Curvature mode shape-based damage detection in composite laminated plates

There is a pressing need to develop effective techniques for structural health monitoring, so that the safety and integrity of the composite structures can be improved. The main objective of this study is to evaluate dynamics-based damage detection techniques for composite laminated plates using smart piezoelectric materials and modern instrumentation like scanning laser vibrometer (SLV). The study comprises of testing an E-glass/epoxy composite plate with an embedded delamination using two different actuator–sensor systems: (1) SLV with PZT (lead–zirconate–titanate) actuators (PZT-SLV), and (2) polyvinylidenefluoride (PVDF) sensors with PZT actuators (PZT-PVDF). The numerical finite element (FE) analysis is also performed to complement the damage detection. The experimental and numerical curvature mode shapes are primarily used to detect the presence, location, and size of the delamination. Three relatively new damage detection algorithms (i.e., simplified gapped smoothing method (GSM), generalized fractal dimension (GFD), and strain energy method (SEM)) are employed to analyze the experimental and numerical curvature mode shape data and uniform load surface (ULS) curvatures. From the damage detection outcomes, it is observed that the PZT-SLV system proves to be more convenient and effective, and it is capable of scanning a large number of points over the entire plate specimens; while the PZT-PVDF system, in which the curvature mode shapes are directly acquired, exhibits good sensitivity to damage. The damage detection algorithms like GSM, GFD and SEM based on the utilization of three consecutive mode curvatures (modes 3–5) and resulting ULS curvature successfully identify the presence, location, and relative size of delamination in the composite plate.