• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.241-248
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• 2009

This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis of the proposed estimation to demonstrate its convergence property by using statistical convergence and system stability theories. We apply our fault detection approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.839-844
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• 2009

In this paper, a real-time eye tracking method using fast face detection is proposed. Most of the current eye tracking systems have operational limitations due to sensors, complicated backgrounds, and uneven lighting condition. It also suffers from slow response time which is not proper for a real-time application. The tracking performance is low under complicated background and uneven lighting condition. The proposed algorithm detects face region from acquired image using elliptic Hough transform followed by eye detection within the detected face region using Haar-like features. In order to reduce the computation time in tracking eyes, the algorithm predicts next frame search region from the information obtained in the current frame. Experiments through simulation show good performance of the proposed method under various environments.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.49-54
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• 2016

In this paper, the confirmation method of target detection for the vehicle mounted metal detector (MD) has been described. The vehicle mounted MD with the arrayed 6 coils to detect the width of 2.4 m was demonstrated. It is important and necessary to inform the location of the objects detected by the MD. The confirmation method of target detection was verified by using the MD GUI and the analysis of the receive signal processing. The receive signal processing is performed by comparing the threshold and the difference of the signal calibrated at initial location and the signal detected at present location.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1954-1971
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• 2017

In this work, first, a multiuser detection (MUD) algorithm based on component-level soft interference cancellation and linear minimum mean square error (CLSIC-LMMSE) is proposed, which can enhance the bit error ratio (BER) performance of the traditional SIC-LMMSE-based MUD by mitigating error propagation. Second, for non-binary low density parity check (NB-LDPC) coded high-order modulation systems, when the proposed algorithm is integrated with partial mapping, the receiver with iterative detection and decoding (IDD) achieves not only better BER performance but also significantly computational complexity reduction over the traditional SIC-LMMSE-based IDD scheme. Extrinsic information transfer chart (EXIT) analysis and numerical simulations are both used to support the conclusions.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.96.3-96
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• 2002

A scheme of clarifying fault feature in the residual is given for model-based fault detection and diagnosis of control systems. It is based on the residual generation using a robust filter and the noise suppresion in test statistics of the residual by multi-scale discrete wavelet transform. By clarifying the fault feature in the residual, the difficulties of existing model based approaches via adopting a threshold can be overcomed and it has advantage of taking the false alarm and missed detection into acount at the same time, which can make the fault detection and diagnosis easy and correct. To show the effectiveness of our approach, the simulation results are illustrated for a linear syste...

• Journal of Communications and Networks
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• v.16 no.6
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• pp.600-612
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• 2014

In this paper, we consider the problem of spectrum sensing for advanced television systems committee (ATSC) digital television (DTV) signal detection. To exploit the cyclostationarity of the ATSC DTV signals, we employ spectral correlation density (SCD) as the decision statistic and propose an optimal detection algorithm. The major difficulty is in obtaining the probability distribution functions of the SCD. To overcome the difficulty, we probabilistically model the pilot frequency location and employ Gaussian approximation for the SCD distribution. Then, we obtain a practically implementable detection algorithm that outperforms the industry leading systems by 2-3 dB. We also propose various techniques that greatly reduce the system complexity with performance degradation by only a few tenths of decibels. Finally, we show how robust the system is to the estimation errors of the noise power spectral density level and the probability distribution of the pilot frequency location.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.3
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• pp.173-180
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• 2016

Fault detection and diagnosis is a task to monitor the occurrence of faults and pinpoint the exact location of faults in the system. Fault detection and diagnosis is gaining importance in development of efficient, advanced and safe industrial systems. Three phase inverter is one of the most common and excessively used power electronic system in industries. A fault diagnosis system is essential for safe and efficient usage of these inverters. This paper presents a fault detection technique and fault classification algorithm. A new feature extraction approach is proposed by using three-phase load current in three-dimensional space and neural network is used to diagnose the fault. Neural network is responsible of pinpointing the fault location. Proposed method and experiment results are presented in detail.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.11a
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• pp.59-65
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• 2002

Recently, lots of researchers work focused on the intrusion detection system. Pattern matching technique is commonly used to detect the intrusion in the system, However, the method requires a lot of time to match between systems rule and inputted packet data. This paper proposes a new intrusion detection system based on the pattern matching technique. Proposed system reduces the required time for pattern matching by using classified system rule. The classified rule is implemented with a general tree for efficient pattern matching. Thereby, proposed system could perform network intrusion detection efficiently.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1106-1116
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• 2011

LINS (Laser Inertial Navigation System) consists of RLG (Ring Laser Gyroscopes)/accelerometers and provides real-time navigation information to the target system. Therefore it is very important to make a decision in the real time whether LINS is in the normal operation or not. That is called a fault detection method. In this paper, we propose the fault detection method of LINS based on the overlapping model. We also show that the fault detection probability is increased through overlapping the hardware model and the software model. It is verified through the long-term operation and RAM (Reliability Availability Maintainability) analysis of LINS that the fault detection method proposed in this paper is able to detect about 97% of probable system failures.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.699-704
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• 2016

In this paper, we propose a development method for a drowsiness detection system using retinex theory and edge information for vehicle safety. Detection of a drowsy state of a driver is very important because the drowsiness of driver is often the main cause of many car accidents. After acquiring an image of the entire face, we executed the pre-process step using the retinex theory. We then applied a technique for the detection of the white pixels using edge information. Experimental results showed that the proposed method improved the accuracy of detecting drowsiness to nearly 98%, and can be used to prevent a car accident caused by the driver's drowsiness.