• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.779-788
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• 2017

System identification and damage detection for structural health monitoring have received considerable attention. Various time domain analysis methodologies based on measured vibration data of structures have been proposed. Among them, recursive least-squares estimation of structural parameters which is also known as parametric Kalman filter (PKF) approach has been studied. However, the conventional PKF requires that all the external excitations (inputs) be available. On the other hand, structural uncertainties are inevitable for civil infrastructures, it is necessary to develop approaches for probabilistic damage detection of structures. In this paper, a parametric Kalman filter with unknown inputs (PKF-UI) is proposed for the simultaneous identification of structural parameters and the unmeasured external inputs. Analytical recursive formulations of the proposed PKF-UI are derived based on the conventional PKF. Two scenarios of linear observation equations and nonlinear observation equations are discussed, respectively. Such a straightforward derivation of PKF-UI is not available in the literature. Then, the proposed PKF-UI is utilized for probabilistic damage detection of structures by considering the uncertainties of structural parameters. Structural damage index and the damage probability are derived from the statistical values of the identified structural parameters of intact and damaged structure. Some numerical examples are used to validate the proposed method.

• Structural Monitoring and Maintenance
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• v.3 no.1
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• pp.51-69
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• 2016

Monitoring the performance and estimating the remaining useful life of aging civil infrastructure in the United States has been identified as a major objective in the civil engineering community. Structural health monitoring has emerged as a central tool to fulfill this objective. This paper presents a review of the major structural monitoring programs that have been recently implemented in the United States, focusing on the integrity and performance assessment of large-scale structural systems. Applications where response data from a monitoring program have been used to detect and correct structural deficiencies are highlighted. These applications include (but are not limited to): i) Post-earthquake damage assessment of buildings and bridges; ii) Monitoring of cables vibration in cable-stayed bridges; iii) Evaluation of the effectiveness of technologies for retrofit and seismic protection, such as base isolation systems; and iv) Structural damage assessment of bridges after impact loads resulting from ship collisions. These and many other applications show that a structural health monitoring program is a powerful tool for structural damage and condition assessment, that can be used as part of a comprehensive decision-making process about possible actions that can be undertaken in a large-scale civil infrastructure system after potentially damaging events.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.95-102
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• 2003

To define an analytical model for a structural system or to assess damage in the system, system identification(SI) methods have been developed and widely applied. The paper presents a method of determining optimal sensor location(OSL) based on the maximum likelihood approach, which is applicable to modal SI methods. To estimate unknown parameters reliably, it is necessary that the information provided by the experiment should be maximized. By applying the Cramer-Rao inequality, a Fisher information matrix in terms of the probability density function of measurements is obtained from a lower bound of the estimation error. The paper also proposes a scheme of determining of OSL on damaged structures by using maximum strain energy factor. Simulation studies have carried out to investigate the proposed OSL algorithm for both undamaged and damaged structures.

• Journal of the Korea institute for structural maintenance and inspection
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• v.1 no.2
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• pp.87-94
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• 1997

This research aims to develop an algorithm of optimal transducer placement using Kinetic Energy of the structural system. The structural vibration response-based health monitoring is considered one of the best for the system which requires a long-term, continuous monitoring. In its experimental modal testing, however, it is difficult to decide on the measurement locations and their number, especially for complex structures, which have a major influence on the quality of the results. In order to minimize the number of sensing operations and optimize the transducer location while maximizing the accuracy of results, this paper discusses about an optimum transducer placement criterion suitable for the identification of structural damage. As a criterion algorithm, it proposes the Kinetic Energy Optimization Technique (EOT), and then addresses the numerical issues which are subsequently applicable to actual experiment where a bridge model is used. By using the experimental data, it compares the EOT with the EIM (Effective Independence Method) which is generally used to optimize the transducer placement for the damage identification and control purposes. The comparison conclusively shows that the EOT algorithm proposed in this paper is preferable when a structure is to be instrumented with fewer sensors.

• Journal of the Korean Society of Industry Convergence
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• v.8 no.4
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• pp.205-212
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• 2005

This paper presents the application of system identification approaches for the load carrying capacity evaluation of composite PCI girder bridges based on the result of field test. For these problems, the moment of inertia of cross-sectional area and the natural frequency of bridge were used as structural parameters, the SAP2000 program for the structural analysis and the SLP method for the minimum error. As a result, it is found that the proposed algorithm for this study appears applicable to real structures with reasonable complexity. It is shown that the introduction of approximate quadratic equations is more realistic and timesaving than the common methods.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.6
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• pp.527-538
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• 2010

This paper presents a nondestructive evaluation approach for system identification (SID) of real railway bridges using field vibration test results. First, a multi-phase SID scheme designed on the basis of eigenvalue sensitivity concept is presented. Next, the proposed multi-phase approach is evaluated from field vibration tests on a real railway bridge (Wondongcheon bridge) located in Yangsan, Korea. On the steel girder bridge, a few natural frequencies and mode shapes are experimentally measured under the ambient vibration condition. The corresponding modal parameters are numerically calculated from a three-dimensional finite element (FE) model established for the target bridge. Eigenvalue sensitivities are analyzed for potential model-updating parameters of the FE model. Then, structural subsystems are identified phase-by-phase using the proposed model-updating procedure. Based on model-updating results, a baseline model and a nondestructive evaluation of test bridge are identified.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.443-450
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• 2003

System identification techniques can be used to build a baseline modal model for a flawed structure that has no modal information on its as-built state. The accuracy of a system identification proposed by Stubbs and Kim is analyzed for plate-girder bridges and its impact on the accuracy of damage detection in those structures is also analyzed. A laboratory-scale model plate-girder is experimentally tested and the initial four bending modes are examined for certain damage scenarios. The performance of individual baseline modal models is assessed by detecting damage in the model structure.

• Structural Monitoring and Maintenance
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• v.11 no.2
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• pp.101-126
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• 2024

To avoid irregularities in buildings, design codes worldwide have introduced detailed guidelines for their check and rectification. However, the criteria used to define and identify each of the plan and vertical irregularities are specific and may vary between codes of different countries, thus making their implementation difficult. This short communication paper proposes a novel approach for quantifying different types of structural irregularities using a common parameter named as unified identification factor, which is exclusively defined for the columns based on their axial loads and tributary areas. The calculation of the identification factor is demonstrated through the analysis of rectangular and circular reinforced concrete models using ETABS v18.0.2, which are further modified to generate plan irregular (torsional irregularity, cut-out in floor slab and non-parallel lateral force system) and vertical irregular (mass irregularity, vertical geometric irregularity and floating columns) models. The identification factor is calculated for all the columns of a building and the range within which the value lies is identified. The results indicate that the range will be very wide for an irregular building when compared to that with a regular configuration, thus implying a strong correlation of the identification factor with the structural irregularity. Further, the identification factor is compared for different columns within a floor and between floors for each building model. The findings suggest that the value will be abnormally high or low for a column in the vicinity of an irregularity. The proposed factor could thus be used in the preliminary structural design phase, so as to eliminate the complications that might arise due to the geometry of the structure when subjected to lateral loads. The unified approach could also be incorporated in future revisions of codes, as a replacement for the numerous criteria currently used for classifying different types of irregularities.

• Structural Engineering and Mechanics
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• v.78 no.3
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• pp.369-378
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• 2021

This paper reviewed a few output-only system identification algorithms and identified the shortcomings of those popular blind source separation methods. To address the issues such as less sensors than the targeted modal modes (under-determinate problem), repeated natural frequencies as well as systems with complex mode shapes, this paper proposed a complex wavelet modified second order blind identification method (CWMSOBI) by transforming the time domain problem into time-frequency domain. The wavelet coefficients with different dominant frequencies can be used to address the under-determinate problem, while complex mode shapes are addressed by introducing the complex wavelet transformation. Numerical simulations with both high and low signal-to-noise ratios validate that CWMSOBI can overcome the above-mentioned issues while obtaining more accurate identified results than other blind identification methods.

• Smart Structures and Systems
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• v.15 no.1
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• pp.151-167
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• 2015

Instrumentation on structural health monitoring system imposes critical issues for applying the structural monitoring system to real world structures, for which not only on the configuration and geometry, but also aesthetics on the system to be monitored should be considered. To illustrate this point, two real world structural health monitoring systems, the structural health monitoring system of Shenzhen Vanke Center and the structural health monitoring system of Shenzhen Bay Stadium in China, are presented in the paper. The instrumentation on structural health monitoring systems of real world structures is addressed by providing the description of the structure, the purpose of the structural health monitoring system implementation, as well as details of the system integration including the installations on the sensors and acquisition equipment and so on. In addition, an intelligent algorithm on stress identification using measurements from multi-region is presented in the paper. The stress identification method is deployed using the fuzzy pattern recognition and Dempster-Shafer evidence theory, where the measurements of limited strain sensors arranged on structure are the input data of the method. As results, at the critical parts of the structure, the stress distribution evaluated from the measurements has shown close correlation to the numerical simulation results on the steel roof of the Beijing National Aquatics Center in China. The research work in this paper can provide a reference for the design and implementation of both real world structural health monitoring systems and intelligent algorithm to identify stress distribution effectively.