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Finite element analysis for friction noise of simplified hip joint and its experimental validation
Jaehyeon Nam,Hoil Choi,Jaeyoung Kang 대한기계학회 2016 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.30 No.8
In a hip joint system, squeak noise often occurs due to friction between the ball and hemispherical cup. To analyze the dynamic instability induced by friction in the hip joint system, the dynamic ball joint model was constructed by using the finite element method. The results from stability analysis revealed that the mode-coupling type instability occurred for one bending mode and its adjacent composite mode with the axial and transverse displacements with the increase of friction coefficient. The vitro squeak test and vibration modal tests confirmed that squeak arose near the frequency of the mode pair.
Comparison of vibration visualization methods for classification of chaos based on CNN
Jaehyeon Nam,강재영 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.6
This study assessed methods for visualizing the vibrations for chaotic systems using a time series, fast Fourier transform (FFT), threshold recurrence plot, and unthresholded recurrence plot. The image classification was then performed using CNN, and the accuracy of each visualization method was compared and analyzed. The nonlinear behavior of chaotic systems was examined using the commonly known Van der pol, Rossler, and Duffing equations. The Lyapunov exponent was calculated for each model parameter change to determine the chaos. The classification accuracy was examined for the chaotic signal in each visualization method of the proposed architecture based on VGG 16 using the determined label and image. The classification accuracy for the chaos of each visualization method is the result of signals mixed randomly five times. FFT analysis showed the highest evaluation result.
마찰곡선을 반영한 인공 고관절 마찰소음 유한요소 해석연구
남재현(Jaehyeon Nam),박기완(Kiwan Park),강재영(Jaeyoung Kang) 대한기계학회 2016 大韓機械學會論文集A Vol.40 No.1
본 논문은 복소수 고유치해석을 통하여 세라믹-세라믹 인공고관절 시스템에서의 동적 불안정성을 연구하고자 하였다. 시스템 파라메터 연구를 통해서 모드 연성 기반의 불안정성을 연구하였고, 음의 기울기를 포함하는 유한요소 해석 모델을 구현하여 음의 기울기에 의한 불안정성에 대해 조사하였다. 그 결과 토션이 지배적인 시스템 모드가 음의 기울기에 의해 불안정해 지며, 이는 축하중에 크게 영향을 받는다는 점을 확인하였다. This study investigated the dynamic instability of a ceramic-on-ceramic artificial hip joint system through complex eigenvalue analysis. We examined the mode-coupling mechanism through eigenvalue sensitivity analysis with the variation of system parameters. In addition, we constructed a finite element model including the negative slope of friction curve for investigating the negative-slope mechanism in the hip squeak problem. The numerical results show that the torsion-dominant mode becomes unstable due to the presence of the negative slope while the axial load is the important factor influencing the negative-slope type instability.
남재현(Jaehyeon Nam),강재영(Jaeyoung Kang) 한국소음진동공학회 2020 한국소음진동공학회 논문집 Vol.30 No.2
In this study, the friction-induced vibration of the reciprocating device is measured under dust conditions and he dynamic instability mechanism using the analytical finite element model is proposed. In the case of absence of dust, a friction-induced vibration did not occur and the corresponding friction coefficient increased with the increase in revolutions per minute (r/min). In contrast, under the dust condition, a negative slope is developed, in which the friction coefficient decreases with increase in r/min. Consequently, the friction-induced vibration is generated. The results show that this system is excited by the negative slope mechanism, and the dynamics instability is predicted using the analytical finite element model. The numerical results show that the unstable frequency is due to dynamics instability caused by the bending mode of the frictional direction.
남재현(Jaehyeon Nam),강재영(Jaeyoung Kang) 한국소음진동공학회 2021 한국소음진동공학회 논문집 Vol.31 No.1
The aim of the study was to classify the chaotic time-series data with the nonlinear problem using the convolutional neural network (CNN), and to determine and verify the chaotic characteristics from a deterministic system. The classical nonlinear differential equation established by the Rossler model was used, and the chaotic characteristics were determined by the Lyapunov exponent. The chaotic properties was visualized using an unthresholded recurrence plot through the proposed procedure. A simple CNN model was developed to learn the extracted image using the proposed feature-visualization technique. As a result, the chaotic characteristics were classified with an accuracy of 99 % or more.