• 제목/요약/키워드: Model-Based Fault Diagnosis

검색결과 217건 처리시간 0.026초

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

  • 김봉석;이인수;이윤준;김경연
    • 전기전자학회논문지
    • /
    • 제7권1호
    • /
    • pp.107-118
    • /
    • 2003
  • 원전 탈기기 저장탱크의 기하학적 구조 및 정상 상태에서의 입출력 흐름율을 고려하여 동적 제어 모델을 설정하고, 적응 추정기를 이용하여 수위 측정 센서의 고장 검출 및 진단 기법을 제안하였다. 영광 3, 4호기의 실제 운전 데이터를 적용하여 제안된 고장 검출 및 진단 기법의 성능을 평가하고 타당성을 검증하였다.

  • PDF

룰 베이스를 이용한 공조기의 고장검출 및 진단 (Fault Detection and Diagnosis of an Air Handling Unit Based on Rule Bases)

  • 한도영;주명재
    • 설비공학논문집
    • /
    • 제14권7호
    • /
    • pp.552-559
    • /
    • 2002
  • The fault detection and diagnosis (FDD) technology may be applied in order to decrease the energy consumption and the maintenance cost of the air conditioning system. In this study, rule bases and curve fitting models were used to detect faults in an air handling unit. Gradually progressed faults, such as the fan speed degradation, the coil water leakage, the humidifier nozzle clogging, the sensor degradation and the damper stoppage, were applied to the developed FBD system. Simulation results show good detections and diagnoses of these faults. Therefore, this method may be effectively used for the fault detection and diagnosis of the air handling unit.

Redundant 디지털 시스템에서의 고장진단에 관한 연구

  • 김기섭;김정선
    • 한국통신학회:학술대회논문집
    • /
    • 한국통신학회 1983년도 추계학술발표회논문집
    • /
    • pp.112-117
    • /
    • 1983
  • In this paper, a functional m-redundant system, which is me-fault tolerant, is defined based on the graph-theory. This system is designed to be t fault-diagnosable by comparing its unit's outcomes without additive test functions, and so, the system down for diagnosis is not needed. the diagnostic model for this system is presented and this effectively uses system's redundancy. It is shown that this model can be converted into Preparata's model. Thus, the diagnostic characteristics of a functional m-redundant system is analyzed by the methods originated by Preparata et al..

  • PDF

Dynamic Simulation and Analysis of the Space Shuttle Main Engine with Artificially Injected Faults

  • Cha, Jihyoung;Ha, Chulsu;Koo, Jaye;Ko, Sangho
    • International Journal of Aeronautical and Space Sciences
    • /
    • 제17권4호
    • /
    • pp.535-550
    • /
    • 2016
  • Securing the safety and the reliability of liquid-propellant rocket engines (LREs) for space vehicles is indispensable as engines consist of many complex components and operate under extremely high energy-dense conditions. Thus, health monitoring has become a mandatory requirement, especially for the reusable LREs that are currently being developed. In this context, a dynamic simulation program based on MATLAB/Simulink was developed in the current research on the Space Shuttle Main Engine (SSME), a partly reusable engine. Then, a series of fault simulations using this program was conducted: at a steady state operating condition (104% Rated Propulsion Level), various simulated fault conditions were artificially injected into the simulation models for the five major valves, the pumps, and the turbines of the SSME. The consequent effects due to each fault were analyzed based on the time responses of the major parameters of the engine. It is believed that this research topic is an essential pre-step for the development of fault detection and diagnosis algorithms for reusable engines in the future.

고분자전해질연료전지를 위한 고장 검출 및 진단 기술 (Fault Detection and Diagnosis Methods for Polymer Electrolyte Fuel Cell System)

  • 이원용;박구곤;손영준;김승곤;김민진
    • 한국수소및신에너지학회논문집
    • /
    • 제28권3호
    • /
    • pp.252-272
    • /
    • 2017
  • Fuel cell systems have to satisfy acceptable operating reliability, sufficient lifetime and price to enter the market in competition with existing products. Fuel cells are made up of complex element technologies and various problems related to the failure of the components can affect the reliability and safety of the system. This problem can be overcome by introducing a monitoring and supervisory control system in addition to automatic control to detect the failure of the fuel cell quickly and properly diagnose the performance degradation. For the fault detection and diagnosis of polymer electrolyte fuel cells, the model based method using the theoretical superposition value and the non-model based method of checking the signal tendency or the converted signal characteristic can be applied. The methods analyzed in this paper can contribute to the development of integrated monitoring and control technology for the whole system as well as the stack.

모델 기반 유도전동기 고장진단에 관한 연구 (A Study on the Model Based Diagnosis of Induction Motor)

  • 이홍희;이현영
    • 전력전자학회:학술대회논문집
    • /
    • 전력전자학회 2003년도 춘계전력전자학술대회 논문집(2)
    • /
    • pp.644-647
    • /
    • 2003
  • The predictive maintenance can help to avoid the serious plant breakdowns and catastrophies. This paper deals with the fault diagnosis of the rotor of the induction motor which is widely used in the plants. In order to detect the broken bar, the Extended Kalman Filter is adopted to estimate the rotor resistance on the base of model-based method. The proposed estimation method is simulated with the aid of Matlab.

  • PDF

Fault Detection and Diagnosis of Winding Short in BLDC Motors Based on Fuzzy Similarity

  • Bae, Hyeon;Kim, Sung-Shin;Vachtsevanos, George
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제9권2호
    • /
    • pp.99-104
    • /
    • 2009
  • The turn-to-turn short is one major fault of the motor faults of BLDC motors and can appear frequently. When the fault happens, the motor can be operated without breakdown, but it is necessary to maintain the motor for continuous working. In past research, several methods have been applied to detect winding faults. The representative approaches have been focusing on current signals, which can give important information to extract features and to detect faults. In this study, current sensors were installed to measure signals for fault detection of BLDC motors. In this study, the Park's vector method was used to extract the features and to isolate the faults from the current measured by sensors. Because this method can consider the three-phase current values, it is useful to detect features from one-phase and three-phase faults. After extracting two-dimensional features, the final feature was generated by using the two-dimensional values using the distance equation. The values were used in fuzzy similarity to isolate the faults. Fuzzy similarity is an available tool to diagnose the fault without model generation and the fault was converted to the percentage value that can be considered as possibility of the fault.

시분할 CNN-LSTM 기반의 시계열 진동 데이터를 이용한 회전체 기계 설비의 이상 진단 (Anomaly Diagnosis of Rotational Machinery Using Time-Series Vibration Data Based on Time-Distributed CNN-LSTM)

  • 김민기
    • 한국멀티미디어학회논문지
    • /
    • 제25권11호
    • /
    • pp.1547-1556
    • /
    • 2022
  • As mechanical facilities are interacting with each other, the failure of some equipment can affect the entire system, so it is necessary to quickly detect and diagnose the abnormality of mechanical equipment. This study proposes a deep learning model that can effectively diagnose abnormalities in rotating machinery and equipment. CNN is widely used for feature extraction and LSTMs are known to be effective in learning sequential information. In LSTM, the number of parameters and learning time increase as the length of input data increases. In this study, we propose a method of segmenting an input segment signal into shorter-length sub-segment signals, sequentially inputting them to CNN through a time-distributed method for extracting features, and inputting them into LSTM. A failure diagnosis test was performed using the vibration data collected from the motor for ventilation equipment installed at the urban railway station. The experiment showed an accuracy of 99.784% in fault diagnosis. It shows that the proposed method is effective in the fault diagnosis of rotating machinery and equipment.

Reliability analysis of nuclear safety-class DCS based on T-S fuzzy fault tree and Bayesian network

  • Xu Zhang;Zhiguang Deng;Yifan Jian;Qichang Huang;Hao Peng;Quan Ma
    • Nuclear Engineering and Technology
    • /
    • 제55권5호
    • /
    • pp.1901-1910
    • /
    • 2023
  • The safety-class (1E) digital control system (DCS) of nuclear power plant characterized structural multiple redundancies, therefore, it is important to quantitatively evaluate the reliability of DCS in different degree of backup loss. In this paper, a reliability evaluation model based on T-S fuzzy fault tree (FT) is proposed for 1E DCS of nuclear power plant, in which the connection relationship between components is described by T-S fuzzy gates. Specifically, an output rejection control system is chosen as an example, based on the T-S fuzzy FT model, the key indicators such as probabilistic importance are calculated, and for a further discussion, the T-S fuzzy FT model is transformed into Bayesian Network(BN) equivalently, and the fault diagnosis based on probabilistic analysis is accomplished. Combined with the analysis of actual objects, the effectiveness of proposed method is proved.

다중 엔진모델을 이용한 센서 고장허용 가스터빈 엔진제어기 설계 (Sensor Fault-tolerant Controller Design on Gas Turbine Engine using Multiple Engine Models)

  • 김중회;이상정
    • 한국추진공학회지
    • /
    • 제20권2호
    • /
    • pp.56-66
    • /
    • 2016
  • 모델기반 FDI 과정에서 모델오차와 센서잡음은 피할 수 없으므로 견실성은 모델기반 FDI에서 매우 중요하다. 본 연구에서는 이러한 선형모델 오차 및 신호잡음으로 인하여 고장진단 과정에서 발생하는 결함판단 오류들을 비선형 NARX (Nonlinear Auto Regressive eXogenous) 모델과 칼만추정기를 적용하여 개선하는 방법을 제안하였다. 최종 고장판단은 퍼지로직을 이용하여 발생하는 오차의 추이에 대한 확률로 결정하여 순간적인 신호잡음에 강인하도록 설계하였다. 시뮬레이션을 통하여 운용 환경조건에서 엔진제어기의 고장허용에 따른 성능을 확인하였다.