In this study, a new approach for global/local damage detection in a finite element model of structures, with limited sensors, is proposed using identified system Markov parameters. The proposed damage detection is directly related to the Markov parameters, locations of actuators and sensors. Also there is no explicit relation between DDA/ISMP and mode shapes. So, it is unnecessary to install a sensor at each DOF for measuring output to identify mode shapes unlike the other damage detection techniques in which mode shapes play an important role in damage identification. The stiffness of all elements of a structure is identified using the proposed DDA/ISMP. The effects of noise, numbers and locations of sensors on the identification precision are investigated. The results demonstrate that, with the limited sensors and the noise contamination in the measured responses, the DDA/ISMP can effectively identify the locations, types and quantities of damages, both locally and globally. To illustrate the efficiency of DDA/ISMP, a four-storey steel moment frame structure and a five-storey shear building are used. Our numerical results show that the DDA/ISMP technique in damage detection is more effective than the scheme proposed by Xu et al. Also, the time consumed in DDA/ISMP is considerably less than the method introduced by Xu.
