• Journal of Power Electronics
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• v.14 no.5
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• pp.967-979
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• 2014

This paper focuses on speed and current sensor fault detection and isolation (FDI) for induction motor (IM) drives. A new, accurate and high-efficiency FDI approach is proposed so that a system can continue operating with good performance even in the presence of speed sensor faults, current sensor faults or both. The proposed three paralleled adaptive observers are capable of current sensor fault detection and localization. By using observers, the rotor flux and rotor speed can be estimated which allows the system to run under the speed sensorless vector control mode when a speed sensor fault occurs. In order to detect speed sensor faults, a threshold-based scheme is proposed. To verify the feasibility and effectiveness of the proposed FDI strategy, experiments are carried out under different conditions based on a dSPACE DS1104 induction motor drive platform.

• Smart Structures and Systems
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• v.21 no.3
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• pp.373-387
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• 2018

Semi-active isolation systems based on leverage-type stiffness control strategies have been widely studied. The main concept behind this type of system is to adjust the stiffness in the isolator to match the fundamental period of the isolated system by using a simple leverage mechanism. Although this system achieves high performance under far-field earthquakes, it is unsuitable for near-fault strong ground motion. To overcome this problem, this study considers the potential energy effect in the control law of the semi-active isolation system. The minimal energy weighting (MEW) between the potential energy and kinetic energy was first optimized through a series of numerical simulations. Two MEW algorithms, namely generic and near-fault MEW control, were then developed to efficiently reduce the structural displacement responses. To demonstrate the performance of the proposed method, a two-degree-of-freedom structure was employed as a benchmark. Numerical results indicate that the dynamic response of the structure can be effectively dampened by the proposed MEW control under both far-field and near-fault earthquakes, whereas the structural responses resulting from conventional control methods may be greater than those for the purely passive control method. Moreover, according to experimental verifications, both the generic and near-fault MEW control modes yielded promising results under impulse-like earthquakes. The practicability of the proposed control algorithm was verified.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.42-50
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• 2002

In this paper, we propose an FDI(fault detection and isolation) method using neural network-based multi-fault models to detect and isolate faults in nonlinear systems. When a change in the system occurs, the errors between the system output and the neural network nominal system output cross a threshold, and 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 the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.830-837
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• 2004

Neural networks-based fault diagnosis algorithm to detect and isolate faults in the nonlinear systems is proposed. In the proposed method, the fault is detected when the errors between the system output and the multilayer neural network-based nominal model output cross a Predetermined threshold. Once a fault in the system is detected, the system outputs are transferred to the fault classifier by nultilayer/ART2 NN (adaptive resonance theory 2 neural network) for fault isolation. 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.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• Smart Structures and Systems
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• v.18 no.2
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• pp.293-315
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• 2016

Seismic isolation is often used in protecting mission-critical structures including hospitals, data centers, telecommunication buildings, etc. Such structures typically house vibration-sensitive equipment which has to provide continued service but may fail in case sustained accelerations during earthquakes exceed threshold limit values. Thus, peak floor acceleration is one of the two main parameters that control the design of such structures while the other one is peak base displacement since the overall safety of the structure depends on the safety of the isolation system. And in case peak base displacement exceeds the design base displacement during an earthquake, rupture and/or buckling of isolators as well as bumping against stops around the seismic gap may occur. Therefore, obtaining accurate peak floor accelerations and peak base displacement is vital. However, although nominal design values for isolation system and superstructure parameters are calculated in order to meet target peak design base displacement and peak floor accelerations, their actual values may potentially deviate from these nominal design values. In this study, the sensitivity of the seismic performance of structures equipped with linear and nonlinear seismic isolation systems to the aforementioned potential deviations is assessed in the context of a benchmark shear building under different earthquake records with near-fault and far-fault characteristics. The results put forth the degree of sensitivity of peak top floor acceleration and peak base displacement to superstructure parameters including mass, stiffness, and damping and isolation system parameters including stiffness, damping, yield strength, yield displacement, and post-yield to pre-yield stiffness ratio.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.183-187
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• 2002

In this paper, the effects of encoder fault and current sensor fault in direct torque controlled induction motor drives are analyzed. On the basis of the analyzed results, a observer based fault detection and isolation scheme is presented. To verify the performance of proposed algorithms, the speed control system is designed for induction motor and evaluated by experimental study. Experimental results various type of sensor faults show the detection and isolation performance of the SFDIS and the applicability of this scheme to fault tolerant control system design.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.689-691
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• 1995

In this paper, a fault detection and isolation unit(FDIU) for a centrifugal pump system driven by DC-motor is proposed. The proposed scheme can be classified into the dedicated observer scheme(DOS). A fuzzy logic based inference engine is adopted for the isolation of each faults. Having the fuzzy inference engine, the proposed FDIU resolve a few important problems of the conventional DOSs with conventional two valued logic. The ouputs of the proposed FDIU are not "ith fault occurred" but the grade of memberships that indicate the consistency of observered symptoms(residuals) with each fault symptoms stored in the rule base. The ouputs can easily be transferred to the ranking of the fault possibilities and it will provide very useful informations in monitoring the process. The simulation results show that the FDIU has very good diagnostic ability even in the noisy environment.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.426-430
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• 1987

The reliability is the critical issue in many computer applications, particularly in process control system. In this paper we describe how to achieve the reliability improvement in controller system based multiprocessor. The proposed method is accomplished by using the techniques of fault detection, fault isolation, safe action, and fault diagnosis.

• Structural Engineering and Mechanics
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• v.43 no.4
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• pp.527-543
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• 2012

This paper presents a response spectrum analysis procedure suitable for base isolated regular buildings subjected to near fault ground motions. This procedure is based on the fact that the isolation system may be treated separately since the superstructure behaves as a rigid body on well selected isolation systems. The base isolated building is decomposed into several single-degree of freedom systems, the first one having the total weight of the building is isolated while the remainder when superposed they replicate approximately the behavior of the superstructure. The response of the isolation system is governed by a response spectrum generated for a single isolated mass. The concept of the procedure and its application for the analysis of base isolated structures is illustrated with an example. The present analysis procedure is shown to be accurate enough for the preliminary design and overcomes the limits of applicability of the conventional linear response spectrum analysis.