• 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 Electrical Engineering and Technology
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• v.11 no.6
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• pp.1846-1856
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• 2016

This study proposes a novel feature point initialization method in order to improve the accuracy of feature point positions by fusing a vision sensor and a lidar. The initialization is a process that determines three dimensional positions of feature points through two dimensional image data, which has a direct influence on performance of a 6-DoF bearing-only SLAM. Prior to the initialization, an extrinsic calibration method which estimates rotational and translational relationships between a vision sensor and lidar using multiple calibration tools was employed, then the feature point initialization method based on the estimated extrinsic calibration parameters was presented. In this process, in order to improve performance of the accuracy of the initialized feature points, an iterative automatic scaling parameter tuning technique was presented. The validity of the proposed feature point initialization method was verified in a 6-DoF bearing-only SLAM framework through an indoor and outdoor tests that compare estimation performance with the previous initialization method.

• 전자공학회논문지 IE
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• v.48 no.1
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• pp.1-6
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• 2011

In this study, it carried out Electromagnetic Field Analysis of Magnetic Bearing due to stator structure and it got the electrical characteristics of 3 structure types of AMB(Active magnetic bearing) systems to get optimal design criteria. The results of simulation in three types of AMB, using FEM method, type 1, 2, and 3 had many paths to move magnetic flux vectors from N pole to S pole and magnetic flux lines are transferred to rotor as a shaft. The paths help to rotate the rotors. So, their data of electrical properties carry out design of magnetic bearing system and the data help to make design criteria.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2003.11a
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• pp.1-11
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• 2003

The service reliability of power plants strongly depends on the excellent performance and integrity of hydrodynamic bearings. Consequently, the bearings must be properly designed so as to control vibration amplitudes of rotor due to mass unbalance in passing critical speeds and also suppress self-excited vibrations of rotor even over maximum rated speeds. Furthermore, the bearings must be designed so as to maintain required tribological performance even under severe operating conditions. However, various tribological troubles have been experienced in power plants in Japan. The actual troubles are analysed, focusing on not only direct mechanical causes but also specific bearing designs that surfaced the troubles. Furthermore human factors that decided such designs are also studied. The powerful database of troubles and analyses will contribute greatly to designing advanced power plants with enhanced service reliability in the future. To this end, trouble information should be disclosed, shared and transferred limitlessly. Cooperation of users of power plants is essential to making more advanced design specifications, because no one has easier access to operating and trouble information of power plants than users.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.1093-1096
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• 2004

Bearings are elementary machinery component which loads and do rotating motion. Excessive loads or many other reasons can cause incipient faults to be created and grown in each component. Moreover, it happens that incipient faults which were caused by manufacturing or assembling process' errors of the bearings are created. Finding the incipient faults as early as possible is necessary to the bearings in severe condition: high speed or frequently varying load condition, etc. How early we can detect the faults has to do with how the detection algorithm finds the fault information from measured signal. Fortunately, the bearing fault signal makes periodic impulse train. This information allows us to find the faults regardless how much noise contaminates the signal. This paper shows the basic signal processing idea and experimental results that demonstrate how good the method is.

• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.129-134
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• 2001

The paper presents the optimal design of a oil-free two-stage compressor, which is driven by 75 kW motor at an operating speed of 39,000 rpm, and the pressure ratio of which is up to 4. First, an attempt is made to obtain the optimal design of a bump bearing which supports a compressor rotor. Second, bump bearings and shaft are considered simultaneously, and the weighted sum of rotor weight and frictional torque is minimized. Finally, the optimal geometry of compressor wheel is considered. The mean efficiency and the - minimum efficiency are maximized respectively. The results presented in this paper provide important design information necessary to reduce the energy loss.

• Journal of KSNVE
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• v.10 no.6
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• pp.985-990
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• 2000

The signals that can be obtained from rotating machines often convey the information of machine. For example, if the machine under investigation has faults, then these signals often have pulse signals, embedded in noise. Therefore the ability to detect the fault signal in noise is major concern of fault diagnosis of rotating machine, In this paper, minimum variance cepstrum (MV cepstrum) . which can easily detect impulse in noise, has been applied to detect the type of faults of ball bearing system. To test the performance of this technique. various experiments have been performed for ball bearing elements that have man made faults. Results show that minimum variance cepstrum can easily detect the periodicity due to faults and also shows the pattern of excitation by the faults.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.614-622
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• 2003

In this paper, the stress-strain curves of bearing steels at hot working conditions are obtained by hot compression test with a computer controlled servo-hydraulic Gleeble 3800 testing machine and elongations and reductions of area of the bearing steels are also obtained by hot tensile test with a Gleeble 1500 testing machine. Experiments are conducted under the various strain-rates and temperatures and their results are used to obtain the flow stress information. A rigid thermo-viscoplastic finite element method is applied to the multi-stage hot forging process in order to predict temperature distribution of workpiece. The experimental results and the analysis results are used to obtain an optimal hot forging condition.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.293-304
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• 2018

This paper described a results of field test based on plate bearing test of the restoration material, which was developed to restore the ground cavity due to sewerage damage. The analysis of bearing capacity characteristics on the restoration materials was performed by experimental results. The results showed that the load bearing capacity in the maximum stress condition of the foundation ground is about 66%-70%, when the expansion mat is embedded at the bottom of 0.1 m and 0.2 m from the ground surface. However, The load bearing capacity of expansion mat according to embedded depth was not large. The load bearing capacity of concrete mats was about 82%-90% compared with that of ground surface, and it showed about 50% of the load bearing capacity compared with the expansion mat. As a result of analysis of allowable bearing capacity according to restoration materials, it was confirmed that the allowable bearing capacity of the expansion mat and the concrete was about 130%-150% and about 160% more than the foundation ground, respectively.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.255-265
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• 2009

This paper presents the acoustic noise and mechanical vibration reduction of a coreless brushless DC motor with an air dynamic bearing used in a digital lightening processor. The coreless brushless DC motor does not have a stator yoke or stator slot to remove the unbalanced force caused by the interaction between the stator yoke and the rotor magnet. An unbalanced force makes slotless brushless DC motors vibrate and mechanically noisy, and the attractive force between the magnet and the stator yoke increases power consumption. Also, when a coreless brushless DC motor is driven by a $120^{\circ}$ conduction type inverter, high frequency acoustic noise occurs because of the peak components of the phase currents caused by small phase inductance and large phase resistance. In this paper, a core-less brushless DC motor with an air dynamic bearing to remove mechanical vibration and to reduce power consumption is applied to a digital lightening processor. A $180^{\circ}$ conduction type inverter drives it to reduce high frequency acoustic noise. The applied methods are simulated and tested using a manufactured prototype motor with an air dynamic bearing. The experimental results show that a coreless brushless DC motor has characteristics of low power consumption, low mechanical vibration, and low high frequency acoustic noise.