• Journal of Advanced Marine Engineering and Technology
• /
• v.30 no.2
• /
• pp.247-252
• /
• 2006

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn until signal is growing to abnormal state that the signal is over or under the set point. therefore cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without any additional sensors. By analyzing the data with high correlation coefficient(CC), correlation level of interactive data can be defined. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC. FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

• Journal of Advanced Marine Engineering and Technology
• /
• v.30 no.2
• /
• pp.253-259
• /
• 2006

There is few study which automatically diagnoses the fault from ship's monitored data. The bigger control and monitoring system is. the more important fault diagnosis and maintenance is to reduce damage caused by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault from monitored data and is composed of fault detection knowledge base and fault diagnosis knowledge base. For all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem, To verify capability of fault detection, diagnosis and prediction, FMS(Fault Management System) is developed by C++. Simulation by FMS is carried out with population data set made by the log book data of 2 months duration from a large full container ship of H shipping company.

• Journal of the Korean Society for Precision Engineering
• /
• v.9 no.3
• /
• pp.53-60
• /
• 1992

This paper deals with developing an Expert system for tool selection using knowledge base system approach, and its application. For the sake of building of knowledge base, the information from process through sensor, tool handbook and interview with expert are referrenced and managed. The system developed shows good application flexibility in providing the actual cutting process with the selection of tool(insert, holder) and cutting conditions(feed, speed, rake type, and so on), is found as a useful system for real-time machining process. The Expert system for tool selection is written in TURBO PROLOG ver. 2.0 for inference engine capability, and can be run in interactive mode for user friendliness. In order to apply the system developed in actual cutting process, more parameters should be considered and scrutinized, and the system should be further extended in modular basis.

• Korean Journal of Computational Design and Engineering
• /
• v.5 no.4
• /
• pp.319-326
• /
• 2000

Expert systems using uncertain and ambiguous knowledge are not of the recent interests about uncertainty problem for performing inference similar to the decision making of a human expert. Human factors on rule-based systems often involve uncertain information. Expert systems had been used the methods of conflict resolution in a rule conflict situation, but this methods not properly solved the rule conflict. If a human expert appends a new rule to an original rule base, the rule base rightly causes a rule conflict. In this paper, the problem of rule conflict is regarded as one in which uncertainty of information is fundamentally involved. In the reduction of problem with uncertainty, we propose an enhanced rule ordering method, which improve the rule ordering method using Dempster-Shafer theory. We also propose a combinative index, which involve human factors of experts decision making.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.12
• /
• pp.35-48
• /
• 2017

Extracting temporal information from documents is becoming more important, because it can be used to various applications such as Question-Answering (QA) systems, Recommendation systems, or Information Retrieval (IR) systems. Most previous studies only focus on English documents, and they are not applicable to the other languages due to the inherent characteristics of languages. In this paper, we propose a new system, named ExoTime, designed to extract temporal information from Korean documents. The ExoTime adopts an external Knowledge Base (KB) in order to achieve better prediction performance, and it also applies a bagging method to the temporal relation prediction. We show that the effectiveness of the proposed approaches by empirical results using Korean TimeBank. The ExoTime system works as a part of ExoBrain that is an artificial intelligent QA system.

• Proceedings of the KSME Conference
• /
• 2001.06a
• /
• pp.114-119
• /
• 2001

An expert system for estimation of fatigue properties from simple tensile data of material is developed, considering nearly all important estimation methods proposed so far, i.e., 7 estimation methods. The expert system is developed to utilize for the case of only hardness data available. The knowledge base is constructed with production rules and frames using an expert system shell, UNIK. Forward chaining is employed as a reasoning method. The expert system has three major functions including the function to update the knowledge base. The performance of the expert system is tested using the 54 $\varepsilon$-N curves consisting of 381 $\varepsilon$-N data points obtained for 22 materials. It is found that the expert system developed has excellent performance especially for steel materials, and reasonably good for aluminum alloys.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2005.06a
• /
• pp.281-286
• /
• 2005

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn while signal is growing to abnormal state until the signal is over or under the set point and cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without additional sensors. By analyzing this data having high correlation coefficient(CC), correlation level of interactive data can be understood. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC, FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2005.06a
• /
• pp.251-256
• /
• 2005

There is few study which automatically diagnose the fault from ship's monitored signal. The bigger control and monitoring system is, the more important fault diagnosis and maintenance is to reduce damage brought forth by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault and is composed to fault detection knowledge base and fault diagnosis knowledge base. For this all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem by analyzing ship's operation data. To verifying capability of fault detection, diagnosis and prediction, Fault Management System(FMS) is developed by C++. Simulation experiment by FMS is carried out with population data set made by log book data of 2 months duration from a large full container ship of H shipping company.

• Journal of the military operations research society of Korea
• /
• v.24 no.1
• /
• pp.88-97
• /
• 1998

It is critical to determine the appropriate actions for safe landing of an aircraft in an emergency situation. An expert system can be very useful for this purpose. An expert system specifically for jet fighter $F-\bigcirc\bigcirc$ has been developed. Its knowledge base contains the standard procedures provided by various flight manuals and the expertise of human specialists such as pilots and emergency management personnels. Advising procedures are represented by an IF-THEN format in the developed rule-based expert system. Advises are provided in real time during the entire flight processes of ground, takeoff, inflight, and landing. The developed system would significantly increase the survivability of pilots and aircraft, while decreasing operational costs of emergency management personnels. By modifying the knowledge base, the developed system can also be applied to other types of aircrafts including civilian airlines.

• Journal of the Korean Society for information Management
• /
• v.17 no.4
• /
• pp.47-65
• /
• 2000

This study aims lo enhance the perfor~nance 01 concept-based information retr~eval through the use of the lraditional thesaurus which, clearly delmes relalions among terms. To achwe lhls, thc study purports to construcl relation-value-based, relalion-bad, and inlegated kumwledge bases tluough the use ol ihc lhcsau~ub. To cornpale and a~alyze retrieval perlor~nance among knowledge bases, two methods weue al~plied. Sequential bnb algorithm is ap~lied to the I-clation-ualue-based and intzgralcd knowledge base while heuristic bnb algorithm is applied to the relal~on-based knowlcdgc base.