• 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%.

• Smart Media Journal
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• v.6 no.4
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• pp.9-16
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• 2017

The railway point machine is an especially important component that changes the traveling direction of a train. Failure of the point machine may cause a serious railway accident. Therefore, early detection of failures is important for the management of railway condition monitoring systems. In this paper, we propose a noise-robust anomaly detection method in railway condition monitoring systems using sound data. First, we extract feature vectors from the spectrogram image of sound signals and convert it into modulation feature to ensure robust performance, and lastly, use the support vector machine (SVM) as an early anomaly detector of railway point machines. By the experimental results, we confirmed that the proposed method could detect the anomaly conditions of railway point machines with acceptable accuracy even under noisy conditions.

• 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 Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1821-1829
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• 2017

A point machine requires lots of time and attention in terms of maintenance, since it causes 40% of failures among the railway signaling devices. The senescence of the point machine critically matters to the overall turnout system. In this paper, we analyzed the aging characteristics of the point machine by using the switching current of the point machine. The analysis is done based on the switching current measurements of the point machines deployed in the Sehwa outdoor test site and the Korail Kyongbu line. It is expected that the analysis result can be utilized for real-time diagnosis in the aspect of the maintenance of the point machines and predicting abnormal operations.

• Journal of the Korean Society for Railway
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• v.18 no.4
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• pp.335-343
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• 2015

The role of the turnouts installed on the points of railway branches and intersections is to safely switch the directions of trains. In case of abnormal forces applied to the turnouts due to extreme operating conditions, it is difficult in the current system to conduct accurate diagnosis and measuring. Moreover, the existing measurement devices for turnout switching power are mostly based on foreign technologies, which provide only limited information on the switching power; this information is insufficient for effective monitoring and maintenance. In this paper, through an analysis of the characteristics of the switching and locking function, the problems in turnout power measurements of current electrical point machines in Korea are examined. And based on the results, a new sensor-based method for measuring switching power is proposed.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.603-609
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• 2008

Nowadays, double-system of TFM(Track-side Functional Modules) developed instead of single-system in use of high speed line to acquisition more availability. Safety Law for Railroad recommend to quality certification of development and general railway machines. It is important to select metrics which form the bases for testing software products. A number of package software development part do not open source cords, so testing external characteristic vectors having relationship with metrics. In this paper, review the process for the TFM Point Modules, Universal Modules and Switchers, think about the test methode of circuit boards output performance by using TFM tester and Simulators.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.40-45
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• 2014

This paper suggests the optimal generation dispatch algorithm for ensuring voltage stability margin considering high wind energy injection. Generally, with wind generation being installed into the power system, we would have to consider several factors such as the voltage stability margin because wind turbine generators are mostly induction machines. If the proportion of wind generation increases in the power system increases this would affect the overall stability of the system including the voltage stability. This paper considers a specific system that is composed of two areas: area 1 and area 2. It is assumed that generation cost in area 1 is relatively higher than that in area 2. From an economic point of view generation in area 1 should be decreased, however, in the stability point of view the generation in area 2 should be decreased. Since the power system is a nonlinear system, it is very difficult to find the optimal solution and the genetic algorithm is adopted to solve the objective function that is composed of a cost function and a function concerned with voltage stability constraints. For the simulations, the New England system was selected. The algorithm is implemented and Python 2.5.