• Journal of Wind Energy
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• v.9 no.4
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• pp.16-23
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• 2018

A damage detection method for the tripod support structure of offshore wind turbines is presented for structural health monitoring. A finite element model of a prototype tripod support structure is established and the modal properties are calculated. The degree and location of the damage are estimated based on the neural network technique using the changes of natural frequencies and mode shape due to the damage. The stress distribution occurring in the support structure is obtained by a dynamic analysis for the wind turbine system to select the output data of the neural network. The natural frequencies and mode shapes for 36 possible damage scenarios were used for the input data of the learned neural network for damage assessment. The estimated damages agreed reasonably well with the accurate ones. The presented method could be effectively applied for damage detection and structural health monitoring of various types of support structures of offshore wind turbines.

• Computers and Concrete
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• v.4 no.3
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• pp.167-186
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• 2007

Ductility based design of reinforced concrete structures implicitly assumes certain damage under the action of a design basis earthquake. The damage undergone by a structure needs to be quantified, so as to assess the post-seismic reparability and functionality of the structure. The paper presents an analytical method of quantification and location of seismic damage, through system identification methods. It may be noted that soft ground storied buildings are the major casualties in any earthquake and hence the example structure is a soft or weak first storied one, whose seismic response and temporal variation of damage are computed using a non-linear dynamic analysis program (IDARC) and compared with a normal structure. Time period based damage identification model is used and suitably calibrated with classic damage models. Regenerated stiffness of the three degrees of freedom model (for the three storied frame) is used to locate the damage, both on-line as well as after the seismic event. Multi resolution analysis using wavelets is also used for localized damage identification for soft storey columns.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.118-125
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• 2003

Seismic damage assessment program for containment structure is developed. The program has been established through the combination of inelastic seismic analysis program and 3-D animation program. Damage indices at finite element level and structural level have been introduced for the seismic damage assessment. The seismic damage assessment program makes it possible to analyze in real-time the actual resistance capacity and damage level of containment structure. It will be expected that the program enables to establish the measures more quickly under the earthquake event.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.2
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• pp.3-10
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• 2018

Damage location and extent of structure could be detected by the inverse analysis on dynamic response properties such as frequencies and mode shapes. In practice the measured difference of natural frequencies represent the stiffness change reliably, however the measured mode shape is insensitive for stiffness change, but provides spatial information of damage. The damage detection index on shear building structures is formulated in this study. The damage detection index could be estimated from mode shape and srory stiffness of undamaged structure and frequency difference between undamaged and damaged structure. For the verification of the observed damage detection method, the numerical analysis of Matlab and MIDAS and shacking table test were performed. In results, the damage index of damaged story was estimated so higher than undamaged stories that indicates the damaged story apparently.

• Smart Structures and Systems
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• v.14 no.2
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• pp.85-104
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• 2014

Damage detection is a challenging, complex, and at the same time very important research topic in civil engineering. Identifying the location and severity of damage in a structure, as well as the global effects of local damage on the performance of the structure are fundamental elements of damage detection algorithms. Local damage detection is essential for structural health monitoring since local damages can propagate and become detrimental to the functionality of the entire structure. Existing studies present several methods which utilize sensor data, and track global changes in the structure. The challenging issue for these methods is to be sensitive enough in identifYing local damage. Autoregressive models with exogenous terms (ARX) are a popular class of modeling approaches which are the basis for a large group of local damage detection algorithms. This study presents an algorithm, called Influence-based Damage Detection Algorithm (IDDA), which is developed for identification of local damage based on regression of the vibration responses. The formulation of the algorithm and the post-processing statistical framework is presented and its performance is validated through implementation on an experimental beam-column connection which is instrumented by dense-clustered wired and wireless sensor networks. While implementing the algorithm, two different sensor networks with different sensing qualities are utilized and the results are compared. Based on the comparison of the results, the effect of sensor noise on the performance of the proposed algorithm is observed and discussed in this paper.

• Journal of Navigation and Port Research
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• v.36 no.3
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• pp.163-168
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• 2012

Recently, people's desire for the waterfront space has been increasing, and more people want to spend their leisure time close to the water. This paper proposes a damage detection technique using the static strain for the floating structure. An existing damage index, in which the modal strain energy was utilized to identify possible location of damage, is expanded to apply the static strain. The new damage index is expressed in terms of the static strains of undamaged and damaged structures. After calculating damage index, the possible damage locations in the structure are determined by the pattern recognition technique. The accuracy and feasibility of the proposed method is demonstrated by using experimental strain data from a scale model of floating structure.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.10a
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• pp.87-94
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• 1995

In highway bridges robust damage detection exercises are mandatory to secure the safety of the structures from hostile environmental conditions such as fatigue earthquake, wind, and corrosion. This paper presents a damage detection practice in a full-scale highway bridge by utilizing modal response parameters of as-built and damaged states of the structure. first the test structure is described and modal testing procedures are outlined. Next, a damage detection model which yields information on the location of damage directly from changes in mode shapes is outlined. Finally, the damage detection model is implemented to predict the location of damage in the ten structure. From the results, it was found that the damage detection model accurately locates damage in the test structures for which modal parameters of only a single mode are available for pre-damage (as-built) and post-damage stages.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.414-421
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• 1998

The content of this paper consists of two related subjects. One is the assessment of damages in the existing structure and the other is the evaluation of seismic capacity of the structure with damage. A method is presented for damage assessment of existing structures using the modal data measured at limited points by the inverse medal perturbation technique. For efficient damage assessment, the number of the unknown probable damaged members is reduced for each damage identification by grouping the members in the large structure. The aseismic capacity is evaluated for the structure using the results of damage assessment. An example analysis is carried out for a building structure subjected to different earthquake excitations.

• Earthquakes and Structures
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• v.18 no.4
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• pp.423-435
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• 2020

An accurate evaluation of structural damage is essential to performance-based seismic design for the structure across the earth fissure. By comparing the calculation results from three commonly used damage models and the experimental results, a weighted combination method using Chen model was selected in this paper as the seismic damage evaluation. A numerical model considering the soil-structure interaction (SSI) was proposed using ABAQUS software. The model was calibrated by comparing with the experimental results. The results from the analysis indicated that, for the structure across the earth fissure, the existence of earth fissure changed the damage distribution of the structural members. The damage of structural members in the hanging wall was greater than that in the foot wall. Besides, the earth fissure enlarged the damage degree of the structural members at the same location and changed the position of the weak story. Moreover, the damage degree of the structure across the earth fissure was greater than that of the structure without the earth fissure under the same excitation. It is expected that the results from this research would enhance the understanding of the performance-based seismic design for the structure across the earth fissure.

• Smart Structures and Systems
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• v.16 no.1
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• pp.223-242
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• 2015

Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases.