A Predictive Model for Temperature Rise of Spindle–Bearing Integrated System

Deng, Xiaolei; Fu, Jianzhong; Zhang, Kun

doi:10.1115/1.4029445

Cited by 10 publications

(5 citation statements)

References 14 publications

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“…The principle is as follows. Given a set (x (1) i , x (2) i , :::, x (n) i , y i ), i = 1, 2, :::, l È É , where [x (1) i , x (2) i , :::, x (n) i ] is the input matrix and y i is the target value, the SVR problem can be reduced to the following objective function:…”

Section: Intelligent Prediction Modelmentioning

confidence: 99%

“…Machine temperature rise prediction modeling can be currently split into two categories: mechanism models and numerical models. The mechanism model 1,2 is based on thermodynamics and the law of conservation of energy to establish a finite element model to predict the change in the temperature field. Some scholars 3 obtained the simulation parameters of the motorized spindle through theoretical calculation, and established a multi-physical field simulation model based on finite element method.…”

Section: Introductionmentioning

confidence: 99%

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Fast identification of machine tool spindle system temperature rise based on multi-model fusion and improved D-S evidence theory

Chen,

Fang,

Deng

et al. 2024

Proceedings of the Institution of Mechanical Engineers, Part C:

Self Cite

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Thermal equilibrium test is the key means to obtain the thermal characteristics of machine tools. In order to shorten the test period and reduce the research and development cost, a novel fast temperature rise identification method for machine tool spindle systems is proposed. The existing prediction identification methods ignore the limitation of the single prediction model, leading to large error fluctuations in different environments. In this study, various intelligent prediction models are combined with the improved D-S evidence theory to improve the accuracy and robustness of the prediction. Firstly, based on the virtual prediction, the evidence identification framework is established through the multiple evaluations of the data information in the evidence segment. Then, the weight allocation of each basic prediction model is carried out by the evidence combination theory. In this process, the evidence identification framework is reconstructed according to the improved strategy to avoid the high conflict problem in classical evidence theory. Finally, the fusion prediction of multiple models can be realized. The VM-850L machining center was selected as the research object for the thermal equilibrium test to evaluate the proposed method. The results show that the proposed multi-model fusion prediction method can accurately predict the temperature rise of selected points in a short time. Moreover, the prediction accuracy is significantly improved compared with the traditional single model. The proposed method has good universality and is expected to be popularized and applied more widely.

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Section: Intelligent Prediction Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fast identification of machine tool spindle system temperature rise based on multi-model fusion and improved D-S evidence theory

Chen,

Fang,

Deng

et al. 2024

Proceedings of the Institution of Mechanical Engineers, Part C:

Self Cite

View full text Add to dashboard Cite

show abstract

“…Therefore, the relationship between the elastic modulus and temperature was approximately expressed in Equation ( 14). According to the temperature rise history of a point in the conductor described in Reference [27], we used the first-order inertia link to simulate the temperature rise process of the connecting shaft according to its final temperature (about 500°C) and the action time. The time constant was set to 50, as shown in Equation ( 15), which will be helpful in modeling throat deformation in the next chapter.…”

Section: Validation Of the Loadmentioning

confidence: 99%

Hybrid Modeling Method of SDR Interstage Valve Based on Mechanism and Data-Driven

Wang

Zeng

Chen³

et al. 2022

International Journal of Aerospace Engineering

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Variable-throat adjustment is the most practical flow regulation method of solid ducted rocket ramjet (SDR). The high-fidelity mathematical model of the interstage valve is the basis for realizing high-precision gas flow and thrust regulation. In this paper, the complex effect of gas was divided into load and throat deformation effect. The load was mainly determined by the clearance, friction torque, and pneumatic torque that the valve was subjected to during operation. And the throat deformation was determined primarily by the deposition and ablation of the valve faced in the gas. Therefore, we could divide the valve model into three parts: the servo motor model, the load characteristic model, and the deformation model of the actual acting throat (referred to as the throat). Given, we have designed a cold-air experiment program, using cold air to equalize the valve load. Furthermore, we analyzed its mechanism of action and established the load model using the experimental data and neural network. Finally, the deformation mechanism of the throat was investigated, and simultaneously, the deformation model was shown based on the flight test data. Compared with the traditional interstage valve model, the model established in this paper is closer to the actual working conditions, which is helpful to carry out the more comprehensive and practical ground simulation. It has essential reference value for further realizing the precise regulation of gas flow.

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“…Although the FEM is more complicated in the process of solving the bearing temperature field, it can effectively reflect the temperature inside the rolling bearing and has certain advantages in analyzing the temperature field of a specific three-dimensional model. Deng et al [19] explored the temperature calculation model of the spindle-bearing system, which has high computational efficiency and accuracy. Aleksandar et al [20] studied the internal temperature of high-speed spindles, using a temperature computation model that reflects the temperature differences of ball bearings at different locations.…”

Section: Introductionmentioning

confidence: 99%

The Simulation Analysis and Experimental Study on the Temperature Field of Four Row Rolling Bearings of Rolling Mill under Non-Uniform Load Conditions

Sun,

Guo,

Guo

et al. 2024

Sensors

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As a key component of the rolling mill, the four-row cylindrical roller bearing (FCRB) operates under complex working conditions of high speed, high temperature, and heavy load. Due to the lack of an effective temperature test scheme for rolling mill bearings, a too high temperature can easily lead to bearing failure or damage under unsteady conditions. To reveal the internal temperature distribution law of four-row roller bearings of rolling mills and solve the common problem of difficult temperature monitoring of rolling mill bearings, in this paper, a four-row cylindrical roller bearing of 1140 mm cold rolling six-high mill is taken as the research object, and the temperature field calculation model for four-row cylindrical roller bearings is established. Firstly, the mechanical analysis model of FCRB is established on the basis of single row bearing by slice method. Secondly, the mechanical calculation model of FCRB is established by the Newton–Raphson method (NRM) and the finite element method (FEM). Thirdly, based on the mechanical calculation model, the finite element method is used to establish the temperature field model of FCRB under uniform load distribution and non-uniform load distribution. Finally, the temperature test experiment is carried out with the FCRB in the rolling mill fault diagnosis test bench. The results show that the error between the FCRB temperature calculation model and the experimental results is less than 10%. It can be seen that the uneven temperature distribution of FCRB is mainly caused by the uneven load distribution. The temperature distribution along the axial direction of the bearing is related to the load distribution of each column, while the circumferential temperature distribution is related to the azimuth angle.

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A Predictive Model for Temperature Rise of Spindle–Bearing Integrated System

Cited by 10 publications

References 14 publications

Fast identification of machine tool spindle system temperature rise based on multi-model fusion and improved D-S evidence theory

Fast identification of machine tool spindle system temperature rise based on multi-model fusion and improved D-S evidence theory

Hybrid Modeling Method of SDR Interstage Valve Based on Mechanism and Data-Driven

The Simulation Analysis and Experimental Study on the Temperature Field of Four Row Rolling Bearings of Rolling Mill under Non-Uniform Load Conditions

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