CNC feed rate optimization method and device for feed shaft load feedback, equipment and medium

Abstract

The invention relates to a CNC feed rate optimization method and device for feed shaft load feedback, equipment and a medium. The method comprises the steps that time sequence data in the first trial cutting machining process of a numerical control machine tool running an original machining program are obtained; performing segmentation association and feature extraction on the feed shaft load data according to the information of each program segment to obtain an actual cutting load value and an original cutting parameter corresponding to each program segment; based on the actual cutting load values and the original cutting parameters corresponding to the program segments with the effective cutting characteristics, a load mapping model reflecting the quantitative relation between the feed shaft load and the cutting parameters is established; calculating a target feed rate corresponding to each program segment according to a preset target load value and a load mapping model; and replacing the feed rate parameter of the corresponding program segment in the original machining program with the target feed rate to generate an optimized machining program. According to the method, the complex working conditions can be automatically adapted, the optimal target feeding rate is generated, and the machining efficiency and the machining quality are improved.

Description

Technical Field

[0001] This invention relates to the field of CNC machining technology, and in particular to a method, apparatus, equipment and medium for optimizing CNC feed rate by feed axis load feedback. Background Technology

[0002] In the field of CNC machining, the various cutting parameters of the machining program (such as feed rate, spindle speed, and cutting depth) are key factors that determine machining efficiency and workpiece quality. In traditional technology, these parameters are usually set empirically by programmers based on part material, tool specifications, and preset post-processing templates.

[0003] To achieve satisfactory machining results, traditional techniques often employ multiple trial cuts combined with manual observation. For example, while the machine tool is running the original machining program, the operator observes the cutting sparks, listens to the cutting sounds, or checks the surface roughness of the workpiece to judge, based on experience, whether the current cutting state is overloaded or too light, and then manually intervenes to adjust the feed rate of the CNC system. After the trial cuts are completed, the programmer modifies the feed rate instructions in the program segment of the machining program based on the feedback results to complete the initial optimization of the machining program.

[0004] However, the above-mentioned solutions have obvious technical limitations. Because they rely heavily on human experience for qualitative judgment, they cannot accurately quantify the real-time physical state during the cutting process, which often leads to conservative or overload risks in the set parameters. Moreover, the manual adjustment process is not only time-consuming, labor-intensive, and extremely inefficient, but also prone to poor consistency of processing parameters due to individual differences in experience. It is difficult to maximize the processing efficiency of the machine tool while ensuring the safety of the machine tool, and it is impossible to achieve refined and automated optimization for complex processing paths. Summary of the Invention

[0005] In view of the above problems, this application provides a CNC feed rate optimization method, apparatus, equipment and medium with feed axis load feedback to solve the above technical problems.

[0006] In a first aspect, the present invention provides a CNC feed rate optimization method based on feed axis load feedback, comprising: Acquire timing data during the initial trial cutting process of the CNC machine tool running the original machining program. The timing data includes feed axis load data and information of each program segment that is time-synchronized with the feed axis load data. Based on the information of each program segment, the feed axis load data is segmented, correlated, and feature extracted to obtain the actual cutting load value and original cutting parameters corresponding to each program segment. Based on the actual cutting load values ​​and original cutting parameters corresponding to each program segment with effective cutting characteristics, a load mapping model reflecting the quantitative relationship between feed axis load and cutting parameters is established. Calculate the target feed rate corresponding to each program segment based on the preset target load value and the load mapping model; An optimized machining program is generated by replacing the feed rate parameter of the corresponding program segment in the original machining program with the target feed rate.

[0007] Secondly, the present invention provides a CNC feed rate optimization device with feed axis load feedback, comprising: The data acquisition module is used to acquire timing data during the initial trial cutting process of the CNC machine tool running the original machining program. The timing data includes feed axis load data and information of each program segment that is time-synchronized with the feed axis load data. The data processing module is used to perform segmented association and feature extraction on the feed axis load data according to the information of each program segment, so as to obtain the actual cutting load value and original cutting parameters corresponding to each program segment; The mapping modeling module is used to establish a load mapping model that reflects the quantitative relationship between feed axis load and cutting parameters based on the actual cutting load value and original cutting parameters corresponding to each program segment with effective cutting characteristics. The feed rate calculation module is used to calculate the target feed rate corresponding to each program segment based on the preset target load value and the load mapping model. The machining program generation module is used to replace the feed rate parameter of the corresponding program segment in the original machining program with the target feed rate to generate an optimized machining program.

[0008] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein: The memory is used to store computer programs; The processor is used to read the program in the memory and execute the steps of the CNC feed rate optimization method with feed axis load feedback as provided in the first aspect above.

[0009] Fourthly, the present invention provides a computer-readable storage medium having a readable computer program stored thereon, which, when executed by a processor, implements the steps of the CNC feed rate optimization method with feed axis load feedback as provided in the first aspect above.

[0010] This invention provides a CNC feed rate optimization method, apparatus, equipment, and medium based on feed axis load feedback. The method synchronizes the feed axis load data acquired during the execution of the original machining program with information from each program segment, extracting the actual cutting load value and original cutting parameters corresponding to each program segment. This establishes a load mapping model reflecting the quantitative relationship between feed axis load and cutting parameters. Subsequently, combined with a preset target load value, the load mapping model is used to calculate a target feed rate matching the current actual cutting conditions, replacing the feed rate parameters in the original machining program. This invention effectively solves the technical problems of inaccurate parameter settings, low adjustment efficiency, and inability to automate optimization for complex machining paths caused by relying solely on manual experience for qualitative judgment of cutting conditions in traditional technologies. This invention can automatically adapt to complex working conditions and generate the optimal target feed rate, maximizing the cutting potential of the machine tool while ensuring the machine tool load remains within a safe range, significantly improving machining efficiency, machining quality, and the level of automated production. Attached Figure Description

[0011] Figure 1 A flowchart of a CNC feed rate optimization method based on feed axis load feedback provided in an embodiment of the present invention.

[0012] Figure 2 The flowchart shows step S300 of the CNC feed rate optimization method with feed axis load feedback provided in the embodiment of the present invention.

[0013] Figure 3 This is a schematic diagram of a CNC feed rate optimization device with feed axis load feedback provided in an embodiment of the present invention.

[0014] Figure 4 This is a schematic diagram of an electronic device provided in an embodiment of the present invention.

[0015] Figure 5 A schematic diagram of a computer storage medium provided in an embodiment of the present invention. Detailed Implementation

[0016] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Preferred embodiments of the invention are shown in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the invention.

[0017] It should be noted that when a component is said to be "fixed to" another component, it can be directly attached to the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0019] This invention provides a CNC feed rate optimization method based on feed axis load feedback. Figure 1 The flowchart of the CNC feed rate optimization method based on feed axis load feedback provided in the embodiments of the present invention is as follows: Figure 1 As shown, the CNC feed rate optimization method based on feed axis load feedback includes the following steps: S100: Acquire timing data during the initial trial cut of the CNC machine tool running the original machining program. This timing data includes feed axis load data and information about each program segment synchronized with the feed axis load data. Optionally, the timing data refers to a set of dynamic data continuously collected in chronological order during the initial trial cut. While the CNC machine tool executes the original machining program, the feed axis load data is acquired in real time, and the information of the program segment being executed by the CNC machine tool at the current moment (e.g., program segment number or code instruction content) is recorded synchronously. By establishing a unified time reference, it is ensured that each set of feed axis load data corresponds one-to-one with the program segment information that generates that load on the time axis, thereby recording the load fluctuations throughout the entire machining program execution process.

[0020] S200: Based on the information of each program segment, the feed axis load data is segmented, correlated, and feature extracted to obtain the actual cutting load value and original cutting parameters corresponding to each program segment. Optionally, using the time synchronization relationship recorded in step S100, the continuous time-series data is divided into multiple execution intervals. An execution interval refers to the time period from when a single program segment is called by the CNC machine tool to when it is completed. The feed axis load data is correlated to the corresponding program segment through the execution intervals. Subsequently, statistical features that characterize the machining state of each program segment are extracted from the feed axis load data corresponding to each program segment as the actual cutting load value, and the original cutting parameters such as the feed rate and depth of cut of that segment are extracted from the original machining program.

[0021] S300: Based on the actual cutting load values ​​and original cutting parameters corresponding to each program segment with effective cutting characteristics, a load mapping model reflecting the quantitative relationship between feed axis load and cutting parameters is established. Optionally, program segments in actual cutting state (i.e., non-idle running state) are first identified from all program segments and defined as sample data with effective cutting characteristics. Then, the variation of actual cutting load values ​​with original cutting parameters in these sample data is analyzed to establish the load mapping model. The load mapping model is used to quantitatively calculate load changes and establish the specific impact of feed rate changes on feed axis load under specific cutting conditions.

[0022] S400: Calculate the target feed rate for each program segment based on the preset target load value and load mapping model. Optionally, the target load value is an ideal load index preset based on the safety load capacity and machining efficiency requirements of the CNC machine tool. After obtaining the load mapping model, the target load value is input as a known condition into the load mapping model for back-calculation. For each specific program segment, based on its original cutting geometry, the feed rate corresponding to achieving the target load value for that segment is calculated using the load mapping model. This calculation result is the target feed rate.

[0023] S500: Replace the feed rate parameters of the corresponding program segments in the original machining program with the target feed rate to generate an optimized machining program. Optionally, replace the original feed rate instructions of each program segment in the original machining program with the target feed rate calculated in step S400, while keeping the machining path instructions and other contents unchanged, thereby reconstructing and outputting a performance-optimized machining program file.

[0024] The CNC feed rate optimization method based on feed axis load feedback provided in this invention synchronously correlates the feed axis load data acquired by the CNC machine tool during the execution of the original machining program with the information of each program segment in time. Based on this, the actual cutting load value and original cutting parameters corresponding to each program segment are extracted, thereby establishing a load mapping model reflecting the quantitative relationship between feed axis load and cutting parameters. Subsequently, combined with a preset target load value, the load mapping model is used to calculate a target feed rate matching the current actual cutting conditions, and this target feed rate replaces the feed rate parameters in the original machining program. This effectively solves the technical problems of inaccurate parameter settings, low adjustment efficiency, and inability to automate optimization for complex machining paths caused by relying solely on manual experience to qualitatively judge the cutting state in traditional technologies. This invention can automatically adapt to complex working conditions and generate the optimal target feed rate, ensuring that the machine tool load remains within a safe range while maximizing the cutting potential of the machine tool, significantly improving machining efficiency, machining quality, and the level of automated production.

[0025] In some embodiments, the CNC feed rate optimization method based on feed axis load feedback provided in this invention includes feed axis load data including current and / or torque data of at least one feed axis motor, or load characterization data obtained based on the current and / or torque data. Optionally, the feed axis load data originates from the drive motors in the CNC machine tool responsible for driving the position changes of each moving axis. During mechanical cutting, the cutting resistance between the tool and the workpiece directly acts on the drive system of the feed axis, causing the motor's operating current or output torque to fluctuate with changes in cutting force. The current percentage or torque feedback value of these drive motors can be read in real time as the feed axis load data through the communication interface of the CNC system. In specific implementation, in order to more comprehensively evaluate the cutting intensity under multi-axis linkage, the collected multi-channel current data or torque data can be mathematically preprocessed to obtain load characterization data. For example, during multi-axis linkage machining, the system synchronously acquires the load component of the X-axis drive motor. Load component of the Y-axis drive motor and the load component of the Z-axis drive motor And use the logic of squares and square roots to perform composite calculations, such as through formulas. By obtaining comprehensive load characterization data or performing normalization processing, load characterization data that comprehensively reflects changes in cutting strength can be obtained. This processing method can transform the complex cutting resistance in space into a unified numerical index, thereby providing more representative and objective data samples for subsequent load mapping model establishment. In addition, the data can also be normalized to map the feedback values ​​of motors of different specifications to a unified dimension, ensuring the universality of the load mapping model.

[0026] By extracting statistical features from the feed axis load data over a time interval, this invention can effectively filter out instantaneous interference and random fluctuations during the machining process, enabling the obtained actual cutting load value to more realistically and stably reflect the actual load level of the interaction between the tool and the workpiece under that program segment.

[0027] In some embodiments, in the CNC feed rate optimization method for feed axis load feedback provided by the present invention, the actual cutting load value is the statistical characteristic value of the feed axis load data within the time interval corresponding to each program segment. The statistical characteristic value includes the average value or the weighted average value. Optionally, the time interval corresponding to each program segment refers to the duration occupied by a single program segment from the start to the end of execution during the first trial cutting process. Since the collected feed axis load data often exhibits dynamic fluctuations due to factors such as tool entry and exit, uneven workpiece material, or mechanical vibration during actual cutting, it is necessary to extract representative load indicators by calculating statistical characteristic values. Specifically, the arithmetic mean of all feed axis load data points collected within the time interval can be calculated to obtain the average value, which is used as the actual cutting load value of the program segment; or different weights can be assigned to the data at different stages within the interval, and the weighted average value can be obtained through weighted average calculation. For example, when executing a linear interpolation program segment, the system obtains the feed axis load data sequence within the corresponding execution time of the segment, removes abnormal fluctuation points at the moment of entry, calculates the average value of the load data in the remaining stable phase, and defines it as the actual cutting load value corresponding to the program segment, so as to eliminate the influence of random noise on load evaluation.

[0028] By extracting statistical features from the feed axis load data over a time interval, this invention can effectively filter out instantaneous interference and random fluctuations during the machining process, enabling the obtained actual cutting load value to more realistically and stably reflect the actual load level of the interaction between the tool and the workpiece under that program segment.

[0029] In some embodiments, the CNC feed rate optimization method with feed axis load feedback provided by this invention includes original cutting parameters such as depth of cut, width of cut, and original feed rate; the load mapping model is a regression model with depth of cut, width of cut, and feed rate as independent variables. Optionally, the depth of cut (axial depth of cut) and width of cut (radial width of cut) together determine the cutting cross-sectional area of ​​the tool during machining, while the original feed rate determines the material removal rate per unit time. These parameters are the core physical variables affecting the fluctuation of feed axis load. When establishing the load mapping model, the system uses the original cutting parameters (including depth of cut, width of cut, and original feed rate) corresponding to each program segment as input independent variables and the synchronously acquired actual cutting load value as the dependent variable. The regression model is used to describe the mathematical logic relationship between these independent and dependent variables. For example, when performing groove machining or stepped surface machining, the depth of cut or width of cut may change in different program segments, causing nonlinear fluctuations in feed axis load. By constructing a regression model, the contribution of feed rate changes to feed axis load under different combinations of depth of cut and width of cut can be analyzed. The load mapping model constructed through regression modeling can not only reflect the influence of a single variable, but also reflect the load characteristics under multi-parameter coupling. This allows for a more accurate prediction of the expected changes in feed axis load after changing the feed rate, providing a scientific calculation model for subsequent calculations of the target feed rate that matches the target load value.

[0030] This invention, by clearly defining the independent variables and model type of the load mapping model, incorporates core geometric and kinematic parameters from cutting mechanics into a quantitative calculation system. Compared to optimization schemes that only consider a single feed rate, this invention considers the substantial impact of cutting depth and width on the load, enabling the load mapping model to adapt to more complex workpiece contours and changing cutting conditions. This significantly improves the accuracy and robustness of the target feed rate calculation, ensuring that the optimized machining program maintains a stable machining load under different cutting depths and widths.

[0031] In some embodiments of the present invention, the CNC feed rate optimization method based on feed axis load feedback is a linear regression model, expressed as: ; in, To predict load values, The cutting depth is [the depth of cut]. The cutting width is... This is the proportionality coefficient. For constant terms, This is the feed rate.

[0032] Optionally, the load mapping model establishes a linear mapping relationship between the product of the depth of cut, width of cut, and feed rate as a comprehensive feature value and the load on the feed axis. Here, the proportionality coefficient reflects the contribution rate of cutting efficiency under a specific tool and material combination, while the constant term represents the basic wear of the feed axis under no-load conditions.

[0033] This invention can transform abstract physical cutting states into precise mathematical expressions. This linear regression model not only shields against interference from machine tool idle wear but also accurately captures the dynamic impact of cutting parameter changes on the load through a proportional coefficient. This provides a high-precision calculation basis for subsequently determining the target feed rate, enabling the optimized machining program to automatically match the optimal feed rate based on different cutting depths and widths. This significantly improves the overall output efficiency of the machine tool while ensuring machining safety.

[0034] In some embodiments, Figure 2 The flowchart of step S300 of the CNC feed rate optimization method with feed axis load feedback provided in the embodiment of the present invention is as follows: Figure 2 As shown, S300: The steps of establishing a load mapping model reflecting the quantitative relationship between feed axis load and cutting parameters based on the actual cutting load values ​​and original cutting parameters corresponding to each program segment with effective cutting characteristics include: S310: Select non-empty cutting program segments from each program segment as sample data with effective cutting characteristics. Optionally, a non-empty cutting program segment refers to a machining path segment where the tool makes substantial contact with the workpiece material and removes material. During the initial trial cutting process, the original machining program may contain a large number of empty run instructions where the tool moves rapidly in the air. The feed axis load generated by these program segments only includes mechanical friction and inertial loads, which cannot reflect the cutting resistance law. Therefore, by identifying the cutting depth and cutting width in the program segments, invalid segments with zero parameters are eliminated, and program segments that truly generate cutting loads are selected as sample data with effective cutting characteristics. For example, selecting multiple actual cutting program segments with different cutting depths or cutting widths can make the sample data cover different machining conditions, thereby ensuring the representativeness of subsequent modeling.

[0035] S320: Regression calculations are performed on the sample data using the least squares method to obtain the proportionality coefficient K and the constant term C. Optionally, the least squares method is a mathematical optimization technique that finds the best function match for the data by minimizing the sum of squared errors. In this embodiment of the invention, the combination of cutting parameters (such as the product of cutting depth, cutting width, and original feed rate) of each sample program segment is used as the independent variable. The corresponding actual cutting load value is used as the dependent variable. Through multiple groups The data points are fitted using least squares to calculate the proportionality coefficient that minimizes the deviation between the predicted load and the actual load. and constant term .

[0036] S330: Establish a load mapping model based on the proportional coefficient K and the constant term C. Optionally, substitute the proportional coefficient and constant term calculated in step S320 into a preset linear function framework to form a complete mathematical expression for the load mapping model. This load mapping model can separate the abstract mechanical transmission loss from the cutting material consumption. The constant term represents the no-load loss of a specific CNC machine tool in the current state (such as guide rail friction, motor excitation, etc.), while the proportional coefficient establishes the proportion of load fluctuation as parameters change.

[0037] As one implementation method, this embodiment of the invention instantiates the load mapping model by analyzing actual machining data from multiple cutting segments. For example, when performing a trial cut on a flat-bottomed aluminum material with a diameter of 6.0 mm, three representative program segments are selected as sample data. The original cutting parameters for segment 1 are: Its actual cutting load value is 60; the original cutting parameters for segment 2 are: Its actual cutting load value is 70; the original cutting parameters for segment 3 are: Its actual cutting load value is 65. Subsequently, the characteristic values ​​corresponding to each segment (i.e., ...) are calculated. The product of these values ​​yields the characteristic value of segment 1 as 2400, segment 2 as 4500, and segment 3 as 3200. The least squares method is then used to perform linear fitting calculations on the above three sets of data points (i.e., the characteristic values ​​and their corresponding actual cutting load values). The linear fitting calculation specifically includes: first, calculating the sample size... Sum of eigenvalues Total load The sum of the products of eigenvalues ​​and loads Sum of squares of eigenvalues Then, according to the least squares formula: and The proportionality coefficient was calculated. Approximately 0.004674, constant term Approximately 49.2642. The final determined load mapping model expression is: .

[0038] This invention, through meticulous screening of sample data and scientific fitting using the least squares method, ensures that the load mapping model is based on real cutting physics. By distinguishing between air cuts and solid cuts, interference from invalid data is eliminated; the optimal proportional coefficient and constant term obtained through the least squares method maximize the restoration of the essential relationship between cutting parameters and feed axis load. This results in a load mapping model with extremely high fitting accuracy and reliability, effectively solving the problem of model inaccuracy caused by high data noise in traditional solutions, and significantly improving the stability of the subsequently generated target feed rate and the execution efficiency of the machining program.

[0039] In some embodiments of the present invention, the CNC feed rate optimization method based on feed axis load feedback provides a target feed rate. Calculate using the following formula: in, The target load value; and when the current program segment is detected. or When the value is zero, the current program segment is determined to be a non-cutting segment, and the feed rate of the program segment is maintained at the original feed rate.

[0040] Optionally, this calculation formula achieves the mapping from the desired load target to the motion parameters of the execution end through the inverse operation of the load mapping model. Target load value Typically, the power is preset based on a percentage of the rated power of the machine tool spindle or feed axis (e.g., set to 85% of the rated load) to ensure efficiency and safety during machining. In the specific calculation process, the cutting geometry parameters of the current program segment are first determined; if the cutting depth... or cutting width If the value is not zero, it indicates that the tool is in a solid cutting state. In this case, the scaling factor can be used. and constant term The optimal feed rate is determined by reverse engineering. If the depth of cut is detected... or cutting width If the value is zero, it is identified as the tool running idle or making tangential avoidance. In this case, no load inversion is performed, and the original feed rate is directly used to ensure the continuity of non-cutting actions.

[0041] For example, in the optimization process of the flat-bottomed aluminum cutting tool in the above embodiments, a target load value is set. The load level is 85 (i.e., 85% of the total load), and the fitted scaling factor is known. Approximately 0.004674, constant term It is approximately 49.2642.

[0042] For section 1 : .

[0043] For section 2 : .

[0044] For section 3 : .

[0045] It should be noted that, in this embodiment, although the original cutting parameters of segment 2 and segment 1 ( and The two are different, but since their product (i.e., the cutting cross-sectional area) is the same... (Section 1 is) Section 2 is Therefore, the target feed rate is derived by inverse calculation based on the load mapping model. The results are identical. This also proves that the load mapping model of this invention can identify the same physical nature of the load under different parameter combinations and give the optimal speed command accordingly.

[0046] Compared to the original feed rate (e.g., the original feed rate of segment 1 is 800 mm / min), the optimized target feed rate achieves a significant improvement while ensuring load safety.

[0047] This invention, through the automatic identification and retention of non-cutting sections, ensures the intelligence and logical rigor of program optimization. This enables the machine tool to operate within its most efficient load range throughout the entire machining cycle, significantly shortening overall machining time and reducing the negative impact on tool life caused by drastic load fluctuations.

[0048] It is understood that the CNC feed rate optimization method based on feed axis load feedback provided in this embodiment of the invention can be developed and executed based on technical carriers such as computer programs, scripting languages, instruction sets, or integrated software systems. These technical carriers can be written in compiled languages ​​(such as C++, C#, Java, etc.) or interpreted scripting languages ​​(such as Python, etc.) and run in the processing unit inside a general-purpose computer, industrial server, embedded controller, or CNC system.

[0049] It should be noted that in actual industrial applications, due to differences in communication protocol standards, data sampling frequencies, and driver feedback mechanisms of CNC machine tool controllers, the method steps described in this embodiment may not be strictly limited to the order or single logical path described in the specification during actual execution. Such adjustments to the logical timing and data processing flow made during actual operation based on system computing resources, hardware response latency, and on-site machining constraints should all be included within the scope of protection of this invention.

[0050] For example, as an implementation example, this invention can construct an automatic feed rate optimization software module integrated into the CNC system. This module is equipped with a graphical user interface (UI) and an underlying load analysis engine. During execution, the operator can directly set the target load value and start the trial cutting monitoring mode through the UI. The platform automatically parses the timing data from the PLC registers and API interfaces, logically calls the least squares regression operator, and automatically generates optimized machining code. Through this platform, the originally complex cutting mechanics calculations can be transformed into visualized load curve monitoring and feed rate prediction. This implementation method, with a software module as the core and a communication protocol driving load feedback and parameter updates, constitutes the specific technical path of the CNC feed rate dynamic closed-loop optimization of this invention.

[0051] Based on the above-described CNC feed rate optimization method using feed axis load feedback, this embodiment of the invention also provides a CNC feed rate optimization device using feed axis load feedback. Figure 3 This is a schematic diagram of a CNC feed rate optimization device with feed axis load feedback provided in an embodiment of the present invention, as shown below. Figure 3 As shown, the device includes: The data acquisition module 100 is used to acquire timing data during the first trial cutting process of the CNC machine tool running the original machining program. The timing data includes feed axis load data and information of each program segment that is time-synchronized with the feed axis load data. The data processing module 200 is used to perform segmented association and feature extraction on the feed axis load data based on the information of each program segment, so as to obtain the actual cutting load value and original cutting parameters corresponding to each program segment. The mapping modeling module 300 is used to establish a load mapping model that reflects the quantitative relationship between feed axis load and cutting parameters based on the actual cutting load value and original cutting parameters corresponding to each program segment with effective cutting characteristics. The feed rate calculation module 400 is used to calculate the target feed rate corresponding to each program segment based on the preset target load value and load mapping model. The machining program generation module 500 is used to replace the feed rate parameter of the corresponding program segment in the original machining program with the target feed rate to generate an optimized machining program.

[0052] For further details regarding the implementation of the above technical solution by each module in the CNC feed rate optimization device with feed axis load feedback, please refer to the description in the CNC feed rate optimization method with feed axis load feedback provided in the above-mentioned embodiments of the invention, which will not be repeated here.

[0053] Based on the above-mentioned CNC feed rate optimization method using feed axis load feedback, this invention also provides an electronic device. Figure 4 A schematic diagram of an electronic device provided in an embodiment of the present invention, such as... Figure 4 As shown, the electronic device 40 provided in this embodiment of the invention includes a processor 41 and a memory 42 coupled to the processor 41. The memory 42 stores a computer program, which, when executed by the processor 41, causes the processor 41 to perform the steps of the CNC feed rate optimization method with feed axis load feedback in the above embodiment.

[0054] For other details regarding the implementation of the above technical solution by the processor 41 in the above electronic device, please refer to the description in the CNC feed rate optimization method with feed axis load feedback provided in the above embodiments of the invention, which will not be repeated here.

[0055] The processor 41 can also be called a CPU (Central Processing Unit). The processor 41 may be an integrated circuit chip with signal processing capabilities. The processor 41 may also be a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor may be a microprocessor, or the processor 41 may be any conventional processor.

[0056] Based on the above-described CNC feed rate optimization method using feed axis load feedback, this embodiment of the invention also provides a computer-readable storage medium 50. Figure 5 A schematic diagram of a computer storage medium provided in an embodiment of the present invention, as shown below. Figure 5As shown, the storage medium 50 stores a readable computer program 51. This computer program 51 can be stored in the storage medium as a software product, including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks or optical disks, ROM (Read-Only Memory), RAM (Random Access Memory), or terminal devices such as computers, servers, mobile phones, and tablets.

[0057] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0058] The above embodiments merely illustrate preferred implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention should be determined by the appended claims.

Claims

1. A CNC feed rate optimization method based on feed axis load feedback, characterized in that, include: Acquire timing data during the initial trial cutting process of the CNC machine tool running the original machining program. The timing data includes feed axis load data and information of each program segment that is time-synchronized with the feed axis load data. Based on the information of each program segment, the feed axis load data is segmented, correlated, and feature extracted to obtain the actual cutting load value and original cutting parameters corresponding to each program segment. Based on the actual cutting load values ​​and original cutting parameters corresponding to each program segment with effective cutting characteristics, a load mapping model reflecting the quantitative relationship between feed axis load and cutting parameters is established. Calculate the target feed rate corresponding to each program segment based on the preset target load value and the load mapping model; An optimized machining program is generated by replacing the feed rate parameter of the corresponding program segment in the original machining program with the target feed rate.

2. The CNC feed rate optimization method based on feed axis load feedback according to claim 1, characterized in that, The feed axis load data includes current and / or torque data of the motor of at least one feed axis, or load characterization data obtained based on the current and / or torque data.

3. The CNC feed rate optimization method based on feed axis load feedback according to claim 1, characterized in that, The actual cutting load value is a statistical characteristic value of the feed axis load data within the time interval corresponding to each program segment, and the statistical characteristic value includes the average value or weighted average value.

4. The CNC feed rate optimization method based on feed axis load feedback according to claim 1, characterized in that, The original cutting parameters include the depth of cut, the width of cut, and the original feed rate; The load mapping model is a regression model with the cutting depth, the cutting width, and the feed rate as independent variables.

5. The CNC feed rate optimization method based on feed axis load feedback according to claim 4, characterized in that, The load mapping model is a linear regression model, and its expression is: ； in, To predict load values, The cutting depth is [the depth of cut]. The cutting width is... This is the proportionality coefficient. For constant terms, This is the feed rate.

6. The CNC feed rate optimization method based on feed axis load feedback according to claim 5, characterized in that, The step of establishing a load mapping model reflecting the quantitative relationship between feed axis load and cutting parameters based on the actual cutting load values ​​and original cutting parameters corresponding to each program segment with effective cutting characteristics includes: Select non-empty cutting program segments from each of the program segments as sample data with effective cutting characteristics; The sample data are regressed using the least squares method to obtain the proportionality coefficient and the constant term. The load mapping model is established based on the scaling factor and the constant term.

7. The CNC feed rate optimization method based on feed axis load feedback according to claim 5, characterized in that, The target feed rate Calculate using the following formula: in, The target load value; and when the current program segment is detected. or When the value is zero, the current program segment is determined to be a non-cutting segment, and the feed rate of the program segment is maintained at the original feed rate.

8. A CNC feed rate optimization device with feed axis load feedback, characterized in that, include: The data acquisition module is used to acquire timing data during the initial trial cutting process of the CNC machine tool running the original machining program. The timing data includes feed axis load data and information of each program segment that is time-synchronized with the feed axis load data. The data processing module is used to perform segmented association and feature extraction on the feed axis load data according to the information of each program segment, so as to obtain the actual cutting load value and original cutting parameters corresponding to each program segment; The mapping modeling module is used to establish a load mapping model that reflects the quantitative relationship between feed axis load and cutting parameters based on the actual cutting load value and original cutting parameters corresponding to each program segment with effective cutting characteristics. The feed rate calculation module is used to calculate the target feed rate corresponding to each program segment based on the preset target load value and the load mapping model. The machining program generation module is used to replace the feed rate parameter of the corresponding program segment in the original machining program with the target feed rate to generate an optimized machining program.

9. An electronic device, characterized in that, Includes memory and processor, wherein: The memory is used to store computer programs; The processor is used to read the computer program in the memory and execute the steps of the CNC feed rate optimization method with feed axis load feedback as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores a readable computer program that, when executed by a processor, implements the steps of the CNC feed rate optimization method with feed axis load feedback as described in any one of claims 1 to 7.

Images