An intelligent control method for a CNC machine tool production line

Abstract

The present invention discloses an intelligent control method for a CNC machine tool production line, which relates to the technical field of CNC machine tool control. It includes extracting the initial maximum temperature and the initial minimum temperature of each group of parts, capturing the machining maximum temperature and the machining minimum temperature of the parts under different machining parameters, and outputting the corresponding changing machining parameters. Calculate the high-temperature influence coefficient and the low-temperature influence coefficient of the changing machining parameters of each group of parts, and calculate the comprehensive temperature influence coefficient; obtain the roundness, flatness, and cylindricity of the parts after the flow production at different cutting temperatures, calculate the precision difference of the parts after the flow production at different cutting temperatures, and determine the adjustment temperature threshold; extract the real-time machining maximum temperature during the actual production process. When the real-time machining maximum temperature exceeds the adjustment temperature threshold, send out a production control instruction and calculate the real-time control machining parameters. It can reduce the thermal deformation and the change of cutting force during the machining process, which helps to maintain the stability of the machining accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of numerical control machine tool control, and specifically to an intelligent control method for a numerical control machine tool production line. Background Art

[0002] With the continuous exploitation of underground resources such as oil and natural gas, the demand for underground drilling equipment and its precision parts is increasing day by day. These parts not only require high precision and high strength, but also need to maintain stable performance in extreme environments. As the core equipment of modern manufacturing, the high-precision and high-efficiency characteristics of numerical control machine tools make them an ideal choice for producing precision parts for underground drilling. However, the traditional control methods of numerical control machine tools are difficult to meet the current production requirements, and the introduction of intelligent control methods has become an inevitable trend. The traditional control methods of numerical control machine tools and their limitations include: manual control depends on the experience and skills of operators and is difficult to achieve high precision and consistency; although automated control improves production efficiency, it lacks intelligent decision-making and adaptive capabilities and is difficult to cope with complex and changeable processing requirements; programming control controls the machining process of the machine tool through a preset program, but once the program is determined, it is difficult to adjust flexibly and is difficult to handle unexpected situations during the machining process.

[0003] In the Chinese invention application with the application publication number CN117075534A, an intelligent control method for a numerical control machine tool production line is disclosed, which includes analyzing the machining parameters of the machine tool for the part machining assembly drawing obtained by the numerical control analysis module, the machining execution module performing part machining production based on the analyzed part machining control parameter information, collecting and obtaining the machining state information of the target part through a sensor group, and then tracing the machining parameters based on the machining state, optimizing the solution space of the machine tool machining control parameters based on the traced target-related machining control parameter information to generate a machine tool machining control parameter memory bank, performing global optimization based on the machine tool machining control parameter memory bank, outputting a set of optimized machine tool machining control parameters, and then using this to control the part production management.

[0004] In the Chinese invention application with the application publication number CN113894617A, a tool state monitoring system and method based on the vibration signal of the machine tool are disclosed. The monitoring system includes a host computer control module and a data acquisition module, which can collect and display relevant information during the machining process of the machine tool in real time. This system can monitor the vibration signal during the machining of the machine tool in real time, and optimize the cutting parameters according to the acquisition results to achieve the purpose of prolonging the tool life and early warning of faults. The monitoring method compares the vibration curve with the standard eigenvalue curve to judge whether the tool needs to be replaced, the tool wear condition, and optimize the cutting parameters according to the comparison results, and finally sends instructions to the numerical control system of the machine tool through the OPCUA protocol, so as to realize the intelligent control of the motion state of the machine tool.

[0005] In the above invention application, the invention CN117075534 performs global optimization based on the machine tool processing control parameter memory bank, outputs a set of optimized machine tool processing control parameters, and controls the production and management of parts based on the set of optimized machine tool processing control parameters. However, once the program is determined, it is difficult to adjust flexibly and difficult to cope with unexpected situations during the processing process.

[0006] Although the invention CN113894617A takes into account the tool state, it cannot solve other unexpected situations well. If the intelligent control system cannot adapt to these changes in time, it will result in the part size, shape or surface quality not meeting the requirements, thereby affecting the overall performance of the product.

[0007] Therefore, the present invention provides an intelligent control method for a numerical control machine tool production line. Summary of the Invention

[0008] (1) Technical problems to be solved

[0009] Aiming at the deficiencies of the prior art, the present invention provides an intelligent control method for a numerical control machine tool production line. The present invention groups and numbers the parts of the underground drilling precision instrument to be processed, extracts the initial maximum temperature and the initial minimum temperature of each group of parts, produces each group of parts of the underground drilling precision instrument to be processed using different processing parameters, captures the maximum processing temperature and the minimum processing temperature of the parts under different processing parameters, and outputs the corresponding changed processing parameters , calculates the high-temperature influence coefficient and the low-temperature influence coefficient of the changed processing parameters of each group of parts, and calculates the comprehensive temperature influence coefficient of the changed processing parameters of each group of parts ; scans the parts that have completed the flow production at different cutting temperatures, obtains the roundness , flatness , and cylindricity of the parts that have completed the flow production at different cutting temperatures, calculates the precision difference of the parts that have completed the flow production at different cutting temperatures, and determines the adjustment temperature threshold; extracts the real-time maximum processing temperature during the actual production process. When the real-time maximum processing temperature exceeds the adjustment temperature threshold, a production control instruction is sent outwards, the real-time processing parameters and the comprehensive temperature influence coefficient are obtained, and the real-time regulated processing parameters are calculated , it can reduce the thermal deformation and cutting force changes during the machining process, which helps to maintain the stability of machining accuracy and improve product quality, thus solving the technical problems described in the background art.

[0010] (II) Technical Solution

[0011] To achieve the above objectives, the present invention is realized through the following technical solutions: An intelligent control method for a numerical control machine tool production line, including the following steps:

[0012] Group and number the parts of the underground drilling precision instrument to be machined, and extract the initial highest temperature and the initial lowest temperature <> of each group of parts to be machined underground drilling precision instrument parts. Produce each group of parts using different machining parameters, and capture the highest machining temperature and the lowest machining temperature of the parts under different machining parameters, and output the corresponding variable machining parameters Calculate the high-temperature influence coefficient and the low-temperature influence coefficient of the variable machining parameters of each group of parts, and calculate the temperature comprehensive influence coefficient of the variable machining parameters of each group of parts ; ;

[0013] Scan the parts that have completed the flow production at different cutting temperatures, and obtain the roundness , flatness and cylindricity of the parts that have completed the flow production at different cutting temperatures, calculate the accuracy difference of the parts that have completed the flow production at different cutting temperatures, and determine the adjustment temperature threshold;

[0014] Extract the real-time highest machining temperature during the actual production process. When the real-time highest machining temperature exceeds the adjustment temperature threshold, send out a production control instruction, obtain the real-time machining parameters and the temperature comprehensive influence coefficient , and calculate the real-time regulated machining parameters .

[0015] Further, group and number the parts of the underground drilling precision instrument to be machined, use an infrared thermal imager to capture the surface temperature field of the workpiece, and extract the initial highest temperature and the initial lowest temperature of each group of parts. Produce each group of parts of the underground drilling precision instrument to be machined using different machining parameters, and use an infrared thermal imager to capture the highest machining temperature and the minimum processing temperature , and output the corresponding changed processing parameters .

[0016] Among them, for each group of precision instrument parts for underground drilling to be processed, the method of controlling variables is adopted. For example, in the first group, the machining feed rate and cutting depth are the same, the cutting speed is different, and the changed processing parameter is the cutting speed; in the second group, the cutting speed and cutting depth are the same, the feed rate is different, and the changed processing parameter is the feed rate; in the third group, the cutting speed and feed rate are the same, the cutting depth is different, and the changed processing parameter is the cutting depth.

[0017] Furthermore, obtain the initial maximum temperature , initial minimum temperature , machining maximum temperature and machining minimum temperature of each group of parts, and calculate the machining high temperature difference and machining low temperature difference :

[0018]

[0019] Among them, i represents the group number of the precision instrument parts for underground drilling to be processed, i=1、2、3 , j represents the sequence number of different changed processing parameters in the same group, j = 1, 2, … n , n is the total number of precision instrument parts for underground drilling to be processed in each group.

[0020] Furthermore, obtain the changed processing parameter and machining high temperature difference of each group of parts, and calculate the high temperature influence coefficient of the changed processing parameter on the machining high temperature difference :

[0021]

[0022] Furthermore, obtain the changed processing parameter and machining low temperature difference of each group of parts, and calculate the low temperature influence coefficient of the changed processing parameter on the machining low temperature difference :

[0023]

[0024] Furthermore, obtain the high temperature influence coefficient of the changed processing parameter of each group of parts and low-temperature influence coefficient , calculate the temperature comprehensive influence coefficient of each group of parts with changed processing parameters : :

[0025]

[0026] Furthermore, use a laser scanner to scan the parts completed in the flow production at different cutting temperatures, and obtain the roundness , flatness and cylindricity of the parts completed in the flow production at different cutting temperatures, and calculate the accuracy difference of the parts completed in the flow production at different cutting temperatures :

[0027]

[0028] Among them, a represents the sequential number of different cutting temperatures, a = 1, 2, … m , m is the total number of cutting temperature numbers

[0029] Furthermore, when the accuracy difference exceeds the accuracy standard of the parts of the underground drilling precision instrument, mark this cutting temperature as the dangerous cutting temperature, and take 0.9 times of the lowest value of the dangerous cutting temperature as the adjustment temperature threshold

[0030] Furthermore, after receiving the production regulation instruction, obtain the real-time processing parameters and the temperature comprehensive influence coefficient , and calculate the real-time regulated processing parameters :

[0031]

[0032] Among them, x represents the time number of the same part processing

[0033] (III) Beneficial effects

[0034] The present invention provides an intelligent control method for a numerical control machine tool production line, which has the following beneficial effects

[0035] 1. Group and number the parts of the underground drilling precision instrument to be processed, extract the initial highest temperature and the initial lowest temperature of each group of parts, produce each group of parts of the underground drilling precision instrument to be processed with different processing parameters, capture the processing highest temperature and the processing lowest temperature of the parts under different processing parameters, and output the corresponding changed processing parameters Calculate the changed machining parameters for each group of parts of the high-temperature influence coefficient and the low-temperature influence coefficient and calculate the changed machining parameters for each group of parts of the comprehensive temperature influence coefficient which can provide a basis for subsequent data analysis and improvement, customize the most suitable machining parameters for each part, thereby improving machining efficiency and product quality.

[0036] 2. Scan the parts after the flow production at different cutting temperatures to obtain the roundness , flatness and cylindricity of the parts after the flow production at different cutting temperatures, calculate the precision difference of the parts after the flow production at different cutting temperatures and determine the adjusted temperature threshold, which can optimize the cutting parameter settings in the production process, contribute to the standardization and automation of the production process, and improve production efficiency and product quality.

[0037] 3. Extract the highest real-time machining temperature during the actual production process When the highest real-time machining temperature exceeds the adjusted temperature threshold, send out a production control instruction outward, obtain the real-time machining parameters and the comprehensive temperature influence coefficient , calculate the real-time adjusted machining parameters which can reduce the thermal deformation and cutting force changes during the machining process, contribute to maintaining the stability of machining precision, and improve product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a schematic flow diagram of an intelligent control method for a numerical control machine tool production line according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. 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 protection scope of the present invention.

[0040] Please refer to Figure 1 , the present invention provides an intelligent control method for a numerical control machine tool production line, including the following steps:

[0041] Step 1. Group and number the parts of the underground drilling precision instrument to be machined, and extract the initial highest temperature of each group of parts and initial minimum temperature , each group of underground drilling precision instrument parts to be processed is produced using different processing parameters, and the highest processing temperature of the parts under different processing parameters is captured. and minimum processing temperature , and output the corresponding change processing parameters , calculate the changing processing parameters of each set of parts High temperature influence coefficient and low temperature effect coefficient , and calculate the changing processing parameters of each set of parts Temperature comprehensive influence coefficient .

[0042] The step 1 includes the following:

[0043] Step 101: Group and number the parts of underground drilling precision instruments to be processed, use an infrared thermal imager to capture the surface temperature field of the workpiece, and extract the initial maximum temperature of each group of parts. and initial minimum temperature Each set of underground drilling precision instrument parts to be processed is produced using different processing parameters, and an infrared thermal imager is used to capture the highest processing temperature of the parts under different processing parameters. and minimum processing temperature , and output the corresponding change processing parameters .

[0044] Among them, each group of underground drilling precision instrument parts to be processed adopts the method of controlling variables. For example, the first group has the same processing feed speed and cutting depth, but different cutting speeds, and the changing processing parameter is cutting speed. The second group has the same processing cutting speed and cutting depth, but different feed speeds, and the changing processing parameter is feed speed. The third group has the same cutting speed and feed speed, but different cutting depths, and the changing processing parameter is cutting depth.

[0045] Step 102: Obtain the initial maximum temperature of each group of parts , initial minimum temperature , Maximum processing temperature and minimum processing temperature , calculate the high temperature difference of processing with different processing parameters and processing low temperature difference :

[0046]

[0047] in, i Indicates the group number of the underground drilling precision instrument parts to be processed, i=1、2、3 , j Indicates the sequence number of different processing parameters in the same group.j = 1, 2, … n , n The total number of each group of underground drilling precision instrument parts to be processed.

[0048] Step 103: Obtain the changing processing parameters of each group of parts and high processing temperature difference , calculate the changing processing parameters of each group of parts High temperature difference during processing High temperature influence coefficient :

[0049]

[0050] Step 104: Obtain the changing processing parameters of each group of parts and processing low temperature difference , calculate the changing processing parameters of each group of parts Low temperature difference for processing Low temperature influence coefficient :

[0051]

[0052] Step 105: Obtain the processing parameters of each set of parts High temperature influence coefficient and low temperature effect coefficient , calculate the changing processing parameters of each set of parts Temperature comprehensive influence coefficient :

[0053]

[0054] When using, combine the contents in steps 101 to 105:

[0055] The underground drilling precision instrument parts to be processed are grouped and numbered, and the initial maximum temperature of each group of parts is extracted. and initial minimum temperature , each group of underground drilling precision instrument parts to be processed is produced using different processing parameters, and the highest processing temperature of the parts under different processing parameters is captured. and minimum processing temperature , and output the corresponding change processing parameters , calculate the changing processing parameters of each set of parts High temperature influence coefficient and low temperature effect coefficient , and calculate the changing processing parameters of each set of parts Temperature comprehensive influence coefficient , which can provide a basis for subsequent data analysis and improvement, customize the most suitable processing parameters for each part, thereby improving processing efficiency and product quality.

[0056] Step 2: Scan the parts that have completed the flow production at different cutting temperatures, and obtain the roundness , flatness and cylindricity of the parts that have completed the flow production at different cutting temperatures, calculate the accuracy difference of the parts that have completed the flow production at different cutting temperatures , and determine the temperature adjustment threshold.

[0057] The said Step 2 includes the following contents:

[0058] Step 201: Use a laser scanner to scan the parts that have completed the flow production at different cutting temperatures, and obtain the roundness , flatness and cylindricity of the parts that have completed the flow production at different cutting temperatures, calculate the accuracy difference of the parts that have completed the flow production at different cutting temperatures :

[0059]

[0060] Among them, a represents the sequential number of different cutting temperatures, a = 1, 2, … m , m is the total number of cutting temperature numbers.

[0061] Step 202: When the accuracy difference exceeds the accuracy standard of the parts of the underground drilling precision instrument, mark this cutting temperature as a dangerous cutting temperature, and take 0.9 times the lowest value of the dangerous cutting temperature as the temperature adjustment threshold.

[0062] When in use, combine the contents in 201 and 202:

[0063] Scan the parts that have completed the flow production at different cutting temperatures, and obtain the roundness , flatness and cylindricity of the parts that have completed the flow production at different cutting temperatures, calculate the accuracy difference of the parts that have completed the flow production at different cutting temperatures , determine the temperature adjustment threshold, which can optimize the cutting parameter settings in the production process, which helps to realize the standardization and automation of the production process, and improve production efficiency and product quality.

[0064] Step 3: Extract the highest real-time processing temperature during the actual production process , when the highest real-time processing temperature When the regulated temperature threshold is exceeded, a production regulation instruction is sent outwards, and real-time processing parameters are obtained. and the comprehensive temperature influence coefficient , calculate the real-time regulated processing parameters .

[0065] The third step includes the following contents:

[0066] Step 301: During the actual production process, use an infrared thermal imager to capture the surface temperature field of the processed workpiece and extract the highest real-time processing temperature. When the highest real-time processing temperature exceeds the regulated temperature threshold, a production regulation instruction is sent outwards.

[0067] Step 302: After receiving the production regulation instruction, obtain the real-time processing parameters and the comprehensive temperature influence coefficient , calculate the real-time regulated processing parameters :

[0068]

[0069] where x represents the time number of machining the same part.

[0070] During use, combine the contents in Steps 301 and 302:

[0071] Extract the highest real-time processing temperature during the actual production process When the highest real-time processing temperature exceeds the regulated temperature threshold, a production regulation instruction is sent outwards, and the real-time processing parameters and the comprehensive temperature influence coefficient are obtained, and the real-time regulated processing parameters are calculated, which can reduce the thermal deformation and cutting force change during the processing, which helps to maintain the stability of the machining accuracy and improve the product quality.

[0072] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by the combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution.

[0073] The unit described as a separation component may or may not be physically separated. The component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0074] As described above, it is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the technical field of this application can easily think of changes or substitutions within the technical scope disclosed by this application, and all of them should be covered within the protection scope of this application.

Claims

1. An intelligent control method for a CNC machine tool production line, characterized by: The steps include: The underground drilling precision instrument parts to be processed are grouped and numbered, and the initial maximum temperature of each group of parts is extracted. and initial minimum temperature , each group of underground drilling precision instrument parts to be processed is produced using different processing parameters, and the highest processing temperature of the parts under different processing parameters is captured. and minimum processing temperature , and output the corresponding change processing parameters , calculate the changing processing parameters of each set of parts High temperature influence coefficient and low temperature effect coefficient , and calculate the changing processing parameters of each set of parts Temperature comprehensive influence coefficient ; Scan the parts produced in a process at different cutting temperatures to obtain the roundness of the parts produced in a process at different cutting temperatures , flatness and cylindricity , calculate the accuracy difference of parts produced in a process at different cutting temperatures , determine the adjustment temperature threshold; Extract the real-time maximum processing temperature during the actual production process , when the maximum temperature is processed in real time When the temperature exceeds the threshold, a production control instruction is issued to obtain real-time processing parameters. and temperature comprehensive influence coefficient , calculate and control processing parameters in real time .

2. The intelligent control method for a CNC machine tool production line according to claim 1, characterized in that: Get the initial maximum temperature of each group of parts , initial minimum temperature , Maximum processing temperature and minimum processing temperature , calculate the high temperature difference of processing with different processing parameters and processing low temperature difference : in, i Indicates the group number of the underground drilling precision instrument parts to be processed, i=1、2、3 , j Indicates the sequence number of different processing parameters in the same group. j=1, 2, ...n , n The total number of each group of underground drilling precision instrument parts to be processed.

3. The intelligent control method for a CNC machine tool production line according to claim 2, characterized in that: Get the changing processing parameters of each group of parts and high processing temperature difference , calculate the changing processing parameters of each group of parts High temperature difference during processing High temperature influence coefficient : 。 4. The intelligent control method for a CNC machine tool production line according to claim 2, characterized in that: Get the changing processing parameters of each group of parts and processing low temperature difference , calculate the changing processing parameters of each group of parts Low temperature difference for processing Low temperature influence coefficient : 。 5. The intelligent control method for a CNC machine tool production line according to claim 4, characterized in that: Get the changing processing parameters of each set of parts High temperature influence coefficient and low temperature effect coefficient , calculate the changing processing parameters of each set of parts Temperature comprehensive influence coefficient : 。 6. The intelligent control method for a CNC machine tool production line according to claim 1, characterized in that: Use a laser scanner to scan the parts produced in a process at different cutting temperatures to obtain the roundness of the parts produced in a process at different cutting temperatures. , flatness and cylindricity , calculate the accuracy difference of parts produced in a process at different cutting temperatures : in, a Indicates the sequential number of different cutting temperatures, a=1, 2, …m , m The total number of cutting temperatures.

7. The intelligent control method for a CNC machine tool production line according to claim 6, characterized in that: When the accuracy is poor When the cutting temperature exceeds the accuracy standard of underground drilling precision instrument parts, the cutting temperature is marked as a dangerous cutting temperature, and 0.9 times the lowest value of the dangerous cutting temperature is taken as the adjustment temperature threshold.

8. The intelligent control method for a CNC machine tool production line according to claim 1, characterized in that: After receiving the production control instructions, obtain real-time processing parameters and temperature comprehensive influence coefficient , calculate and control processing parameters in real time : Among them, x represents the time number of processing the same part.

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