• Journal of the Korean Crystal Growth and Crystal Technology
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• v.7 no.2
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• pp.276-283
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• 1997

A dry impregnation method was used for preparing pellet type Pt/$SnO_2$ gas sensor. The crystal structure, direction of the crystal, crystal size and microstructure between the catalyst and the support ($SnO_2$) were characterized with electron diffraction analysis, transmission electron microscopy, scanning electron microscopy. The characterization indicates that when Pt/$SnO_2$ sample is calcined at $400^{\circ}C$, the Cl content associated with the Pt phase diminishes and the part of Pt is moved into $SnO_2$ support. This results in the enhancement of gas sensitivity. After the reactor with a Pt/$SnO_2$ sample was run with a flow rate of 30 sccm (a mixture of 0.5% $H_2$ in $_N2$) for a while, the resistance of $SnO_2$ was saturated, but the $SnO_2$ kept absorbing $H_2$ gas. This indicates that the surface state was saturated. For the 14 ppm $H_2$ gas, the sensitivity of Pt/$SnO_2$ devices was about 81% at an operating temperature of $300^{\circ}C$.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.5
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• pp.472-481
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• 2002

In this paper, the instantaneous flux Is applied to control the position of the SRG (Switched Reluctance Generator) without position sensor. The position information of the rotor is required in the drive of SRG. These data are generally obtained by a shaft encoder or resolver. In some cases, the EMI(Electro Magnetic Interference), vibration, thermal, and humidity environments may cause the difficulties in maintaining the satisfactory performance for the position detection. Therefore, the elimination of the position and speed sensor is needed. In this paper, a new method for the position estimation of the SRG is proposed. The estimation of the flux is calculated by using the measured voltage and current. The rotor position gets from the flux profile. The output voltage is also controlled constantly by PR control algorithm. These methods are verified by computer simulations md experiments using DSP. Experimental results certificate that the proposed method is able to control the SRG stable, and keep the output voltage constant in spite of changing of the load.

• Journal of Sensor Science and Technology
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• v.8 no.1
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• pp.69-79
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• 1999

The research and implementation was preformed on high-resolution CCTV camera with CCD exclusive DSP conventional analog signal processor CCTV camera has its limit on auto exposure(AE), auto white balance(AWB), back light compensation(BLC) processing, severe distortion and noise of image, manual control parameter setting, etc. In our study, to resolve the problems in conventional CCTV camera, we made it possible to control AE, AWB, BLC automatically by the use of the DSP, which are used exclusively in the CCD camera produced domestically, and the microcontroller. And we utilized the function of screen display of microcontroller for the user-friendly interface to control CCD camera. And the electronic variable resister(EVR) was used to avoid setting parameters manually in the level of manufacturing process. As the result, It became possible to control parameters of the camera by program. And the cost-down effect was accomplished by improving the reliability of parameter values and reducing the efforts in setting parameters.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.54-62
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• 2002

This paper describes a development of the integrated controller system for car electrical signal and sensor input/output control with CAN communication protocol. In order to improve the system reliability and effectiveness for the conventional controller using the wiring harness, a detailed integrated control system is introduced and discussed. The CAN communication protocol is a robust control method with serial bus system for the control of distributed module in the multiplexed network. Therefore, this has high reliability and flexibility in the overall control system implementation. This paper proposes an integrated system with high reliability and stability for control of various car signal, and evaluates the effectiveness of the system using the actual implementation. For these purposes, after a brief of the main features of the CAN will be addressed, this paper presents the result of development of the integrated hardware system and overall control program.

• Journal of Sensor Science and Technology
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• v.10 no.6
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• pp.310-316
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• 2001

We have been designed and constructed an artificial odour recognition system(electronic nose system) using metal oxide type sensor array for recognizing and analyzing various odours. We proposed an unsupervised clustering method based on Euclidean distances in order for human observer to examine easily multi-dimensional data, which has been measured from an array of sensors. This is a combination of Principal Components Analysis(PCA) used as a starting point for Sammom Mapping Method(SMM). No prior assumptions are made of the classes in which odour belong, and the error due to dimensional reduction at the PCA can be minimized without the disadvantages of rotation of clusters when the order of data sets in a data base was changed in the SMM. An artificial odour recognition system with the proposed unsupervised clustering method was applied to assessment of odour differences of Volatile Organic Compounds(VOCs) and Korean whiskies respectively, and demonstrated the best performances throughout the experimental trails.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.6
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• pp.438-445
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• 2019

In this paper, we present a new approach to extract the g-sensitivity scale-factor error for a MEMS gyroscope. MEMS gyroscopes, based on the use of both angular momentum and the Coriolis effect, have a g-sensitivity error due to mass unbalance. Generally, the g-sensitivity error is not considered in general use of gyroscopes, but it deserves our attention if we are to develop for tactical class performance and reliability. The g-sensitivity error during vehicle flight increases navigation error; so it must be analyzed and compensated for the use of MEMS IMU for high dynamics vehicle systems. Therefore, we analyzed how to extract the g-sensitivity scale-factor error from the inertial sensor error model. Furthermore we propose a new method to extract the g-sensitivity error using flight motion simulator. We verified our proposed method with experimental results.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.3
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• pp.381-387
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• 2011

Measurement controller that acquire and control and observe data from scattering sensors is organic with central control room. Therefore, measurement controller is efficient wireless network than wire network. But, serious problem is happened in security from outside if use wireless network. Therefore, this paper proposed suitable MS-WP cryptographic system to measurement control wireless network to augment network efficiency of measure controller. Result that implement proposed MS-WP cryptographic system by chip level and achieve a simulation, confirmed that 130% processing rate increase and system efficiency are increased double than AES algorithm. Proposed MS-WP cryptographic system augments security and is considered is suitable to measurement controller because that low power is possible and the processing speed is fast.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.32-40
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• 2016

IEEE 802.15.4 is the one of the protocols for radio communication in a personal area network. Because of low cost and low power communication for IoT communication, it requires the highest optimization level in the implementation. Recently, the studies of location aware algorithm based on IEEE802.15.4 standard has been achieved. Location estimation is performed basically in equal consideration of reference node information and blind node information. However, an error is not calculated in this algorithm despite the fact that the coordinates of the estimated location of the blind node include an error. In this paper, we enhanced a conventual maximum likelihood estimation using weighted coefficient and implement the hardwired location aware engine for small code size and low power consumption. On the field test using test-beds, the suggested hardware based location awareness method results better accuracy by 10 percents and reduces both calculation and memory access by 30 percents, which improves the systems power consumption.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.29-34
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• 2005

The wound induction motor can provide high starting torque and reduced starting current simultaneously by inserting large resistor externally when starting. And this technique is one of the well known methods among the induction motor starting methods and generally used for heavy load starting such as crane and cement factories. The conventional PI controller has been widely used in industrial application due to the simple control algorithm and is generally used for control of current torque, position, and speed for the wound induction motor drive system. However, the conventional control system for wound induction motor may result in poor performance because sensors have to be used but are often limited by the environmental condition. Recently, to overcome these problems, many sensorless vector control methods for the wound induction motor have been studied. This paper presents a MRAS method for sensorless vector control of the wound induction motor drive. In the conventional MRAS method, in low frequency, the stator resistance variation may result in poor performance. Therefore, this paper presents a MRAS method with stator and rotor resistance tuning for sensorless vector control of the wound induction motor to overcome several shortages of the conventional MRAS caused by parameter variation and to enhance the robustness of the sensorless vector control. The validity and effectiveness of the proposed method is verified through digital simulation.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.