• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.60-64
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• 2022

In the automotive industry, the development of automobiles to meet safety requirements is becoming increasingly complex. This is because quality evaluation agencies in each country are continually strengthening new safety standards for vehicles. Among these various requirements, collision safety must be satisfied by controlling airbags, seat belts, etc., and can be defined as post-crash safety. Apart from this safety system, the Advanced Driver Assistance Systems (ADAS) use advanced detection sensors, GPS, communication, and video equipment to detect the hazard and notify driver before the collision. However, research to improve passenger safety in case of an accident by using the sensor of active safety represented by ADAS in the existing passive safety is limited to the level that utilizes the sudden braking level of the FCA (Forward Collision-avoidance Assist) system. Therefore, this study aims to develop logic that can improve passenger protection in case of an accident by using ADAS information and driving information secured before a collision. The proposed logic was constructed based on LSTM deep learning techniques and trained using crash test data.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.52 no.5
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• pp.211-220
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• 2003

The control method of programmable dynamometer for overall test of machine is to load the reference torque which is computed from torque transducer into motor under test. But the torque information detected from torque transducer have a lot of noise when the load torque of meter is a small quantity or changing. Thus, torque transducer must have a low pass filter to detect a definite torque information. But The torque delay generated by filter with torque transducer occur a torque trouble for meter torque of programmable dynamometer. Therefore, this kind of system could not perform dynamic and nonlinear load. In this paper, the control method using the load torque observer without a measure for torque transducer is Proposed. The proposed system improved the problem of the torque measuring delay with torque transducer, and the load torque is estimated by the minimal order state observer based on the torque component of the vector control induction meter. Therefore, the torque controller is not affected by a load torque disturbance. To verify a superiority of the proposed control algorithm, the analysis for a root locus of a conventional control method and the proposed one, and simulation and experiment is performed. Therefore we hope to be extended in industrial application.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.1
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• pp.16-23
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• 2018

PM synchronous motor may be rotated to an arbitrary direction and speed by outside wind under natural condition in cases where the fan is applied outside, such as in vehicle radiators and outdoor air-conditioners. Sensorless controls that cannot detect rotor position requires additional sensorless control algorithm because a rotor is rotated by an external load. In this study, the sensorless control of a PM synchronous motor under naturally rotating condition is proposed. The natural rotation conditions are classified as forward high-speed rotation, reverse high-speed rotation, and low-speed rotation. Experiment results verify the performance of the sensorless control, including the rotor speed and position detection at natural rotation mode and switch to the closed-loop sensorless control.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.3
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• pp.111-118
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• 2005

Since the residential load is an AC load and the output of solar cell is DC power, the photovoltaic system needs the DC/AC converter to utilize solar cell. In case of driving to interact with utility line, in order to operate at unity power factor, converter must provide the sinusoidal wave current and voltage with same phase of utility line. Since output of solar cell is greatly fluctuated by insolation, it is necessary that the operation of solar cell output in the range of the vicinity of maximum power point. In this paper, DC/AC converter is three phase PWM converter with smoothing reactor. And then, feed-forward control used to obtain a superior characteristic for current control and digital PLL circuit used to detect the phase of utility line.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1183_1184
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• 2009

The synchronized visual message system device of level crossing provides warning system with the use of developed corresponding technology when the train is approaching forward to limited distance in level crossing. To ensure of safety driving for coming transit from road, it detect the location and velocity of train and transport the information to wayside warning device to prevent the collision with train. This paper is about the detailed design of synchronize VMS for passing transit at the level crossing and develop the physical contents of level crossing VMS with expression words, operational device, massage transportation algorism which are based on the proto type study of communication method and information contents for level crossing VMS.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.286-289
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• 2007

This study is to develop a cloud detection algorit1un for COMS and it is currently tested by using MODIS level 2B and MTSAT-1R satellite radiance data. Unlike many existing cloud detection schemes which use a threshold method and traditional statistical methods, in this study a feed-forward neural network method with back-propagation algorit1un is used. MODIS level 2B products are matched with feature information of five-band MTSAT 1R image data to form the training dataset. The neural network is trained over the global region for the period of January to December in 2006 with 5 km spatial resolution. The main results show that this model is capable to detect complex cloud phenomena. And when it is applied to seasonal images, it shows reliable results to reflect seasonal characteristics except for snow cover of winter. The cloud detection by the neural network method shows 90% accuracy compared to the MODIS products.

• The Journal of Korean Institute of Information Technology
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• v.17 no.8
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• pp.75-83
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• 2019

In this paper, we propose a method that can detect and trace the end point of real - time reinforcement steel to various environmental conditions of industrial field by using Median flow and Depth information. We proposed a method to derive two steel end points by using Median filter, Binarization, Morphology, and Blob algorithm on image depth information. The coordinates of the final position were determined by comparing the coordinates of the reinforcement steel endpoints detected in the Depth image and the position tracking coordinates of the reinforcement steel using Median Flow. As a result, when the existing Median Flow method was used, the success rate of the final position determination of reinforcement steel of 75% was increased to 95% when the Depth of reinforcement steel was used.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1559-1565
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• 2007

The many target-detection methods that use forward-looking infrared (FUR) images can deal with large targets measuring $70{\times}40$ pixels, utilizing their shape features. However, detection small targets is difficult because they are more obscure and there are many target-like objects. Therefore, few studies have examined how to detect small targets consisting of fewer than $30{\times}10$ pixels. This paper presents a small target detection method using clutter rejection with stochastic hypothesis testing for FLIR imagery. The proposed algorithm consists of two stages; detection and clutter rejection. In the detection stage, the mean of the input FLIR image is first removed and then the image is segmented using Otsu's method. A closing operation is also applied during the detection stage in order to merge any single targets detected separately. Then, the residual of the clutters is eliminated using statistical hypothesis testing based on the t-test. Several FLIR images are used to prove the performance of the proposed algorithm. The experimental results show that the proposed algorithm accurately detects small targets (Jess than $30{\times}10$ pixels) with a low false alarm rate compared to the center-surround difference method using the receiver operating characteristics (ROC) curve.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.2
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• pp.1-7
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• 2011

The UAV(Unmanned Aerial Vehicle) which is remotely operating with long endurance in high altitude must have a very reliable propulsion system. The precise fault diagnostic system of the turboprop engine as a propulsion system of this type UAV can promote reliability and availability. This work proposes a diagnostic method which can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. It is found by evaluation examples that the proposed diagnostic method can detect well not only single type faults but also multiple type faults.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.263-270
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• 2004

Recently, wavelet transform have been applied to various kinds of problems in many fields. In this paper, we propose method of Daubechies wavelet to detect several kinds of important characteristic waves in tasks EEG that are needed to diagnose EEG. We show that our system could be attained higher performance in detecting characteristic waves than the other methods. In this system, the architecture of the neural network is a three layered feed-forward networks with one hidden layer which implements the error back propagation teaming algorithm. Applying the algorithms to 4 subjects show 92% classification rates. The proposed system shows a little more accurate diagnosis for task EEG by Wavelet and neural network. From the simulation results by the implemented system, we demonstrated this research can be reduce doctor's labors and quantitative diagnosis of task EEG.