Optimal Sensor Placement Strategy for the Identification of Local Bolted Connection Failures in Steel Structures

Abstract

Failure of bolted connections in steel structures may result in catastrophic effects. Many algorithms in existing literature use modal information of a structure to identify damage in that structure, based on the data acquired from accelerometers which record the vibration time histories at different points on the structure. The location of these points may have significant effects on the quality of the acquired data, and thus the identified modal information. In this paper, a distance measure based Markov chain Monte Carlo algorithm is proposed to determine the optimal locations for the accelerometers, and the optimal location of the impact hammer if need. Different damage cases with various combinations of bolt failures are considered in this study. Failures at various levels are simulated by loosening the bolts in a predefined order. To compare the efficiency of the proposed method, the total effect of various damage cases on the accelerations at the optimal locations are calculated for the proposed method and a state-of-the-art method from the existing literature. The results demonstrate the efficiency of the proposed strategy in locating the accelerometers, which can produce data that are more sensitive to the bolted connection failures.