• Smart Media Journal
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• v.6 no.2
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• pp.33-41
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• 2017

Railway point machines act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Since point failure caused by the aging effect can significantly affect railway operations with potentially disastrous consequences, replacement detection of point machine at an appropriate time is critical. In this paper, we propose a replacement condition detection method of point machine in railway condition monitoring systems using electrical current signals, after analyzing and relabeling domestic in-field replacement data by means of OLAP(On-Line Analytical Processing) operations in the multidimensional data cube into "does-not-need-to-be replaced" and "needs-to-be-replaced" data. The system enables extracting suitable feature vectors from the incoming electrical current signals by DWT(Discrete Wavelet Transform) with reduced feature dimensions using PCA(Principal Components Analysis), and employs SVM(Support Vector Machine) for the real-time replacement detection of point machine. Experimental results with in-field replacement data including points anomalies show that the system could detect the replacement conditions of railway point machines with accuracy exceeding 98%.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.231-239
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• 2018

In this paper, we propose a vanishing point detection method using multiple initial vanishing points. Vanishing points are important geometric information that is used for reconstructing 3D structures. Three vanishing points are detected for indoor scenes. In the previous work, it could be inaccurate to detect only one initial vanishing point, because initial vanishing point getting most highest sum of voting could be deferent from the best initial vanishing point. Therefore the method which sets multiple initial vanishing point and detects a best vanishing point from them gives us preparation for the prior case. Also in this paper, we propose a adjusting vanishing point method by postprocessing of detected vanishing points. We could detect more accurate vanishing point by using postprocessing. Experimental results show that the accuracy of the vanishing point detection is about 1~2% higher than that of the existing method through the proposed method and the performance is improved accordingly.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.433-440
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• 2016

Railway point machines act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Since point failure can significantly affect railway operations with potentially disastrous consequences, early stress detection of point machine is critical for monitoring and managing the condition of rail infrastructure. In this paper, we propose a stress detection method for point machine in railway condition monitoring systems using sound data. The system enables extracting sound feature vector subset from audio data with reduced feature dimensions using feature subset selection, and employs support vector machines (SVMs) for early detection of stress anomalies. Experimental results show that the system enables cost-effective detection of stress using a low-cost microphone, with accuracy exceeding 98%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1690-1696
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• 1999

Video sequence should be hierachically classified for the content-based retrieval. Cut detection algorithm is an essential process to classify shots. It is generally difficult for cut detection algorithms to detect cut points since a current frame is compared with a previous one, because movement of camera or object made adrupt scene change. We reduce ratio of failed cut detection so that compare the difference between frames of predicted cut point and their neighbors. In this paper, first we get predicted cut point, then we judge that the predicted cut point is true point or not. And we extracted DC images in MPEG video sequence for comparison. As a result of experiments. We confirmed that the cut detection ratio of the proposed algorithm is higher than of any other algorithms.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.1-8
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• 2008

This paper presents a real-time algorithm for collision detection, collision avoidance and guidance. Three-dimensional point-mass aircraft models are used. For collision detection, conflict probability is calculated by using the Monte-Carlo Simulation. Time at the closest point of approach(CPA) and distance at CPA are needed to determine the collision probability, being compared to certain threshold values. For collision avoidance, one of possible maneuver options is chosen to minimize the collision probability. For guidance to a designated way-point, proportional navigation guidance law is used. Two scenarios on encounter situation are studied to demonstrate the performance of proposed algorithm.

• Information and Communications Magazine
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• v.10 no.10
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• pp.22-29
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• 1993

This paper describes development of a real-time voice recognition dialing system which can recognize around one hundred word vocabularies in speaker independent mode. The voice recognition algorithm is implemented on a DSP board with a telephone interface plugged in an IBM PC AT/486. In the DSP board, procedures for feature extraction, vector quantization(VQ), and end-point detection are performed simultaneously in every 10msec frame interval to satisfy real-time constraints after the word starting point detection. In addition, we optimize the VQ codebook size and the end-point detection procedure to reduce recognition time and memory requirement. The demonstration system is being displayed in MOBILAB of Korea Mobile Telecom at the Taejon EXPO '93.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.23-28
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• 2006

Pitch period that is a important factor in speech signal processing is used in various applications such as speech recognition, speaker identification, speech analysis and synthesis. So many pitch detection algorithms have been studied until now. AMDF which is one of pitch period detection algorithms chooses the time interval from valley point to valley point as pitch period. In selection of valley point to detect pitch period, complexity of the algorithm is increased. So in this paper we proposed the simple algorithm using rotation transform of AMDF that detects global minimum valley point as pitch period of speech signal and compared it with existing methods through simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.515-519
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• 2005

Pitch period that is a important factor in speech signal processing is used in various applications such as speech recognition, speaker identification, speech analysis and synthesis. So many pitch detection algoritms have been studied until now. AMDF which is one of pitch period detection algorithms chooses the time interval from valley point to valley point as pitch period. In selection of valley point to detect pitch period, complexity of the algoritm is increased. So in this paper we proposed the simple algorithm using modified AMDF that detects global minimum valley point as pitch period of speech signal and compared existing methods with it through simulation.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.5
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• pp.449-452
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• 2016

This paper presents a simplified analysis on the rotor position detection error in sensorless interior permanent magnet brushless DC motor (BLDCM) drives, wherein terminal voltage sensing based on the back-electromotive force (back-EMF) zero-crossing point detecting circuitry is employed. The effect of a rotor saliency on the back-EMF's zero-crossing point detection is analyzed using the extended EMF-based voltage equation of the interior permanent BLDCM in a stationary reference frame, and thus the overall analysis is considerably simplified compared to the conventional one. Simulation results are provided to verify the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1360-1363
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• 1996

EPD(End Point Detection) is used to decide etching degree of layer which must be removed at wafer etching process in plasma etching process which is one of the most important process in semiconductor manufacturing. In this thesis, the method which detects malfunction of etching process in real-time will be discussed. Several EPD signal traces are collected in normal plasma etching condition and used as reference EPD signal traces. Critical points can be detected by applying differentiation and zero-crossing techniques to reference EPD signal. Mean and standard deviation of critical parameters which is memorized from reference EPD signal are calculated and these determine the lower and higher limit of control chart. And by applying statical control chart to EPD signals which are collected in real etching process malfunctions of process are detected in real-time. By means of applying this method to the real etching process we prove our method can accurately detect the malfunction of etching process and can compensate disadvantage of current industrial method.