• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.221-226
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• 2018

Special-purposed vehicles are customized according to the user's requirements. When these vehicles are out of oder, they are costly and time consuming to repair. In order to solve these problems, we want to remotely check whether the vehicle is abnormal and remotely identify the fault area, thereby shortening the repair cost and the repair period. In this study, the faulty part of the electric control part is automatically identified, and it is immediately grasped through the user's mobile phone application and an instant fault code is notified to the car manufacturer for quick and smooth fault repair. In order to realize this, we want to build a system that uses the technology of IoT to determine the fault area according to the items required in the field of the special purpose vehicle and notify the manufacturer of the fault on its own.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.1
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• pp.108-118
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• 1997

The heterarchical structure provides a more attractive solution to the conventional hierarchical structure as the density and level of distrubution of computing resources in manufacturing system expands. Tracing the evolution of control structures for automated manufacturing systems, this paper discusses the design principles for heterarchical system to reduce complexity, increase extendability, flexible configurability and suggests a good example of real-time adaptation using the concept of intelligent agent of manufac- turing entities and fault diagmosis system.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.82-90
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• 1995

This paper pressents a condition-based maintenance (CBM) method through bibration analysis. The well known frequency analysis is employed for performing machine fault diagnosis. The statistical control chart is also applied for analyzing the trend of the bearing wear. Vibration sensors are attached to prototype machine and signals are continuously monitored. The sampled data are utilized to evaluate how well the fast fourier transform(FFT) and the statistical control chart techniques could be used to identify defects of machine and to analyze the machine degradation. Experimental results show that the propowed approach could classify every mal-function and could be utilized for real machine diagnosis system.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.281-286
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• 1992

This paper describes a duplexed process control system for a boiler-turbine system of power plant, which is composed of supervisor, controller, and simulater subsystems. Its embeded POL(Problem oriented language) as a structured control language enables this system to do a real-time distributed control and fault diagnosis by simple programming with the actual implementation of advanced control algorithms such as PID autotuning and GPC, etc, the performance of overall system has been greatly enhanced.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.874-882
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• 2003

The condition assessment of engineering systems has increased in importance because the manpower needed to operate and supervise various plants has been reduced. Especially, induction motors are at the core of most engineering processes, and there is an indispensable need to monitor their health and performance. So detection and diagnosis of motor faults is a base to improve efficiency of the industrial plant. In this paper, a model-based fault detection system is developed for induction motors, using steady state vibration signals. Early various fault detection systems using vibration signals are a trivial method and those methods are prone to have missed fault or false alarms. The suggested motor fault detection system was developed using a model-based reference value. The stationary signal had been extracted from the non-stationary signal using a data segmentation method. The signal processing method applied in this research is FFT. A reference model with spectra signal is developed and then the residuals of the vibration signal are generated. The ratio of RMS values of vibration residuals is proposed as a fault indicator for detecting faults. The developed fault detection system is tested on 800 hp motor and it is shown to be effective for detecting faults in the air-gap eccentricities and broken rotor bars. The suggested system is shown to be effective for reducing missed faults and false alarms. Moreover, the suggested system has advantages in the automation of fault detection algorithms in a random signal system, and the reference model is not complicated.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.103-109
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• 2016

Corrective control for asynchronous sequential machines is a novel automatic control theory that compensates illegal behavior or adverse effects of faults in the operation of existent asynchronous machines. In this paper, we propose a scheme of diagnosing and tolerating faults occurring to input channels of corrective control systems. The corrective controller can detect faults occurring in the input channel to the controlled machine, whereas those faults happening in the external input channel cannot be detected. The proposed scheme involves an outer operator which, upon receiving the state feedback, diagnoses a fault and sends an appropriate command signal to the controller for tolerating faults in the external input channel.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.10
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• pp.53-66
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• 1994

In this paper, a fuzzy expert system is developed for fault diagnoisis of a drum-type boiler system in fossil power plants. The develped fuzzy espert system is composed of knowledge base, fuzzification module, knowledge base process module, knowledge base management module, inference module, and linguistic approximation module. The main objective of the fuzzy expert system is to check the states of the system including the drum level and detect faults such as the feedwater flow sensor fault, feedwater flow control valve fault, and water wall bube rupture. The fuzzy expert system diagnoses faults using process values, manipulated values, and knowledge base which is built via interviews and questionaries with the experts on the plant operations. Finally, the validity of the developed fuzzy expert system is shown via experiments using the digital simulator for boiler system is Seoul Power Plant Unit 4.

• Proceedings of the KIPE Conference
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• 2004.07b
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• pp.533-536
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• 2004

In this paper, a novel compensation scheme for ac-dc pwm converters under switching device fault status has been proposed, along with an effective diagnosis method. With the proposed scheme, the pwm converter can be properly operated even when one of the switching devices of the converter is out of control, so that it may ensure the performance and reliability of pwm converters to be increased. The developed scheme is explained in theoretically and the validity is verified by the informative simulation and experimental results in detail.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.836-841
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• 1987

Many kinds of conditioning monitoring technique have been studied, so this study has investigated the possibility of checking the trend in the fault diagnosis of ball bearing, one of the elements of rotating machine, by applying the cepstral analysis method using the adaptive noise cancelling (ANC) method. And computer simulation is conducted in oder to identify obviously the physical meaning of ANC. The optimal adaptation gain in adaptive filter is estimated, the performance of ANC according to the change of the signal to noise ratio and convergence of LMS algorithm is considered by simulation. It is verified that cepstral analysis using ANC method is more effective than the conventional cepstral analysis method in bearing fault diagnosis.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.665-667
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• 1999

An adaptive algorithm is presented for diagnosis of actuator faults. The concept of unknown input decoupling is combined with an adaptive observer, leading to an adaptive diagnostic observer, which has the robustness property in the presence of an unmeasurable term such as uncertainties. The observation error equation for the adaptive diagnostic observer does not depend on the effect of uncertainties and used to construct an adaptive diagnostic algorithm that provides the estimates of the gains of actuators, which can be obtained directly via the use of the augmented error technique. The simulation results indicate that the proposed algorithm is more realistic in the sense that better robustness properties can be assured without knowledge about uncertainties and is potentially useful in the development of a fault tolerant control system.