Results 11 to 20 of about 443,795 (288)

Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm

Machines, 2021
High-speed motorized spindle heating will produce thermal error, which is an important factor affecting the machining accuracy of machine tools. The thermal error model of high-speed motorized spindles can compensate for thermal error and improve ...
Zhaolong Li, Bo Zhu, Ye Dai, Wenming Zhu, Qinghai Wang, Baodong Wang   +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

The check problem of food thermal processes: A mathematical solution [PDF]

, 2015
To calculate the sterilizing value U, and hence, the microbial lethality F in thermal processes of the canned food, starting from the knowledge of heating time B, a mathematical modeling was carried out.
Friso, Dario
core   +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

Optimal Parameter Extraction Scheme of Current Sources and Bias Dependent Elements for HBT by searching the whole unknown Parameter Space [PDF]

, 2003
New analytical expressions for the dynamic resistance,transconductance,base-collector internal capacitance,and base-emitter internal capacitance are derived.And a new scheme,to extract the current source parameters,thermal parameter,and small signal ...
Kim, I.S., Song, J.S., SuH, Youngsuk
core   +1 more source

Prediction of Thermo-Physical Properties of TiO2-Al2O3/Water Nanoparticles by Using Artificial Neural Network [PDF]

, 2020
In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol–gel method. The
Ahmadi, Mohammad Hossein, Ghazvini, Mahyar, Khadang, Amirhosein, Maddah, Heydar, Mosavi, Amirhosein, Nabipour, Narjes, Sadeghzadeh, Milad   +6 more
core   +2 more sources

Asteroid Diameters and Albedos from NEOWISE Reactivation Mission Years 4 and 5 [PDF]

, 2020
The Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE) spacecraft has been conducting a two-band thermal infrared survey to detect and characterize asteroids and comets since its reactivation in 2013 December.
Bauer, J. M., Cutri, R. M., Grav, T., Kramer, E., Mainzer, A. K., Masiero, Joseph R., Pittichová, J., Sonnett, S., Wright, E. L.   +8 more
core   +2 more sources

Thermal Error Modeling for Machine Tools: Mechanistic Analysis and Solution for the Pseudocorrelation of Temperature-Sensitive Points

IEEE Access, 2020
The temperature-sensitive point is the input variable of the thermal error compensation model of computer numerical control (CNC) machine tools. At present, the most commonly used selection method is to measure the multipoint temperature and thermal ...
Hui Liu, Enming Miao, Liyin Zhang, Long Li, Yinlong Hou, Dafeng Tang   +5 more
doaj   +1 more source

The Thermal Error Modeling with Deep Transfer Learning

Journal of Physics: Conference Series, 2020
Abstract Thermal error of CNC machine tools is one of the main factors affecting the machining accuracy. The data-driven method for thermal error modeling is an effective and efficient, but they have some flaws, such as poor accuracy, bad robustness, and etc. because of having no quite enough data set and imbalanced data set.
Peiwen Li, Ping Lou, Junwei Yan, Nianyun Liu   +3 more
openaire   +1 more source