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Recently, motorcycle accidents have increased as the number of motorcycle drivers has increased. Although the head and neck are the body parts most frequently injured when a motorcycle accident occurs, there is a lack of research on the protection afforded to the neck by the safety equipment used by motorcycle drivers. This study presents an airbag system that uses artificial intelligence to prevent injury to the neck of a motorcycle driver. It uses a six-axis sensor, the MPU6050 sensor, which measures acceleration and angular velocity in real time as the user moves. The angles are obtained by using the measured acceleration and angular velocity, and the accident situation is judged by AI, which analyzes the acceleration and angle data. Because data is needed for AI to learn, data by type were collected through experiments. In this study, we compare the judgement performance of a parallel neural networks–convolutional neural network and a parallel neural network.

Injuries to the head and the neck are the most frequent in the event of motorcycle accidents. But enough research has not been done to protect the neck. This paper presents an airbag system that recognizes the accident situation with Artificial Intelligence to protect the driver's neck area from motorcycle accident situations when driving. In some papers with similar themes, most of them are judged based on a critical point. However, in the case of an accident judgment using the critical point, a malfunction may occur such that the airbag operates when a similar operation is performed, or the airbag does not operate due to failing to pass the critical point at the time of an accident. Artificial intelligence was used to avoid malfunctions and inconveniences. Artificial intelligence can solve the problem of malfunction that occurs when it is judged as a critical point and can solve the inconvenience of commercialized products. The CNN presented in this paper can solve these two problems, and the accuracy of accident judgment is as high as 95.75%. Through the MPU 6050 sensor, it operates the airbag by determining the accident situation using the Artificial Intelligence that was learned in advance through the information on acceleration and angular velocity of the driver's movements that were measured in real time. To make Artificial Intelligence learn, the data were collected by dividing several types of accidents on motorcycles. In this paper, the Artificial Intelligence made by Convolutional Neural Networks (CNN) method and the Artificial Intelligence made by Neural Networks (NN) method is compared, and it is confirmed that the performance such as Test Accuracy or Train Accuracy of CNN is better.

Given their wide applicability, vehicle positioning systems are being actively studied currently. As the conventional global positioning system (GPS) cannot determine the vehicle position inside tunnels and other GPS-shaded areas, we propose to improve vehicle positioning using a fuzzy logic system that can retrieve the position of a moving vehicle in such areas. The proposed system analyzes the chromaticity and frequency components of active LED illumination, which is being commonly installed at locations like inside tunnels. We verify the system performance in a test environment that resembles a tunnel. As the proposed method uses the chromaticity and frequency of LED lights for vehicle positioning, it is suitable for areas where GPS reception is poor or unavailable.

The risk of environmental pollution is a consequence of every kind of energy, including fossil fuels, nuclear power plants, and thermoelectric power plants. For the purpose of reducing the use ratio of such energy, research on eco-friendly energy is being actively carried out, and has shown that among all kinds of energy, solar energy has an advantage: it can supply us with inexhaustible clean energy. However, since solar energy depends on sunlight, the output may be unstable as it is influenced by weather or surrounding structures. In this paper, there is presented a control system which transmits power to a storage device, in a specific state, after the energy of the low-illumination section is charged in a supercapacitor using the accumulation-type controller by use of a supercapacitor. Feedback from the power output of photovoltaic panels (PVs) demonstrates that the power of the low-illumination section can be charged without being discarded. The charging rate was compared with other solar controllers being sold on the market, and the comparison was made through state of charge (SOC) measurements after the battery had been charged by photovoltaic panels for a whole day. It was confirmed that the solar controller, by use of supercapacitor integrator proposed in this paper, stored higher levels of energy than the existing solar controllers over the same hours and under the same conditions.

Due to the development of leisure sports industry and the increase in delivery demand, the demand for two-wheeled vehicles such as the motorcycle is increasing every year; moreover, the motorcycle accident rate is increasing. The motorcyclist’s body is exposed to the outside, and in cases of accidents, the head and the neck are particularly vulnerable. This paper proposes a study about an air bag equipped with Artificial Intelligence to protect the driver’s neck spine from motorcycle accidents. Through the six-axis sensor, it receives the driver’s motor condition data about the acceleration and angular velocity data and measures real time speed and angle; combines them with algorithms that can judge accidents through Artificial Intelligence learning to activate airbags in real time. Data were collected and learned by dividing the types of accidents; for Artificial Intelligence learning, the general Neural Network method was not used however, a mix of parallel Neural Network with an existing Neural Network were used instead. The Artificial Intelligence learning method proposed in this paper has been found to have more improved accuracy, stability and learning time compared to the existing Neural Network.

Drones in flight make a variety of vibration frequencies. Therefore, gimbal system is needed to get clean images from drone-mounted cameras. The system consists of two things: one is a structure to support a camera module, and another is a stabilizer to block outside vibrations and keep the right angle. The purpose of this paper focuses on the system's dynamics model and the application of a traditional PID controller. Furthermore, the paper compares the traditional PID and intelligent-PID without any dynamics model through the simulation made of MATLAB/Simulink.

A flying drone generates vibrations in a great variety of frequencies, and it requires a gimbal system stabilization loop design in order to obtain clean and accurate image from the camera attached to the drone under this environment. The gimbal system for drone comprises the structure that supports the camera module and the stabilization loop which follows the precise angle while blocking the vibration from outside. This study developed a dynamic model for one axis for the stabilization loop design of a gimbal system for drones and applied classical PID controller and intelligent PID controller. The Stabilization loop design was developed by using MATLAB/Simulink and compared the performance of each controller through simulation. Especially, the intelligent PID controller can be designed almost without the dynamic model and it demonstrates that the angle can be followed without readjusting the parameters of the controller even when the characteristics of the model changes.

In the field of electronic warfare applications, high voltage power supply(HVPS) for high power phased array transmitters must necessarily have an independent operating characteristics for driving mini TWTs. TWT independent operational characteristics, in order to run without interrupting the electronic warfare mission by maintaining the partial transmission function even when one of the TWT has occurred a failure, is known to be very important. In this paper, we describe the research on high-speed independent control system using a high-density HVPS, including FE modulators, hardware configuration and the FPGA in order to independently operate mini TWTs. Also, we have simulated some possible faults in phased array transmitters, and presents the test results to control a faulted TWT independently.

The electric power required to operate the urban railway supplies DC 1,500 V to the electric train through trolly wire. The rectifier which converts AC to DC has a rectification method using a diode and a rectification method using a thyristor. The thyristor rectification method is easier to adjust the trolly wire voltage than the diode rectification method. In addition, it is possible to reuse the regenerative electric power generated when the electric train stops, thereby helping to reduce the operating cost of the Urban railway operator and to reduce the greenhouse gas. However, the thyristor rectification method has a disadvantage in that the power factor of an urban railway substation is lowered because a harmonic current is generated during rectification and the reactive power becomes large. In this paper, we analyze the harmonic currents generated of Busan Urban railway substation system using thyristor rectifier, we propose an optimal harmonic filter to achieve a power factor of over 90% by simulation.

The common way to obtain a stereoscopic image of a subject at a distance is to place two cameras on the parallel axis rather than crossing axis. To find the IAD and maximum focal length, left and right images are obtained by varying the IAD of cameras and the focal length of the camera lens and the depth budget for the obtained images is analyzed through post production. Then, the database for IAD and focal length of the camera lens with the depth range that does not cause visual fatigue and visual discomfort are developed. These data are used to design fuzzy control and deduce the IAD and focal length of the camera lens to shoot a subject at a distance, and the function of the fuzzy control is confirmed through the actual shooting within the range of deduced IAD and focal length of the camera lens. 키워드 : 원거리 입체영상, 수평식 리그, 깊이범위, 깊이 총량, 퍼지추론 Key word : Remote Stereoscopic Photographs, Parallel Rig, IAD, Depth Range, Depth Budget, Fuzzy InferenceJournal of the Korea Institute of Information andCommunication Engineering

This paper proposes cross-coupling synchronous velocity control based on model reference adaptive control (MRAC) method for an uncertain model of transformer winding system with two non-symmetrical axial systems such as a winding spindle system and a nozzle feed drive system. Since it is difficult to achieve the physical parameters in modeling of the transformer winding system, MRAC is used to ensure the stability of the transformer winding system. In order to minimize the synchronous velocity error between two axial systems, a cross-coupling synchronous control is employed. Accordingly, the velocity error of the winding spindle system is reflected to the nozzle feed drive system and vice versa. Simulation and experimental results show that the proposed controller which is applied to the transformer winding system with uncertain parameters can reduce the synchronous velocity error between two axial systems.

This paper proposes a thyrister rectification type of double converter rectification equipment to simplify trolley line equipment and return the regenerative power into AC motion without storage equipment by converting the double converter into Converter(Forward) or Inverter(Reverse) based on voltages supplied for the trolley lines using high current thyristers and keeping voltages supplied for the trolley lines constant and an optimal thyrister firing angle to improve output characteristics in mode conversion of Converter(Forward) or Inverter(Reverse) by the simulation and experiments for operation and output characteristics of the double converter rectification equipment.

In this paper, a differential sliding mode tracking controller (DSMC) using voltage input is designed for trajectory tracking of the three-wheeled omnidirectional mobile platform (OMP) based on its dynamic modeling with disturbances. First, a tracking error vector is defined, and then a differential sliding surface vector is chosen. A control law is obtained by using Lyapunov direct method with backstepping technique. The control law stabilizes the sliding surface vector and makes the tracking error vector go to zero asymptotically. To implement the designed controllers, a control system is developed based on PIC microcontroller. A camera sensor and encoders are used. The simulation and experiment results are presented to illustrate effectiveness of the proposed controller.

This paper presents a Kinect camera sensor-based object tracking and following system for the four wheel independent steering automatic guided vehicle (4WIS-AGV) using Kalman filter and backstepping control method. To accomplish this task, the following steps are executed: Firstly, a blue colored object is detected by the Kinect camera sensor using a color-based object detection method and its center coordinates inside the RGB image frames are obtained. The global position coordinates of the detected object and the 4WIS-AGV are obtained using Kinect depth data and NAV200 navigation system. Secondly, a Kalman filter is used to estimate the global position and velocity coordinates of the detected moving object. Thirdly, a backstepping control method using Lyapunov function is adopted for the 4WIS-AGV to perform the object following task. Finally, simulation and experiment are performed to verify the effectiveness of the proposed system. The results show that the 4WIS-AGV with Kinect camera sensor can follow the moving object well with the designed controller.

This paper describes a new method for a digital gas metal arc welding (GMAW) system. The GMAW system is an arc welding process that incorporates the GMAW power source (PS-GMAW) with a wire feed unit (WFU). The PS-GMAW requires an electric power of constant voltage. A constant magnitude is maintained for the arc current by controlling the wire-feed speed of the WFU. A mathematical model is derived, and a self-tuning fuzzy proportional-integral-derivative (PID) controller is designed and applied to control the welding current. The electrode wire feeding mechanism with this controller is driven by a DC motor, which can compensate for both the molten part of the electrode and undesirable fluctuations in the arc length during the welding process. By accurately maintaining the output welding current and welding voltage at constant values during the welding process, excellent welding results can be obtained. Simulation and experimental results are shown to prove the effectiveness of the proposed controller.

This paper focuses on the feasibility of IEEE 802.11b wireless LAN for real-time wireless industrial network. In general, it has been known that IEEE 802.11b is not suitable for industrial networking because its medium access control method is the contention-based CSMA/CA (Carrier Sensing Multiple Access with Collision Avoidance) that exhibits unstable performance under heavy traffic and unbounded delay distribution. As an attempt to circumvent the probabilistic nature of IEEE 802.11b, this paper presents an enhanced four-layer architecture using the Network Driver Interface Specification (NDIS) and a virtual polling algorithm. Also, the enhanced four-layer architecture's performance is compared with that of conventional IEEE 802.11b. Based on the experimental results, it is found that the enhanced four-layer architecture for IEEE 802.11b is a very promising alternative for wireless industrial networking.

In this paper, a sensorless vector control method is introduced where rotor speed is estimated based on extended Kalman filter (EKF). The EKF is a recursive optimum stochastic state estimator. The proposed EKF is designed to obtain a small estimation speed error in both transient and steady state over a wide speed range. A major challenge at very low and zero speed is the lost coupling effect from the rotor to the stator, which makes the information on rotor variables unobservable on the stator side. To solve this problem, in the proposed EKF, the load torque and the rotor speed with unmeasurable information are estimated simultaneously. The rotor speed is considered via the equation of motion and the estimation of load torque, on the other hand, is performed as a constant parameter. Hardware and software for experiment of the AC induction motor drive are introduced. The experimental results are presented to show the effectiveness of the proposed system.

Estimates of maximum amplitudes of conductor galloping are needed in order to determine appropriate phase-to-phase clearances of overhead power lines. A new method for computing these estimates is obtained by the use of mathematical models of conductor galloping that include both vertical and torsional motion. The method gives estimates of the maximum gallop amplitude and frequency for various wind speeds. The stability of the predicted gallop limit cycle is determined by perturbation of the limit cycle parameters. Computer simulations show good agreement with the maximum amplitude and frequency estimates predicted by the model. The maximum gallop amplitudes predicted by the model also conform well with those observed on actual galloping lines. In addition, this analysis verifies what a number of galloping conductor researchers had long expected, namely, that torsional conductor motion limits maximum gallop amplitudes.