• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.6
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• pp.615-628
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• 2015

CGRA (Coarse-Grained Reconfigurable Architecture) based multi-core architecture can be considered as a suitable solution for the fault-tolerant computing. However, there have been a few research projects based on fault-tolerant CGRA without exploiting the strengths of CGRA as well as their works are limited to single CGRA. Therefore, in this paper, we propose two approaches to enable exploiting the inherent redundancy and reconfigurability of the multi-CGRA for fault-recovery. One is a resilient inter-CGRA fabric that is ring-based sharing fabric (RSF) with minimal interconnection overhead. Another is a novel intra/inter-CGRA reconfiguration technique on RSF for maximizing utilization of the resources when faults occur. Experimental results show that the proposed approaches achieve up to 94% faulty recoverability with reducing area/delay/power by up to 15%/28.6%/31% when compared with completely connected fabric (CCF).

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.87-87
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• 2000

In this paper, an integrated design of fault detection, diagnosis and reconfigurable control tot multi-input and multi-output system is proposed. It is based on the interacting multiple model estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural and/or parametric changes. This research focuses on the method to recover the performance of a system with failed actuators by switching plant models and controllers appropriately. The proposed scheme is applied to a fault tolerant control design for flight control system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1233-1240
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• 2004

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the nitration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.537-543
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• 2003

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the vibration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.107-116
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• 2003

This paper presents a systematic design methodology for fault tolerant controller against a fault in actuators and sensors of linear stochastic systems with uncertainties. The scheme is based on fault detection and diagnosis(isolation and estimation) using a bank of robust two-stage Kalman filters, and accommodation of the actuator fault by eigenstructure assignment and immediate compensation of the sensor's faulty measurement. In order to clarify the fault feature in test statistics of residual, noise reduction method is given by multi-scale discrete wavelet transform. The effectiveness of our approach Is shown via simulations for a VTOL(vertical take-off and landing) aircraft subjected to parameter variations, external disturbances, process and sensor noises.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.1885-1891
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• 2007

This paper presents a distance relaying algorithm for phase-to-ground faults in transmission lines under Multi-Agent protection environment. In normal condition, a distance relay agent stores the latest states, e.g., voltage of source side, voltage of the opposite side and the loading conditions, etc., through communication between the agents. Once a fault occurs, the relay calculates the fault location using the knowledge about the states just before the fault happens. This stand-alone operation is to improve reliability under the fault condition at which the accuracy or time required for communication may not be guaranteed. The mathematical expression of fault location is derived through loop analysis, before hand, in the manner that both fault current from the opposite end and fault resistance are included implicitly so that their effects are minimized. The suggested algorithm is applied to a typical transmission system with two power sources on both ends to show its effectiveness.

• Smart Structures and Systems
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• v.23 no.3
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• pp.279-293
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• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1130-1132
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• 1999

This paper presents the feature extraction of fault current related to the multi-shot reclosing scheme in the power distribution system. Fourier transform is used to extract the feature of the fault current waveform in the case of the temporary fault and the permanent fault. After the waveform is analyzed using Fourier transform, the magnitude spectrum and the relative variation of THD are calculated. These results are that the relative variation of THD is great in the temporary fault and is little in the permanent fault.

• Advances in robotics research
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• v.2 no.1
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• pp.99-112
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• 2018

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.503-510
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• 2002

This paper presents a fault diagnosis method using neural network-based multi-fault models and statistical method to detect and isolate faults in nonlinear systems. In the proposed method, faults are detected when the errors between the system output and the neural network nominal system output cross a predetermined threshold. Once a fault in the system is detected, the fault classifier statistically isolates the fault by using the error between each neural network-based fault model output and the system output. From the computer simulation results, it is verified that the proposed fault diagonal method can be performed successfully to detect and isolate faults in a nonlinear system.