• 신재생에너지
• /
• 제9권3호
• /
• pp.5-13
• /
• 2013

In the previous research, dynamic results have been analyzed in the time and frequency regions. Time and frequency region can be transformed by the Fourier transform. This transform is very useful about analyzing system behaviors. However, because of coupling, it cannot give clear results in the real system including lots of defects. In this paper, we introduced the analysis based on quefrency region to represent physical means clearly from complicated results. We simulated the drive train system which has defects, and compared between frequency and quefrency region to show its excellence. To do this process, We established mathematical model. The equation of motion was derived by the Lagrange equation and constraint equations. The constraint equation included relationships about gear mesh, flexibility of shaft. About numerical analysis, the Newmark beta method was used to get results. And FFT (Fast Fourier Transform) which converts results from time domain to frequency, qufrequency was used.

• 한국기계가공학회지
• /
• 제18권10호
• /
• pp.54-59
• /
• 2019

The final reduction drive in tactical vehicles has a wear-pad that helps to maintain adequate end floating when the hub assay operates. The input axis and sun gear move repeatedly with the axis when tactical vehicle is operating. The hub assay is designed so that the wear pads won't seize during operation. Seizure of the wear pads during operation results in oil leakage. In our study, the fault mechanism was analyzed to prevent the seizure of the wear pads and an optimal design for the shape and material of the wear-pad was explored. We then observed the changes in temperature, shape, and material of several important parts.

• 드라이브 ㆍ 컨트롤
• /
• 제15권4호
• /
• pp.30-38
• /
• 2018

Electronic control units (ECUs) are currently popular, and have evolved further towards the high-end application of autonomous vehicles in the automotive industry. Such digital technologies have also become widespread, in agriculture and construction equipment. Likewise, transmission control of high-speed tracked vehicles is based on the transmission control unit (TCU), performing complex gear change control functions, and diagnostic algorithms (a TCU's self-diagnostic and reporting capability of malfunction data through CAN communication). Since all functions of TCU are implemented by embedded-software, it is hardly possible to analyze specifications by reverse engineering. In this paper a real-time transmission simulator adaptable to TCU is presented, for analysis of diagnosis algorithm and standards. Signal simulation circuits are deliberately designed considering electrical characteristics of TCU inputs and various analysis tools, such as analog input auto scan function, and global output enable switch, are implemented in software. Test results from hardware-in-the-loop simulator verify tolerance time for each error, as well as cause of fault, error reset conditions.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송∙미디어공학회 2022년도 하계학술대회
• /
• pp.1305-1307
• /
• 2022

자동차 부품의 결함은 시스템 전체의 성능 저하 및 인적 물적 손실이 발생할 수 있으므로 생산라인에서의 불량 검출은 매우 중요하다. 따라서 정확하고 균일한 결과의 불량 검출을 위해 딥러닝 기반의 고장 진단 시스템이 다양하게 연구되고 있다. 하지만 제조현장에서는 정상 샘플보다 비정상 샘플의 발생 빈도가 현저히 낮다. 이는 학습 데이터의 클래스 불균형 문제로 이어지게 되고, 이러한 불균형 문제는 고장을 판별하는 분류 모델의 성능에 영향을 끼치게 된다. 이에 본 연구에서는 모터의 동작음으로부터 불량 모터를 판별하는 불량 검출 시스템 설계를 위한 데이터 불균형 해결 방법을 제안한다. 자동차 사이드 미러 모터의 동작음을 학습 및 테스트를 위한 데이터 셋으로 사용하였으며 손실함수 계산 시 학습 데이터 셋의 클래스별 샘플 수 가 반영되는 label-distribution-aware margin(LDAM) loss 와 Inception, ResNet, DenseNet 신경망 모델의 비교 분석을 통해 불균형 데이터를 처리할 수 있는 가능성을 보여주었다.

• IEIE Transactions on Smart Processing and Computing
• /
• 제2권4호
• /
• pp.240-247
• /
• 2013

The main aim of this study was to suppress the angular velocity against strong winds during storms and analyze the stability and performance of the phase plane method. The utilization of small-scale wind turbine system has become common in agriculture, houses, etc. Therefore, it is considered to be a scheme for preserving the natural energy or avoiding the use of fossil fuels. Moreover, settling small-scaled wind turbines is simpler and more acceptable compared to ordinary huge wind turbines. In addition, after converting the energy there is no requirement for distribution. Therefore, a much lower cost can be expected for small-scaled wind turbines. On the other hand, this system cannot be operated continuously because the small-scaled wind turbine consists of a small blade that has low inertia momentum. Therefore, it may exceed the boundary of angular velocity, which may cause a fault in the system due to the centrifugal force. The aim of this study was to reduce the angular velocity by controlling the stall factor. Stall factor control consists of two control methods. One is a shock absorber that is loaded in the junction of the axis of the blade of the wind turbine gear wheel and the other is pitch angle control. Basically, the stall factor itself exhibits nonlinear behavior. Therefore, this paper confirmed the feasibility of stall factor control in producing desirable performance whilst maintaining stability.

• 반도체디스플레이기술학회지
• /
• 제21권4호
• /
• pp.65-70
• /
• 2022

In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.