and Inverse Finite Element Method

“…SHM consists of five keys: (i) sensing system description, (ii) sensor data acquisition, (iii) shape/strain/stress-sensing process, (iv) global/local failure prediction, and (v) decision-making process. Real-time deformation evaluation [ 8 , 9 ], vibration-based monitoring [ 10 , 11 , 12 , 13 ], and other SHM approaches [ 14 , 15 ] involve the implementation of sensors such as accelerometers, displacement sensors, or strain gauges [ 16 , 17 , 18 ], which are directly mounted on structural components to measure mechanical responses. SHM can assess the structural integrity, cracks, and damage during their initial phase and subsequently reduce the maintenance costs.…”