Estimation of Tension Force in Tension Members Using GRU Algorithm Based on Yoke-Type Elasto-Magnetic Sensor Data

Abstract

This letter proposes a method to the estimation of tension force in tension members using the grated recurrent unit (GRU) algorithm. In this letter, a yoke-type elasto-magnetic (E/M) sensor was developed based on numerical ANSYS Maxwell simulations to enhance the applicability through the structural improvement of the existing solenoid-type magnetized E/M sensor. The induced voltage signal collected based on the yoke-type E/M sensor was applied to the GRU algorithm. As a result of applying the GRU model to the induced voltage signal data according to the change in tension force of the yoke-type E/M sensor, it was proven that high-accuracy tension force estimation is possible. These results suggest new possibilities for structural health monitoring technology through nondestructive testing. This study presents the applicability of artificial-intelligence-based techniques in nondestructive measurements of tension members for the health monitoring of structures.