Numerical control machine tool control system and method based on online dynamic compensation

Abstract

The invention relates to the technical field of numerical control machine tools, in particular to a numerical control machine tool control system and method based on online dynamic compensation. Constructing a parameter change curve, determining an operation change value, and analyzing a change rule of operation parameters of the numerical control machine tool; according to an operation parameter change rule of the numerical control machine tool, determining a prediction time period when the numerical control machine tool reaches an operation parameter standard value, and determining predicted operation parameters at different time points in the prediction time period through the prediction model; and continuously monitoring the operation parameters in real time within the prediction time period, comparing and analyzing the operation parameters, monitored in real time, of the numerical control machine tool with the predicted operation parameters, and determining a compensation value. The compensation value can be calculated according to whether the operation parameters of the numerical control machine tool at different time points are close to the predicted operation parameters or not; and dynamic compensation of operation parameters of the numerical control machine tool is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of numerical control machine tools, and particularly relates to a numerical control machine tool control system and method based on online dynamic compensation. Background Art

[0002] In modern manufacturing, the application of numerical control machine tools is becoming more and more extensive. However, during the operation of a numerical control machine tool, its operating parameters will change due to various factors, and these changes may lead to problems such as a decrease in machining accuracy and equipment failures.

[0003] There are certain limitations in the monitoring and compensation of operating parameters in the prior art. On the one hand, the prior art lacks an accurate judgment of the change law of operating parameters and cannot select a suitable prediction model according to different change types, resulting in inaccurate prediction; on the other hand, in the process of real-time monitoring and compensation adjustment, the methods of the existing system are not perfect enough, and it is difficult to achieve dynamic and precise compensation of operating parameters, thus affecting the machining quality and operating stability of the numerical control machine tool.

[0004] Therefore, we propose a numerical control machine tool control system and method based on online dynamic compensation. Summary of the Invention

[0005] The purpose of the present invention is to provide a numerical control machine tool control system and method based on online dynamic compensation to solve at least one of the above-mentioned prior art problems.

[0006] In the first aspect, the present invention provides a numerical control machine tool control method based on online dynamic compensation, including: Obtaining the operating parameters of the numerical control machine tool; Constructing a parameter change curve, determining the operating change value, and analyzing the change law of the operating parameters of the numerical control machine tool; According to the change law of the operating parameters of the numerical control machine tool, determining the prediction period when the operating parameters of the numerical control machine tool reach the standard value, and determining the predicted operating parameters at different time points within the prediction period through a prediction model; During the prediction period, continue to monitor the operating parameters in real time, compare and analyze the real-time monitored operating parameters of the numerical control machine tool with the predicted operating parameters, and determine the compensation value.

[0007] In the second aspect, the present invention provides a numerical control machine tool control system based on online dynamic compensation, including: A data acquisition module: obtaining the operating parameters of the numerical control machine tool; A law judgment module: constructing a parameter change curve, determining the operating change value, and analyzing the change law of the operating parameters of the numerical control machine tool; Model selection module: According to the variation law of the operating parameters of the numerically controlled machine tool, determine the prediction period when the operating parameters of the numerically controlled machine tool reach the standard values, and determine the predicted operating parameters at different time points within the prediction period through the prediction model; Analysis and adjustment module: During the prediction period, continue to monitor the operating parameters in real time, compare and analyze the operating parameters of the numerically controlled machine tool monitored in real time with the predicted operating parameters, and determine the compensation value.

[0008] Advantages of the present invention: 1. The present invention obtains the operating parameters of the numerically controlled machine tool. Among them, the operating parameters include but are not limited to temperature and cutting force. If the operating parameter is less than the standard value of the operating parameter, an analysis signal is generated. Based on the analysis signal, according to the operating parameters of the numerically controlled machine tool, the operating change value is determined. Based on the operating change value, the variation law of the operating parameters of the numerically controlled machine tool is judged. Among them, the judgment results include linear variation and non-linear variation. The present invention generates an analysis signal by collecting the operating parameters of the numerically controlled machine tool in real time, determines the operating change value based on the analysis signal, analyzes the relationship between the curve slope and the slope of the connecting line between the curve segment and the end point by constructing an operating parameter curve, and judges whether the variation law of the operating parameters is linear variation or non-linear variation. According to the variation trend of the operating parameters, it provides a reliable support for the subsequent dynamic compensation of the operating parameters.

[0009] 2. Based on the judgment result of whether the operating parameters show linear variation, the present invention selects a suitable model as the prediction model. Based on the selected prediction model, determine the prediction period when the operating parameters of the numerically controlled machine tool reach the standard values, and determine the predicted operating parameters at different time points within the prediction period through the prediction model. During the prediction period, continue to monitor the operating parameters in real time, compare and analyze the operating parameters of the numerically controlled machine tool monitored in real time with the predicted operating parameters at different time nodes, obtain the ratio of the number of different time nodes, and judge the variation trend of the operating parameters of the numerically controlled machine tool at different time points based on the ratio of the number of different time nodes. Among them, the judgment results include an approaching signal and a non-approaching signal. Based on the approaching signal, the compensation value is determined. Based on the non-approaching signal, the trend characterization value is determined. According to the trend characterization value, judge whether the degree to which the operating parameters of the numerically controlled machine tool do not approach the predicted operating parameters at different time points is similar. If they are similar, an adjustment signal is generated. Based on the adjustment signal, the compensation value is recalculated. The present invention provides a basis for the compensation adjustment of the numerically controlled machine tool by monitoring the operating parameters of the numerically controlled machine tool in real time and comparing and analyzing them with the predicted operating parameters, generating an approaching signal or a non-approaching signal based on the comparison result, and determining the compensation value based on the approaching signal. By calculating the trend characterization value, it can accurately judge whether the degree to which the operating parameters of the numerically controlled machine tool do not approach the predicted operating parameters at different time points is similar, providing a scientific basis for subsequent adjustment. Based on the adjustment signal, recalculating the compensation value is conducive to realizing the precise compensation of the operating parameters of the numerically controlled machine tool. Description of the Drawings

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0011] Figure 1 is a flowchart of a numerical control machine tool control method based on online dynamic compensation according to an embodiment of the present invention; Figure 2 is a system block diagram of a numerical control machine tool control system based on online dynamic compensation according to an embodiment of the present invention; Figure 3 is a schematic diagram of the device structure of a numerical control machine tool control device based on online dynamic compensation according to an embodiment of the present invention; Reference numerals in the drawings: 3, computer device; 301, processor; 302, memory; 303, computer program. Specific embodiments

[0012] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0013] Embodiment 1 Figure 1 As shown in the figure, a numerical control machine tool control method based on online dynamic compensation provided by an embodiment of the present invention specifically includes:

[0014] As Figure 1 shown, a numerical control machine tool control method based on online dynamic compensation provided by an embodiment of the present invention specifically includes: Step 1: Obtain the operating parameters of the CNC machine tool. The operating parameters include, but are not limited to, temperature and cutting force. If the operating parameter is less than the standard value of the operating parameter, an analysis signal is generated; It should be noted that the operating parameters of the CNC machine tool are obtained by real-time collection through sensors installed in the CNC machine tool; In some embodiments, based on any one of the operating parameters, the operating parameters of the CNC machine tool are obtained in real time, and the operating parameters are compared with the standard values of the operating parameters: If the operating parameter ≥ the standard value of the operating parameter, a normal signal is generated; If the operating parameter < the standard value of the operating parameter, an analysis signal is generated; It should be noted that the standard value of the operating parameter is set by those skilled in the art according to historical experience; Step 2: Based on the analysis signal, determine the operating change value according to the operating parameters of the CNC machine tool. Based on the operating change value, judge the change law of the operating parameters of the CNC machine tool. The judgment results include linear change and non-linear change; Preset a monitoring period, extract all the operating parameters of the CNC machine tool within the monitoring period, and construct an operating parameter curve, where the x-axis represents time and the y-axis represents the operating parameter; Connect the head and tail endpoints of the operating parameter curve to obtain an endpoint connection line, and measure the slope of the endpoint connection line; Divide the operating parameter curve into several curve segments, and measure the slope of the curve segments; If the sign of the slope of the curve segment is the same as the sign of the slope of the endpoint connection line, mark the curve segment as a co-directional curve segment; If the sign of the slope of the curve segment is different from the sign of the slope of the endpoint connection line, mark the curve segment as a reverse curve segment; It should be noted that the same sign means that the slope of the curve segment and the slope of the endpoint connection line are both positive or both negative, and different signs mean that the slope of the curve segment and the slope of the endpoint connection line are not both positive or not both negative or one is 0 and the other is not 0; Perform a difference operation on the slope of the co-directional curve segment and the slope of the endpoint connection line, take the absolute value of the difference, obtain the slope deviation value of the co-directional curve segment, sum and average all the slope deviation values of the co-directional curve segments to obtain the slope deviation average value XJ; Compare the slope deviation value of the co-directional curve segment with the slope deviation average value: If the slope deviation value of the co-directional curve segment > the slope deviation average value, mark the co-directional curve segment as a non-synchronous curve segment; If the slope deviation value of the co-directional curve segment ≤ the slope deviation average value, mark the co-directional curve segment as a synchronous curve segment; Count the number of statistical synchronization curve segments, and process the ratio with the number of same-direction curve segments to obtain the synchronization ratio TB; Process the mean slope deviation XJ and the synchronization ratio TB, and through the formula: Calculate to obtain the linear performance value BG, where s1 and s2 are preset proportionality coefficients; It should be noted that the meaning represented by the linear performance value BG is: by analyzing whether the curve segment change of the operating parameter curve is in the same direction and the degree of synchronization with the overall change of the operating parameter, to analyze whether the operating parameter is a regular continuous change. Among them, the regular continuous change is a continuous linear change. The larger the linear performance value BG, the closer the change of the operating parameter is to the linear change; the smaller the linear performance value BG, the less close the change of the operating parameter is to the linear change; Compare the linear performance value BG with the linear performance threshold: If the linear performance value BG ≥ the linear performance threshold, it indicates that the change type of the abnormal operating parameter is a linear change; If the linear performance value BG < the linear performance threshold, it indicates that the change type of the abnormal operating parameter is a non-linear change; The technical solution of this embodiment is: obtain the operating parameters of the numerically controlled machine tool. Among them, the operating parameters include but are not limited to temperature and cutting force. If the operating parameter is less than the operating parameter standard value, an analysis signal is generated. Based on the analysis signal, according to the operating parameters of the numerically controlled machine tool, determine the operating change value. Based on the operating change value, judge the change law of the operating parameters of the numerically controlled machine tool. Among them, the judgment results include linear change and non-linear change. The present invention generates an analysis signal by collecting the operating parameters of the numerically controlled machine tool in real time, determines the operating change value based on the analysis signal, constructs an operating parameter curve, analyzes the relationship between the curve slope and the slope of the connecting line between the curve segment and the endpoint, and judges whether the change law of the operating parameter is a linear change or a non-linear change, providing a reliable support for subsequent dynamic compensation of the operating parameter according to the change trend of the operating parameter.

[0015] Embodiment Two As Figure 1 shown, a numerically controlled machine tool control method based on online dynamic compensation provided by an embodiment of the present invention specifically includes: Step Three: Based on the judgment result of whether the operating parameter is linearly changed, select a suitable model as the prediction model. Based on the selected prediction model, determine the prediction period when the numerically controlled machine tool reaches the operating parameter standard value, and determine the predicted operating parameters at different time points within the prediction period through the prediction model; Integrate all the operating parameters of the CNC machine tool into a data set, which is used as the training data set. If the change type of the operating parameters is linear, a linear regression model is selected as the prediction model. If the change type of the operating parameters is non-linear, a random forest network model is selected as the prediction model. Use the training data set to train the prediction model to obtain the trained prediction model; Input the standard value of the operating parameter into the prediction model to obtain the time when the operating parameter of the CNC machine tool reaches the standard value of the operating parameter, and mark it as the arrival time point. Perform a difference processing on the arrival time point and the current time point to obtain the remaining duration when the operating parameter of the CNC machine tool reaches the standard value of the operating parameter. Mark the interval between the remaining times as the prediction period; Input different time points within the prediction period into the prediction model to obtain the predicted operating parameters at different time points within the prediction period; Step 4: During the prediction period, continue to monitor the operating parameters in real time. Compare and analyze the real-time monitored operating parameters of the CNC machine tool with the predicted operating parameters at different time nodes to obtain the ratio of the number of different time nodes. According to the ratio of the number of different time nodes, judge the change trend of the operating parameters of the CNC machine tool at different time points. Among them, the judgment results include an approaching signal and a non-approaching signal. Based on the approaching signal, determine the compensation value. Based on the non-approaching signal, determine the trend characterization value. According to the trend characterization value, judge whether the degree to which the operating parameters of the CNC machine tool do not approach the predicted operating parameters at different time points is similar. If it is similar, generate an adjustment signal. Based on the adjustment signal, recalculate the compensation value; Specifically, during the prediction period, a preset monitoring period is set, where the duration corresponding to the preset monitoring period is less than the duration corresponding to the prediction period; It should be noted that: by monitoring in real time whether the operating parameters within the preset monitoring period are close to the predicted operating parameters, analyzing the accuracy of the prediction is beneficial to judging whether the operating parameters of the CNC machine tool will reach the state of the standard value of the operating parameters during the operation; Obtain the real-time monitored operating parameters of the CNC machine tool at different time nodes within the preset monitoring period, and compare them with the predicted operating parameters at different time nodes. Specifically: Based on any one time node; If the operating parameter at the time node is not equal to the predicted operating parameter, mark the time node as a different time node; If the operating parameter at the time node is equal to the predicted operating parameter, mark the time node as the same time node; Count the total number of time nodes and the number of different time nodes within the preset monitoring period, and perform a ratio processing on the number of different time nodes and the total number of time nodes within the preset monitoring period to obtain the ratio of the number of different time nodes; Compare the ratio of the number of different time nodes with the threshold of the ratio of the number of different time nodes; If the ratio of the number of different time nodes > the threshold of the ratio of the number of different time nodes, it indicates that the change trend of the operating parameters of the CNC machine tool at different time nodes does not approach the predicted operating parameters, and a non-approaching signal is generated; If the ratio of the number of different time nodes ≤ the threshold of the ratio of the number of different time nodes, it indicates that the change trend of the operating parameters of the CNC machine tool at different time nodes approaches the predicted operating parameters, and an approaching signal is generated; Based on the approaching signal, subtract the operating parameters of the CNC machine tool monitored in real time when the remaining time arrives from the predicted operating parameters to obtain the operating parameter deviation value; Compare the operating parameter deviation value with the operating parameter deviation threshold: If the operating parameter deviation value > the operating parameter deviation threshold, a normal compensation signal is generated; If the operating parameter deviation value ≤ the operating parameter deviation threshold, a non-compensation signal is generated; Based on the normal compensation signal, use the operating parameter deviation value as the compensation value to compensate the operating parameters during the prediction period; Based on the non-approaching signal, subtract the operating parameters at different time nodes from the predicted operating parameters to obtain the operating parameter difference at different time nodes. If the operating parameter difference is negative, mark the different time nodes as negative time nodes. If the operating parameter difference is positive, mark the different time nodes as positive time nodes; Count the number of negative time nodes and the number of positive time nodes, and compare the number of negative time nodes with the number of positive time nodes: If the number of negative time nodes > the number of positive time nodes, use the negative time nodes as the target nodes. If the number of negative time nodes < the number of positive time nodes, use the positive time nodes as the target nodes; It should be noted that if the number of negative time nodes = the number of positive time nodes, stop the analysis, indicating that the operating parameters of the CNC machine tool are higher than the predicted operating parameters at half of the different time points, and the operating parameters are lower than the predicted operating parameters at the other half of the different time points. The degree to which the operating parameters of the CNC machine tool at different time points do not approach the predicted operating parameters is not similar; Count the number of target nodes, and perform a ratio process with the total number of different time nodes to obtain the target quantity ratio MS; Integrate the operating parameter differences of all target nodes into an operating parameter difference data group, and obtain the variance value YF of the operating parameter difference data group; Perform data processing on the target quantity ratio MS and the variance value YF through the formula: Calculate the trend characterization value QB, where m1 and m2 are both preset proportionality coefficients; Compare the trend characterization value QB with the trend characterization threshold; If the trend characterization value QB > the trend characterization threshold, it indicates that the operating parameters of the CNC machine tool at different time points do not approach the predicted operating parameters to a similar degree, and an adjustment signal is generated; If the trend characterization value QB ≤ the trend characterization threshold, it indicates that the operating parameters of the CNC machine tool at different time points do not approach the predicted operating parameters to a dissimilar degree, and no operation is performed; Based on the adjustment signal, sum up and average the operating parameter values of all target nodes to obtain the average target operating parameter difference. If the average target operating parameter difference is positive, perform a difference operation on the standard value of the CNC machine tool operating parameters and the average target operating parameter difference to obtain the adjusted standard value of the CNC machine tool operating parameters, and re-enter it into the value prediction model to obtain the remaining time again. If the average target operating parameter difference is negative, sum up the threshold of the CNC machine tool operating parameters and the absolute value of the average target operating parameter difference to obtain the adjusted standard value of the CNC machine tool operating parameters, and re-enter it into the value prediction model to obtain the remaining time again; Perform a difference operation on the operating parameters of the CNC machine tool monitored in real time when the newly obtained remaining time arrives and the predicted operating parameters to obtain the adjusted operating parameter deviation value; Compare the adjusted operating parameter deviation value with the operating parameter deviation threshold: If the adjusted operating parameter deviation value > the operating parameter deviation threshold, generate an adjustment compensation signal; If the adjusted operating parameter deviation value ≤ the operating parameter deviation threshold, generate a non-compensation signal; Based on the adjustment compensation signal, use the adjusted operating parameter deviation value as the compensation value to compensate the operating parameters during the prediction period; The technical solution of this embodiment is as follows: Based on the judgment result of whether the operating parameters change linearly, a suitable model is selected as the prediction model. Based on the selected prediction model, the prediction period when the numerical control machine tool reaches the standard value of the operating parameters is determined. The predicted operating parameters at different time points within the prediction period are determined through the prediction model. During the prediction period, the operating parameters are continuously monitored in real time. The real-time monitored operating parameters of the numerical control machine tool are compared and analyzed with the predicted operating parameters at different time nodes to obtain the ratio of the number of different time nodes. According to the ratio of the number of different time nodes, the change trend of the operating parameters of the numerical control machine tool at different time points is judged. Among them, the judgment result includes an approaching signal and a non-approaching signal. Based on the approaching signal, a compensation value is determined. Based on the non-approaching signal, a trend characterization value is determined. According to the trend characterization value, it is judged whether the degree to which the operating parameters of the numerical control machine tool do not approach the predicted operating parameters at different time points is similar. If it is similar, an adjustment signal is generated. Based on the adjustment signal, the compensation value is recalculated. By continuously monitoring the operating parameters of the numerical control machine tool in real time and comparing and analyzing them with the predicted operating parameters, an approaching signal or a non-approaching signal is generated according to the comparison result, and the compensation value is determined based on the approaching signal, providing a basis for the compensation adjustment of the numerical control machine tool. By calculating the trend characterization value, it can accurately judge whether the degree to which the operating parameters of the numerical control machine tool do not approach the predicted operating parameters at different time points is similar, providing a scientific basis for subsequent adjustment. Based on the adjustment signal, the compensation value is recalculated, which is conducive to realizing the precise compensation of the operating parameters of the numerical control machine tool.

[0016] Embodiment III As Figure 2 shown, a numerical control machine tool control system based on online dynamic compensation provided by an embodiment of the present invention specifically includes: Data acquisition module: Acquire the operating parameters of the numerical control machine tool; Regularity judgment module: Construct a parameter change curve, determine the operation change value, and analyze the change regularity of the operating parameters of the numerical control machine tool; Model selection module: According to the change regularity of the operating parameters of the numerical control machine tool, determine the prediction period when the numerical control machine tool reaches the standard value of the operating parameters, and determine the predicted operating parameters at different time points within the prediction period through the prediction model; Analysis and adjustment module: During the prediction period, continue to monitor the operating parameters in real time, compare and analyze the real-time monitored operating parameters of the numerical control machine tool with the predicted operating parameters, and determine the compensation value.

[0017] Embodiment IV Refer to Figure 3, An embodiment of the present invention further provides a computer device 3, including: a memory 302, a processor 301, and a computer program 303 stored on the memory 302. When the computer program 303 is executed on the processor 301, it implements a numerical control machine tool control method based on online dynamic compensation as described in any one of the above methods.

[0018] The computer device 3 may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art can understand that Figure 3 merely examples of the computer device 3, which do not constitute a limitation on the computer device 3, and may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, etc.

[0019] The so-called processor 301 may be a central processing unit (CPU), and the processor 301 may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0020] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as the hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 3. Further, the memory 302 may also include both the internal storage unit and the external storage device of the computer device 3. The memory 302 is used to store an operating system, application programs, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 302 may also be used to temporarily store data that has been output or will be output.

[0021] Embodiment Five An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, it implements a numerical control machine tool control method based on online dynamic compensation as described in any one of the above methods.

[0022] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above embodiment methods of the present application, a computer program can be used to instruct relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above various method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the photographing device / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunication signal.

[0023] In the above embodiments, the descriptions of the various embodiments have their own emphases. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0024] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0025] In the embodiments disclosed in the present application, it should be understood that the disclosed device / terminal device and method can be implemented in other ways. For example, the device / terminal device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0026] Another point, the couplings or direct couplings or communication connections shown or discussed among each other can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0027] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0028] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0029] The above has described in detail an embodiment of the present invention, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A control method for a numerically controlled machine tool based on online dynamic compensation, characterized in that, Including: Obtain the operating parameters of the CNC machine tool; construct a parameter change curve, determine the operating change value, and analyze the change law of the operating parameters of the CNC machine tool; According to the change law of the operating parameters of the CNC machine tool, determine the prediction period when the operating parameters of the CNC machine tool reach the standard value, and determine the predicted operating parameters at different time points within the prediction period through the prediction model; During the prediction period, continue to monitor the operating parameters in real time, compare and analyze the real-time monitored operating parameters of the CNC machine tool with the predicted operating parameters, and determine the compensation value.

2. The control method of a numerically controlled machine tool based on online dynamic compensation according to claim 1, wherein The obtaining method of the said operating change value is: Construct an operating parameter curve, and substitute the mean slope deviation and synchronization ratio into the formula to obtain a linear performance value.

3. A numerical control machine tool control method based on online dynamic compensation according to claim 2, characterized in that The obtaining methods of the said slope deviation mean and synchronization ratio are: Compare the slope of the curve segment obtained by dividing the parameter change curve with the slope of the connecting line of the two end points of the parameter change curve. If the positive and negative are the same, record the curve segment as a co-directional curve segment; Take the absolute value of the difference between the slope of the co-directional curve segment and the slope of the connecting line of the end points, sum them up and take the mean to obtain the mean slope deviation; if the slope deviation value of the co-directional curve segment ≤ the mean slope deviation, mark the co-directional curve segment as a synchronous curve segment; Count the number of synchronous curve segments, and perform a ratio process with the number of co-directional curve segments to obtain the synchronization ratio.

4. A numerical control machine tool control method based on online dynamic compensation according to claim 1, characterized in that The obtaining method of the predicted operating parameters at different time points within the said prediction period is: If the change law of the operating parameters is linear change, use the linear regression model as the prediction model; if it is non-linear change, use the random forest network model as the prediction model; Input the standard value of the operating parameters into the prediction model, output the arrival time point, and record the period between the arrival time point and the current time point as the prediction period; Input different time points within the prediction period into the prediction model to obtain the predicted operating parameters at different time points within the prediction period.

5. A numerical control machine tool control method based on online dynamic compensation according to claim 4, characterized in that, The process of comparing and analyzing the real-time monitored operating parameters with the predicted operating parameters at different time points is: During the prediction period, preset a monitoring period, obtain the operating parameters at different time nodes within the monitoring period. If they are not equal to the predicted operating parameters, mark the time nodes as different time nodes.

6. The control method of a numerically controlled machine tool based on online dynamic compensation according to claim 4, characterized in that, The said compensation value includes the compensation value when the approaching signal is generated and the compensation value when the non-approaching signal is generated. Among them, the obtaining process of the compensation value when the approaching signal is generated is: Count the number of different time nodes, and perform a ratio with the total number of time nodes within the preset monitoring period to obtain the ratio of the number of different time nodes; Take the difference between the real-time monitored operating parameters of the CNC machine tool and the predicted operating parameters when the remaining time arrives to obtain the operating parameter deviation value; if it is greater than the operating parameter deviation threshold, use the operating parameter deviation value as the compensation value.

7. The control method of a numerically controlled machine tool based on online dynamic compensation according to claim 6, characterized in that, The obtaining process of the compensation value when the non-approaching signal is generated is: Analyze the operating parameters and predicted operating parameters at different time nodes to obtain a trend characterization value. If it is greater than the trend characterization threshold, sum up the operating parameter values of all target nodes and take the average to obtain the average difference of the target operating parameters. If it is positive, subtract the average difference of the target operating parameters from the standard value of the CNC machine operating parameters and re-enter the value into the prediction model to obtain the remaining duration again. If it is negative, sum up the absolute value of the average difference of the target operating parameters and the threshold of the CNC machine operating parameters and re-enter the value into the prediction model to obtain the remaining duration again; Take the difference between the operating parameters monitored in real time when the newly obtained remaining duration arrives and the predicted operating parameters to obtain the adjusted operating parameter deviation value. If it is greater than the operating parameter deviation threshold, use the adjusted operating parameter deviation value as the compensation value.

8. A numerical control machine tool control method based on online dynamic compensation according to claim 7, characterized in that, The process of obtaining the trend characterization value is as follows: Obtain the target quantity ratio and variance value, and perform weight calculation to obtain the trend characterization value.

9. The control method for a numerically controlled machine tool based on online dynamic compensation according to claim 8, wherein The process of obtaining the target quantity ratio and variance value is as follows: Take the difference between the operating parameters and predicted operating parameters at different time nodes to obtain the operating parameter difference. If it is negative, mark the different time nodes as negative time nodes. If it is positive, mark the different time nodes as positive time nodes; Count the number of negative time nodes and positive time nodes and compare: if the number of negative time nodes > the number of positive time nodes, take the negative time nodes as the target nodes. If the number of negative time nodes < the number of positive time nodes, take the positive time nodes as the target nodes; Count the number of target nodes and perform a ratio process with the total number of different time nodes to obtain the target quantity ratio; Extract the operating parameter differences of the target nodes and integrate them into an operating parameter difference data group, and calculate the variance value.

10. A numerical control machine tool control system based on online dynamic compensation, which implements a numerical control machine tool control method based on online dynamic compensation as described in any one of claims 1-9, characterized in that, Including: Data acquisition module: Acquire the operating parameters of the CNC machine; Regularity judgment module: Construct a parameter change curve, determine the operating change value, and analyze the change regularity of the operating parameters of the CNC machine; Model selection module: According to the change regularity of the operating parameters of the CNC machine, determine the prediction period when the CNC machine reaches the standard value of the operating parameters, and determine the predicted operating parameters at different time points within the prediction period through the prediction model; Analysis and adjustment module: During the prediction period, continue to monitor the operating parameters in real time, compare and analyze the real-time monitored operating parameters of the CNC machine with the predicted operating parameters, and determine the compensation value.

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