• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1802-1808
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• 2009

A fault detection observer with finite time convergence characteristics(FT_FDO) is proposed and applied to a fault detection isolation system for a dynamic control system. The FT_FDO is a kind of dual state-observer scheme that provides with the state estimates insensitive to a specified fault and the corresponding fault estimate. The state estimates are processed to get the residual that will be logically compared with other residuals to detect and isolate the fault of interest, and the fault estimate may be used for fault compensation. The FDIS employing the FT_FDOs can be considered to be a multiple observer schemes(MOS) in which FT_FDOs are parallelly driven to generate a set of residuals to be compared each other. Due to the finite time convergence characteristics of the FT_FDO, the predetermined detection delay can be considered in the design stage of FDIS so that any fault of interest can be detected and identified in that time. It evidently resolves a well known difficulty of threshold selection owing to the transient responses of the fault detection observers(FDO) employed in FDIS. An FDIS is constructed for instruments(2-sensor, 1-actuator) in an inverted pendulum control system, and simulations are performed to show the performance of the FDIS and fault tolerant control system.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.164-170
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• 2019

In this paper, a lane detection and tracking algorithm based on vision sensors and employing a robust filter for inner edge detection is proposed for developing a lane departure warning system (LDWS). The lateral offset value was precisely calculated by applying the proposed filter for inner edge detection in the region of interest. The proposed algorithm was subsequently compared with an existing algorithm having lateral offset-based warning alarm occurrence time, and an average error of approximately 15ms was observed. Tests were also conducted to verify whether a warning alarm is generated when a driver departs from a lane, and an average accuracy of approximately 94% was observed. Additionally, the proposed LDWS was implemented as an embedded system, mounted on a test vehicle, and was made to travel for approximately 100km for obtaining experimental results. Obtained results indicate that the average lane detection rates at day time and night time are approximately 97% and 96%, respectively. Furthermore, the processing time of the embedded system is found to be approximately 12fps.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.163-166
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• 2000

Real-time traffic detection scheme based on Computer Vision is capable of efficient traffic control using automatically computed traffic information and obstacle detection in moving automobiles. Traffic information is extracted by segmenting vehicle region from road images, in traffic detection system. In this paper, we propose the advanced segmentation of vehicle from road images using multiple local region information. Because multiple local region overlapped in the same lane is processed sequentially from small, the traffic detection error can be corrected.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.570-574
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• 1990

Detection of left ventricular boundary for the functional analysis of LV(left ventricle)is obtained using automatic boundary detection algorithm based on dynamic programming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge. detection methods. The left ventricular diastolic volume and systolic volume and systolic volume were computed after this automatic boundary detection, and these Volume data wm applied to analyze LV ejection fraction.

• Proceedings of the KOR-KST Conference
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• 1995.12a
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• pp.77-107
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• 1995

This paper documents the development of a fuzzy logic based incident detection model for urban diamond interchanges. Research in incident detection for intersections and arterials is at a very initial stage. Existing algorithms are still far from being robust in dealing with the difficulties related with data availability and the multi-dimensional nature of the incident detection problem. The purpose of this study is to develop a new real-time incident detection model for urban diamond interchanges. The development of the algorithm is based on fuzzy logic. The incident detection model developed through this research is capable of detecting lane¬blocking incidents when their effects are manifested by certain patterns of deterioration in traffic conditions and, thereby, adjustments in signal control strategies are required. The model overcomes the boundary condition problem inherent in conventional threshold-based concepts. The model captures system-wide incident effects utilizing multiple measures for more accurate and reliable detection, and serves as a component module of a real-time traffic adaptive diamond interchange control system. The model is designed to be readily scalable and expandable for larger systems of arterial streets. The prototype incident detection model was applied to an actual diamond interchange to investigate its performance. A simulation study was performed to evaluate the model's performance in terms of detection rate, false alarm rate, and mean time to detect. The model's performance was encouraging, and the fuzzy logic based approach to incident detection is promising.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1345-1360
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• 2016

In this paper, we propose a new real-time human detection under omni-directional cameras for visual surveillance purpose, based on CNN with unified detection and AGMM. Compared to CNN-based state-of-the-art object detection methods. YOLO model-based object detection method boasts of very fast object detection, but with less accuracy. The proposed method adapts the unified detecting CNN of YOLO model so as to be intensified by the additional foreground contextual information obtained from pre-stage AGMM. Increased computational time incurred by additional AGMM processing is compensated by speed-up gain obtained from utilizing 2-D input data consisting of grey-level image data and foreground context information instead of 3-D color input data. Through various experiments, it is shown that the proposed method performs better with respect to accuracy and more robust to environment changes than YOLO model-based human detection method, but with the similar processing speeds to that of YOLO model-based one. Thus, it can be successfully employed for embedded surveillance application.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.119-122
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• 2016

Feature detection is recognized as an accurate spectrum sensing approach when the information of the desired signal is partly known at the receiver. This type of detection was proposed to overcome large noise environment. Cyclostationary detection is an example of feature detection in spectrum sensing technique in cognitive radio. However, the cyclostationary process calculation requires a lot of processing time and information about the designed signals. On the other hand, energy detection spectrum sensing is widely known as a simple and compact spectrum sensing technique. However, energy detection is highly affected by large noise and lead to high detection error probability. In this paper, the combination of energy detection and cyclostationary is proposed in order to increase the accuracy and decrease the calculation and processing time. The two-layer threshold is utilized in order to reduce the complexity of computation and processing time in cyclostationary which can lead to the improved throughput of the system. The simulation result shows that the implementation of energy-based cyclostationary detector can help to improve the performance of the system while it can considerably reduce the required time for signal detection.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1880-1884
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• 2004

The wavelet packet transform has been applied for QRS detection with squaring, window integration, and impulse filter techniques to cut down the false detection of QRS complex. This real time QRS detection has been performed on Simulink and Matlab. The correct QRS detection rates have reached to 99.75% in the experiment with 15 sets of ECG data from European ST-T database which are kept in Physionet.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.221-237
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• 2015

An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and geometric mean of the higher statistical moments, and are classified by using the FCM clustering method to achieve nonlinear damage detection. A series of the measured response data, downloaded from the web site of the Los Alamos National Laboratory (LANL) USA, from a three-storey building structure considering the environmental variety as well as different nonlinear damage cases, are analyzed and used to assess the performance of the new nonlinear damage detection method. The effectiveness and robustness of the new proposed method are finally analyzed and concluded.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.9
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• pp.445-452
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• 2001

Two switching signal patterns are proposed to prevent short circuit of PWM ac choppers. The voltage detection method and the current detection method are proposed to execute two switching signal patterns. In the voltage detection method, the dead-time has to be inserted to the switching signals after polarity of input voltage is checked by voltage transducer at input side. In the current detection method, the direction of load current is checked by current transducer at output side, and the dead-time delay is not considered. Controlling circuit built by current detection method is simple because the dead-time delay is considered. The experimental results are presented to prevent short circuit of ac chopper safely.