1.College of Civil and Architecture Engineering, Dalian Nationalities University, Dalian 116600, China; 2. Harbin Institute of Technology Shenzhen Graduate School; Shenzhen 5180553, China; 3.School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China; 4.Smart-Tech Centre, Institute of Fundamental Technological Research, Polish Academy of Sciences, 00-049, Warsaw, Poland
Abstract：A load and damage simultaneous identification method is proposed via taking in which only the damage factors are taken as the optimization variables. Firstly, unknown loads are converted into the function of the damage factors via the load identification method in time domain, such that the number of the optimizational is reduced. The optimization is performed by minimizing the square distance between the measured responses and the estimated responses corresponding to the estimated loads and the given damage factors. During the optimization, in order to increase the computational efficiency, Virtual distortion method (VDM) is employed, which is fast structural reanalysis method. Via VDM, the system impulse response of the damaged structure regard to the given damage factors is constructed efficiently and it avoids repetitively assembling the damaged structural parameters which is time-consuming. Further, the load shape function method is used to estimate unknown load which can improve the ill-conditioning problem of the inverse problem and also obviously reduce the computational work. At last, the optimization is further speeded up by interpolating the estimated structural responses using quadratic polynomial via which the expression of the gradient of the objective function can be obtained. In a numerical simulation of a three-span frame, a moving excitation and the damages including the stiffness-related damages and an additional mass are identified successfully with a 5% Gaussian noise pollution. And an experiment of a cantilever beam is performed to validate the accuracy and the feasibility of the proposed method.
2013, Vol. 32 
