• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.902-905
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• 2004

A heart diagnosis system adopts Superconducting Quantum Interface Device(SQUID) sensors for precision MCG signal acquisitions. Such system is composed of hundreds of sensors, requiring fast signal sampling and precise analog-digital conversions(ADC). Our development of hardware board, processing 64-channel 12-bit 1ks/s, is built by using 8-channel ADC chips, 8-bit microprocessors, SPI interfaces, and parallel data transfers between microprocessors to meet the 1ks/s, i.e. 1 ms speed. The test result shows that the signal acquisition is done in 168 usuc which is much shorter than the required 1 ms period. This hardware will be extended to 256 channel data acquisition to be used for the diagnosis system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.11
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• pp.643-649
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• 2005

A heart diagnosis system adopts Superconducting Quantum Interface Device(SQUD) sensors for precise MCG(MagnetoCardioGram) signal acquisitions. Such system needs to deal with hundreds of sensors, requiring fast signal sampling md precise analog-to-digital conversions(ADC). Our development of hardware board, processing 64-channel 12-bit in 1 ks/s speed, is built by using 8-channel ADC chips, 8-bit microprocessors, SPI interfaces, and specially designed parallel data transfers between microprocessors to meet the 1ks/s, i.e. 1 mili-second sampling interval. We extend the design into 256-channel hardware and analyze the speed .using the measured data from the 64-channel hardware. Since our design exploits full parallel processing, Assembly level coding, and NOP(No Operation) instruction for timing control, the design provides expandability and lowest system timing margin. Our result concludes that the data collection with 256-channel analog input signals can be done in 201.5us time-interval which is much shorter than the required 1 mili-second period.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.538-540
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• 2004

Electrical currents generated by human heart activities create magnetic fields represented by MCG(MagnetoCardioGram). Since an MCG signal acquisition system requires precise and stable operation, the system adopts hundreds of SQUID(Superconducting QUantum Interface Device) sensors for signal acquisition. Such a system requires fast real-time data acquisition in a required sampling interval, i.e., 1 mili-second for each sensor. This paper presents designed hardware to acquire data from 256-channel analog signal with 1 ksamples/sec speed, using 12-bit 8-channel ADC devices, SPI interfaces, parallel interfaces, 8-bit microprocessors, and a DSP processor. We implemented SPI interface between ADCs and a microprocessor, parallel interfaces between microprocessors. Our result concludes that the data collection can be done in $168{\mu}sec$ time-interval for 256 SQUID sensors, which can be interpreted to 6 ksamples/sec speed.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.4
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• pp.151-160
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• 2015

GPS L2C signal is a recently added civil signal to L2 frequency and is constructed by time division multiplexing of civil moderate (L2-CM) and civil long (L2-CL) code signals. While the L2-CM code is 20 ms-periodic and modulates satellite navigation message, the L2-CL code is 1.5s-periodic with 767,250 chips long code sequence and carries no data. Therefore, the L2-CL code signal allows receivers to perform a very long coherent integration. However, due to the length of the L2-CL code, the acquisition of the L2-CL code signal may take too long or require too much hardware resources. In this paper, we propose a three-step ultra-fast L2-CL code acquisition (TSCLA) technique for dual band GPS receivers. In the proposed TSCLA technique, a dual band GPS receiver sequentially acquires the coarse/acquisition (C/A) code signal at L1 frequency, the L2-CM code signal, and the L2-CL code signal to minimize mean acquisition time (MAT). The theoretical performance analysis and numerous Monte Carlo simulations show the significant advantage of the proposed TSCLA technique over conventional techniques introduced in the literature.

• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.337-340
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• 2004

Upper stage telemetry system of KSLV- I (Korea Space Launch Vehicle I) is composed of MDU (Master Data Unit), RDU (Remote Data Unit), SRU (Shock Recorder Unit) and Transmitter. RDU is the front-end telemetry data acquisition unit which gathers analog/discrete signals from various sensors and other units, and transmits the processed data to MDU via MIL-STD-I553B data bus. In order to acquire useful data from analog signal, signal conditioning circuits, such as anti-aliasing or amplifying, should be implemented. For this purpose, SCM (Signal Conditioning Module) had been developed. This paper describes hardware structure of SCM and analog signal conditioning circuits for various sensors. Also, sampling time scheme for different sampling rates were designed and tested.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.229-234
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• 2006

Acquisition is to detect the presence of the GPS signal. Once the signal is detected, the estimated frequency and code phase are passed to a tracking loop to demodulate the navigation data. In order to detect the weak signal, multiple length of data integration is always needed. In this paper, we present five different acquisition approaches based on circular correlation and Fast Fourier Transform (FFT), using coherent as well as non-coherent integration techniques for the multiple length of collected GPS satellite signal. Moreover a general approach of determining the acquisition threshold is introduced based on noise distribution which has been proved effective, and independent of the hardware. In the end of this paper, the processing speed and acquisition gain of each method are illustrated, compared, and analyzed. The results show that coherent approach is much more time consuming compared to noncoherent approaches, and in the case of multiple length of data integration from 2ms to 8ms, the processing times consumed by the fastest non-coherent acquisition method are only 25.87% to 1.52% in a single search, and 34.76% to 1.06% in a global search of those in the coherent acquisition. However, coherent acquisition also demonstrates its better performance in the acquisition gain, and in the case of 8ms of data integration it is 4.23 to 4.41 dB higher than that in the non-coherent approaches. Finally, an applicable scheme of combining coherent and non-coherent acquisition approaches in the development of a real-time Software GPS receiver in the University of Tokyo is provided.

• Journal of Sensor Science and Technology
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• v.16 no.3
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• pp.187-191
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• 2007

This paper presents a development of the multi-channel data acquisition/logging system for a sensor signal processing and a method of the evaluation and a temperature compensation for the A/D converters with the specific analog and digital circuit including the software. Also, we have designed a hardware and a software filters with smart algorithm for better signal processing of the proposed system. Software approach was adopted to obtain the stable data from A/D converter.

• Current Optics and Photonics
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• v.7 no.6
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• pp.683-691
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• 2023

A typical terahertz time-domain spectroscopy system requires large, expensive, and heavy hardware such as a lock-in amplifier and a function generator. In this study, we replaced the lock-in amplifier and the function generator with a single sound card built into a typical desktop computer to significantly reduce the system size, weight, and cost. The sound card serves two purposes: 1 kHz chopping signal generation and raw data acquisition. A unique software lock-in (Python coding program to eliminate noise from raw data) method was developed and successfully extracted THz time-domain signals with a signal-to-noise ratio of ~40,000 (the intensity ratio between the peak and average noise levels). The built-in sound card with the software lock-in method exhibited sufficiently good performance compared with the hardware-based method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.952-955
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• 2000

Nowadays, Internet is so popular that we can easily access the remote site to search information and to communicate remote site and users. People who want to make a collaborate working environment can use JAVA, CORBA, and other internet programming tools like a Perl/XML. The mechanist are try to make the environment fur collaboration within design/manufacturing, simulation, remote sensing through TCP/IP And many industries and research institutions are working towards the agile manufacturing. This paper describes an internet-based real-Time remote monitoring system. The system consists of a hardware setup and a software interface. The hardware setup consists of a machine and its data acquisition hardware, while the software interface incorporates the data acquisition software, the server program, and the client program. The server program acts as the main interface between the data acquisition system and the internet technology. The client program is to be distributed to the remote users who want to monitor the machining status. The system has been demonstrated and verified for an industrial High-Speed Machine (HSM) especially measuring cutting force and acoustic emission. To share the signal, we make the WWW server and display its value. The system has been found to be highly efficient, reliable and accurate.

• The Journal of the Acoustical Society of Korea
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• v.8 no.5
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• pp.95-101
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• 1989

For developing new algorithms or dedicated hardware by using general purpose Digital Signal Processor chip, emulator H/W and simulator S/W are indispensible. But the most of DSP emulators have limitations on H/W flexibility according to their generalized architectures. In this paper, a DSP evaluation system for real time signal processing was developed using TMS 32020. The I/O buffers storing acquisition data of the system were designed to have variable length $(1\sim2048samp1es) &$ sampling frequency $l00\sim8KHz$.