• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.3
• /
• pp.92-103
• /
• 2021

With the continuous acceleration of economic and social development, people gradually pay attention to their health, improve their living environment, diet, strengthen exercise, and even conduct regular health examination, to ensure that they always understand the health status. Even so, people still face many health problems, and the number of chronic diseases is increasing. Recently, COVID-19 has also reminded people that public health problems are also facing severe challenges. With the development of artificial intelligence equipment and technology, medical diagnosis expert systems based on big data have become a topic of concern to many researchers. At present, there are many algorithms that can help computers initially diagnose diseases for patients, but they want to improve the accuracy of diagnosis. And taking into account the pathology that varies from person to person, the health diagnosis expert system urgently needs a new algorithm to improve accuracy. Through the understanding of classic algorithms, this paper has optimized it, and finally proved through experiments that the combined classification algorithm improved by latent factors can meet the needs of medical intelligent diagnosis.

• Journal of the Korean Society of Safety
• /
• v.21 no.3 s.75
• /
• pp.16-21
• /
• 2006

This paper presents a knowledge-based electrical fire cause diagnosis system using the fuzzy reasoning. The cause diagnosis of electrical fires may be approached either by studying electric facilities or by investigating cause using precision instruments at the fire site. However, cause diagnosis methods for electrical fires haven't been systematized yet. The system focused on database(DB) construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. The cause diagnosis system for the electrical fire was implemented with entity-relational DB systems using Access 2000, one of DB development tools. Visual Basic is used as a DB building tool. The inference to confirm fire causes is conducted on the knowledge-based by combined approach of a case-based and a rule-based reasoning. A case-based cause diagnosis is designed to match the newly occurred fire case with the past fire cases stored in a DB by a kind of pattern recognition. The rule-based cause diagnosis includes intelligent objects having fuzzy attributes and rules, and is used for handling knowledge about cause reasoning. A rule-based using a fuzzy reasoning has been adopted. To infer the results from fire signs, a fuzzy operation of Yager sum was adopted. The reasoning is conducted on the rule-based reasoning that a rule-based DB system built with many rules derived from the existing diagnosis methods and the expertise in fire investigation. The cause diagnosis system proposes the causes obtained from the diagnosis process and showed possibility of electrical fire causes.

• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.11 no.1
• /
• pp.25-47
• /
• 2007

Background and Purpose: There was seldom study about method that diagnose 8 Constitution beside method of pulse diagnosis in 8 Constitution Medicine. Objectives: This study is to make out check list for 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning). Methods: Review of literatures about special quality element of 8 Constitution and supplement learning advice of 8 Constitution Medicine Experts constructed knowledge base. And then, knowledge base divided through AHP(Analytic Hierarchy Process), and made out check list with this. Results: Knowledge base based on special quality element of 8 Constitution was divided by 5 greate classification and 25 bisection kind, and check list consisted of 251 item was made out through this. Conclusion: Based on this research, cases necessary to make 8 Constitution Medicine Diagnosis Expert System can be gathered through check list, and further study for 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning) is needed to supplement this research.

• 유공압시스템학회:학술대회논문집
• /
• 2010.06a
• /
• pp.56-61
• /
• 2010

Simulator is a development equipment which enables the ECU to operate in normal mode by simulating the interface signal between ECU and mechanical system electrically. Embedded simulator means simulation function is embedded in ECU firmware, hence the electrical signal interface is replaced by the substitution of information at system program level. This paper explains the development of embedded transmission simulator for the verification of TCU firmware function which covers shifting control and on-board diagnosis. The embedded simulation program is executed in TCU processor along with the TCU firmware and it provides TCU firmware with not only the speed information those are appropriate both in driving and shifting conditions, but also the fault detection signals. Experimental results show that the validity of embedded simulator and its usefulness to the TCU firmware development and verification.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.60 no.2
• /
• pp.94-98
• /
• 2011

Electrolytic power capacitors today form essential components for virtually any power electronic system such as DC/DC converter or UPS. Frequently, electrolytic capacitors for DC link voltage smoothing are the key components which determine the life cycle of the whole unit and often are responsible for converter breakdown failures. In this paper, ethernet-based remote diagnosis system for DC voltage smoothing capacitor using DSP control board is developed. To estimate the status of the capacitor, the equivalent series resistor(ESR) of the component has to be determined. The ESR detection scheme is based on the determination of the capacitor ripple power losses calculated from DC link voltage/current measurement. Experimental results show the veridity and reliability of the proposed ethernet-based remote on-line capacitor diagnosis system.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.1
• /
• pp.33-37
• /
• 2002

Insulation aging diagnosis system provides early warning regarding electrical equipment defects. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear. it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a electromagnetic wave and acoustic signal to diagnose an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System and acquires 2D patterns from analyzing it. For filtering the noise contained in sensor signals we used ICA algorithms. Using this data, we design of the neuro-fuzzy model that diagnoses an electrical equipment and is investigated in this paper. Validity of the new method is asserted by numerical simulation.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.05a
• /
• pp.950-955
• /
• 2003

This paper introduces an enhanced condition monitoring and diagnosis system recently developed for rotating machinery. In the system, the data aquisition/monitoring signal processing, machine condition classifier, case-based reasoning and demonstration modules are effectively integrated with user-friendliness so that machine operators can easily monitor and diagnose the status of rotating machinery in operation. Some of the new features include the directional spectrum, case-based reasoning and neural network techniques. And the demonstrator modules for fault diagnosis of a Bear driving system and for basic understanding of the rotor dynamics are provided to help the potential users better understand the system.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.56 no.4
• /
• pp.168-172
• /
• 2007

The global environment deteriorating which originated from using of fossil fuel is an serious problem for human being to solve. The photovoltaic energy has been considered as a solution. In advanced countries, research and development for photovoltaic(PV) energy system is carrying on. Once installed, a PV array requires maintenance and fault diagnosis other than an occasional cleaning. In this research, the proposed system monitor and diagnosis the output of PV array by on-line for maintenance of PV power plant. The validity of proposed system is verified using sample system.

• 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.