Sparsity-based Reconstruction Method for Simultaneous External Force Monitoring and Structural Damage Identification

Abstract

Load monitoring and damage identification are important tasks in the field of Structural Health Monitoring. Reconstructing unknown force inputs or system parameters usually involves the solution of an inverse problem which is mostly ill-posed. In the last decades a lot of effort has been spent in solving these problems separately. However, unknown loads and damage both have influence on the structural vibration pattern. The difficulty of simultaneous identification of external forces and structural damage is to distinguish these influences by using only the measured vibration effects. The use of prior knowledge of the unknown quantities is advisable for solving the combined inverse problem and to obtain meaningful solutions. In this contribution a sparsity-based reconstruction method in time domain is developed for identifying the unknown structural force excitation and damage parameter simultaneously by using output-only acceleration data. Sparsity means the majority of the solution vector is zero and only a very few elements are nonzero. Here damage is interpreted as additional load on the damaged structural element (virtual distortion). A numerical proof-of-concept experiment of a quadratic aluminum plate is presented. It shows that the proposed reconstruction method is able to identify the unknown external force and damage parameter by using a significant lower number of accelerometers than present methods.