In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using Recursive Principle Component Analysis (RPCA) in conjunction with Time Varying Auto-Regressive Modeling (TVAR) is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal components online using rank-one perturbation method, followed by TVAR modeling of the first transformed response, to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear /non-linear-states that indicate damage. Most of the works available in the literature deal with algorithms that require windowing of the gathered data owing to their data-driven nature which renders them ineffective for online implementation. Algorithms focussed on mathematically consistent recursive techniques in a rigorous theoretical framework of structural damage detection is missing, which motivates the $ Fully documented templates are available in the elsarticle package on CTAN.

In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using recursive principal component analysis (RPCA) in conjunction with online damage indicators is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal modes in online using the rank-one perturbation method, and subsequently utilized to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/nonlinear-states that indicate damage. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. An online condition indicator (CI) based on the L2 norm of the error between actual response and the response projected using recursive eigenvector matrix updates over successive iterations is proposed. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data. The proposed CI, named recursive residual error, is also adopted for simultaneous spatio–temporal damage detection. Numerical simulations performed on five-degree of freedom nonlinear system under white noise and El Centro excitations, with different levels of nonlinearity simulating the damage scenarios, demonstrate the robustness of the proposed algorithm. Successful results obtained from practical case studies involving experiments performed on a cantilever beam subjected to earthquake excitation, for full sensors and underdetermined cases; and data from recorded responses of the UCLA Factor building (full data and its subset) demonstrate the efficacy of the proposed methodology as an ideal candidate for real-time, reference free structural health monitoring.

A vibration-based bridge scour detection procedure using a cantilever-based piezoelectric energy harvesting device (EHD) is proposed here. This has an advantage over an accelerometer-based method in that potentially, the requirement for a power source can be negated with the only power requirement being the storage and/or transmission of the data. Ideally, this source of power could be fulfilled by the EHD itself, although much research is currently being done to explore this. The open-circuit EHD voltage is used here to detect bridge frequency shifts arising due to scour. Using one EHD attached to the central bridge pier, both scour at the pier of installation and scour at another bridge pier can be detected from the EHD voltage generated during the bridge free-vibration stage, while the harvester is attached to a healthy pier. The method would work best with an initial modal analysis of the bridge structure in order to identify frequencies that may be sensitive to scour. Frequency components corresponding to harmonic loading and electrical interference arising from experiments are removed using the filter bank property of singular spectrum analysis (SSA). These frequencies can then be monitored by using harvested voltage from the energy harvesting device and successfully utilised towards structural health monitoring of a model bridge affected by scour.

A novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using Recursive Singular Spectral Analysis (RSSA) in conjunction with Time Varying Auto-Regressive Modeling (TVAR) is proposed in this paper. The acceleration data is used to obtain recursive proper orthogonal components online using rank-one perturbation method, followed by TVAR modeling of the first transformed response, to detect the change in the dynamic behavior of the vibrating system from its original state to contiguous linear /non-linear-states indicating damage. Most work to date deal with algorithms that require windowing of the gathered data that render them ineffective for online implementation. Algorithms focussed on mathematically consistent recursive techniques in a rigorous theoretical framework of structural damage detection is missing, that motivates the development of the present framework. The response from a single channel is provided as input to the algorithm in real time. The RSSA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data without requiring any baseline data. Lower order TVAR models are applied on the transformed responses to improve detectability. Numerical simulations performed on a 5-dof nonlinear system and on an SDOF system modeled using a Duffing oscillator under white noise excitation data, with different levels of nonlinearity simulating the damage scenarios, demonstrate the robustness of the proposed algorithm. The method, further validated on results obtained from experiments performed on a cantilever beam subjected to earthquake excitation; a toy cart experiment model with springs attached to either side; demonstrate the efficacy of the proposed methodology as an appropriate candidate for real time, reference free structural health monitoring.

This manuscript provides a detailed synopsis of the contemporary advancements in the nascent area of real-time structural damage detection for vibrating systems. The paper mainly focuses on the theoretical development and engineering applications of algorithms that are based on first-order perturbation (FOP) techniques applied to vibration responses. The importance of this work stems from the fact that recent developments in the field of online structural health monitoring (SHM) have given rise to algorithms that are computationally complex and, consequently, are not amenable to real-time implementation. In this paper, we discuss and demonstrate the FOP-based algorithms in the light of all the contemporary nonadaptive/nonrecursive techniques to establish their relevance. We review 216 papers in this regard. The efficacy, efficiency, robustness, and the applicability of the FOP family of algorithms are highlighted in light of several experimental, theoretical, and field studies.

No abstract

In this article, a robust output-only real-time damage detection technique for multi-degree-of-freedom degrading systems using recursive canonical correlation analysis is presented. It has been observed that the impact of damage to a vibrating system gradually advances with time that sustains until the system degrades up to a considerable extent. Of significant interest is the effect of sudden damage in presence of continuous degradation in real-time, which is studied in the form of a sudden stiffness reduction in a separate floor. The proposed recursive canonical correlation analysis algorithm estimates the iterative update of eigenspace at each instant from the response data, thereby capturing the features of a time varying degrading structure in an online framework. Furthermore, recursive canonical correlation analysis algorithm is shown to reduce the computational cost by updating the eigenspace at each instant of time. This article explores newly developed recursive condition indicators: recursive Mahalanobis distance and recursive Itakura distance that elicit damage information from the eigenspace. In order to model degradation, simulations aimed at successfully capturing the behavior of the process in real-time becomes imperative. A general stochastic formulation of the coupled response-degradation problem accounting for the evolution of degradation is presented in the light of stiffness degradation problems. The evolution of time varying system responses is generated using a newly proposed Ito–Taylor expansion-based stochastic numerical integration formulation. Numerically simulated structural vibrating systems, namely, 2-degree-of-freedom base-isolated and 4-degree-of-freedom linear systems, have been used to check the performance of the recursive canonical correlation analysis method. The spatial damage detectability of the algorithm in real-time is explored through identifying crack location on a beam traversed by a vehicle. Finally, an experimental case study has been carried out to verify the robustness of the proposed algorithm. The identification results for both numerical and experimental cases demonstrate the efficacy of the proposed algorithm in identification of nonlinear and time varying behavior associated with degrading structural systems.

No abstract