• Title/Summary/Keyword: 내륜

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Dimensional Characteristics according to Internal Density of Automotive Inner Ring in 3D Printing (3D 프린팅에서 자동차용 Inner ring의 내부밀도에 따른 치수 특성)

  • Kim, Hae-Ji;Kim, Nam-Kyung
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.18 no.11
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    • pp.96-102
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    • 2019
  • Reverse engineering involves duplicating a physical part by measuring and analyzing its physical dimensions, features, and material properties. By combining reverse engineering with three-dimensional (3D) printing, engineers can simply fabricate and evaluate functional prototypes. This design methodology has been attracting increasing interest with the advent of the Fourth Industrial Revolution. In the present study, we apply reverse engineering and 3D printing technologies to evaluate a fabricated automotive inner ring prototype. Through 3D printing, inner rings of various densities were prepared. Their physical dimensions were measured with a 3D scanning system. Of our interest was the effect of inner ring density on the physical dimensions of the fabricated prototype. We compared the design dimensions and physical dimensions of the fabricated prototypes. The results revealed that even the 20% density of inner ring was effective for 3D printing in terms of satisfying the design requirements.

A Study on the Detection of Fault Factor in Gear-Integrated Bearing (기어일체형 베어링의 결함인자 검출에 대한 연구)

  • Yeongsik Kang;Ina Yang;Eunjun Lee;Hwajong Jin;Donghyouk Shim
    • Journal of the Korea Institute of Military Science and Technology
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    • v.26 no.2
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    • pp.113-121
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    • 2023
  • High-precision lasers and anti-aircraft radars are the main equipment to protect the Korean Peninsula, and require preemptive maintenance before signs of failure. Of the key components in the drive sector, bearings do not have a fault alarm function. Therefore, the technology for diagnosing defects in bearings before the performance degradation of equipment occurs is becoming more important. In this paper, for the experimental analysis, we measured the acceleration of the four sets of the same lot using acceleration sensors. Through periodic measurements, the factors that changed until the bearing stopped rotating were analyzed. To determine the replacement time, the main factors and threshold values of the bearing signal were analyzed. The error of the theoretical and experimental analysis results of the defect frequency was within 2.8 %, and the validity of the theoretical analysis results could be confirmed. Based on the results, it is possible to remotely transmit trouble alerts to users through the system check function.

Residual Stress Prediction and Hardness Evaluation within Cross Ball Grooved Inner Race by Cold Upsetting Process (냉간 업셋팅 공정에 의한 경사형 볼 그루브를 갖는 내륜의 잔류응력 예측 및 경도 평가)

  • T.W. Ku
    • Transactions of Materials Processing
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    • v.32 no.4
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    • pp.180-190
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    • 2023
  • This study deals with residual stress prediction and hardness evaluation within cross ball grooved inner race fabricated by cold upsetting process consisted of upsetting and ejection steps. A raw workpiece material of AISI 5120H (SCr420H) is first spheroidized and annealed, then phosphophyllite coated to form solid lubricant layer on its outer surface. To investigate influences of the heat treatment, uni-axial compression tests and Vickers micro-hardness measurements are conducted. Three-dimensional elasto-plastic FE simulations on the upsetting step and the ejection one are performed to visualize the residual stress and the ductile (plastic deformation) damage. External feature of the fabricated inner race is fully captured by using an optical 3D scanner, and the micro-hardness is measured on internal cross-sections. Consequently, the dimensional compatibility between the simulated inner race and the fabricated one is ensured with a difference of under 0.243mm that satisfied permissible error range of ±0.50mm on the grooved surface, and the predicted residual stress is verified to have similar distribution tendency with the measured Vickers micro-hardness.

Effect of Powerlock Inner Ring Shape, Bolt-fastening Force, and Friction on Power Transmission Performance (파워록 형상 및 마찰이 동력전달 성능에 미치는 영향 분석)

  • Kim, Dae Rae;Jang, Yeon-Hui;Jang, Myung-Geun;Park, Jin-Ah;Kim, Jong-Bong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.3
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    • pp.241-249
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    • 2017
  • A powerlock is used to transmit torque between two shafts, to protect important equipment from overloads, and to compensate for the misalignment of assembled shafts. In this study, the effect of the shapes of the inner rings, bolt-fastening force, and friction on power transmission performance of powerlocks is investigated. Finite element analysis and experiments were conducted for two cases, and the analysis results were validated. Analyses were carried out for inner rings of various shapes and for various values of bolt-fastening force and friction coefficient. The main factors that affect the torque transmission performance were investigated based on the analysis results.

Bearing Faults Identification of an Induction Motor using Acoustic Emission Signals and Histogram Modeling (음향 방출 신호와 히스토그램 모델링을 이용한 유도전동기의 베어링 결함 검출)

  • Jang, Won-Chul;Seo, Jun-Sang;Kim, Jong-Myon
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.11
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    • pp.17-24
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    • 2014
  • This paper proposes a fault detection method for low-speed rolling element bearings of an induction motor using acoustic emission signals and histogram modeling. The proposed method performs envelop modeling of the histogram of normalized fault signals. It then extracts and selects significant features of each fault using partial autocorrelation coefficients and distance evaluation technique, respectively. Finally, using the extracted features as inputs, the support vector regression (SVR) classifies bearing's inner, outer, and roller faults. To obtain optimal classification performance, we evaluate the proposed method with varying an adjustable parameter of the Gaussian radial basis function of SVR from 0.01 to 1.0 and the number of features from 2 to 150. Experimental results show that the proposed fault identification method using 0.64-0.65 of the adjustable parameter and 75 features achieves 91% in classification performance and outperforms conventional fault diagnosis methods as well.