• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.205-210
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• 2008

In previous paper, we introduced 3d acquisition system with CCD cameras, but it was not distinguished from other 3d acquisition system with PSD camera. In this paper, we introduce the 3d data acquisition system using by stereo method with two cameras, show the calibration method of two cameras, and present 3d acquisition methods. we tried to improve the accuracy of 3d data acquisition and implemented the proposed methods. According to the result, we found that the proposed algorithms can boost the accuracy highly against the previous works. The proposed methods are to remove distortion on input images and adjust z axis. We describes the performance in the result.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.6
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• pp.589-597
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• 2017

This study aims to verify experimentally the specifications of the data acquisition system required for the precise measurement of signals in an underwater explosion (UNDEX) experiment. The three data acquisition systems with different specifications are applied to compare their precision relatively on maximum shock pressures from UNDEX. In addition, a method of assessing the acquired signals is suggested by introducing the concept of measurement uncertainty. The underwater explosion experiments are repeated five times under same conditions, and assessment is conducted on maximum quantities acquired from underwater pressure sensors. It is confirmed that the concept of measurement uncertainty is very useful method in accrediting the measurement results of UNDEX experiments.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.3
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• pp.249-256
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• 2017

Recently, application areas based on M2M (Machine-to-Machine communications) and IoT (Internet of Things) technologies are expanding rapidly. Accordingly, water flow and water quality management improvements are being pursued by applying this technology to water and sewage facilities. Especially, water management will collect and store accurate data based on various ICT technologies, and then will expand its service range to remote meter-reading service using smart metering system. For this, the error in flow rate data transmitting should be minimized to obtain credibility on related additional service system such as real time water flow rate analysis and billing. In this study, we have identified the structural problems in transmitting process and protocol to minimize errors in flow rate data transmission and its handling process which is essential to water supply pipeline management. The result confirmed that data acquisition via communication system is better than via analogue current values and pulse, and for communication method case, applying the industrial standard protocol is better for minimizing errors during data acquisition versus applying user assigned method.

• Journal of the Korea Safety Management & Science
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• v.8 no.6
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• pp.79-90
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• 2006

Recently the construction of the ERP(Enterprise Resource Planning) system becomes accomplished actively from the many enterprises. But the many problems occur in acquisition of production data which is a fundamental data of system. Also to delay the acquisition of the production result is fatal in the efficient business operation. The construction of the POP(Point of Production) system which acquires production data at real time is become accomplished widely, In the POP system it is most important to acquire the production data which is accurate. But the many enterprises drop the competitive power with acquisition of the data which could not be trusted. In this paper, we analyze these causes and present the method which it can improve the reliability of production data. Also we introduce a real application case.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.256-261
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• 1992

Acquisition of 3D points is an essential process for modelling of physical 3D objects. Although Coordinate Measuring Machine(CMM) is most accurate for this purpose, it is very time consuming. To enhance the data aquisition speed for scuptured surfaces, active vision with reflecctometric method was used for our system. A fter the data acquisition, the system automatically generates cutting tool path for the 3-axis milling of the object. The fullyintegrated system from the data acquisition to the NC-code generation was implemented with IBN-PC/386 and necessary hardwears.

• Bulletin of the Korean Chemical Society
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• v.29 no.10
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• pp.2017-2022
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• 2008

Of the experiments to shorten NMR measuring time by sparse sampling, non-uniform sampling (NUS) is advantageous. NUS miminizes systematic errors which arise due to the lack of samplings by randomization. In this study, I report the real-time acquisition of 3D NMR data using NUS and maximum-entropy (MaxEnt) data processing. The real-time acquisition combined with NUS can reduce NMR measuring time much more. Compared with multidimensional decomposition (MDD) method, which was originally suggested by Jaravine and Orekhov (JACS 2006, 13421-13426), MaxEnt is faster at least several times and more suitable for the realtime acquisition. The designed sampling schedule of current study makes all the spectra during acquisition have the comparable resulting resolutions by MaxEnt. Therefore, one can judge the quality of spectra easily by examining the intensities of peaks. I report two cases of 3D experiments as examples with the simulated subdataset from experimental data. In both cases, the spectra having good qualitie for data analysis could be obtained only with 3% of original data. Its corresponding NMR measuring time was 8 minutes for 3D HNCO of ubiquitin.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.2
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• pp.184-193
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• 2015

This paper proposes a cost-efficient and automatic method for large data acquisition from a test chip without expensive equipment to characterize random process variation in an integrated circuit. Our method requires only a test chip, a personal computer, a cheap digital-to-analog converter, a controller and multimeters, and thus large volume measurement can be performed on an office desk at low cost. To demonstrate the proposed method, we designed a test chip with a current model logic driver and an array of 128 current mirrors that mimic the random process variation of the driver's tail current mirror. Using our method, we characterized the random process variation of the driver's voltage due to the random process variation on the driver's tail current mirror from large volume measurement data. The statistical characteristics of the driver's output voltage calculated from the measured data are compared with Monte Carlo simulation. The difference between the measured and the simulated averages and standard deviations are less than 20% showing that we can easily characterize the random process variation at low cost by using our cost-efficient automatic large data acquisition method.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.235-238
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• 2007

This paper presents an efficient data storage and reconstruction method in data acquisition and processing of monitoring system. The proposed method extracts minimum data using an interpolation from raw data which are acquired from a target system. The algorithm for data acquisition and reconstruction is based on Cubic Hermite interpolation. To verify the validity of the proposed scheme, we presents simulation results and it is applied to a monitoring system for grid-connected photovoltaic power generation system to prove the high-performance of the proposed method.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.5
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• pp.798-807
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• 2021

The directivity characteristics of acoustic transducers for conventional single-beam echo sounders considerably limit the detection of fish-size information in acoustic field surveys. To overcome this limitation, using the split-aperture technique to estimate the direction of arrival of single-echo signals from individual fish distributed within the sound beam represents the most reliable method for fish-size classification. For this purpose, we design and develop a split-beam data acquisition and processing system to obtain fish-size information in conjunction with a 50-kHz single-beam echo sounder. This split-beam data acquisition and processing system consists of a notebook PC, a field-programmable gate array board, an external single-transmitter module with a matching network, and four-channel receiver modules operating at a frequency of 50-kHz. The functionality of the developed split-beam data processor is tested and evaluated. Acoustic measurements in an experimental water tank showed that the developed data acquisition and processing system can be used as a fish-sizing echo sounder to estimate the size distribution of individual fish, although an external single-transmitter module with a matching network is required.