An electrical control system for CNC machine tools based on artificial intelligence

Abstract

The present invention relates to the field of CNC machine tool control technology, and in particular to an artificial intelligence-based CNC machine tool electrical control system, comprising: a machine tool data entry module for entering processing component information and CNC machine tool parameters, an operation data acquisition module for acquiring CNC machine tool operation data and processing component images within a monitoring period, a mode analysis module for grading the difficulty level of processing components and analyzing the processing mode of the CNC machine tool, a load monitoring module for analyzing the operating status of the equipment and the load status of the equipment, a component monitoring module for analyzing the processing status of the processing components, a safety warning module for alarming the processing process, and an electrical control module for controlling the working process of the CNC machine tool in the next monitoring period. The present invention effectively improves the safety of the CNC machine tool processing process and the electrical control efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of numerical control machine tool control, and in particular to an artificial intelligence-based numerical control machine tool electrical control system. Background Art

[0002] As the manufacturing industry develops towards intelligence and automation, CNC machine tools, as important equipment for modern mechanical processing, have a direct impact on the processing quality and production efficiency of products. Traditional CNC machine tool electrical control systems mainly rely on preset parameters and fixed control strategies, which are difficult to adapt to complex and changing processing environments and personalized needs. In addition, traditional systems also have obvious deficiencies in fault prediction and diagnosis, resulting in high maintenance costs and affecting production continuity.

[0003] Chinese patent publication number CN114442555A discloses an electrical control system for a CNC machine tool, comprising: an acquisition module for real-time acquisition of operating parameters and environmental parameters of an actuator, wherein the operating parameters include the operating time, operating speed and operating temperature of the actuator and the friction between the actuator end and the processed parts; an analysis module for performing positioning error analysis on the actuator according to the operating parameters and environmental parameters, which is connected to the acquisition module; a judgment module for performing operating state judgment according to the positioning error analysis result, which is connected to the analysis module; an adjustment module for adjusting the operating state of the actuator according to the operating state judgment result, which is connected to the judgment module; a verification module for verifying the positioning error according to the dimensional parameters of the processed parts after adjustment, which is connected to the adjustment module; it can be seen that the invention only analyzes the operating state of the CNC machine tool and the error of the processed parts, and does not analyze the damaged state of the machine tool and parts during the processing of the CNC machine tool. The machine tool and parts may be damaged during the processing, and there are problems of low safety and low processing quality during the processing of the CNC machine tool. Summary of the invention

[0004] The object of the present invention is to provide an electrical control system for CNC machine tools based on artificial intelligence to solve at least one of the problems existing in the prior art.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] Machine tool data entry module, used to enter processing component information and CNC machine tool parameters;

[0007] An operation data acquisition module is used to collect the operation data of the CNC machine tool and the image of the processed parts within the monitoring period;

[0008] A mode analysis module is used to classify the difficulty level of the processing parts according to the processing part information, and analyze the processing mode of the CNC machine tool according to the classification results and the CNC machine tool parameters;

[0009] The load monitoring module is used to analyze the operation status of the equipment according to the CNC machine tool operation data and CNC machine tool parameters within the monitoring period, and analyze the equipment load status according to the analysis results and the CNC machine tool processing mode analysis results;

[0010] A component monitoring module is used to analyze the processing status of the processing component based on the image of the processing component within the monitoring period;

[0011] Safety warning module, used to alarm the processing process according to the analysis results of equipment load status and processing status of processing parts;

[0012] The electrical control module is used to control the working process of the CNC machine tool in the next monitoring cycle according to the alarm result of the machining process in the monitoring cycle.

[0013] Further, the pattern analysis module includes a component property analysis unit, which is used to analyze the physical properties of the processed component according to the processed component information, and to grade the difficulty of the processed component according to the analysis result;

[0014] The component property analysis unit calculates a processing difficulty coefficient α of a processing component, and compares the processing difficulty coefficient α of the processing component with various preset difficulty coefficients to determine a difficulty level of the processing component, wherein the difficulty levels of the processing component include easy processing, normal processing, and difficult processing.

[0015] Furthermore, the pattern analysis module is also provided with a pattern analysis unit, which is used to determine the processing mode of the CNC machine tool according to the difficulty level classification results of the processing parts and the CNC machine tool parameters. The processing modes of the CNC machine tool include a three-level processing mode, a two-level processing mode and a one-level processing mode, and the processing parameters of each mode are set.

[0016] Furthermore, the load monitoring module is provided with an equipment monitoring unit, and the equipment monitoring unit is used to analyze the operation status of the equipment according to the CNC airport operation data within the monitoring period;

[0017] The equipment monitoring unit calculates the equipment status index γ and compares the equipment status index γ with a preset equipment status index Y to determine the operating status of the equipment within the monitoring period. The operating status of the equipment includes normal and abnormal.

[0018] Furthermore, the load monitoring module is also provided with a load analysis unit, which is used to analyze the equipment load status according to the CNC machine tool operation data, the CNC machine tool processing mode and the equipment operation status analysis results within the monitoring period. The analysis results of the equipment load status include low load, normal load and high load.

[0019] Furthermore, the load monitoring module is also provided with an aging analysis unit, which is used to calculate the equipment aging degree β, and compare the equipment aging degree β with the preset aging threshold B to determine the aging degree of the equipment within the monitoring period. The aging analysis result of the equipment includes normal and abnormal, and when the aging analysis result of the equipment is abnormal, the second preset equipment load index is adjusted to H2'.

[0020] Furthermore, the load monitoring module is also provided with a cooling monitoring unit, and the cooling monitoring unit is used to calculate the equivalent temperature t of the cutting area of ​​the machine tool;

[0021] The cooling monitoring unit analyzes the cooling state of the CNC machine tool according to the calculation result t of the equivalent temperature of the cutting area of ​​the machine tool and the coolant flow rate of the CNC machine tool to determine the cooling state of the CNC machine tool within the monitoring period. The cooling state analysis result of the CNC machine tool within the monitoring period includes normal and abnormal. When the cooling state analysis result of the CNC machine tool within the monitoring period is abnormal, the preset aging threshold is optimized to B'.

[0022] Furthermore, the component monitoring module is further provided with a component monitoring unit, and the component monitoring unit is used to analyze the processing state of the processing component according to the image of the processing component within the monitoring period;

[0023] The component monitoring unit compares the surface roughness σ of the processing part of the processing component within the monitoring period with a preset roughness threshold K to determine the processing state of the processing component. The processing state of the processing component includes normal and abnormal.

[0024] Further, the safety warning module alarms the processing process according to the analysis results of the equipment load state and the processing state of the processing component: if the equipment load state is a low load state and the processing state of the processing component is normal, the safety warning module determines that the processing process is normal within the monitoring period and does not alarm; if the equipment load state is a normal load and the processing state of the processing component is normal, the safety warning module determines that the processing process is normal within the monitoring period and does not alarm; if the equipment load state is a high load and the processing state of the processing component is normal, the safety warning module determines that the equipment state is abnormal within the monitoring period and sends an equipment maintenance alarm to the user; if the equipment load state is a low load state and the processing state of the processing component is abnormal, the safety warning module determines that the processing process within the monitoring period is an adjustable equipment abnormality and sends a low-quality processing alarm to the user; if the equipment load state is a normal load and the processing state of the processing component is abnormal, the safety warning module determines that the processing process within the monitoring period is a pattern analysis abnormality and sends a pattern error alarm to the user; if the equipment load state is a high load and the processing state of the processing component is abnormal, the safety warning module determines that the processing process within the monitoring period is an equipment abnormality and suspends the processing process of the processing component.

[0025] Furthermore, the electrical control module is used to control the working process of the CNC machine tool in the next monitoring cycle according to the alarm result of the processing process: if the alarm result is a low-quality processing alarm, the electrical control module will move up the processing mode of the CNC machine tool in the next monitoring cycle; if the alarm result is an equipment maintenance alarm, the electrical control module will adjust the processing parameters of each mode in the next monitoring cycle to ri', di' and gi'; if the alarm result is a mode error alarm, the electrical control module will move down the processing mode of the CNC machine tool in the next monitoring cycle.

[0026] Compared with the prior art, the beneficial effects of the present invention are that the machine tool data entry module acquires the CNC machine tool parameters and the processing component information, thereby improving the accuracy and completeness of the information acquisition; the operation data acquisition module acquires the real-time information required by the system, thereby improving the completeness of the data acquisition; the mode analysis module grades the difficulty levels of the processing components, thereby improving the accuracy of the processing mode analysis; the load monitoring module analyzes the operation status of the equipment, thereby improving the accuracy of the equipment load status analysis; the component monitoring module analyzes the processing status of the processing components, thereby improving the accuracy of the processing quality analysis of the processing components; the safety warning module alarms the processing process, thereby improving the safety of the CNC machine tool processing process; the electrical control module controls the working process of the CNC machine tool in the next monitoring cycle, thereby improving the safety and processing quality of the CNC machine tool processing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 This is a schematic diagram of the structure of the electrical control system of a CNC machine tool based on artificial intelligence in this embodiment.

[0029] Figure 2 Schematic diagram of the structure of the mode analysis module of this embodiment.

[0030] Figure 3 It is a structural diagram of the load monitoring module of this embodiment.

[0031] Figure 4 Schematic diagram of the structure of the component monitoring module of this embodiment. DETAILED DESCRIPTION

[0032] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with preferred embodiments and accompanying drawings. Similar components in the accompanying drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content specifically described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present invention.

[0033] It should be noted that, although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0034] Specifically, the artificial intelligence-based CNC machine tool electrical control system described in this embodiment is installed in the CNC machine tool controller, which is used for electrical intelligent control of the CNC machine tool; the CNC machine tool described in this embodiment is specifically a CNC lathe with a mid-range CNC system.

[0035] See also Figure 1 As shown, it is a structural schematic diagram of the electrical control system of a CNC machine tool based on artificial intelligence in this embodiment, including a machine tool data entry module, which is used to enter processing component information and CNC machine tool parameters.

[0036] Specifically, the processing component information includes the Brinell hardness of the processing component and the impact toughness value of the processing component; the CNC machine tool parameters include the machine tool test feed rate, the machine tool test cutting area, the machine tool test coolant flow, the CNC machine tool motor operating frequency, and the CNC machine tool normal vibration amplitude; this embodiment does not specifically limit the method for obtaining the processing component information and the CNC machine tool parameters, and technical personnel in this field can set them freely, as long as the requirements for obtaining the processing component information and the CNC machine tool parameters are met. In this embodiment, the processing component information and the CNC machine tool parameters are all entered by the user.

[0037] Please continue reading Figure 1 As shown, the system also includes an operation data acquisition module, which collects the CNC machine tool operation data and the processed component image within the monitoring period; the CNC machine tool operation data includes the actual coolant flow of the CNC machine tool, the actual cutting area of ​​the CNC machine tool, the actual feed amount of the CNC machine tool, the Brinell hardness of the standard material, the standard impact toughness value, the vibration amplitude of the CNC machine tool, and the vibration frequency of the CNC machine tool; the processed component image is specifically a grayscale image.

[0038] Specifically, this embodiment does not make any specific limitation on the method for collecting the image of the processing part. Technical personnel in this field can set it freely, and it is only necessary to meet the method for collecting the image of the processing part. In this embodiment, when the processing part stops rotating, the processing part is photographed by a camera above the part to collect the image of the processing part; the price component image described in this embodiment is specifically a grayscale image with a resolution of 300PPI; this embodiment does not make any specific limitation on the value of the duration of the monitoring cycle, and technical personnel in this field can set it freely, and it is only necessary to meet the value requirement of the duration of the monitoring cycle. In this embodiment, the duration of the monitoring cycle is specifically 1 minute; at the same time, the method for obtaining the operation data of the CNC machine tool in this embodiment is to obtain it by the monitoring sensor inside the CNC machine tool.

[0039] Please continue reading Figure 1 As shown, the system further comprises a pattern analysis module, which is connected to the machine tool data entry module, and is used for analyzing the processing mode of the CNC machine tool according to the processing component information and the CNC machine tool parameters.

[0040] See also Figure 2 As shown, it is a schematic diagram of the structure of the mode analysis module of this embodiment, the mode analysis module includes a component property analysis unit, the component property analysis unit is used to analyze the physical properties of the processing component according to the processing component information, and to classify the difficulty level of the processing component according to the analysis result, so as to classify the processing difficulty, and then determine the appropriate processing mode;

[0041] The component property analysis unit calculates the processing difficulty coefficient α of the processing component according to the processing component information, and sets α=ln[(hb-HB) / HB+(ak-AK) / AK];

[0042] Among them, hb is the Brinell hardness of the machined part, HB is the Brinell hardness of the standard material, ak is the impact toughness value of the machined part, and AK is the standard impact toughness value;

[0043] The component property analysis unit compares the processing difficulty coefficient α of the processing component with each preset difficulty coefficient, and analyzes the physical properties of the processing component according to the comparison result: if α<A1, the component property analysis unit determines that the difficulty level of the processing component is easy to process; if A1≤α<A2, the component property analysis unit determines that the difficulty level of the processing component is normal processing; if α≥A2, the component property analysis unit determines that the difficulty level of the processing component is difficult to process;

[0044] Wherein, A1 is a first preset difficulty index, A2 is a second preset difficulty index, and A1<A2; the physical properties of the processed parts are analyzed by the component property analysis unit, thereby improving the accuracy of the processing mode analysis.

[0045] Specifically, this embodiment does not impose specific limitations on the values ​​of the first preset difficulty index A1 and the second preset difficulty index A2. Technical personnel in this field can set them freely as long as the value requirements of the first preset difficulty index A1 and the second preset difficulty index A2 are met. For example, the first preset difficulty index A1 can be set to 1, and the second preset difficulty index A2 can be set to 1.4. At the same time, the values ​​of the Brinell hardness HB and the standard impact toughness value AK of the standard material in this embodiment are consistent with the relevant properties of the tool head of the CNC lathe.

[0046] See also Figure 2 As shown, the pattern analysis module is further provided with a pattern analysis unit, which is connected to the component property analysis unit, and the pattern analysis unit analyzes the processing mode of the CNC machine tool according to the difficulty level classification result of the processing component and the CNC machine tool parameters: if the difficulty level of the processing component is easy processing, the pattern analysis unit sets the processing mode of the CNC machine tool to the third-level processing mode, and sets the third processing parameters; if the difficulty level of the processing component is normal processing, the pattern analysis unit sets the processing mode of the CNC machine tool to the second-level processing mode, and sets the second processing parameters; if the difficulty level of the processing component is difficult processing, the pattern analysis unit sets the processing mode of the CNC machine tool to the first-level processing mode, and sets the first processing parameters;

[0047] The setting process of the first processing parameter is as follows:

[0048] r1=exp[(A1-α) / A1]×r;

[0049] d1=exp[(A1-α) / A1]×d;

[0050] g1=exp[(α-A1) / A1]×g;

[0051] The setting process of the second processing parameter is as follows:

[0052] r2=r;

[0053] d2=d;

[0054] g2=g;

[0055] The setting process of the third processing parameter is as follows:

[0056] r3=exp[(A2-α) / A2]×r;

[0057] d3=exp[(A2-α) / A2]×d;

[0058] g3=exp[(α-A2) / A2]×g;

[0059] Among them, r1 is the feed rate of the CNC machine tool in the first-level processing mode, d1 is the cutting area of ​​the CNC machine tool in the first-level processing mode, g1 is the coolant flow rate of the CNC machine tool in the first-level processing mode, r is the machine tool test feed rate, d is the machine tool test cutting area, g is the machine tool test coolant flow rate, r2 is the feed rate of the CNC machine tool in the second-level processing mode, d2 is the cutting area of ​​the CNC machine tool in the second-level processing mode, g2 is the coolant flow rate of the CNC machine tool in the second-level processing mode, r3 is the feed rate of the CNC machine tool in the third-level processing mode, d3 is the cutting area of ​​the CNC machine tool in the third-level processing mode, and g3 is the coolant flow rate of the CNC machine tool in the third-level processing mode.

[0060] Please continue reading Figure 1 As shown, the system also includes a load monitoring module, which is connected to the mode analysis module and the operation data acquisition module. The mode analysis module is used to analyze the processing mode of the CNC machine tool according to the processing component information and the CNC machine tool parameters.

[0061] See also Figure 3 As shown, the load monitoring module is provided with an equipment monitoring unit, and the equipment monitoring unit is used to analyze the operation status of the equipment according to the CNC airport operation data within the monitoring period, thereby improving the accuracy of the equipment operation status analysis;

[0062] The equipment monitoring unit calculates the equipment state index γ, and sets γ=exp{(zZ) / Z+(vV) / V}; wherein z is the vibration amplitude of the CNC machine tool during the monitoring period, Z is the normal vibration amplitude of the CNC machine tool, v is the vibration frequency of the CNC machine tool during the monitoring period, and V is the operating frequency of the CNC machine tool motor;

[0063] The equipment monitoring unit compares the equipment status index γ with the preset equipment status index Y to determine the operating status of the equipment within the monitoring period. If γ does not exceed the preset equipment status index Y, the equipment monitoring unit determines that the operating status of the equipment is normal; if γ exceeds the preset equipment status index Y, the equipment monitoring unit determines that the operating status of the equipment is abnormal. The equipment operating status is analyzed by the equipment monitoring unit, thereby improving the accuracy of alarming the processing process.

[0064] Specifically, this embodiment does not impose any specific limitation on the value of the preset device state index Y, and those skilled in the art can freely set it as long as the value requirement of the preset device state index Y is met. For example, the preset device state index Y can be set to 1.5.

[0065] Please continue reading Figure 3 As shown, the load monitoring module is also provided with a load analysis unit, which analyzes the load status of the equipment according to the CNC machine operation data, the processing mode of the CNC machine tool and the analysis results of the operation status of the equipment during the monitoring period: if the operation status of the equipment is normal and a1×(R-ri) / ri+a2×(D-di) / di+a3×(G-gi) / gi<H, the load analysis unit determines that the load status of the equipment during the monitoring period is low load; if the operation status of the equipment is normal and a1×(R-ri) / ri+a2×(D-di) / di+a3×(G-gi) / gi<H, the load analysis unit determines that the load status of the equipment during the monitoring period is low load; if the operation status of the equipment is normal and a1×(R-ri) / ri+a2×(D-di) / di+a 3×(G-gi) / gi≥H, the load analysis unit determines that the load state of the equipment during the monitoring period is normal load; if the operating state of the equipment is abnormal and a1×(R-ri) / ri+a2×(D-di) / di+a3×(G-gi) / gi<H, the load analysis unit determines that the load state of the equipment during the monitoring period is normal load; if the operating state of the equipment is abnormal and a1×(R-ri) / ri+a2×(D-di) / di+a3×(G-gi) / gi≥H, the load analysis unit determines that the load state of the equipment during the monitoring period is high load;

[0066] Among them, H is the preset equipment load index, R is the actual feed amount of the CNC machine tool during the monitoring period, D is the actual cutting area of ​​the CNC machine tool during the monitoring period, G is the actual coolant flow rate of the CNC machine tool during the monitoring period, a1 is the feed amount error weight, a2 is the cutting area error weight, a3 is the coolant flow rate error weight, ri is the feed amount of the CNC machine tool in each processing mode, di is the cutting area of ​​the CNC machine tool in each processing mode, gi is the coolant flow rate of the CNC machine tool in each processing mode, i=1,2,3; the equipment processing load is analyzed by the load analysis unit, which improves the accuracy of the load state analysis of the equipment, thereby improving the accuracy of the alarm for the processing process.

[0067] Specifically, this embodiment does not impose any specific limitation on the value of the preset equipment load index H, and those skilled in the art can freely set it as long as the value requirement of the preset equipment load index H is met. For example, the preset equipment load index H can be set to 0.05.

[0068] Please continue reading Figure 3 As shown, the load monitoring module is further provided with an aging analysis unit, which is connected to the load analysis unit. The aging analysis unit analyzes the aging of the equipment according to the CNC machine tool parameters, and adjusts the analysis process of the equipment load state according to the equipment aging analysis result;

[0069] The aging analysis unit is used to calculate the aging degree β of the equipment, and β=ln(f / F); wherein f is the length of time the equipment has been put into use, and F is the design service life of the CNC machine tool;

[0070] The aging analysis unit adjusts the analysis process of the equipment load state according to the relationship between the equipment aging degree β and the preset aging threshold value B: if β does not exceed B, the aging analysis unit determines that the aging degree of the equipment within the monitoring period is normal and does not make any adjustments; if β exceeds B, the aging analysis unit determines that the aging degree of the equipment within the monitoring period is abnormal, and adjusts the analysis process of the equipment load state, adjusts the second preset equipment load index H2 to H2', and sets H2'=H2×[1-(β-B) / B]; the aging analysis unit adjusts the analysis process of the equipment load state according to the analysis result of the equipment aging, thereby improving the accuracy of the equipment load state analysis, and thereby improving the accuracy of the alarm for the processing process.

[0071] Specifically, this embodiment does not impose any specific limitation on the value of the preset aging threshold B, and those skilled in the art can freely set it as long as the value requirement of the preset aging threshold B is met. For example, the preset aging threshold B can be set to 0.5.

[0072] Please continue reading Figure 3As shown, the load monitoring module is further provided with a cooling monitoring unit, which is connected to the aging analysis unit. The cooling analysis unit is used to analyze the cooling state of the CNC machine tool within the monitoring period according to the operation data of the CNC machine tool within the monitoring period, and optimize the adjustment process of the equipment load state according to the analysis result;

[0073] The cooling monitoring unit is used to calculate the equivalent temperature t of the cutting area of ​​the machine tool, and set t=(m×D) / G;

[0074] Among them, m is the speed of the CNC machine tool;

[0075] The cooling monitoring unit analyzes the cooling state of the CNC machine tool according to the calculation result t of the equivalent temperature of the cutting area of ​​the machine tool and the coolant flow rate of the CNC machine tool, and optimizes the adjustment process of the equipment load state according to the analysis result: if t<G×μ, the cooling monitoring unit determines that the cooling state of the CNC machine tool within the monitoring period is normal and does not perform optimization; if t≥G / μ, the cooling monitoring unit determines that the cooling state of the CNC machine tool within the monitoring period is abnormal, and optimizes the preset aging threshold B to B', setting B'=B×exp{[t / [G×μ]-1};

[0076] Wherein, μ is the cooling efficiency of the coolant; the adjustment process of the equipment load state is optimized by the cooling monitoring unit, thereby improving the accuracy of the load state analysis of the equipment, and further improving the accuracy of the alarm for the processing process.

[0077] Specifically, the cooling efficiency μ of the coolant described in this embodiment is in units of ℃ / (mL×s); it can be understood that the unit of the equivalent temperature described in this embodiment is not a traditional temperature unit (℃ and ℉), which is numerically positively correlated with the temperature of the cutting area of ​​the machine tool, and is used to numerically refer to the temperature of the cutting area of ​​the machine tool. The unit of the rotation speed m of the CNC machine tool is revolutions per second, and the unit of the actual cutting area D of the CNC machine tool during the monitoring period is mm 2 , G is the actual coolant flow rate of the CNC machine tool during the monitoring period, and the unit is mL×s.

[0078] Please continue reading Figure 1 As shown, the system further includes a component monitoring module, which is connected to the operation data acquisition module and is used to analyze the processing status of the processing component according to the image of the processing component within a monitoring period.

[0079] See also Figure 4 As shown, the component monitoring module includes an image processing unit, and the image processing unit is used to obtain the surface roughness σ of the processing part of the processing component according to the image of the processing component within the monitoring period, thereby improving the accuracy of surface roughness extraction.

[0080] Specifically, this embodiment does not specifically limit the specific process of "obtaining the surface roughness of the processing part of the processing part from the image of the processing part within the monitoring period", and technical personnel in this field can freely set it. It is the existing technology in this field. This embodiment uses machine vision imaging method to optimize the grayscale distribution and area of ​​the collected image, and obtains the surface arithmetic mean deviation, and uses it as the surface roughness σ of the processing part of the processing part.

[0081] Please continue reading Figure 4 As shown, the component monitoring module is further provided with a component monitoring unit, which compares the surface roughness σ of the processing part of the processing component within the monitoring period with the preset roughness threshold K, and analyzes the processing state of the processing component according to the comparison result: if σ<K×(1+η), the component monitoring unit determines that the processing state of the processing component within the monitoring period is normal; if σ≥K×(1+η), the component monitoring unit determines that the processing state of the processing component within the monitoring period is abnormal;

[0082] Wherein, η is the offset coefficient; the processing state of the processing component within the monitoring period is analyzed by the component monitoring unit, thereby improving the accuracy of the processing quality monitoring of the processing component.

[0083] Specifically, this embodiment does not impose any specific limitation on the value of the preset roughness threshold K. Technical personnel in this field can set it freely as long as the value requirement of the preset roughness threshold K is met. For example, the preset roughness threshold K can be set to 10% of the required accuracy deviation of the processed part; at the same time, the value of the offset coefficient η in this embodiment is 5%.

[0084] See also Figure 1 As shown, the system also includes a safety warning module, which is connected to the component monitoring module and the load monitoring module. The safety warning module alarms the processing process according to the equipment load status analysis results and the processing status analysis results of the processing components: if the equipment load status is a low load status and the processing status of the processing components is normal, the safety warning module determines that the processing process is normal within the monitoring period and does not alarm; if the equipment load status is a normal load and the processing status of the processing components is normal, the safety warning module determines that the processing process is normal within the monitoring period and does not alarm; if the equipment load status is a high load and the processing status of the processing components is normal, the safety warning module determines that the equipment status is abnormal within the monitoring period and sends an equipment maintenance alarm to the user;

[0085] If the equipment load state is a low load state and the processing state of the processing component is abnormal, the safety warning module determines that the processing process within the monitoring period is an adjustable equipment abnormality, and sends a low-quality processing alarm to the user; if the equipment load state is a normal load and the processing state of the processing component is abnormal, the safety warning module determines that the processing process within the monitoring period is a pattern analysis abnormality, and sends a pattern error alarm to the user; if the equipment load state is a high load and the processing state of the processing component is abnormal, the safety warning module determines that the processing process within the monitoring period is an equipment abnormality, and suspends the processing process of the processing component; the safety warning module is used to alarm the processing process, thereby improving the safety of the CNC machine tool processing equipment and the quality of the processed parts.

[0086] Please continue reading Figure 1 As shown, the system also includes an electrical control module, which is connected to the safety warning module. The electrical control system is used to control the working process of the CNC machine tool in the next monitoring cycle according to the alarm result of the processing process: if the alarm result is a low-quality processing alarm, the electrical control module will move up the processing mode of the CNC machine tool in the next monitoring cycle; if the alarm result is an equipment maintenance alarm, the electrical control module will adjust the processing parameters of each mode in the next monitoring cycle to ri', di' and gi', and set: ri'=ri×(1-η); di'=di×(1-η); gi'=gi×(1-η); if the alarm result is a mode error alarm, the electrical control module will move down the processing mode of the CNC machine tool in the next monitoring cycle; the working process of the CNC machine tool in the next monitoring cycle is controlled by the electrical control module, thereby improving the safety and processing quality of the CNC machine tool processing process.

[0087] Specifically, the specific explanation of "moving up the processing mode of the CNC machine tool in the next monitoring cycle" in this embodiment is that if the processing mode of the CNC machine tool is set to the third-level processing mode, then the processing mode of the CNC machine tool in the next monitoring cycle is set to the second-level processing mode; if the processing mode of the CNC machine tool is set to the second-level processing mode, then the processing mode of the CNC machine tool in the next monitoring cycle is set to the first-level processing mode; if the processing mode of the CNC machine tool is set to the first-level processing mode, it remains unchanged; at the same time, the operation process of "moving down the processing mode of the CNC machine tool in the next monitoring cycle" is: if the processing mode of the CNC machine tool is set to the first-level processing mode, then the processing mode of the CNC machine tool in the next monitoring cycle is set to the second-level processing mode; if the processing mode of the CNC machine tool is set to the second-level processing mode, then the processing mode of the CNC machine tool in the next monitoring cycle is set to the third-level processing mode; if the processing mode of the CNC machine tool is set to the third-level processing mode, it remains unchanged.

[0088] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. An electrical control system for CNC machine tools based on artificial intelligence, characterized in that: include: Machine tool data entry module, used to enter processing component information and CNC machine tool parameters; An operation data acquisition module is used to collect the operation data of the CNC machine tool and the image of the processed parts within the monitoring period; A mode analysis module is used to classify the difficulty level of the processing parts according to the processing part information, and analyze the processing mode of the CNC machine tool according to the classification results and the CNC machine tool parameters; The load monitoring module is used to analyze the operation status of the equipment according to the CNC machine tool operation data and CNC machine tool parameters within the monitoring period, and analyze the equipment load status according to the analysis results and the CNC machine tool processing mode analysis results; A component monitoring module is used to analyze the processing status of the processing component based on the image of the processing component within the monitoring period; Safety warning module, used to alarm the processing process according to the analysis results of equipment load status and processing status of processing parts; An electrical control module is used to control the working process of the CNC machine tool in the next monitoring cycle according to the alarm result of the machining process in the monitoring cycle; The mode analysis module is provided with a mode analysis unit, and the mode analysis unit is used to determine the processing mode of the CNC machine tool according to the difficulty level classification result of the processing component and the CNC machine tool parameters. The processing modes of the CNC machine tool include a three-level processing mode, a two-level processing mode and a one-level processing mode, and set the processing parameters of each mode; the specific process is as follows: if the difficulty level of the processing component is easy processing, the mode analysis unit sets the processing mode of the CNC machine tool to the three-level processing mode, and sets the third processing parameter; if the difficulty level of the processing component is normal processing, the mode analysis unit sets the processing mode of the CNC machine tool to the two-level processing mode, and sets the second processing parameter; if the difficulty level of the processing component is difficult processing, the mode analysis unit sets the processing mode of the CNC machine tool to the one-level processing mode, and sets the first processing parameter; The setting process of the first processing parameter is as follows: r1=exp[(A1-α) / A1]×r; d1=exp[(A1-α) / A1]×d; g1=exp[(α-A1) / A1]×g; The setting process of the second processing parameter is as follows: r2=r； d2=d; g2=g; The setting process of the third processing parameter is as follows: r3=exp[(A2-α) / A2]×r; d3=exp[(A2-α) / A2]×d; g3=exp[(α-A2) / A2]×g; Among them, r1 is the feed rate of the CNC machine tool in the first-level processing mode, d1 is the cutting area of ​​the CNC machine tool in the first-level processing mode, g1 is the coolant flow rate of the CNC machine tool in the first-level processing mode, r is the machine tool test feed rate, d is the machine tool test cutting area, g is the machine tool test coolant flow rate, r2 is the feed rate of the CNC machine tool in the second-level processing mode, d2 is the cutting area of ​​the CNC machine tool in the second-level processing mode, g2 is the coolant flow rate of the CNC machine tool in the second-level processing mode, r3 is the feed rate of the CNC machine tool in the third-level processing mode, d3 is the cutting area of ​​the CNC machine tool in the third-level processing mode, g3 is the coolant flow rate of the CNC machine tool in the third-level processing mode, A1 is the first preset difficulty index, A2 is the second preset difficulty index, and α is the processing difficulty coefficient; The load monitoring module is provided with an equipment monitoring unit, and the equipment monitoring unit is used to analyze the operation status of the equipment according to the CNC airport operation data within the monitoring period; The equipment monitoring unit calculates the equipment status index γ, and compares the equipment status index γ with the preset equipment status index Y to determine the operating status of the equipment within the monitoring period, and the operating status of the equipment includes normal and abnormal; the specific process is as follows: set γ=exp{(zZ) / Z+(vV) / V}; wherein z is the vibration amplitude of the CNC machine tool within the monitoring period, Z is the normal vibration amplitude of the CNC machine tool, v is the vibration frequency of the CNC machine tool within the monitoring period, and V is the operating frequency of the CNC machine tool motor; if γ does not exceed the preset equipment status index Y, the equipment monitoring unit determines that the operating status of the equipment is normal; if γ exceeds the preset equipment status index Y, the equipment monitoring unit determines that the operating status of the equipment is abnormal; The load monitoring module is also provided with a load analysis unit, which is used to analyze the equipment load status according to the CNC machine tool operation data, the CNC machine tool processing mode and the equipment operation status analysis results within the monitoring period. The equipment load status analysis results include low load, normal load and high load. The specific process is as follows: if the equipment operation status is normal and a1×(R-ri) / ri+a2×(D-di) / di+a3×(G-gi) / gi<H, the load analysis unit determines that the equipment load status within the monitoring period is low load; if the equipment operation status is normal and a1×(R-ri) / ri+a2×(D-di) / di+a3×(G-gi) / gi≥H, the load analysis unit determines that the load state of the equipment during the monitoring period is normal load; if the operating state of the equipment is abnormal and a1×(R-ri) / ri+a2×(D-di) / di+a3×(G-gi) / gi<H, the load analysis unit determines that the load state of the equipment during the monitoring period is normal load; if the operating state of the equipment is abnormal and a1×(R-ri) / ri+a2×(D-di) / di+a3×(G-gi) / gi≥H, the load analysis unit determines that the load state of the equipment during the monitoring period is high load; Among them, H is the preset equipment load index, R is the actual feed rate of the CNC machine tool during the monitoring period, D is the actual cutting area of ​​the CNC machine tool during the monitoring period, G is the actual coolant flow rate of the CNC machine tool during the monitoring period, a1 is the feed rate error weight, a2 is the cutting area error weight, a3 is the coolant flow rate error weight, ri is the feed rate of the CNC machine tool in each processing mode, di is the cutting area of ​​the CNC machine tool in each processing mode, gi is the coolant flow rate of the CNC machine tool in each processing mode, i=1,2,3; The load monitoring module is also provided with an aging analysis unit, which is used to calculate the aging degree β of the equipment, and compare the aging degree β with the preset aging threshold B to determine the aging degree of the equipment within the monitoring period. The aging analysis results of the equipment include normal and abnormal, and when the aging analysis result of the equipment is abnormal, the second preset equipment load index is adjusted to H2'; the specific process is as follows: set β=ln(f / F); wherein f is the length of time the equipment is put into use, and F is the design service life of the CNC machine tool; if β does not exceed B, the aging analysis unit determines that the aging degree of the equipment within the monitoring period is normal and does not make adjustments; if β exceeds B, the aging analysis unit determines that the aging degree of the equipment within the monitoring period is abnormal, and adjusts the analysis process of the equipment load state, adjusts the second preset equipment load index H2 to H2', and sets H2'=H2×[1-(β-B) / B]; The load monitoring module is also provided with a cooling monitoring unit, which is used to calculate the equivalent temperature t of the cutting area of ​​the CNC machine tool and set t=(m×D) / G; wherein m is the rotation speed of the CNC machine tool; The cooling monitoring unit analyzes the cooling state of the CNC machine tool according to the calculation result t of the equivalent temperature of the cutting area of ​​the machine tool and the coolant flow rate of the CNC machine tool to determine the cooling state of the CNC machine tool within the monitoring period, the cooling state analysis result of the CNC machine tool within the monitoring period includes normal and abnormal, and when the cooling state analysis result of the CNC machine tool within the monitoring period is abnormal, the preset aging threshold is optimized to B'; The specific implementation process is as follows: if t<G×μ, the cooling monitoring unit determines that the cooling state of the CNC machine tool within the monitoring period is normal and no optimization is performed; if t≥G / μ, the cooling monitoring unit determines that the cooling state of the CNC machine tool within the monitoring period is abnormal, and optimizes the preset aging threshold B to B', setting B'=B×exp{[t / [G×μ]-1}; where μ is the cooling efficiency of the coolant.

2. The artificial intelligence-based CNC machine tool electrical control system according to claim 1 is characterized in that: The pattern analysis module includes a component property analysis unit, which is used to analyze the physical properties of the processing component according to the processing component information, and to grade the difficulty of the processing component according to the analysis result; The component property analysis unit calculates a processing difficulty coefficient α of a processing component, and compares the processing difficulty coefficient α of the processing component with various preset difficulty coefficients to determine a difficulty level of the processing component, wherein the difficulty levels of the processing component include easy processing, normal processing, and difficult processing.

3. The artificial intelligence-based CNC machine tool electrical control system according to claim 2 is characterized in that: The component monitoring module is further provided with a component monitoring unit, and the component monitoring unit is used to analyze the processing state of the processing component according to the image of the processing component within the monitoring period; The component monitoring unit compares the surface roughness σ of the processing part of the processing component within the monitoring period with a preset roughness threshold K to determine the processing state of the processing component. The processing state of the processing component includes normal and abnormal.

4. The artificial intelligence-based CNC machine tool electrical control system according to claim 3 is characterized in that: The safety warning module alarms the processing process according to the analysis results of the equipment load state and the processing state of the processing component: if the equipment load state is a low load state and the processing state of the processing component is normal, the safety warning module determines that the processing process is normal within the monitoring period and does not alarm; if the equipment load state is a normal load and the processing state of the processing component is normal, the safety warning module determines that the processing process is normal within the monitoring period and does not alarm; if the equipment load state is a high load and the processing state of the processing component is normal, the safety warning module determines that the equipment state is abnormal within the monitoring period and sends an equipment maintenance alarm to the user; if the equipment load state is a low load state and the processing state of the processing component is abnormal, the safety warning module determines that the processing process within the monitoring period is an adjustable equipment abnormality and sends a low-quality processing alarm to the user; if the equipment load state is a normal load and the processing state of the processing component is abnormal, the safety warning module determines that the processing process within the monitoring period is a pattern analysis abnormality and sends a pattern error alarm to the user; if the equipment load state is a high load and the processing state of the processing component is abnormal, the safety warning module determines that the processing process within the monitoring period is an equipment abnormality and suspends the processing process of the processing component.

5. The artificial intelligence-based CNC machine tool electrical control system according to claim 4 is characterized in that: The electrical control module is used to control the working process of the CNC machine tool in the next monitoring cycle according to the alarm result of the processing process: if the alarm result is a low-quality processing alarm, the electrical control module will move up the processing mode of the CNC machine tool in the next monitoring cycle; if the alarm result is an equipment maintenance alarm, the electrical control module will adjust the processing parameters of each mode in the next monitoring cycle to ri', di' and gi'; if the alarm result is a mode error alarm, the electrical control module will move down the processing mode of the CNC machine tool in the next monitoring cycle.

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