Analysis of damage control of thin plate with piezoelectric actuators using finite element and machine learning approach

Abstract

In recent studies, piezoelectric actuators have been recognized as a practical and effective material for repairing cracks in thin-walled structures, such as plates that are adhesively bonded with piezoelectric patches due to their electromechanical effects. In this study, we used the finite element method through the ANSYS commercial code to determine the stress intensity factor (SIF) at the crack tip of a cracked plate bonded with a piezoelectric actuator under a plane stress model. By running various simulations, we were able to examine the impact of different aspects that affect this component, such as the size and characteristics of the plate, actuator, and adhesive bond. To optimize performance, we utilized machine learning algorithms to examine how these characteristics affect the repair process. This study represents the first-time machine learning has been used to examine bonded PZT actuators in damaged structures, and we found that it had a significant impact on the current problem. As a result, we were able to determine which of these parameters were most helpful in achieving our goal and which ones should be adjusted to improve the actuator's quality and reduce significant time and costs.

Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms

“…The replacement of damaged structural components significantly impacts the life cycle cost of an airplane. In recent years, bonded composite patches have gained widespread use for repairing cracks and defects in aircraft structures [5][6][7]. This technology provides several advantages over traditional methods such as mechanical fastening or riveting, including improved fatigue behavior, restored stiffness and strength, reduced corrosion, and the ability to be readily formed into complex shapes.…”

Optimization of damage repair with piezoelectric actuators using the Taguchi method

“…This multi-faceted configuration emphasized the evolving complexity and sophistication of PZT-driven repair methodologies. Recently, a study has shown that the analysis of damage control in a thin cracked plate has been done by machine learning and the FE approach [17]. The authors focused on reducing human efforts and optimising the best possible solution for reducing crack damage propagation by optimizing the SIF.…”