An Integrated Methodology for Damage Identification in Existing Buildings Using Optimal Sensor Placement Techniques (original) (raw)
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2013
This study investigates the use of vibrational response of structure known as modal parameters, for identification of damage in the civil and architectural buildings. The vibrational response is defined as modal parameters that contain of mode shape, natural frequency and modal damping. Damage is also described as adversely performance of vibrational response which is relevant to changes of physical properties of structures. The proposed approach is based on vibration-based method and sensitivity of natural frequency. The Damage estimation algorithms involve two processes. First, the multiple damage location coefficient (MDLC) which uses a sensitivity matrix of natural frequency modification. In this level, the damage location can be detected via difference between natural frequencies of healthy and damaged structures as well as the sensitivity of natural frequency based on damage parameters. Observing the level of correlation between the variations in the modal parameters for healthy and damaged structures enables damage localization. The sensitivity matrix, developed from finite element model, further accommodate multiple damage detection. Next, the least-squares method is used for damage quantification. For verification of proposed damage algorithms, a simple 6-story shear building as discrete dynamic structure is modelled. Then, a 15-bar planner truss is used. Eventually, the numerical results show that the proposed methods are accurate and reliable approaches for damage localization and quantification in the structures.
Optimal Sensor Placement Strategies for Structural Damage Identification
2000
Reliable diagnosis of the structural condition during structural health monitoring using vibration measure- ments depends to a large extend on the sensor configuration. An optimal sensor configuration is selected such that the measured data are most informative about the condition of the structure over the period of mon- itoring. A cost-effective instrumentation should reveal the condition of critical substructures with
Procedia Engineering, 2014
A structural health monitoring system consists of permanently installed sensors to collect structural information, and these sensors are required to be placed at 'good' positions for damage identification. Conventional sensor placement methods make use of dynamic characteristics of a structure, i.e., mode shapes and natural frequencies, to determine optimal sensor positions. The engineering community has traditionally relied on these modal methods and finite element analysis for dynamic predictions in the low frequency range. However, these techniques become ineffective in mid frequency range due to large number of modes and high modal density. In view of this, in this paper, an optimal sensor placement technique which can be employed for low as well as mid frequency range structures for structural health monitoring as well as structural system identification is presented. The frequency domain based optimal sensor placement technique (FEfi) presented in this paper makes use of principal components evaluated from frequency response functions at the desired frequency levels. Numerical examples with optimally placed sensors dictated by the proposed algorithm are presented and compared with the popular effective independence (Efi) technique based on mode shapes.
Optimal sensor placement for Structural, Damage and Impact identification: A review
The optimum location of the sensors is a critical issue of any successful Structural Health Monitoring System. Sensor optimization problems encompass mainly three areas of interest: system identification, damage identification and impact identification. The current paper is intended as a review of the state of the art at the year 2012 and going back to 1990. The above topics have been dealt with in separate contexts so far but they contain interesting common elements to be exploited.
Title: Optimal Sensor Location Methodology for Structural Identification and Damage Detection
Theoretical and computational issues arising in the selection of the optimal sensor configuration in structural dynamics are addressed. The information entropy is introduced to measure the performance of a sensor configuration. Asymptotic estimates are used to rigorously justify that selections of optimal sensor configurations can be based solely on nominal structural models, ignoring the time history details of the measured data that are not available in the initial experimental design stage. Heuristic algorithms are proposed for constructing effective sensor configurations that are superior, in terms of computational efficiency and accuracy, to the sensor configurations provided by available algorithms suitable for solving general optimisation problems. The theoretical developments and the effectiveness of the proposed algorithms are illustrated by designing the optimal configuration for an array of acceleration sensors placed on a bridge structure.
Optimal sensor location methodology for structural identification and damage detection
3rd European Workshop on Structural Health Monitoring, 2006
Theoretical and computational issues arising in the selection of the optimal sensor configuration in structural dynamics are addressed. The information entropy is introduced to measure the performance of a sensor configuration. Asymptotic estimates are used to rigorously justify that selections of optimal sensor configurations can be based solely on nominal structural models, ignoring the time history details of the measured data that are not available in the initial experimental design stage. Heuristic algorithms are proposed for constructing effective sensor configurations that are superior, in terms of computational efficiency and accuracy, to the sensor configurations provided by available algorithms suitable for solving general optimisation problems. The theoretical developments and the effectiveness of the proposed algorithms are illustrated by designing the optimal configuration for an array of acceleration sensors placed on a bridge structure.
Journal of Structural …, 2004
The paper reports on relative performance of inverse eigensensitivity and response function methods for structural damage detection, location and quantification using vibration data. In implementing each of these methods, a validated baseline finite element (FE) model for the structure, in its undamaged state, is assumed to be available. Depending on this, a matrix of sensitivity of structural dynamic characteristics, in frequency or modal domains, to changes in values of structural parameters, is constructed. An inverse procedure, based on pseudoinverse theory of matrices, is subsequently applied to identify structural damages based on observed changes in vibration response of the structure. Issues arising out of mismatch between degrees of freedom of the FE model and number of measured degrees of freedom are dealt with by using alternative model reduction/expansion schemes. Illustrative examples on synthetically and experimentally generated vibration data on cantilever beams and a three-storied building frame are presented.
2017
Damage detection approach based on dynamic monitoring of structural properties over time has received a considerable attention in recent scientific literature. In earthquake engineering field, the recourse to experimental research is necessary to better understand the mechanical behaviour of various structural and non-structural components. Aim of this paper is the optimisation of a methodology based on the evaluation of the mode curvature to detect and localize a possible damage occurred on a framed structure after an earthquake. The methodology is based on the use of accelerometric sensors, one station for each floor, to record accelerometric time-histories and directly evaluate the fundamental mode shape variations from filtered signals. In order to reduce costs and computation, this paper focuses on the possibility to reduce the number of stations installed on the monitored structures. In this study, the attention has been concentred to minimize the number of sensors, as a funct...
Journal of Sound and Vibration, 2019
Three significant tuning components in structural finite element model updating including objective function, optimization algorithm, and updating variables have a drastic influence on the accuracy of structural damage location diagnosis and intensity prognosis. These three components require both physical concepts and trial-and-error approaches. To assess damage in a structure accurately, the common information of several modes of the structure is required. The availability of higher modes data in engineering structures with a high degree of freedom is a complex task or even not practical in real cases. This study intends to propose a versatile objective function based only on the first vibration frequency and mode shape data. A new hybrid criterion called "Relative Discrepancy Function (RDF)" is proposed which is composed of relative differences of natural frequency and mode shape vector. Hereupon, the efficiency of the proposed identification method is evaluated through five sets including different robust objective functions and meta-heuristic optimization algorithms. These five damage identification sets are composed of three objective functions (Normalized Modal Strain Energy, Modified Total Modal Assurance Criterion, and RDF) and three optimization algorithms (Imperialist Competitive Algorithm, Teaching-Learning-Based Optimization algorithm, and the Most Valuable Player Algorithm (MVPA)). Subsequently, three truss and frame benchmark structures are assessed by means of five identification methods in single and multiple damage scenarios. It is observed that MVPA has both the fastest convergence rate and the lowest computational run time. Furthermore, the damage assessment results illustrate that when merely the first vibration mode data are used, the proposed identification method (RDF, MVPA) not only predicts the damage location properly, but also estimates the damage intensity successfully.
Optimal sensor placement for structural health monitoring
2021
Optimal sensor placement (OSP) is a crucial subject in structural health monitoring. It becomes even more important for large structures like bridges since it is not economical, and most times impossible, to cover the entire structure with sensors. On account of that, there are several methods used in civil engineering to determine optimal sensor placement. In this thesis three methods of OSP are discussed: the effective independence (EFI) method, the modal kinetic energy (MKE) method, and the damage diagnosability (DD) method. The EFI method has additional subtypes based on including sensor noise statistics and the driving point residue, these are also discussed. The three OSP methods are implemented for a hollow steel structure (HSS) beam and the S101 bridge. The methods are coded in MATLAB and make use of SAP2000 models. Furthermore, the HSS beam model is created in SAP2000 and calibrated to match the frequencies obtained through operational modal analysis (OMA). While a calibrat...