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Ren, B., Ren, X.H. and Li, G.Z. (2013) The Lathes and Hydraulic Pressure of CNC Thermal Compensation Based on PSO Algorithm Optimized BP Neural Network. Machine Tool & Hydraulics, 41, 61.

has been cited by the following article:

• TITLE: CNC Thermal Compensation Based on Mind Evolutionary Algorithm Optimized BP Neural Network

  AUTHORS: Yuefang Zhao, Xiaohong Ren, Yang Hu, Jin Wang, Xuemei Bao

  KEYWORDS: Thermal Errors, Thermal Error Compensation, Genetic Algorithm, Mind Evolutionary Algorithm, BP Neural Network

  JOURNAL NAME: World Journal of Engineering and Technology, Vol.4 No.1, February 5, 2016

  ABSTRACT: Thermal deformation error is one of the most important factors affecting the CNCs’ accuracy, so research is conducted on the temperature errors affecting CNCs’ machining accuracy; on the basis of analyzing the unpredictability and pre-maturing of the results of the genetic algorithm, as well as the slow speed of the training speed of the particle algorithm, a kind of Mind Evolutionary Algorithm optimized BP neural network featuring extremely strong global search capacity was proposed; type KVC850MA/2 five-axis CNC of Changzheng Lathe Factory was used as the research subject, and the Mind Evolutionary Algorithm optimized BP neural network algorithm was used for the establishment of the compensation model between temperature changes and the CNCs’ thermal deformation errors, as well as the realization method on hardware. The simulation results indicated that this method featured extremely high practical value.