• 소음진동
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• 제9권2호
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• pp.393-400
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• 1999

Defect frequencies of rolling element bearings are experimentally investigated utilizing the two-sided directional spectra of the complex-valued vibration signals measured from the outer ring of defective bearings. The directional spectra make it possible to discern backward and forward defect frequencies. The experimental results show that the directional zoom spectrum is superior to the conventional spectrum in identification of bearing defect frequencies, in particular the inner race defect frequencies.

• 대한기계학회논문집A
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• 제28권10호
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• pp.1492-1499
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• 2004

In this paper, defect formation in ring rolling is revealed by computer simulation of ring rolling processes. The rigid-plastic finite element method is employed for this study. An analysis model having relatively fine mesh system near the roll gap is used for reducing the computational time and a scheme of minimizing the volume change is applied. The formation of the central cavity formation defect in ring rolling of a taper roller bearing outer race and the polygonal shape defect in ring rolling of a ball bearing outer race has been simulated. It has been seen that the results are qualitatively good with actual phenomena.

• 한국음향학회지
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• 제14권2호
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• pp.92-100
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• 1995

본 연구에서는 결함이 있는 볼베어링을 모델링하여 결함의 형태별로 진동분석을 하였다. 진동측정은 단일결함과 복합결함이 있는 볼베어링에 대하여 결함위치와 회전속도 변화에 대한 진동신호를 측정하고, 신호 성분들은 고주파 공진기법을 이용해 FFT시켰다. 실험결과 단일결함과 복합결함이 있을 때 결함으로 인해 발생하는 주파수는 결함 특성 주파수와 그 배수의 고조파 성분 피크들이 나타남을 확인하였다. 고주파 공진기법을 이용한 신호처리는 결함의 유무 뿐만 아니라 결함의 부위도 진단이 가능함을 알 수 있었다.

• 전기전자학회논문지
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• 제26권2호
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• pp.319-328
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• 2022

베어링은 기계가 작동할때 중요한 역할을 한다. 때문에, 베어링에 결함이 발생하면 기계전체의 치명적인 결함을 발생시킨다. 그러므로 베어링 결함은 조기에 발견되어야한다. 본 논문에서는 연속 웨이블릿 변환과 Switchable 정규화를 기반으로 한 합성곱 신경망(SN-CNN)을 이용한 방법을 베어링 결함 감지 모델에 대해 설명한다. 모델의 정확도는 Case Western Reserve University(CWRU) 베어링 데이터 집합을 사용하여 측정되었다. 또한 배치 정규화(BN, Batch Normalization)[1] 방법과 스펙트로그램 이미지가 모델 성능의 비교를 위해 사용되었다.

• 한국안전학회지
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• 제11권2호
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• pp.42-51
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• 1996

Taper roller bearing is used on rotating shaft where radial and thrust loads are attended. To avoid the sudden failure and maintain the good condition of rotating machinery it is necessary to monitor the condition of bearing and diagnose the defect of bearing. In this study the diagnosis program of taper roller bearing which is used on the lower bearing of V.A.W.T. (Vertical Axis Wind Turbine) is developed. By plenty of test the database is constructed and by Gaussian distribution obtained from database the defect probability of bearing is calculated.

• 한국생산제조학회지
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• 제6권4호
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• pp.46-53
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• 1997

This paper presents a method of detection localized defects on tapered roller bearing in main spindle of machine tool system. The feature vectors, i.e. statistical parameters, in time-domain analysis technique have been calculated to extract useful features from acoustic emission signals. These feature vectors are used as the input feature of an neural network to classify and detect bearing defects. As a results, the detection of bearing defect conditions could be sucessfully performed by using an neural network with statistical parameters of acoustic emission signals.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 춘계학술대회 논문집
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• pp.451-452
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• 2007

• 한국음향학회지
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• 제16권4호
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• pp.21-28
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• 1997

본 연구에서는 빈경하중과 축회전 속도를 변화시켜 가며 하중으로 인한 베어링의 부하-변위량 특성을 Harris 이론과 비교분석하였다. 실험결과 결함이 없는 경우 하중이 적을 때는 Harris이론과 비교적 잘 일치하나, 하중이 증가할 수록 구동축의 변곡, 볼베어링 하중의 불균형 등의 영향을 받아 이론값과 차이를 보였다. 반경방향 하중이 있는 단일결함과 다중결함의 경우 하중이 증가함에 따라 변위량의 변화는 축심변위량 보다 반경변위량이 더욱 커지게 된다는 것을 알았다. 베어링의 결함상태에 따라 하중과 변위량의 기울기인 부하-변위량 특성을 구함으로써 볼베어링의 결함유무를 검출하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문집
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• pp.611-616
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• 2002

Bearing diagnostics is difficult in a gearbox because bearing signals are masked by the strong gear signals. Self adaptive noise cancellation(SANC) is useful technique to seperate bearing signals from gear signals. While gear signals are correlated with a long correlation length, bearing signals are not correlated with a short length. SANC seperates two components on the basis of correlation length. Then we can find defect frequency component in the envelope spectrum of the bearing signals.

• Journal of Advanced Marine Engineering and Technology
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• 제33권5호
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• pp.672-678
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• 2009

Acoustic Emission (AE) technique is a non-destructive testing method and widely used for the early detection of faults in rotating machines in these days, because the sensitivity of AE transducers is higher than normal accelerometers. So it can detect low energy vibration signals. The faults in the rotating machines are generally occurred at bearings and gearboxes which are the principal parts of the machines. It was studied to detect the bearing faults by envelop analysis in several decade years. And the researches showed that AE had a possibility of the application in condition monitoring system(CMS) using the envelope analysis for the rolling bearing. And peak ratio (PR) was developed for expression of the bearing condition in condition monitoring system using AE. Noise level is needed to reduce to take exact PR value because the PR is calculated from total root mean square (RMS) and the harmonics peak levels of the defect frequencies of the bearing. Therefore, in this paper, the discrete wavelet transform (DWT) was added in the envelope analysis to reduce the noise level in the AE signals. And then, the PR was calculated and compared with general envelope analysis result and the result of envelope analysis added the DWT. In the experiment result about inner fault of bearing, defect frequency was difficult to find about only envelop analysis. But it's easy to find defect frequency after wavelet transform. Therefore, Envelop analysis added wavelet transform was useful method for early detection of default in signal process.