• 한국정밀공학회지
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• 제15권2호
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• pp.35-44
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• 1998

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introduced Modular Artificial Neural Network(MANN) for this purpose. MANN 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 trained by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing MANN with multitasking and message transfer between processes in SUN workstation. We tested MANN in reactor system.

• 전기전자학회논문지
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• 제13권1호
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• pp.65-70
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• 2009

We propose an ultrashort pulse optical code-division multiple-access (O-CDMA) scheme based on a pseudorandom binary M-sequence spectral phase encoding and decoding of coherent mode-locked laser pulses and perform a numerical simulation to analyze its feasibility. We demonstrate the ability to properly decode any of the multiple (eight) 10 Gbit/s users by the matched code selection of the spectral phase decoder. The peak power signal to noise ratio of properly and improperly decoded $8{\times}10 Gb/s$ signals could be greater than 15 for 127 M-sequence coding.

• 동의생리병리학회지
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• 제23권4호
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.538-541
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• 2009

Increasing of number of people who suffered from long term chronic diseases which required frequent daily health monitoring and body check up in conjunction with the trendy uses of mobile phones and Personal Digital Assistants (PDAs) in various ubiquitous computing had make portable healthcare system a well known application today. A mobile phone based portable healthcare monitoring system with multiple vital signals monitoring ability at real time in WSN and CDMA network is developed. This system carries out real time monitoring and local data analysis process in the mobile phone. Any detection of abnormal health condition and diagnosis at earlier stage will reduce the risk of patient's life. As an extension to the existing model, a pre-diagnosis management system (PDMS) is designed to minimize the time consuming in pre-diagnosis process in the hospital or healthcare center. An alert is sent to the web server at the healthcare center when the patient detects his health is at critical state where the immediate diagnosis is needed. Preparation of diagnosis equipments and arrangement of doctor and nurses at the hospital side can be done earlier before the arrival of patient at the hospital with the help of PDMS. An efficient pre-diagnosis management increases the chances of diseases recovery rate as well.

• 제어로봇시스템학회논문지
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• 제7권6호
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• pp.494-501
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• 2001

In this paper an ANFIS(Adativo Neuro-Fuzzy Inference System)- based fault detection and diagnosis for a closed loop control system is proposed. The proposed diagnostic system contains two ANFIS. One is run as a parallel model within the model in closed loop control(MCL) and the other is run as a series-parallel model within the process in closed loop(PCL) for the generation of relevant symptoms for fault diagnosis. These symptoms are further processed by another classification logic with simple rules and neural network for process and controller fault diagnosis. Experimental results for a DC shunt motor control system illustrate the effectiveness of the proposed diagnostic scheme.

• 한국자동차공학회논문집
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• 제25권2호
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• pp.149-156
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• 2017

Various kinds of accessories(e.g., clock, radio, automatic door locks, alarm devices, etc.) or unit components (e.g., black box, navigation system, alarm, private audio, etc.) require dark current even when the vehicle power is turned off. However, accessories or unit components can be the causes of excessive dark current generation. It results in battery discharge and the vehicle's failure to start. Therefore, immediate detection of abnormal dark current and response are very important for a successful repair job. In this paper, we can increase the maintenance efficiency by presenting a standardized diagnostic process for the measurement of the dark current and the existing problem. As a result of the absence of a system to block the dark current in a vehicle, diagnosis and repair were performed immediately by using a standardized dark current diagnostic process.

• 대한한방부인과학회지
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• 제33권1호
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• pp.104-115
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• 2020

Objectives: The purpose of this study is to discuss the differential diagnosis of postpartum pain. Methods: In this study, postpartum pain cases reported in the Journal of Korean Medicine were investigated, and a case of postpartum patient who diagnosed syringomyelia was reported. Results: Patients with autoimmune diseases who complained of postpartum pain had a different course of treatment process and they had related family history. Patients with syringomyelia also differed from the usual treatment process. Conclusions: In patients with postpartum pain who differ from usual treatment process, differential diagnosis of autoimmune disease and syringomyelia is necessary.

• 한국치위생학회지
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• 제11권5호
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• pp.749-758
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• 2011

Objectives : The purpose of this study was to analyse case reports performed through a dental hygiene process and provide basic data on clinical education of dental hygiene. Methods : 154 case reports which collected for six years were analysed. This study applied dental hygiene process model in dental hygiene diagnosis. Dental hygiene diagnosis was more cleared by dental a hygiene process model. Data analysis was performed by the Frequency statistics using SPSS 12.0 for Windows. Results : 1. The clients are mainly comprised 20's university student(91.9%). 2. In assessment phase, clients finished 100% test of subjective data. 3. When applied a dental hygiene process model in dental hygiene diagnosis, students have identified 23 type of dental hygiene problem and analysed dental hygiene problem frequently used as bleeding of gingiva, calculus and deposit of dental plaque. 4. In case of plan of dental hygiene intervention, Fluoride application showed the most high level(98.1%) in clinical intervention. 5. Results of intervention showed that performance rate(98.7%) of scaling is the most high level. Conclusions : Dental hygiene process model is more useful than other diagnostic models in clinical practice based on dental hygiene process.

• 제어로봇시스템학회논문지
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• 제9권2호
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• pp.159-167
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• 2003

This study suggests the hybrid fault diagnosis method of signed digraph (SDG) and partial least squares (PLS). SDG offers a simple and graphical representation for the causal relationships between process variables. The proposed method is based on SDG to utilize the advantage that the model building needs less information than other methods and can be performed automatically. PLS model is built on local cause-effect relationships of each variable in SDG. In addition to the current values of cause variables, the past values of cause and effect variables are inputted to PLS model to represent the Process armies. The measured value and predicted one by dynamic PLS are compared to diagnose the fault. The diagnosis example of CSTR shows the proposed method improves diagnosis resolution and facilitates diagnosis of masked multiple-fault.

• 한국가스학회지
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• 제4권4호
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• pp.42-49
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• 2000

대부분의 화학공정은 매우 크고 복잡하기 때문에 전체 공정에 대한 진단시스템을 만드는 것은 매우 어렵다. 따라서, 대형공정을 몇 개의 부공정으로 분할하여 진단하는 체계적인 방법이 필요하다. 이 논문에서는 이상-결과 트리모델에 기반하여 정성적 이상진단을 위한 공정분할전략을 제안하였다. 분할기준으로 유연한 진단, 지식베이스의 크기축소, 및 복잡한 지식베이스의 일관된 구축을 사용하였다 부공정간의 인과관계를 연결하기 위해 통로변수를 도입한 다음 오프라인 분석을 통해 통로변수의 이상-결과 트리모델을 구축하였다 계분할이 없는 경우와 같은 진단결과를 얻을 수 있도록 온라인 진단전략을 수립하였다 제안된 방법의 유용성을 대형 보일러 공정에 대한 이상진단시스템을 통해 보였다.