• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.1
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• pp.90-98
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• 1998

This paper is to describe the improved vector control which can control the induction motor robustly in low speed. When the induction motor is drived with low speed, below 10 percent of the rated speed, an algorithm which can compensate the error of unit vector angle generated by the harmonics is proposed. Another algorithm which can be tuned to the rotor time constant so that nay be robust to the rotor parameter change in low speed and transient state was proposed. The ripple of flux and torque was reduced by the proposed vector control and then the stable output characteristics was obtained in low speed. When the input and output is sinusoidal, the proposed vector control, the direct vector control and the indirect vector control were analyzed and compared in the low speed characteristics. And each control characteristics is compared and analyzed in state of containing harmonics. The estimation and tunning performance of rotor time constant is confirmed with simulation. The whole control system is implemented by real hardware and experimented to compare the proposed vector control with the direct vector control. As a result of the experiment with two control methods in low speed, the torque ripple of the proposed vector control is improved by 45 percent than the direct vector control. And it is confirmed that the flux current ripple is reduced in 0.2 p.u. and torque current ripple is reduced in 0.6 p.u. It is confirmed that the rotor time constant by the estimation and the tunning algorithm is tunned by the real rotor time constant. Finally, it was confirmed that the validity and robustness for the proposed vector control in low speed existed.

• Journal of Sensor Science and Technology
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• v.9 no.2
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• pp.96-105
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• 2000

Fiber optic TR-EFPI(total reflected extrtinsic Fabry-Perot interferometric) sensor was developed to measure the strain of structures, such as building, bridge, aircraft, etc. It has been difficult to distinguish the increase and decrease of the strain from the conventional fiber optic EFPI sensor because their signals only have a sinusoidal wave pattern related to the change of strain. Also, the absolute strain could not be measured by the simple fiber optic EFPI sensor. In this study, in order to measure the magnitude of strain with the direction of strain, the fiber optic sensor was simply constructed with the total reflected EFPI sensor probe. This probe was manufactured with a single mode fiber and a mirror coated fiber in a silica glass capillary tube. The output signal of this fiber optic TR-EFPT sensor can give the information about the magnitude and the direction of strain. The loading-unloading test was performed by the universal testing machine with alluminum beam specimen to compare the strain from fiber optic TR-EFPI sensor with the value from electrical strain gauge. In the result of this experiment. the strain from fiber optic TR-EFPI sensor had a good agreement with the values from the electrical strain gauge.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.42-48
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• 2016

In this paper, a high-precision peak detector circuit that detects the output voltage information of a fly-back converter is proposed. The proposed design consists of basic analog elements with only one operational amplifier and three transistors. Because of its simple structure, the proposed circuit can minimize the delay time of the detection process, which has a strong impact on the precision of the regulation aspect of the fly-back converter. Furthermore, by using an amplifier and several transistors, the proposed detector can be fully integrated on-chip, instead of using discrete circuit elements, such as capacitors and diodes, as in conventional designs, which reduces the production cost of the fly-back converter module. In order to verify the performance of the proposed scheme, the peak detector was simulated and implemented by using a 0.35 m MagnaChip process. The gained results from the simulation with a sinusoidal stimulus signal show a very small detection error in the range of 0.3~3.1%, which is much lower than other reported detecting circuits. The measured results from the fabricated chip confirm the simulation results. As a result, the proposed peak detector is recommended for designs of high-performance fly-back converters in order to improve the poor regulation aspect seen in conventional designs.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.4
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• pp.65-73
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• 2003

This paper presents the implementation of an analog signal-processing ASIS to detect an angular velocity signal from a vibrator angular velocity detection sensor. The output of the sensor to be charge appeared as the variation of the capacitance value in the structure of the sensor was detected using charge amplifiers and a self oscillation circuit for driving the sensor was implemented with a sinusoidal self oscillation circuit using the resonance characteristics of the sensor. Specially an automatic gain control circuit was utilized to prevent the deterioration of self-oscillation characteristics due to the external elements such as the characteristic variation of the sensor process and the temperature variation. The angular velocity signal, amplitude-mod)Hated in the operation characteristics of the sensor, was demodulated using a synchronous detection circuit. A switching multiplication circuit was used in the synchronous detection circuit to prevent the magnitude variation of detected signal caused by the amplitude variation of the carrier signal. The ASIC was designed and implemented using 0.5${\mu}{\textrm}{m}$ CMOS process. The chip size was 1.2mm x 1mm. In the experiment under the supply voltage of 3V, the ASIC consumed the supply current of 3.6mA and noise spectrum density from dc to 50Hz was in the range of -95 dBrms/√Hz and -100 dBrms/√Hz when the ASIC, coupled with the sensor, was in normal operation.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.429-438
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• 1997

Mechanical valve is one of the most widely used implantable artificial organs of which the reliability is so important that its failure means the death of patient. Therefore early noninvasive detection is essentially required, though mechanical valve failure with thrombosis is the most common. The objective of this paper is to detect the thrombosis formation by spectral analysis and neural network. Using microphone and amplifier, we measured the sound from the mechanical valve which is attached to the pneumatic ventricular assist device. The sound was sampled by A/D converter(DaqBook 100) and the periodogram is the main algorithm for obtaining spectrum. We made the thrombosis models using pellethane and silicon and they are thrombosis model on the valvular disk, around the sewing ring and fibrous tissue growth across the orifice of valve. The performance of the measurment system was tested firstly using 1 KHz sinusoidal wave. The measurement system detected well 1KHz spectrum as expected. The spectrum of normal and 5 kinds of thrombotic valve were obtained and primary and secondary peak appeared in each spectrum waveform. We find that the secondary peak changes according to the thrombosis model. So to distinguish the secondary peak of normal and thrombotic valve quantatively, 3 layer back propagation neural network, which contains 7, 000 input node, 20 hidden layer and 1 output was employed The trained neural network can distinguish normal and valve with more than 90% probability. As a conclusion, the noninvasive monitoring of implanted mechanical valve is possible by analysing the acoustical spectrum using neural network algorithm and this method will be applied to the performance evaluation of other implantable artificial organs.