• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.125.4-125
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• 2001

The problem of recongurable ight control is investigated, focusing on model reference adaptive control(MRAC) through imprecise fault diagnosis. The method integrates the fault detection and isolation(FDI) scheme with the model reference adaptive control, and can be implemented on-line and in real-time. The algorithm can cope with the fast varying parameters. The Simulation results demonstrate the ability of reconguration to maintain the stability and acceptable performance after a failure.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.841-842
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• 1988

For determination of black-out area and restoration area by an expert system for fault section estimation and power system restoration using information from circuit breakers, it is necessary that the recognition of system isolation state and a method of finding the change of system isolation state by the state transition of breakers in isolated system. This paper presents a method of resolving the above problem by rule-based approach.

• Earthquakes and Structures
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• v.13 no.3
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• pp.267-277
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• 2017

Base-isolation is now being adopted as a retrofitting strategy to improve seismic behaviour of reinforced concrete (r.c.) framed structures subjected to far-fault earthquakes. However, the increase in deformability of a base-isolated framed building may lead to amplification in the structural response under the long-duration horizontal pulses of high-magnitude near-fault earthquakes, which can become critical once the strength level of a fire-weakened r.c. superstructure is reduced. The aim of the present work is to investigate the nonlinear seismic response of fire-damaged r.c. framed structures retrofitted by base-isolation. For this purpose, a five-storey r.c. framed building primarily designed (as fixed-base) in compliance with a former Italian seismic code for a medium-risk zone, is to be retrofitted by the insertion of elastomeric bearings to meet the requirements of the current Italian code in a high-risk seismic zone. The nonlinear seismic response of the original (fixed-base) and retrofitted (base-isolated) test structures in a no fire situation are compared with those in the event of fire in the superstructure, where parametric temperature-time curves are defined at the first level, the first two and the upper levels. A lumped plasticity model describes the inelastic behaviour of the fire-damaged r.c. frame members, while a nonlinear force-displacement law is adopted for the elastomeric bearings. The average root-mean-square deviation of the observed spectrum from the target design spectrum together with a suitable intensity measure are chosen to select and scale near- and far-fault earthquakes on the basis of the design hypotheses adopted.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.886-889
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• 2017

An active Fault Tolerant Model Predictive Control (FTMPC) using Fuzzy scheduler is developed. Fault tolerant Control (FTC) system stages are broadly classified into two namely Fault Detection and Isolation (FDI) and fault accommodation. Basically, the faults are identified by means of state estimation techniques. Then using the decision based approach it is isolated. This is usually performed using soft computing techniques. Fuzzy Decision Making (FDM) system classifies the faults. After identification and classification of the faults, the model is selected by using the information obtained from FDI. Then this model is fed into FTC in the form of MPC scheme by Takagi-Sugeno Fuzzy scheduler. The Fault tolerance is performed by switching the appropriate model for each identified faults. Thus by incorporating the fuzzy scheduled based FTC it becomes more efficient. The system will be thereafter able to detect the faults, isolate it and also able to accommodate the faults in the sensors and actuators of the Continuous Stirred Tank Reactor (CSTR) process while the conventional MPC does not have the ability to perform it.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2198-2202
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• 2005

In this paper we have presented a condition monitoring method of check valve using neural network. The acoustic emission sensor was used to acquire the condition signals of check valve in direct vessel injection (DVI) test loop. The acquired sensor signal pass through a signal conditioning which are consisted of steps; rejection of background noise, amplification, analogue to digital conversion, extract of feature points. The extracted feature points which represent the condition of check valve was utilized input values of fault diagnosis algorithms using pre-learned neural network. The fault diagnosis algorithm proceeds fault detection, fault isolation and fault identification within limited ranges. The developed algorithm enables timely diagnosis of failure of check valve’s degradation and service aging so that maintenance and replacement could be preformed prior to loss of the safety function. The overall process has been experimented and the results are given to show its effectiveness.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.8
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• pp.906-915
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• 1988

The reliability enhancement is the critical issue in many computer applications, particulary in process control system. In this paper we describe how to achieve the reliability improvement in control system which is based on multiprocessors. The proposed method is accomplished by using the techniques of fault detection which composed by internal and external fault detections, fault isolation for removing the fault propagation, safety action for driving safe input, and fault diagnosis. This approach is experimented and asopted in boiler backup control system constructed by VMEbus system, CPU boards, graphic system, and other interface boards with UNIX operating system.

• 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 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 the Korean Society for Aeronautical & Space Sciences
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• v.49 no.4
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• pp.311-320
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• 2021

A study is performed for the real time fault diagnosis during operation and health estimation relating to performance deterioration in a turbojet engine used for an unmanned air vehicle. For this study the real time dynamic model is derived from the transient thermodynamic gas path analysis. For real fault conditions which are manipulated for the simulation, the detection techniques are applied such as Kalman filter and probabilistic decision-making approach based on statistical hypothesis test. Thereby the effectiveness is verified by showing good fault detection and isolation performances. For the health estimation with measurement parameters, it shows using an assumed performance degradation that the method by adaptive Kalman filter is feasible in practice for a condition based diagnosis and maintenance.

• Smart Structures and Systems
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• v.16 no.4
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• pp.701-723
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• 2015

Friction isolators are one of the most important types of bearings used to mitigate damages of earthquakes. The adaptive behavior of these isolators allows them to achieve multiple levels of performances and predictable seismic behavior during different earthquake hazard levels. There are three main types of friction isolators. The first generation with one sliding surface is known as Friction Pendulum System (FPS) isolators. The double concave friction pendulum (DCFP) with two sliding surfaces is an advanced form of FPS, and the third one, with fully adaptive behavior, is named as triple concave friction pendulum (TCFP). The current study has been conducted to investigate and compare seismic responses of these three types of isolators. The structure is idealized as a two-dimensional single degree of freedom (SDOF) resting on isolators. The coupled differential equations of motion are derived and solved using state space formulation. Seismic responses of isolated structures using each one of these isolators are investigated under seven near fault earthquake motions. The peak values of bearing displacement and base shear are studied employing the variation of essential parameters such as superstructure period, effective isolation period and effective damping of isolator. The results demonstrate a more efficient seismic behavior of TCFP isolator comparing to the other types of isolators. This efficiency depends on the selected effective isolation period as well as effective isolation damping. The investigation shows that increasing the effective isolation period or decreasing the effective isolation damping improves the seismic behavior of TCFP compared to the other isolators. The maximum difference in seismic responses, the base shear and the bearing displacement, for the TCFP isolator are calculated 26.8 and 13.4 percent less than the DCFP and FPS in effective isolation damping equal to10%, respectively.