• Journal of Internet of Things and Convergence
• /
• v.7 no.3
• /
• pp.9-14
• /
• 2021

This paper discovers the energy loss factors through the insulation diagnosis of houses or buildings, and proposes directions for energy efficiency improvement. The energy efficiency factor of a building consists of insulation diagnosis, thermal bridge diagnosis, window diagnosis, airtight diagnosis, and equipment diagnosis. Among the residents and facilities in the energy welfare blind spot, an energy efficiency diagnosis was conducted for one senior citizen building located in Naju-si, Jeollanam-do, and energy efficiency diagnosis was conducted after insulation was installed. Energy measurement, diagnosis and analysis were performed using the IoT-based integrated wired/wireless energy diagnosis platform, Energy Finder. As a result of comparison, an overall energy saving rate of 16.38% was achieved. Annual heating energy consumption per unit area decreased from 333.51kWh before construction to 277.35kWh after construction, and annual cooling energy consumption per unit area decreased from 5.51kWh before construction to 5.22kWh after construction. The annual primary energy consumption per unit area decreased from 464.52kWh before construction to 403.69kWh after construction, and the annual energy cost was reduced from 3,063,307.14 won before construction to 2,641,072.49 won after construction. The additional improvement work is needed on the standards affecting energy efficiency other than insulation.

• Journal of the Korean Solar Energy Society
• /
• v.36 no.5
• /
• pp.91-100
• /
• 2016

This paper proposes the PV module fault diagnosis sensor which is applied to Zigbee wireless network, and monitoring system using the developed sensor. It is designed with embedded sensor in junction box. The diagnosis elements for algorithm were voltage and temperature. For that reason, It is able to reduce the price and separate the fault of bypass diode from shading differently from other monitoring systems. This fault diagnosis algorithm verified through the Field-installed operations of PV module.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.7
• /
• pp.1295-1302
• /
• 2016

In this paper, a black box, which is provided the reliability and user safety of home battery energy storage system connected with solar energy generation, is developed. In the developed scheme, a status and diagnosis data of battery management system, power conditioning system, solar energy generation and grid is measured. This status and diagnosis data is stored and displayed in the developed black box. In addition, this status and diagnosis data is stored and displayed in a monitoring system and a smart phone of user. A performance evaluation of the developed black box is carried out using emulator of home battery energy storage system connected with solar energy generation. Consequently, the developed black box is proved its superiority of the reliability and user safety.

• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.22 no.1
• /
• pp.45-56
• /
• 2018

The authors are using Qi-diagnosis (integrated diagnosis by bio-energy) that is a method of diagnosis and treatment. We applied Qi-diagnosis to the main study to lay the foundation and framework for research and education about the Korean Medicine. The authors try to describe systemically and specifically the Qi-diagnosis that the authors are using in clinical diagnosis ane treatment so that anyone can use it. The authors have been able to grasp the flow of human bio-energy through years of training. It has had many effects by applying the Qi-diagnosis to patients. The steps of the bio-energy flow have become objective. And the authors have been applied to acupuncture, herbal medicine, moxibustion, bruising treatment and anthrax anesthesia in clinical through the Qi-diagnosis. Also, it is applied to the life management of patients. It is applied to arts such as music therapy and art therapy. The deeper the depth of the Qi-diagnosis, the greater the opportunity to utilize the Qi-diagnosis. The Qi-diagnosis is the origin of the korean medicine. It was able to make diagnosis and treatment correct and to establish clues that the medical problems would be solved through the Qi-diagnosis. In order to do so, the diagnostician must be able to feel the auricular flow of the body accurately and objectively. In addition, he must have a comprehensive understanding of the overall framework of medicine. As a result, diagnosis and treatment of the patient as well as general problems of the patient can be identified and advised, so comprehensive treatment is possible. And it is not only a specific person can do it, but it is a diagnostic method that anyone can take if they take the basic steps step by step.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.67 no.3
• /
• pp.160-167
• /
• 2018

In this paper, a black box, which is provided the reliability and user safety of home battery energy storage system connected with solar energy generation, is developed. In the developed scheme, a status and diagnosis data of battery management system, power conditioning system, solar energy generation and grid is measured. This status and diagnosis data is stored and displayed in the developed black box. In addition, this status and diagnosis data is stored and displayed in a monitoring system and a smart phone of user. A performance evaluation of the developed black box is carried out using emulator of home battery energy storage system connected with solar energy generation. Consequently, the developed black box is proved its superiority of the reliability and user safety.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.9
• /
• pp.512-519
• /
• 2000

A Neural networks has been used for a expert system and fault diagnosis system. It is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping.쪼두 a fault occur in system a state of system is changed with transient state. Because of a previous state signal is considered as a information DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• Proceedings of the Korean Nuclear Society Conference
• /
• 1996.05a
• /
• pp.340-345
• /
• 1996

Because of limited resources of time and information processing capability during abnormal situation, diagnosis is difficult tasks in nuclear power plant (NPP) operators. Moreover since minimizing of adverse consequences according to process abnormalities is vital for the safety of NPP, introducing of diagnosis support systems have particularly emphasized. However, considerable works to develop effective diagnostic support system are not sufficiently fulfilled because of the complexity of NPP is one of the major problems. To cope with this complexity, a lot of model-based diagnosis support systems have considered and implemented worldwide. In this paper, as a prior step to development of model-based diagnosis support systems, primary side of pressurized water reactor is functionally modeled by multilevel flow modeling (MFM) concept. MFM is suitable for complex system modeling and for diagnosis of abnormalities. Furthermore, knowledge-based diagnosis process, of NPP operator could be supported because this diagnosis strategy can represent operator's one.

• Nuclear Engineering and Technology
• /
• v.50 no.4
• /
• pp.599-605
• /
• 2018

Fault diagnosis depends critically on the selection of sensors monitoring crucial process variables. Boolean network (BN) is composed of nodes and directed edges, where the node state is quantized to the Boolean values of True or False and is determined by the logical functions of the network parameters and the states of other nodes with edges directed to this node. Since BN can describe the fault propagation in a sensor network, it can be applied to propose sensor selection strategy for fault diagnosis. In this article, a sufficient condition for parameter identifiability of BN is first proposed, based on which the sufficient condition for fault identifiability of a sensor network is given. Then, the fault identifiability condition induces a sensor selection strategy for sensor selection. Finally, the theoretical result is applied to the fault diagnosis-oriented sensor selection for a nuclear heating reactor plant, and both the numerical computation and simulation results verify the feasibility of the newly built BN-based sensor selection strategy.

• Journal of Mechanical Science and Technology
• /
• v.19 no.8
• /
• pp.1670-1681
• /
• 2005

In-situ diagnosis of chiller performance is an essential step for energy saving business. The main purpose of the in-situ diagnosis is to predict the performance of a target chiller. Many models based on thermodynamics have been proposed for the purpose. However, they have to be modified from chiller to chiller and require profound knowledge of thermodynamics and heat transfer. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). The effect of sample data distribution on training the ANFIS is investigated. It is found that the data sampling over 10 days during summer results in a reliable ANFIS whose performance prediction error is within measurement errors. The reliable ANFIS makes it possible to prepare an energy audit and suggest an energy saving plan based on the diagnosed chilled water supply system.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.19 no.4
• /
• pp.840-847
• /
• 2005

This study was written in order to help understanding of visible diagnosis of energy and color(기색). Visible diagnosis of energy and color is a very important factor of diagnosis and a necessary step of visible diagnosis. As human's body is under the control of spirit(신) and spirit(신) is stored by five viscera(오장), so spirit expresses the change of five viscera and is reflected by energy and color(기색). Strictly speaking, energy and color(기색) is not divided into each other. But, we can say that glittering glossy part belongs to energy(기) and blue, red, yellow, white and black part belongs to color(색). Various changes of energy and color(기색) observe the rules of yin-yang(음양). If we consider the interior and exterior(내외), top and bottom(상하), right and left(좌우), rise and fall(부침), clearness and muddiness(청탁), weak and severe(미심), spread and gather(산박), gloss and dness(택요) etc. we can decide the yin and yang(음양), inside and outside(표리), coldness and heatness(한열), truth and false(허보), life and death(생사) and prognosis. One man's own color is determined by the five human type(오형인), There are very various points of changing colors. As divided into principal groups, there are three main groups, that is, sky(천), earth(지) and man(인). A season(사시), day and night(주야) and cloud and clear(음청) belong to the factor of sky(천), a direction and configuration of the ground(지형) belong 治 the factor of earth(지), and motion and rest(동정), seven emotions(칠정), age and youth(노소), poor and rich(빈부) and high and low(귀천) belong to the factor of man(인).