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Journal of Tsinghua University(Science and Technology)    2018, Vol. 58 Issue (12) : 1107-1114     DOI: 10.16511/j.cnki.qhdxxb.2018.21.024
MECHANICAL ENGINEERING |
Load spectrum compilation for machining center spindles based on S-shaped specimens
CHEN Daiwei1, WU Jun1, ZHANG Binbin1, WANG Liping1, LIANG Jianhong2
1. Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China;
2. School of Information Engineering, Southwest University of Science and Technology, Mianyang, 621010, China
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Abstract  Spindle reliability tests characterized by the load spectrum are used to test spindle reliability. This paper presents a spindle load spectrum compilation method based on coefficient identification and cutting simulations. The cutting force coefficient in a cutting force model is identified and the cutting force predicted by the cutting model is compared with the measured cutting force to validate the model. The simulated cutting force on an S-shaped specimen was analyzed to obtain time histories of the cutting parameters. The cutting force model and the cutting parameters were then used to predict the dynamic cutting force with the cycles of the dynamic counted with the rain-flow counting method. Alternative probability distribution models were fit to the counting result with the best model selected based on the multi-fitting curve and the KS (Kolmogorov-Smirnov) test. The load spectrum was then used to guide a spindle loading test. The results show that the dynamic force is accurately predicted and can be used to predict the load spectrum and also guide loading tests. This method will improve spindle test reliability.
Keywords load spectrum      cutting force model      coefficient identification      rain-flow counting      probability distribution model     
Issue Date: 13 December 2018
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CHEN Daiwei
WU Jun
ZHANG Binbin
WANG Liping
LIANG Jianhong
Cite this article:   
CHEN Daiwei,WU Jun,ZHANG Binbin, et al. Load spectrum compilation for machining center spindles based on S-shaped specimens[J]. Journal of Tsinghua University(Science and Technology), 2018, 58(12): 1107-1114.
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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2018.21.024     OR     http://jst.tsinghuajournals.com/EN/Y2018/V58/I12/1107
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
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