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The ball screw system operates under the coupling condition of external loads, preloads, and thermal loads, and its thermo-mechanical characteristics significantly affect its dynamics performance. Therefore, a thermal-mechanical real-time dynamics model is necessary. In this work, the screw systems thermo-mechanical coupling mechanism was first analysed. Second, a new dynamic thermal network model for the screw system with moving heat excitation was proposed using the position of the moving nut obtained by FANUC Open CNC API Specifications (FOCAS), which can rapidly determine the transient temperature field. Based on this model, a new thermo-mechanical coupling real-time dynamics model of the screw system was established. The influence of temperature on dynamics characteristics was analysed using the dynamics model, and the results showed that the system preload caused by thermal elongation of the screw decreases with an increase in temperature. The system preload caused by the thermal deformation of the bearing increases with an increase in temperature. The total preload of the system depends on the interaction between the thermal deformation of the screw and the axial thermal deformation of the bearing. Additionally, the system stiffness and natural frequency variation relative to the increase in temperature and position of the carriage were obtained. Thermo-mechanical dynamics performance experiments of the feed system were carried out to validate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

In view of the time-varying complexity of the heat source for the ball screw feed system, this paper proposes an adaptive inverse problem-solving method to estimate the time-varying heat source and temperature field of the feed system under working conditions. The feed system includes multiple heat sources, and the rapid change of the moving heat source increases the difficulty of its identification. This paper attempts to develop a numerical calculation method for identifying the heat source by combining the experiment with the optimization algorithm. Firstly, based on the theory of heat transfer, a new dynamic thermal network model was proposed. The temperature data signal and the position signal of the moving nut captured by the sensors are used as input to optimize the solution of the time-varying heat source. Then, based on the data obtained from the experiment, finite element software parametric programming was used to optimize the estimate of the heat source, and the results of the two heat source prediction methods are compared and verified. The other measured temperature points obtained by the experiment were used to compare and verify the inverse method of this numerical calculation, which illustrates the reliability and advantages of the dynamic thermal network combined with the genetic algorithm for the inverse method. The method based on the on-line monitoring of temperature sensors proposed in this paper has a strong application value for heat source and temperature field estimation of complex mechanical structures.

Abstract: A methodology for modeling and simulating the electro-thermal behavior of an enclosed electronic package is presented and validated. The electro-thermal model is constructed using system dynamics. The system model, in which the electrical and the thermal domain are combined, is presented. The developed model describes the dynamic thermal behavior system that was an electronic device in the test enclosure. An effective way to identify the thermal parameters of the system, especially the thermal contact resistance, is suggested. In detail, the new method for thermal resistance identification is based on the temperature difference behavior between the component and the air temperature inside the enclosure. Based on the proposed model, either the variation of the heat source or the ambient temperature can be estimated. Simulated results were in good agreement with the measured temperature in the transient state accompanying with the variation of the environment. [Copyright &y& Elsevier]

In view of the time-varying complexity of the heat source for the ball screw feed system, this paper proposes an adaptive inverse problem-solving method to estimate the time-varying heat source and temperature field of the feed system under working conditions. The feed system includes multiple heat sources, and the rapid change of the moving heat source increases the difficulty of its identification. This paper attempts to develop a numerical calculation method for identifying the heat source by combining the experiment with the optimization algorithm. Firstly, based on the theory of heat transfer, a new dynamic thermal network model was proposed. The temperature data signal and the position signal of the moving nut captured by the sensors are used as input to optimize the solution of the time-varying heat source. Then, based on the data obtained from the experiment, finite element software parametric programming was used to optimize the estimate of the heat source, and the results of the two heat source prediction methods are compared and verified. The other measured temperature points obtained by the experiment were used to compare and verify the inverse method of this numerical calculation, which illustrates the reliability and advantages of the dynamic thermal network combined with the genetic algorithm for the inverse method. The method based on the on-line monitoring of temperature sensors proposed in this paper has a strong application value for heat source and temperature field estimation of complex mechanical structures. [ABSTRACT FROM AUTHOR]