Adaptive modeling of environmental effects in modal parameters for damage detection in civil structures

Many researchers have proposed damage detection techniques that exploit changes in modal parameters to identify the extent and location of damage in large structures. These analyses, however, generally neglect the effects of environmental changes on modal parameters. Such environmental effects include changes in loads, boundary conditions, temperature, and humidity. Data from real bridge structures indicate that the effects of environmental changes can be significant. In fact, these changes can often mask more subtle structural changes caused by damage. This paper examines a linear adaptive model that may discriminate the changes of modal parameters due to temperature changes from those caused by structural damage or other environmental effects. Data from the Alamosa Canyon Bridge in the state of New Mexico were used to demonstrate the effectiveness of the adaptive filter for this problem. Results indicate that a linear four-input (two time and two spatial dimensions) filter of temperature can reproduce the natural variability of the frequencies with respect to time of day. Using this simple model, we attempt to establish a confidence interval of the fundamental frequency for a new temperature profile in order to discriminate the natural variation due to temperature.