• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.9-17
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• 2023

In this paper, we propose a one-class vibration anomaly detection system for bearing defect diagnosis. In order to reduce the economic and time loss caused by bearing failure, an accurate defect diagnosis system is essential, and deep learning-based defect diagnosis systems are widely studied to solve the problem. However, it is difficult to obtain abnormal data in the actual data collection environment for deep learning learning, which causes data bias. Therefore, a one-class classification method using only normal data is used. As a general method, the characteristics of vibration data are extracted by learning the compression and restoration process through AutoEncoder. Anomaly detection is performed by learning a one-class classifier with the extracted features. However, this method cannot efficiently extract the characteristics of the vibration data because it does not consider the frequency characteristics of the vibration data. To solve this problem, we propose an AutoEncoder model that considers the frequency characteristics of vibration data. As for classification performance, accuracy 0.910, precision 1.0, recall 0.820, and f1-score 0.901 were obtained. The network design considering the vibration characteristics confirmed better performance than existing methods.

• Journal of IKEEE
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• v.26 no.3
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• pp.488-493
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• 2022

In manufacturing sites, bearing fault in eletrically driven motors cause the entire system to shut down. Stopping the operation of this environment causes huge losses in time and money. The reason of this bearing defects can be various factors such as wear due to continuous contact of rotating elements, excessive load addition, and operating environment. In this paper, a motor driving environment is created which is similar to the domestic manufacturing sites. In addition, based on the established environment, we propose a dataset for bearing fault detection by collecting changes in vibration characteristics that vary depending on normal and defective conditions. The sensor used to collect the vibration characteristics is Microphone G.R.A.S. 40PH-10. We used various machine learning models to build a prototype bearing fault detection system trained on the proposed dataset. As the result, based on the deep neural network model, it shows high accuracy performance of 92.3% in the time domain and 98.3% in the frequency domain.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.1-8
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• 2023

If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.464-469
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• 2019

Tapered roller bearings are used widely in vans, trucks, and trains because they can support the vehicle in a stable manner even under a heavy load. The cage of a tapered roller bearing maintains the gap between the rollers, which prevents friction wear and suppresses heating. If the cage is severely deformed due to resonance, the roller may not be able to roll smoothly and even leave the cage. Consequently, it is very important to analyze the dynamic characteristics of the cage for reliable performance of a bearing. The cage essentially has geometrical tolerance in the manufacturing process. In this paper, the effects of those geometrical imperfections on the dynamic characteristics of the cage were investigated. As a result, natural frequency separation occurred near the natural frequency of the ideal cage due to geometrical imperfections. In addition, the interval was proportional to the magnitude of the geometric error, and the interval increased with increasing mode number.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.50-50
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• 2008

본 연구에서는 전방항성 초음파 액추에이터의 제작, 시뮬레이션, 구동 드라이버 제작, 제어 방법에 대하여 연구하였다. 우선, 시뮬레이션 툴인 ATILA를 사용하여 전방향성 초음파 액추에이터를 설계하였고 구동 주파수, 어드미턴스 특성 그리고 액추에이터의 움직임을 분석하여 최적의 구동 주파수 영역을 파악하였다. 실제 구동을 확인하기 위하여 액추에이터 스테이지와 구동 드라이버를 개발 하였다. 전방항성 액추에이터 스테이지의 구조는 액추에이터와 4개의 볼 베어링이 알루미나 볼을 압착하는 형태이며 세라믹에 인가되는 사인파의 위상차에 의하여 4개의 방향으로 구동 할 수 있다. 또한, 액추에이터를 위치 제어를 위하여 로터리 엔코더 두 개를 사용하여 구의 움직임을 파악하였고 PID 제어기법을 사용하여 액추에이터의 움직임을 제어하였다. 스테이지 구조상 엔코더의 $70^{\circ}$ 내에서만 구동 가능하며, 실험 결과를 통하여 전방향성 초음파 액추에이터는 약 $1.2^{\circ}$의 분해능을 가지고 구동영역 내 원하는 좌표로의 이동이 가능했고, 향후 고 정밀 관절 및 인공 눈에 응용 가능할 것으로 사료된다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.10a
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• pp.73-79
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• 1994

(1) 진공청소기의 소음은 팬모타의 회전에 기인하는 유체소음과 진동소음이 주류를 이루며, 여기에 공기의 흡입과 배출에 따른 유체소음등이 복합되어 나타난다. (2) 진공청소기의 소음특성은 각 소음원들의 특성에 따라 주파수대역을 구분할 수 있으며, 기계적 진동음인 500Hz부근에서 peak를 보인다. (3) 소음의 저감을 위하여는 기존에 정립되어 있는 흡음, 차음, 감쇠, 방진, 유압유속감소 등의 기술을 종합적으로 활용하여 제한된 공간내에서 효과를 극대화할 수 있는 구조개발이 필요하며 본 연구에 적용하였다. (4) 본 연구의 '정음유로구조'는 차음효과, 유로길이 증가에 의한 감쇠효과, 흡음효과를 극대화할 수 있는 구조이다. (5) 팬모타의 진동모드는 회전축을 중심으로 원운동을 하며, 진동량은 흡입구와 뒷쪽 베어링부위가 가장 작으므로 회전축에 가까운 곳을 지지하는 것이 방진에 유리하다. (6) 본 구조에서 사용된 케이싱은 484Hz의 고유진동수 성분을 가지며 이는 모타와 공진할 우려가 있다. 이에 공진주파수 성분의 진동량이 가장 작은 전면과 후면의 중앙부를 지지하여 진동을 줄일 수 있었다. (7) 본체소음의 전반적인 저감에 따라 흡입구 등에서 발생하는 공기마찰소음의 영향이 상대적으로 커지며, 따라서 흡입구의 유선형 설계 및 누설소음의 흡음, 차폐 등의 역할이 중요한 관리 요소로 된다.

• Plant Journal
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• v.13 no.1
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• pp.30-36
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• 2017

During the start-up of 500 MW class coal-fired power plant, abnormal shaft vibration was occurred on bearings installed on both side of high and intermediate pressure steam turbine. Shaft vibration was analyzed to investigate the reason and find the resolution, based on well-known theory in this study. Typical vibration characteristics which occur when rotating parts contact with stationary parts were observed at the analysis of frequency, amplitude and phase angle. The reason of abnormal vibration was assumed to be rub and internal parts wear was observed during repair period. As a result of applying low speed turning and balancing for resolution of abnormal vibration, balancing was more effective for rub removal. So balancing could be excellent resolution in the case of abnormal vibration which is similar to this study.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.1022-1027
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• 2002

This paper describes the fluttering characteristics of the upper pad in a tilting pad journal bearing(6-pad, LOP type) using a steam turbine. In order to investigate the phenomena of the upper pad fluttering experimentally, the absolute vibration of the upper pads the relative vibration between bearing and shaft and the circumferential distribution of the film thickness are measured under the different values of supply oil flow rate, shaft speed and bearing load. It can be known that the fluttering mechanism of the upper pads has a tendency of the self-excited vibration from the study of fluttering frequencies and amplitudes with the change of shaft speed. furthermore, it is observed that the incipient upper pad fluttering velocity is increased by the increase of oil supply flow rate and fluttering amplitude of the upper pads is increased by the decrease of the oil flow rate and by the increase of the bearing load.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.6
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• pp.467-473
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• 2003

This paper describes the fluttering characteristics of the upper pad in a tilting pad journal bearing(6-pad, LOP type) using a steam turbine. In order to investigate the phenomena of the upper pad fluttering experimentally, the absolute vibration of the upper pads, the relative vibration between bearing and shaft and the circumferential distribution of the film thickness are measured under the different values of supply oil flow rate, shaft speed and bearing load. It can be known that the fluttering mechanism of the upper pads has a tendency of the self-excited vibration from the study of fluttering frequencies and amplitudes with the change of shaft speed. Furthermore, it is observed that the incipient upper pad fluttering velocity is increased by the increase of oil supply flow rate and the fluttering amplitude of the upper pads is increased by the decrease of the ell flow rate and by the increase of the bearing load.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.349-358
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• 2019

This paper aimed at collecting sensor signals to extract characteristic parameter of the rotor. A vibration test rig has been developed to perform model tests. Signal characteristics were analyzed when driving normally. Envelope FFT Analysis is used to extract vibration components caused by periodic impacts from other vibration factors. Signal analysis was performed when load changes were given to speed sensors and vibration test rigs that show low frequency characteristics of the rotor and signal analysis according to rotational speed. The acceleration signal measured in the bearing housing has a small amplitude and produces only the rotational frequency component and harmonic component of the motor. As the number of rotations increases, the amplitude of acceleration can be seen. As the rotational speed increases, it can be seen that there is a difference in the shape of the original data and compared with the acceleration FFT graph, it can be seen that the noise is strong at low frequencies and the corresponding rotational frequency components are clearly represented. It can be seen that changing the load does not increase the main rotational frequency component.