• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.43-50
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• 2022

Correlation Power Analysis(CPA) is a sub-channel attack method that measures the detailed power consumption of attack target equipment equipped with cryptographic algorithms and guesses the secret key used in cryptographic algorithms with more than 90% probability. Since CPA performs analysis based on statistics, a large amount of data is necessarily required. Therefore, the CPA must measure power consumption for at least about 15 minutes for each attack. In this paper proposes a method of using a Convolutional Neural Network(CNN) capable of accumulating input data and predicting results to solve the data collection problem of CPA. By collecting and learning the power consumption of the target equipment in advance, entering any power consumption can immediately estimate the secret key, improving the computational speed and 96.7% of the secret key estimation accuracy.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.6-12
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• 2011

The fast growing of the number of users requires the development of reliable communication systems able to provide higher data rates. In order to meet those requirements, techniques such as Multiple Input Multiple Out (MIMO) and Orthogonal Frequency Division multiplexing (OFDM) have been developed in the recent years. In order to combine the benefits of both techniques, the research activity is currently focused on MIMO-OFDM systems. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions; and using sub-carrier frequency, and power allocation techniques. Depending on how accurate the feedback-based system obtain the channel state information (CSI) and feed it back to the transmitter without delay, the overall system performance would be poor or optimal. In this paper, we propose a Signal to Noise Ratio (SNR) estimation algorithm where the preamble is known for both sides of the transciever. Through simulations made over several channel environments, we prove that our proposed SNR estimation algorithm is more accurate compared with the traditional SNR estimation.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.219-225
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• 1999

Monitoring of the cutting force signals in cutting process has been well emphasized in machine tool communities. Although the cutting force can be directly measured by a tool dynamometer, this method is not always feasible because of high cost and limitations in setup. In this paper an indirect cutting force monitoring system is developed so that the cutting force in turning process is estimated based on a AC spindle drive model. This monitoring system considers the cutting force as a disturbance input to the spindle drive and estimates the cutting force based on the inverse dynamic model. The inverse dynamic model represents the dynamic relation between the cutting force, the motor torque and the motor power. The proposed monitoring system is realized on a CNC lathe and its estimation performance is evaluated experimentally.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.53-55
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• 2007

Industrial interest in switched reluctance moor (SRM) drives has varied since 1850s. This has been primarily due to the emerging markets for variable speed drives in consumer and industrial products, such as home appliances, air conditioning, hand tools, fans, pump motor, etc. However, SRM has been plagued with the acoustic noise and vibration problem by input power of fixed section. Therefore, This paper offers electromagnetic analysis for torque ripple reduction in mechanical geometry and electric parameters. This means that the rotor pole arc and electric parameters have related to produce the active and negative torque. This analysis results are verified by the finite element method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.75-80
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• 1998

Statistical Energy Analysis(SEA) has been considered as a possible method for predicting responses of complex structures, especially at higher frequencies. In this paper, an SEA model of vehicle was built using 138 energy storing subsystems connected together using 1019 junctions. SEAM software program was used to build and calculate the model. To demonstrate the accuracy of the SEA model, predicted response levels were compared with measured levels. The source input levels were measured at the engine mounting parts. For the vibration levels, the agreement between the calculation results and the experimental ones was found to be good. The energy flow between connected subsystems can be presented, because the analysis method is based on the estimation of the power flow between subsystems. This paper also identifies some dominant energy flow paths from sources. It is finally presented that the SEA model can optimize the design parameters of vehicles using model parameters and energy flow paths.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.250-255
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• 1993

In this paper, for detection and isolation of instrument and process faults related with steam generator(S/G) in nuclear power plant, two types of observers are designed based on the linearized dynamic model of S/G : a bank of Dedicated Observers (DOS) for instrument faults detection and a bank of Unknown Input Observers(UIO) for process faults detection. And then, they are combined to decide which one between the above two faults occurs. In principle, the failure in ith instrument(process) can be isolated by monitoring the error between the ith output and its estimation obtained from the ith DOS(UIO). It is shown via computer simulations that the present scheme is feasible in finding out the source of a fault.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.11-15
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• 1999

Monitoring of the cutting force signals in cutting process has been well emphasized in machine tool communities. Although the cutting force can be directly measured by a tool dynamometer, this method is not always feasible because of high cost and limitations in setup. In this paper an indirect cutting force monitoring system is developed so that the cutting force in turning process is estimated based on a AC spindle drive model. This monitoring system considers the cutting force as a disturbance input to the spindle drive and estimates the cutting force based on the inverse dynamic model. The inverse dynamic model represents the dynamic relation between the cutting force, the motor torque and the motor power. The proposed monitoring system is realized on a CNC lathe and its estimation performance is evaluated experimentally.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.333-335
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• 2005

In this paper, supposed to solve these problem to PID parameters controller algorithm using ANN. In the proposed algorithm, the parameters of the controller were adjusted to reduce by on-line system the error of the speed of IM. In this process, EBPANN was constituted to an output error value of an IM and conspired an input and output. The performance of the self-tuning controller is compared with that of the PID controller tuned by conventional method (Ziehler-Nichols). The effectiveness of the proposed control method is verified thought the Matlab Simulink and experimental results.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.237-239
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• 2005

This paper describes the ultra precise position estimation of a servomotor using sinusoidal encoder based on Arcsine Interpolation Method. The amplitude and offset errors of the sinusoidal encoder output signals are effectively compensated and on-line tuned by utilizing a low cost programmable differential amp without any special expensive equipments. To theoretically evaluate the practical resolution of this system, the relationship between the amplitude of A/D converter input signal errors and the anticipated resolution is briefly dealt with. The performance of the proposed method is verified by the experiments, by comparing it with position and speed control characteristics of the servomotor driving system using a digital incremental 50,000ppr encoder.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.316-318
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• 1993

In order to estimation the optimum PID parameter of the turbine speed controller, the response cure of the object plant was compared with the reference pattern and then the magnitude peak value error and peak time error was calculated. With the calculated errors as input into the Fuzzy inference Method was introduced to propose the tuning method for each parameter. And the computer simulation was performed with the above Fuzzy inference method in which the Chunju hydro power plant turbine governor system was used as a model. This Study also aims to develop the exclusive tuner for govenor using industrial computer.