• Title/Summary/Keyword: 고장검출과 진단

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Development of Inverter fault diagnostic algorithm based on CT for small-sized wind turbine system (CT기반의 소형 풍력발전 시스템 인버터 고장진단 알고리즘 개발)

  • Moon, Dae-Sun;Kim, Sung-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.767-774
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    • 2011
  • In recent years, wind turbine system has been considered as the most efficient renewable energy source. Wind turbine system is a complex system which is composed of blade, generator and inverter systems. Recently, lots of researches on fault detection and diagnosis of wind turbine system have been done. Most of them are related with the fault diagnosis of mechanical elements using bivration signal. In this work, a new type of inverter fault detection and diagnstic algorithm is proposed. Furthermore, extensive simulation studies and practical experiments are carried out to verify the proposed algorithm.

Design on Fult Diagnosis System based on Dynamic Fuzzy Model (동적포지모델기반 고장진단 시스템의 설계)

  • 배상욱
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.2
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    • pp.94-102
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    • 2000
  • This paper presents a new FDI scheme based on dynamic fuzzy model(DFM) for the unknown nonlinear system, which can detect and isolate process faults continuously over all ranges of operating condition. The dynamic behavior of a nonlinear process is represented by a set of local linear models. The parameters of the DFM are identified by an on-line methods. The residual vector of the FDI system is consisted of the parameter deviations from nominal model and the set of grade of membership values indicating the operating condition of the nonlinear process. The detection and isolation of faults are performed via a neural network classifier that are learned the relationship between the residual vector and fault type. We apply the proposed FDI scheme to the FDI system design for a two-tank system and show the usefulness of the proposed scheme.

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Diagnostic Test Pattern Generation for Combinational Circuits (조합회로에 대한 고장 진단 검사신호 생성)

  • Park, Young-Ho;Min, Hyoung-Bok;Lee, Jae-Hoon;Shin, Yong-Whan
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.36C no.9
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    • pp.44-53
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    • 1999
  • Generating diagnostic test patterns for combinational circuits remain to be a very difficult problem. For example, ISCAS85 c7552 benchmark circuit has 100 million fault pairs, Thus, we need more sophisticated algorithm to get more information. A new diagnostic algorithm for test pattern generation is suggested and implemented in this paper. DIATEST algorithm based on PODEM is also implemented for comparison to the new algorithm. These two algorithms have been applied to ISCAS85 benchmark circuits. Experimental results show that (1) both algorithms achieve fault pair coverage over 99%, (2) total test length of the new algorithm is much shorter than that of DIATEST, and (3) the new algorithm gives much more information used for making diagnostic dictionary, diagnostic decision tree or diagnostic test system despite DIATEST is faster than the new algorithm.

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State Transition Fault Diagnosis in Brushless DC Motor Based on Fuzzy System (퍼지를 이용한 BLDC 모터의 상태천이 고장진단)

  • Baek, Gyeong-Dong;Kim, Youn-Tae;Kim, Sung-Shin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.3
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    • pp.367-372
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    • 2008
  • In this paper we proposed a model of a fault diagnosis expert system with high reliability to compare identical well-functioning motors. The purpose of the survey was to determine if any differences exit among these identical motors and to identify exactly what these differences were, if in fact they were found. Using measured data for many identical brushless dc motors, this study attempted to find out whether normal and fault can be classified by each other. Measured data was analyzed using the State Transition Model (STM). Based on a proposed STM method, the effect of a different normal state is minimized and the detection of fault is improved in identical motor system. Experimental results are presented to prove that STM method could be a useful tool for diagnosing the condition of identical BLDE motors.

A Study on Efficient Fault-Diagnosis for Multistage Interconnection Networks (다단 상호 연결 네트워크를 위한 효율적인 고장 진단에 관한 연구)

  • Bae, Sung-Hwan;Kim, Dae-Ik;Lee, Sang-Tae;Chon, Byoung-SIl
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.5
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    • pp.73-81
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    • 1996
  • In multiprocessor systems with multiple processors and memories, efficient communication between processors and memories is critical for high performance. Various types of multistage networks have been proposed. The economic feasibility and the improvements in both computing throughput and fault tolerance/diagnosis have been some of the most important factors in the development of these computer systems. In this paper, we present an efficient algorithm for the diagnosis of generalized cube interconnection networks with a fan-in/fan-out of 2. Also, using the assumed fault model present total fault diagnosis by generating suitable fault-detection and fault-location test sets for link stuck fault, switching element fault in direct/cross states, including broadcast diagnosis methods based on some basic properties or generalized cube interconnection networks. Finally, we illustrate some example.

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Remote Fault Detection in Conveyor System Using Drone Based on Audio FFT Analysis (드론을 활용하고 음성 FFT분석에 기반을 둔 컨베이어 시스템의 원격 고장 검출)

  • Yeom, Dong-Joo;Lee, Bo-Hee
    • Journal of Convergence for Information Technology
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    • v.9 no.10
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    • pp.101-107
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    • 2019
  • This paper proposes a method for detecting faults in conveyor systems used for transportation of raw materials needed in the thermal power plant and cement industries. A small drone was designed in consideration of the difficulty in accessing the industrial site and the need to use it in wide industrial site. In order to apply the system to the embedded microprocessor, hardware and algorithms considering limited memory and execution time have been proposed. At this time, the failure determination method measures the peak frequency through the measurement, detects the continuity of the high frequency, and performs the failure diagnosis with the high frequency components of noise. The proposed system consists of experimental environment based on the data obtained from the actual thermal power plant, and it is confirmed that the proposed system is useful by conducting virtual environment experiments with the drone designed system. In the future, further research is needed to improve the drone's flight stability and to improve discrimination performance by using more intelligent methods of fault frequency.

Fault diagnosis of Induction motors by DFT based feature extraction and distance similarity (DFT기반 특징추출 및 거리유사도에 의한 유도전동기 고장진단)

  • Park, Chan-Won;Kwon, Mann-Jun;Park, Sung-Mu;Lee, Dae-Jong;Chun, Myung-Geun
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.157-158
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    • 2007
  • 본 논문에서는 산업전반에 걸쳐 널리 사용되는 유도전동기의 고장상태를 검출하기 위해 DFT(Discreet Fourier Transform)와 LDA에 기반을 둔 진단 알고리즘을 제안하고자 한다. 실험에 의해 측정된 전류값을 DFT에 의해 시간공간에서 주파수 공간으로 변환한 후에 LDA기법을 이용하여 특징벡터를 산출한 후 거리 유사도에 의해 진단이 수행된다. 제안된 방법의 타당성을 보이기 위해 여섯 가지의 고장을 대상으로 다양한 조건하에서 실험한 결과 기존 방법에 비교하여 우수한 결과를 나타냈다.

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Development of a Fault Detection and Diagnosis Algorithm Using Fault Mode Simulation for a Centrifugal Chiller (고장모사 시뮬레이션을 이용한 터보냉동기의 고장검출 및 진단 알고리즘 개발)

  • Han, Dong-Won;Chang, Young-Soo
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.20 no.10
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    • pp.669-678
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    • 2008
  • When operating a complex facility, Fault Detection and Diagnosis (FDD) system is beneficial in equipment management by providing the operator with tools which can help find out a failure of the system. In this research, FDD algorithm was developed using the general pattern classifier method that can be applied to centrifugal chiller system. The simulation model for a centrifugal chiller system was developed in order to obtain characteristic data of turbo chiller system under normal and faulty operation. We tested FDD algorithm of a centrifugal chiller using data from simulation model at full load performance and 60% part load performance. In this research, we presented fault detection method using a normalized distance. Sensitivity analysis of fault detection was carried out with respect to fault progress. FDD algorithm developed in this study was found to indicate each failure modes accurately.

Development of fault diagnostic system for mass unbalance and aerodynamic asymmetry of wind turbine system by using GH-Bladed (GH-Bladed를 이용한 풍력발전기의 질량 불평형 및 공력 비대칭 고장진단 시스템 개발)

  • Kim, Se-Yoon;Kim, Sung-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.1
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    • pp.96-101
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    • 2014
  • Wind power is the fastest growing renewable energy source in the world and it is expected to remain so for some times. Recently, there is a constant need for the reduction of Operational and Maintenance(O&M) costs of Wind Energy Conversion Systems(WECS). The most efficient way of reducing O&M cost would be to utilize CMS(Condition Monitoring System) of WECS. CMS allows for early detection of the deterioration of the wind generator's health, facilitating a proactive action, minimizing downtime, and finally maximizing productivity. There are two types of faults such as mass unbalance and aerodynamic asymmetry which are related to wind turbine's rotor faults. Generally, these faults tend to generate various vibrations. Therefore, in this work a simple fault detection algorithm based on spectrums of vibration signals and simple max-min decision logic is proposed. Furthermore, in order to verify its feasibility, several simulation studies are carried out by using GH-bladed software.