Numerical control machine tool control method and device, computer equipment and storage medium

Abstract

The embodiment of the invention provides a numerical control machine tool control method and device, computer equipment and a storage medium. The method comprises the steps that in the process of controlling the numerical control machine tool to execute workpiece machining based on plan control data, actual machining state data of the numerical control machine tool are acquired; wherein the plan control data comprises control parameters of each stage after the processing rhythm is divided into a plurality of stages; performing comparative analysis on the actual processing state data and expected processing state data corresponding to the plan control data to obtain difference characteristic data corresponding to each stage; adjusting plan control data according to the difference characteristic data, and controlling the numerical control machine tool to execute the process of machining the workpiece based on the adjusted plan control data. By acquiring the actual machining state data of the numerical control machine tool in real time and comparing and analyzing the actual machining state data with the planned control data, the difference characteristic data in the machining process can be recognized in time, so that the control parameters are dynamically adjusted, and the machining precision and efficiency are improved.

Description

Technical Field

[0001] The present application relates to the field of mechanical manufacturing, and specifically to a CNC machine tool control method, device, computer equipment and storage medium. Background Art

[0002] With the continuous development of CNC technology, CNC machine tools are increasingly used in the manufacturing industry, encompassing precision machining, mass production, and the manufacture of complex workpieces. To improve machining accuracy and efficiency, modern CNC machine tools typically rely on planned control data, which divides the machining process into multiple stages and sets corresponding control parameters for each stage.

[0003] However, existing CNC machine tools are subject to numerous factors during actual machining, such as tool wear, material deformation, and machine vibration. These factors can cause discrepancies between the actual machining state and the desired state in the planned control data. If these discrepancies are not detected and corrected promptly, they can directly impact machining accuracy and, in turn, product quality. Summary of the Invention

[0004] In view of this, multiple embodiments of the present application are dedicated to providing a CNC machine tool control method, which can improve the machining accuracy of the CNC machine tool to a certain extent.

[0005] In a first aspect, an embodiment of the present application provides a method for controlling a CNC machine tool, comprising:

[0006] In the process of controlling a CNC machine tool to process a workpiece based on planned control data, actual processing status data of the CNC machine tool is obtained; wherein, the planned control data includes control parameters for each stage after the processing cycle is divided into multiple stages; the actual processing status data is compared and analyzed with expected processing status data corresponding to the planned control data to obtain difference characteristic data corresponding to each stage; the planned control data is adjusted according to the difference characteristic data, and the CNC machine tool is controlled to process the workpiece based on the adjusted planned control data.

[0007] Optionally, the method also includes: obtaining historical processing power data and historical processing control data generated by the CNC machine tool during the process of processing the workpiece; the historical processing power data includes spindle load data, and the historical processing control data includes feed rate data; based on the comparison result of the spindle load data and the specified idle tool power threshold, the processing rhythm is divided into multiple stages; wherein, the multiple stages include an idle tool stage and a processing stage; the spindle load data corresponding to the idle tool stage is less than the specified idle tool power threshold; the spindle load data corresponding to the processing stage is greater than the specified idle tool power threshold; the historical processing control data of at least part of the stages are optimized to generate the planned control data.

[0008] Optionally, the planned control data includes feed rate optimization data, and the feed rate optimization data corresponds to an idle tool feed rate optimization value and a machining feed rate optimization value, and the idle tool feed rate optimization value is greater than the machining feed rate optimization value; optimizing the historical machining control data of at least part of the stage to generate the planned control data includes: when the spindle load data is less than the specified idle tool power threshold, increasing the feed rate data to obtain the idle tool feed rate optimization value.

[0009] Optionally, the method also includes: optimizing the actual machining control data of at least part of the stages to generate the planned control data, and also includes: when the spindle load data is greater than the specified empty tool power threshold and less than the specified hard point power threshold, reducing the feed rate data to obtain the optimized machining feed rate value.

[0010] Optionally, the feed rate data corresponds to a baseline value, and the baseline value of the feed rate data is less than the optimized processing feed rate value; the step of optimizing the actual processing control data of at least part of the stage to generate the planned control data also includes: when the spindle load data is greater than the specified hard point power threshold, reducing the feed rate data to obtain the baseline value of the feed rate data.

[0011] Optionally, the actual processing status data includes actual control time; the expected processing status data includes expected control time; the actual processing status data is compared and analyzed with the expected processing status data corresponding to the planned control data to obtain the difference characteristic data corresponding to each stage, including: comparing the actual control time and the expected control time of each stage to obtain the control time deviation.

[0012] Optionally, the step of comparing and analyzing the actual processing status data with the expected processing status data corresponding to the planned control data to obtain the difference characteristic data corresponding to each stage also includes: obtaining the control distance deviation based on the control time deviation and feed rate data; using the feed rate data and the control distance deviation to generate the time compensation data; the time compensation data is used to adjust the planned control data; wherein, the difference characteristic data includes the time compensation data.

[0013] Optionally, the planned control data includes a planned entry into processing control time node, and the adjusted planned control data includes an adaptive entry into processing control time node; the steps of adjusting the planned control data according to the difference feature data, and controlling the CNC machine tool to execute the process of processing the workpiece based on the adjusted planned control data include: deriving an adaptive entry into processing control time node based on the time compensation data and the planned entry into processing control time node; the adaptive entry into processing control time node is used to control the CNC machine tool to execute the process of processing the workpiece.

[0014] In the second aspect, an embodiment of the present application also provides a CNC machine tool control device, including: an acquisition module, used to obtain the actual processing status data of the CNC machine tool in the process of controlling the CNC machine tool to execute processing of a workpiece based on planned control data; wherein, the planned control data includes the control parameters of each stage after the processing rhythm is divided into multiple stages; an analysis module, used to compare and analyze the actual processing status data with the expected processing status data corresponding to the planned control data, and obtain the difference feature data corresponding to each stage; an adjustment module, used to adjust the planned control data according to the difference feature data, and control the CNC machine tool to execute the process of processing the workpiece based on the adjusted planned control data.

[0015] In a third aspect, an embodiment of the present application further provides an electronic device, comprising a memory and a processor, wherein the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor to implement the CNC machine tool control method as described above.

[0016] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one computer program, and when the at least one computer program is executed by a processor, it can implement the aforementioned CNC machine tool control method.

[0017] In various embodiments provided herein, by acquiring the actual machining state data of a CNC machine tool in real time and comparing and analyzing it with planned control data, it is possible to promptly identify differential characteristic data during the machining process, thereby dynamically adjusting control parameters to achieve improved machining accuracy. This CNC machine tool control method can effectively address the effects of factors such as tool wear, material deformation, and machine tool vibration, ensuring that the machining state is more consistent with expectations and improving the quality of the final product. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flowchart of a CNC machine tool control method provided for one embodiment of the present application.

[0019] Figure 2 A schematic diagram of the division of processing stages provided for one embodiment of the present application.

[0020] Figure 3 A schematic diagram of feed rate optimization is provided for one embodiment of the present application.

[0021] Figure 4 A schematic diagram of a multi-stage feed rate database for planning optimization provided for one embodiment of the present application.

[0022] Figure 5 A schematic diagram of the i-stage processing phase division and time points provided for one embodiment of the present application.

[0023] Figure 6 A schematic diagram of the machining feed rate data for the i-th stage provided for one embodiment of the present application.

[0024] Figure 7 A schematic diagram of the difference between the multi-stage planned control feed rate and the actual control feed rate provided in one embodiment of the present application.

[0025] Figure 8 A schematic diagram of a module of a CNC machine tool control device provided in one embodiment of the present application.

[0026] Figure 9 A schematic diagram of an electronic device provided in accordance with one embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0028] See also Figure 1. An embodiment of the present application provides a method for controlling a CNC machine tool. The method for controlling a CNC machine tool can be applied to a CNC machine tool control device. The CNC machine tool control device can be an electronic device with certain computing capabilities. The electronic device can have a controller and a memory, etc. Of course, in some embodiments, the CNC machine tool control device can also refer to a program module running in an electronic device. The method for controlling a CNC machine tool can include the following steps.

[0029] Step S110: in the process of controlling the CNC machine tool to process a workpiece based on the planned control data, obtaining actual processing status data of the CNC machine tool; wherein the planned control data includes control parameters of each stage after the processing cycle is divided into multiple stages.

[0030] Step S120: comparing and analyzing the actual processing state data with the expected processing state data corresponding to the planned control data to obtain difference feature data corresponding to each stage.

[0031] Step S130: adjusting the planning control data according to the difference feature data, and controlling the CNC machine tool to execute a process of machining a workpiece based on the adjusted planning control data.

[0032] In this embodiment, the actual processing state data can be used to describe the actual working state of the CNC machine tool during the process of processing the workpiece. The CNC machine tool control device can obtain the actual processing state data fed back by the sensors set on the CNC machine tool during the operation of the CNC machine tool. For example, the actual processing state data may include information such as processing temperature, feed speed, and tool wear. Accordingly, a variety of sensors can be set in the CNC machine tool to obtain the aforementioned state data. The planned control data can be pre-set processing parameters. For example, the planned control data may include a control strategy after dividing the processing cycle into multiple stages, as well as the expected processing state data for each stage.

[0033] Specifically, during the CNC machine tool's workpiece processing, the control device can obtain actual processing status data to understand the machine tool's operating status in real time. The control device can compare and analyze the actual processing status data with the expected processing status data in the planned control data, thereby identifying differential characteristic data at each stage. This differential characteristic data is derived by comparing the deviation between the actual state and the expected state and can reflect abnormal conditions in the processing process.

[0034] The CNC machine tool control device can use the differential feature data as the basis for subsequent machining process adjustments. Based on the identified differential feature data, the CNC machine tool control device can dynamically adjust the planned control data, thereby correcting the machining parameters to make them more in line with actual machining needs.

[0035] In various embodiments provided herein, by acquiring the actual machining state data of a CNC machine tool in real time and comparing and analyzing it with planned control data, it is possible to promptly identify differential characteristic data during the machining process, thereby dynamically adjusting control parameters to achieve improved machining accuracy. This CNC machine tool control method can effectively address the effects of factors such as tool wear, material deformation, and machine tool vibration, ensuring that the machining state is more consistent with expectations and improving the quality of the final product.

[0036] See also Figure 2 In some embodiments, a CNC machine tool control device can obtain historical processing power data and historical processing control data generated by the CNC machine tool during the process of processing a workpiece; the historical processing power data includes spindle load data, and the historical processing control data includes feed rate data; based on a comparison result of the spindle load data with a specified idle tool power threshold, the processing cycle is divided into multiple stages; wherein the multiple stages include an idle tool stage and a processing stage; the spindle load data corresponding to the idle tool stage is less than the specified idle tool power threshold; the spindle load data corresponding to the processing stage is greater than the specified idle tool power threshold; the historical processing control data of at least part of the stages are optimized to generate the planned control data.

[0037] In this embodiment, the CNC machine tool control device includes a controller that can be used to specifically execute control logic and issue control signals to control the processing process of the CNC machine tool.

[0038] In this embodiment, the historical processing power data is used to represent the actual energy consumption of the CNC machine tool during the process of processing the workpiece, and the historical processing control data is used to represent the control state of the CNC machine tool during the process of processing the workpiece. Specifically, in the process of processing the workpiece, the CNC machine tool control device will record the spindle load data in the historical processing power data, and compare and analyze the spindle load data with the specified idle tool power threshold. In this way, the CNC machine tool control device can divide the processing cycle into multiple stages, specifically including the idle tool stage and the processing stage. In the idle tool stage, the spindle load data is less than the specified idle tool power threshold, and the feed rate data of the CNC machine tool in this stage is in a variable state; while in the processing stage, the spindle load data is greater than the threshold, and the feed rate data of the CNC machine tool in this stage is in a stable and unchanged state.

[0039] On this basis, the CNC machine tool control device can optimize the historical processing control data of at least some stages to generate more reasonable planned control data. Furthermore, the CNC machine tool control device can dynamically adjust its processing strategy to adapt to changes in energy consumption during the actual processing process.

[0040] By combining the historical processing power data with the comparison results of the specified idle tool power threshold, this embodiment can effectively realize the stage division of the CNC machine tool processing process and optimize the adjustment of the control parameters, thereby improving the rationality of the control strategy at each stage of the processing process.

[0041] See also Figure 3 、 Figure 4 In some embodiments, the CNC machine tool control device can optimize the efficiency of the CNC machine tool feed rate based on the CNC machine tool multi-stage feed rate data obtained by the CNC machine tool controller and whether the CNC machine tool spindle load data is greater than the hard point power threshold and whether it is greater than the empty tool power threshold, and generate the planned control data. The CNC machine tool control device can optimize the empty tool feed rate when the CNC machine tool spindle load data is less than the empty tool power threshold, optimize the processing feed rate when it is greater than the empty tool power threshold and less than the hard point power threshold, and adjust the CNC machine tool feed rate to the original processing feed rate when it is greater than the hard point power threshold.

[0042] In some embodiments, the planned control data includes feed rate optimization data, and the feed rate optimization data corresponds to an idle tool feed rate optimization value and a machining feed rate optimization value, and the idle tool feed rate optimization value is greater than the machining feed rate optimization value; optimizing the historical machining control data of at least part of the stage to generate the planned control data includes: when the spindle load data is less than the specified idle tool power threshold, increasing the feed rate data to obtain the idle tool feed rate optimization value.

[0043] In this embodiment, the feed rate data included in the historical processing control data is used to describe the cutting speed of the tool relative to the workpiece during the CNC machine tool processing process, that is, the speed at which the tool rotates with the CNC machine tool spindle and cuts forward according to a preset path. Specifically, increasing the feed rate data can increase the amount of workpiece cutting by the tool per unit time, thereby shortening the processing time and improving the processing efficiency of the CNC machine tool. The fact that the CNC machine tool spindle load data is less than the specified idle tool power threshold can indicate that the impact on the tool during the processing of the CNC machine tool at this time is relatively small. At this time, increasing the feed rate data to the idle tool feed rate optimization value can effectively improve the processing efficiency of the CNC machine tool. In some embodiments, for example, the idle tool feed rate optimization value can be equal to 120.

[0044] In response to the situation where the spindle load data of a CNC machine tool is less than the specified idle tool power threshold, this application proposes an optimization processing method for increasing the feed rate data. By increasing the feed rate data, the amount of cutting of the workpiece by the tool per unit time is increased. This method can effectively improve the processing efficiency of the CNC machine tool.

[0045] In some embodiments, the step of optimizing the actual machining control data of at least part of the stages to generate the planned control data also includes: when the spindle load data is greater than the specified empty tool power threshold and less than the specified hard point power threshold, reducing the feed rate data to obtain the optimized machining feed rate value.

[0046] In this embodiment, if the spindle load data is greater than a specified idle tool power threshold and less than a specified hard point power threshold, it can indicate that the impact on the tool during machining on the CNC machine tool is increasing. Reducing the feed rate data to the optimized machining feed rate can reduce the impact on the tool and protect the tool. When the CNC machine tool feed rate data is equal to the optimized machining feed rate, the CNC machine tool can achieve higher machining efficiency while protecting the tool. In some embodiments, for example, the optimized machining feed rate can be equal to 110.

[0047] In response to the situation where the spindle load data of a CNC machine tool is greater than the specified empty tool power threshold and less than the specified hard point power threshold, this application proposes an optimization processing method for reducing the feed rate data. By reducing the feed rate data, the impact on the CNC machine tool tool is reduced. This method can effectively protect the tool of the CNC machine tool to extend the tool life, while taking into account the processing efficiency of the CNC machine tool.

[0048] In some embodiments, the feed rate data corresponds to a baseline value, and the baseline value of the feed rate data is less than the optimized processing feed rate value; the step of optimizing the actual processing control data of at least part of the stage to generate the planned control data also includes: when the spindle load data is greater than the specified hard point power threshold, reducing the feed rate data to obtain the baseline value of the feed rate.

[0049] In this embodiment, the spindle load data being greater than the specified hard point power threshold may indicate an abnormal situation in the CNC machine tool processing process, such as when the CNC machine tool's tool encounters a hard point or a difficult-to-cut material in the workpiece. At this time, the impact on the CNC machine tool's tool is extremely great, and the load on the tool increases at the same time, posing a high risk of damage. At this time, reducing the feed rate data to the reference value of the feed rate data can effectively reduce the impact on the CNC machine tool's tool and protect the tool. The reference value of the feed rate data can be a smaller feed rate value. If the CNC machine tool's feed rate is reduced to the reference value and still cannot effectively reduce the load on the CNC machine tool's tool, the CNC machine tool control device will sound an alarm and force the CNC machine tool to stop, thereby protecting the tool and the workpiece. In some embodiments, for example, the reference value of the feed rate can be equal to 100.

[0050] In response to the situation where the spindle load data of a CNC machine tool is greater than the specified hard point power threshold, this application proposes an optimization processing method for reducing the feed rate data. By reducing the feed rate data, the impact on the CNC machine tool tool is reduced. This method can effectively protect the CNC machine tool tool and workpiece when the CNC machine tool control device identifies an abnormal situation during the CNC machine tool processing process.

[0051] See also Figure 4 In some embodiments, the idle tool phase and the machining phase after the feed rate of multiple phases in one cycle of the CNC machine tool are optimized are merged according to the cycle time to obtain a planned optimized multi-stage feed rate database. In some embodiments, for example, the planned optimized multi-stage feed rate database includes the idle tool step-in feed rate f of each phase in multiple phases within one cycle. i1 =100, idle cutter optimized feed rate f i2 =120, machining optimization feed rate f i3 =110, planned to enter processing control time node t i5 The planned control data in the planned optimization multi-stage feed rate database can be uploaded to the CNC machine tool controller for comparison and analysis with the actual processing state data of the CNC machine tool to obtain the difference characteristic data of each stage.

[0052] In some embodiments, the actual processing status data includes actual control time; the expected processing status data includes expected control time; the actual processing status data is compared and analyzed with the expected processing status data corresponding to the planned control data to obtain the difference characteristic data corresponding to each stage, including: comparing the actual control time and the expected control time of each stage to obtain the control time deviation.

[0053] See also Figure 5 、 Figure 6 In some embodiments, the control time deviation can be divided into the control time deviation of the idle knife stage and the control time deviation of the processing stage, and the control time deviation can be obtained through the following steps.

[0054] Step S210: Calculate the planned idle knife control time t i2―i1 and planned processing control time t i4―i3 The calculation of planned idle tool control time and planned machining control time is based on the formula:

[0055] t i2―i1 =t i2 ―t i1

[0056] t i4―i3 =t i4 ―t i3

[0057] Among them, t i2 Indicates the planned end time of empty knife control, t i1 Indicates the planned empty knife control start time node, t i4 Indicates the end time node of planned processing control, t i3 Indicates the time node when planned processing control starts. For example, t i2―i1 =t i4―i3 =1s.

[0058] Step S220: Calculate the actual idle knife control time and actual processing control time The calculation of actual idle tool control time and actual machining control time is based on the formula:

[0059]

[0060] in, Indicates the actual end time of the empty knife control, t i1 Indicates the planned empty knife control start time node, Indicates the actual processing control end time node, t i3 Indicates the start time node of planned processing control. For example,

[0061] In this embodiment, actual machining state data describes the real-time machining state of a CNC machine tool during workpiece machining, including feed rate, actual control time, and power data. Expected machining state data represents the desired machining state after optimizing each stage of the CNC machine tool according to a pre-defined feed rate optimization method. Expected machining state data guides the operation of each stage of the CNC machine tool and includes information such as the desired control time and feed rate. This data serves as reference data for the CNC machine tool control device to analyze and compensate for machining deviations during actual operation.

[0062] Specifically, during the machining process, CNC machine tools are affected by a variety of factors, such as tool wear, material deformation, and machine vibration. Consequently, there is a certain difference between their actual machining state and the desired machining state after optimization according to a pre-set feed rate optimization method. By acquiring actual machining state data in real time and comparing it with the desired machining state data, control time deviations and other differential feature data can be identified. Using these differential feature data, the CNC machine tool control device can further derive compensation data for the CNC machine tool's machining deviations, which can be used to dynamically adjust the machine tool's operating nodes to ensure that each stage of operation is more in line with expectations.

[0063] The compensation strategy in this implementation achieves automatic control by calculating control time deviations and combining them with differential feature data. This control mechanism dynamically adjusts the planned control data during the CNC machine tool's execution of the machining task, enabling the machine to maintain stability and machining accuracy despite power fluctuations in various load stages. Ultimately, the generated time compensation data is input into the planned control data, improving the CNC machine tool's adaptability and accuracy in complex machining environments, while also enhancing machining efficiency.

[0064] In some embodiments, the step of comparing and analyzing the actual processing status data with the expected processing status data corresponding to the planned control data to obtain the difference characteristic data corresponding to each stage also includes: obtaining the control distance deviation based on the control time deviation and feed rate data; using the feed rate data and the control distance deviation to generate the time compensation data; the time compensation data is used to adjust the planned control data; wherein the difference characteristic data includes the time compensation data.

[0065] In this embodiment, the control distance deviation refers to the difference between the feed rate during the CNC machine tool's actual machining process and the feed rate corresponding to the desired machining state after optimizing each machining stage according to a pre-defined feed rate optimization method. This difference is influenced not only by the control time deviation but also by the feed rate data for each stage. Based on the control time deviation and the feed rate data for each stage, the control distance deviation can be calculated and used to generate time compensation data for subsequent control strategies.

[0066] See also Figure 7 In some embodiments, the control distance deviation Δ can be obtained by the following steps. i .

[0067] Step S310: Calculate the planned control distance S i .

[0068] In some embodiments, the feed distance of the CNC machine tool can be obtained by calculating the product of the feed rate and the feed time of the CNC machine tool. The feed rate of the CNC machine tool is in a constantly changing state during actual operation. During the time period when the feed rate of the CNC machine tool changes, the feed rate of the CNC machine tool can be obtained by calculating the trapezoidal area of ​​the feed rate-time graph during the time period of change. i The calculation is based on the formula:

[0069]

[0070] Among them, S i Indicates the planned reverse control feed distance, f i1 Indicates the machining feed rate, f i2Indicates the idle tool feed rate, f i3 Indicates the machining optimization feed rate.

[0071] Step S320: Calculate the actual reverse control feed distance Actual reverse control feed distance The calculation is based on the formula:

[0072]

[0073] Among them, S i Indicates the planned reverse control feed distance, f i1 Indicates the machining feed rate, f i2 Indicates the idle tool feed rate, f i3 Indicates the machining optimization feed rate.

[0074] Step S330: Calculate the control distance deviation Δ in the i-th stage i The control distance deviation Δ in the i-th stage i The calculation is based on the formula:

[0075]

[0076] where t i2―i1 To plan the empty knife control time, ti 4―i3 To plan processing and control time, For actual empty knife control time, is the actual processing control time. i1 Indicates the machining feed rate, f i2 Indicates the idle tool feed rate, f i3 The above-mentioned control distance deviation calculation formula intuitively shows the difference between the actual processing state data of the CNC machine tool and the expected processing state data corresponding to the planned control data. Indicates the control time deviation of the CNC machine tool during the idle tool stage. In some embodiments, Δ can be calculated based on the specific data of the above control process and the calculation process of this step. i =2.

[0077] During the comparison and analysis process, the identification and generation of differential feature data provides a basis for subsequent machining control adjustments. In particular, time compensation data generated by using feed rate override data and control distance deviation can be promptly fed back into the planned control data, enabling the CNC machine tool to dynamically compensate for machining time nodes. This time compensation data is used to adjust the CNC machine tool's operating rhythm, ensuring that the actual execution of each machining phase is more consistent with expectations, thereby optimizing machining accuracy.

[0078] In some embodiments, at the planned processing control end time node ti4 Afterwards, the CNC machine tool optimizes the feed rate f i3 Run, at this time the CNC machine tool control device enters the processing control time node t through the control plan i5 The processing deviation of CNC machine tools can be eliminated. The time compensation data of stage i t iΔ The calculation is based on the formula:

[0079]

[0080] Among them, Δ i represents the control distance deviation in stage i, It represents the time deviation of the idle knife control in the i-th stage, represents the processing control time deviation of stage i. i1 Indicates the machining feed rate, f i2 Indicates the idle tool feed rate, f i3 Indicates the feed rate for machining optimization. The generation process of the time compensation data of the i-th stage reflects the real-time adjustment capability of the CNC machine tool control device during the machining process of the CNC machine tool, that is, the deviation in the machining process is corrected in real time through the time compensation data. In some embodiments, the time compensation data t of the i-th stage can be calculated based on the specific data of the above-mentioned control process and the calculation process of this step. iΔ =0.02s, the first idle knife stage t iΔ =0.

[0081] This embodiment combines feed rate data and control distance deviation to obtain time compensation data for CNC machine tool processing deviations, which is used to adjust the planned control data, enabling effective adjustment of control parameters at each stage during the processing process, making the processing operation more stable and meeting the desired processing goals. Furthermore, the embodiments of the present application can provide a precise and efficient real-time compensation mechanism for CNC machine tools in complex processing environments. This real-time feedback mechanism not only improves the processing accuracy of CNC machine tools, but also improves the efficiency of the processing process.

[0082] In some embodiments, the planned control data includes a planned entry into processing control time node, and the adjusted planned control data includes an adaptive entry into processing control time node; the step of adjusting the planned control data according to the difference feature data, and controlling the CNC machine tool to execute the process of processing the workpiece based on the adjusted planned control data includes: deriving an adaptive entry into processing control time node based on the time compensation data and the planned entry into processing control time node; the adaptive entry into processing control time node is used to control the CNC machine tool to execute the process of processing the workpiece.

[0083] In some embodiments, the i-th stage adaptively enters the processing control time node The calculation is based on the formula:

[0084]

[0085] in, Indicates the time node of adaptive entry into processing control in stage i, t i5 Indicates the time node of the i-th stage plan to enter the processing control, t iΔ Represents the time compensation data of stage i.

[0086] In this embodiment, the time compensation data is used to adjust the time node at which the machine tool plans to enter the processing control. After the feed rate of the CNC machine tool is optimized, the CNC machine tool usually starts each processing stage according to the preset time node. However, during the actual operation of the CNC machine tool, due to the influence of various factors, its actual processing state is often different from the expected state in the planned control data. Based on the planned entry processing control time node and the time compensation data in the planned control data, the time node at which the CNC machine tool starts each processing stage can be adjusted. Specifically, if the time compensation data shows that the time processing speed of the CNC machine tool lags behind the planned speed, the CNC machine tool control device can automatically adjust the start time of the subsequent stage to improve the continuity and efficiency of the entire processing process. This adjustment enables the CNC machine tool control device to dynamically adjust its processing rhythm according to the actual processing situation to adapt to changes in the actual processing state of the machine tool in a complex working environment.

[0087] This embodiment provides a more precise and flexible CNC machine tool control method. This method uses time compensation data to adjust planned control data and then controls the CNC machine tool's workpiece machining process based on the adjusted planned control data. This method dynamically adjusts machining plans based on the CNC machine tool's real-time machining status, significantly enhancing the machine tool's machining flexibility. This not only improves machining accuracy and efficiency, but also optimizes the machine tool's energy consumption and maintenance cycle, reducing its operating costs.

[0088] See also Figure 8 . One embodiment of the present application further provides a CNC machine tool control device, comprising: an acquisition module, configured to acquire actual processing status data of the CNC machine tool in a process of controlling the CNC machine tool to process a workpiece based on planned control data; wherein the planned control data includes control parameters for each stage after the processing cycle is divided into multiple stages; an analysis module, configured to compare and analyze the actual processing status data with the expected processing status data corresponding to the planned control data, and obtain difference feature data corresponding to each stage; an adjustment module, configured to adjust the planned control data according to the difference feature data, and control the CNC machine tool to process the workpiece based on the adjusted planned control data.

[0089] In this embodiment, the specific functions and effects achieved by the CNC machine tool control device can be explained by referring to other embodiments of the present application and will not be repeated here.

[0090] The embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the processor implements the aforementioned CNC machine tool control method.

[0091] The embodiment of the present application further provides a computer program product comprising instructions, which implements the aforementioned CNC machine tool control method when executed by a processor.

[0092] See also Figure 9 An embodiment of the present application may provide an electronic device, comprising: a memory, and one or more processors communicatively connected to the memory; the memory stores instructions executable by the one or more processors, and the instructions are executed by the one or more processors to enable the one or more processors to implement the aforementioned CNC machine tool control method.

[0093] In some embodiments, the electronic device may include a processor, a storage medium, and a communication interface connected by a system bus. The storage medium may store a related computer program.

[0094] The user information or user account information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, etc.) involved in multiple implementation methods of this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0095] It should be understood that the specific examples herein are only intended to help those skilled in the art better understand the embodiments of the present application, rather than to limit the scope of the present invention.

[0096] It can be understood that in the various implementation methods of this application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation method of this application.

[0097] It can be understood that the various embodiments described in this application can be implemented individually or in combination, and the embodiments of this application are not limited to this.

[0098] Unless otherwise indicated, all technical and scientific terms used in the embodiments of the present application have the same meaning as those commonly understood by those skilled in the art in the technical field of the present application. The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit the scope of this application. The term "and / or" used in this application includes any and all combinations of one or more related listed items. The singular forms "a", "above", and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates otherwise.

[0099] It is understood that the processor in the embodiments of the present application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above-mentioned method embodiment can be completed by hardware integrated logic circuits in the processor or software instructions. The above-mentioned processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above-mentioned method.

[0100] It will be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (programmable ROM, PROM), an erasable programmable read-only memory (erasable PROM, EPROM), an electrically erasable programmable read-only memory (EEPROM) or flash memory. The volatile memory may be a random access memory (RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0101] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0102] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, devices and units can refer to the corresponding processes in the aforementioned method implementation methods and will not be repeated here.

[0103] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0104] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of this embodiment.

[0105] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0106] If the function 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 this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling an electronic device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0107] The above description is merely a specific embodiment of the present application, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for controlling a numerically controlled machine tool, characterized in that: The method comprises: Acquiring actual machining state data of the CNC machine tool during the process of controlling the CNC machine tool to process a workpiece based on the planned control data; wherein the planned control data includes control parameters for each stage after the machining cycle is divided into multiple stages; Comparing and analyzing the actual processing state data with the expected processing state data corresponding to the planned control data to obtain difference feature data corresponding to each stage; The planning control data is adjusted according to the difference feature data, and the CNC machine tool is controlled to execute a process of machining a workpiece based on the adjusted planning control data.

2. The method according to claim 1, characterized in that Also includes: Acquiring historical machining power data and historical machining control data generated by the CNC machine tool during the process of machining a workpiece; the historical machining power data includes spindle load data, and the historical machining control data includes feed rate data; Based on the comparison result of the spindle load data and the specified idle tool power threshold, the processing cycle is divided into multiple stages; wherein the multiple stages include an idle tool stage and a processing stage; the spindle load data corresponding to the idle tool stage is less than the specified idle tool power threshold; the spindle load data corresponding to the processing stage is greater than the specified idle tool power threshold; Optimizing the historical processing control data of at least part of the stages to generate the planned control data.

3. The method according to claim 2, characterized in that The planning control data includes feed rate optimization data, the feed rate optimization data corresponds to an idle cut feed rate optimization value and a machining feed rate optimization value, and the idle cut feed rate optimization value is greater than the machining feed rate optimization value; The step of optimizing the historical processing control data of at least part of the stages to generate the planned control data includes: When the spindle load data is less than the specified idle tool power threshold, the feed rate data is increased to obtain the idle tool feed rate optimization value.

4. The method according to claim 2, characterized in that The step of optimizing the actual processing control data of at least part of the stages to generate the planned control data further includes: When the spindle load data is greater than a specified idle tool power threshold and less than a specified hard point power threshold, the feed rate data is reduced to obtain the optimized machining feed rate value.

5. The method according to claim 2, characterized in that The feed rate data corresponds to a reference value, and the reference value of the feed rate data is less than the machining feed rate optimization value; The step of optimizing the actual processing control data of at least part of the stages to generate the planned control data further includes: When the spindle load data is greater than a specified hard point power threshold, the feed rate data is reduced to obtain a reference value of the feed rate data.

6. The method according to claim 1, characterized in that The actual processing state data includes actual control time; the expected processing state data includes expected control time; The step of comparing and analyzing the actual processing state data with the expected processing state data corresponding to the planned control data to obtain the difference feature data corresponding to each stage includes: Compare the actual control time and expected control time in each stage to obtain the control time deviation.

7. The method according to claim 6, characterized in that The step of comparing and analyzing the actual processing state data with the expected processing state data corresponding to the planned control data to obtain the difference feature data corresponding to each stage also includes: Based on the control time deviation and feed rate data, a control distance deviation is obtained; Using the feed rate data and the control distance deviation, the time compensation data is generated; the time compensation data is used to adjust the planning control data; Wherein, the difference feature data includes the time compensation data.

8. The method according to claim 1, characterized in that The planned control data includes a planned entry processing control time node, and the adjusted planned control data includes an adaptive entry processing control time node; The steps of adjusting the planning control data according to the difference feature data, and controlling the CNC machine tool to execute a process of machining a workpiece based on the adjusted planning control data include: Determining an adaptive entry processing control time node based on the time compensation data and the planned entry processing control time node; The self-adaptive entry processing control time node is used to control the process of the CNC machine tool executing the processing of the workpiece.

9. A CNC machine tool control device, characterized in that: include: an acquisition module, configured to acquire actual processing status data of the CNC machine tool during the process of controlling the CNC machine tool to process a workpiece based on the planned control data; wherein the planned control data includes control parameters for each stage after the processing cycle is divided into multiple stages; An analysis module, configured to compare and analyze the actual processing state data with the expected processing state data corresponding to the planned control data, and obtain difference feature data corresponding to each stage; An adjustment module is used to adjust the planning control data according to the difference feature data, and control the CNC machine tool to execute a process of processing a workpiece based on the adjusted planning control data.

10. An electronic device, characterized in that: The electronic device includes a memory and a processor, wherein the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor to implement the CNC machine tool control method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium stores at least one computer program, and when the at least one computer program is executed by a processor, it can implement the CNC machine tool control method according to any one of claims 1 to 8.

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