基于GRA-RBF-FA的整体叶盘通道盘铣加工多目标参数优化

Translated title of the contribution: Multi-Objective Optimization of Processing Parameters for Disc-Mill Cutter Machining Blisk-Tunnel Based on GRA-RBF-FA Method

Nan Zhang, Yaoyao Shi, Chen Yang, Zhen Chen, Jiang Liu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

The process of disc-mill cutter machining blisk-tunnel is a typical multi-input and multi-output system, therefore multi-objective optimization is applied to improve the process. In this paper, an integrated approach that Grey Relational Analysis(GRA)couples with Radial Basis Function (RBF) neural network and Firefly algorithm (FA) is used to solve the optimization problem. The aim is to satisfy the minimum cutting force and maximum material removal rate simultaneously by optimizing the cutting speed, feed rate per tooth and cutting height. The results for verifying experiment indicated that GRA-RBF-FA method can be applied to optimize the processing parameters of disc-mill cutter machining TC17 blisk-tunnel and the optimization results are superior to the GRA's.

Translated title of the contributionMulti-Objective Optimization of Processing Parameters for Disc-Mill Cutter Machining Blisk-Tunnel Based on GRA-RBF-FA Method
Original languageChinese (Traditional)
Pages (from-to)160-166
Number of pages7
JournalXibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
Volume37
Issue number1
DOIs
StatePublished - 1 Feb 2019

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