• 제목/요약/키워드: Abnormal Noise

검색결과 236건 처리시간 0.022초

선내 회전장비의 이상진동 진단 시스템 개발 (Development of Vibration Diagnosis System for Rotating Machinery Onboard Ships)

  • 김극수;최수현;백일국
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2001년도 추계학술대회논문집 II
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    • pp.1067-1072
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    • 2001
  • In this study, the vibration diagnosis program for onboard machinery has been developed. The developed program includes signal monitoring module, system diagnosis module, and system modification module. The signal monitoring module is to monitor the vibration signal in time and frequency domains. And the system diagnosis module, which is developed by using Neural Network with error back propagation algorithm, can detect the abnormal symptom indicating the malfunction of the machinery onboard ships. The investigations of the developed system are presented through the experiment using Rotor Kit. Abnormal vibration signals are created by adding additional weight, manually misaligning the shaft, and loosening the bolts.

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공장자동화를 위한 소음 자동검사 시스템의 개발에 관한 연구 (Development of an Automatic Noise Detection System for Factory Automation)

  • 윤강섭;김현기;이만형;이권순
    • 한국정밀공학회지
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    • 제9권2호
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    • pp.128-137
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    • 1992
  • An automatic noise detection system is developed to sense abnormal noises in operating a microwave electronic range. A noise detection method is presented which accounts for the effects of backgound and dynamic noises of the range. A recursive formula used as a noise estimator is a special case of the discrete-time Kalman filter in stochastic processes. Noise levels were measured using a noise acquisition processor in a closed room free of background noise, and detected signals were processes using a microcomputer. The results obtaines showed that the fault detection system should be fast in response to the data acquired and should be high in accuracy and reliability.

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공분산 및 신호관리를 이용한 RF탐색기 시선각 변화율 추정기법 (RF Seeker LOS Rate Estimation Method using Covariance and Signal Management)

  • 문관영;전병을
    • 한국항공우주학회지
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    • 제40권4호
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    • pp.292-299
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    • 2012
  • 칼만 필터를 이용하여 RF 탐색기의 시선각 변화율 추정을 수행하였다. 김발형 탐색기의 모델링을 기반으로 칼만필터를 설계하였다. 필터 설계 시 주요한 인자인 공정 잡음 및 측정 잡음의 특성에 대해 살펴보았으며, RF 탐색기의 신호 특성에 맞는 측정 잡음치를 선정하여 필터링을 수행하였다. 측정 잡음관리를 위해 SNR 및 관련 신호를 이용하였으며, 공정 잡음에 따른 필터의 민감도 확인을 위해 대수적 방식을 사용하였다. 일식 등으로 탐색기 신호가 없는 경우 선형 해석을 통해 필터의 안정도를 분석하였다. 수치 시뮬레이션을 통해 제안된 시선각 변화율 추정기법의 타당성을 검토하였다.

산업 설비의 이상 진동 감지를 위한 스마트 센싱 디바이스의 개발 (A Development of Smart Sensing Device for Monitoring Abnormal Vibration of Industrial Equipment)

  • 류대현;최태완
    • 한국전자통신학회논문지
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    • 제12권2호
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    • pp.361-366
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    • 2017
  • 산업체 전반의 주요 설비에서 이상 상태는 온도의 이상 상승, 진동과 소음의 변화를 수반하여 나타나게 된다. 본 연구에서는 BLE 를 탑재한 스마트 센싱 모듈를 개발하고, MEMS 기반의 가속도 센서를 인터페이스하여, 설비의 자체결함으로 인한 이상진동을 감지할 수 있는 스마트 센싱 디바이스를 개발하였다. 본 연구에서 개발한 스마트 센싱장치는 좁은 공간에 쉽게 설치하여, 설비의 진동상태를 실시간으로 모니터링 할 수 있으며, 어레이 LED 디스플레이로 정상상태와 문제 발생상태를 간편하게 사용자에게 알려줄 수 있다.

환경소음.진동 피해 분쟁 조정을 위한 기준설정에 관한 소고 (A brief review on the standards of regulations and compensation in the environmental noise and vibration disputes resolution)

  • 이수갑;김재환;김규태;홍지영;은희준
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2008년도 춘계학술대회논문집
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    • pp.876-878
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    • 2008
  • The standards of acceptable limit and compensation is one of the most important things in environmental noise and vibration disputes resolution. In this paper, review on the present acceptable limit level and compensation standard in National Environmental Dispute Resolution Commission is introduced. Discordance of standards between in the regulation law and in the dispute resolution commission and it's improvement are discussed. Abnormal reasoning for compensation standards is pointed out from a author's private view.

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상관관계 기반 신호 분류를 이용한 비정상 호흡 상태 모니터링 시스템 (Cross Correlation based Signal Classification for Monitoring System of Abnormal Respiratory Status)

  • 이덕우
    • 한국산학기술학회논문지
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    • 제21권5호
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    • pp.7-13
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    • 2020
  • 본 논문에서는 사람의 비정상적인 호흡과 정상적인 호흡 신호를 획득한 후, 이 신호들을 분석하고, 특히 비정상 호흡신호를 감지하는 방법과 정상 및 비정상 신호를 분류하는 방법을 제시한다. 본 연구에서 사람의 호흡신호는 BIOPAC 장비를 활용하여 획득하며, 사람의 호흡 상태를 정량적인 수치 정보를 활용하여 판단한다. 궁극적으로 본 논문에서는 일반 환경에서 사람의 호흡상태를 신호로 획득하여 분석하고, 호흡상태를 모니터링 할 수 있는 시스템을 개발하고자 하며, 무호흡 상태를 감지 할 수 있는 방법을 제안한다. 획득되는 호흡신호를 활용하여 정량적인 정보를 바탕으로 호흡신호를 상태에 따라 분류한다. 접촉식 의료장비를 활용하여 호흡신호를 획득하고 호흡상태를 분류하기 전에 잡음제거 알고리즘을 적용한다. 기존의 사비츠키-골레이 필터와 중간값 필터의 장점만을 활용하여 혼합필터를 사용하여 신호를 분석하기에 적절한 상태가 되도록 한다. 서로 다른 호흡 상태, 즉 서로 다른 클래스간 거리는 최대로 하고, 동일한 호흡상태, 즉 같은 클래스 간의 거리는 최소로 하기 위해 신호 획득후 신호의 특징값들 간의 상호상관 계수를 계산한다. 제안하는 알고리즘은 실제 호흡 환경에 적용할 수 있을 정도로 직관적이고, 제안하는 방법을 증명하기 위한 실험 결과들을 함께 제시한다.

가정용 에어컨 실외기의 기동 소음 분석 (The correlation between noise of outdoor unit and thermodynamic properties of cycle at transient condition of room air-conditioner)

  • 손영부;이승목;하종훈;이병철
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2012년도 추계학술대회 논문집
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    • pp.577-582
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    • 2012
  • Recently, noise reduction of air-conditioner is one of the important design factors for high quality product. Especially, customer complaints arise due to noise problem of the outdoor unit. After the operation of air-conditioner start, noise level of outdoor unit is increased gradually and sometimes abnormal noise occurs until it reaches steady state condition. The aim of this paper is to investigate the relation between noise of outdoor unit and thermodynamic properties of cycle at transient condition of room air-conditioner. In order to find out the noise characteristics of outdoor unit, noise and vibration measurements are carried out. Also, the thermodynamic properties of compressor and heat exchanger are measured by using temperature and pressure sensors and experimental results are discussed. Finally, we find out the relation between noise and cycle properties at starting of room air-conditioner and the improvement method to reduce noise level is proposed.

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비정상 호흡 감지를 위한 신호 분석 (Signal Analysis for Detecting Abnormal Breathing)

  • 김현진;김진현
    • 센서학회지
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    • 제29권4호
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    • pp.249-254
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    • 2020
  • It is difficult to control children who exhibit negative behavior in dental clinics. Various methods are used for preventing pediatric dental patients from being afraid and for eliminating the factors that cause psychological anxiety. However, when it is difficult to apply this routine behavioral control technique, sedation therapy is used to provide quality treatment. When the sleep anesthesia treatment is performed at the dentist's clinic, it is challenging to identify emergencies using the current breath detection method. When a dentist treats a patient that is under the influence of an anesthetic, the patient is unconscious and cannot immediately respond, even if the airway is blocked, which can cause unstable breathing or even death in severe cases. During emergencies, respiratory instability is not easily detected with first aid using conventional methods owing to time lag or noise from medical devices. Therefore, abnormal breathing needs to be evaluated in real-time using an intuitive method. In this paper, we propose a method for identifying abnormal breathing in real-time using an intuitive method. Respiration signals were measured using a 3M Littman electronic stethoscope when the patient's posture was supine. The characteristics of the signals were analyzed by applying the signal processing theory to distinguish abnormal breathing from normal breathing. By applying a short-time Fourier transform to the respiratory signals, the frequency range for each patient was found to be different, and the frequency of abnormal breathing was distributed across a broader range than that of normal breathing. From the wavelet transform, time-frequency information could be identified simultaneously, and the change in the amplitude with the time could also be determined. When the difference between the amplitude of normal breathing and abnormal breathing in the time domain was very large, abnormal breathing could be identified.

자기조직화특징지도와 학습벡터양자화를 이용한 회전기계의 이상진동진단 알고리듬 (Abnormal Vibration Diagnostics Algorithm of Rotating Machinery Using Self-Organizing Feature Map nad Learing Vector Quantization)

  • 양보석;서상윤;임동수;이수종
    • 소음진동
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    • 제10권2호
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    • pp.331-337
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    • 2000
  • The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Many research has been conducted to manipulate field vibration signal data for diagnosing the fault of designated machinery. As the pattern recognition tool of that signal, neural network which use usually back-propagation algorithm was used in the diagnosis of rotating machinery. In this paper, self-organizing feature map(SOFM) which is unsupervised learning algorithm is used in the abnormal defect diagnosis of rotating machinery and then learning vector quantization(LVQ) which is supervised learning algorithm is used to improve the quality of the classifier decision regions.

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An Extended Scalar Adaptive Filter for Mitigating Sudden Abnormal Signals of Guided Missile

  • Lim, Jun-Kyu;Park, Chan-Gook
    • International Journal of Aeronautical and Space Sciences
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    • 제12권1호
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    • pp.37-42
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    • 2011
  • An extended scalar adaptive filter for guided missiles using a global positioning system receiver is presented. A conventional scalar adaptive filter is adequate filter for eliminating sudden abnormal jumping measurements. However, if missile or vehicle velocities have variation, the conventional filter cannot eliminate abnormal measurements. The proposed filter utilizes an acceleration term, which is an improvement not used in previous conventional scalar adaptive filters. The proposed filter continuously estimates noise measurement variance, velocity error variance and acceleration error variance. For estimating the three variances, an innovation method was used in combination with the least square method for the three variances. Results from the simulations indicated that the proposed filter exhibited better position accuracy than the conventional scalar adaptive filter.