CN114895627B - Thermal error compensation method for zoned machine tool - Google Patents

Thermal error compensation method for zoned machine tool Download PDF

Info

Publication number
CN114895627B
CN114895627B CN202210604031.2A CN202210604031A CN114895627B CN 114895627 B CN114895627 B CN 114895627B CN 202210604031 A CN202210604031 A CN 202210604031A CN 114895627 B CN114895627 B CN 114895627B
Authority
CN
China
Prior art keywords
machine tool
temperature
thermal error
point
variable data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202210604031.2A
Other languages
Chinese (zh)
Other versions
CN114895627A (en
Inventor
魏新园
陈雨尘
胡卫东
潘巧生
苗恩铭
冯旭刚
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Anhui University of Technology AHUT
Original Assignee
Anhui University of Technology AHUT
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Anhui University of Technology AHUT filed Critical Anhui University of Technology AHUT
Priority to CN202210604031.2A priority Critical patent/CN114895627B/en
Publication of CN114895627A publication Critical patent/CN114895627A/en
Application granted granted Critical
Publication of CN114895627B publication Critical patent/CN114895627B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/404—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by control arrangements for compensation, e.g. for backlash, overshoot, tool offset, tool wear, temperature, machine construction errors, load, inertia
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/35—Nc in input of data, input till input file format
    • G05B2219/35408—Calculate new position data from actual data to compensate for contour error
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P70/00—Climate change mitigation technologies in the production process for final industrial or consumer products
    • Y02P70/10—Greenhouse gas [GHG] capture, material saving, heat recovery or other energy efficient measures, e.g. motor control, characterised by manufacturing processes, e.g. for rolling metal or metal working

Landscapes

  • Engineering & Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • Manufacturing & Machinery (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Automatic Control Of Machine Tools (AREA)
  • Numerical Control (AREA)

Abstract

The invention discloses a thermal error compensation method for a zoned machine tool, and belongs to the field of control of numerical control equipment. According to the method, the region is divided into the working table, the thermal error prediction model of each region is built, in the compensation implementation process, the region of the machine tool spindle is judged according to the real-time acquired machine tool spindle coordinate values, and then the thermal error prediction model of the region is called to predict and compensate the thermal error of the spindle relative to the region, so that the difference of the machine tool thermal error in different ranges of the working table is considered, and the high-precision compensation of the machine tool thermal error in the whole working table range is realized.

Description

Thermal error compensation method for zoned machine tool
Technical Field
The invention belongs to the field of control of numerical control equipment, and particularly relates to a thermal error compensation method of a zoned machine tool.
Background
The machining precision of a numerical control machine tool often represents the performance of the machine tool. In the actual machining operation process of the numerical control machine tool, the machine tool parts expand to generate thermal deformation due to the influences of friction heat, cutting heat, environmental temperature and other factors. This thermal distortion can change the relative position between the parts of the machine tool, causing the tool to deviate from the ideal cutting point, resulting in reduced machine tool machining accuracy, and such errors caused by thermal distortion are referred to as thermal errors.
According to statistics, the thermal error of the numerical control machine accounts for 40-70% of the total error of the machine, and the proportion is further increased along with the improvement of the grade of the machine product. Modeling, prediction and compensation of thermal errors are common means for effectively solving the problem of machine tool accuracy reduction caused by thermal errors at present, and domestic and foreign students have conducted a great deal of intensive research on the problem, thermal error modeling theory is continuously developed, and thermal error actual compensation effect is continuously improved. However, the current technology for compensating the thermal error of the precise numerical control machine tool at home and abroad basically refers to the method for compensating the thermal error in the international standard, and the thermal error compensation is only carried out on the fixed single-point position (usually the center of the workbench) of the workbench.
For example, the Chinese patent application number is: CN201510425395.4, publication date: one patent document of 2015, 9 and 30 discloses a machine tool thermal error compensation method based on a reinforced naive Bayesian network, which can effectively improve the machining precision of the machine tool. According to the method, a naive Bayesian network classification model and a BAN network structure are established through actually measured sample data, then a conditional probability table is calculated and classification is completed, and finally machine tool thermal error prediction under specific working conditions is realized through real-time prediction of machine tool thermal errors and corresponding compensation adjustment of the machine tool.
For another example, chinese patent application No.: CN201610256897.3, publication date: one patent literature of 2016, 6 and 22 discloses a data processing method for realizing machine tool robustness thermal error compensation of a large-range environment temperature, comprising the following steps: 1. extracting modeling temperature independent variables Xk;2. performing standardization treatment on Xk, and converting the standardized temperature independent variable Xk to obtain an expression of a main component Zk; 3. extracting the first p principal components to participate in modeling; 4. performing standardized treatment on the thermal deformation Sj of the main shaft, and establishing a multiple linear regression equation between the standardized thermal deformation Sj and the first p main components; 5. converting a regression equation between Sj and the first p principal components into an equation of Sj and Xk; 6. converting a regression equation of Sj and Xk into an equation of Sj and Xk, and establishing a thermal error compensation model; and further analyzing the predicted performance of the thermal error model.
The two schemes are single-point type machine tool thermal error compensation methods, and in practice, due to the fact that the thermal deformation rule of the workbench is complex and changeable, the thermal error rule of the machine tool in different ranges of the whole workbench has significant differences, so that when the thermal error compensation method based on a certain fixed position point is embodied in the range of the whole workbench, the thermal error compensation effect is obviously reduced.
In the prior art, a non-single-point type machine tool thermal error compensation method also exists, but the effect is not ideal in actual use. For example, the Chinese patent application number is: CN201610231754.7, publication date: patent literature of 2016, 6 and 22 days discloses a method for compensating curved surface thermal errors of a full workbench of a precision numerical control machine tool, which comprises the following steps: acquiring temperature information of a main shaft key part of a machine tool and Z-axis coordinate information of a representative position point of a workbench; screening out temperature sensitive points; establishing a thermal error model of each measuring point in the range of the full workbench; embedding the built thermal error model of each measuring point into a compensator; calculating the predicted thermal deformation quantity at each measuring point at the current temperature moment; carrying out curved surface modeling on the predicted thermal deformation of each measuring point at the temperature moment, and establishing a curved surface thermal error compensation model of the whole workbench; calculating a thermal error compensation value of the machine tool at the coordinate position; and inputting the obtained compensation value into a machine tool, and realizing real-time compensation of the Z-axis axial thermal error in the whole working table range of the machine tool by combining with the coordinate origin offset. According to the scheme, modeling, prediction and compensation of thermal errors can be carried out on the Z-axis axial direction of the whole workbench range, but a complex two-dimensional curved surface model needs to be established, so that the instantaneity of thermal error compensation is poor, and the actual compensation effect is reduced.
Disclosure of Invention
1. Problems to be solved
Aiming at the problem that the existing machine tool thermal error compensation method is difficult to solve the problem that the thermal error rules of the machine tool in different ranges of the whole workbench are different, the invention provides the zoned machine tool thermal error compensation method which can divide the workbench into zones and establish thermal error prediction models of all zones so as to realize high-precision compensation of the machine tool thermal error in the range of the whole workbench.
2. Technical proposal
In order to solve the problems, the invention adopts the following technical scheme.
A thermal error compensation method of a zoned machine tool comprises the following steps:
1. Selecting a plurality of position points on a machine tool workbench, dividing the workbench into a plurality of areas, and recording the two-dimensional coordinates of each position point;
2. selecting a plurality of temperature measurement points on a machine tool, and periodically and simultaneously measuring thermal error variable data of each position point and temperature variable data of each temperature measurement point;
3. Selecting a temperature measurement point as a corresponding temperature sensitive point for each position point, and establishing a thermal error prediction model;
4. Judging the area of the main shaft according to the position of the main shaft of the machine tool;
5. Calling a thermal error prediction model of each position point contained in the region to which the spindle belongs, predicting the thermal error of the spindle of each position point according to the temperature variable data of the temperature sensitive point measured in real time, averaging the thermal error prediction data of each position point, and predicting and compensating the thermal error of the region;
6. And when the position of the main shaft of the machine tool changes, repeating the step five and the step six until the thermal error compensation is finished.
In one possible embodiment of the present invention, the specific process of the first step is:
(1) Establishing a two-dimensional coordinate system on a machine tool workbench, selecting N position points in a certain range, dividing the selected position point into a plurality of identical rectangular areas, and recording the coordinates (X, Y) of each position point;
(2) The coordinate range included in each rectangular area is calculated and recorded according to the coordinates (X, Y) of the four position points included in each rectangular area.
In one possible embodiment of the invention, the certain range is the effective travel range of the machine tool spindle on the workbench.
In one possible implementation manner of the present invention, the specific process of the second step is:
Selecting a plurality of temperature measurement points on a machine tool, and simultaneously measuring thermal error variable data S of each position point and temperature variable data X of each temperature measurement point to obtain:
S＝[S1,S2,...Sp,...,SN]；
X＝[X1,X2,...Xq,...,XQ]；
S is the thermal deformation of the spindle of the machine tool relative to the spindle of each position point, S p is the thermal error variable data of the p-th position point, and N is the number of the position points; x is the temperature increment of each temperature measurement point, X q is the temperature variable data at the Q-th position point, and Q is the number of the temperature measurement points.
In one possible implementation mode of the invention, the machine tool spindle is provided with a displacement sensor, and each temperature measuring point is provided with a temperature sensor.
In one possible embodiment of the present invention, in the second step, the measurement interval is 4-6 minutes, and the measurement time is greater than 4 hours.
In one possible implementation manner of the present invention, the specific process of the third step is:
(1) The correlation coefficient ρ between the temperature variable data of each temperature measurement point and the thermal error variable data of each position point is calculated one by one using the following formula:
Wherein ρ qp is a correlation coefficient between the temperature variable data of the qth position point and the thermal error variable data at the p-th position point; cov (X q,Sp) is the covariance between the temperature variable data at the q-th position point and the thermal error variable data at the p-th position point; var (X q) is the variance of the temperature variable data at the qth position point; var (S p) is the variance of the thermal error variable data at the p-th position point;
According to the calculation result, selecting two temperature measurement points with the largest correlation coefficient as temperature sensitive points of the q-th position point, and recording the temperature sensitive points as the i-th temperature measurement point and the j-th temperature measurement point;
(2) Establishing the following model relation between the thermal error variable data and two temperature sensitive points:
S＝β0+β1Xi+β2Xj；
M＝[X0,Xi,Xj]；
Wherein, For the ridge regression model coefficient, X i and X j are temperature variable data of the ith temperature measurement point and the jth temperature measurement point respectively; m is a vector matrix, T is a transposed symbol, I is a unit matrix, and lambda is a ridge parameter; x 0 is a unit column vector;
The number of rows and columns of I and X 0 corresponds to the number of rows and columns of M.
3. Advantageous effects
Compared with the prior art, the method for compensating the thermal errors of the machine tool in the subarea is characterized in that the areas of the workbench are divided, so that the thermal error prediction models of the areas are built, in the compensation implementation process, the area of the machine tool spindle is judged according to the coordinate values of the machine tool spindle acquired in real time, and then the thermal error prediction models of the area are called to predict and compensate the thermal errors of the spindle relative to the area, so that the differences of the machine tool thermal errors in different ranges of the workbench are considered, and the high-precision compensation of the machine tool thermal errors in the whole workbench range is realized.
Drawings
FIG. 1 is a flow chart of a thermal error compensation method of the present invention;
FIG. 2 is a distribution diagram of 15 locations selected within the range of the table;
FIG. 3 is 10 temperature variable data of a K1 batch experiment obtained from LEADERWAY-V450 numerically controlled machine tool experiments;
FIG. 4 is Z-direction thermal error data of 15 position points of a K1 batch experiment obtained by LEADERWAY-V450 numerical control machine experiments;
FIG. 5 shows the thermal error curves of the full table before and after compensation obtained by the LEADERWAY-V450 numerical control machine tool experiment.
Detailed Description
The invention provides a method for compensating thermal errors of a machine tool in different areas, which divides a workbench into a plurality of areas and establishes a thermal error prediction model of each area, considers the differences of the thermal errors of the machine tool in different ranges of the workbench, and realizes high-precision compensation of the thermal errors of the machine tool in the range of the whole workbench.
As shown in fig. 1, the method comprises the steps of:
1. Selecting a plurality of position points on a machine tool workbench, dividing the workbench into a plurality of areas, and recording the two-dimensional coordinates of each position point.
2. And selecting a plurality of temperature measurement points on the machine tool, and periodically and simultaneously measuring the thermal error variable data of each position point and the temperature variable data of each temperature measurement point.
3. And selecting a temperature measurement point as a corresponding temperature sensitive point for each position point, and establishing a thermal error prediction model.
4. And judging the area of the main shaft according to the position of the main shaft of the machine tool.
5. And calling a thermal error prediction model of each position point included in the region to which the spindle belongs, predicting the thermal error of the spindle of each position point according to the temperature variable data of the temperature sensitive point measured in real time, averaging the thermal error prediction data of each position point, and predicting and compensating the thermal error of the region.
6. And when the position of the main shaft of the machine tool changes, repeating the step five and the step six until the thermal error compensation is finished.
Specifically, the first step is performed in the following two steps:
(1) As shown in fig. 2, a two-dimensional coordinate system is established on a machine tool workbench, N position points are selected in a certain range, the selected position points divide the selected range into a plurality of identical rectangular areas, and the coordinates (X, Y) of each position point are recorded;
(2) The coordinate range included in each rectangular area is calculated and recorded according to the coordinates (X, Y) of the four position points included in each rectangular area.
The specific process of the second step is as follows: and selecting a plurality of temperature measuring points on the machine tool, wherein each temperature measuring point is provided with a temperature sensor, and a displacement sensor is arranged on a main shaft of the machine tool. Simultaneously measuring thermal error variable data S of each position point and temperature variable data X of each temperature measuring point, wherein the measurement interval time is 4-6 minutes, and the measurement time is more than 4 hours, so as to obtain:
S＝[S1,S2,...Sp,...,SN]；
X＝[X1,X2,...Xq,...,XQ]。
S is the thermal deformation of the spindle of the machine tool relative to the spindle of each position point, S p is the thermal error variable data of the p-th position point, and N is the number of the position points; x is the temperature increment of each temperature measurement point, X q is the temperature variable data at the Q-th position point, and Q is the number of the temperature measurement points.
The third step is divided into the following two steps:
(1) The correlation coefficient ρ between the temperature variable data of each temperature measurement point and the thermal error variable data of each position point is calculated one by one using the following formula:
Wherein ρ qp is a correlation coefficient between the temperature variable data of the qth position point and the thermal error variable data at the ρ position point; cov (X q,Sp) is the covariance between the temperature variable data at the q-th position point and the thermal error variable data at the p-th position point; var (X q) is the variance of the temperature variable data at the qth position point; var (S p) is the variance of the thermal error variable data at the p-th position point.
Then, according to the calculation result, two temperature measurement points with the largest correlation coefficient are selected as temperature sensitive points of the q-th position point, and the temperature sensitive points are marked as the i-th temperature measurement point and the j-th temperature measurement point.
(2) Establishing the following model relation between the thermal error variable data and two temperature sensitive points:
S＝β0+β1Xi+β2Xj；
M＝[X0,Xi,Xj]；
Wherein, For the ridge regression model coefficient, X i and X j are temperature variable data of the ith temperature measurement point and the jth temperature measurement point respectively; m is a vector matrix, T is a transposed symbol, I is a unit matrix, lambda is a ridge parameter, and generally 10-20 is taken; x 0 is the unit column vector.
Note that the number of rows and columns of I and X 0 corresponds to the number of rows and columns of M.
For ease of understanding, step five is illustrated herein, for example, where one region a 1 contains position points 1,2,3,4, then the data for thermal error prediction and compensation for region a 1 is the average of the principal axis thermal error prediction data for the four position points.
In order to more clearly understand the temperature-sensitive point selection method of the present invention, the present invention is further described below with reference to specific examples and drawings.
In the embodiment, the data processing method provided by the invention is applied to thermal error experimental data of LEADERWAY-V450 type numerical control machine tools. In the embodiment, 10 temperature measurement points are arranged on a machine tool in total, a temperature sensor is arranged at each temperature measurement point, one or more eddy current displacement sensors are arranged in the X-axis direction, the Y-axis direction and/or the Z-axis direction of a main shaft of the machine tool, thermal error and temperature data acquisition are carried out every 5 minutes, the duration of a single experiment is more than 4 hours, and 12 experiments are carried out in total and are respectively recorded as K1-K12 batch experiments. Wherein, table 1 is the position and effect of 10 temperature sensors measuring LEADERWAY-V450 numerical control machine temperature conditions, and table 2 is the temperature sensitive point selection result and modeling result of the thermal error variable data of 15 position points. The K1 batch experimental data is taken as an example for illustration.
TABLE 1
TABLE 2
1. As shown in fig. 2, 15 position points are selected on the machine tool table, the table is divided into 8 areas, and the two-dimensional coordinates of each position point are recorded.
2. As shown in table 1, 10 temperature measurement points were selected on the machine tool, and the thermal error variable data of each position point and the temperature variable data of each temperature measurement point were measured at the same time on a regular basis, and the results are shown in fig. 3 and 4.
3. And selecting a temperature measurement point as a corresponding temperature sensitive point for each position point, and establishing a thermal error prediction model of each position point, wherein the results are shown in table 2.
4. And taking an average value of the thermal error prediction models of the position points contained in each region as the thermal error prediction model of each region.
5. And judging the area of the main shaft according to the position of the main shaft of the machine tool.
6. And according to the temperature variable data of the temperature sensitive point measured in real time, a thermal error prediction model of the region to which the main shaft belongs is called to predict and compensate the thermal error of the main shaft relative to the region to which the main shaft belongs.
7. And when the position of the main shaft of the machine tool changes, repeating the step five and the step six until the thermal error compensation is finished.
In this experiment, the thermal error curved surface of the whole workbench before and after compensation is shown in fig. 5, and other batches of experimental data can be used for temperature sensitive point selection based on the steps. As can be seen from the results in fig. 5, the method for compensating the thermal errors in the whole workbench in the region division can effectively reduce the influence of the thermal errors of the machine tool in the whole workbench range, thereby ensuring the actual compensation effect of the thermal errors in the whole workbench range and having great practical engineering application value.
The examples of the present invention are merely for describing the preferred embodiments of the present invention, and are not intended to limit the spirit and scope of the present invention, and those skilled in the art should make various changes and modifications to the technical solution of the present invention without departing from the spirit of the present invention.

Claims (5)

1. A thermal error compensation method of a zoned machine tool is characterized in that: the method comprises the following steps:
1. Selecting a plurality of position points on a machine tool workbench, dividing the workbench into a plurality of areas, and recording the two-dimensional coordinates of each position point;
2. selecting a plurality of temperature measurement points on a machine tool, and periodically and simultaneously measuring thermal error variable data of each position point and temperature variable data of each temperature measurement point;
3. Selecting a temperature measurement point as a corresponding temperature sensitive point for each position point, and establishing a thermal error prediction model;
4. Judging the area of the main shaft according to the position of the main shaft of the machine tool;
5. Calling a thermal error prediction model of each position point contained in the region to which the spindle belongs, predicting the thermal error of the spindle of each position point according to the temperature variable data of the temperature sensitive point measured in real time, averaging the thermal error prediction data of each position point, and predicting and compensating the thermal error of the region;
6. When the position of the main shaft of the machine tool changes, repeating the fifth step and the sixth step until the thermal error compensation is finished;
the specific process of the second step is as follows:
Selecting a plurality of temperature measurement points on a machine tool, and simultaneously measuring thermal error variable data S of each position point and temperature variable data X of each temperature measurement point to obtain:
S＝[S1,S2,...Sp,...,SN]；
X＝[X1,X2,…Xq,…,XQ]；
S is the thermal deformation of the spindle of the machine tool relative to the spindle of each position point, S p is the thermal error variable data of the p-th position point, and N is the number of the position points; x is the temperature increment of each temperature measurement point, X q is the temperature variable data at the Q-th position point, and Q is the number of the temperature measurement points;
the specific process of the third step is as follows:
(1) The correlation coefficient ρ between the temperature variable data of each temperature measurement point and the thermal error variable data of each position point is calculated one by one using the following formula:
Wherein ρ qp is a correlation coefficient between the temperature variable data of the qth position point and the thermal error variable data at the p-th position point; cov (X q,Sp) is the covariance between the temperature variable data at the q-th position point and the thermal error variable data at the p-th position point; var (X q) is the variance of the temperature variable data at the qth position point; var (S p) is the variance of the thermal error variable data at the p-th position point;
According to the calculation result, selecting two temperature measurement points with the largest correlation coefficient as temperature sensitive points of the q-th position point, and recording the temperature sensitive points as the i-th temperature measurement point and the j-th temperature measurement point;
(2) Establishing the following model relation between the thermal error variable data and two temperature sensitive points:
S＝β0+β1Xi+β1Xj；
M＝[X0,Xi,Xj]；
Wherein, For the ridge regression model coefficient, X i and X j are temperature variable data of the ith temperature measurement point and the jth temperature measurement point respectively; m is a vector matrix, T is a transposed symbol, I is a unit matrix, and lambda is a ridge parameter; x 0 is a unit column vector;
The number of rows and columns of I and X 0 corresponds to the number of rows and columns of M.
2. The method for compensating thermal errors of a zoned machine tool according to claim 1, wherein: the specific process of the first step is as follows:
(1) Establishing a two-dimensional coordinate system on a machine tool workbench, selecting N position points in a certain range, dividing the selected position point into a plurality of identical rectangular areas, and recording the coordinates (X, Y) of each position point;
(2) The coordinate range included in each rectangular area is calculated and recorded according to the coordinates (X, Y) of the four position points included in each rectangular area.
3. The method for compensating thermal errors of a zoned machine tool according to claim 2, wherein: the certain range is the effective travel range of the machine tool spindle on the workbench.
4.A method of thermal error compensation for a zoned machine tool according to claim 3, wherein: the machine tool spindle is provided with a displacement sensor, and each temperature measuring point is provided with a temperature sensor.
5. The method for compensating thermal errors of a zoned machine tool according to claim 4, wherein: in the second step, the measurement interval time is 4-6 minutes, and the measurement time is more than 4 hours.
CN202210604031.2A 2022-05-31 2022-05-31 Thermal error compensation method for zoned machine tool Active CN114895627B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210604031.2A CN114895627B (en) 2022-05-31 2022-05-31 Thermal error compensation method for zoned machine tool

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210604031.2A CN114895627B (en) 2022-05-31 2022-05-31 Thermal error compensation method for zoned machine tool

Publications (2)

Publication Number Publication Date
CN114895627A CN114895627A (en) 2022-08-12
CN114895627B true CN114895627B (en) 2024-06-21

Family

ID=82727060

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210604031.2A Active CN114895627B (en) 2022-05-31 2022-05-31 Thermal error compensation method for zoned machine tool

Country Status (1)

Country Link
CN (1) CN114895627B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115328025B (en) * 2022-09-21 2024-07-09 重庆大学 Machine tool thermal error double-closed-loop modeling and compensation method based on model applicability evaluation index

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105700473B (en) * 2016-04-13 2018-04-03 合肥工业大学 A kind of full workbench curved surface thermal error compensation method of precise numerical control machine
CN105759719B (en) * 2016-04-20 2018-08-24 合肥工业大学 A kind of numerical control machining tool heat error prediction technique and system splitting model based on unbiased esti-mator
CN106736848B (en) * 2016-12-13 2019-04-12 西安交通大学 Numerically controlled lathe Thermal Error measures compensation system and compensation method
CN108415372B (en) * 2018-03-12 2021-03-30 攀枝花学院 Thermal error compensation method for precision machine tool
CN109739182B (en) * 2019-01-31 2020-06-16 大连理工大学 Spindle thermal error compensation method insensitive to cooling system disturbance
CN109623499B (en) * 2019-01-31 2020-08-25 大连理工大学 Geometric/thermal error online measurement and compensation system of numerical control machine tool
CN110889091B (en) * 2019-11-18 2023-04-11 重庆理工大学 Machine tool thermal error prediction method and system based on temperature sensitive interval segmentation

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
基于正则化的机床热误差自适应稳健建模算法;魏新园;仪器仪表学报;20220515;第43卷(第5期);77-85 *
数控机床实切工况下温度敏感点稳健性选择方法研究;刘昀晟;苗恩铭;张明德;冯定;李建刚;;重庆理工大学学报(自然科学);20200915(09);全文 *

Also Published As

Publication number Publication date
CN114895627A (en) 2022-08-12

Similar Documents

Publication Publication Date Title
CN105759719B (en) A kind of numerical control machining tool heat error prediction technique and system splitting model based on unbiased esti-mator
CN110543140B (en) Time characteristic-based numerical control machine tool spindle system thermal key point selection modeling method
CN110889091B (en) Machine tool thermal error prediction method and system based on temperature sensitive interval segmentation
Liu et al. Robust machine tool thermal error compensation modelling based on temperature-sensitive interval segmentation modelling technology
Wang et al. Compensation for the thermal error of a multi-axis machining center
CN104597842A (en) BP neutral network heavy machine tool thermal error modeling method optimized through genetic algorithm
CN112433507B (en) LSO-LSSVM (least squares support vector machine) -based five-axis numerical control machine tool thermal error comprehensive modeling method
CN110716500B (en) Method and system for determining segmented modeling points of temperature sensitive interval
CN114237155A (en) Error prediction and compensation method, system and medium for multi-axis numerical control machining
CN111650881B (en) Method, system and storage medium for predicting and compensating positioning error of numerical control machine
CN114895627B (en) Thermal error compensation method for zoned machine tool
CN111459094B (en) Regional selection method for temperature sensitive point combination in machine tool spindle thermal error modeling
Yao et al. Thermal error modeling and prediction analysis based on OM algorithm for machine tool’s spindle
Wang et al. State space modelling of variation propagation in multistage machining processes for variable stiffness structure workpieces
Zimmermann et al. Self-optimizing thermal error compensation models with adaptive inputs using Group-LASSO for ARX-models
CN102540884A (en) Intelligent adjustment device and method for thermal error of machine tool
Geng et al. A new fuzzy process capability estimation method based on kernel function and FAHP
CN116160291B (en) Blade profile machining cutter length compensation method based on-machine measurement
Li et al. A reconstructed variable regression method for thermal error modeling of machine tools
CN103273380A (en) Simulation-model-based online monitoring method for errors in thermal deformation of numerical control machine tool
CN108415372B (en) Thermal error compensation method for precision machine tool
CN116611314A (en) Machine tool machining process thermal error online evaluation method based on physical information neural network
Blaser Adaptive learning control for thermal error compensation
CN114895630B (en) Method for selecting temperature sensitive points of machine tool thermal error prediction model
Naumann et al. Optimization of characteristic diagram based thermal error compensation via load case dependent model updates

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant