• Title/Summary/Keyword: process fault

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Development of Dual System Technology for PC based control system at the steel plant

  • Park, Yeong-Bok
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.179.3-179
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    • 2001
  • This paper describes the dual system technology of PC based control system at steel plant. Because PC is developed to be used in wide area such as Office Automation, Personal, It is cheaper and more portable than the present process control system, but is less stable and less reliable. In this research, We gathered the fault example of a general process control system and steel process control system, analyzed the cause of fault and decided the target fault that took over in our proposed system. The proposed PC based system is the dual system that has a shared RAID system connected by SCSI bus between two systems. In order to assist system reliability, we proposed watchdog manager to monitor ...

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Fault Detection of the Machine Tool Gearbox using Acoustic Emission Methodof (음향 방출법에 의한 공작기계 기어상자의 결함 검출)

  • Kim, Jong-Hyeon;Kim, Won-Il
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.11 no.4
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    • pp.154-159
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    • 2012
  • Condition monitoring(CM) is a method based on Non-destructive test(NDT). Therefore, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days also. Because its sensitivity is higher than normal accelerometers and it can detect low energy vibration signals. A machine tool consist of many parts such as the bearings, gears, process tools, shaft, hydro-system, and so on. Condition of Every part is connected with product quality finally. To increase the quality of products, condition monitoring of the components of machine tool is done completely. Therefore, in this paper, acoustic emission method is used to detect a machine fault seeded in a gearbox. The AE signals is saved, and power spectrums and feature values, peak value, mean value, RMS, skewness, kurtosis and shape factor, were determined through Matlab.

A Method of Fault Diagnosis for Engine Synchronization Using Analytical Redundancy (해석적 중복을 이용한 내연 기관 엔진의 동기화 처리 이상 진단)

  • 김용민;서진호;박재홍;윤형진
    • Transactions of the Korean Society of Automotive Engineers
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    • v.11 no.2
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    • pp.89-95
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    • 2003
  • We consider a problem of application of analytical redundancy to engine synchronization process of spark ignition engines, which is critical to timing for every ECU process including ignition and injection. The engine synchronization process we consider here is performed using the pulse signal obtained by the revolution of crankshaft trigger wheel (CTW) coupled to crank shaft. We propose a discrete-time linear model for the signal, for which we construct FDI (Fault Detection & Isolation) system consisting residual generator and threshold based on linear observer.

Generalization of the Testing-Domain Dependent NHPP SRGM and Its Application

  • Park, J.Y.;Hwang, Y.S.;Fujiwara, T.
    • International Journal of Reliability and Applications
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    • v.8 no.1
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    • pp.53-66
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    • 2007
  • This paper proposes a new non-homogeneous Poisson process software reliability growth model based on the coverage information. The new model incorporates the coverage information in the fault detection process by assuming that only the faults in the covered constructs are detectable. Since the coverage growth behavior depends on the testing strategy, the fault detection process is first modeled for the general testing strategy and then realized for the uniform testing. Finally the model for the uniform testing is empirically evaluated by applying it to real data sets.

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Performance Comparison of GPS Fault Detection and Isolation via Pseudorange Prediction Model based Test Statistics

  • Yoo, Jang-Sik;Ahn, Jong-Sun;Lee, Young-Jae;Sung, Sang-Kyung
    • Journal of Electrical Engineering and Technology
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    • v.7 no.5
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    • pp.797-806
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    • 2012
  • Fault detection and isolation (FDI) algorithms provide fault monitoring methods in GPS measurement to isolate abnormal signals from the GPS satellites or the acquired signal in receiver. In order to monitor the occurred faults, FDI generates test statistics and decides the case that is beyond a designed threshold as a fault. For such problem of fault detection and isolation, this paper presents and evaluates position domain integrity monitoring methods by formulating various pseudorange prediction methods and investigating the resulting test statistics. In particular, precise measurements like carrier phase and Doppler rate are employed under the assumption of fault free carrier signal. The presented position domain algorithm contains the following process; first a common pseudorange prediction formula is defined with the proposed variations in pseudorange differential update. Next, a threshold computation is proposed with the test statistics distribution considering the elevation angle. Then, by examining the test statistics, fault detection and isolation is done for each satellite channel. To verify the performance, simulations using the presented fault detection methods are done for an ideal and real fault case, respectively.

RBR Based Network Configuration Fault Management Algorithms using Agent Collaboration (에이전트들 간의 협력을 통한 RBR 기반의 네트워크 구성 장애 관리 알고리즘)

  • Jo, Gwang-Jong;An, Seong-Jin;Jeong, Jin-Uk
    • The KIPS Transactions:PartC
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    • v.9C no.4
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    • pp.497-504
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    • 2002
  • This paper proposes fault diagnosis and correction algorithms using agent collaboration, and a management model for managing network configuration faults. This management model is composed of three processes-fault detection, fault diagnosis and fault correction. Each process, based on RBR, operates on using rules which are consisted in Rule-based Knowledge Database. Proposed algorithm selves the complex fault problem that a system could not work out by itself, using agent collaboration. And the algorithm does efficiently diagnose and correct network configuration faults in abnormal network states.

Web Server Fault Diagnoisi and Recovery Mechanism Using INBANCA (INBANCA기법을 이용한 웹 서버 장애 진단 및 복구기법)

  • Yun, Jung-Mee;Ahn, Seong-Jin;Chung, Jin-Wook
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.8
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    • pp.2497-2504
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    • 2000
  • This paper is aimed at defining items of fault, and then constructing rules of fault diagnosis and recovery using INBANCA technology for the purpose of managing the weh server. The fault items of web server consist of the process fault, server overload, network interface fault, configuration and performance fault. Based on these items, the actual fault management is carried out fault referencing. In order to reference the fault, we have formulated the system-level fault diagnosis production rule and the service-level fault diagnosis rule, conjunction with translating management knowledge into active network. Also, adaptive recovery mechanism of web server is applied to defining recovery rule and constructing case library for case-based web server fault recovery. Finally, through the experiment, fault environment and applicability of each proposed production rule and recovering scheme are presented to verify justification of proposed diagnosis rules and recovery mechanism for fault management. An intelligent case-based fault management scheme proposed in this paper can minimize an effort of web master to remove fault incurred web administration and operation.

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Real-time In-situ Plasma Etch Process Monitoring for Sensor Based-Advanced Process Control

  • Ahn, Jong-Hwan;Gu, Ja-Myong;Han, Seung-Soo;Hong, Sang-Jeen
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.11 no.1
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    • pp.1-5
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    • 2011
  • To enter next process control, numerous approaches, including run-to-run (R2R) process control and fault detection and classification (FDC) have been suggested in semiconductor manufacturing industry as a facilitation of advanced process control. This paper introduces a novel type of optical plasma process monitoring system, called plasma eyes chromatic system (PECSTM) and presents its potential for the purpose of fault detection. Qualitatively comparison of optically acquired signal levels vs. process parameter modifications are successfully demonstrated, and we expect that PECSTM signal can be a useful indication of onset of process change in real-time for advanced process control (APC).

A Study on the Fault Diagnosis of Roller-Shape Using Frequency-Domain Analysis of Tension Signals (장력신호의 주파수 해석을 이용한 롤 형상 이상 진단에 관한 연구)

  • Sin, Gi-Hyeon
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.12
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    • pp.107-114
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    • 2000
  • Rollers and rolls in the continuous process systems are noes of key components that determine the quality of web products. The condition of rollers and rolls(ex. eccentricity wear) should be consistently monitored in order to maintain the process conditions (ex. tension, edge position) within a required specification. In this paper, a new diagnosis technique is suggested to detect the defect of rollers/rolls (ex. eccentricity, wear) based on frequency domain analysis of web tension signal. The kernel of this technique is to use the spectrum amplitude of tension signal which allows to identify the fault rollers/rolls and to also diagnose the degree of fault in corresponding rollers and rolls. The experimental results proved that the suggested diagnosis technique can be successfully used to identify the defect rollers and rolls as well as to diagnose the degree of the defect of those rollers. The suggested technique can be applied to monitor and diagnose the shape of rollers and rolls in various multi-span web transport systems.

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Bearing fault detection through multiscale wavelet scalogram-based SPC

  • Jung, Uk;Koh, Bong-Hwan
    • Smart Structures and Systems
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    • v.14 no.3
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    • pp.377-395
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    • 2014
  • Vibration-based fault detection and condition monitoring of rotating machinery, using statistical process control (SPC) combined with statistical pattern recognition methodology, has been widely investigated by many researchers. In particular, the discrete wavelet transform (DWT) is considered as a powerful tool for feature extraction in detecting fault on rotating machinery. Although DWT significantly reduces the dimensionality of the data, the number of retained wavelet features can still be significantly large. Then, the use of standard multivariate SPC techniques is not advised, because the sample covariance matrix is likely to be singular, so that the common multivariate statistics cannot be calculated. Even though many feature-based SPC methods have been introduced to tackle this deficiency, most methods require a parametric distributional assumption that restricts their feasibility to specific problems of process control, and thus limit their application. This study proposes a nonparametric multivariate control chart method, based on multiscale wavelet scalogram (MWS) features, that overcomes the limitation posed by the parametric assumption in existing SPC methods. The presented approach takes advantage of multi-resolution analysis using DWT, and obtains MWS features with significantly low dimensionality. We calculate Hotelling's $T^2$-type monitoring statistic using MWS, which has enough damage-discrimination ability. A bootstrap approach is used to determine the upper control limit of the monitoring statistic, without any distributional assumption. Numerical simulations demonstrate the performance of the proposed control charting method, under various damage-level scenarios for a bearing system.