Localization and quantification of different types of defects in composite structures with SMART sensor layers

Abstract

With the increasing use of composite materials in modern structures, the defect detection of carbon fiber‐reinforced plastics (CFRP) with ultrasonic waves is always a hot topic. Theoretical and experimental results demonstrate that the out‐of‐plane displacement of A0 mode of Lamb waves is dominant at low‐frequency ranges. Different types of defects including artificial defects, holes and cracks for flat plates, and artificial defects for a curved and stiffened (C&S)–CFRP plate are diagnosed. A shape compensatory matrix is introduced based on the symmetry of the structural features for C&S–CFRP plate. Then the statistical models of different types of defects are established and the probability‐based defect size estimation is carried out. For flat plates, the maximum relative errors are 16.3% for localization and 20.0% for size estimation. For the C&S–CFRP plate, the maximum relative errors are 11.7% for localization and 7.5% for size estimation. Therefore, a level three structural health monitoring system with defect localization and quantification functions is well‐established using PZT sensor layers.