Damage Identification of Bolt Connections in a Steel Frame

It is well-known that damage in a structure is a local phenomenon. Based on measured vibration data from sensors, the detection of a local structural damage requires the finite-element formulation for the equations of motion, so that any change in stiffness in a structural element can be identified. However, the finite-element model (FEM) of a complex structure involves a large number of degrees of freedom (DOF), which requires a large number of sensors and involves a heavy computational effort for the identification of structural damages. To overcome such a challenge, we propose the application of a reduced-order model in conjunction with a recently proposed damage detection technique, referred to as the adaptive quadratic sum-square error with unknown inputs (AQSSE-UI). Experimental data for the shake table tests of a 1/3-scale six-story steel frame structure, in which damages of the joints were simulated by loosening the connection bolts, have been available recently. Based on these experimental data, it is demonstrated that the proposed combination of the reduced-order finite-element model and the adaptive quadratic sum-square error with unknown inputs is quite effective for the damage assessment of joints in the frame structure.