Dynamic balance testing method and system for grinding wheel assembly

Abstract

The invention relates to the technical field of mechanical dynamic balance testing, and discloses a dynamic balance testing method and system for a grinding wheel assembly, and the method comprises the steps: combining the geometric characteristics and material characteristics of the grinding wheel assembly; establishing a non-uniformity correction model; acquiring frequency domain characteristics of the vibration signals; correcting the vibration signal to obtain a non-uniformity corrected vibration signal; constructing a dynamic unbalance point optimization objective function; the mass distribution of the grinding wheel assembly is optimized; and carrying out dynamic balance performance verification on the optimized grinding wheel assembly. Compared with the prior art that the technical problem of eccentric distribution caused by non-uniformity of material density is difficult to accurately solve under the condition of high-speed rotation of a grinding wheel assembly, the method has the advantages that the correction capability of non-uniform distribution of the material density is improved by establishing a correction model of the non-uniformity of the material density and combining a dynamic correction method of a vibration signal; therefore, the vibration problem caused by eccentricity is avoided, and the dynamic balance test precision of the grinding wheel assembly is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of mechanical dynamic balance testing, and particularly relates to a dynamic balance testing method and system for a grinding wheel assembly. Background Art

[0002] Currently, during the dynamic balance testing of a grinding wheel assembly, the problem of eccentric distribution caused by uneven material density distribution has not been effectively solved. For example, existing technologies usually adopt an unbalance point positioning method based on vibration signal acquisition and simple calculation, but fail to fully consider the density non-uniformity of the grinding wheel assembly material and its influence on mass distribution, resulting in difficulty in accurately positioning the mass, eccentricity distance, and angle of the unbalance point under high-speed rotation conditions. Especially under complex material density distribution or high-speed rotation states of the assembly, traditional methods cannot meet the requirements of high-precision dynamic balance testing due to the accumulation of measurement errors. Therefore, there is an urgent need for a method that can still achieve high-precision positioning of unbalance points and optimized counterweight adjustment while considering the influence of material density non-uniformity, so as to improve the dynamic balance performance and testing reliability of the grinding wheel assembly under high-speed rotation conditions. Summary of the Invention

[0003] Aiming at the above-mentioned technical deficiencies, the purpose of the present invention is to propose a dynamic balance testing method for a grinding wheel assembly, aiming to solve the technical problem in the prior art that it is difficult to accurately solve the eccentric distribution caused by material density non-uniformity under the high-speed rotation condition of the grinding wheel assembly.

[0004] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a dynamic balance testing method for a grinding wheel assembly,

[0005] The dynamic balance testing method for the grinding wheel assembly includes:

[0006] Step S10: According to the geometric characteristics of the grinding wheel assembly, including the outer diameter d, thickness h, and central axis z, combined with the material characteristics of the grinding wheel assembly, including density and elastic modulus E, simulate the dynamic characteristics of the grinding wheel assembly under high-speed rotation by finite element analysis (FEA) and establish a material non-uniformity correction model, where the non-uniformity correction model is described by the following formula:

[0007]

[0008] Where ρ(x, y, z) is the value of the material density of the grinding wheel assembly at the spatial point (x, y, z); ρ 0 is the reference density of the material of the grinding wheel assembly; (x, y, z) is the spatial coordinate used to describe the spatial position of any point inside the grinding wheel assembly; ∈ is the non-uniformity amplitude correction coefficient used to reflect the deviation of the material density; ε is the material density deviation correction coefficient; is the density fluctuation characteristic in the radial direction; is the density fluctuation characteristic in the thickness direction; is the density fluctuation characteristic in the direction of the rotation axis; δ is the dynamic stress caused by the high-speed rotation of the grinding wheel assembly;

[0009] Step S20: While the grinding wheel assembly rotates at the rated speed ω, collect the vibration signal of the grinding wheel assembly at time t through a multi-directional vibration sensor, and perform a fast Fourier transform on the collected vibration signal to obtain the frequency-domain characteristic a(t) of the vibration signal of the grinding wheel assembly. Based on the value ρ(x, y, z) of the material density of the grinding wheel assembly obtained in Step S10 at the spatial point (x, y, z), correct the frequency-domain characteristic a(t) of the vibration signal of the grinding wheel assembly to obtain the non-uniformity corrected vibration signal F corrected (x, y, z, t);

[0010] Step S30: Combine the value of the material density of the grinding wheel assembly at the spatial point (x, y, z) obtained in Step S10 and the non-uniformity corrected vibration signal F corrected (x, y, z, t) to construct an optimization objective function for dynamic unbalance points; use the particle swarm optimization algorithm to iteratively solve the optimization objective function of the unbalance points to determine the unbalance point parameters at time t, including the unbalance point mass, the unbalance point eccentricity distance, and the unbalance point rotation angle;

[0011] Step S40: Obtain the vibration force F(t) to be compensated at time t according to the frequency-domain characteristic a(t) of the vibration signal of the grinding wheel assembly, calculate the counterweight adjustment amount Δm(t) by combining the unbalance point parameters at time t calculated in Step S30, and automatically add or remove the calculated counterweight adjustment amount Δm(t) at the unbalance point position to obtain a grinding wheel assembly with an optimized mass distribution;

[0012] Step S50: After obtaining the grinding wheel assembly with an optimized mass distribution, repeat Step S20 to obtain an optimized non-uniformity corrected vibration signal and compare it with a preset standard non-uniformity corrected vibration signal to generate a dynamic balance test report.

[0013] Preferably, in Step S20, the calculation formula for the non-uniformity corrected vibration signal F corrected (x, y, z, t) is F corrected (x, y, z, t) = ρ(x, y, z) · a(t) · w t , where w t is the weighting coefficient at time t.

[0014] Preferably, the calculation formula for the weighting coefficient w t at time t is:

[0015]

[0016] where f is the vibration frequency at time t, and α t is the weight adjustment coefficient, β is the frequency deviation sensitivity control parameter, and f target is the preset reference frequency.

[0017] Preferably, in step S30, the dynamic unbalance point optimization objective function is:

[0018]

[0019] where P is the dynamic unbalance point optimization objective function; ρ(x i , y i , z i ) is the density of the i-th unbalance point; m i is the mass of the i-th unbalance point; d i is the eccentricity distance of the i-th unbalance point; F measured,i is the non-uniformity correction vibration signal measured at the i-th unbalance point; λ is the regularization coefficient; N is the total number of preset unbalance samplings; and M total is the total mass of the grinding wheel assembly.

[0020] Preferably, in step S40, the calculation formula for the counterweight adjustment amount Δm(t) is: where is the vibration force influence coefficient; and d i is the eccentricity distance of the i-th unbalance point.

[0021] Preferably, in step S40, the calculation formula for the vibration force F(t) to be compensated at time t is F(t) = M effective ·a(t), where M effective is the effective mass of the grinding wheel assembly, which is determined by the geometric characteristics and material characteristics of the grinding wheel assembly.

[0022] Preferably, in step S50, the content of the dynamic balance test report includes the comparison data of the non-uniformity correction vibration signals before and after optimizing the mass distribution, and the specific positions of the unbalance points before optimizing the mass distribution and the corresponding counterweight adjustment amounts.

[0023] The present invention also provides a dynamic balance test system for a grinding wheel assembly, including:

[0024] A material non-uniformity correction model establishment module, configured to simulate the dynamic characteristics of the grinding wheel assembly in a high-speed rotation state by finite element analysis (FEA) according to the geometric characteristics of the grinding wheel assembly, including the outer diameter d, thickness h, and central axis z, and in combination with the material characteristics of the grinding wheel assembly, including density and elastic modulus E, and establish a material non-uniformity correction model, where the non-uniformity correction model is described by the following formula:

[0025]

[0026] Among them, ρ(x, y, z) is the value of the material density of the grinding wheel assembly at the spatial point (x, y, z); ρ 0 is the reference density of the material of the grinding wheel assembly; (x, y, z) are spatial coordinates used to describe the spatial position of any point inside the grinding wheel assembly; ∈ is the inhomogeneity amplitude correction coefficient used to reflect the deviation of the material density; ε is the material density deviation correction coefficient; is the density fluctuation characteristic in the radial direction; is the density fluctuation characteristic along the thickness direction; is the density fluctuation characteristic in the direction of the rotation axis; δ is the dynamic stress caused by the high-speed rotation of the grinding wheel assembly;

[0027] The vibration signal acquisition and correction module is used to collect the vibration signal of the grinding wheel assembly at time t through a multi-directional vibration sensor when the grinding wheel assembly rotates at the rated speed ω, and perform a fast Fourier transform on the collected vibration signal to obtain the frequency-domain characteristic a(t) of the vibration signal of the grinding wheel assembly. Based on the value ρ(x, y, z) of the material density of the grinding wheel assembly at the spatial point (x, y, z) obtained in step S10, the frequency-domain characteristic a(t) of the vibration signal of the grinding wheel assembly is corrected to obtain the inhomogeneity-corrected vibration signal F corrected (x, y, z, t);

[0028] The dynamic optimization and unbalance point parameter solving module is used to combine the value of the material density of the grinding wheel assembly at the spatial point (x, y, z) obtained in step S10 and the inhomogeneity-corrected vibration signal F corrected (x, y, z, t) obtained in step S20 to construct a dynamic unbalance point optimization objective function; use the particle swarm optimization algorithm to iteratively solve the unbalance point optimization objective function to determine the unbalance point parameters at time t, including the unbalance point mass, the unbalance point eccentricity distance, and the unbalance point rotation angle;

[0029] The counterweight adjustment and mass optimization module is used to obtain the vibration force F(t) to be compensated at time t according to the frequency-domain characteristic a(t) of the vibration signal of the grinding wheel assembly, calculate the counterweight adjustment amount Δm(t) in combination with the unbalance point parameters at time t calculated in step S30, and automatically add or remove the calculated counterweight adjustment amount Δm(t) at the unbalance point position to obtain a grinding wheel assembly with an optimized mass distribution;

[0030] The dynamic balance test report generation module is used to, after obtaining the grinding wheel assembly with an optimized mass distribution, repeat step S20 to obtain an optimized inhomogeneity-corrected vibration signal and compare it with a preset standard inhomogeneity-corrected vibration signal to generate a dynamic balance test report.

[0031] The present invention also provides a computer program product, including a dynamic balance test program for a grinding wheel assembly. When the dynamic balance test program for the grinding wheel assembly is executed by a processor, the dynamic balance test method for the grinding wheel assembly as described above is implemented.

[0032] The beneficial effects of the present invention are as follows: Compared with the prior art in which it is difficult to accurately solve the technical problem of eccentric distribution caused by non-uniform material density under the condition of high-speed rotation of the grinding wheel assembly, the present invention improves the correction ability for uneven material density distribution by establishing a correction model for non-uniform material density and combining a dynamic correction method for vibration signals, thereby avoiding vibration problems caused by eccentricity and improving the dynamic balance test accuracy of the grinding wheel assembly. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0034] Figure 1 It is a schematic flowchart of the first embodiment of a dynamic balance test method for a grinding wheel assembly of the present invention.

[0035] Figure 2 It is a schematic diagram of the equipment for a dynamic balance test method for a grinding wheel assembly of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0037] Embodiment 1: As Figure 1 shown, it is a schematic flowchart of the first embodiment of the dynamic balance test method for a grinding wheel assembly of the present invention, and the first embodiment of the dynamic balance test method for a grinding wheel assembly of the present invention is proposed.

[0038] In the first embodiment, the dynamic balance test method for the grinding wheel assembly includes:

[0039] Step S10: According to the geometric characteristics of the grinding wheel assembly, including the outer diameter d, thickness h, and central axis z, and combining with the material characteristics of the grinding wheel assembly, including density and elastic modulus E, simulate the dynamic characteristics of the grinding wheel assembly in a high-speed rotation state through finite element analysis (FEA) and establish a material non-uniformity correction model. The non-uniformity correction model is described by the following formula:

[0040]

[0041] where ρ(x, y, z) is the value of the grinding wheel assembly material density at the spatial point (x, y, z); ρ 0 is the reference density of the grinding wheel assembly material; (x, y, z) are the spatial coordinates used to describe the spatial position of any point inside the grinding wheel assembly; ∈ is the non-uniformity amplitude correction coefficient used to reflect the deviation of the material density; ε is the material density deviation correction coefficient; is the density fluctuation characteristic in the radial direction; is the density fluctuation characteristic along the thickness direction; is the density fluctuation characteristic in the direction of the rotation axis; δ is the dynamic stress caused by the high-speed rotation of the grinding wheel assembly;

[0042] It should be understood that traditional dynamic balance testing methods usually introduce significant errors in the vibration signal due to the failure to consider the spatial non-uniformity of the material density distribution, resulting in insufficient positioning accuracy of the unbalance point parameters. However, through the density correction model established in the present invention, the dynamic distribution characteristics of the material density can be accurately described at spatial points. Further combined with the vibration signal correction method, it can significantly reduce the problem of frequency-domain signal distortion caused by material non-uniformity, especially for the complex dynamic stress caused by the high-speed rotation state.

[0043] Step S20: Collect the vibration signal of the grinding wheel assembly at time t through a multi-directional vibration sensor when the grinding wheel assembly rotates at the rated speed ω, and perform a fast Fourier transform on the collected vibration signal to obtain the frequency-domain characteristics a(t) of the grinding wheel assembly vibration signal. Based on the value ρ(x, y, z) of the grinding wheel assembly material density at the spatial point (x, y, z) obtained in Step S10, correct the frequency-domain characteristics a(t) of the grinding wheel assembly vibration signal to obtain the non-uniformity corrected vibration signal F corrected (x, y, z, t);

[0044] It should be noted that when the grinding wheel assembly rotates at a high speed, due to the non-uniformity of material density, error signals related to material properties will be superimposed on the vibration signals. These errors mainly come from the eccentric force and dynamic stress effects caused by uneven density distribution, which directly affect the accuracy of the frequency-domain signals. By correcting the frequency-domain characteristics of the collected vibration signals using the material density correction model obtained in step S10, the signal distortion caused by material non-uniformity can be effectively compensated, and the non-uniformity-corrected vibration signal that truly reflects the dynamic characteristics of the grinding wheel assembly can be obtained.

[0045] It can be understood that the corrected signal can truly reflect the vibration response characteristics of the grinding wheel assembly, thus providing a reliable basis for the accurate positioning of the dynamic unbalance point.

[0046] Step S30: Combine the value of the material density of the grinding wheel assembly at the spatial point (x, y, z) obtained in step S10 and the non-uniformity-corrected vibration signal F corrected (x, y, z, t) to construct an optimization objective function for the dynamic unbalance point; use the particle swarm optimization algorithm to determine the unbalance point parameters at time t by iteratively solving the unbalance point optimization objective function, including the unbalance point mass, the unbalance point eccentricity distance, and the unbalance point rotation angle;

[0047] It should be noted that during the dynamic balance test, the eccentric distribution of the grinding wheel assembly caused by material density non-uniformity will trigger complex dynamic vibration phenomena. To accurately determine the parameters of the unbalance point, in this step, an optimization objective function for the dynamic unbalance point is constructed by combining the material density correction model established in step S10 and the corrected vibration signal in step S20, and the particle swarm optimization algorithm is used. By iteratively solving the objective function, the key parameters of the unbalance point can be accurately calculated under the dynamic condition at time t.

[0048] It should be understood that traditional methods cannot fully consider the dual effects of material density non-uniformity and dynamic signal correction, resulting in a large positioning error for the unbalance point parameters. However, the dynamic optimization model constructed in this step not only incorporates the material density correction model but also combines the dynamic signal correction at time t, which can greatly improve the positioning accuracy of the unbalance point parameters.

[0049] Step S40: Obtain the vibration force F(t) to be compensated at time t according to the frequency-domain characteristics a(t) of the vibration signal of the grinding wheel assembly, calculate the counterweight adjustment amount Δm(t) by combining the unbalance point parameters at time t calculated in step S30, and automatically add or remove the calculated counterweight adjustment amount Δm(t) at the unbalance point position to obtain an optimized mass distribution grinding wheel assembly;

[0050] It should be understood that traditional dynamic balance adjustment methods usually calculate by experience or manually adjust the counterweight, and it is difficult to accurately compensate for the vibration force under complex density distributions and dynamic conditions. However, this step adopts a counterweight adjustment method based on the parameters of the unbalanced point obtained by dynamic optimization and the real-time vibration force, which can significantly improve the accuracy and adjustment efficiency of the counterweight. For example, the deviation between the calculated counterweight and the actual compensation requirement can be controlled within 1%, and the automatically adjusted counterweight position can ensure the rapid recovery of the dynamic balance performance.

[0051] Step S50: After obtaining the optimized mass distribution grinding wheel assembly, repeat Step S20 to obtain the optimized non-uniformity corrected vibration signal and compare it with the preset standard non-uniformity corrected vibration signal to generate a dynamic balance test report.

[0052] It should be noted that after completing the counterweight adjustment of the optimized mass distribution grinding wheel assembly, by repeating the vibration signal acquisition and correction method of Step S20, the optimized non-uniformity corrected vibration signal can be obtained. Comparing this signal with the preset standard non-uniformity corrected vibration signal can comprehensively evaluate the effect of the optimization adjustment. By comparing the characteristics of the vibration signals before and after optimization, the improvement degree of the dynamic balance performance of the grinding wheel assembly can be verified, and a comprehensive dynamic balance test report can be generated based on this.

[0053] It should be understood that traditional dynamic balance tests only rely on the amplitude of the adjusted vibration signal as the evaluation criterion and cannot fully reflect the impact of material density non-uniformity on dynamic balance performance. By combining the standard non-uniformity corrected signal as a reference, this method can comprehensively verify the balance effect in terms of signal amplitude, frequency domain characteristics, and dynamic response, thus providing a more scientific basis for the optimization of the grinding wheel assembly. At the same time, the automatically generated dynamic balance test report includes a comparison of key performance indicators, which can significantly improve the reliability and traceability of the test results.

[0054] In addition, a dynamic balance test system for a grinding wheel assembly provided by the present invention adopts the dynamic balance test method for a grinding wheel assembly in the above-mentioned embodiment, and can solve the technical problem of the dynamic balance test of a grinding wheel assembly. Compared with the prior art, the beneficial effects of the dynamic balance test system for a grinding wheel assembly provided by the present invention are the same as those of the dynamic balance test method for a grinding wheel assembly provided in the above-mentioned embodiment, and other technical features in the dynamic balance test system for a grinding wheel assembly are the same as the features disclosed in the method of the above-mentioned embodiment, and will not be elaborated here.

[0055] The present invention provides a dynamic balance test device for a grinding wheel assembly. Please refer to Figure 2, A dynamic balance testing device for a grinding wheel assembly includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute a dynamic balance testing method for a grinding wheel assembly in Embodiment 1 above. The dynamic balance testing device for a grinding wheel assembly in an embodiment of the present invention may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. The dynamic balance testing device for a grinding wheel assembly is merely an example and should not impose any limitations on the functions and scope of use of the embodiments of the present invention. The dynamic balance testing device for a grinding wheel assembly may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the dynamic balance testing device for a grinding wheel assembly are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the dynamic balance testing device for a grinding wheel assembly to communicate with other devices wirelessly or wiredly to exchange data. Although a dynamic balance testing device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems may be implemented or had alternatively.

[0056] The present invention also provides a computer program product, including a computer program which, when executed by a processor, implements the steps of a dynamic balance test method for a grinding wheel assembly as described above. The computer program product provided by the present invention can solve the technical problem of dynamic balance test for a grinding wheel assembly. Compared with the prior art, the beneficial effects of the computer program product provided by the present invention are the same as those of the dynamic balance test method for a grinding wheel assembly provided in the above embodiments, and will not be elaborated herein.

[0057] In particular, according to the embodiments disclosed by the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment disclosed by the present invention includes a computer program product which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by a processing device 1001, it executes the above functions defined in the methods of the embodiments disclosed by the present invention.

[0058] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0059] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these changes and modifications.

Claims

1. A dynamic balance test method for a grinding wheel assembly, characterized in that: Methods include: Step S10: According to the geometric characteristics of the grinding wheel assembly, including the outer diameter d, the thickness h and the central axis z, combined with the material characteristics of the grinding wheel assembly, including the density and the elastic modulus E, the dynamic characteristics of the grinding wheel assembly under high-speed rotation are simulated by finite element analysis FEA and a material inhomogeneity correction model is established, wherein the inhomogeneity correction model is described by the following formula: Among them, ρ(x, y, z) is the value of the grinding wheel assembly material density at the spatial point (x, y, z); ρ0 is the reference density of the grinding wheel assembly material; (x, y, z) is the spatial coordinate, which is used to describe the spatial position of any point inside the grinding wheel assembly; ∩ is the non-uniformity amplitude correction coefficient, which is used to reflect the deviation of material density; ε is the material density deviation correction coefficient; is the density fluctuation characteristic in the radial direction; is the density fluctuation characteristic along the thickness direction; is the density fluctuation characteristic in the direction of the rotation axis; δ is the dynamic stress caused by the high-speed rotation of the grinding wheel assembly; Step S20: When the grinding wheel assembly rotates at the rated speed ω, the vibration signal of the grinding wheel assembly at time t is collected by a multi-directional vibration sensor, and the collected vibration signal is fast Fourier transformed to obtain the frequency domain characteristic a(t) of the vibration signal of the grinding wheel assembly. Based on the value ρ(x, y, z) of the material density of the grinding wheel assembly at the spatial point (x, y, z) obtained in step S10, the frequency domain characteristic a(t) of the vibration signal of the grinding wheel assembly is corrected to obtain the non-uniformity corrected vibration signal F corrected (x,y,z,t); Step S30: Combining the value of the grinding wheel assembly material density at the spatial point (x, y, z) obtained in step S10 with the non-uniformity corrected vibration signal F corrected in step S20 corrected (x, y, z, t) constructs a dynamic unbalanced point optimization objective function; uses a particle swarm optimization algorithm to iteratively solve the unbalanced point optimization objective function to determine the unbalanced point parameters at time t, including the unbalanced point mass, the unbalanced point eccentricity distance and the unbalanced point rotation angle; Step S40: Obtain the vibration force F(t) that needs to be compensated at time t according to the frequency domain characteristic a(t) of the vibration signal of the grinding wheel assembly, calculate the counterweight adjustment amount Δm(t) in combination with the unbalance point parameter at time t calculated in step S30, and automatically add or remove the calculated counterweight adjustment amount Δm(t) at the unbalance point position to obtain a grinding wheel assembly with optimized mass distribution; Step S50: After obtaining the grinding wheel assembly with optimized mass distribution, repeat step S20 to obtain the optimized non-uniformity correction vibration signal and compare it with the preset standard non-uniformity correction vibration signal to generate a dynamic balancing test report.

2. A dynamic balance test method for a grinding wheel assembly as claimed in claim 1, characterized in that: In step S20, the non-uniformity corrected vibration signal F corrected The calculation formula for (x,y,z,t) is F corrected (x,y,z,t)=ρ(x,y,z)·a(t)·w t , where w t is the weighting coefficient at time t.

3. A dynamic balance test method for a grinding wheel assembly as claimed in claim 2, characterized in that: The weighting coefficient w at time t t The calculation formula is: Among them, f is the vibration frequency at time t, α t is the weight adjustment coefficient, β is the frequency deviation sensitivity control parameter, f target is the preset reference frequency.

4. A dynamic balance test method for a grinding wheel assembly as claimed in claim 1, characterized in that: In step S30, the dynamic imbalance point optimization objective function is: Where P is the dynamic unbalanced point optimization objective function; ρ(x i ,y i ,z i ) is the density of the ith unbalanced point; m i is the mass of the ith unbalanced point; d i is the eccentric distance of the i-th unbalanced point; F measured,i is the non-uniformity corrected vibration signal measured at the ith unbalanced point; λ is the regularization coefficient; N is the total number of preset unbalanced samples; M total is the total mass of the grinding wheel assembly.

5. A dynamic balance test method for a grinding wheel assembly as claimed in claim 1, characterized in that: In step S40, the calculation formula of the weight adjustment amount Δm(t) is: in, is the vibration force influence coefficient; d i is the eccentricity distance of the i-th imbalance point.

6. A dynamic balance test method for a grinding wheel assembly as claimed in claim 1, characterized in that: In step S40, the vibration force F(t) to be compensated at time t is calculated as F(t)=M effective a(t), where M effective It is the effective mass of the grinding wheel component, which is determined by the geometric characteristics of the grinding wheel component and the material properties of the grinding wheel component.

7. A dynamic balance test method for a grinding wheel assembly as claimed in claim 1, characterized in that: In step S50, the content of the dynamic balancing test report includes the comparison data of the non-uniformity corrected vibration signal before and after the optimization of the mass distribution and the specific position of the unbalanced point before the optimization of the mass distribution and the corresponding counterweight adjustment amount.

8. A dynamic balance test system for a grinding wheel assembly, characterized in that: The dynamic balancing test system of the grinding wheel assembly comprises: The material inhomogeneity correction model establishment module is used to simulate the dynamic characteristics of the grinding wheel assembly under high-speed rotation through finite element analysis (FEA) and establish a material inhomogeneity correction model based on the geometric characteristics of the grinding wheel assembly, including the outer diameter d, thickness h and center axis z, and the material characteristics of the grinding wheel assembly, including density and elastic modulus E. The inhomogeneity correction model is described by the following formula: Among them, ρ(x, y, z) is the value of the grinding wheel assembly material density at the spatial point (x, y, z); ρ0 is the reference density of the grinding wheel assembly material; (x, y, z) is the spatial coordinate, which is used to describe the spatial position of any point inside the grinding wheel assembly; ∈ is the non-uniformity amplitude correction coefficient, which is used to reflect the deviation of material density; ε is the material density deviation correction coefficient; is the density fluctuation characteristic in the radial direction; is the density fluctuation characteristic along the thickness direction; is the density fluctuation characteristic in the direction of the rotation axis; δ is the dynamic stress caused by the high-speed rotation of the grinding wheel assembly; The vibration signal acquisition and correction module is used to collect the vibration signal of the grinding wheel assembly at time t through a multi-directional vibration sensor when the grinding wheel assembly rotates at a rated speed ω, and perform fast Fourier transform on the collected vibration signal to obtain the frequency domain characteristic a(t) of the vibration signal of the grinding wheel assembly, and based on the value ρ(x, y, z) of the material density of the grinding wheel assembly at the spatial point (x, y, z) obtained in step S10, correct the frequency domain characteristic a(t) of the vibration signal of the grinding wheel assembly to obtain the non-uniformity correction vibration signal F corrected (x,y,z,t); The dynamic optimization and unbalance point parameter solving module is used to combine the value of the grinding wheel assembly material density at the spatial point (x, y, z) obtained in step S10 and the non-uniformity correction vibration signal F corrected in step S20 corrected (x, y, z, t) constructs a dynamic unbalanced point optimization objective function; uses a particle swarm optimization algorithm to iteratively solve the unbalanced point optimization objective function to determine the unbalanced point parameters at time t, including the unbalanced point mass, the unbalanced point eccentricity distance and the unbalanced point rotation angle; A counterweight adjustment and quality optimization module, for obtaining the vibration force F(t) to be compensated at time t according to the frequency domain characteristics a(t) of the vibration signal of the grinding wheel assembly, calculating the counterweight adjustment amount Δm(t) in combination with the unbalance point parameters at time t calculated in step S30, and automatically adding or removing the calculated counterweight adjustment amount Δm(t) at the unbalance point position to obtain a grinding wheel assembly with optimized mass distribution; The dynamic balancing test report generating module is used to obtain the grinding wheel assembly with optimized mass distribution, repeat step S20 to obtain the optimized non-uniformity corrected vibration signal and compare it with the preset standard non-uniformity corrected vibration signal to generate a dynamic balancing test report.

9. A dynamic balance test device for a grinding wheel assembly, characterized in that: The dynamic balancing test equipment of the grinding wheel assembly comprises: a memory, a processor and a dynamic balancing test program of the grinding wheel assembly stored in the memory and executable on the processor. When the dynamic balancing test program of the grinding wheel assembly is executed by the processor, the dynamic balancing test method of the grinding wheel assembly described in any one of claims 1 to 7 is implemented.

10. A computer program product, characterized in that The computer program product comprises a dynamic balancing test program for a grinding wheel assembly, and when the dynamic balancing test program for the grinding wheel assembly is executed by a processor, the dynamic balancing test method for the grinding wheel assembly described in any one of claims 1 to 7 is implemented.

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