• Proceedings of the KIEE Conference
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• 2004.05b
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• pp.94-96
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• 2004

In order to observe the thermal behavior of oil immersed power transformers the temperature rise prediction algorithm and monitoring system were developed. The algorithm is formulated into a computer program based on the TNM (Thermal Network Method) which was divided into several elements, and the temperature of each element was calculated according to each time lapse. A monitoring system can show the real time active part temperatures of the transformer under various electric loads and for any types of thermal environment.

• Journal of the Korean Society of Safety
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• v.21 no.4 s.76
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• pp.95-101
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• 2006

It is well known that the thermal load in PSC(prestressed concrete) box-girder bridge is the principal cause of detrimental crack. The longitudinal stress caused by the lateral stress from the temperature gradient in slab of PSC box-girder bridge has a considerable influence on the durability and economy of bridge structures. As the basic study for the rational consideration of thermal load and the derivation of design guide, the inverse thermal analysis program for PSC box-girder bridges using field measurement data is developed. In this paper, thermal analyses are performed using field monitoring data for the sample PSC box-girder bridge. It is proposed that the link between monitoring program and the inverse analysis program is available.

• Corrosion Science and Technology
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• v.15 no.6
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• pp.259-264
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• 2016

With a specially designed electrochemical cell, the changes in impedance behavior for Inconel 600 and aluminide diffusion coatings under molten sulfate film with thermal cycles (from $800^{\circ}C$ to $350^{\circ}C$) were monitored with electrochemical impedance measurements. It was found that corrosion resistance for both materials increased with lower temperatures. At the same time, the state of molten salt was also monitored successfully by measuring the changes in impedance at high frequency, which generally represents the resistance of molten salt itself. After two thermal cycles, both Inconel 600 and aluminide diffusion coatings showed excellent corrosion resistance. The results from SEM observation and EDS analysis correlated well with the results obtained by electrochemical impedance measurements. It is concluded that electrochemical impedance is very useful for monitoring the corrosion resistance of materials under molten salt film conditions even with thermal cycles.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.1100-1109
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• 2006

In this study, two different technologies which can measure temperature simultaneously at many points are introduced. One is to use a thermal sensor cable that is comprised of addressable thermal sensors connected in parallel within a single cable. The other is to use an optic fiber with Distributed Temperature Sensing (DTS) system. The difference between two technologies can be summarized as follows. A thermal sensor cable has a concept of 'point sensing' that can measure temperature at accurate position of a thermal sensor. So the accuracy and resolution of temperature measurement are up to the ability of the thermal sensor. Whereas optic fiber sensor has a concept of 'distributed sensing' because temperature is measured by ratio of Stokes and anti-Stokes component intensities of Raman backscatter that is generated when laser pulse travels along an optic fiber. It's resolution is determined by measuring distance, measuring time and spatial resolution. The purpose of this study is that application targets of two temperature measurement techniques are checked in technical and economical phases by examining the strength and weakness of them. Considering the functions and characteristics of two techniques, the thermal sensor cable will be suitable to apply to the assessment of groundwater flow, geothermal distribution and grouting efficiency within 300m distance. It is expected that the optic fiber sensor can be widely utilized at various fields (for example: pipe line inspection, tunnel fire detection, power line monitoring etc.) which need an information of temperature distribution over relatively long distance.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.206-207
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• 2020

Accurate estimation of concrete strength development at early ages is a critical factor to secure structural stability as well as to speed up the construction process. The temperature generated from the heat of hydration is considered as a key parameter in predicting the early age strength. Conventionally, concrete temperature has been measured by temperature sensors installed inside concrete. However, considering the measurement on building structures with multiple floors, this method requires reinstallation and repositioning of hardware such as sensors, data loggers and routers for data transfer. This makes the temperature monitoring work cumbersome and inefficient. Concrete temperature monitoring by using thermal remote sensing can be an effective alternative to supplement those shortcomings. In this study, image processing was carried out through K-means clustering technique, which is a unsupervised learning method, and the classification results were analyzed accordingly. In the future, research will be conducted on how to automatically recognize concrete among various objects by using deep learning techniques.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.535-537
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• 2004

The flame image processing and it's analysis system has been developed for optimal coal firing of thermal power plant, especially for reducing NOx and safe operations. We aimed at gaining the relationship between burner flame image, emissions of NOx and LOI(Loss on ignition) in furnace by utilizing the flame image processing methods. And the relationship determines quantitatively the conditions of combustion on the individual burners. The test was conducted on Samchonpo thermal power plant #4 unit(560MW) of KOSEP which has 24 burners. The system simplified the burner adjustment works in accordance with the real time trending of flame behavior like NOx profiles and unburned carbon profiles for individual burners. But, This kind of conventional method increases the cost as the number of burner are increased. Also there is a difficulty to measure exhausted gas of each burner because of measurement errors. This paper intends to propose the useful "Flame Monitoring System" that can find Low NOX and LOI at the upper furnace and to compare with the conventional System.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1177-1186
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• 2009

High temperature steam pipes of thermal power plant are subject to a severe thermal range and usually operates well into the creep range. Cyclic operation of the plant subjects the piping system to mechanical and thermal fatigue damages. Also, poor or malfunctional supports can impose massive loads or stress onto the piping system. In order to prevent the serious damage and failure of the critical piping system, various inspection methods such as visual inspection, computational analysis and on-line piping displacement monitoring were developed. 3-dimensional piping displacement monitoring system was developed with using the aluminum alloy rod and rotary encoder sensors, this system was installed and operated on the high temperature steam piping of "Y" thermal power plant successfully. It is expected that this study will contribute to the safety of piping system, which could minimize stress and extend the actual life of critical piping.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• Structural Monitoring and Maintenance
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• v.3 no.2
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• pp.129-144
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• 2016

We present a methodology to validate with monitoring data finite element models of existing concrete dams: numerical analyses are performed to assess the structural response under the effects of seasonal loading conditions, represented by hydrostatic pressure on the upstream-downstream dam surfaces and thermal variations as recorded by a thermometers network. We show that the stiffness effect of the rock foundation and the surface degradation of concrete due to aging are crucial aspects to be accounted for a correct interpretation of the real behavior. This work summarizes some general procedures developed by this research group at Politecnico di Milano on traditional static monitoring systems and two significant case studies: a buttress gravity and an arch-gravity dam.

• Journal of the Korean Geotechnical Society
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• v.23 no.4
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• pp.15-24
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• 2007

Two kinds of temperature monitoring technology have been introduced in this study, which can measure coincidently temperatures at many points along a single length of cable. One is to use a thermal sensor cable comprizing of addressable thermal sensors. The other is to use an optic fiber sensor with Distributed Temperature Sensing (DTS) system. The differences between two technologies can be summarized as follows: A thermal sensor cable has a concept of "point sensing" that can measure temperature only at a predefined position. The accuracy and resolution of temperature measurement are up to the capability of the individual thermal sensor. On the other hand, an optic fiber sensor has a concept of "distributed sensing" because temperature is measured practically at all points along the fiber optic cable by analysing the intensity of Raman back-scattering when a laser pulse travels along the fiber. Thus, the temperature resolution depends on the measuring distance, measuring time and spatial resolution. The purpose of this study is to investigate the applicability of two different temperature monitoring techniques in technical and economical sense. To this end, diverse experiments with two techniques were performed and two techniques are applied under the same condition. Considering the results, the thermal sensor cable will be well applicable to the assessment of groundwater flow, geothermal distribution and grouting efficiency within about loom distance, and the optic fiber sensor will be suitable for long distance such as pipe line inspection, tunnel fire detection and power line monitoring etc.