• Journal of IKEEE
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• v.22 no.3
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• pp.822-828
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• 2018

Recently, energy issues such as massive blackout due to increase in power consumption have been emerged, and it is necessary to improve the accuracy of prediction of power consumption as a solution for these problems. In this study, we investigate the difference between the actual power consumption and the predicted power consumption through the deep learning- based power consumption forecasting experiment, and the possibility of adjusting the power reserve ratio. In this paper, the prediction of the power consumption based on the deep learning can be used as a basis to reduce the power reserve ratio so as not to excessively produce extra power. The deep learning method used in this paper uses a learning model of long-short-term-memory (LSTM) structure that processes time series data. In the computer simulation, the generated power consumption data was learned, and the power consumption was predicted based on the learned model. We calculate the error between the actual and predicted power consumption amount, resulting in an error rate of 21.37%. Considering the recent power reserve ratio of 45.9%, it is possible to reduce the reserve ratio by 20% when applying the power consumption prediction algorithm proposed in this study.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.9
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• pp.799-804
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• 2016

Broadband powerline communication (BPLC) uses distribution lines as a medium for achieving effective bidirectional data communication along with electric current flow. As the material characteristics of power lines are not good at the communication channel, the development of power line communication (PLC) systems for internet, voice, and data services requires measurement-based models of the transfer characteristics of the network suitable for performance analysis by simulation. In this paper, an analytic model describing a complex transfer function is presented to obtain the attenuation and path parameters for a multipath power line model. The calculated results demonstrated frequency-selective fading in multipath channels and signal attenuation with frequency, and were in good agreement with the experimental results. Inductive coupling units are used as couplers for coupling the signal to the power line to avoid physical connections to the distribution line. The inductance of the ferrite core, which depends on the frequency, determines the cut-off frequency of the inductive coupler. Coupling loss can be minimized by increasing the number of windings around the coupler. Coupling efficiency was improved by more than 6 dB with three windings compared to the results obtained with one winding.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.447-454
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• 2011

Power-line interference(PLI) can distort certain regions in analysing the ECG signal. In particular, the regions such as P and R wave that are important element in diagnosing with arrhythmia is expressed as different type of noise according to the case whether power-line frequency is multiples of sampling frequency and or not. Noise characteristics is also divided into linearity and non-linearity. In this paper, adaptive subtraction method for removing variable PLI of ECG signal is proposed. We classify the multiple relationship between power line and sampling frequency as Multiple and Non-multiple. PLI of Linear segment is extracted through moving average filter, PLI of non-linear segment is extracted through the interference component that is extracted in the linear segment and stored in the temporary buffer. The performance of P wave and R wave detection is evaluated by using 119 data record of MIT-BIH arrhythmia database. The achieved scores indicate P wave detection rate of 97.91%, R wave detection rate of 96.66% and P wave detection rate of 99.01%, R wave detection rate of 97.93% accuracy respectively for Notch filter and proposed subtraction method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.109-116
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• 2022

In this paper, we propose a band rejection filter (BRF) with a state variable filter (SVF) structure to effectively remove the influence of 60 Hz line frequency noise introduced into the sensor system. The conventional BRF of the SVF structure uses an additional operational amplifier (OPAMP) to add a low pass filter (LPF) output and a high pass filter (HPF) output or an input signal and a band pass filter. Therefore, the notch frequency and the notch depth that determine the signal attenuation of the BRF greatly depend on the tolerance of the resistors used to obtain the sum or difference of the signals. On the other hand, in the proposed BRF, since the BRF output is formed naturally within the SVF structure, there is no need for a combination between each port. The notch frequency of the proposed BRF is 59.99 Hz, and it can be confirmed that it is not affected at all by the tolerance of the resistor through the Monte Carlo simulation results. The notch depth also has an average of -42.54dB and a standard deviation of 0.63dB, confirming that normal operation as a BRF is possible. Also, with the proposed BRF, noise filtering was applied to the electrocardiogram (ECG) signal that interfered with 60 Hz noise, and it was confirmed that the 60 Hz noise was appropriately suppressed.