• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.4
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• pp.330-335
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• 2013

Since real-time monitoring system like a fault early detection has been very important, infrared thermography technique as a new diagnosis method was proposed. This study is focused on the damage detection and temperature characteristic analysis of ball bearing using the non-destructive infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with the frequency data of the existing. As results, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally it was confirmed that the infrared technique was useful for real-time detection of the bearing damages.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.11
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• pp.1091-1100
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• 2004

This paper presents an approach for the monitoring and detection of faults in induction machine by using data fusion technique and Dempster-Shafer theory Features are extracted from motor stator current and vibration signals. Neural network is trained and Hosted by the selected features of the measured data. The fusion of classification results from vibration and current classifiers increases the diagnostic accuracy. The efficiency of the proposed system is demonstrated by detecting motor electric and mechanical faults originated from the induction motors. The results of the test confirm that the proposed system has potential for real time application.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.7
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• pp.587-595
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• 2006

A system operating algorithm was developed for the effective operation of a multi-type air-conditioning system. The system operating algorithm includes control algorithms for a safety mode, an initial operating mode, a stabilization mode, a fault diagnosis mode, an efficiency mode, and a tracking mode. Various tests were performed to show the effectiveness of these algorithms. Tests showed good results for the operation of a multi-type air-conditioning system. Therefore, these algorithms developed for this study may be used for the effective control of a multi-type air-conditioning system.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.615-621
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• 2014

Power transformer is one of the most important equipments in electrical power system. The detection of certain gases generated in transformer is the first indication of a malfunction that may lead to failure if not detected. Dissolved gas analysis (DGA) of transformer oil has been one of the most reliable techniques to detect the incipient faults. Many conventional DGA methods have been developed to interpret DGA results obtained from gas chromatography. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when DGA results falls outside conventional method codes or when more than one fault exist in transformer. To overcome these limitations, fuzzy inference system (FIS) is proposed. 250 different cases are used to test the accuracy of various DGA methods in interpreting the transformer condition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.175-189
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• 2023

Fault detection and diagnosis (FDI) algorithms are actively being researched for ensuring the integrity and reliability of environment perception sensors in autonomous vehicles. In this paper, a fault detection algorithm based on a multi-sensor perception system composed of radar, camera, and lidar is proposed to guarantee the safety of an autonomous vehicle's perception system. The algorithm utilizes reference generation filters and residual generation filters based on finite impulse response (FIR) filter estimates. By analyzing the residuals generated from the filtered sensor observations and the estimated state errors of individual objects, the algorithm detects faults in the environment perception sensors. The proposed algorithm was evaluated by comparing its performance with a Kalman filter-based algorithm through numerical simulations in a virtual environment. This research could help to ensure the safety and reliability of autonomous vehicles and to enhance the integrity of their environment perception sensors.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.769-774
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• 2006

In this paper, we discuss the problem of non-mutual detectability using the invariant zero. We propose a representation method for excess spaces by linear equation based on the Rosenbrock system matrix. As an alternative to the system enlargement method proposed by White[1], we propose an appropriate form of an enlarged system to make a set of faults mutually detectable by assigning sufficient geometric multiplicity of invariant zeros. We show the equivalence between the two methods and a necessary condition for the system enlargement in terms of the geometric and algebraic multiplicities of invariant zeros.

• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.28-33
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• 2015

Three phase heaters in 7 buildings of 2 sites were examined for precise diagnosis. The sample size was 626. Precise examinations of current and the heater wiring status revealed contact failures and arcs in equipments that had CUF larger than 10%. Contact failures and arcs may cause electrical fire. Therefore, the correlation between the CUF and the imperfections in heater equipment and its wiring was analyzed for three phase heaters. In addition, the protection devices used for detection of heater imperfections were found to be unsuitable for the purpose. Current status of the protection devices was analyzed, and suggestions for improvements were made for new standards of the protection device selection.

• Journal of the Korean Society of Industry Convergence
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• v.14 no.3
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• pp.95-100
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• 2011

The modern society longing for the convenience of up-to-date technology, there are attempts of miniaturization and high reliance of power equipments in the effectiveness aspect of urban area's usage of space while requiring more electrical energy than now. Consequently, paper used to the Neral Network for a forcasting conservation system. A neral network is powerful asta modeling tool that is able to capture and represent complex input/output relationships. The true power and advantage of neral networks lies in their ability to learn these relationships directly from the data being modeled. Traditional linear models are simply inadequate when it comes to modeling data that contains non-linear characteristics. Form results of this study, the Neral Network is will play an important role for insulation diagnosis system of real site GIS and power eqipment using $SF_6$ gas.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.147-154
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• 1998

As technical systems in building are being developed, the processes and systems get more difficult for the average operator to understand. When operating a complex facility, it is beneficial in equipment management to provide the operator with tools which can help in dicision making for recovery from a failure of the system. The main object of the study is to develop real-time automatic fault detection and diagnosis system for optimal operation of IBS building.

• Journal of KSNVE
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• v.10 no.6
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• pp.985-990
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• 2000

The signals that can be obtained from rotating machines often convey the information of machine. For example, if the machine under investigation has faults, then these signals often have pulse signals, embedded in noise. Therefore the ability to detect the fault signal in noise is major concern of fault diagnosis of rotating machine, In this paper, minimum variance cepstrum (MV cepstrum) . which can easily detect impulse in noise, has been applied to detect the type of faults of ball bearing system. To test the performance of this technique. various experiments have been performed for ball bearing elements that have man made faults. Results show that minimum variance cepstrum can easily detect the periodicity due to faults and also shows the pattern of excitation by the faults.