• Title/Summary/Keyword: Model-based fault detection

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Design of Self-Repairing Suspension Systems via Variable Structure Control Scheme (가변구조 제어기법을 이용한 고장허용 현가장치 설계)

  • 김도현
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.11
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    • pp.922-927
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    • 2002
  • A variable structure control (VSC) based model following control system that possesses fault detection and isolation (FDI) capability as well as fault tolerance property is proposed. The nonlinear part of the proposed control law. whose magnitude is determined by sliding variables, plays the role of suppressing fault effect. Thus, approximate fault reconstruction is also possible via the analysis of sliding variables. The proposed algorithm is applied to an active suspension system of pound vehicles to verify its applicability.

Real-Time Fault Detection in Discrete Manufacturing Systems Via LSTM Model based on PLC Digital Control Signals (PLC 디지털 제어 신호를 통한 LSTM기반의 이산 생산 공정의 실시간 고장 상태 감지)

  • Song, Yong-Uk;Baek, Sujeong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.2
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    • pp.115-123
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    • 2021
  • A lot of sensor and control signals is generated by an industrial controller and related internet-of-things in discrete manufacturing system. The acquired signals are such records indicating whether several process operations have been correctly conducted or not in the system, therefore they are usually composed of binary numbers. For example, once a certain sensor turns on, the corresponding value is changed from 0 to 1, and it means the process is finished the previous operation and ready to conduct next operation. If an actuator starts to move, the corresponding value is changed from 0 to 1 and it indicates the corresponding operation is been conducting. Because traditional fault detection approaches are generally conducted with analog sensor signals and the signals show stationary during normal operation states, it is not simple to identify whether the manufacturing process works properly via conventional fault detection methods. However, digital control signals collected from a programmable logic controller continuously vary during normal process operation in order to show inherent sequence information which indicates the conducting operation tasks. Therefore, in this research, it is proposed to a recurrent neural network-based fault detection approach for considering sequential patterns in normal states of the manufacturing process. Using the constructed long short-term memory based fault detection, it is possible to predict the next control signals and detect faulty states by compared the predicted and real control signals in real-time. We validated and verified the proposed fault detection methods using digital control signals which are collected from a laser marking process, and the method provide good detection performance only using binary values.

Fast Diagnosis Method for Submodule Failures in MMCs Based on Improved Incremental Predictive Model of Arm Current

  • Xu, Kunshan;Xie, Shaojun
    • Journal of Power Electronics
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    • v.18 no.5
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    • pp.1608-1617
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    • 2018
  • The rapid and correct isolation of faulty submodules (SMs) is of great importance for improving the reliability of modular multilevel converters (MMCs). Therefore, a fast diagnosis method containing fault detection and fault location determination was presented in this paper. An improved incremental predictive model of arm current was proposed to detect failures, and the multi-step prediction method was used to eliminate the negative impact of disturbances. Moreover, a control method was proposed to strengthen the fault characteristics to rapidly locate faulty arms and faulty SMs by detecting the variation rate of the SM capacitor voltage. The proposed method can rapidly and easily locate faulty SMs under different load conditions without the need for additional sensors. The experimental results have validated the effectiveness of the proposed method by using a single-phase MMC with four SMs per arm.

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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Ungrounded System Fault Section Detection Method by Comparison of Phase Angle of Zero-Sequence Current

  • Yang, Xia;Choi, Myeon-Song;Lee, Seung-Jae;Lim, Il-Hyung;Lim, Seong-Il
    • Journal of Electrical Engineering and Technology
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    • v.3 no.4
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    • pp.484-490
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    • 2008
  • In this paper, an integrated fault section detection and isolation strategy is proposed based on the application of the Distribution Automation System(DAS) utilizing advanced IT and communication technologies. The Feeder Remote Terminal Unit(FRTU) has been widely used to collect data in the Korean distribution system. The achieved data is adopted in this method for detecting multiple fault types. Especially in the case of single phase-to-ground fault, the fault section is detected by comparison of the zero-sequence current phase angle. The test results have verified the effectiveness of the proposed method in a radial distribution system through extensive simulations in Matlab/Simulink. Furthermore, a communication-based demo system identical to the simulation model has been developed, and it can be applied as an online monitoring and control program for fault section detection and isolation.

An Integrated Fault Detection and Isolation Method for Sensors and Actuators of LEO Satellite (저궤도 인공위성의 센서 및 구동기 통합 고장검출 및 분리 기법)

  • Lim, Jun-Kyu;Lee, Jun-Han;Park, Chan-Gook
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.11
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    • pp.1117-1124
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    • 2011
  • An integrated fault detection and isolation method is proposed in this paper. The main objective of this paper is development fault detection, isolation and diagnosis algorithm based on the DKF (Decentralized Kalman Filter) and the bank of IMM (Interacting Multiple Model) filters using penalty scalar for both partial and total faults and the outlier detection algorithm for preventing false alarm also included. The proposed FDI (Fault Detection and Isolation) scheme is developed in four phases. In the first phase, the outlier detection filter is designed to prevent false alarm as a pre-filter. In the second phases, two local filters and master filter are designed to detect sensor faults. In the third phases, the proposed FDI scheme checks sensor residual to isolate sensor faults and 11 EKFs actuator fault models are designed to detect wherever actuator faults occur. In the last phases, four filters are designed to identify the fault type which is either the total fault or partial fault. The developed scheme can deal with not only sensor and actuator faults, but also preventing false alarm. An important feature of the proposed FDI scheme can decreases fault isolation time and figure out not only fault detection and isolation but also fault type identification. To verify the proposed FDI algorithm performance, the Simulator is also developed under the Matlab/Simulink environment.

Development of Vehicle Longitudinal Controller Fault Detection Algorithm based on Driving Data for Autonomous Vehicle (자율주행 자동차를 위한 주행 데이터 기반 종방향 제어기 고장 감지 알고리즘 개발)

  • Yoon, Youngmin;Jeong, Yonghwan;Lee, Jongmin;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.11 no.2
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    • pp.11-16
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    • 2019
  • This paper suggests an algorithm for detecting fault of longitudinal controller in autonomous vehicles. Guaranteeing safety in fault situation is essential because electronic devices in vehicle are dependent each other. Several methods like alarm to driver, ceding control to driver, and emergency stop are considered to cope with fault. This research investigates the fault monitoring process in fail-safe system, for controller which is responsible for accelerating and decelerating control in vehicle. Residual is computed using desired acceleration control command and actual acceleration, and detection of its abnormal increase leads to the decision that system has fault. Before computing residual for controller, health monitoring process of acceleration signal is performed using hardware and analytic redundancy. In fault monitoring process for controller, a process model which is fitted using driving data is considered to improve the performance. This algorithm is simulated via MATLAB tool to verify performance.

Unscented Kalman Filter For Aircraft Sensor Fault Detection

  • Kim, In-Jung;Kim, You-Dan
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2335-2339
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    • 2003
  • To prevent the critical situation due to the fault in the aircraft sensor system, the fault tolerant system with triple or quadruple redundancy can be made. However, if the faults are occurred in two or more than sensors simultaneously, the conventional fault detection process, such as cross-channel monitoring, may give the wrong fault alarm. For this case, we can detect the fault by estimating the state vector based on the system dynamics model, which is nonlinear for aircraft. In this paper, we propose the unscented Kalman filter to estimate the nonlinear state vector. This filter utilizes the so-called unscented transformation of sigma points featured the statistical characteristics of the random variable. For verification, we perform the simulations for F-16 aircraft with accelerometers, gyros, GPS and air data system.

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Model-Free Hybrid Fault Detection and Isolation For UAV Inertial Measurement Sensors (무인기 관성측정 센서의 비모델 복합 고장진단기법)

  • Kim, Seung-Keun;Kim, You-Dan
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.3
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    • pp.200-206
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    • 2005
  • In this paper, a redundancy management system for aircraft is studied, and FDI (Fault Detection and Isolation) algorithm of inertial sensor system is proposed. UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional FDI method cannot isolate multiple faults in a triple redundancy system. In this paper, hardware based FDI technique is proposed, which combines a parity equation approach with the wavelet based technique, which is a model-free FDI method. To verify the effectiveness of the proposed FDI method, numerical simulations are performed.

Design of the robust propulsion controller using nonlinear ARX model (비선형 ARX 모델을 이용한 센서 고장에 강인한 추진체 제어기 설계)

  • Kim, Jung-Hoe;Gim, Dong-Choon;Lee, Sang-Jeong
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2011.11a
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    • pp.599-602
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    • 2011
  • A propulsion controller for one-time flight vehicles should be designed robustly so that it can complete its missions even in case sensor failures. These vehicles improve their fault tolerance by back-up sensors prepared for the failure of major sensors, which raises the total cost. This paper presents the NARX model which substitutes vehicles' velocity sensors, and detects failure of sensor signals by using model based fault detection. The designed NARX model and fault detection algorithm were optimized and installed in TI's TMS320F2812 so that they were linked to HILS instruments in real-time. The designed propulsion controller made the vehicle to have better fault tolerance with fewer sensors and to complete its missions under a lot of complicated failure situations. The controller's applicability was finally confirmed by tests under the HILS environment.

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