• Journal of the Korea Society for Simulation
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• v.7 no.2
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• pp.137-152
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• 1998

One of the components that constitute the simulation models is the state variables whose values are determined by the time related simulation process. Embedding rule-based expert systems into the simulation models should provide a systematic way of handling these time-dependent variables without distracting the essential problem solving capabilities of the expert systems which are well suited for expressing the decision making function of complex cases. The expert system, however, is inefficient in dealing with the time elapsing characteristics of target system compare to the simulation models. To solve the problem, this paper provides an interruptible inference engine whose inferencing process can be interrupted when the variables' value, which are used as the parameters of the rules, are not yet determined due to the time dependent nature of the state variables. The process is resumed when the variables are ready. The elapse of time is calculated by time-advance function of the simulation model to which the expert system has been embedded. The example modeling shown exploits the embedded interruptible inferencing capability for the controlling and monitoring of metal grating process.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.444-451
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• 1999

A diagnostic rule-base design method for enhancing fault detection and isolation performance of multiple obsever based fault detection isolation schemes (FIDS) is presented. The diagnostic rule-base has a hierarchical framework to perform detection and isolation of faults of interest, and diagnosis of process faults. The decision unit comprises a rule base and a fuzzy inference engine and removes some difficulties of conventional decision unit which includes crisp logic with threshold values. Emphasis is placed on the design and evaluation methods of the diagnostic rult-base. The suggested scheme is applied to the FDIS design for a DC motor driven centrifugal pump system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.2
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• pp.19-28
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• 2019

The purpose of this study is to examine the trends on machine learning and deep learning research in the published journals from the Web of Science Database. To achieve the study purpose, we used the abstracts of 20,664 articles published between 1990 and 2017, which include the word 'machine learning', 'deep learning', and 'artificial neural network' in their titles. Twenty major research topics were identified from topic modeling analysis and they were inclusive of classification accuracy, machine learning, optimization problem, time series model, temperature flow, engine variable, neuron layer, spectrum sample, image feature, strength property, extreme machine learning, control system, energy power, cancer patient, descriptor compound, fault diagnosis, soil map, concentration removal, protein gene, and job problem. The analysis of the time-series linear regression showed that all identified topics in machine learning research were 'hot' ones.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.29-34
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• 2012

Nowadays, the problem of ETCS terminal in becoming popular gradually is that there is no services except for ETC. Therefore, we need new system that provide many type of additional services at one-terminal. In this paper, we study the additory function of ETCS terminal to afford many type of the vehicle administration beside collection and provider of traffic information. We descrived the method of Eco-driving function beside to save fuel signing instant and mean fuel-efficiency, measurement of section fuel-efficiency on OLED and then brings out the best driving habit in people and to prevent dangerous at the wheel as diagnosing engine oil, cooling water, fan belt, the point of changing consumables, diagnoses to an overheated engine, charges on generator through ECU. The multi-services terminal consist of the vehicle diagnosis module base on OBD-II and ETCS terminal.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.6
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• pp.797-804
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• 2013

In this study, the authors develop a methodology for a diagnostic system with a vibration parameter that is influenced by environmental factors. The data tends to have a varying average over time. Often, these features are found in statistical data retrieved from a production line. If we utilize existing statistical techniques for these features, we could derive an incorrect diagnostic conclusion based on the different average values. To overcome the limitations of previous methods, the authors apply a function analyzed through regression analysis to predict the mean value and corresponding upper and lower limits at each stage. This technique also provides corresponding statistical parameters in varying dynamic means. To validate the proposed methods, we retrieve data from the engine assembly line of H Motors and verify the results.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.5
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• pp.163-170
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• 2005

Urban transit is a complex system that is combined electrically and mechanically, it is necessary to construct maintenance system for securing safety accompanying high-speed driving and maintaining promptly. Expert system is a computer program which uses numerical or non-numerical domain-specific knowledge to solve problems. In this research, we intend to develop the expert system which diagnose failure causes quickly and display measures. For the development of expert system, standardization of failure code classification system and creation of BOM(Bill Of Materials) have been first performed. Through the analysis of failure history and maintenance manuals, knowledge base has been constructed. Also, for retrieving the procedure of failure diagnosis and repair linking with the knowledge base, we have built RBR(Rule Based Reasoning) engine by pattern matching technique and CBR(Case Based Reasoning) engine by similarity search method. This system has been developed based on web to maximize the accessibility.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.5899-5905
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• 2014

Faults in electric power system can be a critical problem for vehicles. The system durability is determined mainly by the durability of their components and operating conditions. Monitoring the conditions of the electric power system may be necessary because it is very difficult to predict precisely when it will fail. Therefore, the aim of this study was to develop a diagnosis system for an electric power system of a vehicle. The alternator voltage, excitation voltage, lamp voltage, battery voltage, and engine rpm from a crank angle sensor are monitored continuously and the system fault can be then detected in real time. NI USB- 9201 DAQ and LabVIEW SW have been used to measure the voltages and analyze the data. Compared to conventional measurements for only each component, an integrated and portable measurement method was developed. In addition to the monitoring the electric power system in real time, the saved data from the measurement also provides valuable information to improve the durability of the components.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.4
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• pp.200-206
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• 2022

This study is to develop database by an experimental method for the development of condition based maintenance for auxiliary equipment in marine engine systems. Existing ships have been performing regular maintenance, so the actual measurement data development is very incomplete. Therefore, it is best to develop a database on land tests. In this paper, a database developed by an experimental method is presented. First, failure case analysis and reliability analysis were performed to select a failure mode. For the failure simulation test, a test bed for land testing was developed. The failure simulation test was performed based on the failure simulation scenario in which the failure simulation test plan was defined. A 1.5TB failure simulation database has been developed, and it is expected to serve as a basis for ship failure diagnosis and prediction algorithm model development.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.223-229
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• 2018

Recently, the necessity of safety diagnosis of electrical devices has been increasing as the fire caused by electric devices has increased rapidly. This study is concerned with the safety diagnosis of electric equipment using intelligent Fuzzy technology. It is used as a diagnostic input for the multiple electrical safety factors such as the use current, cumulative use time, deterioration and arc characteristics inherent to the equipment. In order to extract these information in real time, a device composed of various sensor circuits, DSP signal processing, and communication circuit is implemented. The fuzzy logic algorithm using the Gaussian function for each information is designed and compiled to be implemented on a small DSP board. The fuzzy logic receives the four diagnostic information, deduces it by the fuzzy engine, and outputs the overall safety status of the device as a 100-step analog fuzzy value familiar to human sensibility. By experiments of a device that combines hardware and fuzzy algorithm implemented in this study, it is verified that it can be implemented in a small DSP board with human-friendly fuzzy value, diagnosing real-time safety conditions during operation of electric equipment. In the future, we expect to be able to study more intelligent diagnostic systems based on artificial intelligent with AI dedicated Micom.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.497-504
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• 2018

This paper studies about the Oriental Medical Expert System, based on Open Source Drools for rule engine processing, which contains scalability, availability, and modifiability. The system is developed with the Spring MVC framework and Ajax for stable services of the Web-based Medical Expert System. The diagnosis and treatment process of this Medical Expert system provides a service that provides the general users to accesses the web with a series of questionnaires. In order to compensate for the asynchronous communication between clients and services, and also for the complicated JDBC weaknesses, we applied the data handling in JSON to reduce the servers' loads, and also the Mybatis framework to improve the performance of the RDBMS, respectively. In addition, as the number of users increases to cope with the maximum available services of the web-based system, the load balancing structure using Nginx has been developed to solve the server traffic problems and the service availability has been increased. The experimental results show the stable services by approving the scalability test.