• Title/Summary/Keyword: Signal Detection

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진동 신호 이용 모델 기반 모터 결함 검출 시스템 개발 (Development of a Model-Based Motor Fault Detection System Using Vibration Signal)

  • 임호순;;정길도
    • 제어로봇시스템학회논문지
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    • 제9권11호
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    • pp.874-882
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    • 2003
  • The condition assessment of engineering systems has increased in importance because the manpower needed to operate and supervise various plants has been reduced. Especially, induction motors are at the core of most engineering processes, and there is an indispensable need to monitor their health and performance. So detection and diagnosis of motor faults is a base to improve efficiency of the industrial plant. In this paper, a model-based fault detection system is developed for induction motors, using steady state vibration signals. Early various fault detection systems using vibration signals are a trivial method and those methods are prone to have missed fault or false alarms. The suggested motor fault detection system was developed using a model-based reference value. The stationary signal had been extracted from the non-stationary signal using a data segmentation method. The signal processing method applied in this research is FFT. A reference model with spectra signal is developed and then the residuals of the vibration signal are generated. The ratio of RMS values of vibration residuals is proposed as a fault indicator for detecting faults. The developed fault detection system is tested on 800 hp motor and it is shown to be effective for detecting faults in the air-gap eccentricities and broken rotor bars. The suggested system is shown to be effective for reducing missed faults and false alarms. Moreover, the suggested system has advantages in the automation of fault detection algorithms in a random signal system, and the reference model is not complicated.

A Design of Snoring Detection System using Chaotic Signal

  • Choo, Yeon-Gyu
    • Journal of information and communication convergence engineering
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    • 제8권5호
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    • pp.560-565
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    • 2010
  • In this study, the existence of chaotic characteristics in snoring signals obtained in the form of time series data was checked through quantitative and qualitative analysis methods, and a snoring signal detection system was designed applied with detection algorithms considering diverse parameters of occurring signals in order to enhance the accuracy and reliability of detections and the performance of the system was checked. The system was tested with certain snoring patients and thereby the results as follows could be obtained.

차량검지를 위한 세그먼트에 기반을 둔 신호처리 알고리즘 (Segmentation-based Signal Processing Algorithm for Vehicle Detection)

  • 고기원;우광준
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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    • pp.306-308
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    • 2005
  • The vehicle detection method using pulse radar has the advantage of maintenance in comparison with loop detection method. We have the information about the vehicle being and position by dividing the signals into sectors in accordance with SSC method, and by applying the discriminant function based on stochastical data. We also reduce the signal processing time.

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HSI 색상 모델에서 색상 분할을 이용한 교통 신호등 검출과 인식 (Traffic Signal Detection and Recognition Using a Color Segmentation in a HSI Color Model)

  • 정민철
    • 반도체디스플레이기술학회지
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    • 제21권4호
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    • pp.92-98
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    • 2022
  • This paper proposes a new method of the traffic signal detection and the recognition in an HSI color model. The proposed method firstly converts a ROI image in the RGB model to in the HSI model to segment the color of a traffic signal. Secondly, the segmented colors are dilated by the morphological processing to connect the traffic signal light and the signal light case and finally, it extracts the traffic signal light and the case by the aspect ratio using the connected component analysis. The extracted components show the detection and the recognition of the traffic signal lights. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the detection and the recognition of traffic signals.

자동 연상 기억장치 신경망을 이용한 음향 표적의 신호 주파수선 탐지 (Detection of Signal Frequency Lines for Acoustic Target using Autoassociative Momory Neural Network)

  • 이성은;황수복;남기곤;김재창
    • 한국음향학회지
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    • 제15권5호
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    • pp.118-124
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    • 1996
  • 수동 소나 시스템에서 표적을 탐지, 식별하는데 가장 중요한 인자는 표적소음에서 나타나는 신호 주파수선 성분이다. 수중의 주변잡음과 표적소음이 복합된 환경에서 표적의 신호 주파수선 성분을 정확히 추출하는데는 신호 탐지 문턱값 설정이나 주변잡음의 변화 때문에 어려움이 따른다. 이 연구에서는 자동 연상 기억장치 신경망을 이용하여 신호 탐지 문턱값 설정이나 주변잡음의 변화에 강인한 음향 표적의 신호 주파수선 탐지 방식을 제안한다. 모의 실험 및 실제 표적 신호에 적용하여 제안한 방식이 우수한 신호 주파수선 탐지성능을 나타냄을 보인다.

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음향방출 신호를 이용한 압력용기의 누설 검사기법 개발 (Leak Detection Technique of Pressure Vessel Using Acoustic Emission Signal)

  • 이성재;정연식;강명창;김정석
    • 한국공작기계학회논문집
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    • 제13권4호
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    • pp.95-99
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    • 2004
  • In this study, the leak detection technique of pressure vessel by using acoustic emission(AE) signal is suggested experimentally. The leak of pressure vessel is located at the welding line due to welding defects. we measured the AE signal using Rl5I sensor, and examined the AE parameters in leak condition. It is investigated that the mean value of AE signal is dependent on leak source location. So the absolute mean value of AE signal is adopted as dominant AE parameter. We proposed leak detection algorithm using AE signal mean value for monitoring the leak source location.

DSP를 이용한 FMCW 레이다 신호처리 알고리즘 (Signal Processing Algorithm of FMCW RADAR using DSP)

  • 한성칠;박상진;강성민;구경헌
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2001년도 하계종합학술대회 논문집(1)
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    • pp.425-428
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    • 2001
  • In this paper, FMCW radar signal processing technique for the vehicle detection system are studied. And FMCW radar sensor is used as a equipment for vehicle detection. To test the performance of developed algorithm, the evaluation of the algorithm is done by simulation for signal processing technique of vehicle detection system. RADAR signal of a driving vehicle is generated by using the Matlab. Distance and velocity of vehicles are calculated with developed a1gorithm. Also the signal processing procedure is done for the virtual data with FM-AM converted noise.

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수신 신호 변화를 활용한 화재 감지 기법 (The Fire Detection Scheme Utilizing Received Signal Variation)

  • 하경욱;김동완
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2018년도 추계학술대회
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    • pp.251-254
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    • 2018
  • 주변 환경 변화에 따라 무선 수신 신호가 변화되는 현상을 활용한 Internet of Things(IoT) 시스템에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 고정된 송수신기 간 주기적 신호 교환 시, 수신 신호가 주변 온도 변화에 따라 변화함을 증명하고, 수신 신호 변화를 활용한 화재 감지 기법을 제안한다. 제안 기법은 수신 신호 변화 감지부와 수신기 내부 온도 감지부로 구성되며, 수신기 내부 온도 감지부는 무선 채널 환경 변화에 따른 수신 신호 변화를 화재 발생으로 감지됨을 방지한다. 제안 기법은 화재 감지를 위해 별도의 장치 추가 없이 기존 수신기에 소프트웨어 개선을 통해 지원가능하다는 장점을 지닌다.

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GPS L1 C/A 기만 신호 검출 기법 설계 (Design of GPS L1 C/A Spoofing Signal Detection Algorithm)

  • 임순;임덕원;허문범;남기욱
    • 한국항행학회논문지
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    • 제18권1호
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    • pp.7-13
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    • 2014
  • 본 논문에서는 GPS 전파 간섭 신호의 한 종류인 기만 신호를 검출하는 기법을 제안한다. 본 논문에서 기만의 대상이 되는 신호에는 민간에 구조가 공개된 GPS L1 C/A 신호로 선정하였으며 GPS L1 C/A 기만 신호의 영향을 분석하고 이를 통해서 기만 신호 검출 기법을 제안한다. 제안하는 기만 신호 검출 기법은 상관함수가 왜곡된 정도로 기만 신호의 인가를 판단한다. 기만 신호의 판단기준은 수신기 열잡음의 통계적 특성으로부터 정량적인 수치로 계산된 임계값을 이용하였다. 제안하는 기법을 검증하기 위한 시뮬레이션은 MATLAB을 기반으로 구성하였으며 기만 신호에 의한 상관함수 왜곡 및 코드 위상 오차를 확인하였다. 그리고 본 논문에서 제안하는 기만 신호 검출 기법을 적용하여 기만 신호의 검출 시뮬레이션을 수행하여 제안하는 기법에 의한 기만 신호 검출성능을 확인하였다.

실시간 차량 검지를 위한 펄스 레이더 신호처리 알고리즘 (Real-time Pulse Radar Signal Processing Algorithm for Vehicle Detection)

  • 류석경;우광준
    • 제어로봇시스템학회논문지
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    • 제12권4호
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    • pp.353-357
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    • 2006
  • The vehicle detection method using pulse radar has the advantage of maintenance in comparison with loop detection method. We propose the pulse radar signal processing algorithm in which we devide the trace. data from pulse radar into segments by using SSC concept, and then construct the sectors in accordance with period and amplitude of segments, and finally decide the vehicle detection probability by applying the SSC parameters of each sectors into the discriminant function. We also improve the signal processing time by reducing the quantities of processing data and processing routines.