锻压技术

曲轴锻造模具Archard磨损模型系数修正及视觉验证

英文标题：Coefficient correction and visual verification on Archard wear model for crankshaft forging die

作者：李朝昆曾琦刘庆生

分类号：TG316

出版年,卷(期):页码：2024,49(1):202-209

摘要：

热模锻模具在实际生产过程中由于受到交变应力的影响，受力情况复杂且服役环境相当恶劣。基于Archard磨损模型，通过典型曲轴锻造模具的有限元模拟结果与实际磨损量的对比，计算出磨损模型的磨损系数K值，从而获得适合曲轴热锻生产的修正Archard磨损模型；通过修正后的Archard磨损模型预测模具寿命，并基于机器视觉系统对模具的磨损失效进行判断。结果表明：K的修正值为1.425×10-7，与实际测量值的吻合度达91.47％，预测寿命为6351件，与实际生产情况6400件相吻合；对磨损失效模具进行了机器视觉判断，验证了机器视觉技术在锻造模具磨损检测方向的可行性。

Due to the influence of alternating stress during the actual production process, hot forging mold has complex stress conditions and a very harsh service environment. Therefore, based on the Archerd wear model, the wear coefficient K value of the wear model was calculated by comparing the finite element simulation result of a typical crankshaft forging die with the actual wear amount to obtain a modified Archerd wear model suitable for the hot forging production of crankshaft. Then, the die life was predicted by the modified Archerd wear model, and the wear and failure of the die were judged based on the machine vision system. The results show that the correction value of K is 1.425×10-7, and the agreement with the actual measured value is 91.47%. The predicted life is 6351 pieces, which is consistent with the actual production condition of 6400 pieces. Machine vision judgment is performed on the wear and failure die to verify the feasibility of machine vision technology in forging die wear detection.

基金项目：

作者简介：李朝昆（1996-），男，硕士 E-mail：444580543@qq.com 通信作者：曾琦（1974-），女，博士，研究员 E-mail：laxzengq@163.com

参考文献：

[1] 田福祥,王者静.现代模具技术及其进展[J].模具制造,2002，(3):3-6.

Tian F X，Wang Z J. Modern mold technology and its progress [J]. Mold Manufacturing，2002，(3): 3-6.

[2] 徐华,胡双锋,付秀娟.基于Deform的三缸曲轴模锻设计[J].锻压技术，2022，47(1):161-167.

Xu H，Hu S F，Fu X J. Design of three cylinder crankshaft die forging based on Deform [J]. Forging & Stamping Technology，2022,47(1): 161-167.

[3] 金飞翔,董奇,徐梦洁.基于有限元铝合金复杂精密锻造模具失效分析及优化[J].锻压技术，2023,48(2):180-184.

Jin F X，Dong Q，Xu M J. Failure analysis and optimization of complex precision forging dies for aluminum alloy based on finite element method [J]. Forging & Stamping Technology，2023，48(2): 180-184.

[4] 陈小刚,陈贵清.基于Archard理论的曲轴模具磨损研究[J].热加工工艺,2013,42(7):125-127.

Chen X G，Chen G Q. Research on crankshaft die wear based on Archard theory [J]. Hot Working Technology，2013,42(7): 125-127.

[5] 车路长,蒋平,刘俊,等.Ti-6Al-4V钛合金筋板类吊挂锻造成形工艺优化及模具磨损研究[J].精密成形工程,2022,47(10):250-256.

Che L C，Jiang P，Liu J，et al. Optimization of Ti-6Al-4V titanium alloy suspension forging process and research on mold wear [J].

Journal of Netshape Forming Engineering，2022，47(10): 250-256.

[6] Lukasz Dworzak，Hawryluk M R，Ziemba J P. Wear analysis of die inserts in the hot forging process of a forked type forging using reverse scanning techniques[J]. Advances in Science and Technology-Research Journal，2017，11(4): 225-238.

[7] Cai L G，Liu H D，Li D，et al. Mold wear during die forging based on variance analysis and prediction of die life [J]. Transactions of Nanjing University of Aeronautics and Astonautis，2020，37(6): 872-883.

[8] Ulf Sthlberg，Jonas Hallstrm. A comparison between two wear models[J]. Journal of Materials Processing Technology，1999，87(1-3): 223-229.

[9] 蒋钰钢.高速切削加工过程有限元仿真研究[D].重庆：重庆大学,2019.

Jiang Y G. Finite Element Simulation Research on High Speed Cutting Process [D]. Chongqing: Chongqing University，2019.

[10]Rabinowicz E. New coefficients predict wear of metal parts[J].Product Engineering，1958，29:71-73.

[11]Rabinowicz E. Wear coefficients-Metals[J].Wear Control Handbook，1980,103(2):188-194.

[12]Obiko J O，Mwema F M. Forging optimization process using numerical simulation and Taguchi method [J]. SN Applied Sciences，2020，5(33): 712-721.

服务与反馈：

【文章下载】【加入收藏】