Numerical control machine tool cutting force intelligent regulation and control method and system based on data analysis

Abstract

The invention discloses a numerical control machine tool cutting force intelligent regulation and control method and system based on data analysis, and relates to the field of numerical control machine tool machining control, and the method comprises the steps of S1, data collection, S2, state evaluation model construction, S3, tool and personnel associated monitoring, and S4, hierarchical regulation and control and response. Related data in the cutting process of the numerical control machine tool are collected through various sensors; quantifying the overall state of the cutting process based on the collected data; monitoring the cutter state in real time, and associating the cutter state with personnel operation in combination with the operation habit and skill level data of an operator; rapid cutting force state judgment and response are achieved through data analysis, and a multi-stage regulation and control triggering mechanism is set; according to the method, through multi-dimensional monitoring and intelligent response, a management closed loop of collection-evaluation-monitoring-regulation is formed, an innovative solution is provided for efficient and stable machining of the numerical control machine tool, and the machining quality and efficiency are effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of numerical control machine tool processing control, and particularly relates to a numerical control machine tool cutting force intelligent regulation and control method and system based on data analysis. BACKGROUND

[0002] With the development of intelligent numerical control machine tools, the requirements for processing precision, efficiency and stability are increasing, and the traditional cutting force regulation method gradually cannot meet the needs; the traditional regulation relies on manual experience to set parameters, and cannot adapt to the changes in the working conditions in the processing process in real time; the cutting state evaluation is mainly based on a single parameter, and it is difficult to quantify the overall state of the cutting process; the monitoring of the tool state is not real-time and accurate enough, and it is difficult to ensure the stability of the cutting process; the emergency response mechanism is not flexible and intelligent enough, and the time-consuming of the closed loop from cutting force abnormality identification to parameter adjustment is long, which makes it difficult to effectively avoid problems such as processing quality decline and equipment damage, and it is difficult to meet the development needs of intelligent processing of numerical control machine tools.

[0003] In the existing numerical control machine tool processing technology, the cutting force regulation mainly relies on manual adjustment of parameters, the data is lagging and cannot fully reflect the cutting state, and it is difficult to adapt to complex and variable processing scenes; the cutting state evaluation is fragmented, and the cutting force, tool wear and processing quality are analyzed in isolation, and there is no global correlation model, and the overall cutting state depends on experience; the tool state monitoring and personnel operation monitoring are separated, and the tool abnormality caused by improper personnel operation cannot be found in time; the emergency response mechanism is rigid, and it is difficult to timely contain the expansion of processing problems caused by cutting force abnormalities, and it is difficult to meet the development trend of intelligent and efficient processing of numerical control machine tools. SUMMARY

[0004] The present application provides a numerical control machine tool cutting force intelligent regulation and control method and system based on data analysis, which solves the problems in the background art.

[0005] To solve the above technical problems, the present application adopts the following technical scheme: the present application provides a numerical control machine tool cutting force intelligent regulation and control method based on data analysis, comprising: S1. Data acquisition, using a variety of sensors to collect relevant data in the cutting process of the numerical control machine tool;

[0006] S2. State evaluation model construction, based on the relevant data in the cutting process of the numerical control machine tool, constructing a cutting force state evaluation model, a tool wear evaluation model and a processing quality evaluation model, and monitoring the temperature change in the cutting process of the numerical control machine tool;

[0007] S3. Tool and personnel correlation monitoring, relying on data analysis technology, the tool state is monitored in real time, and at the same time, the operation habits and skill level data of the operating personnel are combined to identify the operation behavior specification, and the tool state and personnel operation are correlated to ensure the stability of the cutting process;

[0008] S4. Hierarchical regulation and response, through data analysis to realize rapid cutting force state judgment and response, different cutting force state grades are obtained, and corresponding parameter adjustment and operation prompt are carried out according to different cutting force state grades.

[0009] The second aspect of the application provides a system for performing data analysis-based intelligent regulation of cutting force of a numerical control machine tool, comprising: a data acquisition module, which acquires relevant data in a cutting process of the numerical control machine tool by using various sensors;

[0010] A state evaluation model construction module, based on the relevant data in the cutting process of the numerical control machine tool, constructs a cutting force state evaluation model, a tool wear evaluation model and a machining quality evaluation model, and monitors temperature changes in the cutting process of the numerical control machine tool;

[0011] A tool and personnel correlation monitoring module, relying on data analysis technology, real-time monitors tool state, and at the same time, in combination with operation habit and skill level data of an operator, identifies operation behavior specification, correlates tool state and personnel operation, and safeguards stability of the cutting process;

[0012] A hierarchical regulation and response module, through data analysis to realize rapid cutting force state judgment and response, different cutting force state grades are obtained, and corresponding parameter adjustment and operation prompt are carried out according to different cutting force state grades.

[0013] The beneficial effects of the application are as follows: 1. In the state evaluation model construction S2, by constructing the cutting force state evaluation model, the tool wear evaluation model and the machining quality evaluation model, the overall state of the cutting process of the numerical control machine tool can be comprehensively and quantitatively evaluated, potential problems can be accurately identified, and compared with traditional single data evaluation, the precision is greatly improved.

[0014] 2. In the tool and personnel correlation monitoring S3, relying on data analysis technology, the tool state can be real-time monitored, at the same time, in combination with operation habit and skill level data of an operator, operation behavior specification of the personnel is identified, improper operation is found and corrected in time, and the stability of the cutting process is effectively safeguarded.

[0015] 3. In the hierarchical regulation and response S4, through data analysis to realize rapid cutting force state judgment and response, the multi-level regulation triggering mechanism ensures to make timely and reasonable response to different cutting force state grades, automatically carries out corresponding parameter adjustment and gives operation prompt, improves machining regulation efficiency, and reduces machining quality problems and equipment loss. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to make the technical solutions of the embodiments of the present application or the prior art clearer, the accompanying drawings needed in the embodiments or prior art description will be briefly introduced below. Obviously, the accompanying drawings in the following description only aim to some of the embodiments of the present application, and all other embodiments obtained by those of ordinary skill in the art without creative effort based on the embodiments of the present application shall fall within the protection scope of the present application.

[0017] Figure 1 The schematic diagram for connecting the method for implementing the present application.

[0018] Figure 2 The schematic diagram for connecting the system structure of the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort shall fall within the protection scope of the present application.

[0020] Referring to Figure 1 As shown in the figure, the present application provides a numerical control machine tool cutting force intelligent control method based on data analysis, comprising: S1. Data acquisition, collecting relevant data in the numerical control machine tool cutting process by using various sensors.

[0021] In the specific embodiments of the present application, the relevant data in the numerical control machine tool cutting process is collected, which specifically includes:

[0022] Collecting relevant data in the numerical control machine tool cutting process and personnel state data, wherein the relevant data in the numerical control machine tool cutting process includes three-direction cutting force of cutting tool, cutting depth, feed per tooth, cutting line speed, and tool tip arc radius; the personnel state data includes feed overshoot rate; since the data dimensions are different in calculation, the data needs to be standardized, and linear transformation is performed through the mean and standard deviation of the data to eliminate the dimension influence.

[0023] It should be noted that the cutting force, vibration, temperature and other data are collected by using various sensors, according to the "piezoelectric measurement technology" in the technical report, the piezoelectric force sensor (such as quartz crystal sensor) can be installed on the tool holder or workbench to collect three-direction cutting force components (X / Y / Z axes) in real time, and convert them into digital signals through the data acquisition system; the parameters such as "cutting depth, feed per tooth" are explicitly defined as "key process parameters affecting cutting force" in the technical report, and are read in real time through the CNC system; the standardization processing is linear transformation through the mean and standard deviation of the data, Where x is the original data, μ is the mean, and σ is the standard deviation; the processed data has a mean of 0 and a standard deviation of 1, which can eliminate the dimension effect.

[0024] S2. Construction of state assessment model: Based on the relevant data of the CNC machine tool cutting process, a cutting force state assessment model, a tool wear assessment model and a processing quality assessment model are constructed to quantify the overall state of the CNC machine tool cutting process.

[0025] In a specific embodiment of the present invention, the cutting force state evaluation model is constructed to evaluate the cutting force stability based on time domain and frequency domain characteristics, and the specific method is as follows:

[0026] Cutting force status evaluation index, comparing the real-time cutting force average with the standard working condition average, Where F is the three-dimensional cutting force measured in real time, and F x 、F y 、F z are the cutting forces on the x, y, and z axes, i.e., the three-dimensional cutting forces. F′ is the theoretically predicted cutting force, and F′=r1·a p ·f z , r1 is the material cutting coefficient stored in the database, a p is the cutting depth, f z is the feed per tooth.

[0027] It should be noted that the above is a time-domain analysis of cutting forces. Frequency-domain analysis can also be used to identify potential cutting instabilities in advance and to supplement the limitations of time-domain analysis (e.g., short-term high-frequency vibrations may not significantly affect the mean, but will accelerate tool wear).

[0028] Cutting force state frequency domain characteristic evaluation, using instruments to detect the E1000 ratio of the cutting tool, E1000 is the ratio of the energy in the 1000Hz frequency band to the total energy. 1000Hz is an empirical frequency band, usually corresponding to the characteristic frequency of tool wear or workpiece vibration. It can be adjusted according to actual conditions in different processing scenarios and materials. max is the threshold of energy ratio of the empirical frequency band, E1000≥E max When the energy proportion of this frequency band exceeds the maximum threshold, it indicates that there is high-frequency vibration in the cutting system, which may be caused by tool wear, unreasonable cutting parameters or insufficient rigidity of the workpiece. In the preliminary experiment of the technical report, it was determined that 1000Hz is the industry standard empirical frequency band, which corresponds to the characteristic frequency of tool wear or workpiece vibration. When the energy proportion of this frequency band exceeds 30%, it indicates that there is strong high-frequency vibration in the cutting process, such as tool wear and bluntness, and the workpiece is too hard, resulting in increased friction. At this time, the cutting state may be unstable and needs to be adjusted.

[0029] In specific embodiments of the present application, the tool wear evaluation model is constructed, in particular, the tool wear degree is evaluated by combining the cutting force change and the vibration characteristics, and the specific steps are as follows:

[0030] According to the relevant data in the cutting process of the numerical control machine tool, a tool wear evaluation model is constructed to obtain a tool wear index VB=r2·∫(F x ·v c )dt, wherein r2 is a tool wear coefficient stored in a database, v c is a cutting linear speed.

[0031] In specific embodiments of the present application, the processing quality evaluation model is constructed, and the specific steps are as follows:

[0032] B1. According to the relevant data in the cutting process of the numerical control machine tool, a cutting tool surface roughness index R is obtained, wherein C is a material constant stored in a database, f z is a feed per tooth, and r ε is a tool tip arc radius;

[0033] B2. The sample size deviation processed by the numerical control machine tool is calculated, ΔD=α·F y , wherein α is a machine tool stiffness coefficient;

[0034] B3. Based on the surface roughness index and the sample size deviation, the processing quality is evaluated to obtain a processing quality index S q =h1·R a +h1·ΔD, h1 and h2 are weight coefficients, and h1+h2=1.

[0035] It should be noted that the tool wear index is consistent with the positive correlation between the "tool flank wear VB" and the "cutting force increase and vibration intensification" in the technical report. The technical report verifies through experiments that when VB≥0.3mm, the average cutting force increases by more than 15%, and the tool needs to be replaced. The parameter fitting in the sample size deviation is based on the "cutting force influence on workpiece deformation experiment" in the technical report, which indicates that the larger the cutting force, the higher the surface roughness, and the larger the size error, and the thin-walled part processing experiment is verified.

[0036] In specific embodiments of the present application, the temperature change in the cutting process of the numerical control machine tool is monitored, which specifically includes: by reasonably arranging temperature sensors at key positions, the tool temperature T and the temperature change ΔT in the cutting process can be accurately obtained; through continuous monitoring and analysis of the above temperature related data, the thermal state in the cutting process can be comprehensively and accurately mastered, thereby providing detailed and reliable data support for intelligent control of the cutting force.

[0037] It should be noted that the tool generates a large amount of heat by friction with the workpiece during cutting, and high temperature can accelerate tool wear, reduce hardness, and even cause tool collapse. Real-time monitoring of tool temperature can reflect the cutting state in time; if the temperature of the hard alloy tool exceeds 600 DEG C, the wear rate will increase significantly, and the temperature needs to be controlled by adjusting the flow of cooling liquid or optimizing the cutting parameters; During the cutting process, the bearings, servo motors, ball screws and other moving parts of the spindle generate heat due to friction, and if the temperature is too high, it will cause lubrication failure and mechanical precision to decrease; for example, if the temperature of the spindle bearing exceeds 70 DEG C, it may cause vibration to increase, which needs to be monitored in real time by embedding a temperature sensor; and the change of the feed per tooth will affect the friction between the tool and the workpiece, and then cause the temperature to change, the feed increases, and the cutting heat increases, and the temperature rises; the flow of cooling liquid plays a key role in heat dissipation, and sufficient flow can effectively reduce the temperature, and insufficient flow may cause the temperature to rise; the change of the spindle speed will change the cutting speed, affect the generation and discharge of cutting heat, and high speed is easy to cause the temperature to rise sharply; therefore, real-time monitoring of the temperature, according to the change of the temperature, the feed, the flow of cooling liquid and the spindle speed are adjusted cooperatively to form a closed loop control, which can ensure that the cutting process is carried out in a suitable thermal state, and the machining precision and tool life are guaranteed.

[0038] S3. Tool and personnel association monitoring, relying on data analysis technology, real-time monitoring of tool state, combined with operation habit and skill level data of operating personnel, identifying operation behavior specification, associating tool state and personnel operation, and ensuring stable cutting process.

[0039] In specific embodiments of the present application, the operation habit and skill level data of the operating personnel are combined to identify the operation behavior specification, associate the tool state and the personnel operation, and ensure the stability of the cutting process, which specifically includes:

[0040] evaluating tool abnormal probability, wherein P y is the tool abnormal probability, VB max is the maximum threshold of the tool wear index stored in the database, R o is the feed overshoot rate (the core index of personnel operation specification), R' o is the feed overshoot rate threshold, and min is the minimum value function.

[0041] S4. Graded regulation and response: realizing rapid cutting force state judgment and response through data analysis, setting a multi-level regulation trigger mechanism for the system, and adjusting the parameters and operation prompts according to different cutting force state levels.

[0042] In specific embodiments of the present application, the multi-level regulation trigger mechanism is set for the system, which specifically includes;

[0043] According to the evaluation results, the system sets up a three-level control trigger mechanism, in which the first level prevents personal injury, the second level prevents damage to tools, machine tools and other equipment, and the third level reduces adverse conditions such as reduced processing quality; by evaluating the cutting force state level, the system triggers multi-level control and performs multi-level control on the dynamically configurable Where ∨ is the logical OR symbol, F is the cutting force state level, and the following thresholds are stored in the database including θ f 1 is the low risk threshold of cutting force, θ f 2 is the high risk threshold of cutting force, θ V B1 is the tool low wear threshold, θ V B2 is the tool high wear threshold, θ T1 is the low danger threshold of temperature change, θ T2 is the high-risk threshold of temperature change, θ P is the tool abnormality probability, T limit is the tool temperature melting threshold.

[0044] It should be noted that according to the "Study on the Safety Threshold of Cutting Force Coefficient Kf" in the technical report, it was determined through experiments in CNC machine tools that: K f ≤0.8 is a safe state, K f >1.0 has the risk of overload, so the cutting force threshold θ is recommended f1 =0.8,θ f2 =1.0.

[0045] In a specific embodiment of the present invention, the corresponding parameter adjustment and operation prompt according to different cutting force state levels specifically include:

[0046] When F=1, it means that the cutting force is abnormal, the tool wear warning or the temperature rise is too fast; the feed rate needs to be fine-tuned, and the feed rate per tooth f is reduced. z新 =f z ×(1-η f ), η f is the feed reduction rate per tooth, while increasing the coolant flow Q 新 =Q×(1+δ Q ), δ Q Increase the coolant flow rate to reduce cutting forces, reduce tool wear and control temperature rise;

[0047] When F=2, it indicates cutting force danger, that is, the cutting force coefficient is greater than the cutting force danger threshold, wear is serious, vibration exceeds the standard, and the overall risk is high; the spindle speed n needs to be reduced. 新 =n×(1-η n ), η n The spindle speed reduction rate, and the tool change time is calculated based on the tool flank wear width where K tThe reference time length coefficient K is a reference time length coefficient of the tool;

[0048] When F=3, it represents that the axial force is out of limit, the temperature is melted, and the human accident is high risk, the emergency shutdown is triggered immediately after the triggering, and the corresponding alarm code is given according to different triggering reasons; if the axial force F is out of limit, the alarm code is E01, if the temperature T is out of limit, the alarm code is E02, and if the abnormal index P is out of limit, the alarm code is E03. z The limit triggering alarm code is E01, if the temperature T is out of limit, the alarm code is E02, and if the abnormal index P is out of limit, the alarm code is E03. y The high risk triggering alarm code is E03, and the alarm position is displayed at the same time.

[0049] It should be noted that the parameter adjustment and operation prompt "first level early warning fine feeding amount, increase cooling liquid flow" are consistent with the process suggestions "reduce the cutting load by reducing the feeding amount" and "improve the cutting heat by cooling liquid" in the technical report; "second level early warning reduces the spindle speed, calculates the tool changing time", corresponding to the report "linear relationship between spindle speed and cutting force" and "tool life database", the reference time length coefficient K of the tool changing t can be adjusted according to the tool changing efficiency of the production line,

[0050] It should be further pointed out that the present application also includes a database for storing reference original data, including the cutting force predicted by the cutting tool theory, the material cutting coefficient, the experience frequency band energy proportion threshold value, the tool wear coefficient, the material constant, the tool wear failure threshold value, the surface roughness qualified value, the maximum threshold value of the tool wear index, the feeding overshoot rate threshold value, the low risk threshold value of the cutting force, the high risk threshold value of the cutting force, the low wear threshold value of the tool, the high wear threshold value of the tool, the low danger threshold value of the temperature change, the high danger threshold value of the temperature change, the tool abnormal probability and the tool temperature melting threshold value.

[0051] Referring to Figure 2 The second aspect of the present application provides a numerical control machine tool cutting force intelligent regulation and control system based on data analysis, which comprises: a data acquisition module, which acquires relevant data in the cutting process of the numerical control machine tool by using a plurality of sensors;

[0052] A state evaluation model construction module, based on the relevant data in the cutting process of the numerical control machine tool, constructs a cutting force state evaluation model, a tool wear evaluation model and a machining quality evaluation model, and monitors the temperature change in the cutting process of the numerical control machine tool;

[0053] A tool and personnel correlation monitoring module, relying on data analysis technology, real-time monitoring the tool state, and combining the operation habit and skill level data of the operator, identifying the operation behavior specification, correlating the tool state and the personnel operation, and ensuring the stability of the cutting process;

[0054] The hierarchical regulation and response module realizes the quick cutting force state judgment and response through data analysis, obtains different cutting force state grades, and adjusts parameters and gives operation prompts according to different cutting force state grades.

Claims

1. A method for intelligently controlling the cutting force of a CNC machine tool based on data analysis, characterized in that: include: S1. Data acquisition: using a variety of sensors to collect relevant data during the CNC machine tool cutting process; S2. State assessment model construction: Based on relevant data from the CNC machine tool cutting process, a cutting force state assessment model, a tool wear assessment model, and a machining quality assessment model are constructed, and temperature changes during the CNC machine tool cutting process are monitored; S3. Tool and personnel correlation monitoring: Relying on data analysis technology, tool status is monitored in real time. In combination with operator habits and skill level data, it identifies operating behavior norms, correlates tool status with operator operation, and ensures a stable cutting process. S4. Gradual control and response: Through data analysis, rapid cutting force state judgment and response are achieved, different cutting force state levels are obtained, and corresponding parameter adjustments and operation prompts are made according to different cutting force state levels.

2. The method and system for intelligently controlling cutting force of a CNC machine tool based on data analysis according to claim 1, characterized in that: The collecting of relevant data during the CNC machine tool cutting process specifically includes: Collect relevant data of the CNC machine tool cutting process and personnel status data. The relevant data of the CNC machine tool cutting process include the three-dimensional cutting force, cutting depth, feed per tooth, cutting linear speed, and tool tip arc radius of the cutting tool; the personnel status data includes the feed overshoot rate; because the dimensions of the data in the calculation are different, the data needs to be standardized, and linear transformation is performed through the mean and standard deviation of the data to eliminate the dimensional effect.

3. The method and system for intelligently controlling cutting force of a CNC machine tool based on data analysis according to claim 2, characterized in that: The cutting force state evaluation model is constructed to evaluate the cutting force stability based on the time domain and frequency domain characteristics. The specific method is as follows: Cutting force status evaluation index, comparing the real-time three-way cutting force resultant and the standard working condition cutting force, where K f is the cutting force state evaluation index, F is the three-dimensional cutting force resultant measured in real time, and F x 、F y 、F z are the cutting forces on the x, y, and z axes, i.e., the three-dimensional cutting forces. F′ is the theoretically predicted cutting force, and F′=r1·a p ·f z , r1 is the material cutting coefficient stored in the database, a p is the cutting depth, f z is the feed per tooth.

4. The method and system for intelligently controlling cutting force of a CNC machine tool based on data analysis according to claim 2, characterized in that: The tool wear evaluation model is constructed by combining cutting force changes and vibration characteristics to evaluate the tool wear index. The specific steps are as follows: According to the relevant data of the CNC machine tool cutting process, the tool wear evaluation model is constructed to obtain the tool wear index, VB = r2·∫(F x ·v c )dt, where r2 is the tool wear coefficient stored in the database, v c is the cutting speed.

5. The method and system for intelligently controlling cutting force of a CNC machine tool based on data analysis according to claim 4, characterized in that: The specific steps of constructing the processing quality assessment model are as follows: B1. Based on the relevant data of the CNC machine tool cutting process, the surface roughness index of the cutting tool is obtained. Where C is the material constant stored in the database, f z is the feed per tooth, r ε is the tool tip arc radius; B2. Calculate the dimensional deviation of the sample processed by CNC machine tools, ΔD = α·F y , where α is the machine tool stiffness coefficient; B3. Based on the surface roughness index and sample size deviation, the processing quality is evaluated to obtain the processing quality index S q =h1·R a +h1·ΔD, h1 and h2 are weight coefficients, and h1+h2=1.

6. The method and system for intelligently controlling cutting force of a CNC machine tool based on data analysis according to claim 4, characterized in that: The monitoring of temperature changes during the cutting process of the CNC machine tool specifically includes: By rationally placing temperature sensors at key locations, the tool temperature T and the temperature change ΔT during the cutting process can be accurately obtained. By continuously monitoring and analyzing the above temperature-related data, the thermal state of the cutting process can be fully and accurately understood, thereby providing detailed and reliable data support for the intelligent control of cutting force.

7. The method and system for intelligently controlling cutting force of a CNC machine tool based on data analysis according to claim 4, characterized in that: The method of combining the operator's operating habits and skill level data, identifying the operating behavior specifications, and associating the tool status with the operator's operation specifically includes: Evaluate the probability of tool abnormality, Among them, P y is the tool abnormality probability, VB max is the maximum threshold of tool wear index stored in the database, R o is the feed overshoot rate, is the core indicator of personnel operation standardization, R′ o is the feed overshoot rate threshold stored in the database, and min is the minimum value function.

8. The method and system for intelligently controlling cutting force of a CNC machine tool based on data analysis according to claim 4, characterized in that: The method of realizing rapid cutting force state judgment and response through data analysis to obtain different cutting force state levels specifically includes: According to the evaluation results, the system sets up a three-level control trigger mechanism, in which the first level prevents personal injury, the second level prevents damage to tools, machine tools and other equipment, and the third level reduces adverse conditions such as reduced processing quality; by evaluating the cutting force state level, the system triggers multi-level control and performs multi-level control on the dynamically configurable Where ∨ is the logical OR symbol, F is the cutting force state level, and the following thresholds are stored in the database including θ f 1 is the low risk threshold of cutting force, θ f 2 is the high risk threshold of cutting force, θ V B1 is the tool low wear threshold, θ V B2 is the tool high wear threshold, θ T1 is the low danger threshold of temperature change, θ T2 is the high-risk threshold of temperature change, θ P is the tool abnormality probability, T limit is the tool temperature melting threshold.

9. The method and system for intelligently controlling cutting force of a CNC machine tool based on data analysis according to claim 4, characterized in that: The parameter adjustment and operation prompts according to different cutting force state levels specifically include: When F=1, it means that the cutting force is abnormal, the tool wear warning or the temperature rise is too fast; the feed rate needs to be fine-tuned, and the feed rate per tooth f is reduced. z新 =f z ×(1-η f ), η f is the feed reduction rate per tooth, while increasing the coolant flow Q 新 =Q×(1+δ Q ), δ Q Increase the coolant flow rate to reduce cutting forces, reduce tool wear and control temperature rise; When F=2, it indicates cutting force danger, that is, the cutting force coefficient is greater than the cutting force danger threshold, wear is serious, vibration exceeds the standard, and the overall risk is high; the spindle speed n needs to be reduced. 新 =n×(1-η n ), η n The spindle speed reduction rate, and the tool change time is calculated based on the tool flank wear width where K t is the benchmark duration coefficient; When F=3, it means the axial force exceeds the limit, the temperature melts, and the risk of man-made accidents is high. After the trigger, the emergency shutdown will be immediately carried out, and the corresponding alarm code will be given according to the different triggering reasons. If the axial force F z If the alarm is triggered due to temperature T exceeding the limit, the alarm code is E01. If the alarm is triggered due to abnormal index P y High risk trigger, the alarm code is E03, and the alarm location is displayed at the same time.

10. A system for executing the method for intelligently controlling cutting force of a CNC machine tool based on data analysis according to any one of claims 1 to 9, comprising: The data acquisition module uses a variety of sensors to collect relevant data during the cutting process of CNC machine tools; The state assessment model construction module builds cutting force state assessment models, tool wear assessment models, and machining quality assessment models based on relevant data during the CNC machine tool cutting process, and monitors temperature changes during the CNC machine tool cutting process; The tool and personnel association monitoring module relies on data analysis technology to monitor the tool status in real time. At the same time, it combines the operator's operating habits and skill level data to identify operating behavior norms, associate tool status with personnel operations, and ensure the stability of the cutting process. The hierarchical control and response module can quickly judge and respond to the cutting force status through data analysis, obtain different cutting force status levels, and make corresponding parameter adjustments and operation prompts according to different cutting force status levels.

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