Bayesian linear regression for surface roughness prediction-Reference-Cited by-同舟云学术

Bayesian linear regression for surface roughness prediction

Published:2020-08 Issue: Volume:142 Page:106770
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Kong Dongdong^ORCID,Zhu Junjiang,Duan Chaoqun^ORCID,Lu Lixin,Chen Dongxing

Funder

Research and Development

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference36 articles.

1. Advanced monitoring of machining operations;Teti;CIRP Ann-Manuf. Techn.,2010

2. A new algorithm for developing a reference-based model for predicting surface roughness in finish machining of steels;Fang;Int. J. Prod. Res.,1997

3. A multiple regression model to predict in-process surface roughness in turning operation via accelerometer;Huang;J. Ind. Tech.,2001

4. Surface roughness prediction based on cutting parameter and tool vibration in turning operation;Abouelatta;J. Mater. Process. Tech.,2001

5. Prediction of surface roughness and dimensional deviation by measuring cutting forces and vibrations in turning process;Risbood;J. Mater. Process. Tech.,2003

Cited by 71 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A review of artificial intelligent methods for machined surface roughness prediction;Tribology International;2024-11

2. Extreme learning machine oriented surface roughness prediction at continuous cutting positions based on monitored acceleration;Mechanical Systems and Signal Processing;2024-10

3. A multi-target predictive model for predicting tool wear and surface roughness;Expert Systems with Applications;2024-10

4. Prediction of Ship-Unloading Time Using Neural Networks;Applied Sciences;2024-09-12

5. A data-driven method for prediction of surface roughness with consideration of milling tool wear;The International Journal of Advanced Manufacturing Technology;2024-09-10