• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.815-820
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• 2000

The early damage detection of large structures is very important to prevent the disaster due to its global failure. In this paper, a damage detection method of the beam-analogy structure based on the wavelet transformation of mode shape is presented. This can effectively detect the singularity of mode shape caused to the inconsistency of bending moment and shear force at the damaged part using the discrete wavelet and its inverse transforms. To investigate the validity and the applicability of the presented damage detection method, numerical simulation and experiment are carried out for the idealized beam and the real ship structures.

• Structural Monitoring and Maintenance
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• v.2 no.2
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• pp.165-180
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• 2015

In this paper lead zirconate titanate transducers (PZT) are employed for damage detection of four reinforced concrete (RC) column specimens retrofitted with carbon fiber reinforced polymer (CFRP) jackets. A major disadvantage of FRP jacketing in RC members is the inability to inspect visually if the concrete substrate is damaged and in such case to estimate the extent of damage. The parameter measured during uniaxial compression tests at random times for known strain values is the real part of the complex number of the Electromechanical Admittance (Conductance) of the sensors, obtained by a PXI platform. The transducers are placed in specific positions along the height of the columns for detecting the damage in different positions and carrying out conclusions for the variation of the Conductance in relation to the position the failure occurred. The quantification of the damage at the concrete substrate is achieved with the use of the root-mean-square-deviation (RMSD) index, which is evaluated for the corresponding strain values. The experimental results provide evidence that PZT transducers are sensitive to damage detection from an early stage of the experiment and that the use of PZT sensors for monitoring and detecting the damage of FRP-retrofitted reinforced concrete members, by using the Electromechanical Admittance (EMA) approach, can be a highly promising method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.90-95
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• 2012

Remotely sensed data provide valuable information on land monitoring due to multi-temporal observation over large areas. Especially, high resolution imagery with 0.6~1.0 m spatial resolutions contain a wealth of information and therefore are very useful for thematic mapping and monitoring change in urban areas. Recently, remote sensing technology has been successfully utilized for natural disaster monitoring such as forest fire, earthquake, and floods. In this paper, an efficient change detection method based on texture differences observed from high resolution multi-temporal data sets is proposed for mapping disaster damage and extracting damage information. It is composed of two parts: feature extraction and detection process. Timely and accurate information on disaster damage can provide an effective decision making and response related to damage.

• Computers and Concrete
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• v.27 no.5
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• pp.447-455
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• 2021

Research on damage detection methods in structures began a few decades ago with the introduction of methods based on structural vibration frequencies, which, of course, continues to this day. The value of important structures, on the one hand, and the countless maintenance costs on the other hand, have led researchers to always try to identify more accurate methods to diagnose damage to structures in the early stages. Among these, one of the most important and widely used methods in damage detection is the use of time-frequency representations. By using time-frequency representations, it is possible to process signals simultaneously in the time and frequency domains. In this research, the Short-Time Fourier transform, a known time-frequency function, has been used to process signals and identify the system. Besides, a new damage index has been introduced to identify damages in concrete piers of bridges. The proposed method has relatively simple calculations. To evaluate the method, the finite element model of an existing concrete bridge was created using as-built details. Based on the results, the method identifies the damages with high accuracy.

• 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.

• Toxicological Research
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• v.32 no.1
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• pp.47-56
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• 2016

The identification of biomarkers for the early detection of acute kidney injury (AKI) is clinically important. Acute kidney injury (AKI) in critically ill patients is closely associated with increased morbidity and mortality. Conventional biomarkers, such as serum creatinine (SCr) and blood urea nitrogen (BUN), are frequently used to diagnose AKI. However, these biomarkers increase only after significant structural damage has occurred. Recent efforts have focused on identification and validation of new noninvasive biomarkers for the early detection of AKI, prior to extensive structural damage. Furthermore, AKI biomarkers can provide valuable insight into the molecular mechanisms of this complex and heterogeneous disease. Our previous study suggested that pyruvate kinase M2 (PKM2), which is excreted in the urine, is a sensitive biomarker for nephrotoxicity. To appropriately and optimally utilize PKM2 as a biomarker for AKI requires its complete characterization. This review highlights the major studies that have addressed the diagnostic and prognostic predictive power of biomarkers for AKI and assesses the potential usage of PKM2 as an early biomarker for AKI. We summarize the current state of knowledge regarding the role of biomarkers and the molecular and cellular mechanisms of AKI. This review will elucidate the biological basis of specific biomarkers that will contribute to improving the early detection and diagnosis of AKI.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.3
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• pp.185-192
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• 2015

Since real-time monitoring systems, such as early fault detection, have been very important, an infrared thermography technique was proposed as a new diagnosis method. This study focused on damage detection and temperature characteristic analysis of ball bearings using the non-destructive, infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with finite element analysis (FEA) results from ANSYS. In this investigation, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally, it was confirmed that the infrared thermography technique was useful for the real-time detection of damage to bearings.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.504-514
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• 2009

Recently, fire monitoring application systems have been an active research area due to the safety of industries, historical monuments and so on. The fire monitoring application systems can reduce the damage of properties by providing earlier warning for possible fire situation. However, the existing systems have a drawback that they detect fire with delay due to their uniform epoch in fire detection algorithm. Moreover, they do not provide user-friendly graphical user interfaces in their fire monitoring systems. To resolve the problems, First, we propose a new fire detection algorithm (Early Fire Detection Fire Algorithm) which uses the distribution of sensing data for early fire detection. Our fire detection algorithm is better in terms of fire detection time than the existing work because it can set a start time of fire detection epoch dynamically based on data distribution. Second, we develop a fire monitoring application system which provides users with both a user-friendly graphical user interface and a fire alarm message when fire occurs. Finally, we show from our experiment that our developed system is effectively used for early fire warning in a variety of fire situations.

• Clinical and Experimental Pediatrics
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• v.56 no.7
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• pp.271-274
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• 2013

Brain insults, including neurotrauma, infection, and perinatal injuries such as hypoxic ischemic encephalopathy, generate inflammation in the brain. These inflammatory cascades induce a wide spectrum of cytokines, which can cause neuron degeneration, have neurotoxic effects on brain tissue, and lead to the development of seizures, even if they are subclinical and occur at birth. Cytokines are secreted by the glial cells of the central nervous system and they function as immune system mediators. Cytokines can be proinflammatory or anti-inflammatory. Interleukin (IL)-$1{\beta}$ and IL-8 are proinflammatory cytokines that activate additional cytokine cascades and increase seizure susceptibility and organ damage, whereas IL-1 receptor antagonist and IL-10 act as anti-inflammatory cytokines that have protective and anticonvulsant effects. Therefore, the immune system and its associated inflammatory reactions appear to play an important role in brain damage. Whether cytokine release is relevant for the processes of epileptogenesis and antiepileptogenesis, and whether epileptogenesis could be prevented by immunomodulatory treatment should be addressed in future clinical studies. Furthermore, early detection of brain damage and early intervention are essential for the prevention of disease progression and further neurological complications. Therefore, cytokines might be useful as biomarkers for earlier detection of brain damage in high-risk infants.

• Computers and Concrete
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• v.20 no.5
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• pp.563-572
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• 2017

Ordinary reinforced concrete (RC) and prestressed concrete bridges are two popular and typical types of short- and medium-span bridges that accounts for the vast majority of all existing bridges. The cost of maintaining, repairing or replacing degraded existing RC bridges is immense. Detecting the abnormality of RC bridges at an early stage and taking the protective measures in advance are effective ways to improve maintenance practices and reduce the maintenance cost. This study proposes a systematic method from influence line (IL) identification to damage detection with applications to RC bridges. An IL identification method which integrates the cubic B-spline function with Tikhonov regularization is first proposed based on the vehicle information and the corresponding moving vehicle induced bridge response time history. Subsequently, IL change is defined as a damage index for bridge damage detection, and information fusion technique that synthesizes ILs of multiple locations/sensors is used to improve the efficiency and accuracy of damage localization. Finally, the feasibility of the proposed systematic method is verified through experimental tests on a three-span continuous RC beam. The comparison suggests that the identified ILs can well match with the baseline ILs, and it demonstrates that the proposed IL identification method has a high accuracy and a great potential in engineering applications. Results in this case indicate that deflection ILs are superior than strain ILs for damage detection of RC beams, and the performance of damage localization can be significantly improved with the information fusion of multiple ILs.