• Title/Summary/Keyword: automatic diagnosis system

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Simulation for Defect Diagnosis in Belt Transport System (벨트 이송 시스템의 결함 진단을 위한 시뮬레이션)

  • Lee, Nam-Hoon;Lyu, Sang-Heon;Ihn, Yong-Seok;Choi, Yeon-Sun;Koo, J.C.
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.16 no.4 s.109
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    • pp.366-371
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    • 2006
  • As functional requirements of automatic office machines like printers, Automatic Tellex Machines(ATMs), copying machines are on a trend for the higher speed and precision, extensive technical advances are being developed and implemented in the industry. Media transport system is a device to convey a sheet of paper in ATMs and printers. The stability of media transport system is a matter of concern as their operating throughput rapidly increases. And defects of belts or rollers in a transport system directly affect the level of stability of the system. Therefore an automatic diagnostic system for predicting various defects is necessary for the stable operation of the media transport system. A simulation based on multi-body dynamics has been done for a feasibility study of a system design for the defect anticipation.

Machine Fault Diagnosis Method based on DWT Power Spectral Density using Multi Patten Recognition (다중 패턴 인식 기법을 이용한 DWT 전력 스펙트럼 밀도 기반 기계 고장 진단 기법)

  • Kang, Kyung-Won;Lee, Kyeong-Min;Vununu, Caleb;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.22 no.11
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    • pp.1233-1241
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    • 2019
  • The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.

A study on Radial pulse diagnosis of the korean medicine (한방 맥 진단에 관한 연구)

  • Lee, H.J.;Kim, J.W.;Huh, W.
    • Proceedings of the KOSOMBE Conference
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    • v.1992 no.05
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    • pp.71-74
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    • 1992
  • This paper describes research about the realization of computerized radial pulse diagnosis system in order to remove the subjectivity of a diagnostician, when diagnostician diagnoses a sickness using tactile percept ion in korean traditional medicine. Using radial pulse wave detection system, we effectively measured pressure radial pulse rave and after analyzing it, we detected the characteristic parameters and also quantified it and then we objectified more or less the judgement standard of radial pulse diagnosis by the aids of a clinical expert. on this base, we confirmed the possibility for realizing of automatic radial pulse diagnosis by radial pulse diagnosis system.

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Automatic Reading System for On-off Type DNA Chip

  • Ryu, Mun-Ho;Kim, Jong-Dae;Kim, Jong-Won
    • Journal of Information Processing Systems
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    • v.2 no.3 s.4
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    • pp.189-193
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    • 2006
  • In this study we propose an automatic reading system for diagnostic DNA chips. We define a general specification for an automatic reading system and propose a possible implementation method. The proposed system performs the whole reading process automatically without any user intervention, covering image acquisition, image analysis, and report generation. We applied the system for the automatic report generation of a commercialized DNA chip for cervical cancer detection. The fluorescence image of the hybridization result was acquired with a $GenePix^{TM}$ scanner using its library running in HTML pages. The processing of the acquired image and the report generation were executed by a component object module programmed with Microsoft Visual C++ 6.0. To generate the report document, we made an HWP 2002 document template with marker strings that were supposed to be searched and replaced with the corresponding information such as patient information and diagnosis results. The proposed system generates the report document by reading the template and changing the marker strings with the resultant contents. The system is expected to facilitate the usage of a diagnostic DNA chip for mass screening by the automation of a conventional manual reading process, shortening its processing time, and quantifying the reading criteria.

Studies of Automatic Dental Cavity Detection System as an Auxiliary Tool for Diagnosis of Dental Caries in Digital X-ray Image (디지털 X-선 영상을 통한 치아우식증 진단 보조 시스템으로써 치아 와동 자동 검출 프로그램 연구)

  • Huh, Jangyong;Nam, Haewon;Kim, Juhae;Park, Jiman;Shin, Sukyoung;Lee, Rena
    • Progress in Medical Physics
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    • v.26 no.1
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    • pp.52-58
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    • 2015
  • The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

Remote Diagnosis of Hypertension through HTML-based Backward Inference

  • Song, Yong-Uk;Chae, Young-Moon;Cho, Kyoung-Won;Ho, Seung-Hee
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.496-507
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    • 2001
  • An expert system for the diagnosis and indication of hypertension is implemented through HTML-based backward inference. HTML-based backward inference is performed using the hypertext function of HTML, and many HTML files, which are hyperlinked to each other based on the backward rules, should be prepared beforehand. The development and maintenance of the HTML files are conducted automatically using the decision graph. Still, the drawing and input of the decision graph is a time consuming and tedious job if it is done manually. So, automatic generator of the decision graph for the diagnosis and indication of hypertension was implemented. The HTML-based backward inference ensures accessibility, multimedia facilities, fast response, stability, easiness, and platform independency of the expert system. So, this research reveals that HTML-based inference approach can be used for many Web-based intelligent site with fast and stable performance.

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Fault Diagnosis Method for Automatic Machine Using Artificial Neutral Network Based on DWT Power Spectral Density (인공신경망을 이용한 DWT 전력스펙트럼 밀도 기반 자동화 기계 고장 진단 기법)

  • Kang, Kyung-Won
    • Journal of the Institute of Convergence Signal Processing
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    • v.20 no.2
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    • pp.78-83
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    • 2019
  • Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.

Study on Trouble Diagnosis of Stacker Crane by Case Base Inference (사례추론에 의한 S/C 이상진단에 관한 연구)

  • Kim, Dong-Hun;Song, Jun-Yeop
    • 연구논문집
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    • s.25
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    • pp.99-104
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    • 1995
  • At present, a lot of researches on AS/RS(Automatic Storage and Retrival System) are being performed and also applied to realization of FA, FMS and CIM. Especially facility management and diagnosis of stacker crane that is major equipment of AS/RS, is recognized more importantly. In this paper, Case Base is designed for manager that is non-expert and it is implemented according to possible trouble case for the purpose of trouble diagnosis and maintenance of stacker crane.

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A Study on the Development of a Web Based Knowledge-Based Diagnosis System through a Combination of SIS and MMIS (안전정보와 보전관리정보를 연계한 Web 기반 지식베이스 진단시스템 구현)

  • 박주식;이선태;박상민;남호기
    • Journal of the Korea Safety Management & Science
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    • v.2 no.4
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    • pp.59-70
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    • 2000
  • To keep enterprise's competitiveness on condition of the automatic manufacturing system such as FA, FMS and CIM, all the maintenance problems should be considered seriously in not only production and maintenance but also related industrial safety. As we analyze in the surveys for the maintenance management of domestic enterprises and the causes of Industrial accident, there will be necessity of drawing up countermeasures for prevention of industrial accidents and for ensuring expertise maintenance technologies. Based on these analyses, this study studied the safety information system, maintenance management information system, and the machinery condition diagnosis technique by using of the knowledge-based system under the internet environment. This web based knowledge-based diagnosis system can easily provide not only the knowledge of expert about deterioration phenomenon of industrial robot, but also the knowledge of relating safety and facility on everywhere, everytime. Therefore, when we use this system, it is expected to improve the efficiency of business processes in the production and safety.

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A Study on the Development of a Web Based Knowledge-Based Diagnosis System for Production and Safety Efficiency (생산과 안전의 효율화를 위한 Web 기반 지식베이스 진단시스템 구현)

  • 이선태;박상민;남호기
    • Proceedings of the Safety Management and Science Conference
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    • 2000.11a
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    • pp.269-279
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    • 2000
  • To keep enterprise's competitiveness on condition of the automatic manufacturing system such as FA, FMS and CIM, all the maintenance problems should be considered seriously in not only production and maintenance but also related Industrial safety. As we analyze in the surveys for the maintenance management of domestic enterprises and the causes of industrial accident, there will be necessity of drawing up countermeasures for prevention of industrial accidents and for ensuring expertise maintenance technologies. Based on these analyses, this study studied the safety information system, maintenance management information system, and the machinery condition diagnosis technique by using of the knowledge-based system under the internet environment. This web based knowledge-based diagnosis system can easily provide not only the knowledge of expert about deterioration phenomenon of industrial robot, but also the knowledge of relating safety and facility on everywhere, everytime. Therefore, when we use this system, it is expected to improve the efficiency of business processes in the production and safety.

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