Feeding system agility parameter identification method and device based on Bode diagram, computer readable storage medium and computer program product

Abstract

The invention belongs to the technical field of numerical control, and relates to a Bode diagram-based feed system agility parameter identification method and equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: (1) acquiring a closed-loop Bode diagram of a to-be-identified feed shaft instruction to a workbench; (2) enabling a feeding system to be equivalent to a low-order system; (3) replacing the relation curve of the agility and the speed fluctuation of the feed shaft to be identified with the relation curve of the agility and the speed fluctuation of the equivalent low-order system; and (4) determining a speed fluctuation threshold value of the equivalent low-order system according to processing requirements, and determining a rapid degree parameter conforming to the speed fluctuation threshold value according to a relation curve of the rapid degree and the speed fluctuation of the equivalent low-order system. According to the method, a machine tool operator can accurately identify and optimize the rapid parameters, and the adaptability of the rapid parameters of the feeding system to the machine tool capacity and tasks is improved.

Description

Technical Field

[0001] The present invention belongs to the field of numerical control technology, and more specifically, relates to a method, device, computer-readable storage medium and computer program product for identifying the agility parameters of a feed system based on a Bode diagram, which can solve the problem of setting the agility motion parameters of a machine tool feed system in engineering applications to a certain extent. Background Art

[0002] Currently, CNC machine tools are developing towards high speed and high precision. Under high-speed and high-acceleration conditions, the operational performance of the feed system significantly impacts the machining quality and efficiency. Furthermore, certain new five-axis machine tools, such as etching machines, utilize laser processing, eliminating direct contact between the workpiece and the tool. Therefore, the operational performance of the feed system is a primary factor influencing machining accuracy.

[0003] The acceleration and deceleration parameters of the feed system act on motion control and have a significant impact on the operating performance of the feed system. Increasing the acceleration and agility of the feed instructions can improve processing efficiency, but it will increase the bandwidth, making it more difficult to control the following errors of the CNC machine tool axes and the synthetic linkage trajectory errors, as well as the contour and thickness errors of the workpiece. At the same time, the increase in the excitation components in the instructions can easily arouse vibrations in the machine tool's mechanical structure, increasing the possibility of quality defects such as chatter marks on the workpiece. Therefore, it is necessary to set appropriate acceleration and deceleration parameters according to the working conditions and processing tasks to maximize processing efficiency while meeting the processing requirements.

[0004] Feed system acceleration and deceleration parameters are directly dictated to technicians and machine operators. Currently, most manufacturers rely on these operators to evaluate, set, and adjust based on their experience, lacking a mature system identification solution. Setting agility parameters by adjusting them and observing the actual response requires relevant knowledge and experience from the commissioning personnel. Furthermore, the agility parameters must be adjusted accordingly for different operating conditions, resulting in significant time and labor costs. Some studies have used agility application time matching the machine tool's main vibration frequency to calculate the inflection point where speed fluctuation increases with agility, using this as the agility parameter. This approach does not consider indicator thresholds and cannot adjust the corresponding agility based on actual machining requirements. Furthermore, agility and speed fluctuation, or other evaluation indicators, are not simply positively correlated. During machine operation, actual agility often falls short of the commanded agility, and actual speed fluctuation may exceed the speed fluctuation corresponding to the agility at the inflection point. Therefore, this method cannot accurately calculate agility parameters that meet machining requirements. Summary of the Invention

[0005] In response to the above-mentioned defects or improvement needs of the prior art, the present invention provides a method, device, computer-readable storage medium and computer program product for identifying the agility parameters of a feed system based on a Bode diagram, the purpose of which is to solve the technical problem that the existing method cannot accurately calculate the agility parameters that meet the processing requirements.

[0006] To achieve the above object, according to one aspect of the present invention, a method for identifying agility parameters of a feed system based on a Bode diagram is provided, comprising the following steps:

[0007] (1) Obtain the closed-loop Bode diagram from the feed axis instruction to the workbench;

[0008] (2) Equivalently treating the feed system as a low-order system, including: adjusting system parameters of the low-order system so that the error between the closed-loop Bode diagram amplitude-frequency characteristic curve of the low-order system and the closed-loop Bode diagram amplitude-frequency characteristic curve of the feed system is within a preset range, and the low-order system is considered to be equivalent to the feed system, and the parameters of the low-order system at this time are determined to be the parameters of the equivalent low-order system;

[0009] (3) The relationship curve between the agility and speed fluctuation of the equivalent low-order system is used to replace the relationship curve between the agility and speed fluctuation of the feed axis to be identified;

[0010] (4) Determine the speed fluctuation threshold of the equivalent low-order system according to the processing requirements, and then determine the agility parameter that meets the speed fluctuation threshold based on the relationship curve between the agility and speed fluctuation of the equivalent low-order system.

[0011] Furthermore, in step (2), the system parameters of the low-order system are adjusted through iteration of the optimization algorithm. Specifically, the lose value of the optimization algorithm is reduced to a preset range, so that the error between the closed-loop Bode diagram amplitude-frequency characteristic curve of the low-order system and the closed-loop Bode diagram amplitude-frequency characteristic curve of the feed system meets the preset range, thereby fitting the equivalent low-order system parameters of the target feed system, wherein the calculation method of the lose value is as follows:

[0012]

[0013] Where n is the number of subdivided frequencies, i = 1 to n, A fi ,A oi are the frequency ω in the fitted amplitude-frequency curve of the low-order system and the actual amplitude-frequency curve of the target feed system, respectively. i The corresponding amplitudes respectively.

[0014] Furthermore, the low-order system in step (3) is a second-order system, and the relationship curve between the agility and speed fluctuation of the second-order system is approximately:

[0015]

[0016] where v m is the velocity fluctuation of the equivalent second-order system, which is defined as the maximum value of the peak minus the minimum value of the trough in the actual curve of the velocity S-shaped curve of the equivalent second-order system; ω n ,ξ are the natural frequency and damping of the equivalent second-order system, a,j are the acceleration and agility of the equivalent second-order system, h(t) is the unit step response of the equivalent second-order system, t is the time independent variable, and β is the phase angle.

[0017] Furthermore, in step (1), if the machine tool feed axis is not equipped with a grating ruler, a laser interferometer or a plane grating is used to collect the machine tool worktable data to obtain the Bode diagram.

[0018] Furthermore, in step (2), the feed system is equivalent to a second-order system, and the degree of deviation between the amplitude-frequency characteristic curve of the equivalent second-order system Bode diagram and the amplitude-frequency characteristic curve of the actual Bode diagram is used as the loss value, and the lower the frequency, the greater the corresponding deviation proportion.

[0019] Furthermore, in step (3), it is necessary to ensure that the feed axis can operate normally and the speed fluctuation in the steady speed section is much smaller than the speed fluctuation caused by acceleration and deceleration.

[0020] Furthermore, the agility parameter in step (4) should satisfy the following condition: the speed fluctuations corresponding to all agility values less than the agility parameter should be less than the set speed fluctuation threshold.

[0021] According to another aspect of the present invention, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the aforementioned method for identifying agility parameters of a feed system.

[0022] According to another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for identifying the agility parameter of the feed system as described in any of the above items is implemented.

[0023] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the method for identifying the agility parameter of a feed system as described in any one of the preceding items.

[0024] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0025] (1) The Bode diagram-based feed system agility parameter identification method of the present invention can be used to set the feed axis machining / rapid traverse agility parameters of CNC machine tools. It can make corresponding adjustments based on different machining requirements, identify appropriate agility parameters, and improve the adaptability of the feed system agility parameters to the machine tool capabilities and tasks. An optimization algorithm is also used to improve the efficiency and accuracy of parameter identification.

[0026] (2) The feed system agility parameter identification method based on the Bode diagram of the present invention can be integrated into the numerical control system, and the machine tool operator can easily and quickly determine the feed axis agility parameter, which reduces the experience and professional knowledge requirements of the machine tool operator.

[0027] (3) The method for identifying the agility parameters of the feed system based on the Bode diagram of the present invention approximates the feed system as a low-order system, and can quickly and easily obtain the relationship curve between the agility parameter and the speed fluctuation through the formula. At the same time, the influence of other motion parameters on the response of the feed system can also be approximately determined by referring to this method. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 1. A flow chart of a method for identifying agility parameters of a feed system based on a Bode diagram according to a preferred embodiment of the present invention;

[0029] Figure 2 A simulation model of a CNC machine tool feed system built using Simulink used in the preferred embodiment of the present invention;

[0030] Figure 3 A comparison diagram of the amplitude-frequency curve of the model Bode diagram and the fitted Bode diagram in a preferred embodiment of the present invention;

[0031] Figure 4 1 is a comparison diagram of the actual and fitted agility and speed fluctuation relationship curves of an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0033] A preferred method for identifying the agility parameters of a feed system based on a Bode diagram of the present invention mainly includes the following steps:

[0034] (1) Obtain the closed-loop Bode diagram from the feed axis command to the worktable by sweeping the frequency with a sine wave or chirp wave.

[0035] (2) By using an optimization algorithm, the low-order system Bode diagram amplitude-frequency curve is fitted with the closed-loop Bode diagram amplitude-frequency curve obtained in step (1) to determine the low-order system parameters.

[0036] (3) The relationship curve between the agility of the low-order system and the speed fluctuation is determined according to the formula, which is approximately the relationship curve between the agility of the feed axis to be identified and the speed fluctuation.

[0037] (4) Determine the threshold value according to the processing requirements, and then determine the corresponding speed parameter according to the relationship curve.

[0038] Preferably, the closed-loop Bode diagram described in step (1) needs to be able to truly reflect the changing trend, peak frequency and corresponding amplitude of the feed shaft amplitude-frequency curve; if the machine tool feed shaft is not equipped with a grating scale, a laser interferometer or a plane grating can be used to collect the machine tool worktable data to obtain the Bode diagram.

[0039] Preferably, the optimization algorithm used in step (2) needs to use the degree of deviation between the amplitude-frequency characteristic curve of the fitted Bode diagram and the amplitude-frequency characteristic curve of the actual Bode diagram as the loss value, and the lower the frequency, the greater the corresponding deviation proportion.

[0040] Preferably, the accuracy of the curve fitting of the relationship between agility and speed fluctuation described in step (3) is related to the feed shaft state and system characteristics. In order to obtain relatively accurate results, it is necessary to ensure that the feed shaft can operate normally and the fluctuation in the steady speed section is much smaller than the speed fluctuation caused by acceleration and deceleration.

[0041] Preferably, the determination of the agility parameter according to the threshold value and the relationship curve in step (4) needs to ensure that the speed fluctuations corresponding to all agility values less than the agility parameter are less than the set threshold value.

[0042] Taking the second-order system in the low-order system as an example, the specific implementation steps of the present invention are described as follows:

[0043] (1) Obtain the amplitude-frequency characteristic curve of the closed-loop Bode diagram of the feed system model through methods such as sinusoidal wave sweeping or chirp wave sweeping.

[0044] (2) The feed system is equivalent to a second-order system as follows:

[0045] A typical second-order system is introduced. Through optimization algorithms such as PSO or PPSO, the system parameters of the second-order system are adjusted so that the closed-loop Bode diagram amplitude-frequency characteristic curve of the second-order system is similar to the closed-loop Bode diagram amplitude-frequency characteristic curve of the feed system (for example, the error is within a preset range). At this time, the second-order system is considered equivalent to the feed system, and the second-order system parameters at this time are determined to be the parameters of the equivalent second-order system. The maximum value of the frequency range fitted by the optimization algorithm is set to twice the lowest natural frequency. The calculation method of the loss value used by the optimization algorithm is:

[0046]

[0047] Where n is the number of subdivided frequencies, i = 1 to n, A fi ,A oi are the frequency ω in the fitted amplitude-frequency curve of the second-order system and the actual amplitude-frequency curve of the target feed system, respectively. i The corresponding amplitudes (the fitting results of the Bode diagram amplitude-frequency characteristic curve are as follows Figure 3 The optimization algorithm makes the lose value as small as possible through iteration, thereby optimizing the second-order system parameters, fitting the target feed system, and obtaining the equivalent second-order system corresponding to the target feed system.

[0048] (3) The relationship curve between the agility and speed fluctuation of the equivalent low-order system is used to replace the relationship curve between the agility and speed fluctuation of the feed axis to be identified;

[0049] In a preferred embodiment, the speed S-curve planning is used for illustration, and the relationship between the speed fluctuation and agility of the equivalent second-order system is approximately as follows:

[0050]

[0051] where v m is the velocity fluctuation of the equivalent second-order system, which is defined as the maximum value of the peak minus the minimum value of the trough in the actual curve of the velocity S-shaped curve of the equivalent second-order system; ω n ,ξ are the natural frequency and damping of the equivalent second-order system, a,j are the acceleration and agility of the equivalent second-order system, respectively. h(t) is the unit step response of the equivalent second-order system, expressed as:

[0052]

[0053] Where t is the time independent variable and β is the phase angle.

[0054] According to the above formula, the relationship curve between the agility and speed fluctuation of the equivalent second-order system can be calculated, which is compared with the relationship curve between the agility and speed fluctuation of the feed axis to be identified by changing the agility parameters by enumeration method. Figure 4 shown.

[0055] (4) The speed fluctuation threshold of the equivalent second-order system is set according to the processing requirements, and then the agility parameter corresponding to the equivalent second-order system within the speed fluctuation threshold range is determined according to the relationship curve between the agility and speed fluctuation of the equivalent second-order system. The agility parameter should meet the following conditions: the speed fluctuation corresponding to all agility values less than the agility parameter should be less than the set speed fluctuation threshold.

[0056] In summary, this invention uses a loss function-based algorithm optimization and Bode plots to fit the actual feed system using a low-order system. This method further derives an approximate relationship curve between agility and speed fluctuation. The agility parameter is then determined by setting a threshold based on actual machining requirements. This allows machine tool operators to accurately identify and optimize the agility parameter, improving the adaptability of the feed system's agility parameters to the machine tool's capabilities and tasks.

[0057] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for identifying agility parameters of a feed system based on Bode diagram, characterized in that: The steps include: (1) Obtain the closed-loop Bode diagram from the feed axis instruction to the workbench; (2) Equivalently treating the feed system as a low-order system, including: adjusting system parameters of the low-order system so that the error between the closed-loop Bode diagram amplitude-frequency characteristic curve of the low-order system and the closed-loop Bode diagram amplitude-frequency characteristic curve of the feed system is within a preset range, and the low-order system is considered to be equivalent to the feed system, and the parameters of the low-order system at this time are determined to be the parameters of the equivalent low-order system; (3) The relationship curve between the agility and speed fluctuation of the equivalent low-order system is used to replace the relationship curve between the agility and speed fluctuation of the feed axis to be identified; (4) Determine the speed fluctuation threshold of the equivalent low-order system according to the processing requirements, and then determine the agility parameter that meets the speed fluctuation threshold based on the relationship curve between the agility and speed fluctuation of the equivalent low-order system.

2. The method for identifying agility parameters of a feed system based on a Bode diagram according to claim 1, wherein: In step (2), the system parameters of the low-order system are adjusted by iterative optimization algorithm. Specifically, the lose value of the optimization algorithm is reduced to a preset range, so that the error between the closed-loop Bode diagram amplitude-frequency characteristic curve of the low-order system and the closed-loop Bode diagram amplitude-frequency characteristic curve of the feed system meets the preset range, thereby fitting the equivalent low-order system parameters of the target feed system. The calculation method of the lose value is as follows: Where n is the number of subdivided frequencies, i = 1 to n, A fi ,A oi are the frequency ω in the fitted amplitude-frequency curve of the low-order system and the actual amplitude-frequency curve of the target feed system, respectively. i The corresponding amplitudes respectively.

3. The method for identifying agility parameters of a feed system based on a Bode diagram according to claim 1, wherein: The low-order system in step (3) is a second-order system. The relationship curve between the agility and speed fluctuation of the second-order system is approximately: where v m is the velocity fluctuation of the equivalent second-order system, which is defined as the maximum value of the peak minus the minimum value of the trough in the actual curve of the velocity S-shaped curve of the equivalent second-order system; ω n ,ξ are the natural frequency and damping of the equivalent second-order system, a,j are the acceleration and agility of the equivalent second-order system, h(t) is the unit step response of the equivalent second-order system, t is the time independent variable, and β is the phase angle.

4. A method for identifying agility parameters of a feed system based on a Bode diagram according to any one of claims 1 to 3, characterized in that: In step (1), if the machine tool feed axis is not equipped with a grating ruler, a laser interferometer or a plane grating is used to collect the machine tool table data to obtain the Bode diagram.

5. The method for identifying agility parameters of a feed system based on a Bode diagram according to any one of claims 1 to 3, characterized in that: In step (2), the feed system is equivalent to a second-order system. The degree of deviation between the amplitude-frequency characteristic curve of the equivalent second-order system Bode diagram and the amplitude-frequency characteristic curve of the actual Bode diagram is used as the loss value, and the lower the frequency, the greater the corresponding deviation proportion.

6. A method for identifying agility parameters of a feed system based on a Bode diagram according to any one of claims 1 to 3, characterized in that: In step (3), it is necessary to ensure that the feed axis can operate normally and the speed fluctuation in the steady speed section is much smaller than the speed fluctuation caused by acceleration and deceleration.

7. A method for identifying agility parameters of a feed system based on a Bode diagram according to any one of claims 1 to 3, characterized in that: The agility parameter in step (4) should satisfy the following condition: the speed fluctuations corresponding to all agility values less than the agility parameter should be less than the set speed fluctuation threshold.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the method for identifying agility parameters of a feed system according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for identifying the agility parameters of the feed system according to any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for identifying the agility parameters of the feed system according to any one of claims 1 to 7 is implemented.

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