Numerical control machine tool machining precision optimization method and system

Abstract

The invention relates to the technical field of numerical control machine tool machining, and discloses a numerical control machine tool machining precision optimization method and system. The system comprises a machining data acquisition module, a machining environment data acquisition module, a precision data analysis module and a precision influence early warning module. According to the system, tool bit abrasion data of each tool of the current numerical control machine tool, the flatness of a clamp of the numerical control machine tool, collected cooling liquid spraying uniformity and a workpiece surface scrap residual value are comprehensively calculated to obtain a first precision risk coefficient, and whether a first adjustment strategy is executed to clean the numerical control machine tool or not is judged; based on the electric signal interference frequency and the temperatures of the transmission parts, a second precision risk coefficient is obtained through comprehensive calculation, whether a second adjustment strategy is executed or not is judged, whether other parts need to be overhauled or not is judged, and therefore interference of external factors on the numerical control machine tool is avoided by considering multiple factors.

Description

Technical Field

[0001] The invention relates to the technical field of CNC machine tool processing, and in particular to a CNC machine tool processing accuracy optimization method and system. Background Art

[0002] The machining accuracy of CNC machine tools is mainly affected by factors such as spatial geometric errors, thermal errors, load errors, and servo errors of machine tool parts and structures. The geometric error of a machine tool refers to the deviation of the actual geometric parameters and positions of each component or part of the machine tool from the ideal geometric parameters and positions due to defects in the design, manufacturing, and assembly of the machine tool. This error is generally related to the geometric elements of each component or part of the machine tool and is an inherent error of the machine tool itself. A large number of studies on the error sources of CNC machine tools have shown that 50% of the machining errors are caused by the geometric errors of the machine tool. These errors include positioning errors, straightness errors, roll errors, swing errors, yaw errors, and verticality and parallelism errors between moving axes. The mutual coupling effect ultimately affects the machining accuracy of the machine tool, but apart from these inherent errors, there are still other factors that affect the machining accuracy of the machine tool. Summary of the invention

[0003] 1. Technical issues to be resolved In view of the deficiencies in the prior art, the present invention provides a method and system for optimizing machining accuracy of CNC machine tools, which has the advantages of optimizing factors affecting accuracy and solves the above-mentioned technical problems.

[0004] (II) Technical solution To achieve the above-mentioned object, the present invention provides the following technical solutions: a CNC machine tool machining accuracy optimization system, comprising a machining data acquisition module, a machining environment data acquisition module, a precision data analysis module and a precision impact warning module; The processing data acquisition module includes a tool data acquisition unit, a fixture data acquisition unit and a coolant spraying data acquisition unit. The tool data acquisition unit is used to collect the tool head wear data of each tool of the current CNC machine tool, the fixture data acquisition unit is used to collect the flatness of the fixture of the CNC machine tool, and the coolant spraying data acquisition unit is used to collect the coolant spraying uniformity and the residual value of the debris on the workpiece surface; The processing environment data acquisition module includes an electric signal interference acquisition unit and a transmission component temperature acquisition unit. The electric signal interference acquisition unit is used to collect the number of electric signal interferences in the processing environment, and the transmission component temperature acquisition unit is used to collect the temperatures of several transmission components in the CNC machine tool. The precision data analysis module obtains a first precision risk coefficient based on the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying, and the residual value of debris on the workpiece surface, and inputs the first precision risk coefficient into the precision impact warning module, and the precision impact warning module determines whether to execute the first adjustment strategy; If the first adjustment strategy is not executed, the accuracy data analysis module calculates the second accuracy risk coefficient based on the electrical signal interference frequency and the temperature of several transmission components, and inputs it into the accuracy impact warning module, and the accuracy impact warning module determines whether to execute the second adjustment strategy.

[0005] As a preferred technical solution of the present invention, the specific expression for the tool head wear data collected by the tool data collection unit for each tool of the current CNC machine tool is as follows: in, represents the tool head wear dataset, Respectively represent the wear data of the first cutter head of the CNC machine tool CNC Machine Tools Wear data of each cutting head CNC Machine Tools The wear data of the tool head of the CNC machine tool Wear data of each cutting head The specific expression is as follows: in, Indicates the CNC machine tool Current length of the blade, Indicates the CNC machine tool The initial length of the blade, Indicates the CNC machine tool The wear area of ​​the blade surface of the tool head is obtained by laser scanning. Indicates the CNC machine tool The area of ​​the blade face of the cutter head.

[0006] As a preferred technical solution of the present invention, the fixture data acquisition unit is used to collect the specific expression of the flatness of the CNC machine tool fixture as follows: in, represents the CNC machine tool fixture flatness data set, Respectively represent the CNC machine tool fixture The flatness of the area CNC machine tool fixture The flatness of the area CNC machine tool fixture The flatness of the area, the CNC machine tool The flatness of the area The specific expression is as follows: in, Indicates the CNC machine tool In the region The area of ​​the concave or convex part, Indicates In the region The area of ​​the concave or convex parts is summed up. Indicates the CNC machine tool The area of ​​a region.

[0007] As a preferred technical solution of the present invention, the specific expression of the coolant spraying uniformity collected by the coolant spraying data collection unit is as follows: in, represents the coolant spray uniformity data set, Respectively represent the uniformity of the first sub-area of ​​the workpiece during the processing Processing parts Sub-region uniformity Processing parts sub-area uniformity, and the workpiece Sub-region uniformity The expression is as follows: in, Indicates standard temperature, Indicates the workpiece The temperature of the sub-region, express The absolute value of .

[0008] As a preferred technical solution of the present invention, the specific expression of the residual value of the debris on the workpiece surface collected by the coolant spraying data collection unit is as follows: in, Represents the data set of chip residue value on the workpiece surface, Respectively represent the residual weight of surface debris after the first workpiece processing is completed within a maintenance cycle No. The residual weight of the surface debris after the workpiece is processed No. The residual weight of surface debris after the workpiece is processed.

[0009] As a preferred technical solution of the present invention, the specific expression of the number of electrical signal interferences collected by the electrical signal interference collection unit in the processing environment is as follows: in, represents the interference data set, Respectively represent the number of electrical signal interferences that the CNC machine tool receives at the first sampling moment No. The number of electrical signal interferences at the sampling moment No. The number of electrical signal interferences at the sampling moment.

[0010] As a preferred technical solution of the present invention, the specific expression for the transmission component temperature acquisition unit to acquire the temperature of several transmission components in the CNC machine tool is as follows: in, Represents the temperature data set of the transmission components in the CNC machine tool, Respectively represent the temperature of the first transmission component in the CNC machine tool No. The temperature of the transmission parts No. The temperature of the transmission components.

[0011] As a preferred technical solution of the present invention, the precision data analysis module comprehensively calculates the first precision risk coefficient based on the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying and the residual value of debris on the workpiece surface as follows: in, represents the first precision risk coefficient, Represents the tool head wear data set The minimum value in Represents the CNC machine tool fixture flatness data set The maximum value of Represents the coolant spray uniformity data set The maximum value, Represents the data set of chip residue value on the workpiece surface The maximum value of When the first risk threshold is exceeded, the first adjustment strategy is executed to repair the tool, fixture and coolant spraying equipment.

[0012] As a preferred technical solution of the present invention, the precision data analysis module comprehensively calculates the second precision risk coefficient based on the electrical signal interference frequency and the temperature of several transmission components, and the specific expression is as follows: in, represents the second precision risk coefficient, Represents a disturbance dataset The maximum value, Represents the temperature data set of the transmission components in the CNC machine tool The maximum value of When the second risk threshold is exceeded, the second adjustment strategy is executed to inspect and repair the signal transmission components of the CNC machine tool, clean the travel of the transmission parts, and add lubricants.

[0013] The present invention also provides a method for optimizing machining accuracy of a CNC machine tool, based on the above-mentioned system for optimizing machining accuracy of a CNC machine tool, comprising the following steps: Step 1: Collect the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying and the residual value of debris on the workpiece surface; Step 2: Based on the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying and the residual value of debris on the workpiece surface, the first precision risk coefficient is calculated comprehensively; Step 3: Determine whether to execute the first adjustment strategy. If so, terminate the step. If not, execute step 4. Step 4: Based on the electrical signal interference frequency and the temperatures of several transmission components, a second accuracy risk coefficient is obtained by comprehensive calculation, and it is determined whether to execute the second adjustment strategy.

[0014] Compared with the prior art, the present invention provides a method and system for optimizing machining accuracy of CNC machine tools, which has the following beneficial effects: The present invention collects the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of the coolant spraying and the residual value of the debris on the workpiece surface, and comprehensively calculates the first precision risk coefficient to determine whether to execute the first adjustment strategy to clean the CNC machine tool. If no cleaning is required, based on the electrical signal interference frequency and the temperature of several transmission components, a second precision risk coefficient is comprehensively calculated to determine whether to execute the second adjustment strategy and whether it is necessary to inspect and repair the remaining components, thereby taking multiple factors into consideration to avoid interference with the CNC machine tool by external factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the system framework of the present invention; Figure 2 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] See also Figure 1-Figure 2 , a CNC machine tool machining accuracy optimization system, including a machining data acquisition module, a machining environment data acquisition module, a precision data analysis module and a precision impact warning module; The processing data acquisition module includes a tool data acquisition unit, a fixture data acquisition unit and a coolant spraying data acquisition unit. The tool data acquisition unit is used to collect the tool head wear data of each tool of the current CNC machine tool. The fixture data acquisition unit is used to collect the flatness of the fixture of the CNC machine tool. The coolant spraying data acquisition unit is used to collect the coolant spraying uniformity and the residual value of the debris on the workpiece surface. The specific expression of the tool head wear data collected by the tool data acquisition unit for each tool of the current CNC machine tool is as follows: in, represents the tool head wear dataset, Respectively represent the wear data of the first cutter head of the CNC machine tool CNC Machine Tools Wear data of each cutting head CNC Machine Tools Wear data of tool heads, CNC machine tools Wear data of each cutting head The specific expression is as follows: in, Indicates the CNC machine tool Current length of the blade, Indicates the CNC machine tool The initial length of the blade, Indicates the CNC machine tool The wear area of ​​the blade surface of the tool head is obtained by laser scanning. Indicates the CNC machine tool The specific expression of the fixture data acquisition unit used to collect the flatness of the CNC machine tool fixture is as follows: in, represents the CNC machine tool fixture flatness data set, Respectively represent the CNC machine tool fixture The flatness of the area CNC machine tool fixture The flatness of the area CNC machine tool fixture Flatness of the area, CNC machine tool The flatness of the area The specific expression is as follows: in, Indicates the CNC machine tool In the region The area of ​​the concave or convex part, Expressing the In the region The area of ​​the concave or convex parts is summed up. Indicates the CNC machine tool The specific expression of the coolant spraying uniformity collected by the coolant spraying data acquisition unit is as follows: in, represents the coolant spray uniformity data set, Respectively represent the uniformity of the first sub-area of ​​the workpiece during the processing Processing parts Sub-region uniformity Processing parts sub-area uniformity, and the workpiece Sub-region uniformity The expression is as follows: in, Indicates standard temperature, Indicates the workpiece The temperature of the sub-region, The specific expression of the residual value of the debris on the workpiece surface collected by the coolant spraying data acquisition unit is as follows: in, Represents the data set of chip residue value on the workpiece surface, Respectively represent the residual weight of surface debris after the first workpiece processing is completed within a maintenance cycle No. The residual weight of the surface debris after the workpiece is processed No. The residual weight of the surface debris after the workpiece is processed; The processing environment data acquisition module includes an electrical signal interference acquisition unit and a transmission component temperature acquisition unit. The electrical signal interference acquisition unit is used to collect the number of electrical signal interferences in the processing environment. The transmission component temperature acquisition unit is used to collect the temperature of several transmission components in the CNC machine tool. The specific expression of the number of electrical signal interferences collected by the electrical signal interference acquisition unit in the processing environment is as follows: in, represents the interference data set, Respectively represent the number of electrical signal interferences that the CNC machine tool receives at the first sampling moment No. The number of electrical signal interferences at the sampling moment No. The number of electrical signal interferences at the sampling time, the specific expression of the transmission component temperature acquisition unit collecting the temperature of several transmission components in the CNC machine tool is as follows: in, Represents the temperature data set of the transmission components in the CNC machine tool, Respectively represent the temperature of the first transmission component in the CNC machine tool No. The temperature of the transmission parts No. The temperature of each transmission component; The precision data analysis module obtains the first precision risk coefficient based on the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying, and the residual value of debris on the workpiece surface, and inputs the first precision risk coefficient into the precision impact warning module. The precision impact warning module determines whether to execute the first adjustment strategy. The precision data analysis module obtains the specific expression of the first precision risk coefficient based on the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying, and the residual value of debris on the workpiece surface. The following is the formula: in, represents the first precision risk coefficient, Represents the tool head wear data set The minimum value in Represents the CNC machine tool fixture flatness data set The maximum value of Represents the coolant spray uniformity data set The maximum value, Represents the data set of chip residue value on the workpiece surface The maximum value of When the first risk threshold is exceeded, the first adjustment strategy is executed to repair the tool, fixture and coolant spraying equipment; If the first adjustment strategy is not executed, the precision data analysis module comprehensively calculates the second precision risk coefficient based on the electrical signal interference frequency and the temperature of several transmission components and inputs it into the precision impact warning module. The precision impact warning module determines whether to execute the second adjustment strategy. The precision data analysis module comprehensively calculates the second precision risk coefficient based on the electrical signal interference frequency and the temperature of several transmission components. The specific expression is as follows: in, represents the second precision risk coefficient, Represents a disturbance dataset The maximum value, Represents the temperature data set of the transmission components in the CNC machine tool The maximum value of When the second risk threshold is exceeded, the second adjustment strategy is executed to inspect and repair the signal transmission components of the CNC machine tool, clean the travel of the transmission parts, and add lubricants. Embodiment 1

[0018] This embodiment is the data calculation process of the above technical content, and the specific data is as follows in Table 1:

[0019] At this time, the first accuracy risk coefficient , exceeding the first risk threshold, executing the first adjustment strategy, and repairing the tool, fixture and coolant spraying equipment; Embodiment 2

[0020] This embodiment is the data calculation process of the above technical content, and the specific data is as follows in Table 2:

[0021] At this time, the first accuracy risk coefficient , does not exceed the first risk threshold, then calculate , at this time, the second adjustment strategy is executed. It can be seen that considering multiple factors can avoid the interference of external factors on the CNC machine tool; The present invention also provides a method for optimizing machining accuracy of a CNC machine tool, based on the above-mentioned system for optimizing machining accuracy of a CNC machine tool, comprising the following steps: Step 1: Collect the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying and the residual value of debris on the workpiece surface; Step 2: Based on the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying and the residual value of debris on the workpiece surface, the first precision risk coefficient is calculated comprehensively; Step 3: Determine whether to execute the first adjustment strategy. If so, terminate the step. If not, execute step 4. Step 4: Based on the electrical signal interference frequency and the temperatures of several transmission components, a second accuracy risk coefficient is obtained by comprehensive calculation, and it is determined whether to execute the second adjustment strategy.

[0022] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A CNC machine tool machining accuracy optimization system, characterized by: It includes processing data acquisition module, processing environment data acquisition module, precision data analysis module and precision impact warning module; The processing data acquisition module includes a tool data acquisition unit, a fixture data acquisition unit and a coolant spraying data acquisition unit. The tool data acquisition unit is used to collect the tool head wear data of each tool of the current CNC machine tool, the fixture data acquisition unit is used to collect the flatness of the fixture of the CNC machine tool, and the coolant spraying data acquisition unit is used to collect the coolant spraying uniformity and the residual value of the debris on the workpiece surface; The processing environment data acquisition module includes an electric signal interference acquisition unit and a transmission component temperature acquisition unit. The electric signal interference acquisition unit is used to collect the number of electric signal interferences in the processing environment, and the transmission component temperature acquisition unit is used to collect the temperatures of several transmission components in the CNC machine tool. The precision data analysis module obtains a first precision risk coefficient based on the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying, and the residual value of debris on the workpiece surface, and inputs the first precision risk coefficient into the precision impact warning module, and the precision impact warning module determines whether to execute the first adjustment strategy; If the first adjustment strategy is not executed, the accuracy data analysis module comprehensively calculates the second accuracy risk coefficient based on the electrical signal interference frequency and the temperatures of several transmission components, and inputs the second accuracy risk coefficient into the accuracy impact warning module, and the accuracy impact warning module determines whether to execute the second adjustment strategy.

2. The CNC machine tool machining accuracy optimization system according to claim 1, characterized in that: The specific expression for the tool head wear data collected by the tool data collection unit for each tool of the current CNC machine tool is as follows: in, represents the tool head wear dataset, Respectively represent the wear data of the first cutter head of the CNC machine tool CNC Machine Tools Wear data of each cutting head CNC Machine Tools The wear data of the tool head of the CNC machine tool Wear data of each cutting head The specific expression is as follows: in, Indicates the CNC machine tool Current length of the blade, Indicates the CNC machine tool The initial length of the blade, Indicates the CNC machine tool The wear area of ​​the blade surface of the tool head is obtained by laser scanning. Indicates the CNC machine tool The area of ​​the blade face of the cutter head.

3. A CNC machine tool machining accuracy optimization system according to claim 2, characterized in that: The fixture data acquisition unit is used to collect the specific expression of the flatness of the CNC machine tool fixture as follows: in, represents the CNC machine tool fixture flatness data set, Respectively represent the CNC machine tool fixture The flatness of the area CNC machine tool fixture The flatness of the area CNC machine tool fixture The flatness of the area, the CNC machine tool The flatness of the area The specific expression is as follows: in, Indicates the CNC machine tool In the region The area of ​​the concave or convex part, Indicates In the region The area of ​​the concave or convex parts is summed up. Indicates the CNC machine tool The area of ​​a region.

4. The CNC machine tool machining accuracy optimization system according to claim 3, characterized in that: The specific expression for collecting the coolant spraying uniformity by the coolant spraying data collection unit is as follows: in, represents the coolant spray uniformity data set, Respectively represent the uniformity of the first sub-area of ​​the workpiece during the processing Processing parts Sub-region uniformity Processing parts sub-area uniformity, and the workpiece Sub-region uniformity The expression is as follows: in, Indicates standard temperature, Indicates the workpiece The temperature of the sub-region, The absolute value of .

5. The CNC machine tool machining accuracy optimization system according to claim 4, characterized in that: The specific expression for collecting the chip residual value on the workpiece surface by the coolant spraying data acquisition unit is as follows: in, Represents the data set of chip residue value on the workpiece surface, Respectively represent the residual weight of surface debris after the first workpiece processing is completed within a maintenance cycle No. The residual weight of the surface debris after the workpiece is processed No. The residual weight of surface debris after the workpiece is processed.

6. The CNC machine tool machining accuracy optimization system according to claim 5, characterized in that: The specific expression for the number of electrical signal interferences collected by the electrical signal interference collection unit in the processing environment is as follows: in, represents the interference data set, Respectively represent the number of electrical signal interferences that the CNC machine tool receives at the first sampling moment No. The number of electrical signal interferences at the sampling moment No. The number of electrical signal interferences at the sampling moment.

7. The CNC machine tool machining accuracy optimization system according to claim 6, characterized in that: The specific expression for the transmission component temperature acquisition unit to acquire the temperature of several transmission components in the CNC machine tool is as follows: in, Represents the temperature data set of the transmission components in the CNC machine tool, Respectively represent the temperature of the first transmission component in the CNC machine tool No. The temperature of the transmission parts No. The temperature of the transmission components.

8. The CNC machine tool machining accuracy optimization system according to claim 7, characterized in that: The precision data analysis module obtains a specific expression of the first precision risk coefficient by comprehensive calculation based on the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying, and the residual value of debris on the workpiece surface as follows: in, represents the first precision risk coefficient, Represents the tool head wear data set The minimum value in Represents the CNC machine tool fixture flatness data set The maximum value of Represents the coolant spray uniformity data set The maximum value, Represents the data set of chip residue value on the workpiece surface The maximum value of When the first risk threshold is exceeded, the first adjustment strategy is executed to repair the tool, fixture and coolant spraying equipment.

9. The CNC machine tool machining accuracy optimization system according to claim 8, characterized in that: The precision data analysis module calculates the second precision risk coefficient based on the electrical signal interference frequency and the temperature of several transmission components through comprehensive calculation as follows: in, represents the second precision risk coefficient, Represents a disturbance dataset The maximum value, Represents the temperature data set of the transmission components in the CNC machine tool The maximum value of When the second risk threshold is exceeded, the second adjustment strategy is executed to inspect and repair the signal transmission components of the CNC machine tool, clean the travel of the transmission parts, and add lubricants.

10. A method for optimizing machining accuracy of a CNC machine tool, based on a system for optimizing machining accuracy of a CNC machine tool according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Collect the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying and the residual value of debris on the workpiece surface; Step 2: Based on the tool head wear data of each tool of the current CNC machine tool, the flatness of the CNC machine tool fixture, the uniformity of coolant spraying and the residual value of debris on the workpiece surface, the first precision risk coefficient is calculated comprehensively; Step 3: Determine whether to execute the first adjustment strategy. If so, terminate the step. If not, execute step 4. Step 4: Based on the electrical signal interference frequency and the temperatures of several transmission components, a second accuracy risk coefficient is obtained by comprehensive calculation, and it is determined whether to execute the second adjustment strategy.

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