• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1540-1551
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• 2015

The detection of position and speed in BLDC motors without using position sensors has meant many efforts for the last decades. The aim of this paper is to develop a sensorless technique for detecting the position and speed of BLDC motors, and to overcome the drawbacks of position sensor-based methods by improving the performance of traditional approaches oriented to motor phase voltage sensing. The position and speed information is obtained by computing the derivative of the terminal phase voltages regarding to a virtual neutral point. For starting-up the motor and implementing the algorithms of the detection technique, a FPGA board with a real-time processor is used. Also, a versatile hardware has been developed for driving BLDC motors through pulse width modulation (PWM) signals. Delta and wye winding motors have been considered for evaluating the performance of the designed hardware and software, and tests with and without load are performed. Experimental results for validating the detection technique were attained in the range 5-1500 rpm and 5-150 rpm under no-load and full-load conditions, respectively. Specifically, speed and position square errors lower than 3 rpm and between 10º-30º were obtained without load. In addition, the speed and position errors after full-load tests were around 1 rpm and between 10º-15º, respectively. These results provide the evidence that the developed technique allows to detect the position and speed of BLDC motors with low accuracy errors at starting-up and over a wide speed range, and reduce the influence of noise in position sensing, which suggest that it can be satisfactorily used as a reliable alternative to position sensors in precision applications.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.5
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• pp.352-360
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• 2015

Squeal noise is a harsh, high-pitched sound that occurs when railways are running at sharp curve tracks. The cause of squeal noise is known to be the transient lateral traction force between wheel and rail. Field measurements are too difficult to control the parameters. Thus, the scaled test rig should have been made in order to investigate the generating mechanism of squeal noise. The unique feature of our test rig, HSTR(Hongik Squeal Testing Rig), is that DOFs of its wheelset are as close to as those of the real railway. The attack angle and running speed of the rail roller are controlled in real time for simulating a transient characteristic of driving curve. The environment conditions, such as given axle load, running speed, and wheel's yaw angle have been identified for generating squeal noise and the squeal noise itself has been measured. The relation between wheel creepage and creep force in lateral direction and the criteria for squeal noise have been investigated, which results has been verified by finite element method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.67-80
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• 2020

High-speed weigh in motion (HS-WIM) is a real-time unmanned system for measuring the weight of a freight-carrying vehicle while it is in motion without controlling vehicle traffic flow or deceleration. In Korea, HS-WIM systems are installed on the national highways and general national ways for pre-selection by law enforcement. In this study, to improve the measurement accuracy of HS-WIM, we devise improvements to the existing integral and peak weight conversion algorithms, and we provide a new fusion algorithm that can be applied to the mat-type HS-WIM. As a result of analyzing vehicle driving tests at a real site, we confirmed the highest level of weight-measuring accuracy.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.944-956
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• 2013

Drivers need lots of information when they drive on the highway, however it is necessary and important to be provided information which is appropriate formation. In order to offer the suitable information, adequate size, quantity, and frequency of provided information are required for the drivers. To evaluate propriety of the expressed message of VMS that provides real-time traffic conditions, first of all, the amount of message about legibility distance and viewing should be estimated. In this research, drivers' characteristics of VMS message design were also reviewed to enhance the efficiency of VMS. And legibility distance, the amount of viewing information, and ratio of viewing information were analyzed on the currently operating VMS. The results of this study proposed that the appropriate size, quantity, and frequency were concluded by the legibility and memory of message on the real driving conditions. Consequently, these design methods of VMS could be expected to improve the transmitting capability of highway information to drivers.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.113-123
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• 2000

In the navigation for a mobile robot, the collision avoidance with unexpected obstacles is essential for the safe navigation and it is independent of the technique used to control the mobile robot. This paper presents a new collision avoidance algorithm using neural network for the safe navigation of the autonomous mobile robot equipped with CAN and ultrasonic sensors. A tracked wheeled mobile robot has a stability and an efficiency to move on a rough ground. And its mechanism is simple. However it has difficulties to recognize its surroundings. Because the shape of the tracked wheeled mobile robot is a square type, sensor modules are generally located on the each plane surface of 4 sides only. In this paper, the algorithm using neural network is proposed in order to avoid unexpected obstacles. The important character of the proposed algorithm is to be able to detect the distance and the angle of inclination of obstacles. Only using datum of the distance and the angle, informations about the location and shape of obstacles are obtained, and then the driving direction is changed. Consequently, this algorithm is capable of real time processing and available for a mobile robot which has few sensor modules or the limited sensing range such as a tracked wheeled mobile robot. Effectiveness of the proposed algorithm is illustrated through a computer simulation and an experiment using a real robot.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.11
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• pp.319-328
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• 2023

Unlike cloud computing, edge computing technology analyzes and judges data close to devices and users, providing advantages such as real-time service, sensitive data protection, and reduced network traffic. EdgeX Foundry, a representative open source of edge computing platforms, is an open source-based edge middleware platform that provides services between various devices and IT systems in the real world. EdgeX Foundry provides a service for handling camera devices, along with a service for handling existing sensed data, which only supports simple streaming and camera device management and does not store or process image data obtained from the device inside EdgeX. This paper presents a technique that can store and process image data inside EdgeX by applying some of the services provided by EdgeX Foundry. Based on the proposed technique, a service pipeline for object detection services used core in the field of autonomous driving was created for experiments and performance evaluation, and then compared and analyzed with existing methods.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.99-109
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• 2007

Variable message signs (VMS), which are used for providing real-time information on traffic conditions and accident occurrences, are one of the important components of intelligent transportation systems VMS messages need to meet human factor requirements: messages should be readable and understandable while driving. Lab-controlled experiments on VMS messages were conducted to obtain useful data for analyzing drivers' responsive characteristics for VMS messages. Binary logistic regression (BLR) modeling techniques were applied to explore the relationships among drivers' message perceptions, message reading time, and amount of VMS messages. Probabilistic outcomes of the proposed BLR-based perception model could be greatly utilized to design VMS messages considering drivers' legibility performance. The major contribution of this study is to develop invaluable statistical models that can be used in designing VMS messages more effectively from the human factor point of view. The results could be further applied to establish the scheme of VMS message phase and duration.

• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.473-480
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• 2004

In this paper we propose an effective feature compensation scheme based on the speech model in order to achieve robust speech recognition. The proposed feature compensation method is based on parallel combined mixture model (PCMM). The previous PCMM works require a highly sophisticated procedure for estimation of the combined mixture model in order to reflect the time-varying noisy conditions at every utterance. The proposed schemes can cope with the time-varying background noise by employing the interpolation method of the multiple mixture models. We apply the‘data-driven’method to PCMM tot move reliable model combination and introduce a frame-synched version for estimation of environments posteriori. In order to reduce the computational complexity due to multiple models, we propose a technique for mixture sharing. The statistically similar Gaussian components are selected and the smoothed versions are generated for sharing. The performance is examined over Aurora 2.0 and speech corpus recorded while car-driving. The experimental results indicate that the proposed schemes are effective in realizing robust speech recognition and reducing the computational complexities under both simulated environments and real-life conditions.

• Journal of Platform Technology
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• v.8 no.4
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• pp.11-19
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• 2020

In an autonomous driving environment, dynamic recognition of objects is essential as the situation changes in real time. In addition, as the number of sensors and control modules built into an autonomous vehicle increases, the amount of data the central control unit has to process also rapidly increases. By minimizing the output data from the sensor, the load on the central control unit can be reduced. This study proposes a dynamic object recognition algorithm solely using the embedded processor on a LiDAR sensor. While there are open source algorithms to process the point cloud output from LiDAR sensors, most require a separate high-performance processor. Since the embedded processors installed in LiDAR sensors often have resource constraints, it is essential to optimize the algorithm for efficiency. In this study, an embedded processor based object recognition algorithm was developed for autonomous vehicles, and the correlation between the size of the point clouds and processing time was analyzed. The proposed object recognition algorithm evaluated that the processing time directly increased with the size of the point cloud, with the processor stalling at a specific point if the point cloud size is beyond the threshold

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.132-145
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• 2020

By coming of the 4th industrial revolution era, HD map have became a key infrastructure for determining precise location of autonomous driving in areas of futuristic cars, logistics and robots. Autonomous vehicles have became more dependent on HD map to determine the exact location of objects detected by various sensors such as LiDAR, GNSS, Radar, and stereo cameras as well as self-location decisions. By actualizing autonomous driving and C-ITS technologies, the demand for precise information on HD map have increased. And also the demand for the creation of new information based on the convergence of various changes and real-time information have increased. In this study, domestic and international HD map standards and related environments have analyzed. Based on this, usability has researched which comparison with standard HD map established by various institutions. Additionally, usability of standard HD map have studied for applying actual autonomous vehicles by reworking HD map. By the result of study, standard HD map have well established to use by various institutions. If further research about layer classification and definition by institutions will carried out based on this study, it has expected that and efficient establishment and renewal of HD map will take place.