• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2164.1_2165.1
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• 2009

In this study we suggest fire detection algorithm using fuzzy inference with input variables of temperature and smoke density to detect electrical fire of early stage. The algorithm consists of membership function of temperature and smoke density and fire probability. The antecedent part of the algorithm consists of temperature and smoke density, and the consequent part consists of fire possibility. The inference rules of the algorithm is estimated to input temperature and smoke density obtained by real fire. With the help of algorithms using fuzzy inference we may be diagnose electrical fire precisely.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.137-151
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• 1995

A difficult problem in operating Flexible Manufacturing Systems (FMS) is to control the system in real-time by coordinating heterogeneous machines and integrating distributed information. The objective of the paper is to present the models and methodologies useful to resolve the difficult problem. The detailed objectives can be described in three folds. First, a hierarchical Colored and Timed Petri-Net (CTPN) is designed to control an FMS in real-time. The concerned FMS consists of a loading station, several machining cells, a material handling system, and an unloading station. Timed-transitions are used to represent the timed-events such as AGV movements between stations and cells, part machining activities in the cells. Signal places are also used to represent communication status between the host and the cell controllers. To resolve the event conflicts and scheduling problems, dispatching rules are introduced and applied. Second, an implementation methodology used to monitor and diagnose the errors occurring on the machines during system operation is proposed. Third, a Petri-Net simulator is developed to experiment with the designed control logic.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.42-48
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• 2003

In general many engineers can diagnose the fault condition using the abnormal ones among data monitored from a diesel engine, but they don't need the system modelling or identification for the work. They check the abnormal data and the relationship and then catch the fault condition of the engine. This paper proposes the construction of a fault diagnosis engine through malfunction data gained from the data fault detection system of neural networks for diesel generator engine, and the rule inference method to induce the rule for fuzzy inference from the malfunction data of diesel engine like a site engineer with a fuzzy system. The proposed fault diagnosis system is constructed in the sense of the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HMH). The system is concerned with the rule reduction method of knowledge base for related data among the various interactive data.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.161-165
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• 2001

End milling is one of the most widely used machining operations. It is associated with productivity and production quality progress. In metal cutting with up and down milling, moment is important factor to diagnose the cutting characteristics because the amount of tool wear directly influences the moment. In this study, the effects of number of milling cutting edges on the cutting performance, especially on the moment, are investigated. The results acquired through the cutting test measuring moment show that up milling is superior to down milling.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.350-354
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• 1995

The Tension Leveller of Cold Rolling Mill In POSCO performs levelling the strip in high speed line. But minor variations in operating condition of driving machines such as motor, gear box, and support bearings, a small gap-variation of supporter and strip slip by poor roll revolutions can cause serious problems in the quality of strip. In this study, firstly, A condition monitoring standard for each sensor is made through with the detail analysis of vibration and strip slip. Secondly, An automatic monitoring and diagnosing system was developed to monitor the condition of Tension Leveller, and diagnose the cause of abnormal condition. Finally, A diagnosing algorithm for abnormal condition and man-machine interface (MMI) for easy operation are developed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.868-871
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• 1995

In order to remain competitive, a manufacturing company needs to maintain the optimal condition of its manufacturing system. Machine tools as an important element of a manufacturing system comprises complex mechanical as well as electronic components. Therefore, diagnosing the troubles of machine tools is a tricky process which requires a lot of experience and knowledge. Since providing machine tool users with necessary services at the right time is very difficult and expensive, a remote diagnosis system is to be regarded as a good alternative,with which users can diagnose and fix the machine troubles. This paper presents a framework for a remote machine tool diagnosis system using the world wide web technology and backward reasoning expert system.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.196-202
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• 1999

Recent trend changes a criterion for evaluation of burner that environmental problem is raised as global issue. For efficient driving problem, the higher thermal efficiency and the lower oxygen in exhaust gas, burner is evaluated the better. For environmental problem, burner must satisfy $NO_{X}$ limit and CO limit. Consequently, 'good burner' means on whose thermal efficiency is high under the constraint of $NO_{X}$ and CO consistency. To make existing burner satisfy recent criterion, it is highly recommended to develop feedback control scheme whose output is the consistency of $NO_{X}$ and CO. This paper describes development of real time flame diagnosis technique that evaluate and diagnose combustion state such as consistency of components in exhaust gas, stability of flame in quantitative sense. This study focuses on wave length of luminescence from chemical reaction measurement of the luminescence via optical measuring apparatus and derive correlation with consistency of components in exhaust gas by image processing technique.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.832-835
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• 2002

This paper presents a new approach integrated Case-Based Reasoning with Self. Organization Map(SOM) in diagnosis systems. The causes of faults are obtained by case-base trained from SOM. When the vibration problem of rotating machinery occurs, this provides an exact diagnosis method that shows the fault cause of vibration problem. In order to verify the performance of algorithm, we applied it to diagnose the fault cause of the electric motor.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.6
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• pp.558-563
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• 2010

In this paper, the novel approach for the fault diagnosis of the bearing equipped with rotational mechanical facilities was studied. As research works, by applying the ball bearing used extensively in many industrial fields, experiments were conducted in order to propose the new prognostic method about the condition monitoring for the rotational bodies based on the condition analysis of infrared thermography. Also, by using the vibration spectrum analysis, the real time monitoring was performed. As results, it was confirmed that infrared thermography method could be adapted into monitor and diagnose the fault for bearing by evaluating quantitatively and qualitatively the temperature characteristics according to the condition of the ball bearing.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.582-589
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• 1998

This paper presents the analysis results of ex-core and in-core neutron noise, acceleration signals and pressure fluctuation measured at Ulchin Nuclear Unit 1 & 2 to identify and monitor the reactor internals vibration including fuel motion. A phase separation algorithm developed by authors was applied to the neutron noises to clearly identify the reactor internals vibratory motion. The beam mode frequency of the core support barrel was identified to be 8Hz and the shell mode to be 20Hz. The first frequency of the fuel assembly was also found to be 3Hz, while first two acoustic frequencies of the primary coolant system were 6 and 17.5Hz. By monitoring and analyzing these frequencies periodically, it is possible to diagnose the operating condition of reactor internals and to provide an early detection of faults for the predictive maintenance.