• Journal of Sensor Science and Technology
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• v.26 no.6
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• pp.432-437
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• 2017

As 4.0 industry has been developed, research on a self-driving car technology and related parts of an automobile has been highly investigated recently. Particularly, a TAS(Torque Angle Sensor) module on steering wheel system has been considered as a key technology because of its precise angle, torque detection and high speed signal processing. The environmental assessment is generally required on the TAS module to examine high resolution of angle/torque detection. In the case of existing TAS module, angle detection errors has been occurred by back-lash on main and sub gear in addition to complicated structure caused by gears. In this paper, a structure of the TAS module, which minimizes the numbers of components and angle detection errors on the module compared with the existing TAS module, for vehicle steering system based on a Multi-track Encoder has been proposed. Also, angle detection signal processing board, and key technology of the TAS module were fabricated and evaluated. As a result of the experiments, we confirmed an excellent performance of the fabricated signal processing board for angle detection and an applicability of the fabricated angle detection board on the TAS module of vehicles by the environmental assessment an automobile standard.

• Journal of Power Electronics
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• v.10 no.3
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• pp.300-305
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• 2010

This paper presents a two Hall sensor method for rotor angle detection in permanent magnet synchronous motors (PMSM). To minimize the implementation complexity, the system is designed to measure the edge field of permanent magnet pieces. However, there are nonlinearities in the measured values of the edge field. In this work, an angle correction algorithm is proposed, and the improvements in accuracy are verified through experiments. Finally, a field orientation controller is constructed with the proposed angle detection algorithm.

• ETRI Journal
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• v.33 no.3
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• pp.415-422
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• 2011

In this paper, we present a novel vision-based method of recognizing finger actions for use in electronic appliance interfaces. Human skin is first detected by color and consecutive motion information. Then, fingertips are detected by a novel scale-invariant angle detection based on a variable k-cosine. Fingertip tracking is implemented by detected region-based tracking. By analyzing the contour of the tracked fingertip, fingertip parameters, such as position, thickness, and direction, are calculated. Finger actions, such as moving, clicking, and pointing, are recognized by analyzing these fingertip parameters. Experimental results show that the proposed angle detection can correctly detect fingertips, and that the recognized actions can be used for the interface with electronic appliances.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.411-419
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• 2012

This paper proposes a new FDI(Fault Detection and Isolation) method, which is called EPSA(Extended Parity Space Approach). This method is particularly suitable for fault detection and isolation of the system with one faulty sensor or two faulty sensors. In the system with two faulty sensors, the fault detection and isolation probability may be decreased when two faults are occurred between the sensors related to the large fault direction angle. Nonetheless, the previously suggested FDI methods to treat the two-faults problem do not consider the effect of the large fault direction angle. In order to solve this problem, this paper analyzes the effect of the large fault direction angle and proposes how to increase the fault detection and isolation probability. For the increase the detection probability, this paper additionally considers the fault type that is not detected because of the cancellation of the fault biases by the large fault direction angle. Also for the increase the isolation probability, this paper suggests the additional isolation procedure in case of two-faults. EPSA helps that the user can know the exact fault situation. The proposed FDI method is verified through Monte Carlo simulation.

• Smart Structures and Systems
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• v.28 no.6
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• pp.811-825
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• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.62-65
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• 2000

In this paper we propose skewed angle detection methods for images that contain text that is not aligned horizontally. In most images text areas are aligned along the horizontal axis, however there are many occasions when the text may be at a skewed angle (denoted by 0 < ${\theta}\;{\leq}\;{\pi}$). In the work described, we adapt the Hough transform, Shadow and Threshold Projection methods to detect the skewed angle of text in an input image using the orthogonal angle view property. The results of this method are a primary text skewed angle, which allows us to rotate the original input image into an image with horizontally aligned text. This utilizes document image processing prior to the recognition stage.

• Bulletin of the Korean Chemical Society
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• v.26 no.9
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• pp.1344-1346
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• 2005

We report microcavity effect of top emission organic light-emitting diodes (OLEDs) by using Al cathode and anode, which are feasible for not only top emission EL and angle dependant effects but facile evaporation process without ion sputtering. The device in case of $Alq_3$ green emission showed largely shifted EL maximum wavelength as 650 nm maximum emission. It was also observed that detection angle causes different EL maximum wavelength and different CIE values in R, G, B color emission. As a result, the green device using $Alq_3$ emission showed 650 nm emission ($0^{\circ}$) to 576 nm emission ($90^{\circ}$) as detection angle changed. We believe that these phenomena can be also explained with microcavity effect which depends on the different length of light path caused by detection angle.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.7
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• pp.10-16
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• 2012

In this paper, we tried to realize a next generation MILES detection system which is robust to optical noise using a narrow band interference optical filter. Applying a narrow band interference optical filter which has the wavelength range of 895~915nm to the LASER wavelength of 900nm, we could obtain detection characteristics robust to strong optical noise which can be occurred in street battles. However, the MILES detection system has the blind range of detection in the incident angle range of $30^{\circ}{\sim}90^{\circ}$. To solve this problem we proposed a method of incident angle scatter using refractors. Applying a concave meniscus lens refractor which has diopter of 5.4 to the MILES detection system, we could eliminate the blind angle of detection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.452-455
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• 2018

Wheel loader performs digging and dumping tasks using boom and bucket. The operation of the wheel loader equipment has a lot of repetitive tasks and the working environment is poor, but only by hand by man. Recently, demands for applying unmanned automated systems are increasing more and more in electrical components. For automated systems, accurate angle detection is indispensable for stable control. This paper proposes a signal processing system for precise angular control with noise robust features. As a result of implementing the proposed system and applying it to the wheel loader boom angle system, it was possible to detect an angle change of about 0.1 degree.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.94-103
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• 1997

This paper presents motor speed and revolution angle detection method using a sinusoidal AC tacho-generator. The 2-phase or 3-phase output tacho-generator can be adopted, and its' output voltages must have sinusoidal waveforms. Because the detection algorithm is simple, the proosed method can be implemented with analog devices or microprocessor conveniently. And the proposed method has a very short detection delay time. Especially in the analog implementation, there is no delay time without the settling time of analog devices. With the experimental results, it is verified that the proposed method can acculately detect the instantaneous motor speed and revolution angle over the wide ranges.