• Journal of the Korean Professional Engineers Association
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• v.32 no.6
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• pp.94-99
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• 1999

Recently, flood damage is rapidly increasing because of warming of globe, urbanization and industrialization. As a countermeasure to prevent these flood damages, it is quite required to extend the flood control ability by improving the objective rivers in the watershed and building more medium to large scale reserviors. Simultaneously repairing and rehabilitation of facilities through the safety diagnosis for reinforcement of the facilities should be continuously proceeded. Also extensive implementation of drainage improvement, establishment of prevention and refairing system against flood damage and raise of accuracy of weather forecasting should be proceeded.

• Journal of Yeungnam Medical Science
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• v.18 no.1
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• pp.13-29
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• 2001

The enzyme activities of creatine kinase (CK), its isoenzyme MB (CK-MB) and of lactate dehydrogenase isoenzyme 1 (LD-1) have been used for years in diagnosing patients with chest pain in order to differentiate patients with acute myocardial infarction (AMI) from non-AMI patients. These methods are easy to perform as automated analyses, but they are not specific for cardiac muscle damage. During the early 90's the situation changed. First, creatine kinase ME mass (CK-MB mass) replaced the measurement of CK-MB activity. Subsequently cardiac-specific proteins, troponin T (cTnT) and troponin I (cTnI) appeared and displacing LD-1 analysis. However, troponin concentrations in blood increase only from four to six hours after onset of chest pain. Therefore a rapid marker such as myoglobin, fatty acid binding protein or glycogen phosphorylase BB could be used in early diagnosis of AMI. On the other hand, CK-MB isoforms alone may also be useful in rapid diagnosis of cardiac muscle damage. Myoglobin, CK-MB mass, cTnT and cTnI are nowadays widely used in diagnosing patients with acute chest pain. Myoglobin is not cardiac-specific and therefore requires supplementation with some other analyses such as troponins to support the myoglobin value. Troponins are very highly cardiac-specific. Only the sera of some patients with severe renal failure, which requires hemodialysis, have elevated cTnT and/or cTnI without there being any evidence of cardiac damage. The latest studies have shown that elevated troponin levels in sera of hemodialysis patients point to an increased risk of future cardiac events in a similar manner to the elevated troponin values in sera of patients with unstable angina pectoris. In addition, the bedside tests for cTnT and cTnI alone- or together with myoglobin and CK-ME mass can be used instead of quantitative analyses in the diagnosis of patients with chest pain. These rapid tests are easy to perform and they do not require expensive instrumentation. For the diagnosis of patient with chest pain, routinely myoglobin and CK-ME mass measurements should be performed whenever they are requested (24 h/day) and cTnT or cTnI on admission to the hospital and then 4-6 and 12 hours later and maintained less than 10% in imprecision.

• Journal of the Korean housing association
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• v.26 no.2
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• pp.67-79
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• 2015

As the Korean construction market in the apartment housing has changed to a housing consumer focused market, interest and importance on efficient use and management on existing buildings has increased rather than demand for new buildings. Interest of housing consumers on apartment house quality has increased in this market paradigm, and this spontaneously is connected to quality flaw related defect disputes and lawsuits that the importance of defect diagnosis has continuously increased. This defect diagnosis is directly connected to maintenance charges in defect dispute and lawsuit processes that rather objective and highly credible progress of duty is required. However, most defect diagnosis firms today that progress defect diagnosis are using different diagnosis methods and depend on the experience of experienced professionals that there is no standardized defect diagnosis process. Therefore, the purpose of this study is to provide common defect diagnosis process model for defect diagnosis firms utilizing the BPMN (Business Process Modeling Notation) modeling method. It is expected that this will contribute to professional and reliable task performances of concerned defect diagnosis workers. Furthermore, it is expected that design lawsuit damage will be substantially reduced by standardizing defect diagnosis processes.

• Structural Engineering and Mechanics
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• v.31 no.3
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• pp.333-347
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• 2009

Due to structural complicacy, structural health monitoring for civil engineering needs more accurate and effectual methods of damage identification. This study aims to import multi-source information fusion (MSIF) into structural damage diagnosis to improve the validity of damage detection. Firstly, the essential theory and applied mathematic methods of MSIF are introduced. And then, the structural damage identification method based on multi-mode information fusion is put forward. Later, on the basis of a numerical simulation of a concrete continuous box beam bridge, it is obviously indicated that the improved modal strain energy method based on multi-mode information fusion has nicer sensitivity to structural initial damage and favorable robusticity to noise. Compared with the classical modal strain energy method, this damage identification method needs much less modal information to detect structural initial damage. When the noise intensity is less than or equal to 10%, this method can identify structural initial damage well and truly. In a word, this structural damage identification method based on multi-mode information fusion has better effects of structural damage identification and good practicability to actual structures.

• Smart Structures and Systems
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• v.5 no.1
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• pp.95-117
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• 2009

In this paper, the time series based damage detection algorithms developed by Nair, et al. (2006) and Nair and Kiremidjian (2007) are applied to the benchmark experimental data from the National Center for Research on Earthquake Engineering (NCREE) in Taipei, Taiwan. Both acceleration and strain data are analyzed. The data are modeled as autoregressive (AR) processes, and damage sensitive features (DSF) and feature vectors are defined in terms of the first three AR coefficients. In the first algorithm developed by Nair, et al. (2006), hypothesis tests using the t-statistic are applied to evaluate the damaged state. A damage measure (DM) is defined to measure the damage extent. The results show that the DSF's from the acceleration data can detect damage while the DSF from the strain data can be used to localize the damage. The DM can be used for damage quantification. In the second algorithm developed by Nair and Kiremidjian (2007) a Gaussian Mixture Model (GMM) is used to model the feature vector, and the Mahalanobis distance is defined to measure damage extent. Additional distance measures are defined and applied in this paper to quantify damage. The results show that damage measures can be used to detect, quantify, and localize the damage for the high intensity and the bidirectional loading cases.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.2
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• pp.253-259
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• 2006

There is few study which automatically diagnoses the fault from ship's monitored data. The bigger control and monitoring system is. the more important fault diagnosis and maintenance is to reduce damage caused by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault from monitored data and is composed of fault detection knowledge base and fault diagnosis knowledge base. For all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem, To verify capability of fault detection, diagnosis and prediction, FMS(Fault Management System) is developed by C++. Simulation by FMS is carried out with population data set made by the log book data of 2 months duration from a large full container ship of H shipping company.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.251-256
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• 2005

There is few study which automatically diagnose the fault from ship's monitored signal. The bigger control and monitoring system is, the more important fault diagnosis and maintenance is to reduce damage brought forth by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault and is composed to fault detection knowledge base and fault diagnosis knowledge base. For this all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem by analyzing ship's operation data. To verifying capability of fault detection, diagnosis and prediction, Fault Management System(FMS) is developed by C++. Simulation experiment by FMS is carried out with population data set made by log book data of 2 months duration from a large full container ship of H shipping company.

• Structural Monitoring and Maintenance
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• v.5 no.3
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• pp.379-390
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• 2018

In this paper, a novel and effective damage diagnosis algorithm is proposed to detect and estimate damage using two stages least squares support vector machine (LS-SVM) and limited number of attached sensors on structures. In the first stage, LS-SVM1 is used to predict the unmeasured mode shapes data based on limited measured modal data and in the second stage, LS-SVM2 is used to predicting the damage location and severity using the complete modal data from the first-stage LS-SVM1. The presented methods are applied to a three story irregular frame and cantilever plate. To investigate the noise effects and modeling errors, two uncertainty levels have been considered. Moreover, the performance of the proposed methods has been verified through using experimental modal data of a mass-stiffness system. The obtained damage identification results show the suitable performance of the proposed damage identification method for structures in spite of different uncertainty levels.

• Smart Structures and Systems
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• v.17 no.1
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• pp.107-122
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• 2016

We propose an effective methodology using electromechanical impedance characteristics for estimating the remaining tensile force of tendons and simultaneously detecting damages of the anchorage blocks. Once one piezoelectric patch is attached on the anchor head and the other is bonded on the bearing plate, impedance responses are measured through these two patches under varying tensile force conditions. Then statistical indices are calculated from the impedances, and two types of relationship curves between the tensile force and the statistical index (TE Curve) and between statistical indices of two patches (SR Curve) are established. Those are considered as database for monitoring both the tendon and the anchorage system. If damage exists on the bearing plate, the statistical index of patch on the bearing plate would be out of bounds of the SR curve and damage can be detected. A change in the statistical index by damage is calibrated with the SR curve, and the tensile force can be estimated with the corrected index and the TE Curve. For validation of the developed methodology, experimental studies are performed on the scaled model of an anchorage system that is simplified only with 3 solid wedges, a 3-hole anchor head, and a bearing plate. Then, the methodology is applied to a real scale anchorage system that has 19 strands, wedges, an anchor head, a bearing plate, and a steel duct. It is observed that the proposed scheme gives quite accurate estimation of the remaining tensile forces. Therefore, this methodology has great potential for practical use to evaluate the remaining tensile forces and damage status in the post-tensioned structural members.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.585-590
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• 2024

In this study, rail surface defects are increasing due to the aging of urban railway rails, but in the detailed guidelines for track performance evaluation established by the country, rail surface damage is inspected with the naked eye of engineers and simple measuring tools. With the recent enactment of the Track Diagnosis Act, a large budget has been invested and the volume of rail diagnosis is rapidly increasing, but it is difficult to secure the reliability of diagnosis results using labor-intensive visual inspection techniques. It is very important to discover defects in the rail surface through periodic track tours and visual inspection. However, evaluating the severity of defects on the rail surface based on the subjective judgment of the inspector has significant limitations in predicting damage inside the rail. In this study, the rail internal crack characteristics due to rail surface damage were studied. In field measurements, rail surface damage locations were selected, samples of various damage types were collected, and the rail surface damage status was evaluated. In indoor testing, we intend to analyze the correlation between rail surface defects and internal defects using a electron scanning microscope (SEM). To determine the crack growth rate of urban railway rails currently in use, the Gaussian probability density function was applied and analyzed.