Condition-based decision using traffic-light concept applied to civil engineering buildings

Abstract

Analyzing the integrity of a structure and implementing a process to estimate the level of damage in real time increase the safety of people and goods and reduce economic losses associated with the production interruption or operation of the structure. The appearance of damage to a building changes its dynamic response (frequency, damping and/or modal shape) and, therefore, one of the most effective methods for continuous assessment of integrity is based on the use of ambient vibrations. However, if the resonance frequency can be used as indicator of changes, a misinterpretation can be due to the fact that frequency is not only affected by the occurrence of damage, but also by certain operating conditions and especially certain atmospheric conditions. In this study, after analyzing the correlation of the resonance frequency values with temperature for one building, we used the data mining method called "association rule learning" (ARL) to predict the future frequency depending on the measured temperature. We then propose an interpretation strategy of anomalies using the method called "traffic-light".