Results 21 to 30 of about 1,892,423 (234)

Study of Error Propagation in the Transformations of Dynamic Thermal Models of Buildings [PDF]

Journal of Control Science and Engineering, 2017
Dynamic behaviour of a system may be described by models with different forms: thermal (RC) networks, state-space representations, transfer functions, and ARX models. These models, which describe the same process, are used in the design, simulation, optimal predictive control, parameter identification, fault detection and diagnosis, and so on.
Loïc Raillon, Christian Ghiaus
openaire   +4 more sources

Thermal error modeling based on BiLSTM deep learning for CNC machine tool

Advances in Manufacturing, 2021
The machining accuracy of computer numerical control machine tools has always been a focus of the manufacturing industry. Among all errors, thermal error affects the machining accuracy considerably.
Puling Liu, Z. Du, Huimin Li, Ming Deng, Xiaobing Feng, Jian-guo Yang   +5 more
semanticscholar   +1 more source

A review on transfer learning in spindle thermal error compensation of spindle [PDF]

Advanced Manufacturing
Data-driven approaches offer unprecedented opportunities for smart manufacturing to facilitate the transition to Industry 4.0-based production. One of the key factors affecting the accuracy of machine tools is the thermal error caused by thermal ...
Yue Zheng, Guoqiang Fu, Sen Mu, Sipei Zhu, Kunlong Lin, Long Yang   +5 more
doaj   +1 more source

Thermal Error Model of Linear Motor Feed System Based on Bayesian Neural Network

IEEE Access, 2021
The linear motor feed system has been in service in complex working conditions for a long time, thus causing the nonuniform distribution of the temperature field distribution.
Shengsen Liu, Zeqing Yang, Qiang Wei, Yingshu Chen, Libing Liu   +4 more
doaj   +1 more source

ASSESSING GEO-TYPICAL TECHNIQUES FOR MODELING BUILDINGS USING THERMAL SIMULATIONS [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022
Building modeling from remote sensing data is essential for creating accurate 3D and 4D digital twins, especially for temperature modeling. In order to represent buildings as gap-free, visually appealing, and rich in details models, geo-typical ...
D. Bulatov, B. Kottler, E. Strauss, G. Häufel, M. May, P. Helmholz, F. Mancini   +6 more
doaj   +1 more source

Application of Grey System Model to Thermal Error Modeling on Machine Tools [PDF]

, 2006
The basic principle and method of grey system model and its application in thermal error modeling on machine tools has been presented. How to utilize thermal error sequence surveyed to model and predict is discussed by adopting total data GM (1,1) model, new information GM(1,1) model and metabolic GM(1,1) model after function transform is brought ...
Yongxiang Li, Jianguo Yang, Hongtao Zhang, Hengchao Tong   +3 more
openaire   +1 more source

EFFECTS OF COOLING SYSTEMS ON THE THERMAL BEHAVIOUR OF MACHINE TOOLS AND THERMAL ERROR MODELS

Journal of Machine Engineering, 2020
Today, cooling systems are increasingly applied to the structure of machine tools (MT). Unfortunately, to date there have been few efforts to precisely control these cooling systems, which inhibits the full utilisation of their potential to improve MT thermal behaviour (to reduce thermal errors). Moreover, the effects of cooling systems, especially the
Otakar Horejš, Martin Mareš, Štěpán Fiala, Lukáš Havlík, Petr Stříteský   +4 more
openaire   +2 more sources

Modeling of Thermal Contact Resistance of Ball Screws Considering the Load Distribution of Balls

, 2021
A new analytical method for the modeling of the thermal contact resistance of ball screws considering the load distribution of balls is proposed in this research.
Zan, Tao, Gao, Xiangsheng, Li, Qi, Wang, Min, Ma, Jiqian   +4 more
core   +2 more sources

An Unsupervised Regularization and Dropout based Deep Neural Network and Its Application for Thermal Error Prediction

Applied Sciences, 2020
Due to the large size of the heavy duty machine tool-foundation systems, space temperature difference is high related to thermal error, which affects to system’s accuracy greatly. The recent highly focused deep learning technology could be an alternative
Yang Tian, Guangyuan Pan
doaj   +1 more source

Thermal Error Analysis of Five-Axis Machine Tools Based on Five-Point Test Method

Lubricants, 2022
The accuracy of five-axis machine tools is a key performance indicator. Among the various error sources of high precision five-axis machine tools, thermal and geometric errors occupy the majority.
Yu Li, Hongchuan Tian, Difei Liu, Quanbo Lu   +3 more
doaj   +1 more source