Optimal selection method and system for power and position parameters of active temperature control source of machine tool

Abstract

The invention discloses a machine tool active temperature control source power and position parameter optimization method and system, and belongs to the technical field of machining, and the method comprises the steps: S1, building a quantitative relation between different powers and positions of a temperature control source and thermal deformation; s2, the effect of reducing the machining thermal error of the machine tool is achieved through an active temperature control strategy of adjusting the position and power of a temperature control source; and S3, developing a corresponding engineering application energy-saving active temperature control system. According to the machine tool active temperature control source power and position parameter optimization method and system, firstly, heat source temperature field and deformation field simulation analysis is carried out on a machine tool heat generation and dissipation model, the influence rule of temperature control source power on thermal deformation is analyzed and summarized, and the influence rule of temperature control source position on thermal deformation is revealed through a neural network means; then, an active temperature control strategy for searching the optimal temperature control source power and position is formulated, and finally, a corresponding engineering application energy-saving active temperature control system is established for reducing thermally induced errors of a machine tool and improving the part machining precision.

Description

Technical Field

[0001] The present invention relates to the technical field of machining, and in particular to a method and system for optimizing the power and position parameters of an active temperature control source for a machine tool. Background Art

[0002] High-grade CNC machine tools are increasingly widely and deeply used in fields such as vehicle and ship manufacturing, aerospace, and medical devices. The machining level of precision machine tools is an important evaluation index of the manufacturing capacity. The key to improving the machining level of precision machine tools is to reduce the machining and manufacturing errors of the machine tool, and the thermal error accounts for 60-75% of the machining and manufacturing errors of the machine tool. In order to reduce the thermal error of precision machine tools, structural thermal balance design, thermal error compensation, and active temperature field control are the main ways to reduce or suppress thermal errors. Among them, active temperature field control has received extensive attention due to its low cost and simple operation. The principle of active temperature field control is to change the temperature field of the machine tool by arranging active temperature control cold / heat sources on the machine tool, thereby adjusting the deformation field of the key functional components of the machine tool, and finally reducing the relative pose change between the tool and the workpiece and improving the machining and manufacturing errors of the machine tool. However, at present, due to the influence of factors such as the diversity of machine tool types, the complexity of structures, and the time-variability of working conditions, although the thermal characteristics of machine tools have been well studied, the universal thermal laws behind them have not been systematically summarized. And although the active temperature control method has been applied, no corresponding temperature control strategy and engineering application system have been formed, and the optimal effect of reducing the influence of thermal error on machining accuracy cannot be achieved. It is necessary to summarize the thermal characteristic laws and propose an active thermal error control strategy. Therefore, there is an urgent need to propose a method for finding the optimal parameters of the active temperature control source to achieve the best control effect of the machining and manufacturing errors of the machine tool, and to develop an energy-saving engineering application system. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for optimizing the power and position parameters of an active temperature control source for a machine tool to solve the problems existing in the above background art.

[0004] To achieve the above purpose, the present invention provides a method for optimizing the power and position parameters of an active temperature control source for a machine tool, including the following steps: S1. Establish a quantitative relationship between different powers, positions of the temperature control source and thermal deformation, specifically including: S11. Establish a heat generation and dissipation model for machine tool thermal simulation analysis and a machine tool machining error evaluation model; S12. Use the induction method to establish a quantitative relationship between the power of the temperature control source and thermal deformation; S13. Use the neural network method to establish a quantitative relationship between the position of the temperature control source and thermal deformation; S2. Achieve the best effect of reducing the machining thermal error of the machine tool through an active temperature control strategy of adjusting the position and power of the temperature control source, specifically including: S21. Establish an evaluation index for the machining thermal error or thermal deformation degree of the machine tool; S22. Solve the machining error degree of the machine tool for different combinations of the positions and powers of the temperature control sources, and find the optimal combination value; S3. Develop a corresponding energy-saving active temperature control system for engineering applications.

[0005] Preferably, step S11 specifically includes: according to the actual structure of the machine tool, simplifying and deleting the fine structures during the modeling process, establishing a simplified structure model of the machine tool, and then using the heat generation situation and heat transfer mechanism of the internal heat sources of the machine tool under different working conditions to establish a heat generation and dissipation model of the machine tool; according to the transfer mechanism of the machining error of the machine tool, analyzing the thermal deformation of the machine tool that seriously affects the relative position of the tool and the workpiece, and establishing a machining error evaluation model of the machine tool; identifying the undetermined parameters of the two models.

[0006] Preferably, step S12 is specifically: through a large number of simulation experiments for different heat sources, including the superimposed thermal deformation caused by a single heat source and the thermal deformation caused by superimposed heat sources, the relationship between the thermal deformations caused by different heat power sources, etc., summarizing the quantitative relationship between the power of the temperature control source and the thermal deformation, and revealing the principle similar to Hooke's law of heat between the heat power and the machining error evaluation model of the machine tool.

[0007] Preferably, step S13 is specifically: based on the thermal deformations generated by the active temperature control sources at different positions obtained from the simulation experiments, expressing the thermal deformations in a suitable data form, using the neural network method with the position value of the temperature control source as the input and the suitable thermal deformation description data as the output, and adopting the neural network fitting algorithm to construct the relationship between the position of the temperature control source and the machining error of the machine tool to obtain a prediction function, and revealing their quantitative relationship.

[0008] Preferably, step S21 is specifically: based on the simulation results of the machine tool under different working conditions, establishing an index for evaluating the machining error of the machine tool on the basis of comprehensively considering the difference between the machining error after temperature control and the machining error before temperature control, so as to evaluate the pros and cons of the temperature control effect.

[0009] Preferably, step S22 is specifically: using the finite element simulation software to traverse the machining errors of the machine tool under different combinations of the powers and positions of the temperature control sources, obtaining its change trend, and obtaining the power and position values when the evaluation index of the machining error degree of the machine tool is optimal.

[0010] Preferably, step S3 is specifically: using the power and position values obtained in step S22 to establish a corresponding energy-saving active temperature control system for engineering applications for this machine tool, and this system should comprehensively consider the comprehensive optimal effects of system energy consumption and machining error.

[0011] The present invention also provides a system for optimizing the power and position parameters of the active temperature control source of the machine tool, including: Model construction module: Establish a heat generation and dissipation model for the machine tool according to the working conditions of the machine tool, and identify the model parameters; specifically including: The first model construction unit establishes a heat generation and dissipation model for the machine tool; The second model construction unit establishes a machining error evaluation model for the machine tool; The undetermined parameter identification unit identifies the undetermined parameters in the heat generation and dissipation model of the machine tool and the machining error evaluation model based on the machine tool usage condition data; Analysis module: Achieve the best effect of reducing the machining thermal error of the machine tool through the active temperature control strategy of adjusting the position and power of the temperature control source; specifically including: The evaluation unit establishes an evaluation index for the degree of machining error of the machine tool; The solution unit solves the thermal deformation degree of different combinations of temperature control source positions and powers, and finds the optimal combination value; Application module: Apply the optimized temperature control source power and position parameters in engineering to achieve the best effect of reducing the machining error of the machine tool.

[0012] Preferably, the construction process of the first model construction unit is: According to the actual structure of the machine tool, simplify and delete the fine structures during the modeling process, establish a simplified structure model of the machine tool, and then use the heat generation situation and heat transfer mechanism of the internal heat sources of the machine tool under different working conditions to establish a heat generation and dissipation model of the machine tool; The construction process of the second model construction unit is: According to the transfer mechanism of the machining error of the machine tool, analyze the thermal deformation of the machine tool that seriously affects the relative position of the tool and the workpiece, and establish a machining error evaluation model of the machine tool; The working process of the undetermined parameter identification unit is: Determine the corresponding thermal boundary conditions in the heat generation and dissipation model of the machine tool according to the actual heat generation and dissipation of the internal heat sources under different working conditions; Determine the error transfer process and the final concentration point in the machining error evaluation model of the machine tool according to the actual assembly relationship of the machine tool structural parts.

[0013] Preferably, the working process of the evaluation unit is: Based on the final concentration point in the machining error evaluation model of the machine tool, according to the simulation results of the machine tool under different working conditions, establish an index for evaluating the machining error of the machine tool by mathematical methods on the basis of considering the difference between the machining error after temperature control and the machining error before temperature control, so as to evaluate the quality of the temperature control effect; The solution process of the solution unit is: Use the finite element simulation software to traverse the machining errors of the machine tool under different combinations of temperature control source powers and positions, reveal the change trend, and obtain the power and position values when the evaluation index of the machining error degree of the machine tool is optimal; The application process of the application module is: Apply the optimized temperature control source power and position parameters for this machine tool in engineering, taking into account the comprehensive optimal effect of system energy consumption and machining error.

[0014] Therefore, the present invention adopts the above-mentioned method and system for optimizing the power and position parameters of the active temperature control source of the machine tool, overcoming the drawbacks existing in the existing active temperature field control process of the machine tool: only considering the direct effect of the active temperature control source on adjusting the thermal error, unable to accurately reflect the quantitative relationship between the thermal power and position of the active temperature control source and the thermal deformation; only considering the influence of the change of a single index on the machining error of the machine tool, unable to accurately reveal the machining error of the machine tool when the power and position of the temperature control source change simultaneously; failing to develop an active temperature control system for engineering applications; the present invention uses the induction method and the neural network method to establish the quantitative relationship law between the thermal power and position of the active temperature control source and the thermal deformation, and achieves the best effect of reducing the machining thermal error of the machine tool through the active temperature control strategy of simultaneously adjusting the power and position of the temperature control source, and develops a corresponding active temperature control system for engineering applications, which can quantitatively, comprehensively, and actually achieve the active temperature field control of the machine tool.

[0015] The technical solution of the present invention will be further described in detail below with reference to the drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flowchart of the method for optimizing the power and position parameters of the active temperature control source of the machine tool according to the present invention; Figure 2 is a flowchart of establishing the quantitative relationship between different powers, positions of the temperature control source and the thermal deformation in the embodiment of the present invention; Figure 3 is a flowchart of achieving the best effect of reducing the machining thermal error of the machine tool in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] The following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the present invention claimed, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0018] Please refer to Figures 1 - 3 , the method for optimizing the power and position parameters of the active temperature control source of the machine tool includes the following steps: S1. Establish the quantitative relationship between different powers, positions of the temperature control source and the thermal deformation; including: S11. According to the actual structure of the machine tool, simplify and delete the small structures during the modeling process, establish a simplified structure model of the machine tool, and then use the heat generation situation and heat transfer mechanism of the internal heat sources of the machine tool under different working conditions to establish a heat generation and dissipation model of the machine tool; according to the transmission mechanism of the machining error of the machine tool, analyze the thermal deformation of the machine tool affecting the relative position of the tool and the workpiece, and establish a machining error evaluation model of the machine tool; identify the undetermined parameters of the two models.

[0019] S12. Through a large number of simulation experiments for different heat sources, including the superposition thermal deformation caused by a single heat source and the thermal deformation caused by superposition heat sources, and the relationship between the thermal deformations caused by heat sources with different thermal powers, etc., summarize the quantitative relationship between the power of the temperature control source and the thermal deformation, and reveal the principle similar to Hooke's law of heat between the thermal power and the machine tool processing error evaluation model.

[0020] S13. Based on the thermal deformations generated by the active temperature control sources at different positions obtained from the simulation experiments, express the thermal deformations with appropriate data. Use the neural network method with the position value of the temperature control source as the input and the appropriate thermal deformation description data as the output. Adopt the neural network fitting algorithm to construct the relationship between the position of the temperature control source and the machine tool processing error to obtain the prediction function, and reveal the quantitative relationship between the two.

[0021] S2. Achieve the best effect of reducing the thermal error of machine tool processing through the active temperature control strategy of adjusting the position and power of the temperature control source. The steps include: S21. Based on the simulation results under different working conditions of the machine tool, establish an index for evaluating the machine tool processing error on the basis of comprehensively considering the difference between the processing error after temperature control and the processing error before temperature control. This index is used to evaluate the quality of the temperature control effect.

[0022] S22. Use the finite element simulation software to traverse the machine tool processing errors under different combinations of the power and position of the temperature control source, reveal the change trend, and obtain the power and position values when the evaluation index of the degree of machine tool processing error is optimal.

[0023] S3. Use the method of finding the optimal power and position of the active temperature control source to establish the corresponding energy-saving active temperature control system for engineering applications. This system should comprehensively consider the overall optimal effect of system energy consumption and processing error.

[0024] The system for optimizing the power and position parameters of the active temperature control source of the machine tool includes: Model construction module: Establish the heat generation and dissipation model of the machine tool and the machine tool processing error evaluation model according to the working conditions of the machine tool, and identify the model parameters; specifically include: The first model construction unit establishes the heat generation and dissipation model of the machine tool; according to the actual structure of the machine tool, simplify and delete the fine structures during the modeling process, establish the simplified structure model of the machine tool, and then use the heat generation situation and heat transfer mechanism of the internal heat sources of the machine tool under different working conditions to establish the heat generation and dissipation model of the machine tool.

[0025] The second model construction unit establishes the machine tool processing error evaluation model; according to the transmission mechanism of the machine tool processing error, analyze the thermal deformation of the machine tool that seriously affects the relative position of the tool and the workpiece, and establish the machine tool processing error evaluation model.

[0026] The unit for identifying undetermined parameters determines the corresponding thermal boundary conditions in the heat generation and dissipation model of the machine tool according to the actual heat generation and dissipation of the internal heat source under different working conditions such as different feed speeds; determines the error transfer process and the final concentration point in the machining error evaluation model of the machine tool according to the actual assembly relationship of the machine tool structural parts.

[0027] Analysis module: Achieves the best effect of reducing the machining thermal error of the machine tool through the active temperature control strategy of adjusting the position and power of the temperature control source. Includes: Evaluation unit: Based on the final concentration point in the machining error evaluation model of the machine tool and the simulation results under different working conditions of the machine tool, a mathematical method is used to establish an index for evaluating the machining error of the machine tool on the basis of comprehensively considering the difference between the machining error after temperature control and the machining error before temperature control. This index is used to evaluate the quality of the temperature control effect.

[0028] Solution unit: Uses finite element simulation software to traverse the machining errors of the machine tool under different combinations of the power and position of the temperature control source, reveals the change trend, and obtains the power and position values when the evaluation index of the machining error degree of the machine tool is optimal.

[0029] Application module: Applies the optimized power and position parameters of the temperature control source for this machine tool in engineering, considering the comprehensive optimal effect of system energy consumption and machining error.

[0030] In this embodiment, a computer program for implementing the method and system for optimizing the power and position parameters of the active temperature control source of the above-mentioned machine tool is also provided.

[0031] In this embodiment, an information data processing terminal for implementing the method and system for optimizing the power and position parameters of the active temperature control source of the above-mentioned machine tool is also provided.

[0032] In this embodiment, a computer-readable storage medium is also provided, including instructions, which when running on a computer, cause the computer to execute the method for optimizing the power and position parameters of the active temperature control source of the machine tool in the above-mentioned embodiment.

[0033] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in whole or in part in the form of a computer program product, the computer program product includes one or more computer instructions. When the computer program instructions are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more integrated available media. The available medium may be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid-state disk (SSD)).

[0034] Therefore, the present invention adopts the above method and system for optimizing the power and position parameters of the active temperature control source of the machine tool. First, through the simulation analysis of the heat source temperature field and deformation field of the machine tool heat generation and dissipation model, the influence law of the thermal power of the temperature control source on thermal deformation is analyzed and summarized, and the influence law of the position of the temperature control source on thermal deformation is revealed by neural network means. Since among all the parameters of the active temperature control source, the position and power are easy to adjust. Therefore, an active temperature control strategy for finding the optimal power and position of the temperature control source is formulated, and finally, a corresponding energy-saving active temperature control system for engineering applications is established to reduce the thermal error of the machine tool and improve the machining accuracy of parts.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify or equivalently replace the technical solutions of the present invention, and these modifications or equivalent replacements do not make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for optimizing power and position parameters of an active temperature control source of a machine tool, characterized in that: The following steps are involved: S1. Establish the quantitative relationship between different power and position of temperature control source and thermal deformation, including: S11. Establish a heat dissipation model and a machine tool processing error evaluation model for machine tool thermal simulation analysis; S12, using the inductive method to establish the quantitative relationship between the temperature control source power and thermal deformation; S13, using a neural network method to establish a quantitative relationship between the temperature control source position and thermal deformation; S2. Active temperature control strategy by adjusting the position and power of the temperature control source to reduce the thermal error of machine tool processing, including: S21. Formulate evaluation indicators for machine tool processing error levels; S22, solving the degree of machine tool processing error for different temperature control source positions and power combinations, and finding the optimal combination value; S3. Develop corresponding energy-saving active temperature control systems for engineering applications.

2. The method for optimizing power and position parameters of a machine tool active temperature control source according to claim 1, characterized in that: Step S11 specifically includes: according to the actual structure of the machine tool, the small structure is simplified and deleted during the modeling process to establish a simplified structure model of the machine tool, and then the heat generation and heat transfer mechanism of the internal heat source of the machine tool under different working conditions is used to establish a heat generation and dissipation model of the machine tool; according to the transmission mechanism of the machine tool processing error, the thermal deformation of the machine tool that affects the relative position of the tool and the workpiece is analyzed to establish a machine tool processing error evaluation model; and the pending parameters of the two models are identified.

3. The method for optimizing power and position parameters of a machine tool active temperature control source according to claim 1, characterized in that: Step S12 is specifically as follows: through simulation experiments on different heat sources, including the relationship between the superimposed thermal deformation caused by a single heat source and the thermal deformation caused by superimposed heat sources, and the thermal deformation caused by heat sources with different thermal powers, the quantitative relationship between the temperature control source power and the thermal deformation is summarized, and the principle between the thermal power and the machine tool processing error evaluation model is revealed.

4. The method for optimizing power and position parameters of a machine tool active temperature control source according to claim 1, characterized in that: Step S13 is specifically as follows: based on the thermal deformation generated by the active temperature control source at different positions obtained in the simulation experiment, the thermal deformation is described by data, a neural network method is used with the temperature control source position value as input, and the thermal deformation description data is used as output, and a neural network fitting algorithm is used to construct a relationship between the temperature control source position and the machine tool processing error to obtain a prediction function, thereby revealing the quantitative relationship between the two.

5. The method for optimizing power and position parameters of a machine tool active temperature control source according to claim 1, characterized in that: Step S21 is specifically as follows: according to the simulation results under different working conditions of the machine tool, an index for evaluating the machining error of the machine tool is established on the basis of comprehensively considering the difference between the machining error after temperature control and the machining error before temperature control, so as to evaluate the quality of the temperature control effect.

6. The method for optimizing power and position parameters of a machine tool active temperature control source according to claim 1, characterized in that: Step S22 is specifically as follows: using finite element simulation software to traverse the machine tool processing errors under different combinations of temperature control source power and position, obtain its change trend, and find the power and position values ​​when the machine tool processing error degree evaluation index is optimal.

7. The method for optimizing power and position parameters of a machine tool active temperature control source according to claim 6, characterized in that: Step S3 specifically includes: using the power and position values ​​obtained in step S22 to establish a corresponding engineering application energy-saving active temperature control system for this machine tool.

8. The system for optimizing the power and position parameters of the active temperature control source of a machine tool is characterized in that: include: Model building module: Establish a heat dissipation model for machine tools based on the machine tool working conditions and identify model parameters; specifically includes: Model building unit No. 1, building the heat dissipation model of the machine tool; Model building unit No. 2, to establish a machine tool processing error evaluation model; Identification unit for undetermined parameters, which identifies undetermined parameters in the machine tool heat dissipation model and the processing error evaluation model based on the machine tool usage condition data; Analysis module: The active temperature control strategy that adjusts the position and power of the temperature control source can reduce the thermal error of machine tool processing; specifically includes: Evaluation unit, establishing evaluation index of machine tool processing error degree; Solving unit, solving the degree of thermal deformation of different temperature control source positions and power combinations, and finding the optimal combination value; Application module: The optimal temperature control source power and position parameters are applied in engineering to achieve the best effect of reducing machine tool processing errors.

9. The system for optimizing power and position parameters of active temperature control source for machine tools according to claim 8, characterized in that: The construction process of the No. 1 model construction unit is as follows: based on the actual structure of the machine tool, the small structure is simplified and deleted during the modeling process to establish a simplified structure model of the machine tool, and then the heat generation and heat transfer mechanism of the internal heat source of the machine tool under different working conditions is used to establish a heat generation and heat dissipation model of the machine tool; The construction process of the No. 2 model construction unit is as follows: according to the transmission mechanism of machine tool processing errors, the machine tool thermal deformation that affects the relative position of the tool and the workpiece is analyzed to establish a machine tool processing error evaluation model; The working process of the unit for identifying undetermined parameters is as follows: according to the actual heat dissipation of the internal heat source under different working conditions, the corresponding thermal boundary conditions in the heat dissipation model of the machine tool are determined; The error transfer process and final concentration point in the machine tool processing error evaluation model are determined according to the actual machine tool structural parts assembly relationship.

10. The system for optimizing power and position parameters of active temperature control source for machine tools according to claim 8, characterized in that: The working process of the evaluation unit is as follows: according to the final concentration point in the machine tool processing error evaluation model, according to the simulation results under different working conditions of the machine tool, and on the basis of considering the difference between the processing error after temperature control and the processing error before temperature control, a mathematical method is used to establish an index for evaluating the processing error of the machine tool, which is used to evaluate the quality of the temperature control effect; The solving process of the solving unit is as follows: using finite element simulation software to traverse the machine tool processing errors under different combinations of temperature control source power and position, revealing the changing trend, and obtaining the power and position values ​​that make the machine tool processing error degree evaluation index optimal; The application process of the application module is: to apply the optimal temperature control source power and position parameters for this machine tool in engineering, which comprehensively considers the comprehensive optimal effect of system energy consumption and processing error.

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