Research on the Degradation Model of the Clamping Device Based on CAE Simulation and Data-driven

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Jul 14, 2017
Yu Li Kang Rui Zhang Bin Wang Yansong

Abstract

The paper is based on PHM oriented design and modeling of durability testing for clamping devices. The testing scheme is made out through the Computer Aided Engineering (CAE) simulation result and the degradation model is studied by Data-driven according to the test data. Based on the analysis of main failure mode and mechanism, it is concluded that the reason of clamping device cracking is fatigue which caused by the cycle force. The durability test is conducted by CAE simulation analysis, and the strain data of the device have been collected by the NI data acquisition equipment. Based on the collected data, Data-driven method is used to model the high-cycle fatigue degradation caused by the cycle force. And with the comparison among different regression models, we selected the appropriate one which will provide theoretical support for PHM management of similar machines. In applications, by updating this model with actual degradation data of the target device, can monitor the health state and predict the remaining service life of the target device. So that the actively predictive maintenance can be done and the failure can be avoided.

Abstract 32 | PDF Downloads 24

##plugins.themes.bootstrap3.article.details##

Keywords

PHM

References
ZHANG Pengwei, LIU Ztao, LI Jianfeng, LI Jinglu, YU Xiaoli. Fatigue crack identification method based on relative change of strain in engine block[J].Journal of Zhejiang University: Engineering Science, 2012,46(6):948-953.
SHI Huajie, XUE Songdong. Degradation data driven online prediction for equipment residual life[M].Computer Engineering and Applications,2016,52(23):249-254
KENNETH, P. BURNHAM,DAVID R. ANDERSON. Multimodel Inference Understanding AIC and BIC in Model Selection, SOCIOLOGICAL METHODS & RESEARCH, Vol. 33, No. 2, November 2004 261-304
Si X S,Wang W B,Hu C H,et al. Remaining useful life estimation—a review on the statistical data driven approaches[J].European Journal of Operational Research,2011,213(1):1-14.
HU Changhua, SHI Quan, SI Xiaosheng, ZHAGN Zhengxin. Data-driven Life Prediction and Health Management: State of the Art[J] cnki.xk.2017.0072:72-78
Pecht M G. Prognostics and health management of electronics[M].New Jersey: John Wiley and Sons,2008:1-315.
WANG Xiaolin, GUO Bo, CHEN Zhijun. Real-time reliability evaluation for product with nonlinear driftbased Wiener process[J].Journal of Central South University: Science and Technology,2013,44(8):3203-3209.
Section
Regular Session Papers