Thermal error prediction and reliability sensitivity analysis of motorized spindle based on Kriging model. (September 2021)

• Record Type: Journal Article
• Authors: Jiang, Zhiyuan; Huang, Xianzhen; Chang, Miaoxin; Li, Chun; Ge, Yang
• Is Part Of: Engineering failure analysis. Volume 127(2021)
• Publication Date: 2021-09
• Subjects: Motorized spindle -- Multi-physical field coupling -- Kriging model -- Quasi-Monte Carlo -- Reliability sensitivity analysis; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2021.105558
• Languages: English
• ISSNs: 1350-6307

Abstract

Highlights: A new thermal error analysis model of motorized spindle is proposed based on multi-physical field coupling; The influence of random physical parameters of motorized spindle on thermal error is considered; Kriging model is used to replace the multi-physical field coupling method to improve calculation efficiency; A method for calculating reliability and reliability sensitivity of the motorized spindle is established; Abstract: A large amount of heat is generated by motorized spindles during the machining process of CNC machine tools, and it is the main factor restricting the further improvement of machining accuracy. Furthermore, physical properties and material parameters of the motorized spindle are uncertain in practical engineering. Therefore, it is necessary to evaluate the reliability and reliability sensitivity of the motorized spindle system. In this paper, a new thermal error estimation model of motorized spindle is established based on multi-physical field coupling theory. The Quasi-Monte Carlo (QMC) method is introduced to calculate the reliability of the motorized spindle system. An accurate and efficient surrogate model, called Kriging, is used to calculate the reliability and reliability sensitivity of the motorized spindle system to further improve computational efficiency. Moreover, the experimental platform for measuring the temperature and thermal error of the motorized spindle is built to verify the applicability of the proposed model. The analytical framework proposed in this paper provide a guidance for the reliability design and robustness evaluation of motorized spindle.