Intelligent monitoring method and system for numerical control machine tool

Abstract

The invention discloses an intelligent monitoring method and system for a numerical control machine tool, and relates to the technical field of intelligent monitoring of the numerical control machine tool, and the method comprises the steps of pulse signal monitoring, operation monitoring of the numerical control machine tool, and operation analysis and early warning prompt of the numerical control machine tool. The output state of the pulse signal corresponding to the numerical control machine tool is predicted, the operation information corresponding to the numerical control machine tool is obtained, the operation state corresponding to the numerical control machine tool is judged, then the product after the numerical control machine tool completes machining operation is correspondingly monitored, and the abnormal part corresponding to the numerical control machine tool is judged; comprehensive intelligent monitoring of the numerical control machine tool is achieved, efficient and safe application and operation of the numerical control machine tool are guaranteed, and based on intelligent analysis developed from the angle of corresponding pulse signals of the numerical control machine tool, the phenomena of machining risks and non-compliance of machining in the application and manufacturing process of the numerical control machine tool can be effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring of numerically controlled machine tools, and particularly to an intelligent monitoring method and system for numerically controlled machine tools. Background Art

[0002] With the application of numerically controlled machine tools in the manufacturing and processing industry, their automated control and processing technology have made the current process of part processing and creation easier and more convenient. Therefore, it is necessary to perform corresponding intelligent monitoring on numerically controlled machine tools to ensure the stable operation of numerically controlled machine tools, realize the convenient manufacturing of part processing, extend the service life of numerically controlled machine tools, ensure that numerically controlled machine tools can achieve effective part processing during application, and improve the part processing efficiency of numerically controlled machine tools.

[0003] An existing technology, such as a numerically controlled machine tool intelligent monitoring method and system disclosed in the invention patent application with publication number CN115220396B, this method includes: deploying a variety of sensors on the numerically controlled machine tool to collect the operation data of each detection parameter during the operation of the machine tool for detecting and analyzing the parameter data of the machine tool; establishing a data analysis model, based on the analysis of each detection parameter data, extracting the characteristic parameters during the operation of the machine tool for analyzing the operation status of the machine tool; based on the extracted characteristic parameters of the machine tool operation, automatically detecting the machine tool status to achieve intelligent monitoring of the numerically controlled machine tool. The present invention accurately extracts abnormal data and avoids the influence of noise data on its detection process.

[0004] Regarding the above solution, the applicant of the present invention found that the above technical problems at least exist in the following technical problems: The above invention mainly arranges multiple sensors on the numerically controlled machine tool, and then extracts abnormal data to avoid the influence of noise data on its detection process. It does not conduct subsequent analysis on the numerically controlled machine tool from the corresponding pulse signal of the numerically controlled machine tool. Therefore, it is impossible to predict the output state of the pulse signal corresponding to the numerically controlled machine tool. At the same time, it does not divide the numerically controlled machine tool into internal component monitoring and external component monitoring according to the output of the pulse signal, and fails to reflect the orderly monitoring and targeted monitoring of the numerically controlled machine tool. It is impossible to timely understand the response state of the pulse signal according to the operation performance of the parameters during the operation of the numerically controlled machine tool, and it cannot achieve rapid pulse response abnormal maintenance, increasing the risk of unsafe operation of the numerically controlled machine tool, reducing the high efficiency of part processing of the numerically controlled machine tool, and it does not analyze the part processing quality corresponding to the numerically controlled machine tool, and it is impossible to know whether the numerically controlled machine tool still stores abnormal behaviors of components, and it cannot ensure the safe application of the numerically controlled machine tool. Summary of the Invention

[0005] Aiming at the above existing technical deficiencies, the purpose of the present invention is to provide an intelligent monitoring method and system for numerically controlled machine tools.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides an intelligent monitoring method for a numerically controlled machine tool, including: Step 1, Pulse signal monitoring: By monitoring the pulse signals output by the current numerically controlled machine tool, the output state of the pulse signals corresponding to the numerically controlled machine tool is predicted.

[0007] Step 2, Operation monitoring of the numerically controlled machine tool: Perform processing operation monitoring on the numerically controlled machine tool controlled by the pulse signal output, and then obtain the corresponding operation information of the numerically controlled machine tool and judge the corresponding operation state of the numerically controlled machine tool.

[0008] Step 3, Operation analysis of the numerically controlled machine tool: Monitor the products after the numerically controlled machine tool completes the processing operation, judge the quality of the processed products corresponding to the numerically controlled machine tool, and judge the abnormal components corresponding to the numerically controlled machine tool.

[0009] Step 4, Early warning prompt: Give an early warning prompt when the operation state of the numerically controlled machine tool is abnormal or the quality of the processed products corresponding to the numerically controlled machine tool is unqualified.

[0010] In the second aspect, the present invention provides an intelligent monitoring system for a numerically controlled machine tool, including: A pulse signal monitoring module, used for monitoring the pulse signals output by the current numerically controlled machine tool, and then predicting the output state of the pulse signals corresponding to the numerically controlled machine tool.

[0011] A numerically controlled machine tool operation monitoring module, used for performing processing operation monitoring on the numerically controlled machine tool controlled by the pulse signal output and judging the corresponding operation state of the numerically controlled machine tool.

[0012] A numerically controlled machine tool operation analysis module, used for monitoring the products after the numerically controlled machine tool completes the processing operation, judging the quality of the processed products corresponding to the numerically controlled machine tool, and judging the abnormal components corresponding to the numerically controlled machine tool.

[0013] An early warning prompt module, used for giving an early warning prompt when the operation state of the numerically controlled machine tool is abnormal or the quality of the processed products corresponding to the numerically controlled machine tool is unqualified.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides an intelligent monitoring method and system for a numerically controlled machine tool. First, by monitoring the pulse signals output by the current numerically controlled machine tool, the output state of the pulse signals corresponding to the numerically controlled machine tool is predicted, and the operation information corresponding to the numerically controlled machine tool is obtained to judge the operation state of the numerically controlled machine tool. Secondly, the products after the numerically controlled machine tool completes the processing operation are monitored correspondingly to judge the abnormal components corresponding to the numerically controlled machine tool, realizing the comprehensive intelligent monitoring of the numerically controlled machine tool, ensuring the efficient and safe application and operation of the numerically controlled machine tool, solving the deficiencies existing in the current technology, and based on the intelligent analysis from the perspective of the pulse signals corresponding to the numerically controlled machine tool, effectively ensuring the application safety of the numerically controlled machine tool, being able to effectively reduce the processing risks and non-compliant processing phenomena existing in the application and manufacturing of the numerically controlled machine tool, improving the manufacturing efficiency and product quality of the numerically controlled machine tool part processing, extending the service life corresponding to the numerically controlled machine tool. At the same time, the intelligent monitoring method of the numerically controlled machine tool also saves the energy and cost of manual monitoring to a certain extent, helps the numerically controlled machine tool to prevent operation risks in a timely manner, reduces the downtime and maintenance cost, and improves the application rate of the numerically controlled machine tool. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a schematic flow chart of the implementation steps of the method of the present invention.

[0017] Figure 2 It is a schematic connection diagram of the system structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0019] Please refer to Figure 1 As shown, an intelligent monitoring method for a numerically controlled machine tool includes Step 1. Pulse signal monitoring: By monitoring the pulse signals output by the current numerically controlled machine tool, the output state of the pulse signals corresponding to the numerically controlled machine tool is predicted.

[0020] As an alternative implementation, the monitoring of the pulse signal output by the current numerical control machine tool is as follows: Based on the fact that the pulse signal output by the numerical control machine tool is in a progressive sequence, each time period is set, and the oscilloscope is used to monitor the pulse signal of the numerical control machine tool for each time period, and the monitoring data values of the pulse signal of the numerical control machine tool corresponding to each time period are collected, where the monitoring data values include pulse frequency, pulse width, pulse interval, phase, and signal amplitude.

[0021] As an alternative implementation, the prediction of the output state of the pulse signal corresponding to the numerical control machine tool is as follows: Compare the monitoring data values of the pulse signal of the numerical control machine tool corresponding to each time period with the reference pulse values corresponding to each monitoring history stored in the database. If the monitoring data value of the pulse signal of the numerical control machine tool corresponding to a certain time period is greater than or equal to the reference pulse value corresponding to each monitoring history stored in the database, it is determined that the pulse signal in this time period is in a high-quality output state, and then the output states of the pulse signals in each time period are obtained by analogy comparison, so as to predict the output state of the pulse signal corresponding to the numerical control machine tool.

[0022] It should be noted that the reference pulse value: Obtain the pulse signals corresponding to each historical collection of the numerical control machine tool from the database, extract the pulse signal values corresponding to the qualified processing of each numerical control machine tool product, and then use the extracted pulse signals as the reference pulse signal values, and arrange them in ascending order according to the collection time, so as to obtain the reference pulse values corresponding to each monitoring history.

[0023] Step 2: Monitoring the operation of the numerical control machine tool: Monitor the processing operation of the numerical control machine tool controlled by the pulse signal output, and then obtain the corresponding operation information of the numerical control machine tool and judge the operation state of the numerical control machine tool.

[0024] It should be noted that each internal component includes a stepper motor and a servo motor, etc., each monitoring sensor includes a current sensor and a displacement sensor, etc., each external component includes a tool, a bed, a base, a column, a crossbeam, a slide, a workbench, a spindle box, and a feed mechanism, etc., and each external monitoring instrument includes a tachometer, a rate measuring instrument, and an electronic angle measuring instrument, etc.

[0025] As an alternative implementation, the monitoring of the processing operation of the numerical control machine tool controlled by the pulse signal output is as follows: A1. The output control of the pulse signal corresponding to the data machine tool includes the reception of internal components and the execution of external components, and then unified processing operation monitoring is performed.

[0026] A2. According to the pulse signals released by the numerical control machine tool, obtain each internal component monitored by the numerical control machine tool, and set the numerical value range of the reference operating data. Start each monitoring sensor by issuing an activation command, and then monitor each internal component corresponding to the numerical control machine tool, and collect the operating data corresponding to each internal component. The operating data includes motor current, motor speed, and motor position. When the operating data corresponding to a certain internal component exceeds the set numerical value range of the reference operating data, record the data corresponding to this internal component. When the numerical control machine tool completes the corresponding processing operation, end the monitoring of each internal component corresponding to the numerical control machine tool.

[0027] A3. Based on the data of the connection relationship between the external components corresponding to each internal component of the numerical control machine tool stored in the database, monitor each external component corresponding to the numerical control machine tool, and set the numerical value range of the external reference operating data. Turn on each external monitoring instrument, and monitor the execution data corresponding to each external component for each monitoring time period. The execution data includes cutting speed, cutting angle, and feed speed. When the execution data corresponding to a certain external component exceeds the set numerical value range of the external reference operating data, record the data corresponding to this external component. When the numerical control machine tool completes the corresponding processing operation, end the monitoring of each external component corresponding to the numerical control machine tool. By synthesizing the monitoring of the internal components corresponding to the numerical control machine tool, obtain the operation information corresponding to the numerical control machine tool. The operation information includes operating data and execution data, so as to complete the monitoring of the processing operation corresponding to the numerical control machine tool.

[0028] It should be noted that the numerical value range of the reference operating data and the numerical value range of the external reference operating data are obtained from the product manual corresponding to the numerical control machine tool. Before the numerical control machine tool is sold, the manufacturer will perform corresponding processing operation tests on the numerical control machine tool. By setting each processing test group, the numerical control machine tool is tested according to each processing test group. When each test group completes the corresponding part processing task, obtain the operating data and external operating data corresponding to each processing test group, and compare the parts processed by each processing test group with the parts already sold on the market. If the parts processed by a certain processing test group are the same as the parts already sold on the market, record the operating data and external operating data corresponding to this processing test group as a reference. By analogy, obtain the operating data and external operating data corresponding to each processing test group, and record them as the numerical value range of the reference operating data and the numerical value range of the external reference operating data.

[0029] As an alternative implementation, the process of determining the operating state corresponding to the CNC machine tool is as follows: Input the operating information into the prediction model, and then calculate the machining operation coefficient corresponding to the CNC machine tool. When the output result of predicting the machining operation coefficient corresponding to the CNC machine tool is 0, it is determined that the operation corresponding to the CNC machine tool is in a non-compliant state, and it is determined that the pulse signal response corresponding to the CNC machine tool is abnormal. If the output result of predicting the machining operation coefficient corresponding to the CNC machine tool is 1, it is determined that the operation corresponding to the CNC machine tool is in a normal state, and thus the operating state corresponding to the CNC machine tool is judged.

[0030] It should be noted that the prediction model includes a linear regression model, a logistic regression model, a support vector regression model, a decision tree model, a random forest model, etc.

[0031] As an alternative implementation, the process of calculating the machining operation coefficient corresponding to the CNC machine tool is as follows: Perform normalization processing on the operating information corresponding to the CNC machine tool, and then substitute it into the calculation formula:

[0032]

[0033] to obtain the machining operation coefficient θ of the CNC machine tool. k is the number of each internal component, k = 1, 2,....., y, where y is any integer greater than 2. x is the number of each external component, x = 1, 2,....., p, where p is any integer greater than 2. r 1 、r 2 、r 3 、r 4 and r 5 are respectively the weight factors of the set motor current, the weight factor of the motor position, the weight factor of the cutting speed, the weight factor of the cutting angle, and the weight factor of the feed speed. B k is the motor current corresponding to the kth internal component of the CNC machine tool. D k is the motor position corresponding to the kth internal component of the CNC machine tool. E x is the cutting speed corresponding to the xth external component of the CNC machine tool. F x is the cutting angle corresponding to the xth external component of the CNC machine tool. G x is the feed speed corresponding to the xth external component of the CNC machine tool. p is the set reference operation evaluation coefficient, 0 < r 1 <1, 0 < r 2 <1, 0 < r 3 <1, 0 < r 4 <1, 0 < r 5 <1.

[0034] It should be noted that the operation evaluation coefficients of each historical operation of the CNC machine tool are obtained by statistically calculating the operation evaluation coefficients of each historical operation in the normal state, and then calculating the average value of the statistically obtained operation evaluation coefficients to obtain the average operation evaluation coefficient, which is used as the reference operation evaluation coefficient.

[0035] It should also be noted that the weight factors of the motor current, motor position, cutting speed, cutting angle, and feed speed are obtained through the principal component analysis method. First, the information of the corresponding motor current, motor position, cutting speed, cutting angle, and feed speed is concentrated, and then the corresponding variance explanation rate is obtained, and then divided by the variance explanation rate to obtain the corresponding weights.

[0036] Once again, it should be noted that information concentration refers to condensing multiple analysis items into several key general indicators. The variance explanation rate refers to the contribution degree of each principal component or factor to the total variance, usually expressed as a percentage, indicating how much information of the original data is contained in the factor.

[0037] Step 3: CNC machine tool operation analysis: Monitor the products after the CNC machine tool completes the processing operation, judge the quality of the products corresponding to the CNC machine tool for processing, and identify the abnormal components corresponding to the CNC machine tool.

[0038] It should be noted that a camera is used to obtain the product image after the CNC machine tool completes the processing operation, and the apparent data extracted from the CNC machine tool is compared with the required product in terms of appearance to obtain the similarity between the current product and the required product, and subtract the similarity from 100% to obtain the apparent error. A roughness measuring instrument is used to obtain the corresponding apparent roughness of the product, and the product cutting position data extracted from the CNC machine tool is compared with the required product cutting position to obtain the cutting position error.

[0039] As an optional implementation method, the monitoring of the products after the CNC machine tool completes the processing operation is specifically as follows: Based on the monitoring camera, obtain the product image after the corresponding processing of the CNC machine tool, and obtain the basic information of the products corresponding to the CNC machine tool for processing from the product image, where the basic information includes the apparent error, apparent roughness, and cutting position error, and substitute them into the calculation formula: Calculate the basic evaluation coefficient β of the products corresponding to the CNC machine tool for processing, where η′ is the set reference apparent error, is the set reference apparent roughness, γ′ is the set reference cutting position error, η is the apparent error of the products corresponding to the CNC machine tool for processing, is the apparent roughness of the products corresponding to the CNC machine tool for processing, γ is the cutting position error of the products corresponding to the CNC machine tool for processing, and They are the weight factor of the set apparent error, the weight factor of the apparent roughness, and the weight factor of the cutting position error respectively.

[0040] It should be noted that the apparent errors corresponding to the historical processed products of the CNC machine tool are obtained from the database, and the average value is calculated and substituted to obtain the average apparent error, and the average apparent error is used as the reference apparent error. The apparent roughness corresponding to the historical processed products of the CNC machine tool is obtained from the database, and the average value is calculated and substituted to obtain the average apparent roughness, and the average apparent roughness error is used as the reference apparent roughness. The cutting position errors corresponding to the historical processed products of the CNC machine tool are obtained from the database, and the average value is calculated and substituted to obtain the average cutting position error, and the average cutting position error is used as the reference cutting position error.

[0041] It should also be noted that the weight factors of the apparent error, the weight factor of the apparent roughness, and the weight factor of the cutting position error are obtained through the principal component analysis method. First, the information of the corresponding apparent error, apparent roughness, and cutting position error is concentrated, then the corresponding variance explanation rate is obtained, and then the corresponding weight is obtained by dividing by the variance explanation rate.

[0042] As an optional implementation manner, the quality of the processed product corresponding to the CNC machine tool is judged as follows: The basic evaluation coefficient of the processed product corresponding to the CNC machine tool is compared with the reference basic evaluation coefficient threshold of the processed product stored in the database. If the basic evaluation coefficient of the processed product corresponding to the CNC machine tool is less than or equal to the reference basic evaluation coefficient threshold of the processed product stored in the database, it is determined that the quality of the processed product corresponding to the CNC machine tool is qualified. If the basic evaluation coefficient of the processed product corresponding to the CNC machine tool is greater than the reference basic evaluation coefficient threshold of the processed product stored in the database, it is determined that the quality of the processed product corresponding to the CNC machine tool is unqualified, and further monitoring of the CNC machine tool is continued to judge the quality of the processed product corresponding to the CNC machine tool.

[0043] It should also be noted that the basic evaluation coefficient thresholds when the historical processed products of the CNC machine tool correspond to qualified batches are obtained, and the basic evaluation coefficient thresholds when the historical processed products correspond to qualified batches are calculated based on the average value to obtain the average basic evaluation coefficient threshold, and the average basic evaluation coefficient threshold is used as the reference basic evaluation coefficient threshold.

[0044] As an alternative implementation, the process of determining the abnormal component corresponding to the CNC machine tool is as follows: Compare the product image of the product processed by the CNC machine tool with the set product image of the processed product, and then extract the abnormal operation data of the product processed by the CNC machine tool. Compare the abnormal data of the product processed by the CNC machine tool with the set of operation data corresponding to each machine part stored in the database. If the abnormal data of the product processed by the CNC machine tool is within the set of operation data corresponding to a certain machine part stored in the database, then this machine part is regarded as the abnormal component corresponding to the CNC machine tool, and thus the abnormal component corresponding to the CNC machine tool is determined.

[0045] It should be noted again that the set of operation data is obtained from the product manual corresponding to the CNC machine tool, and the operation functions corresponding to each machine part of the CNC machine tool are marked in the manual.

[0046] Step 4. Early warning prompt: Give an early warning prompt when the operating state of the CNC machine tool is abnormal or the quality of the product processed by the CNC machine tool is unqualified.

[0047] Please refer to Figure 2 As shown, an intelligent monitoring system for a CNC machine tool includes a pulse signal monitoring module, a CNC machine tool operation monitoring module, a CNC machine tool operation analysis module, an early warning prompt module, and a database.

[0048] The pulse signal monitoring module is respectively connected to the CNC machine tool operation monitoring module and the database. The CNC machine tool operation monitoring module is respectively connected to the CNC machine tool operation analysis module, the database, and the early warning prompt module. The CNC machine tool operation analysis module is respectively connected to the database and the early warning prompt module.

[0049] The pulse signal monitoring module is used to monitor the pulse signal output by the current CNC machine tool, and then predict the output state of the pulse signal corresponding to the CNC machine tool.

[0050] The CNC machine tool operation monitoring module is used to monitor the processing operation of the CNC machine tool controlled by the pulse signal output and judge the operating state of the CNC machine tool.

[0051] The CNC machine tool operation analysis module is used to monitor the product after the CNC machine tool completes the processing operation, judge the quality of the product processed by the CNC machine tool, and judge the abnormal component corresponding to the CNC machine tool.

[0052] The early warning prompt module is used to give an early warning prompt when the operating state of the CNC machine tool is abnormal or the quality of the product processed by the CNC machine tool is unqualified.

[0053] The database is used to store monitored data values, reference pulse values, operation information, reference operating data value ranges, external reference operating data value ranges, basic information, and reference basic evaluation coefficient thresholds.

[0054] In the embodiment of the present invention, first, the pulse signals output by the current numerical control machine tool are monitored, and then the output state of the pulse signals of the numerical control machine tool is predicted, and the operation information corresponding to the numerical control machine tool is obtained to judge the operation state of the numerical control machine tool. Secondly, the products after the numerical control machine tool completes the processing operation are monitored correspondingly to judge the abnormal components corresponding to the numerical control machine tool, realizing the comprehensive intelligent monitoring of the numerical control machine tool, ensuring the efficient and safe application and operation of the numerical control machine tool, solving the deficiencies in the current technology, and based on the intelligent analysis from the perspective of the pulse signals corresponding to the numerical control machine tool, effectively ensuring the application safety of the numerical control machine tool, being able to effectively reduce the processing risks and non-compliant processing phenomena existing in the application and manufacturing of the numerical control machine tool, improving the manufacturing efficiency and product quality of the numerical control machine tool part processing, extending the application life corresponding to the numerical control machine tool. At the same time, the intelligent monitoring method of the numerical control machine tool also saves the energy and cost of manual monitoring to a certain extent, helps the numerical control machine tool prevent operation risks in a timely manner, reduces the downtime and maintenance costs, and improves the application rate of the numerical control machine tool.

[0055] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of the present technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A method for intelligent monitoring of CNC machine tools, characterized in that: include: Step 1: Pulse signal monitoring: by monitoring the pulse signal corresponding to the current CNC machine tool output, the output state of the corresponding pulse signal of the CNC machine tool is predicted; Step 2: CNC machine tool operation monitoring: Perform processing operation monitoring on the CNC machine tool based on pulse signal output control, thereby obtaining the corresponding operation information of the CNC machine tool and determining the corresponding operation status of the CNC machine tool; Step 3: CNC machine tool operation analysis: Monitor the products after the CNC machine tool completes the processing operation, determine the quality of the products processed by the CNC machine tool, and determine the abnormal parts of the CNC machine tool; Step 4: Early warning: Issue an early warning when the corresponding operating status of the CNC machine tool is abnormal or the quality of the corresponding processed products of the CNC machine tool is unqualified.

2. A CNC machine tool intelligent monitoring method as claimed in claim 1, characterized in that: The pulse signal corresponding to the output of the current CNC machine tool is monitored, and the specific monitoring process is as follows: Based on the fact that the pulse signal output by the CNC machine tool is in a progressive sequence, each time period is set. By using an oscilloscope to monitor the pulse signal of the CNC machine tool in each time period, the monitoring data values ​​of the pulse signal of the CNC machine tool corresponding to each time period are collected, wherein the monitoring data values ​​include pulse frequency, pulse width, pulse interval, phase and signal amplitude.

3. The intelligent monitoring method for CNC machine tools according to claim 1, characterized in that: The prediction obtains the output state of the corresponding pulse signal of the CNC machine tool, and the specific prediction process is as follows: The monitoring data value of the pulse signal of the CNC machine tool corresponding to each time period is compared with the reference pulse value corresponding to each monitoring history stored in the database. If the monitoring data value of the pulse signal of the CNC machine tool corresponding to a certain time period is greater than or equal to the reference pulse value corresponding to each monitoring history stored in the database, it is determined that the pulse signal in this time period is in a high-quality output state, and then the output state of the pulse signal in each time period is obtained by analogy and comparison, so as to predict the output state of the corresponding pulse signal of the CNC machine tool.

4. The intelligent monitoring method for a CNC machine tool according to claim 1, characterized in that: The processing operation monitoring of the CNC machine tool based on pulse signal output control is performed, and the specific monitoring process is as follows: A1. The output control of the corresponding pulse signal of the data machine tool includes internal machine receiving and external machine execution, thereby performing unified processing operation monitoring; A2. According to the pulse signal issued by the data machine tool, the corresponding internal parts of the CNC machine tool are obtained, and the reference operation data value range is set. The monitoring sensors are started by issuing a start command, and the corresponding internal parts of the data machine tool are monitored, and the operation data of the internal parts are collected, wherein the operation data includes the motor current, the motor speed and the motor position. When the operation data corresponding to a certain internal part exceeds the set reference operation data value range, the data corresponding to the internal part is recorded, and when the CNC machine tool completes the corresponding processing operation, the monitoring of the corresponding internal parts of the data machine tool is terminated; A3. Based on the connection relationship data of each internal part of the CNC machine tool corresponding to the external components stored in the database, the external parts corresponding to the CNC machine tool are monitored, and the external reference operation data value range is set. Each external monitoring instrument is turned on to monitor the execution data of each external part corresponding to each monitoring time period, wherein the execution data includes cutting speed, cutting angle and feed speed. When the execution data corresponding to a certain external part exceeds the set external reference operation data value range, the corresponding data of the external part is recorded, and when the CNC machine tool completes the corresponding processing operation, the monitoring of each external part corresponding to the data machine tool is ended. Combined with the monitoring of the internal parts corresponding to the data machine tool, the corresponding operation information of the data machine tool is obtained, wherein the operation information includes operation data and execution data, thereby completing the corresponding processing operation monitoring of the CNC machine tool.

5. The intelligent monitoring method for CNC machine tools according to claim 1, characterized in that: The specific judging process of judging the corresponding operating state of the CNC machine tool is as follows: The operation information is input into the prediction model, and then the processing operation coefficient corresponding to the CNC machine tool is calculated. When the output result of the predicted processing operation coefficient corresponding to the CNC machine tool is 0, it is determined that the corresponding operation of the CNC machine tool is in an irregular state, and the corresponding output pulse signal response of the CNC machine tool is abnormal. If the output result of the predicted processing operation coefficient corresponding to the CNC machine tool is 1, it is determined that the corresponding operation of the CNC machine tool is in a normal state, thereby judging the corresponding operation state of the CNC machine tool.

6. A method for intelligent monitoring of CNC machine tools as claimed in claim 5, characterized in that: The calculation results in the machining operation coefficient corresponding to the CNC machine tool. The specific calculation process is as follows: By normalizing the operation information corresponding to the CNC machine tool, the calculation formula is substituted: The machining operation coefficient θ corresponding to the CNC machine tool, k is the number of each internal machine part, k = 1, 2, ..., y, y is an arbitrary integer greater than 2, x is the number of each external machine part, x = 1, 2, ..., p, p is an arbitrary integer greater than 2, r1, r2, r3, r4 and r5 are the weight factors of the set motor current, motor position, cutting speed, cutting angle and feed speed, respectively, B k is the motor current corresponding to the kth internal component of the CNC machine tool, D k is the motor position corresponding to the kth internal component of the CNC machine tool, E x is the cutting speed corresponding to the xth external part of the CNC machine tool, F x is the cutting angle corresponding to the xth external part of the CNC machine tool, G x is the feed speed corresponding to the x-th external part of the CNC machine tool, p is the set reference operation evaluation coefficient, 0<r1<1, 0<r2<1, 0<r3<1, 0<r4<1, 0<r5<1.

7. The intelligent monitoring method for a CNC machine tool according to claim 1, characterized in that: The corresponding monitoring of the products after the CNC machine tool completes the processing operation is carried out, and the specific monitoring process is as follows: Based on the surveillance camera, the image of the product processed by the CNC machine tool is obtained, and the basic information of the product processed by the CNC machine tool is obtained from the product image. The basic information includes the apparent error, apparent roughness and cutting position error, and is substituted into the calculation formula: The basic evaluation coefficient β of the CNC machine tool corresponding to the processed product is calculated, and η′ is the set reference apparent error. is the set reference apparent roughness, γ′ is the set reference cutting position error, η is the apparent error of the corresponding processed product of the CNC machine tool, is the apparent roughness of the product processed by the CNC machine tool, γ is the cutting position error of the product processed by the CNC machine tool, and They are the weight factors of the set apparent error, apparent roughness and cutting position error, respectively.

8. The intelligent monitoring method for a CNC machine tool according to claim 1, characterized in that: The judgment obtains the quality of the corresponding processed product of the CNC machine tool, and the specific judgment process is as follows: The basic evaluation coefficient of the CNC machine tool corresponding to the processed product is compared with the reference basic evaluation coefficient threshold corresponding to the processed product stored in the database. If the basic evaluation coefficient of the CNC machine tool corresponding to the processed product is less than or equal to the reference basic evaluation coefficient threshold corresponding to the processed product stored in the database, the quality of the processed product corresponding to the CNC machine tool is judged to be qualified. If the basic evaluation coefficient of the CNC machine tool corresponding to the processed product is greater than the reference basic evaluation coefficient threshold corresponding to the processed product stored in the database, the quality of the processed product corresponding to the CNC machine tool is judged to be unqualified. Further monitoring of the CNC machine tool is continued to be performed to determine the quality of the processed product corresponding to the CNC machine tool.

9. The intelligent monitoring method for a CNC machine tool according to claim 1, characterized in that: The specific process of determining the abnormal parts corresponding to the CNC machine tool is as follows: The product image of the CNC machine tool's corresponding processed product is compared with the set processed product image, and then the abnormal operation data of the CNC machine tool's corresponding processed product is extracted. The abnormal data of the CNC machine tool's corresponding processed product is compared with the operation data set corresponding to each machine part stored in the database. If the abnormal data of the CNC machine tool's corresponding processed product is in the operation data set corresponding to a certain machine part stored in the database, then the machine part is regarded as the abnormal part corresponding to the CNC machine tool, so as to determine the abnormal part corresponding to the CNC machine tool.

10. An intelligent monitoring system for CNC machine tools for executing the intelligent monitoring method for CNC machine tools according to any one of claims 1 to 9, characterized in that: include: The pulse signal monitoring module is used to monitor the pulse signal corresponding to the current output of the CNC machine tool, and then predict the output state of the corresponding pulse signal of the CNC machine tool; The CNC machine tool operation monitoring module is used to perform processing operation monitoring on the CNC machine tool based on pulse signal output control and determine the corresponding operation status of the CNC machine tool; The CNC machine tool operation analysis module is used to monitor the products after the CNC machine tool completes the processing operation, determine the quality of the corresponding processed products of the CNC machine tool, and determine the corresponding abnormal parts of the CNC machine tool; The early warning prompt module is used to issue early warning prompts when the corresponding operating status of the CNC machine tool is abnormal or the quality of the corresponding processed products of the CNC machine tool is unqualified.

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