Thermal Error Modelling of the Spindle Using Neurofuzzy Systems
Joint Authors
Li, Yanlei
Tang, Xiaoqi
Feng, Jingan
Song, Bao
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-03-09
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This paper proposes a new combined model to predict the spindle deformation, which combines the grey models and the ANFIS (adaptive neurofuzzy inference system) model.
The grey models are used to preprocess the original data, and the ANFIS model is used to adjust the combined model.
The outputs of the grey models are used as the inputs of the ANFIS model to train the model.
To evaluate the performance of the combined model, an experiment is implemented.
Three Pt100 thermal resistances are used to monitor the spindle temperature and an inductive current sensor is used to obtain the spindle deformation.
The experimental results display that the combined model can better predict the spindle deformation compared to BP network, and it can greatly improve the performance of the spindle.
American Psychological Association (APA)
Feng, Jingan& Tang, Xiaoqi& Li, Yanlei& Song, Bao. 2016. Thermal Error Modelling of the Spindle Using Neurofuzzy Systems. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112676
Modern Language Association (MLA)
Feng, Jingan…[et al.]. Thermal Error Modelling of the Spindle Using Neurofuzzy Systems. Mathematical Problems in Engineering No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1112676
American Medical Association (AMA)
Feng, Jingan& Tang, Xiaoqi& Li, Yanlei& Song, Bao. Thermal Error Modelling of the Spindle Using Neurofuzzy Systems. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112676
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112676