A baseline-free structural damage indicator based on node displacement of structural mode shapes. (27th October 2018) - Huang, Tianxiang; Chaves-Vargas, Mauricio; Yang, Jinshui; Schröder, Kai-Uwe
Abstract: Most widely studied Structural Health Monitoring methods need baseline data from the undamaged state and a high number of sensors attached to the structure, which makes these methods difficult to be applied in real structures for on-line monitoring. In order to deal with that, the NOde DISplacement (NODIS) method is proposed by considering the structural damage indicator. The idea of the present work is to develop a baseline-free damage location and quantification method based on the node displacement of structural mode shapes. The damage location procedure is developed by combining the nodes from different mode shapes and the damage quantification is achieved by the proposed Transfer-Function-based Damage Indicator (TFDI). The advantages of this method are: (1) baseline-free, in terms of the comparison with a reference signal is not needed, (2) only a relatively small number of sensors is required for real-time damage location and (3) with the proposed TFDI, the damage detection result can be quantified. In the present paper, the baseline-free damage location algorithm is proposed and validated on a steel beam with an analytical model, a numerical model and experiments. In addition, the influence of temperature, the additional weight of the sensor and the error in sensor location on the NODIS method are studied. After that, the TFDI is developed and improved for the experiment. Finally, the method is applied to a supporting structure of a sailplane under complex boundary condition and different environmental temperatures. Highlights: We proposed a structural damage indicator based on the node displacement. The method can access the damage with a small number of sensors. A TFDI is proposed to normalize and quantify the damage detection result. The method is applied on real structure under complex operational conditions.