Structural damage assessment through features in quefrency domain Marcello Morgantini a,⇑ , Raimondo Betti a , Luciana Balsamo b a Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USA b Thornton Tomasetti, New York, NY 10005-1304, USA article info Article history: Received 26 September 2019 Received in revised form 21 May 2020 Accepted 29 May 2020 Keywords: Structural Health Monitoring Cepstral coefficients Quefrency domain AutoRegressive coefficients Principal Component Analysis Z24 Bridge abstract The difficulties in dynamic system modeling and the recently developed machine learning tools have moved the attention of the structural damage assessment community towards a new direction. Attention is now placed on the immediate extraction of damage sensitive features directly from the monitored dynamic response of the structure, allowing engi- neers by-pass the creation of complex and sophisticated structural models. It is in this framework that the work presented in this paper has to be considered: the extraction of new damage sensitive features in the quefrency domain is discussed in the context of a vibration based analysis. Despite such a domain has been fully explored in acoustics, it rep- resents an uncommon approach for the civil engineering community. In this paper, some variables characterizing the system dynamic response in the quefrency domain, referred to as cepstral coefficients, have been derived as functions of the structural characteristics and used in a damage assessment strategy. The main advantage of the quefrency domain over the frequency domain consists in a massive dimensionality reduction and, when deal- ing with real data, in a simplification of the extraction of cepstral coefficients versus that of natural frequencies. In this paper, the analytical expression of cepstral coefficients of the structural acceleration response has been derived and the statistical distribution of such coefficients has been investigated in a pattern recognition approach. In addition, a damage assessment strategy has been proposed by extracting, through a Principal Component Analysis (PCA), the projections of the cepstral coefficients with the lowest variances so to minimize the effect of external disturbances. The effectiveness of the proposed damage assessment strategy has been validated through numerical simulations and experimental data. Ó 2020 Elsevier Ltd. All rights reserved. 1. Introduction As our infrastructure system rapidly ages and deteriorates, maintenance and rehabilitation operations constitute an increasingly large economic effort. These activities cannot be performed daily for both logistic and economic reasons. In fact, direct inspections may often result in costly and ineffective operations: unforecasted events may suddenly compromise the working conditions of a structure and urgent repair may be needed (the waiting time before the next scheduled inspection may result into a high risk factor). However, nowadays, thanks to incredible advances in sensor and computer technologies, https://doi.org/10.1016/j.ymssp.2020.107017 0888-3270/Ó 2020 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. E-mail address: mm4651@columbia.edu (M. Morgantini). Mechanical Systems and Signal Processing 147 (2021) 107017 Contents lists available at ScienceDirect Mechanical Systems and Signal Processing journal homepage: www.elsevier.com/locate/ymssp