• International Journal of Automotive Technology
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• v.8 no.3
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• pp.299-308
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• 2007

This study proposes a two-layer hierarchical control system that integrates active front wheel steering and four wheel braking torque control to improve vehicle handling performance and stability. The first layer is a robust model matching controller (R-MMC) based on linear matrix inequalities (LMIs), which optimizes an active front steering angle compensation and a desired yaw moment control, and calculates reference wheel slip for the target wheel according to the desired yaw moment. The second layer is a moving sliding mode controller (MSMC) that can track the reference wheel slip in a predetermined time by commanding proper braking torque on the target wheel to achieve the desired yaw moment. Since vehicle sideslip angle measurement is difficult to achieve in practice, a sliding mode observer (SMO) that requires only vehicle yaw rate as the measured input is also developed in this study. The performance and robustness of the SMO and the integrated control system are demonstrated through comprehensive computer simulations. Simulation results reveal the satisfactory tracking ability of the SMO, and the superior improved vehicle handling performance, stability and robustness of the integrated control vehicle.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.258-267
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• 2022

Weak over-the-horizon perception and blind spot are the main problems in intelligent connected vehicles (ICVs). In this paper, a V2V image transmission-based road condition warning method is proposed to solve them. The encoded road emergency images which are collected by the ICV are transmitted to the on-board unit (OBU) through Ethernet. The OBU broadcasts the fragmented image information including location and clock of the vehicle to other OBUs. To satisfy the channel quality of the V2X communication in different times, the optimal fragment length is selected by the OBU to process the image information. Then, according to the position and clock information of the remote vehicles, OBU of the receiver selects valid messages to decode the image information which will help the receiver to extend the perceptual field. The experimental results show that our method has an average packet loss rate of 0.5%. The transmission delay is about 51.59 ms in low-speed driving scenarios, which can provide drivers with timely and reliable warnings of the road conditions.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.527-532
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• 2005

The construction industries are facing problems of productivity, quality of work, safety, and the completion of projects in time. In construction industry a worker is exposed to hazardous environment, and has to do more physical work, effecting his health and also productivity. The automation and robotics can offer solution to many problems of the industry. In the past the major barrier to construction automation is the lack of electronic components and systems. This is solved now with the development of information technology, and the current obstacle is the high cost of automated systems, shortage of public money for R&D, and problems of acceptance. The robots employed in construction have followed the same concept as those employed in manufacturing. However, construction industry requires a different kind of robot compared to manufacturing Industry. The robots are stationery and product moves along the assembly line in manufacturing sector, but construction robots have to move about the site because buildings are stationary and of large size. The construction robots must function in adverse weather conditions, including variation in humidity, and temperature and increase the overall construction productivity rate. The major objective of the paper is to review the existing applications of building robots and to assess their implementation in building industry. A case study is considered for the implementation of robots for the painting work of the University Building at Saifabad PG College of Science, Hyderabad, India.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.791-802
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• 2023

The manual inspection of photovoltaic (PV) panels to meet the requirements of inspection work for large-scale PV power plants is challenging. We present a hot spot detection and positioning method to detect hot spots in batches and locate their latitudes and longitudes. First, a network based on the YOLOv3 architecture was utilized to identify hot spots. The innovation is to modify the RU_1 unit in the YOLOv3 model for hot spot detection in the far field of view and add a neural network residual unit for fusion. In addition, because of the misidentification problem in the infrared images of the solar PV panels, the DeepLab v3+ model was adopted to segment the PV panels to filter out the misidentification caused by bright spots on the ground. Finally, the latitude and longitude of the hot spot are calculated according to the geometric positioning method utilizing known information such as the drone's yaw angle, shooting height, and lens field-of-view. The experimental results indicate that the hot spot recognition rate accuracy is above 98%. When keeping the drone 25 m off the ground, the hot spot positioning error is at the decimeter level.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1677-1688
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• 2020

In the sodium-cooled fast reactor, the steam generator is a heat exchange device between sodium and water, which may cause leakage, resulting in a sodium-water reaction accident, which in turn affects the safe operation of the entire nuclear reactor. To this end, the electromagnetic vortex flowmeter is used to detect leakage of the steam generator and its signal processing method is studied in this paper. The hydraulic experiment was carried out by using water instead of liquid sodium, and the sensor output signal of the electromagnetic vortex flowmeter under different gas injection volumes was collected. The bubble noise signal is reflected by the base line of the sensor output signal. According to the relationship between the proportion of the bubble noise signal in the sensor output signal and the gas injection volume, a signal processing method based on the energy ratio calculation is proposed to detect whether the water contains bubbles. The gas injection experiment of liquid sodium was conducted to verify the effectiveness of the signal processing method in the detection of bubbles in sodium, and the minimum detectable leak rate of water in the steam generator was detected to be 0.2 g/s.

• Journal of IKEEE
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• v.22 no.2
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• pp.274-280
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• 2018

In this paper, we have developed the vacuum infusion automation system for the safety and quality advancement of the boat. It is necessary for the precise mixing rate of resinoid and curingagent to inject in an inner ship and deck at short time. We need for the optimal condition to a strengthen construction of boat. This one can solve the post deformability of the strengthen structure and can control the precise mixing rate of resinoid and curingagent to the resinoid fluidity and flowing rate per time. Under these condition, we can advance the an quality construction that based on the model and database information of the boat. Also, we can have an effective process management and retrench the production cost.

• Design & Manufacturing
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• v.16 no.1
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• pp.21-26
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• 2022

In the CNC machining process, problems such as lowering of machine operation rate, setting errors, and machining precision occur due to the increase in setting time and preparation time. These machining errors cause delays in delivery and increase in cost due to an increase in the number of mounting and dismounting of the workpiece, an increase in measurement and reprocessing time, and an increase in the finishing time in the assembly process. Therefore, in this study, by automating the setting of the work piece using OMV (On Machine Verification), which is a meteorological measurement system, the preparation time for machining the work piece and the setting accuracy were improved, the rework rate was reduced, and the mold manufacturing process was shortened. Through the advancement, standardzation, and automation of the mold part manufacturing process, we have improved productivity by minimizing low-value-added repetitive tasks. In addition, the measurement time was reduced by more than 50% and the machining measurement rate was improved by more than 20%, eliminating repetitive work for correcting machining defects, and reducing the work preparation time by more than 15% through automatic setting.

• ETRI Journal
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• v.45 no.5
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• pp.768-780
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• 2023

The application of unmanned aerial vehicles (UAVs) has recently attracted considerable interest in various areas. A three-dimensional multiple-input multiple-output concentric two-hemisphere model is proposed to characterize the scattering environment around a vehicle in an urban UAV-to-vehicle communication scenario. Multipath components of the model consisted of lineof-sight and single-bounced components. This study focused on the key parameters that determine the scatterer distribution. A time-variant process was used to analyze the nonstationarity of the proposed model. Vital statistical properties, such as the space-time-frequency correlation function, Doppler power spectral density, level-crossing rate, average fade duration, and channel capacity, were derived and analyzed. The results indicated that with an increase in the maximum scatter radius, the time correlation and level-crossing rate decreased, the frequency correlation function had a faster downward trend, and average fade duration increased. In addition, with the increase of concentration parameter, the time correlation, space correlation, and level-crossing rate increased, average fade duration decreased, and Doppler power spectral density became flatter. The proposed model was compared with current geometry-based stochastic models (GBSMs) and showed good consistency. In addition, we verified the nonstationarity in the temporal and spatial domains of the proposed model. These conclusions can be used as references in the design of more reasonable communication systems.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.296-307
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• 2020

Permanent magnet sodium flowmeter (PMSF) have been used to measure the sodium flow in fast breeder reactors. Due to the effects of irradiation, thermal cycling, time lapse, etc., the magnetic flux density of the PMSF will decrease after being used in the reactor for a period of time. Therefore, it must be calibrated regularly. But some flowmeters that immersed in sodium cannot be removed for an off-line calibration, so the on-line calibration is required. However, the best online calibration accuracy of PMSF using cross-correlation analysis method was 2.0-level without considering the repeatability. In order to further improve this work, the operational principle of the transducer in PMSF is analyzed and the design principle of the transducer is proposed. The transducers were tested on the sodium flow loop to collect the experimental data. The signal characteristics are analyzed from the time and frequency domains, respectively. The cross-correlation analysis method based on biased estimation is adopted to obtain the flow rate. The verification experimental results showed that the measurement accuracy is 1.0-level when the flow velocity is above 0.5 m/s, and the measurement accuracy is 3.0-level when the flow velocity is in the range of 0.2 m/s to 0.5 m/s.

• Journal of The Korean Astronomical Society
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• v.45 no.6
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• pp.167-173
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• 2012

Inter-granular Bright Points (igBPs) are small-scale objects in the Solar photosphere which can be seen within dark inter-granular lanes. We present a new algorithm to automatically detect and extract igBPs. Laplacian and Morphological Dilation (LMD) technique is employed by the algorithm. It involves three basic processing steps: (1) obtaining candidate "seed" regions by Laplacian; (2) determining the boundary and size of igBPs by morphological dilation; (3) discarding brighter granules by a probability criterion. For validating our algorithm, we used the observed samples of the Dutch Open Telescope (DOT), collected on April 12, 2007. They contain 180 high-resolution images, and each has a $85{\times}68\;arcsec^2$ field of view (FOV). Two important results are obtained: first, the identified rate of igBPs reaches 95% and is higher than previous results; second, the diameter distribution is $220{\pm}25km$, which is fully consistent with previously published data. We conclude that the presented algorithm can detect and extract igBPs automatically and effectively.