Optimal Tilt Sensor Configuration of Urban Subway Shield Tunnel Structure

Various tunnel defects are very harmful to urban subway tunnels, as they will endanger the safety of subway trains and shorten the time span of the maintenance cycle as well as the service life of the subway tunnel. Thus, it is very important to develop a structural health monitoring (SHM) system for maintaining, repairing, and reinforcement of the subway tunnel. Over the last few decades, there has been great interest in the development of a SHM methodology based on vibration data. The quantity and quality of the measured data (i.e., the number of sensors and the corresponding locations) are very important for the success of SHM utilizing measured dynamic responses. However, most works in the literature relate to the sensor placement problem in the civil engineering area concentrating on bridges, buildings, towers, and others, and the studies on the optimal sensor placement for the urban subway tunnel structure are seldom involved. In this paper, to extract the most information from the measured data for the purpose of structural model updating, an entropy- based methodology is presented for optimally locating a given number of tilt sensors in a mathematical model of urban subway tunnel structure. The information entropy measure is used to quantify the uncertainty in the model parameters, which are computed by a Bayesian statistical methodology. Then by using a genetic algorithm (GA), the entropy measure is minimized over the set of possible sensor configurations. A beam-spring model for a typical subway shield tunnel is used as a numerical example to illustrate the proposed methodology.