• Title/Summary/Keyword: multiple fault diagnosis

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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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Development of Multiple Neural Network for Fault Diagnosis of Complex System (복합시스템 고장진단을 위한 다중신경망 개발)

  • Bae, Yong-Hwan
    • Journal of the Korean Society of Safety
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    • v.15 no.2
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    • pp.36-45
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    • 2000
  • Automated production system is composed of many complicated techniques and it become a very difficult task to control, monitor and diagnose this compound system. Moreover, it is required to develop an effective diagnosing technique and reduce the diagnosing time while operating the system in parallel under many faults occurring concurrently. This study develops a Modular Artificial Neural Network(MANN) which can perform a diagnosing function of multiple faults with the following steps: 1) Modularizing a complicated system into subsystems. 2) Formulating a hierarchical structure by dividing the subsystem into many detailed elements. 3) Planting an artificial neural network into hierarchical module. The system developed is implemented on workstation platform with $X-Windows^{(r)}$ which provides multi-process, multi-tasking and IPC facilities for visualization of transaction, by applying the software written in $ANSI-C^{(r)}$ together with $MOTIF^{(r)}$ on the fault diagnosis of PI feedback controller reactor. It can be used as a simple stepping stone towards a perfect multiple diagnosing system covering with various industrial applications, and further provides an economical approach to prevent a disastrous failure of huge complicated systems.

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Fault Detection and Diagnosis of CAN-Based Distributed Systems for Longitudinal Control of All-Terrain Vehicle(ATV) (무인 ATV의 종 방향 제어를 위한 CAN 기반 분산형 시스템의 고장감지 및 진단)

  • Kim, Soon-Tae;Song, Bong-Sob;Hong, Suk-Kyo
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.10
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    • pp.983-990
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    • 2008
  • This paper presents the fault detection and diagnosis(FDD) algorithm to enhance reliability of a longitudinal controller for an autonomous All-Terrain Vehicle(ATV). The FDD is designed to monitor and identify faults which may occur in distributed hardware used for longitudinal control, e.g., DSPs, CAN, sensors, and actuators. The proposed FDD is an integrated approach of decentralized and centralized FDD. While the former is processed in a DSP and suitable to detect faults in a single hardware, it is sensitive to noise and disturbance. On the other hand, the latter is performed via communication and it detects and diagnoses faults through analyzing concurrent performances of multiple hardware modules, but it is limited to isolate faults specifically in terms of components in the single hardware. To compensate for disadvantages of each FDD approach, two layered structure including both decentralized and centralized FDD is proposed and it allows us to make more robust fault detection and more specific fault isolation. The effectiveness of the proposed method will be validated experimentally.

FPGA Based Robust Open Transistor Fault Diagnosis and Fault Tolerant Sliding Mode Control of Five-Phase PM Motor Drives

  • Salehifar, Mehdi;Arashloo, Ramin Salehi;Eguilaz, Manuel Moreno;Sala, Vicent
    • Journal of Power Electronics
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    • v.15 no.1
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    • pp.131-145
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    • 2015
  • The voltage-source inverters (VSI) supplying a motor drive are prone to open transistor faults. To address this issue in fault-tolerant drives applicable to electric vehicles, a new open transistor fault diagnosis (FD) method is presented in this paper. According to the proposed method, in order to define the FD index, the phase angle of the converter output current is estimated by a simple trigonometric function. The proposed FD method is adaptable, simple, capable of detecting multiple open switch faults and robust to load operational variations. Keeping the FD in mind as a mandatory part of the fault tolerant control algorithm, the FD block is applied to a five-phase converter supplying a multiphase fault-tolerant PM motor drive with non-sinusoidal unbalanced current waveforms. To investigate the performance of the FD technique, the fault-tolerant sliding mode control (SMC) of a five-phase brushless direct current (BLDC) motor is developed in this paper with the embedded FD block. Once the theory is explained, experimental waveforms are obtained from a five-phase BLDC motor to show the effectiveness of the proposed FD method. The FD algorithm is implemented on a field programmable gate array (FPGA).

Real Time Fault Diagnosis of UAV Engine Using IMM Filter and Generalized Likelihood Ratio Test (IMM 필터 및 GLRT를 이용한 무인기용 엔진의 실시간 결함 진단)

  • Han, Dong-Ju;Kim, Sang-Jo;Kim, Yu-Il;Lee, Soo-Chang
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.8
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    • pp.541-550
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    • 2022
  • An effective real time fault diagnosis approach for UAV engine is drawn from IMM filter and GLRT methods. For this purpose based on the linear diagnosis model derived from engine dynamic performance analysis the Kalman filter for residual estimation and each method are applied to the fault diagosis of the actuator for engine control sensors. From the process of the IMM filter application the effective FDI measure is obtained and the state responses due to actuator fault are estimated. Likewise from the GLRT method the fault magnitudes of actuator and sensors are estimated associated with some FDI functionings. The numerical simulations verify the effectiveness of the IMM filter for FDI and the GLRT in estimating the fault magnitudes of each fault mode.

Application of Multiple Parks Vector Approach for Detection of Multiple Faults in Induction Motors

  • Vilhekar, Tushar G.;Ballal, Makarand S.;Suryawanshi, Hiralal M.
    • Journal of Power Electronics
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    • v.17 no.4
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    • pp.972-982
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    • 2017
  • The Park's vector of stator current is a popular technique for the detection of induction motor faults. While the detection of the faulty condition using the Park's vector technique is easy, the classification of different types of faults is intricate. This problem is overcome by the Multiple Park's Vector (MPV) approach proposed in this paper. In this technique, the characteristic fault frequency component (CFFC) of stator winding faults, rotor winding faults, unbalanced voltage and bearing faults are extracted from three phase stator currents. Due to constructional asymmetry, under the healthy condition these characteristic fault frequency components are unbalanced. In order to balanced them, a correction factor is added to the characteristic fault frequency components of three phase stator currents. Therefore, the Park's vector pattern under the healthy condition is circular in shape. This pattern is considered as a reference pattern under the healthy condition. According to the fault condition, the amplitude and phase of characteristic faults frequency components changes. Thus, the pattern of the Park's vector changes. By monitoring the variation in multiple Park's vector patterns, the type of fault and its severity level is identified. In the proposed technique, the diagnosis of faults is immune to the effects of unbalanced voltage and multiple faults. This technique is verified on a 7.5 hp three phase wound rotor induction motor (WRIM). The experimental analysis is verified by simulation results.

A Study on Fault Diagnosis of Power System Using Fuzzy Petri Nets (퍼지 페트리네트를 이용한 전력계통 고장진단에 관한 연구)

  • Roh, Myong-Gyun;Hong, Sang-Eun
    • Proceedings of the KIEE Conference
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    • 2000.07a
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    • pp.122-124
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    • 2000
  • As the complexity of power systems increases, especially in the case of multiple faults or incorrect operation of protective devices, fault diagnosis requires new and systematic methods to the reasoning process, which improves both its accuracy and its efficiency. Therefore this paper proposes a method of the modeling of protection systems and fault diagnosis in power systems using Fuzzy Petri Nets (FPN). The proposed method can reduce processing time and increase accuracy when compared with the traditional methods. And also this method can cover online processing of real-time data from SCADA (Supervisory Control and Data Acquisition).

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Ductility demands of steel frames equipped with self-centring fuses under near-fault earthquake motions considering multiple yielding stages

  • Lu Deng;Min Zhu;Michael C.H. Yam;Ke Ke;Zhongfa Zhou;Zhonghua Liu
    • Structural Engineering and Mechanics
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    • v.86 no.5
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    • pp.589-605
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    • 2023
  • This paper investigates the ductility demands of steel frames equipped with self-centring fuses under near-fault earthquake motions considering multiple yielding stages. The study is commenced by verifying a trilinear self-centring hysteretic model accounting for multiple yielding stages of steel frames equipped with self-centring fuses. Then, the seismic response of single-degree-of-freedom (SDOF) systems following the validated trilinear self-centring hysteretic law is examined by a parametric study using a near-fault earthquake ground motion database composed of 200 earthquake records as input excitations. Based on a statistical investigation of more than fifty-two (52) million inelastic spectral analyses, the effect of the post-yield stiffness ratios, energy dissipation coefficient and yielding displacement ratio on the mean ductility demand of the system is examined in detail. The analysis results indicate that the increase of post-yield stiffness ratios, energy dissipation coefficient and yielding displacement ratio reduces the ductility demands of the self-centring oscillators responding in multiple yielding stages. A set of empirical expressions for quantifying the ductility demands of trilinear self-centring hysteretic oscillators are developed using nonlinear regression analysis of the analysis result database. The proposed regression model may offer a practical tool for designers to estimate the ductility demand of a low-to-medium rise self-centring steel frame equipped with self-centring fuses progressing in the ultimate stage under near-fault earthquake motions in design and evaluation.

A High-Performance Fault-Tolerant Switching Network and Its Fault Diagnosis (고성능 결함감내 스위칭 망과 결함 진단법)

  • 박재현
    • Journal of KIISE:Information Networking
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    • v.31 no.3
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    • pp.335-346
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    • 2004
  • In this paper, we present a high-performance fault-tolerant switching networks using a deflection self-routing scheme, and present fault-diagnosis method for the network. We use the facts: 1) Each stage of the Banyan network is arrayed as the sequences of a Cyclic group of SEs. 2) There is the homomorphism between adjacent stages from a view of self-routing, so that all of each Cyclic group is the subgroup of the Cyclic group in the next stage, and there are factor groups due to such subgroup and homomorphism. We provide high-performance fault-tolerant switching networks of which the all links including augmented links are used as the alternate links detouring faulty links. We also present the fault diagnosis scheme for the proposed switching network that provide multiple paths for each input-output pair.

Actuator Fault Diagnosis of UAVs using Adaptive Unknown Input Observers (적응 미지입력 관측기를 이용한 무인항공기의 조종면 구동기 고장진단)

  • Cho, Shin-Je;Shin, Sung-Sik;Choi, Seung-Kie;Moon, Jung-Ho;Roh, Eun-Jung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.12
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    • pp.1177-1183
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    • 2010
  • In this paper, a parallel bank of multiple adaptive unknown input observers approach suggested by D.Wang is applied to detect a single fault of control surface actuator and to estimate the actuator position of lock-in-place fault using a small fixed-wing UAV model with eight control surfaces. This paper shows that not only the fault diagnosis algorithm detects and estimates each faults of lock-in-place in 1 second by simulation but also it may be unavailable to isolate among two same-shaped rudders.