Vibration-Based Damage Detection under Changing Environmental and Operational Conditions

Abstract

Structural Health Monitoring (SHM) allows to perform a diagnosis on demand which assists the operator to plan his future maintenance or repair activities. Using structural vibrations to extract damage sensitive features, problems can arise due to variations of the dynamical properties with changing environmental and operational conditions (EOC). The dynamic changes due to changing EOCs like variations in temperature, rotational speed, wind speed, etc. may be of the same order of magnitude as the variations due to damage making a reliable damage detection impossible. In this paper, we show a method for the compensation of changing EOC. The well-known null space based fault detection (NSFD) is used for damage detection. In the first stage, a training is performed using data from the undamaged structure under varying EOC. For the compensation of the EOC-e ects the undamaged state is modeled by different reference data corresponding to different representative EOC conditions. Finally, in the application, the influences of one or other EOC on each incoming data is weighted separately by means of a fuzzy-classiffcation algorithm. The theory and algorithm is successfully tested with data sets from a real wind turbine and with data from a laboratory model.