Prediction of Transmission Error of Cable Precision Drive based on BP Neural Network

Xie Hongwei; Tao Zhong; Zhou Xiaoguang; Hou Junzhan; Zhang Weiguo; Wang Honghao

doi:10.16578/j.issn.1004.2539.2017.09.026

您当前的位置：

首页 >

文章列表页 >

Prediction of Transmission Error of Cable Precision Drive based on BP Neural Network

更新时间：2022-10-20

- Prediction of Transmission Error of Cable Precision Drive based on BP Neural Network
- Vol. 41, Issue 9, Pages: 130-134(2017)
- 作者机构：
  
  1. 西安应用光学研究所
  2. 陆军航空兵军事代表局驻西安地区军代室
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2017.09.026
  CLC：
扫描看全文
[1]谢宏伟,陶忠,周晓光,侯军占,张卫国,王宏浩.基于BP神经网络的钢丝绳精密传动误差预测[J].机械传动,2017,41(09):130-134.

Xie Hongwei, Tao Zhong, Zhou Xiaoguang, et al. Prediction of Transmission Error of Cable Precision Drive based on BP Neural Network. [J]. 41(9):130-134(2017)
[1]谢宏伟,陶忠,周晓光,侯军占,张卫国,王宏浩.基于BP神经网络的钢丝绳精密传动误差预测[J].机械传动,2017,41(09):130-134. DOI： 10.16578/j.issn.1004.2539.2017.09.026.

Xie Hongwei, Tao Zhong, Zhou Xiaoguang, et al. Prediction of Transmission Error of Cable Precision Drive based on BP Neural Network. [J]. 41(9):130-134(2017) DOI： 10.16578/j.issn.1004.2539.2017.09.026.

摘要

针对不同绳组数的钢丝绳精密传动方式,研究了基于神经网络的传动误差预测方法。以预紧力、负载、转角为输入,传动误差为输出,建立了双隐含层BP神经网络模型。在不同绳组数的传动条件下,测试了不同预紧力、负载和转角下的传动误差。将传动误差测试结果分为训练组和预测组,对网络进行训练和检验。测试结果显示,从动轮在0°,1,80°范围内转动时,传动误差随转角的增大而增大,最大值为5.6 mrad,随绳组数的增加而降低。在该转角范围内,模型预测误差小于0.294 mrad。表明采用双隐含层BP神经网络模型对传动误差进行预测是有效的。

Abstract

For cable drive with different rope number,the transmission error prediction method is explored based on BP neural network. A prediction model for transmission error is developed by a double hidden layer BP neural network. The input parameters of the model are preload,load and rotation angle respectively. The output parameter is the transmission error. The transmission errors under different conditions are tested firstly.And then the results are divided to training samples and prediction samples,which are used to train the network and verify the performance of the trained network. The experiment results show that the transmission error increases with the increase of rotation angle at the range of 0 to 180. And the biggest value is 5. 6 mrad,the prediction error is less than 0. 294 mrad. In conclusion,the double hidden layer BP neural network is effective to predict transmission error.

关键词

钢丝绳传动传动误差预测BP神经网络预紧力负载

Keywords

Cable driveTransmission error predictionBP neural networkPreload forceLoad

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Design and Motion Analysis of an Automatic Retractable Manipulator for a Vehicle-mounted Wheelchair

A Self-adaptive CS Algorithm and Its Application in Fault Diagnosis of Wind Turbine Gearboxes

Fault Diagnosis Method of Planetary Gearboxes Based on LMD Permutation Entropy and BP Neural Network

Transmission Error Prediction of RV Reducer based on SSA-BP

Research on Solving the Excavation Pose of Shield Machine based on Neural Network-Newton Hybrid Algorithm

Related Author

No data

Related Institution

College of Mechanical and Vehicle Engineering, Hunan University

Tianjin Key Laboratory of Modern Electromechanical Equipment Technology

School of Mechanical Engineering, Tiangong University

Engineering College, Honghe University, Mengzi

College of Mechanical and Control Engineering, Guilin University of Technology

⁰