A new damage indicator denoted by the distance between ARMA models is proposed in this paper to identify structural damage including its location and severity. Two definitions are introduced as the distance, either the cepstral metric or subspace angles of ARMA models. However, the accuracy is deteriorated when the multiple inputs have strong correlations. To overcome this difficulty, a pre-whitening filter is applied. Thus, the proposed damage indicator is applicable for varieties of excitation types in civil engineering, such as wind, traffic loading and earthquake excitations. A five-storey building model is used for performance verification when subjected to different excitations. Ambient force and earthquake input have been used as excitations acting on the structure. Two calculating methods of the proposed damage indicators are both evaluated. When the excitations are mutually correlated, by using the pre-whitening filter, the damage identification ability of the proposed damage indicator improves significantly, especially for damage localization. The damage indicator increases monotonically with damage severity, which provides the potential for damage quantification. Copyright © 2007 John Wiley & Sons, Ltd.

In this paper, the distance measures of autoregressive (AR) models are used as damage indicators. Two distance measures are discussed: one is the Itakura distance, and the other is the cepstral distance. The distance measures of AR model have been successfully applied in image, speech, and neurological signal processing applications. This research explores new applications of two distance measures for damage detection in civil engineering. A five-storey building model is used for performance verification. Verification simulations show efficiencies of both distance-based damage indicators when the excitations are mutually uncorrelated. However, the ability of damage indicators for damage localization is deteriorated when the multiple excitations are mutually correlated as there are strong correlations among them. In practice, the excitations acting on civil engineering structures are mutually dependent and correlated, such as wind and traffic loading. To overcome this difficulty, a pre-whitening filter is applied for removal of correlations in excitations before calculating the damage indicators. To examine the proposed methodology, simulation and experiment data have been tested. It can be concluded from the results that, by using the pre-whitening filter, the damage identification ability of the proposed damage indicators improves significantly, especially for damage localization. The damage indicators increase monotonically with damage severity, which provides the potential to damage quantification.