• Journal of Advanced Marine Engineering and Technology
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• 제18권3호
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• pp.85-93
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• 1994

A new diagnosis method is developed in this paper, in which the fuzzy set theory is introduced to diagnose the defects of rolling element bearings. The selection of membership function and the fuzzy operation model are discussed in detail here. The system is successfully used for various defects diagnosis of rolling element bearings.

• 산업경영시스템학회지
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• 제23권54호
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• pp.155-165
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• 2000

The fault diagnosis is a systematic and unified method to find based on the observing data resulting in noises. This paper presents the fault prediction and diagnosis using fuzzy expert system technique to manipulate the uncertainties efficiently in predictive perspective. We apply a fuzzy event tree analysis to the computer system, and build up the fault prediction and diagnosis using fuzzy expert system that predicts and diagnoses the error of the system in the advance of error.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 춘계학술대회 논문집
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• pp.457-462
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• 1995

This paper describes diagnosis strategy of the Flexible Multiple Fault Diagnosis Module for forecasting faults in system and deciding current machine state form sensor information. Most studydeal with diagnosis control stategy about single fault in a system, this studies deal with multiple fault diagnosis. This strategy is consist of diagnosis control module such as backward tracking expert system shell, various neural network, numerical model to predict machine state and communication module for information exchange and cooperate between each model. This models are used to describe structure, function and behavior of subsystem, complex component and total system. Hierarchical structure is very efficient to represent structural, functional and behavioral knowledge. FT(Fault Tree). ST(Symptom Tree), FCD(Fault Consequence Diagrapy), SGM(State Graph Model) and FFM(Functional Flow Model) are used to represent hierachical structure. In this study, IA(Intelligent Agent) concept is introduced to match FT component and event symbol in diagnosed system and to transfer message between each event process. Proposed diagnosis control module is made of IPC(Inter Process Communication) method under UNIX operating system.

• 한국의사학회지
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• 제25권2호
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• pp.105-112
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• 2012

The purpose of this paper is to suggest diagnosis support system for diseases of mind so that users can make effective decisions without professional knowledge by developing efficient knowledge system and utilizing ontology with which questions and logic inference are possible to diagnose diseases of mind. Furthermore, this diagnosis support system could be applied to supplement previous diagnosis method which depends on experiences by activating the diagnose of mind diseases thru ontology and determining state of mind effectively without technical knowledge. As a result of this experiment, diagnosis support system for diseases of mind was found to be accordance with the result of consulting instructions and show additional relevance thru utility extension.

• Journal of Gastric Cancer
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• 제23권4호
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• pp.549-560
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• 2023

Purpose: According to the American Joint Committee on Cancer cancer staging system, positive peritoneal washing cytology (PWC) indicates stage IV gastric cancer. However, rapid intraoperative diagnosis of PWC has no established reliable method. This study evaluated and compared the diagnostic accuracy of the Shorr and the modified ultrafast Papanicolaou (MUFP) methods for intraoperative PWC. Materials and Methods: This study included patients with gastric cancer who were clinically diagnosed with stage cT3 or higher. The Shorr and MUFP methods were performed on all PWC specimens, and the results were compared with those of conventional Papanicolaou (PAP) staining with carcinoembryonic antigen immunohistochemistry. Sensitivity, specificity, and partial likelihood tests were used to compare the 2 methods. Results: Forty patients underwent intraoperative PWC between November 2019 and August 2021. The average time between specimen reception and slide preparation using Shorr and MUFP methods was 44.4±4.5 minutes, and the average time between specimen reception and pathologic diagnosis was 53.9±8.9 minutes. Eight patients (20.0%) had positive cytology in PAP staining. The Shorr method had a sensitivity of 75.0% and specificity of 93.8%; the MUFP method had 62.5% sensitivity and 100.0% specificity. The area under the curve was 0.844 for Shorr and 0.813 for MUFP. In comparing the C-indices of each method with overall survival, no difference was found among the Shorr, MUFP, and conventional PAP methods. Conclusions: The Shorr and MUFP methods are acceptable for the intraoperative diagnosis of PWC in advanced gastric cancer.

• Journal of Power Electronics
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• 제9권3호
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• pp.377-385
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• 2009

In this paper, a diagnosis method for switch open-circuit faults in three-phase PWM inverters is proposed, which employs support vector machine (SVM) as classifying method. At first, a discrete wavelet transform (DWT) is used to detect a discontinuity of currents due to the fault, and then the features for fault diagnosis are extracted. Next, these features are employed as inputs for the SVM training. After training, the SVM produces an optimized boundary which is used identifying the fault. Finally, the fault classification is performed online with instantaneous features. The experimental results have verified the validity of the proposed estimation algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.125-127
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• 2000

Multiple faults are hard to diagnose correctly because the operation of circuit breakers tripped by former fault changes the topology of power systems. The information including operating time of actuated relays and tripped circuit breakers is used for considering changes of the network topology in fault section diagnosis. This paper presents a method for fault section diagnosis using a set of matrices which represent changes of the network topology due to operation of circuit breakers. The proposed method uses fuzzy relation to cope with the unavoidable uncertainties imposed on fault section diagnosis of power systems. The inference executed by the proposed matrices provides the fault section candidates in the form of a matrix made up of the degree of membership. Experimental studies for real power systems reveal usefulness of the proposed technique to diagnose multiple faults.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권1호
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• pp.33-37
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• 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.

• 대한기계학회논문집A
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• 제20권5호
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• pp.1411-1418
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• 1996

Large scale plants are equipped with a number of the rotating machineries which ocuupy important positions in the plant system. Therefore, the most important one is a vibraiton diagnostic thchnology which can detect quickly any abnormal symptom of operating malfunction and guve operational and inspection guides adequately. A new diagnosis method is developed in this paper, in which the fuzzy set theory is introduced to diagnose the defects of ratating machinery. The selection of memgership function and the fuzzy operation model are discussed in datail here. The systme is sucessfully used for various defacts diagnosis of rotating machinery. The result indicate that realixtic application can be builtusing this approach.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.790-795
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• 1994

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item, component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introducd to Hierarchical Artificial Neural Network(HANN) for this purpose. HANN consists of four level neural network, first level for symptom classification, second level for item fault diagnosis, third level for component symptom classification,forth level for component fault diagnosis. Each network is multi layer perceptron with 7 inputs, 30 hidden node and 7 outputs trainined by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing HANN with multitasking and message transfer between processes in SUN workstation. We tested HANN in reactor system.