A method, system and program product for intelligent control of numerical control machining process

Abstract

The present invention discloses an intelligent control method, system and program product for a numerical control machining process. First, according to the shape, size and machining process requirements of the machined product, the tool type, tool material, workpiece material and workpiece size are determined, and various machining parameters of the machine tool are set. Then, a simulation model is established based on preset parameters to simulate the cutting operation in the numerical control machining process and obtain simulation experimental data. At the same time, sensor data in the numerical control machining process is collected to monitor the working state and machining parameters of the numerical control machine tool. Next, based on the simulation experimental data and sensor data, the two data are verified and compared. Finally, based on the compensation parameters obtained by prediction or the optimized machining parameters obtained by regulation, the machining parameters of the machine tool are adjusted and optimized. The present invention can make the adjustment of the numerical control machining process more intelligent through the collaborative cooperation of multiple steps / modules, and can also improve the precision and production efficiency of the machined workpiece.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent control of numerical control machining processes, and relates to intelligent control technology of numerical control machining processes, and specifically to an intelligent control method, system and computer program product of a numerical control machining process. Background Art

[0002] Computer Numerical Control (NC) is a process that uses a computer control system to control machine tools and cutting tools for processing. Compared with traditional manual operations or traditional mechanical processing methods, CNC processing is efficient, accurate, and flexible, and is widely used in the processing and production of various parts. CNC processing includes CNC lathe processing, CNC milling machine processing, CNC drilling machine processing and other forms, and is one of the important processing methods in modern manufacturing.

[0003] The core of existing CNC machining technology is to guide the movement of machine tools and cutting tools through pre-written CNC programs to achieve cutting, milling, drilling and other processing of workpieces. Although CNC machining technology has a high level of automation, there are still many problems and challenges in practical applications. For example, the existing CNC machining technology mainly plays the role of a sequential and logical executor in terms of regulation, lacking the function of interacting with other intelligent decision-making systems of the manufacturing system and the ability to coordinate; CNC machining programs need to be compiled in advance, and when compiling the program, appropriate parameters need to be set in advance. Appropriate parameters can be obtained through complex calculations, but it is impossible to know whether the obtained parameters are coordinated with the goals of the entire manufacturing system. At the same time, the tool will wear during processing, and tool wear will lead to inaccurate processing of the workpiece.

[0004] In summary, the existing CNC machining technology has many deficiencies in intelligent control and cannot meet the needs of the modern intelligent manufacturing environment. Therefore, it is an urgent technical problem to develop intelligent control technology for CNC machining process to achieve real-time optimization and dynamic adjustment of CNC machining process, improve machining accuracy and efficiency, and reduce production costs. Summary of the invention

[0005] (I) Purpose of the invention

[0006] In view of the defects and shortcomings of existing CNC machining technology in intelligent control, and to solve at least one of the above-mentioned and other technical problems in the prior art, the present invention aims to provide a method, system and program product for intelligent control of a CNC machining process. Through the collaborative cooperation of multiple modules, the CNC machining process can be intelligently controlled, while improving the precision and production efficiency of the processed workpiece.

[0007] (II) Technical solution

[0008] In order to achieve the purpose of the invention and solve the technical problems, the present invention adopts the following technical solutions:

[0009] The first invention object of the present invention is to provide a method for intelligently controlling a numerical control machining process, which is used to realize intelligent adjustment and optimization of the numerical control machining process. The method comprises the following steps when implemented:

[0010] SS1. Determine the tool type, tool material, workpiece material and workpiece size according to the shape, size and processing requirements of the processed product, and set the various processing parameters of the machine tool. The processing parameters of the machine tool include at least cutting speed, feed speed and cutting depth;

[0011] SS2. Establish a simulation model based on the tool type, tool material, workpiece material, workpiece size and machine tool processing parameters preset in step SS1, simulate the cutting operation in the CNC machining process, and obtain simulation experimental data;

[0012] SS3. Collect sensor data during CNC machining to monitor the working status and machining parameters of the CNC machine tool, wherein the sensor data includes at least speed sensor data, displacement sensor data, acceleration sensor data, force sensor data and vibration sensor data;

[0013] SS4. Based on the simulation experimental data obtained in step SS2 and the sensor data collected in step SS3, the correct processing parameter range is generated, and the two data are verified and compared. When the two are consistent, the prediction compensation operation of the processing parameters is performed, and when the two are inconsistent, the processing parameter adjustment operation is performed;

[0014] SS5. When performing the prediction and compensation operation of the machining parameters, the tool head data is collected based on the sensor data collected in step SS3, a mathematical model of tool head wear is established, the tool head wear in the future is predicted, and the compensation parameters of the machine tool machining parameters are calculated;

[0015] SS6. When performing the control operation of the processing parameters, based on the verification and comparison results of the two data in step SS4 that are inconsistent, adjust the machine tool processing parameters of the simulation model in step SS2, and re-simulate, and based on the adjusted simulation results and combined with the sensor data, re-execute the verification and comparison operation of step SS4 until the two data are consistent;

[0016] SS7. Based on the compensation parameters of the machine tool processing parameters predicted in step SS5 or the optimized processing parameters obtained by control in step SS6, the actual processing parameters set by the machine tool in the optimization step SS1 are adjusted to achieve intelligent adjustment and optimization of the CNC processing process.

[0017] The second invention object of the present invention is to provide a computer program product, including computer instructions, for executing the above-mentioned CNC machining process intelligent control method of the present invention.

[0018] The third invention object of the present invention is to provide an intelligent control system for a numerical control machining process, comprising a parameter setting module, a simulation module, a data acquisition module, a verification module, a control and regulation module, and a prediction and compensation module, wherein:

[0019] The parameter setting module is used to determine the tool type, tool material, workpiece material, and workpiece size according to the shape, size, and processing requirements of the processed product, and to set various parameters of the machine tool, including cutting speed, feed speed, and cutting depth;

[0020] The input end of the simulation module is communicatively connected to the parameter setting module, and a simulation model is established based on the tool type, tool material, workpiece material, workpiece size and machine tool processing parameters preset in the parameter setting module, and a simulation experiment is performed on the cutting operation in the CNC machining process to obtain simulation experiment data;

[0021] The data acquisition module is used to collect sensor data in the CNC machining process in real time to monitor the machine tool status and machining parameters, and the sensor data at least includes speed sensor data, displacement sensor data, acceleration sensor data, force sensor data and vibration sensor data;

[0022] The input end of the data verification module is communicatively connected to the simulation module and the data acquisition module, and based on the received simulation experiment data of the simulation module and the actual production and processing data of the data acquisition module, generates a correct processing parameter range, and verifies and compares the data. When the data are consistent, the data is transmitted to the prediction and compensation module, and when the data are inconsistent, the data is transmitted to the control and regulation module;

[0023] The input end of the prediction and compensation module is communicatively connected to the data verification module, which collects the cutter head data based on the known sensor data, establishes a mathematical model of cutter head wear, and uses these data as the input of the prediction and compensation mechanism to predict the wear in the future period of time and calculate the corresponding compensation parameters;

[0024] The input end of the control and regulation module is communicatively connected to the data verification module, which is used to parse the instructions in the CNC program, convert them into execution control signals and output them. At the same time, when the data verification results are inconsistent, the machine tool processing parameters of the simulation model in the simulation module are adjusted and optimized, and the simulation is re-performed. Based on the adjusted simulation results and combined with the sensor data, verification and comparison are re-performed until the data remains consistent.

[0025] (III) Technical Effect

[0026] Compared with the prior art, the CNC machining process intelligent control method, system and program product of the present invention have the following beneficial and significant technical effects:

[0027] (1) The present invention can optimize processing parameters comprehensively and improve processing efficiency and quality through collaborative decision-making and interaction among steps or modules such as parameter setting, simulation, data collection, data verification, prediction compensation and control regulation, and can also reduce errors caused by manual intervention, thereby improving the overall performance and intelligent level of regulation;

[0028] (2) The present invention compares and verifies the data of the simulated processing process and the data of the actual processing through simulation, data collection and data verification, and sets the processing parameter range according to the data of the simulated processing process. When the data of the two are consistent, normal processing will continue. When the data are inconsistent, the data will be transmitted to the control and regulation step or module for regulation, so that it can be timely understood whether the actual processing data is coordinated with the final processing target. At the same time, it can also timely discover the errors and deviations in the adjustment process, and adjust the actual processing parameters so that the actual processing data is within the range of the simulated processing data;

[0029] (3) The present invention sets predictive compensation in conjunction with parameter predictive simulation in simulation. The predictive compensation first predicts the tool head wear condition in a future period of time and obtains compensation parameters, outputs the compensation parameters to the parameter predictive simulation in simulation, verifies and adjusts the compensation parameters through simulation experiments, and finally transmits the compensation parameters to the predictive compensation. The predictive compensation step or module transmits the compensation parameters to the control step or module, which is controlled by outputting instructions to complete the predictive compensation parameter control. The added compensation parameters can effectively reduce the problem of poor workpiece quality caused by tool wear. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a flow chart of the intelligent control method of the numerical control machining process of the present invention;

[0031] Figure 2 The figure is a block diagram of the intelligent control system for the numerical control machining process of the present invention. DETAILED DESCRIPTION

[0032] In order to better understand the present invention, the content of the present invention is further explained below in conjunction with embodiments. In the accompanying drawings, the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The embodiments described below by reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limitations of the present invention.

[0033] Example 1

[0034] As a specific example, Figure 1 As shown, the CNC machining process intelligent control method provided by the present invention is used to realize intelligent adjustment and optimization of the CNC machining process, improve machining accuracy and production efficiency, and the method includes the following steps when implemented:

[0035] SS1. Determine the tool type, tool material, workpiece material and workpiece size according to the shape, size and processing requirements of the processed product, and set the various processing parameters of the machine tool. The processing parameters of the machine tool include at least cutting speed, feed speed and cutting depth.

[0036] SS2. Establish a simulation model based on the tool type, tool material, workpiece material, workpiece size and machine tool processing parameters preset in step SS1, simulate the cutting operation in the CNC machining process, and obtain simulation experimental data.

[0037] SS3. Collect sensor data during CNC machining to monitor the working status and machining parameters of the CNC machine tool. The sensor data includes at least speed sensor data, displacement sensor data, acceleration sensor data, force sensor data and vibration sensor data.

[0038] SS4. Based on the simulated experimental data obtained in step SS2 and the sensor data collected in step SS3, the correct processing parameter range is generated, and the two data are verified and compared. When the two are consistent, the processing parameter prediction compensation operation is performed. When the two are inconsistent, the processing parameter adjustment operation is performed.

[0039] SS5. When performing the predictive compensation operation of the machining parameters, the tool head data is collected based on the sensor data collected in step SS3, a mathematical model of tool head wear is established, the tool head wear in the future is predicted, and the compensation parameters of the machine tool machining parameters are calculated.

[0040] SS6. When performing the adjustment operation of the processing parameters, based on the verification and comparison results of the inconsistency of the two data in step SS4, adjust the machine tool processing parameters of the simulation model in step SS2 and re-simulate, and based on the adjusted simulation results and combined with the sensor data, re-execute the verification and comparison operation of step SS4 until the two data are consistent.

[0041] SS7. Based on the compensation parameters of the machine tool processing parameters predicted in step SS5 or the optimized processing parameters obtained by control in step SS6, the actual processing parameters set by the machine tool in the optimization step SS1 are adjusted to achieve intelligent adjustment and optimization of the CNC processing process.

[0042] In some preferred embodiments, in the above step SS1, the tool type, tool material, workpiece material, and workpiece size are determined according to the shape, size, and processing requirements of the processed product, and the processing process of setting various machine tool parameters is as follows: according to the requirements of the processed product and the characteristics of the processed material, the tool type and tool material are determined, including the shape, material, and blade angle of the tool; the material and size of the workpiece are determined, including parameters such as the hardness and strength of the workpiece; according to the characteristics of the selected tool and workpiece, the various machine tool parameters are set, including the cutting speed, feed speed, and cutting depth.

[0043] In some preferred embodiments, in the above step SS2, a simulation model is established to simulate the cutting operation in the CNC machining process, and the process of obtaining simulation experimental data is as follows: the tool type, tool material, workpiece material, workpiece size and machine tool parameters preset in step SS1 are used as input data, and a simulation model is established; a simulation experiment is performed based on the established simulation model to simulate the cutting operation in the CNC machining process, and various data in the simulation experiment are recorded, including cutting speed, cutting depth, cutting force, and feed speed.

[0044] Furthermore, when a simulation experiment is conducted based on the established simulation model, a parameter prediction simulation operation is also included: the compensation parameters calculated in step SS5 are used as input data, including information such as tool compensation amount and compensation type, and a tool wear model is established based on the input compensation parameters, wherein the model considers factors such as tool material, cutting conditions, and processing materials; the time period of the simulation experiment is determined, that is, the use of the simulated tool head in the future is simulated; the wear process of the tool in the set time period is simulated according to the established wear model to obtain simulation result data; the wear data obtained from the simulation experiment is compared and analyzed with the input compensation parameters to verify the compensation parameters. When the data are consistent, the compensation parameters do not need to be adjusted. When the data are inconsistent, the compensation parameters are adjusted according to the verification results to obtain the final data; the obtained compensation parameters are transmitted to step SS5 again for prediction compensation operation.

[0045] In some preferred embodiments, in the above step SS3, the processing process of real-time acquisition of sensor data during CNC machining is as follows: data of speed sensor, displacement sensor, acceleration sensor, force sensor and vibration sensor are collected respectively, the speed sensor is used to monitor the cutting speed, the displacement sensor is used to monitor the position and motion trajectory of the workpiece during the machining process, so as to determine the parameters of the cutting depth, the acceleration sensor is used to monitor the acceleration of the machine tool or the workpiece, and the parameters of the feed speed during the machining process, the force sensor is used to monitor the cutting force and feedback force during the cutting process and evaluate the cutting load, and the vibration sensor is used to monitor the vibration of the tool during the cutting process.

[0046] In some preferred embodiments, in the above step SS4, the processing process of verifying and comparing the data is as follows: receiving the simulation experiment data of step SS2 and the actual processing data of step SS3; setting the processing parameter range according to the simulation experiment data, the cutting speed is V1, the cutting depth is D1, the cutting force is S1 and the feed speed is A1, and for the cutting speed in the actual processing data is V2, the cutting depth is D2, the cutting force is S2 and the feed speed is A2: when V2∈V1, D2∈D1, S2∈S1, A2∈A1, the two data are consistent, and the data is transmitted to step SS5 for predictive compensation operation; when If the two data are inconsistent, the data is transmitted to step SS6 for data regulation.

[0047] In some preferred embodiments, in the above step SS5, the wear condition in the future is predicted based on the mathematical model of the tool head wear, and the corresponding compensation parameter is calculated. The processing process is as follows: Based on the known sensor data, a mathematical model of tool head wear is established, and the tool head wear amount W is set as a function of these sensor data. The specific formula is: W(t) = f(x 1t ,x 2t ,x 3t ,x 4t ,x 5t ), where W(t) represents the wear of the tool tip at time t, x 1t 、x 2t 、x 3t 、x 4t 、x 5t Respectively represent the data of the speed sensor, displacement sensor, acceleration sensor, force sensor, and vibration sensor at time t; the prediction algorithm is used to predict the wear of the cutter head in the future. The specific formula is: W p =β0+β1x 1f +β2x 2f +β3x 3f +β4x 4f +β5x 5f , where W p represents the predicted value of tool head wear in the future, β0, β1, β2, β3, β4, β5 are model parameters, and x 1f 、x 2f 、x 3f 、x 4f 、x 5f Represents the data of the speed sensor, displacement sensor, acceleration sensor, force sensor, and vibration sensor at a future time point; according to the predicted tool head wear, combined with the compensation algorithm, calculate the corresponding compensation parameters, including the compensation length and compensation angle of the tool; output the calculated compensation parameters to step SS3 for simulation.

[0048] Furthermore, according to the predicted wear of the cutter head, the corresponding compensation parameter is calculated as follows: the wear amount W of the cutter head in the future period of time is obtained p , determine the tool compensation strategy and algorithm, calculate the corresponding compensation length and compensation angle, the specific formula is:

[0049] [T=k1·W p +b1]

[0050] [a=k2·W p +b2]

[0051] Among them, k1, b1, k2, b2 are constants, T and a are the calculated compensation length and compensation angle respectively.

[0052] Example 2

[0053] Corresponding to Example 1, Figure 2 As shown, this embodiment is used to introduce in detail the intelligent control system of the CNC machining process of the present invention, including a parameter setting module, a simulation module, a data acquisition module, a verification module, a control and regulation module, a prediction and compensation module, etc.

[0054] The parameter setting module in the present invention is used to determine the tool type, tool material, workpiece material, and workpiece size according to the shape, size, and processing requirements of the processed product, and to set various parameters of the machine tool, including cutting speed, feed speed, and cutting depth.

[0055] The input end of the simulation module is communicatively connected to the parameter setting module, and a simulation model is established based on the tool type, tool material, workpiece material, workpiece size and machine tool processing parameters preset in the parameter setting module, and a simulation experiment is performed on the cutting operation in the CNC machining process to obtain simulation experiment data; the data acquisition module is used to collect sensor data in the CNC machining process in real time, monitor the machine tool status and processing parameters, and the sensor data at least includes speed sensor data, displacement sensor data, acceleration sensor data, force sensor data and vibration sensor data.

[0056] At the same time, the input end of the data verification module in the present invention is communicatively connected to the simulation module and the data acquisition module, and based on the received simulation experimental data of the simulation module and the actual production and processing data of the data acquisition module, a correct processing parameter range is generated, and the data is verified and compared. When the data is consistent, the data is transmitted to the prediction and compensation module, and when the data is inconsistent, the data is transmitted to the control and regulation module; the input end of the prediction and compensation module is communicatively connected to the data verification module, and the tool head data is collected based on the known sensor data, a mathematical model of tool head wear is established, and these data are used as the input of the prediction and compensation mechanism to predict the wear conditions in the future period of time and calculate the corresponding compensation parameters; the input end of the control and regulation module is communicatively connected to the data verification module, which is used to parse the instructions in the CNC program, convert them into execution control signals and output them, and when the data verification results are inconsistent, the machine tool processing parameters of the simulation model in the simulation module are adjusted and optimized, and the simulation is re-performed, and the verification and comparison are re-performed based on the adjusted simulation results and combined with the sensor data until the data remain consistent.

[0057] In addition, the CNC machining process intelligent control system of the present invention preferably also sets up a data integration module, which is used to represent the knowledge and information related to the CNC machining process in the form of a knowledge graph, including various machine tools, processing technologies, material properties, and establish the association relationship between them, and finally store the data; according to the collected data, the entities and relationships of the knowledge graph are established; the data is divided by different nodes, and the nodes are used to represent various machine tools, cutting tools, processing technologies and material properties, which are specifically divided into machine tools, cutting tools, processing technologies, and material properties, among which: machine tools: including lathes, milling machines, and drilling machines; cutting tools: various types of cutting tools, including milling cutters, drill bits, and turning tools; processing technologies: including milling, drilling, and turning; material properties: properties of various processing materials, including metals, plastics, and ceramics; edges are used to represent the association between nodes, and attribute information is added to nodes and edges to describe the relationship and characteristics between each element; the established knowledge graph is stored in a graph database, and managed and maintained. It should be noted that by establishing a knowledge graph, various machine tools, cutting tools, processing technologies and material properties can be managed in a structured form. This is not only conducive to data organization and retrieval, but also enables the relationship between nodes to be displayed more clearly.

[0058] In some preferred embodiments, the simulation module can be divided into a processing simulation unit and a parameter prediction simulation unit. The processing simulation unit simulates processing by preset parameters, and can obtain processing data to provide powerful judgment data for actual processing. At the same time, the processing simulation unit can use Mastercam software to simulate the processing process. The specific operation process of the parameter prediction simulation unit includes:

[0059] The calculated compensation parameters are used as input data, including information such as tool compensation amount and compensation type; a tool wear model is established based on the input compensation parameters; the model considers factors including tool material, cutting conditions, and processing materials; the time period of the simulation experiment is determined, that is, the use of the simulated tool head in the future is simulated; the simulation experiment is run using simulation software, and the wear process of the tool in the set time period is simulated according to the established wear model to obtain simulation result data; the wear data obtained from the simulation experiment is compared and analyzed with the input compensation parameters to verify the compensation parameters. When the data is consistent, the compensation parameters do not need to be adjusted. When the data is inconsistent, the compensation parameters are adjusted according to the verification results to obtain the final data; the compensation parameters are transmitted to the prediction compensation module again.

[0060] It should be noted that the parameter prediction simulation unit can use AdvantEdge software to simulate the wear of the tool head in the future. At the same time, the final predicted compensation parameters can be obtained through simulation experiments, making the compensation parameters more accurate and convenient for subsequent actual processing.

[0061] As a preferred embodiment, the verification module in the present invention receives the experimental data of the simulation module and the processing data of the actual production, generates the correct processing parameter range, and verifies and compares the data. When the data are consistent, the data is transmitted to the prediction compensation module, and when the data are inconsistent, the data is transmitted to the control and regulation module. Through the linkage of the verification and regulation modules, the accuracy and consistency of the processing parameters can be guaranteed, thereby improving the precision and quality of the processing.

[0062] In some preferred embodiments, the prediction and compensation module in the present invention collects tool head data based on known sensor data, establishes a mathematical model of tool head wear, and uses these data as inputs of the prediction and compensation mechanism to predict the wear conditions in the future and calculate the corresponding compensation parameters. It should be noted that the tool will wear during processing, and tool wear may cause deviations in the processing of the workpiece. Therefore, calculating the compensation length and compensation angle can make the processed workpiece more accurate. In addition, by predicting the wear of the tool head in the future and calculating the corresponding compensation parameters in a timely manner, preventive adjustments can be made before tool wear affects the processing quality.

[0063] Through the above embodiments, the purpose of the present invention is fully and effectively achieved. Those skilled in the art can understand that the present invention includes but is not limited to the contents described in the drawings and the above specific embodiments. Although the present invention has been described with respect to the most practical and preferred embodiments currently considered, it should be understood that the present invention is not limited to the disclosed embodiments, and any modification that does not deviate from the functional and structural principles of the present invention will be included in the scope of the claims.

Claims

1. A method for intelligent control of a numerical control machining process, characterized in that: The steps include: SS1. Determine the tool type, tool material, workpiece material and workpiece size according to the shape, size and processing requirements of the processed product, and set the various processing parameters of the machine tool; SS2. Establish a simulation model based on various parameters preset in step SS1, simulate the cutting operation in the CNC machining process, and obtain simulation experiment data, wherein the process is as follows: take the tool type, tool material, workpiece material, workpiece size and machine tool parameters preset in step SS1 as input data, and establish a simulation model; then conduct a simulation experiment based on the established simulation model, simulate the cutting operation in the CNC machining process, and record various data in the simulation experiment, including cutting speed, cutting depth, cutting force, and feed speed; SS3. Collect sensor data during CNC machining to monitor the working status and machining parameters of CNC machine tools; SS4. Generate a correct range of processing parameters based on the simulated experimental data obtained in step SS2 and the sensor data collected in step SS3, and verify and compare the two data. When the two are consistent, perform a prediction and compensation operation of the processing parameters. When the two are inconsistent, perform a control operation of the processing parameters. SS5. When performing the predictive compensation operation of the machining parameters, the tool head data is collected based on the sensor data collected in step SS3, a mathematical model of tool head wear is established, the tool head wear in the future is predicted, and the compensation parameters of the machine tool machining parameters are calculated. The processing process is as follows: First, based on the known sensor data, a mathematical model of tool head wear is established. W As a function of these sensor data, the specific formula is: in, W ( t ) indicates the time t The wear of the cutter head, x 1t , x 2t , x 3t , x 4t , x 5t Respectively, in time t Data from speed sensors, displacement sensors, acceleration sensors, force sensors, and vibration sensors; Then, the prediction algorithm is used to predict the wear of the cutter head in the future. The specific formula is: in, W p Indicates the predicted value of tool head wear in the future period of time, β 0. β 1. β 2. β 3. β 4. β 5 is the model parameter, x 1f , x 2f , x 3f , x 4f , x 5f Represents the data of the speed sensor, displacement sensor, acceleration sensor, force sensor, and vibration sensor at a future time point; Then, according to the predicted wear of the tool head and the compensation algorithm, the corresponding compensation parameters are calculated, including the compensation length and compensation angle of the tool; Finally, the calculated compensation parameters are output to step SS3 for simulation; SS6. When performing the control operation of the processing parameters, based on the verification and comparison results of the two data inconsistency in step SS4, the machine tool processing parameters of the simulation model in step SS2 are adjusted and optimized, and the simulation is re-performed. Based on the adjusted simulation results and combined with the sensor data, the verification and comparison operation of step SS4 is re-executed until the two data are consistent; SS7. Based on the compensation parameters of the machine tool processing parameters predicted in step SS5 or the optimized processing parameters obtained by control in step SS6, the actual processing parameters set by the machine tool in step SS1 are adjusted to achieve intelligent adjustment and optimization of the CNC processing process; And wherein, when performing the simulation experiment based on the established simulation model in step SS2, the following parameter prediction simulation operation is also included: The compensation parameters calculated in step SS5 are used as input data, including information such as tool compensation amount and compensation type, and a tool wear model is established based on the input compensation parameters. The model considers factors such as tool material, cutting conditions, and processing materials; Determine the time period of the simulation experiment, that is, simulate the use of the cutter head in the future; The wear process of the tool within a set time period is simulated according to the established wear model to obtain simulation result data; Compare and analyze the wear data obtained from the simulation experiment with the input compensation parameters to verify the compensation parameters. If the data are consistent, the compensation parameters do not need to be adjusted. If the data are inconsistent, adjust the compensation parameters according to the verification results to obtain the final data. The obtained compensation parameters are transmitted again to step SS5 for predictive compensation operation.

2. The intelligent control method for numerical control machining process according to claim 1, characterized in that: In the above step SS1, according to the shape, size and processing requirements of the processed product, the tool type, tool material, workpiece material, and workpiece size are determined, and the processing process of setting various parameters of the machine tool is as follows: Determine the tool type and tool material according to the requirements of the processed product and the characteristics of the processed material, including the shape, material and edge angle of the tool; Determine the material and size of the workpiece, including parameters such as hardness and strength of the workpiece; According to the characteristics of the selected tool and workpiece, set the machine tool parameters, including cutting speed, feed rate, and cutting depth.

3. The intelligent control method for numerical control machining process according to claim 1 is characterized in that: In the above step SS3, the processing process of real-time acquisition of sensor data during CNC machining is as follows: The data of speed sensor, displacement sensor, acceleration sensor, force sensor and vibration sensor are collected respectively. The speed sensor is used to monitor the cutting speed. The displacement sensor is used to monitor the position and motion trajectory of the workpiece during the processing to determine the parameters of the cutting depth. The acceleration sensor is used to monitor the acceleration of the machine tool or the workpiece and the parameters of the feed speed during the processing. The force sensor is used to monitor the cutting force and feedback force during the cutting process. The vibration sensor is used to monitor the vibration of the tool during the cutting process.

4. The intelligent control method for numerical control machining process according to claim 1, characterized in that: In the above step SS4, the process of verifying and comparing the data is as follows: Receiving the simulation experiment data of step SS2 and the actual processing data of step SS3; According to the simulation experiment data, the machining parameter range is set, the cutting speed is V1, the cutting depth is D1, the cutting force is S1 and the feed speed is A1. For the actual machining data, the cutting speed is V2, the cutting depth is D2, the cutting force is S2 and the feed speed is A2: When V2∈V1, D2∈D1, S2∈S1, A2∈A1, the two data are consistent, and the data is transmitted to step SS5 for prediction compensation operation; When V2∉V1, D2∉D1, S2∉S1, A2∉A1, the two data are inconsistent, and the data is transferred to step SS6 for data control.

5. The intelligent control method for numerical control machining process according to claim 1 is characterized in that: According to the predicted tool head wear, the process of calculating the corresponding compensation parameters is as follows: Get the wear amount of the cutter head in the future W p , determine the tool compensation strategy and algorithm, calculate the corresponding compensation length and compensation angle, the specific formula is: in, k 1. b 1. k 2. b 2 is a constant, T , a They are the calculated compensation length and compensation angle respectively.

6. A computer program product, characterized in that It includes computer instructions, which instruct a computing device to execute the intelligent control method for a numerical control machining process as described in any one of claims 1 to 5.

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