• Journal of Advanced Navigation Technology
• /
• v.13 no.3
• /
• pp.319-326
• /
• 2009

In this paper, the key technologies of Navigation receiver for GNSS sensor station are presented as a development result of a GNSS ground station in ETRI. A wide-band antenna and RF/IF components and SW signal processing unit to cover the GPS and Galileo signals for GNSS receiver are developed and its performance is verified by using GPS live signal and GNSS RF signal simulator from SpirentTM. We also gather GIOVE-A signal by using H/W antenna and RF/IF units in IF-level as sampling frequency and bit number, 112MHz and 8bits, respectively by using the developed wide-band antenna and RF/IF components. Data acquisition is done by using commercial data acquisition device from National Instrument TM. The gathered data is fed into SW receiver to process Galileo E1 to verify Galileo signal processing by Galileo live signal from GIOVE-A.

• Journal of the Institute of Convergence Signal Processing
• /
• v.6 no.4
• /
• pp.169-175
• /
• 2005

In recent, implementation of the embedded system is gradually in the spotlight of world-wide by information technology(IT) engineers. By this time, an implementation of real time system is limited on image acquisition and processing system in practical. In this paper, the USB camera interface system based on the embedded linux OS is implemented using USB 2.0 camera with low cost. This system can obtain image signals into the memory via X-hyper255B processor from USB camera. It is need to initialize USB camera by the Video4Linux for the kernel device driver. From the system image capturing and image processing can be performed. It is confirmed that the image data can be transformed to packet of Network File System(NFS) and connected to the internetwork, then the data can be monitored from the client computer connected to the internetwork.

• Smart Structures and Systems
• /
• v.24 no.5
• /
• pp.567-585
• /
• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.6 no.1
• /
• pp.27-33
• /
• 2011

In this paper, for a software-based Global Positioning System receiver (SGR), the principle capturing Global Positioning System (GPS) signal is researched extensively in order to analyze the processing of the GPS raw data signal at the lowest level, and the process of capturing the GPS signal was simulated by Matlab. The simulation results show the accuracy and the feasibility of this method, which is comparable to study under a true environment. We know that the improvement of the receiving facilities is of very vital significance to the performance of this system, and the fine frequency can be found through comparing phases within a few tens of Hertz.

• Journal of Biomedical Engineering Research
• /
• v.9 no.1
• /
• pp.31-36
• /
• 1988

A personal computer-based brain map is described which will display a gray scale maps showing the distribution of signals derived from the electrical activity of the brain such as EEG or EP This topographic brain mapping system has a flexibility which describe the electrode number and placement mapping onto any shaped space and generate a brain maps by incoorporated the data acquisition and processing software with conventional EEG machine.

• Proceedings of the KIEE Conference
• /
• 1992.07a
• /
• pp.293-295
• /
• 1992

This Paper presents the design of an automated EEG analyzing system. The design considerations including processing speed, A/D conversion, filtering, and waveforms detection, are overviewed with the description of the associated EEG charateristics. The architecture of the currently implemented system consists of a -controller based front-end signal processing unit and a host computer system. The data acquisition procedures are described along with a couple of illustrations of the acquired EEG/EOG signal.

• Proceedings of the KIEE Conference
• /
• 1992.07a
• /
• pp.183-186
• /
• 1992

The distribution automation functions include feeder automation, data acquisition and processing, remote meter reading and load management. This report explains the function of feeder automation and the accomplishment method of feeder automation using the switches of distribution system with multi functions.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.462-467
• /
• 1999

In this paper, very high performance millimeter-wave radiometer of 92 GHz is presented. Radiometer system design, brightness temperature measurement and calibration methods are described. The architecture of radiometer including data acquisition, storage and digital signal processing using a notebook computer are explained and some experimental data in the laboratory are introduced. The system noise figure and total gain of implemented radiometer are 12 dB and 56 dB, respectively. The system stability is evaluated from the experiment. The difference of the detector output voltage for two targets, whose brightness temperature are 80 K and 300K, is 4 mV. The mechanical scanning method is considered to get a brightness temperature Image of the earth surface scene.

• 한국해양학회지
• /
• v.27 no.1
• /
• pp.19-34
• /
• 1992

Marine seismic refraction surveys have been carried out by Korea Institute of Geology, Mining and Materials(KIGAM) since 1984. The recording of refraction data was based on analog instrumentation. Therefore the resolution of refraction data was not good enough to distinguish many layers. The objective of the interpretation of seismic refraction data is the determination of intervals and critically refracted seismic wave propagation velocities through the layers beneath the sea floor. To determine intervals and velocities precisely, the resolution of refraction data should be enhanced. The intent of the study is to improve the quality of shallow marine refraction data by the digital technique using microcomputer- based acquisition and processing system. The system consists of an IBM AT microcomputer clone, an analog-digital(A/D) converter. A mass storage unit and a parallel processing board. The A/D converter has 12 bits of precision and 250 kHz of conversion rate. The magneto-optical disk drive is used for the mass storage of seismic refraction data. Shallow marine seismic refraction surveys have been carried out using the system at 6 locations off Ulsan and Pusan area. The refraction data were acquired by the radio sonobuoy. The refraction profiles have been produced by the laser printer with 300 dpi resolution after the basic computer processing. 5-9 layers were interpreted from digital refraction profiles, whereas 2-4 layers were interpreted from analog refraction profiles. the propagation velocities of sediments were interpreted as 1.6-2.1 km/sec. The propagation velocities of acoustic basement were interpreted as 2.4-2.7 km/sec off Ulsan area, 4.8 km/sec off Pusan area.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
• /
• 1997.11a
• /
• pp.282-288
• /
• 1997

The purpose of this paper is to predict the situation of leak in closed space using an Artificial Neural Network (ANN). The existing system can't monitor the whole He situations with on/off signals. Especially the first stage of data determines the leak spot and intensity is disregarded in gas accidents. To complement these faults, a new prototype of monitoring system is proposed. Ihe system is composed of'sensing systenL data acquisition system computer, and ANN implemented in software and is capable of identifying the leak spot and intensity in closed space. The concentration of gas is measured at the 4 different places. The network has 3 layers that are composed of 4 input Processing Element (PE),24 hidden PEs, md 4 output PEs. The ANN has optimum condition through several experiments and as a consequence the recognition rate of93.75% is achieved finally