• Title/Summary/Keyword: 전기신호

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Sound Signal Analysis Using the Time-Frequency Representations (시주파수 표현법을 이용한 소리신호의 분석)

  • Iem, Byeong-Gwan
    • Journal of IKEEE
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    • v.23 no.3
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    • pp.893-898
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    • 2019
  • Time-frequency representations are methods to display the magnitude or energy density of a signal on the two dimensional plane of both time and frequency. They are useful in analyzing the characteristics of time-varying signals. Music is a typical time-varying signal, and it can be analyzed by time-frequency representations. Recently, it is popular to change the sound quality by attaching a safety sounder to an instrument. It is performed to improve perception subjectively by spending little cost and modifying sound quality. In time domain, it is difficult to notify the difference between music signals with and without the sounder. But, it is easy to find the difference in frequency domain or in time-frequency domain. In this paper, the music signal from a flute with sounder is analyzed both in the frequency domain and in the time-frequency domain. It is confirmed that the frequency components in the mid-frequency range of 500~2500 are reinforced.

Deep Learning based Raw Audio Signal Bandwidth Extension System (딥러닝 기반 음향 신호 대역 확장 시스템)

  • Kim, Yun-Su;Seok, Jong-Won
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.1122-1128
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    • 2020
  • Bandwidth Extension refers to restoring and expanding a narrow band signal(NB) that is damaged or damaged in the encoding and decoding process due to the lack of channel capacity or the characteristics of the codec installed in the mobile communication device. It means converting to a wideband signal(WB). Bandwidth extension research mainly focuses on voice signals and converts high bands into frequency domains, such as SBR (Spectral Band Replication) and IGF (Intelligent Gap Filling), and restores disappeared or damaged high bands based on complex feature extraction processes. In this paper, we propose a model that outputs an bandwidth extended signal based on an autoencoder among deep learning models, using the residual connection of one-dimensional convolutional neural networks (CNN), the bandwidth is extended by inputting a time domain signal of a certain length without complicated pre-processing. In addition, it was confirmed that the damaged high band can be restored even by training on a dataset containing various types of sound sources including music that is not limited to the speech.

Design of 4-Layer PCB Considering EMC for Automotive Bluetooth Speaker (차량용 블루투스 스피커를 위한 EMC를 고려한 4층 PCB 설계)

  • Yoon, Ki-Young;Kim, Boo-Gyoun;Lee, Seongsoo
    • Journal of IKEEE
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    • v.25 no.4
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    • pp.591-597
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    • 2021
  • This paper proposes an EMC-aware PCB design method to reduce electromagnetic emission, where trace length and teturn path of critical signal are shortened by changing chip location and trace layout on the PCB, while additional filters or decoupling capacitors are not required. In the proposed method, signal velocity is calculated for various signals on the PCB. Critical signal with the fastest signal velocity is determined and its return path is shortened as much as possible by placing chip location and trace routing first. Return path of critical signal should be carefully designed not to have discontinuity. Power plane and ground plane should be carefully designed not to be divided, since these planes are the reference of return path. The proposed method was applied to automotive directional Bluetooth speaker which failed to pass CISPR 32 and CISPR 25 EMC tests. Its PCB was redesigned based on the proposed method and it easily passed the EMC tests. The proposed method is useful to EMC-sensitive electronic equipments.

An Efficient Data Collection Method for Deep Learning-based Wireless Signal Identification in Unlicensed Spectrum (딥 러닝 기반의 이기종 무선 신호 구분을 위한 데이터 수집 효율화 기법)

  • Choi, Jaehyuk
    • Journal of IKEEE
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    • v.26 no.1
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    • pp.62-66
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    • 2022
  • Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.

A Residual Echo and Noise Reduction Scheme with Linear Prediction for Hands-Free Telephony (핸즈프리 전화기를 위한 선형 예측기를 이용한 잔여반향 및 잡음 제거 구조)

  • Hwang, Kyung-Rok;Son, Kyung-Sik;Kim, Hyun-Tae
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.5
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    • pp.454-460
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    • 2009
  • In this paper, we propose a residual echo and noise reduction scheme by using linear predictor for hands-free telephony applications. The proposed scheme whitens residual echo by the linear prediction during the non double-talk. But whitened residual echo signal still has speech characteristics. In this scheme, the whitened residual echo signal is more whitened by using the power of the linear prediction error signal and the linear predicted signal. After whitening process, near-end speech and ambient noise is present during double-talk but white noise will appear during non double-talk situation. By linearly predicting again the combined signal of the near-end speech and the whitened signal, the ambient noise is removed. Through computer simulation, it is shown that the proposed method performs well at the side of AIC (acoustic interference cancellation).

The Implementation of Sub-MRA PWM Technique Using DSP (DSP를 이용한 Sub-MRA PWM 기법의 실현)

  • 이성백;이종규;원영진;한완옥;박진홍
    • The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.8 no.2
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    • pp.41-45
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    • 1994
  • In this paper, it is implemented that Sub- MRA PWM techinque which is applied to MRA PWM technique using the Digital Signal Processor. Unstable element of analog is reduced for Sub - MRA PWM technique by digital signal pressing. And harmonic is analized by simulation to verify that. It is afford the process induction motor control with real time by minimizing the delay time of digital system. Time delay which is a defect of digital control can by minimized using fast caculation. Therefore, real time control is implemented in the induction motor

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A Study on the Detection of Ultrasonic Signal for the Diagnosis of Transformer (변압기 예방진단을 위한 초음파 신호 검출에 관한 연구)

  • 권동진;광희로
    • The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.9 no.6
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    • pp.65-70
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    • 1995
  • This paper describes the detection of the ultrasonic signals reduced by materials of a transformer for diagnosis of the transformer using ultrasonic signal which is generated by partial discharge. When partial discharge is generated on the surface of the winding and between the winding and the core in the transformer, the ultrasonic signal can be measured as the proper selection of the ultrasonic detectors' location.

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가전제품용 센서의 인텔리전트화

  • 대한전기협회
    • JOURNAL OF ELECTRICAL WORLD
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    • s.284
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    • pp.60-65
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    • 2000
  • 가전제품은 최근 수년 사이에 급격한 사회정세의 변화와 더불어 소비자의식에 대폭적인 변혁을 가져온 가운데 적절한 가격의 납득이 가는 진짜상품이 요구되는 추세이다. 한편 가전제품에서의 센서(Sensor)기술은, 참으로 성능쇄신의 요소기술을 담당하는 중요한 기술로 센서 그 자체의 고도화$\cdot$다양화에 더하여 마이크로 프로세서를 주체로 하는 지적인 신호처리에 의한 기능과 성능의 향상이 눈부신 바 있으며, 이 두 수레바퀴에 의하여 가전제품용 센서의 인텔리전트시스템이 구성되고 있다. 본고에서는 후자의 신호처리에 의한 인텔리전트화 기술을 지적제어 처리로 간주하여, 센싱 기술에서의 지적제어처리의 자리매김과 구체적인 가전품에서의 응용 예로서 세탁기에 지적제어처리를 탑재하여 기능 향상을 도모한 개발사례를 중심으로 그 개요를 소개한다. 최근의 개발사례로서 세탁기, 에어컨, 냉장고, 청소기 등에 퍼지제어나 뉴럴네트워크, 또한 비선형 처리 등의 응용 예를 표로서 나타내었다. 특히 세탁기에서는 모터의 회전수를 검출하는 회전센서출력의 처리에 의해 다음의 두가지 센싱시스템을 개발하였다. (1) 부하량 검지 시스템 무단계 부하량 검출을 실현하여 검출오차를 약 1/3로 저감시킴과 동시에 에너지 절약(물$\cdot$세제$\cdot$시간)을 도모한다. (2) 언밸런스 건지 시스템 속도감속 성분량 추출에 의한 검출정도 향상과 현행센서 삭제에 의한 코스트 저감을 이룬다.

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BLDC Motor Control for Plug-In Door (플러그인 도어용 BLDC 전동기 제어)

  • Chun, Jang-Sung;Hwang, Sang-Yeon;Kim, Won-Il;Lee, Jung-Sik;Im, Seung-Kwan
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.774-775
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    • 2008
  • 본 논문에서는 전동차용 전기식 플러그인 도어를 구동하기 위해 영구자석형 무정류자 직류전동기(Brushless DC Motor)를 적용하였다. BLDC 전동기의 속도제어를 위해 사용되어지는 홀센서 신호를 속도제어로만 사용하는 것이 아니라 이러한 홀센서 파형을 검출, 위치제어를 위한 신호로 활용하였으며 실제로 도어시스템에 적용, 실험하여 그 가능성을 확인하였다.

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The synchronization of voltage-current waveform and high-speed camera image (전압-전류 파형과 고속카메라 영상의 동기화)

  • Yun, Ji-Ho;Noh, Choong-Ho;Park, Ji-Hun;Park, Jong-Hwa
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.5-6
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    • 2008
  • 차단기, 개폐기, 배전반과 같은 전력기기에 대한 성능시험시, 전압과 전류, 제어신호를 측정하고, 필요한 경우 고속카메라를 이용해 시험장면을 촬영한 다음, 이들을 종합적으로 분석하여 시험결과를 판정한다. 이때, 대부분 개별 시스템으로 전압-전류 시험파형과 시험영상을 측정하고 분석하기 때문에, 시간 동기화가 불가능하여 시험현상이나 시료동작특성 분석에 많은 어려움이 있다. 따라서 개별 시스템으로 측정한 신호를 동기 시켜 동시에 분석할 수 있는 프로그램이 있다면, 시험결과 판정뿐만 아니라 시험 중에 발생하는 전기적 과도현상이나 시료의 동작특성분석에 많은 도움이 될 것이다. 이러한 목적을 위해, PT&T에서는 측정시스템과 고속카메라를 이용하여 측정한 전압-전류 시험파형과 시험영상을 동기 시켜 동시에 분석할 수 있는 프로그램인 Dual Viewer를 개발하였다. 본 논문에서는 Dual Viewer에 대한 기능과 특징에 대해 소개하고자 한다.

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