• Journal of Ocean Engineering and Technology
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• v.24 no.3
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• pp.1-10
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• 2010

In this study, hybrid smart sensor nodes were developed for the autonomous structural health monitoring of prestressed concrete (PSC) girders. In order to achieve the objective, the following approaches were implemented. First, we show how two types of smart sensor nodes for the hybrid health monitoring were developed. One was an acceleration-based smart sensor node using an MEMS accelerometer to monitor the overall damage in concrete girders. The other was an impedance-based smart sensor node for monitoring the local damage in prestressing tendons. Second, a hybrid monitoring algorithm using these smart sensor nodes is proposed for the autonomous structural health monitoring of PSC girders. Finally, we show how the performance of the developed system was evaluated using a lab-scaled PSC girder model for which dynamic tests were performed on a series of prestress-loss cases and girder damage cases.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.225-231
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• 2006

The purpose of this study is to develop a promising hybrid structural health monitoring system for structural joints. For this propose, the combined use of vibration-based techniques and electro-mechanical impedance technique is employed. For the verification of the proposed health monitoring scheme, a series of damage scenarios are designed to simulate various situations at which the connection joints can experience during their service life. The obtained experimental results, modal parameters and electro-magnetic impedance signatures, are carefully analyzed to recognize the connecting states and the target damage locations. From the analysis. it is shown that the proposed hybrid health monitoring system is successful for acquiring global and local damage information on the structural joints.

• Smart Structures and Systems
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• v.22 no.5
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• pp.587-609
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• 2018

There is greater significance in identifying the incipient damages in structures at the time of their initiation as timely rectification of these minor incipient cracks can save huge maintenance cost. However, the change in the global dynamic characteristics of a structure due to these subtle damages are insignificant enough to detect using the majority of the current damage diagnostic techniques. Keeping this in view, we propose a hybrid damage diagnostic technique for detection of minor incipient damages in the structures. In the proposed automated hybrid algorithm, the raw dynamic signatures obtained from the structure are decomposed to uni-modal signals and the dynamic signature are reconstructed by identifying and combining only the uni-modal signals altered by the minor incipient damage. We use these reconstructed signals for damage diagnostics using ARMAX model. Numerical simulation studies are carried out to investigate and evaluate the proposed hybrid damage diagnostic algorithm and their capability in identifying minor/incipient damage with noisy measurements. Finally, experimental studies on a beam are also presented to compliment the numerical simulations in order to demonstrate the practical application of the proposed algorithm.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.669-674
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• 2007

To develop a promising hybrid structural health monitoring (SHM) system, a combined use of structural vibration and electro-mechanical (EM) impedance is proposed. The hybrid SHM system is designed to use vibration characteristics as global index and EM impedance as local index. The proposed health monitoring scheme is implemented into prestressed concrete (PSC) girder bridges for which a series of damage scenarios are designed to simulate various prestress-loss situations at which the target bridges car experience during their service life. The measured experimental results, modal parameters and electro-magnetic impedance signatures, are carefully analyzed to recognize the occurrence of damage and furthermore to indicate its location.

• Smart Structures and Systems
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• v.7 no.5
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• pp.393-416
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• 2011

Hybrid acceleration-impedance sensor nodes on Imote2-platform are designed for damage monitoring in steel girder connections. Thus, the feasibility of the sensor nodes is examined about its performance for vibration-based global monitoring and impedance-based local monitoring in the structural systems. To achieve the objective, the following approaches are implemented. First, a damage monitoring scheme is described in parallel with global vibration-based methods and local impedance-based methods. Second, multi-scale sensor nodes that enable combined acceleration-impedance monitoring are described on the design of hardware components and embedded software to operate. Third, the performances of the multi-scale sensor nodes are experimentally evaluated from damage monitoring in a lab-scaled steel girder with bolted connection joints.

• Computational Structural Engineering
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• v.9 no.2
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• pp.163-171
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• 1996

A hybrid knowledge model which amalgamates an object-oriented modeling approach and logic programming implementation is presented for structural health monitoring and diagnosis of instrumented structures. Domain knowledge in structural monitoring and diagnosis is formalized and represented in a logic-based object-oriented modeling environment. The model and environment have been implemented and illustrated in the context of a laboratory case study of damage detection in a successively damaged steel structure.

• Wind and Structures
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• v.24 no.4
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• pp.385-403
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• 2017

In recent years, the wind energy has played an increasingly important role in national energy sector of many countries. To harvest more electric power, the wind turbine (WT) tower structure becomes physically larger, which may cause more risks during long-term operation. Associated with the great development of WT projects, the number of accidents related to large-scaled WT has also been increased. Therefore, a structural health monitoring (SHM) system for WT structures is needed to ensure their safety and serviceability during operational time. The objective of this study is to develop a hybrid damage detection method for WT tower structures by measuring vibration and impedance responses. To achieve the objective, the following approaches are implemented. Firstly, a hybrid damage detection scheme which combines vibration-based and impedance-based methods is proposed as a sequential process in three stages. Secondly, a series of vibration and impedance tests are conducted on a lab-scaled model of the WT structure in which a set of bolt-loosening cases is simulated for the segmental joints. Finally, the feasibility of the proposed hybrid damage detection method is experimentally evaluated via its performance during the damage detection process in the tested model.

• Structural Engineering and Mechanics
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• v.40 no.5
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• pp.719-743
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• 2011

A hybrid damage monitoring scheme using parallel acceleration-impedance approaches is proposed to detect girder damage and support damage in steel plate-girder bridges which are under ambient train-induced excitations. The hybrid scheme consists of three phases: global and local damage monitoring in parallel manner, damage occurrence alarming and local damage identification, and detailed damage estimation. In the first phase, damage occurrence in a structure is globally monitored by changes in vibration features and, at the same moment, damage occurrence in local critical members is monitored by changes in impedance features. In the second phase, the occurrence of damage is alarmed and the type of damage is locally identified by recognizing patterns of vibration and impedance features. In the final phase, the location and severity of the locally identified damage are estimated by using modal strain energy-based damage index methods. The feasibility of the proposed scheme is evaluated on a steel plate-girder bridge model which was experimentally tested under model train-induced excitations. Acceleration responses and electro-mechanical impedance signatures were measured for several damage scenarios of girder damage and support damage.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1A
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• pp.61-73
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• 2009

In this paper, hybrid health monitoring techniques using acceleration-impedance features are newly proposed to detect two damage-type in steel plate-girder bridges, which are girder's stiffness-loss and support perturbation. The hybrid techniques mainly consists of three sequential phases: 1) to alarm the occurrence of damage in global manner, 2) to classify the alarmed damage into subsystems of the structure, and 3) to estimate the classified damage in detail using methods suitable for the subsystems. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the alarmed damage is classified into subsystems by recognizing patterns of impedance features. In the final phase, the location and the extent of damage are estimated by using modal strain energy-based damage index method and root mean square deviation (RMSD) method. The feasibility of the proposed hybrid technique is evaluated on a laboratory-scaled steel plate-girder bridge model for which hybrid acceleration-impedance signatures were measured for several damage scenarios. Also, the effect of temperature on the accuracy of the impedance-based damage monitoring results are experimentally examined from combined scenarios of support damage cases and temperature changes.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.