Modeling method of thermal error least squares support vector machine of numerically-controlled machine tool

A support vector machine and least squares technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as working condition uncertainty, achieve low hardware requirements, improve self-learning ability, good reliability sexual effect

Inactive Publication Date: 2009-06-03
ZHEJIANG UNIV
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Problems solved by technology

Due to the characteristics of thermal errors, such as time-varying, multi-factor, and worki...

Method used

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  • Modeling method of thermal error least squares support vector machine of numerically-controlled machine tool
  • Modeling method of thermal error least squares support vector machine of numerically-controlled machine tool
  • Modeling method of thermal error least squares support vector machine of numerically-controlled machine tool

Examples

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Embodiment

[0048] Thermal error modeling analysis of a XHK-714F CNC machining center. The thermal deformation data of the machine tool spindle is collected by a laser displacement sensor (LK-150H). The temperature field measurement system is composed of 14 intelligent temperature sensors, ARM7 embedded system platform (FS44B0XLII) and liquid crystal display unit. Under similar conditions, the temperature rise and the axial thermal error of the spindle were tested repeatedly during the continuous operation of the machining center for 6 hours and the shutdown for 1 hour, and a total of 70 sets of data were obtained.

[0049] According to the data acquisition, take the spindle temperature change T 0 , Spindle motor measuring point temperature rise T 1 , Ball screw measuring point temperature rise T 2 , Temperature rise T of column measuring point 3 , The temperature rise T of the machine bed measuring point 4 , ambient temperature T 5 , with the spindle axial error D 1 , Spindle radi...

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Abstract

The invention discloses a modeling method of a thermal error least squares support vector machine of a numerically-controlled machine tool. The method comprises the following steps: (1) selecting a kernel function and determining parameters; and (2) establishing a thermal error model of the machine tool according to least squares support vector machine theory. A compensating system of the invention has the advantages of simple structure and reliable application; and the modeling method of the least squares support vector machine improves the model precision and generalization capability and overcomes defects of the existing prediction methods, such as low precision, low generalization capability and the like. The modeling method has higher prediction precision when the sample size is small and even the sample data are small, thus reducing dependence on experience. Meanwhile, the method improves the self-learning ability of the system, the thermal error model obtained by training can reflect the manufacturing procedure change of the machine tool, and the method has the advantages of adaptability, low hardware requirements for the thermal error compensating system, simple structure and good reliability.

Description

technical field [0001] The invention relates to a thermal error least square support vector machine modeling method of a numerically controlled machine tool. Background technique [0002] Thermal error control of CNC machine tools is one of the basic technologies for precision and ultra-precision machining. The main steps of machine tool thermal error compensation are: detection and analysis of error source, establishment of comprehensive mathematical model of error motion, identification of error element, execution of error compensation and evaluation of error compensation effect. [0003] In thermal error compensation, the establishment of thermal error model is a key step. The experimental modeling method is the most commonly used thermal error modeling method, which uses the thermal error data measured by the experiment and the temperature value of the machine tool and uses the least square principle to perform fitting modeling. However, the thermal error of the machin...

Claims

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Application Information

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IPC IPC(8): G06F17/50
Inventor 傅建中姚鑫骅林伟清陈子辰
Owner ZHEJIANG UNIV
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