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A semi-analytical model for cutting force prediction in face-milling of spiral bevel gears

•Investigates the forming rule and un-deformed chips description.•Proposes the quadratic polygon description method for un-deformed chips.•Proposes the cutting force prediction model for spiral bevel gear.•Reveals the micro and macro cutting force variation in the gear face-milling process.•Verifies...

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Bibliographic Details
Published in:Mechanism and machine theory 2021-02, Vol.156, p.104165, Article 104165
Main Authors: Zheng, Fangyan, Han, Xinghui, Hua, Lin, Tan, Rulong, Zhang, Weiqing
Format: Article
Language:English
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Summary:•Investigates the forming rule and un-deformed chips description.•Proposes the quadratic polygon description method for un-deformed chips.•Proposes the cutting force prediction model for spiral bevel gear.•Reveals the micro and macro cutting force variation in the gear face-milling process.•Verifies the proposed model through FEM simulation and experiment In the machining process, prediction of the cutting force is the key to cutting simulation and optimization. Specially, for the face milling of the spiral bevel gear, the un-deformed chip varies during the process due to the complicated generating kinematics, bringing great challenge to the prediction of cutting force. Regarding this, with a thorough investigation carried out, it is found that the un-deformed chips can be summarized as six cases and described by quadratic polygon interpolation. On such basis, a highly efficient and accurate analytical cutting force prediction model for generated face-milling spiral bevel gear is proposed. Compared to the Boolean operation based method, the proposed method is faster; compared to the chip-simplify method, the method is more precise; and compared to the semi-analytical method, the method is more effective as the chip forming rule is fully considered, which in turn simplifies the operation. Further, the proposed method is validated through both FEM simulation and cutting force experiment with a tolerance within 10%.
ISSN:0094-114X
1873-3999
DOI:10.1016/j.mechmachtheory.2020.104165