Data-Driven Structural Health Monitoring on Shaking Table Tests of a 3-Story Steel Building with Sliding Slabs

Abstract

Data-driven structural health monitoring (SHM) is an approach which relies on the information contained in the data and through signal analysis techniques captures the features, variations, and uncertainties that data contain. This paper presents the response of shaking table tests of a full-scale, 3-story building with sliding slabs connected by horizontal buckling-restrained braces for energy dissipation. First, the global dynamic characteristics of the structure were identified from a series of the building response data under different intensity level of base excitations. The variation of the identified modal parameters, such as the mode frequencies and modal shapes, was discovered. The influence of sliding slabs on the dynamic characteristics of the frame was also investigated through the measured response and the equation of motion with six degree of freedom systems. Comparison on the achieved interstory stiffness due to the implementation of sliding slabs and the fixed (locked up) slab was examined. The mechanism and dynamic characteristics of sliding slabs, including energy dissipation of the friction force, BRB hysteresis behavior, and unintended damping force during strong base excitation were analyzed directly using the ARX/recursive model. The extracted unintended damping force performed like a friction hysteretic response, which needs to be considered for frame modeling in shaking table tests. The findings through the data analysis have clarified the important aspects of sliding slabs and demonstrated the benefits and applicability of sliding slabs on reducing the frame response.