• 제목/요약/키워드: Diagnosis of performance

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A Study on the Diagnosis of Thermal Performance in the Steam Turbine for Generation (발전용 증기터빈 열성능 진단에 관한 연구)

  • Kim, Kwang-Hong;Hong, Eun-Kee;Hwang, Kwang-Won;Jang, Chul-Ho;Kim, Si-Moon
    • Proceedings of the KSME Conference
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    • 대한기계학회 2007년도 춘계학술대회B
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    • pp.3236-3240
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    • 2007
  • This paper describes the results of steam turbine performance tests. The objectives of performance test is to exactly evaluate the degradation(decrease in performance) of the coal-fired steam turbine generator in order to provide plant information to help performance engineers identify problems, improve performance, and make economic decisions about scheduling maintenance and optimizing operation. To achieve these goals, the periodic thermal performance tests have been carried out since the initial operation period, 1997. We made the calculation program and guidelines for the tests and developed the performance index of the turbine cycle on the basis of the ASME PTC. By comparing the performance changes throughout the whole operation period, we confirmed the performance reliabilities of the turbine and its conditions.

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A Study on Remote ECG Diagnostic System Using Telephone Line (공중회선망을 이용한 원격 심전도 진단 시스템)

  • Lee, M.H.;Park, S.H.;Kim, Y.M.;Shin, K.S.;Jeong, H.K.;Jeong, K.S.
    • Journal of Biomedical Engineering Research
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    • 제13권1호
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    • pp.69-78
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    • 1992
  • This Paper describes implementation of a remote ECG diagnostic system using telephone line. The overall system includes ECG data acquisition system, ECG terminal, system control software, automatic diagnosis system, and transmission system.'The proposed system provides various functions, which are ECG data acquisition, transmission, receiving, diagnosis and dialogue between patients and medical doctors. Thls system is very simple and convienient to use. We evaluate the performance of modem and the accuracy of automatic diagnosis algorithm. The obtained results suggest the Possibilities of a remote ECG diagnostic system using the only existed telephone line.

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A Study on Diagnosis and Prognosis for Machining Center Main Spindle Unit (머시닝센터 주축 고장예측에 관한 연구)

  • Lee, Tae-Hong
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • 제15권4호
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    • pp.134-140
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    • 2016
  • Main Spindle System has effect on performance of machine tools and working quality as well as is required of high reliability. Especially, it takes great importance in producing automobiles which includes a large number of working processes. However, main spindle unit in Machine tools are often cases where damage occurs do not meet the design life due to driving in harsh environments. This is when excessive maintenance and repair of machine tools or for damage stability has resulted in huge economic losses. Therefore, this studying propose a method of accelerated life test for diagnosing and prognosis the state of life assessment main spindle system. Time status monitoring of diagnostic data - through the analysis of the frequency band signals were carried out inside the main spindle bearing condition monitoring and fault diagnosis.

Sensorless Diagnosis Method and Characteristic Analysis of Short-Circuited Turn for Generator Rotor (발전기 회전자의 층간단락 센서리스 진단기법 및 특성 해석)

  • Kim Sun-Ja;Jeon Yoon-Seok;Lee Seung-Hak;Choe Gyu-Ha
    • Proceedings of the KIPE Conference
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    • 전력전자학회 2003년도 추계학술대회 논문집
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    • pp.210-213
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    • 2003
  • Short-circuited can have significant effects on a generator and its performance. One of effective method detecting inter-turn short circuits on round rotor winding is a method using sensor detecting. But the method needs duplicate design of sensor for characteristic change according to types and forms of generator. Thus rotor shorted-turn diagnosis method without sensor is needed for detecting short turn when generator is driven. Diagnosis method without sensor depend on change of electric property in generator For the reason, this paper presents characteristic analysis of shorted-turns in generator by detecting the output voltage of generator.

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Intelligent Software System for the Advanced Control Room of a Nuclear Power Plant

  • Chang, Soon-Heung;Park, Seong-Soo;Park, Jin-Kyun;Gyunyoung Heo;Kim, Han-Gon
    • Proceedings of the Korean Nuclear Society Conference
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    • 한국원자력학회 1997년도 추계학술발표회논문집(1)
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    • pp.443-448
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    • 1997
  • The intelligent software system for nuclear power plants (NPPs) has been conceptually designed in this study. Its design goals are to operate NPPs in n improved manner and to support operators' cognitive tasks. It consists of six major modules such as "Information Processing," "Alarm Processing," "Procedure Tracking," "Performance Diagnosis," and "Event Diagnosis" modules for operators and "Malfunction Diagnosis" module for maintenance personnel. Most of the modules have been developed for several years and the others are under development. After the completion of development, they will be combined into one system that would be main parts of advanced control rooms in NPPs. that would be main parts of advanced control rooms in NPPs.

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FPGA-based ARX-Laguerre PIO fault diagnosis in robot manipulator

  • Piltan, Farzin;Kim, Jong-Myon
    • Advances in robotics research
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    • 제2권1호
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    • pp.99-112
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    • 2018
  • The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.

Comparative Analysis of Diagnostic Prediction Algorithm Performance for Blood Cancer Factor Validation and Classification (혈액암 인자 유효성 검증과 분류를 위한 진단 예측 알고리즘 성능 비교 분석)

  • Jeong, Jae-Seung;Ju, Hyunsu;Cho, Chi-Hyun
    • Journal of Korea Multimedia Society
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    • 제25권10호
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    • pp.1512-1523
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    • 2022
  • Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach.

PCA Based Fault Diagnosis for the Actuator Process

  • Lee, Chang Jun
    • International Journal of Safety
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    • 제11권2호
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    • pp.22-25
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    • 2012
  • This paper deals with the problem of fault diagnosis for identifying a single fault when the number of assumed faults is larger than that of predictive variables. Principal component analysis (PCA) is employed to isolate and identify a single fault. PCA is a method to extract important information as reducing the number of large dimension in a process. The patterns of all assumed faults can be recognized by PCA and these can be employed whether a new fault is one of predefined faults or not. Through PCA, empirical models for analyzing patterns can be trained. When a single fault occurs, the pattern generated by PCA can be obtained and this is used to identify a fault. The performance of the proposed approach is illustrated in the actuator benchmark problem.

A Fault Diagnosis Methodology for Module Process of TFT-LCD Manufacture Using Support Vector Machines (SVM을 이용한 TFT-LCD 모듈공정의 불량 진단 방안)

  • Shin, Hyun-Joon
    • Journal of the Semiconductor & Display Technology
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    • 제9권4호
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    • pp.93-97
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    • 2010
  • Fast incipient fault diagnosis is becoming one of the key requirements for economical and optimal process operation management in high-tech industries. Artificial neural networks have been used to detect faults for a number of years and shown to be highly successful in this application area. This paper presents a novel test technique for fault detection and classification for module process of TFT-LCD manufacture using support vector machines (SVMs). In order to evaluate SVMs, this paper examines the performance of the proposed method by comparing it with that of multilayer perception, one of the artificial neural network techniques, based on real benchmarking data.

Fault Detection and Diagnosis of the Deaerator System in Nuclear Power Plants (원전 탈기기 시스템의 수위 측정 센서의 고장 검출 및 진단)

  • Kim, Bong-Seok;Lee, In-Soo;Lee, Yoon-Joon;Kim, Kyung-Youn
    • Journal of IKEEE
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    • 제7권1호
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    • pp.107-118
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    • 2003
  • In this paper, dynamic control model is formulated by considering the geometrical structure of the deaerator storage tank in nuclear power plant and input-output flow rate at steady state, and we describe fault detection and diagnosis (FDD) scheme based on the adaptive estimator. The performance and effectiveness of the proposed FDD scheme are evaluated by applying real operating data obtained from the YOUNGKWANG 3 & 4 FSAR.

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