Heat Source Forecast of Ball Screw Drive System Under Actual Working Conditions Based on On-Line Measurement of Temperature Sensors

Abstract

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.

Research on an Equivalent Heat Source Model of the AC Arc in the Short Gap of a Copper-Core Cable and a Fire Risk Assessment Method

“…Compared with the traditional optimization algorithm, the genetic algorithm optimization has the advantages of group search, high search efficiency, operation speed block, and good adaptability. Figure 8 shows the process of the genetic algorithm, including population initialization, fitness function, selection operation, crossover operation, and mutation operation [ 37 , 38 ]. The first step is to initialize the population of the genetic algorithm.…”

Time-varying thermoelastic coupling analysis of heat source of ball screw feed drive system

“…These studies start with boundary conditions, and the time-varying heat source obtained is induced by the external environment, ignoring the coupling effect of ball, screw and nut in friction heat generation, so the theoretical solution of time-varying heat source obtained is one-sided. Li et al obtained the variation rule of heat source through parameter identi cation, obtained the temperature of monitoring points through sensors, etc., and further tted the intensity of heat source, or re ected the state of heat source through the side of experimental data [11][12][13][14]. This method has high application value for speci c working conditions, but the heat source model is not universal due to the lack of theoretical basis.…”

Study on real-time thermal–mechanical–frictional coupling characteristics of ball bearings based on the inverse thermal network method

“…Hence, the thermal-mechanical coupling characteristics of bearings need to be studied. In the existed literature, many works were conducted in modeling the heat transfer and temperature field of rolling bearings based on the finite-element method (FEM) [13][14][15][16][17] and the thermal network model (TNM). [18][19][20][21][22][23][24] Huang et al 13 presented a new inverse FEM used for determining time-varying heat generations.…”

“…Than et al 14 also presented a novel inverse model to calculate timevarying heat sources using experimentally measured temperatures based on the FEM. Li et al 15 proposed a new inverse problem-solving model by combining the genetic algorithm and the FEM to investigate the timevarying heat source and temperature distribution. Zhou et al 16 proposed a calculation model to derive the temperature distribution of ball bearings under different radial loads and rotating speeds based on the FEM.…”

“…So, inverse heat transfer problems have been researched by some scholars. [13][14][15] However, these models based on the FEM are not suitable for real-time analysis.…”