Transactions of Materials and Heat Treatment

Title：Self-adaptive straightening technology of thin-walled slender shaft

Authors： Han Bin Wang Xiaodi Teng Chaobin Li Yinghui Wang Jucun Zhang Qi

Unit： Xi′an Jiaotong University AECC South Industy Company Limited

KeyWords： shaft parts self-adaptive straightening technology BP neural network algorithm three-point bending straightening intelligent straightening

ClassificationCode：TH69

year,vol(issue):pagenumber：2022,47(2):100-105

Abstract：

In order to improve the detection accuracy of existing straightness straightening equipment and improve the calculation accuracy of straightening parameters. The advantages and disadvantages of the existing straightening methods for shaft parts were analyzed. Aiming at the straightness straightening processing of common slender shaft parts，the over structure of a self-adaptive straightening equipment for thin-walled slender shaft parts with the straightening accuracy of 0.1 mm·m-1 was designed. The straightening process was established based on machine learning consisting of BP neural network algorithm and database accumulation. Based on the basic principle of three-point bending and straightening，a BP neural network structure suitable for this straightening process of this equipment was determined. Its structure is that the input layer has seven nodes，the output layer has one node, and the single hidden layer has six nodes. By verifying the accuracy of the neural network structure, it can be concluded that when the database containes 800 sets of experimental data, the accuracy requirements can be met after one straightening process. This equipment can greatly reduce the numbers of straightening.

Funds：

西安交通大学校企合作科研项目（N-20010394）

作者简介：韩宾（1986-），男，博士，副教授,E-mail：hanbinghost@mail.xjtu.edu.cn ;通信作者：张琦（1978-），男，博士，教授,E-mail：henryzhang@mail.xjtu.edu.cn

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