6-DOF (Degrees-of-Freedom) Robotic Arm-Assisted Modal Testing to Identify System Parameters

Abstract The authors of this paper present a novel benchtop experimental approach for identifying system parameters—such as mass, stiffness, and damping ratio—of 3D-printed structures without the need for high-end equipment or intensive computational resources. The study focuses on developing a robot-assisted modal testing method to ensure consistent force application and precise excitation locations, addressing limitations associated with traditional manual techniques like hand-held hammer testing. The proposed method enhances repeatability and accuracy in extracting structural parameters by leveraging robotic automation. Once acceleration, velocity, and position data are obtained, the approach is validated on a reference structure before being applied to manually altered, defective structures. The resulting behavioral trends, presented graphically, illustrate the method’s effectiveness in detecting structural deficiencies. The findings demonstrate that despite having identical material properties—such as density, geometry, and configuration—3D-printed structures exhibit differences in strength, stiffness, and damping compared to bulk structures, and authors show their differences of m, c, and k in equations. The proposed robot-assisted modal testing method successfully captures these variations, highlighting its potential as a reliable tool for evaluating structural integrity in nonconventional manufacturing processes.