• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.24-32
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• 2002

This paper is concerned with the fault diagnosis for stuck-at faults of a multistage interconnection network(MIM) which is a kind of interconnection networks in multicomputer systems. Up to the present, a fault diagnosis scheme has dealt with a fault model of all types, which results in complicated algorithms. In the literature, it is shown that a number of steps and computation are required for the fault detection and isolation algorithms for a class of MINs. In this paper, we propose a simple and easily implementable algorithm for the detection and isolation of the stuck-at fault in MIM. specifically, we develope an at algorithm for the isolation of the source fault in switching elements whenever tile stuck-at fault is detected in MINs. After all, the proposed algorithm is illustrated by an example of 16$\times$16 baseline networks of MINs.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.601-607
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• 2010

For commercial success of emerging service robots, the fault tolerant technology for system reliability and human safety is crucial. Traditionally fault tolerance methods have been implemented in application level. However, from our studies on the common design patterns in fault tolerance, we argue that a framework-based approach provides many benefits in providing reliability for system development. To demonstrate the benefits, we build a framework-based fault tolerant engine for OPRoS (Open Platform for Robotic Services) standards. The fault manager in framework provides a set of fault tolerant measures of detection, isolation, and recovery. The system integrators choose the appropriate fault handling tools by declaring XML configuration descriptors, considering the constraints of components and operating environment. By building a fault tolerant navigation application from the non-faulttolerant components, we demonstrate the usability and benefits of the proposed framework-based approach.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.28-37
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• 2013

This paper presents a fault-tolerant control technique for wind turbine systems with sensor and actuator faults. The control objective is to maximize power production and minimize turbine loads by calculating a desired pitch angle within their limits. Any fault with a sensor and actuator can cause significant error in the pitch position of the corresponding blade. This problem may result in insufficient torque such that the power reference cannot be achieved. In this paper, a fault-tolerant control technique using a robust dynamic inversion observer and control allocation is employed to achieve successful pitch control despite these faults in the sensor and actuator. The observer based detection method is used to detect and isolate sensor faults by checking whether errors are larger than threshold values. In addition, the control allocation technique is adopted to tolerate actuator fault. Control allocation is one of the most commonly used fault-tolerant control techniques, especially for over-actuated systems. Further, the control allocation method can be used to achieve the power reference even in the event of blade actuator fault by redistributing the lost torque due to erroneous pitch position into non-faulty blade actuators. The effectiveness of the proposed method is demonstrated through simulations with a benchmark model of the wind turbine.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.251-258
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• 2003

Optical Switching Matrix (OSM) or Optical Multistage Interconnection Networks (OMINs) comprising photonic switches have been studied extensively as important interconnecting blocks for Optical Cross Connects (OXC) based on Optical Burst Switching (OBS). A basic element of photonic switching networks is a 2$\times$2 directional coupler with two inputs and two outputs. This paper is concerned with the diagnosis of multiple crosstalk-faults in OSM. As the network size becomes larger in these days, the conventional diagnosis methods based on tests and simulation become inefficient, or even more impractical. We propose a simple and easily implementable algorithm for detection and isolation of the multiple crosstalk-faults in OSM. Specifically. we develop an algorithm for isolation of the source fault in switching elements whenever the multiple crosstalk-faults arc detected in OSM. The proposed algorithm is illustrated by an example of 16$\times$16 OSM.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.859-868
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• 2016

This paper proposes a new global positioning system (GPS) receiver algorithm to improve the positioning accuracy of a transporter using fault detection and isolation techniques from satellite signals. To improve the positioning accuracy, several factors including a feasible number of satellite signals, SNR, NAV Measurement Quality Indicator (mesQI), and Doppler, among others, have been utilized in the proposed algorithm. To increase the number of feasible satellite signals, an erroneous satellite signal has been replaced by the previous one. In conventional approaches, received GPS signals are analyzed and directly determined to be contaminated or not. The only clean signals are utilized for identifying the current location. This fault detection and isolation (FDI) feasibility test is popular for commercial GPS receivers. In the urban environment, especially near a building, the feasible number of satellite signals becomes insufficient to position the transporter. To overcome this problem, satellite signals are efficiently selected and recovered. Additionally, using the proposed GPS receiver algorithm, a feasible number of satellite signals can be increased, thereby improving the positional accuracy. Real world experiments using a transporter that carries blocks in a shipyard have demonstrated the superiority of the proposed algorithm compared to conventional approaches.

• Smart Structures and Systems
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• v.16 no.2
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• pp.329-345
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• 2015

As commonly known, sensor errors and faulty signals may potentially lead structures in vibration to catastrophic failures. This paper presents a new approach to deal with sensor errors/faults in vibration control of structures by using the Fault detection and isolation (FDI) technique. To demonstrate the effectiveness of the approach, a space truss structure with semi-active devices such as Magneto-Rheological (MR) damper is used as an example. To address the problem, a Linear Matrix Inequality (LMI) based fixed-order $H_{\infty}$ FDI filter is introduced and designed. Modeling errors are treated as uncertainties in the FDI filter design to verify the robustness of the proposed FDI filter. Furthermore, an innovative Fuzzy Fault Tolerant Controller (FFTC) has been developed for this space truss structure model to preserve the pre-specified performance in the presence of sensor errors or faults. Simulation results have demonstrated that the proposed FDI filter is capable of detecting and isolating sensor errors/faults and actuator faults e.g., accelerometers and MR dampers, and the proposed FFTC can maintain the structural vibration suppression in faulty conditions.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.308-314
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• 2003

This paper presents a serial communication based fault diagnosis scheme for a brushless DC (BLDC) motor using parameter estimation and Bayes classifier. The presented scheme consists of a smart network board, and a fault detection and isolation (FDI) master. The smart network board is installed near the BLDC motor drive system to acquire motor data and transmit motor data to the FDI-master via serial communication channel. The FDI-master estimates BLDC motor resistance to detect symptom of faults, and assign symptom to fault type using Bayes classifier. In this scheme, since communication time delay has a serious effect on performance, periodic and fixed communication protocol is designed. Hence, the delay time is priory known. By experiment result, presented scheme was verified.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.203-207
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• 1998

In this paper, it is shown how Fuzzy Pattern Matching can be applied to diagnosis of the most common faults of Rotating Machinery. The whole diagnosis process has been divided in three steps : Fault Detection, Fault Isolation and Fault Identification, whose possible results are described by linguistic patterns. Diagnosis will consist in obtaining a set of matching indexes that indexes that express the compatibility of the fuzzified features extracted from the measured vibration signals, with the knowledge contained in the corresponding patterns.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2627-2629
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• 2000

This paper introduces the design of a reduced order observer with unknown inputs for the purpose of fault detection and isolation(FDI) in a class of bilinear systems. To Analyze the observer and FDI, this paper uses BPF(block-pulse functions). The operational properties of BPF are much applied to the analysis of bilinear systems. The integral operational matrix BPF converts the form of the differential equation into the algebraic problems.