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Thermal characteristics of a CNC feed system under varying operating conditions
Affiliation:1. State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, PR China;2. Research Institute of Zhejiang University—Taizhou, Taizhou 318000, Zhejiang, PR China;1. Dipartimento di Fisica e Scienze della Terra, Università degli Studi di Ferrara, Ferrara, Italy;2. Department of Physics and Astronomy, University of Kentucky, Lexington, USA;1. Université Paris Ouest, Laboratoire Thermique Interfaces Environnement (LTIE), EA 4415, 50 rue de Sèvres, 92410 Ville d’Avray, France;2. Thales Global Services, 19-21 Avenue Morane Saulnier, 78140 Vélizy-Villacoublay, France;1. State Key Laboratory of Mechanical Transmission, Chongqing University, China;2. Nuclear Power Institute of China, China
Abstract:In high-speed and high-precision feed systems, thermal positioning errors are mainly caused by the non-uniform temperature variations and resulting time-varying thermal deformations under different operating conditions. The research presented here ultimately aims to develop a generic method capable of evaluating the thermal characteristics (such as temperature rise of heat sources, thermal positioning error) of the feed system induced by varying operating conditions (feed speed, cutting load and preload of ball screw). The thermal contact resistance between the balls and the inner and outer rings of supporting bearing is calculated using the Hertzian theory and JHM method. Experiments were carried out on a high-speed feed system experimental bench, and the influences of operating conditions on temperature rises of supporting bearings and ball screw nut were analyzed. Based on a WNN-NARMAL2 model, the relationship between temperature rise of supporting bearings and operating conditions was established. Furthermore, with the temperature of the ball screw nut set to be a moving heat source load, the temperature and thermal deformation distributions of the ball screw were simulated. The work described lays a solid foundation for thermal error prediction and compensation of a feed system under varying operating conditions.
Keywords:Thermal error  Wavelet neural network  Operating condition  Feed system
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