The research about micromachining accuracy control based on fuzzy evaluation algorithm. (2nd October 2018)

• Record Type: Journal Article
• Authors: Qiao, Jian; Lu, Qinghua; Zhang, Wenbao; Xue, Xiangyao
• Other Names: Manogaran Gunasekaran guestEditor.; Chilamkurti Naveen guestEditor.; Hsu Ching‐Hsien guestEditor.; Vijayakumar V. guestEditor.
• Is Part Of: Concurrency and computation. Volume 31:Number 10(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-10-02
• Subjects: accuracy control -- fuzzy algorithm -- micromachining -- machining accuracy -- nonlinear cluster training; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4745
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: The calculation method of nonlinear artificial neural network based on fuzzy evaluation algorithm is introduced. This method is used to evaluate the precision of micro machined machining and to find the influence factors of the precision of micromachining. The traditional machining precision control mainly adopts the linear control strategy, but the micromachining involves the mechanical characteristics of the micro field, and many linear machine adding precision control methods cannot effectively control the precision of the micromachining. Using fuzzy evaluation method, large data cluster training method can be used to fit the control curve of micromachining accuracy. The nonlinear mapping of the fuzzy evaluation algorithm is realized by the large sample training method, and the objective and effective parameter evaluation and precision control of the machining precision in the micro machined field are realized. It is proved that the fuzzy evaluation algorithm can accurately evaluate the precision of micro machined machining. Learning through large data samples can effectively improve the topology practicability and rationality of the algorithm.