Most of the civil structures exhibit nonlinear hysteresis behavior during earthquakes. However, detection of damage in these structures is a challenging issue due to successive change in structural characteristics during a seismic excitation. The current paper presents a promising approach for damage detection of nonlinear moment frames. First, several instantaneous time-frequency methods including Hilbert-Huang transform, direct quadrature, Teager energy operator, and higher-order energy operator are investigated as signal processing tools and the most appropriate method is selected using an outlier analysis. Next, a procedure is proposed based on time-frequency analysis in conjunction with clustering to find damage extension in moment frames under a seismic excitation using frequency, amplitude, and energy damage measures. A probabilistic approach is implemented to investigate capability of the procedure for different ground motion records using incremental dynamic analysis. Results show that frequency is not an appropriate feature to detect damage in nonlinear structures. 1. Introduction During an earthquake many civil structures undergo damages. Therefore, it is important to ensure serviceability and safety of the structures after a seismic excitation. Today, nondestructive evaluation techniques (NDE) are widely utilized for health monitoring and damage detection of structures. At present, current practical methods are based on visual inspection, CT scanning, ultrasonic, stress waves, acoustic emission, and so forth [1]. However, these local damage detection methods are effective only for small structures or structural members. Recently, global vibration-based techniques have attracted researchers since they can solve the problem of large and complicated structures. These methods include power spectrum, Fourier transform, spectrum analysis, and cepstrum analysis [2]. The main drawback of these procedures is that they cannot trace time-varying nature of signals due to their fixed functions. Instead, time-frequency methods are effective tools for analyzing nonstationary signals which makes them appropriate for health monitoring and fault detection of civil, mechanical, and aerospace systems [3]. Doebling et al. [4] and also Fan and Qiao [5] gave a detailed review of vibration-based damage detection methods. An experimental investigation was conducted on a three-story shear building by Xu and Chen [6]. They studied applicability of empirical mode decomposition (EMD) to detect sudden change in structural stiffness. Yang et al. [7] tried to extract
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