• 제목/요약/키워드: Rotating Machine

검색결과 449건 처리시간 0.026초

영상처리 기법을 이용한 원통형 용기내의 회전유속의 측정 (Image Processing Technique for Rotational Velocity Measurements in a Circular Cylinder)

  • 김재원;엄정섭;임태규
    • 설비공학논문집
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    • 제7권1호
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    • pp.13-19
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    • 1995
  • An experimental investigation has been made for flow in a circular cylinder with a rotating bottom disk. Flow system considered in this paper is a characteristic model of interior flows of an electric washing machine. Flows in a tub of an electric washing machine are driven by a rotating bottom disk called a pulsator. The simple and characteristic model was composed of a circular cylinder with impulsively rotating endwall disk and a viscous fluid in it. Rotational motion of the pulsator is periodic and alternative in rotation direction. The flow field in the interior region is governed by a horizontal boundary layer forms on the impulsively rotating disk. Experimental approach was accomplished by adopting an image processing technique for velocity measurements. Comprehensive details of the flow structure are presented. Also a meridional circulation is obtained by tracking image particles suspended in the fluid. Flow structure and data are successfully procured for this complex rotating flow field.

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Milling characteristics of cutting-type rice milling machine according to the rotating speed of the main shaft

  • Cho, Byeong-Hyo;Han, Chung-Su;Kang, Tae-Hwan;Lee, Dong-Il;Won, Jin-Ho;Lee, Hee-Sook
    • 농업과학연구
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    • 제44권3호
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    • pp.416-423
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    • 2017
  • This study aimed to identify milling characteristics depending on the rotating speed of the main shaft of the cutting-type rice milling machine which can minimize the conventional milling process. Brown rice, which was produced in Gunsan-si, Jeollabuk-do, Republic of Korea, in 2016, was used as the experimental material. The milling characteristics of white rice were measured under four different rotating speeds of main shaft: 950 - 1,050 rpm, 1,000 - 1,100 rpm, 1,050 - 1,150 rpm, and 1,100 - 1,160 rpm. For each shaft speed, 300 kg of brown rice was processed, and the milling characteristics were measured according to the whiteness, grain temperature, cracked rice ratio, broken rice ratio, turbidity, and energy consumption. The whiteness of rice grain was found to be consistent at around $40{\pm}0.5$ only when milled at the shaft speed of 950 - 1,050 or 1,000 - 1,100 rpm. The grain temperature during the milling process increased by 11.35 to $11.85^{\circ}C$, showing little differences amongst shaft speeds. The cracked rice ratio increased by 8.2 to 10.4% at all conditions. The broken rice ratio ranged from 0.58 to 0.76%, reflecting a low level. The turbidity after milling was 54.8 ppm when milled at 1,000 - 1,100 rpm. Energy consumption of 12.98 and 12.18 kWh/ton were recorded at the shaft speed of 1,000 - 1,100 and 1,050 - 1,150 rpm, respectively. The result of this study indicates that the optimal rotating speed of main shaft would be 1,000 - 1,100 rpm for a cutting-type rice milling machine.

공작기계 베어링 결합부의 전산 모델링 (Computational Modeling of the Bearing Coupling Section of Machine Tools)

  • 김현명;서재우;박형욱
    • 한국정밀공학회지
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    • 제29권10호
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    • pp.1050-1055
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    • 2012
  • The bearing coupling section of machine tools is the most important factor to determine their static/dynamic stiffness. To ensure the proper performance of machine tools, the static/dynamic stiffness of the rotating system has to be predicted on the design stage. Various parameters of the bearing coupling section, such as the spring element, node number and preload influence the characteristics of rotating systems. This study focuses on the prediction of the static and dynamic stiffness of the rotating system with the bearing coupling section using the finite element (FE) model. MATRIX 27 in ANSYS has been adopted to describe the bearing coupling section of machine tools because the MATRIX 27 can describe the bearing coupling section close to the real object and is applicable to various machine tools. The FE model of the bearing couple section which has the sixteen node using MATRIX 27 was constructed. Comparisons between finite element method (FEM) predictions and experimental results were performed in terms of the static and dynamic stiffness.

철근 밴딩기 롤러의 피로파괴 CAE 해석 (Fatigue CAE Analysis of a Rebar Bending Machine Roller)

  • 신유정;최창환;이성건;김진호
    • 한국기계가공학회지
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    • 제14권2호
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    • pp.75-80
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    • 2015
  • The rebar factory production process involves the repetitive bending of rebars. Therefore, the fatigue failure of the rebar bending machine needs to be considered. In this paper, fatigue analysis of the rebar machine was performed using the commercial software DAFUL, which is based on MFBD (Multi Flexible Body Dynamics). The rotating roller, fixing roller and rebar were modeled by the finite element method. The rebar bending process is simulated and the mechanical stresses on the rollers are calculated. Structural analysis of the rebar bending roller was performed using the maximum bending angle of $180^{\circ}$ and maximum processing rebar diameter of ${\Phi}19mm$. Then, for fatigue analysis, the S-N curve of STD-11 was. The fatigue life of rollers is estimated by modified Goodman diagram. The fatigue life range of the rotating roller is $2.99961{\times}10^5{\sim}1{\times}10^8$ while that of the fixed roller is $2.53142{\times}10^5{\sim}1{\times}10^8$. STD-11 has an infinite life cycle after $1{\times}10^8$. Therefore, the rollers of the rebar bending machine may be expected to suffer fatigue failure. Thus, we performed a parameter study of fatigue life according to various axial radii of the fixed roller and rotating roller, and redesign of the rebar bending machine. Consequently, the axial radius of the fixed roller and rotating roller was found to be 35~37.5mm and 30~35mm, respectively, and an infinite life cycle was confirmed at these.

기계학습을 적용한 회전체 고장진단에 관한 연구 (A study on the fault diagnosis of rotating machine by machine learning)

  • 전항규;김지선;김봉주;김원진
    • 한국음향학회지
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    • 제39권4호
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    • pp.263-269
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    • 2020
  • 본 논문에서는 정상상태와 8가지의 고장이 재현가능한 회전체를 제작하고 진동 데이터를 취득하였다. 취득한 데이터로 특징을 계산하여 인공신경망과 유전알고리즘을 적용한 고장진단을 통해 정확성을 분석한다. 최적의 시간과 높은 정확성의 구현을 위해 특징을 3가지 영역으로 구분하여 고장진단에 적용하였다. 설정변수는 학습수로 설정하였다. 회전체 고장진단의 결과는 다른 영역보다 주파수영역에서 높은 정확성을 보였으며 학습수 5000, 8000회에서 10회의 구동 모두 정확한 고장진단을 하였다. 시간의 효율성을 고려하였을 경우, 학습수가 5000회일 때 가장 우수하다고 판단하였다.

은닉 마르코프 모델을 이용한 질량 편심이 있는 회전기기의 상태진단 (Condition Monitoring Of Rotating Machine With Mass Unbalance Using Hidden Markov Model)

  • 고정민;최찬규;강토;한순우;박진호;유홍희
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2014년도 추계학술대회 논문집
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    • pp.833-834
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    • 2014
  • In recent years, a pattern recognition method has been widely used by researchers for fault diagnoses of mechanical systems. A pattern recognition method determines the soundness of a mechanical system by detecting variations in the system's vibration characteristics. Hidden Markov model has recently been used as pattern recognition methods in various fields. In this study, a HMM method for the fault diagnosis of a mechanical system is introduced, and a rotating machine with mass unbalance is selected for fault diagnosis. Moreover, a diagnosis procedure to identity the size of a defect is proposed in this study.

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Bi-spectrum for identifying crack and misalignment in shaft of a rotating machine

  • Sinha, Jyoti K.
    • Smart Structures and Systems
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    • 제2권1호
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    • pp.47-60
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    • 2006
  • Bi-spectrum is a tool in the signal processing for identification of non-linear dynamic behvaiour in systems, and well-known for stationary system where components are non-linearly interacting. Breathing of a crack during shaft rotation is also exhibits a non-linear behaviour. The crack is known to generate 2X (twice the machine RPM) and higher harmonics in addition to 1X component in the shaft response during its rotation. Misaligned shaft also shows similar such feature as a crack in a shaft. The bi-spectrum method has now been applied on a small rotating rig to observe its features. The bi-spectrum results are found to be encouraging to distinguish these faults based on few experiments conducted on a small rig. The results are presented here.

해수제빙장치의 최적 운전 조건 탐색을 위한 실험적 연구 (Experimental Study for Investigating the Optimum Operating Conditions of a Seawater Ice Machine)

  • 이화;주우진;정석권
    • 동력기계공학회지
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    • 제14권5호
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    • pp.76-82
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    • 2010
  • This paper investigates the optimum operating conditions to construct total automatic control system with high energy efficiency of a newly developed seawater ice machine. The machine has an electronic expansion valve(EEV) and a variable speed rotating drum with an evaporator installed inside. The coefficient of performance(COP) was used as an index to evaluate energy efficiency of the machine. At first, the opening angle of EEV was adjusted to obtain COP of the machine at a constant speed of the drum. Then, we checked seawater ice product versus opening angles of the EEV. Finally, effect of drum's rotating speed in response to product of seawater ice and seawater ice temperature were considered.

고압회전기 절연열화진단의 현장적용기술연구 (A Study on Site Application Techniques for Insulation Reliability of Rotating Machine)

  • 김길용;조경해;김택수;한상욱;이현수
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 하계학술대회 논문집
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    • pp.286-291
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    • 1991
  • Most of the failures of rotating machine are stator coil insulation failures. The insulation diagnostic testing for high voltage motors and generators are only megger test and P. I Test which is applied DC voltage until now. But it was impossible to judge insulation deterioration status of high voltage rotating machinery by above testing. In other words, even though the megger measurement values are fairly high, they used to be failed from time to time. Therefore in order to excute reliable and detailed diagnosis of insulation deterioration for rotating machinery, the tangent delta test, the alternating current test and the partial discharge test shall be applied to the insulation diagnostic testing on site.

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웨이블렛 변환과 신경망 알고리즘을 이용한 회전기기 결함진단 (Fault Diagnosis of Rotating Machines Using Wavelet Transform and Neural Network)

  • 최태묵;조대승
    • 한국해양공학회지
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    • 제16권5호
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    • pp.61-65
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    • 2002
  • The fault detection and diagnosis of rotating machinery widely used in plants including the ship are important for maintaining the performance of Plants. Recently, the wavelet transform has been recognized an efficient method to detect a little variation of physical quantities by the synchronous localization of time and frequency domains using the translation and dilation of signals. In this Paper, In order to develop efficient and reliable fault detection and diagnosis system rotating machines, the performance of wavelet transformation to detect a little variation of machine status and neural network to diagnose the cause of machine faults are investigated and experimented.