Axial magnetic field motor noise suppression method and system

Abstract

The present invention relates to a method and system for suppressing noise of an axial magnetic field motor. The method comprises: collecting data including current waveform, vibration spectrum and magnetic field distribution in the running state of the motor to construct a multi-dimensional running state data set; performing synchronous coupling analysis on the multi-dimensional running state data in the running state data set to identify the harmonic component characteristics of the current waveform, the resonant frequency characteristics of the vibration spectrum and the spatial inhomogeneity characteristics of the magnetic field distribution to obtain a target feature set; constructing a dynamic suppression strategy set including current waveform optimization, vibration frequency matching and magnetic field compensation strategy based on the target feature set; generating target phase compensation waveform parameters and magnetic field adjustment instruction set according to the dynamic suppression strategy set, controlling the output current waveform according to the phase compensation waveform parameters and correcting the spatial magnetic field distribution according to the magnetic field adjustment instruction set to effectively suppress the running noise of the axial magnetic field motor.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a method and system for suppressing noise of an axial magnetic field motor. Background Art

[0002] In the electric motor field, axial-field motors are widely used due to their unique structure and performance advantages. However, the noise generated by axial-field motors during operation remains a critical challenge that needs to be addressed. Existing motor noise suppression methods mostly address a single dimension, such as considering only the impact of the current waveform on noise or focusing solely on factors related to the vibration spectrum. These methods lack comprehensive consideration and collaborative analysis of multi-dimensional data on the motor's operating status. This one-sided approach fails to fully and deeply understand the root causes of motor noise, resulting in poor suppression effectiveness and difficulty meeting the stringent low-noise requirements of practical applications. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for suppressing noise of an axial magnetic field motor, aiming to effectively reduce the operating noise of the axial magnetic field motor and improve its operating stability and reliability.

[0004] In order to achieve the above-mentioned object, a first aspect of an embodiment of the present disclosure provides a method for suppressing noise of an axial magnetic field motor, the method comprising:

[0005] Collecting current waveform, vibration spectrum and magnetic field distribution data of the axial magnetic field motor in operation to construct a multi-dimensional operation status data set;

[0006] performing synchronous coupling analysis processing on the multi-dimensional operating status data set to identify harmonic component characteristics in the current waveform data, resonant frequency characteristics in the vibration spectrum data, and spatial inhomogeneity characteristics in the magnetic field distribution data;

[0007] Based on the harmonic component characteristics, the resonant frequency characteristics and the spatial inhomogeneity characteristics, a dynamic suppression strategy set is constructed, wherein the dynamic suppression strategy set includes a current waveform optimization strategy, a vibration frequency matching strategy and a magnetic field compensation strategy;

[0008] generating initial phase compensation waveform parameters according to the dynamic suppression strategy set, and calling a preset harmonic suppression algorithm to iteratively optimize the initial phase compensation waveform parameters to generate optimized target current waveform parameters, wherein the iterative optimization includes amplitude suppression of harmonic components of a specified order in the initial phase compensation waveform parameters based on an amplitude attenuation coefficient, and phase cancellation of remaining harmonic components in the initial phase compensation waveform parameters based on a compensation phase angle;

[0009] Calculating target current values ​​and power-on timings of each compensation coil in the magnetic field adjustment device according to the dynamic suppression strategy set and based on the excitation parameters of the multi-stage compensation coils, and generating a magnetic field adjustment instruction set according to the target current values ​​and power-on timings of each compensation coil;

[0010] The target current waveform parameters are input to the current controller of the axial magnetic field motor to adjust the output current waveform, and the magnetic field adjustment instruction set is sent to the magnetic field adjustment device of the axial magnetic field motor to correct the spatial magnetic field distribution.

[0011] According to a second aspect of the present disclosure, a system for suppressing noise of an axial magnetic field motor is provided, the system comprising:

[0012] A first building module is configured to collect current waveform, vibration spectrum and magnetic field distribution data of the axial magnetic field motor in an operating state to construct a multi-dimensional operating state data set;

[0013] an analysis module configured to perform synchronous coupling analysis processing on the multi-dimensional operating status data set to identify harmonic component characteristics in the current waveform data, resonant frequency characteristics in the vibration spectrum data, and spatial inhomogeneity characteristics in the magnetic field distribution data;

[0014] A second building module is configured to build a dynamic suppression strategy set based on the harmonic component characteristics, the resonant frequency characteristics, and the spatial inhomogeneity characteristics, wherein the dynamic suppression strategy set includes a current waveform optimization strategy, a vibration frequency matching strategy, and a magnetic field compensation strategy;

[0015] a generation module configured to generate initial phase compensation waveform parameters according to the dynamic suppression strategy set, and call a preset harmonic suppression algorithm to iteratively optimize the initial phase compensation waveform parameters to generate optimized target current waveform parameters, wherein the iterative optimization includes amplitude suppression of harmonic components of a specified order in the initial phase compensation waveform parameters based on an amplitude attenuation coefficient, and phase cancellation of remaining harmonic components in the initial phase compensation waveform parameters based on a compensation phase angle;

[0016] a calculation module configured to calculate, according to the dynamic suppression strategy set and based on the excitation parameters of the multi-stage compensation coils, a target current value and a power-on sequence for each compensation coil in the magnetic field adjustment device, and generate a magnetic field adjustment instruction set according to the target current value and the power-on sequence for each compensation coil;

[0017] The control module is configured to input the target current waveform parameters into the current controller of the axial magnetic field motor to adjust the output current waveform, and send the magnetic field adjustment instruction set to the magnetic field adjustment device of the axial magnetic field motor to correct the spatial magnetic field distribution.

[0018] According to a third aspect of the present disclosure, an electronic device is provided, including:

[0019] a memory having a computer program stored thereon;

[0020] A processor is used to execute the computer program in the memory to implement the steps of any one of the methods in the first aspect.

[0021] The present invention provides a method and system for suppressing noise in an axial magnetic field motor. Compared with the prior art, it has the following advantages:

[0022] By collecting multi-dimensional operating status data of axial magnetic field motors and performing synchronous coupling analysis, it is possible to comprehensively and accurately identify noise-related characteristics in various aspects, such as current, vibration, and magnetic field. Based on these characteristics, a dynamic suppression strategy set is constructed, which in turn generates phase compensation waveform parameters and a set of magnetic field adjustment instructions, while also adjusting the current waveform and spatial magnetic field distribution. This comprehensive, coordinated noise suppression method fundamentally addresses the drawbacks of the one-sided treatment of traditional methods, significantly improving the noise suppression effect, effectively reducing the operating noise of axial magnetic field motors, and improving their operational stability and reliability.

[0023] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following detailed description, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:

[0025] Figure 1 This is a flow chart of a method for suppressing noise of an axial magnetic field motor according to an embodiment of the specification.

[0026] Figure 2 The present invention is a block diagram of an axial magnetic field motor noise suppression system according to an embodiment of the specification.

[0027] Figure 3 The present invention is a block diagram of a device for performing a method for suppressing noise of an axial magnetic field motor according to an embodiment of the specification. DETAILED DESCRIPTION

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0029] The following describes the specific embodiments of the present disclosure in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present disclosure and are not intended to limit the present disclosure.

[0030] The present disclosure provides a method for suppressing noise of an axial magnetic field motor, which is applied to a motor controller. Figure 1 This is a flow chart illustrating a method for suppressing noise in an axial magnetic field motor according to an embodiment. Specifically, the method includes:

[0031] In step S11, the current waveform, vibration spectrum and magnetic field distribution data of the axial magnetic field motor in the operating state are collected to construct a multi-dimensional operating state data set;

[0032] Among them, the axial magnetic field motor is a type of motor in which the direction of the magnetic field is parallel to the direction of the motor axis. It has unique structural characteristics and performance advantages and is often used in occasions with special requirements on space size and power density.

[0033] Among them, current waveform: a graphical representation of the change of current over time, reflecting the change of the magnitude and direction of the current over time. The current waveform has different characteristics under different working conditions. Vibration spectrum: the vibration signal is decomposed into a set of different frequency components through methods such as Fourier transform. Each frequency component corresponds to an amplitude and phase, which is used to analyze the causes and characteristics of vibration. Magnetic field distribution data: data that describes the size and direction of the magnetic field at different positions in space. It can be obtained through magnetic field measurement equipment and reflects the spatial characteristics of the magnetic field. Multi-dimensional operating status data set: a set formed by integrating multiple different types of operating status data (such as current, vibration, magnetic field distribution, etc.) to comprehensively describe the operating status of the motor.

[0034] In the disclosed embodiments, during the operation of an axial magnetic field motor, a current sensor is used to collect current signals. A data acquisition card converts the analog current signals into digital signals to obtain current waveform data. A vibration sensor is used to collect the motor's vibration signals. After processing them on the data acquisition card, vibration spectrum data is obtained using methods such as Fourier transform. A magnetic field measurement device (such as a Hall sensor array) is used to measure magnetic field strength at various locations around the motor to obtain magnetic field distribution data. These different types of data are integrated to form a multi-dimensional operating status data set that comprehensively reflects the motor's operating status in various aspects.

[0035] In step S12, synchronous coupling analysis processing is performed on the multi-dimensional operating status data set to identify harmonic component characteristics in the current waveform data, resonant frequency characteristics in the vibration spectrum data, and spatial inhomogeneity characteristics in the magnetic field distribution data;

[0036] Among them, synchronous coupling analysis and processing is to synchronously analyze multiple different types of data in time and space, taking into account the mutual influence and correlation between them to explore the hidden characteristics and laws in the data.

[0037] Among them, harmonic component characteristics: the characteristics of each harmonic in the current waveform other than the fundamental wave, including the order, amplitude, phase, etc. of the harmonics. Harmonics will affect the performance and stability of the motor. Resonant frequency characteristics: frequency components in the vibration spectrum that are the same or close to the natural frequency of the system. When the external excitation frequency is close to the resonant frequency, the system will resonate, causing the vibration to intensify. Spatial inhomogeneity characteristics: the characteristics of the magnetic field distribution data in which the size and direction of the magnetic field at different locations in space vary. This inhomogeneity will affect the performance and efficiency of the motor.

[0038] In the disclosed embodiment, a synchronous coupling analysis and processing is performed on a multi-dimensional operating status data set, taking into account the mutual influence between current, vibration, and magnetic field. For the current waveform data, Fourier transform is used to decompose it into the fundamental wave and each harmonic, and characteristic parameters such as the order, amplitude, and phase of the harmonics are extracted as harmonic component characteristics; for the vibration spectrum data, by analyzing the peak frequency in the spectrum, it is determined whether there are frequency components close to the natural frequency of the system, and the resonant frequency characteristics are determined; for the magnetic field distribution data, by calculating the difference in magnetic field strength at different positions, the uneven distribution of the magnetic field in space is analyzed, and spatial inhomogeneity characteristics, such as the magnitude and change trend of the magnetic field gradient, are extracted.

[0039] In step S13, a dynamic suppression strategy set is constructed based on the harmonic component characteristics, the resonance frequency characteristics, and the spatial inhomogeneity characteristics. The dynamic suppression strategy set includes a current waveform optimization strategy, a vibration frequency matching strategy, and a magnetic field compensation strategy.

[0040] Among them, the dynamic suppression strategy set is a set of strategies for suppressing adverse effects based on the characteristics of harmonic components, resonant frequency and spatial inhomogeneity. These strategies will be adjusted in real time according to the operating status of the motor. Current waveform optimization strategy: a strategy that improves current quality, reduces harmonic content, and improves motor operating efficiency and stability by adjusting the parameters of the current waveform (such as amplitude, phase, frequency, etc.). Vibration frequency matching strategy: a strategy that adjusts the motor operating parameters or takes other measures to avoid the resonance frequency and reduce the impact of resonance on the motor. Magnetic field compensation strategy: a strategy that compensates for the inhomogeneity in the magnetic field distribution by controlling the magnetic field adjustment device, making the magnetic field distribution more uniform and improving motor performance.

[0041] In the disclosed embodiments, a corresponding dynamic suppression strategy is formulated based on the identified harmonic component characteristics, resonant frequency characteristics, and spatial inhomogeneity characteristics. For the harmonic component characteristics, the harmonic content is reduced by adjusting the parameters of the current waveform, such as by using a filtering algorithm or an optimization control strategy, to form a current waveform optimization strategy. For the resonant frequency characteristics, a vibration frequency matching strategy is formulated by adjusting the motor's operating frequency, changing the load characteristics, or increasing damping, so that the vibration frequency avoids the resonant frequency. For the spatial inhomogeneity characteristics, based on the magnetic field compensation principle, the inhomogeneous parts of the magnetic field distribution are compensated by controlling the compensation coils in the magnetic field adjustment device, thereby constructing a magnetic field compensation strategy. These strategies are integrated together to form a dynamic suppression strategy set.

[0042] In step S14, initial phase compensation waveform parameters are generated according to the dynamic suppression strategy set, and a preset harmonic suppression algorithm is called to iteratively optimize the initial phase compensation waveform parameters to generate optimized target current waveform parameters, wherein the iterative optimization process includes amplitude suppression of harmonic components of a specified order in the initial phase compensation waveform parameters based on the amplitude attenuation coefficient, and phase cancellation of remaining harmonic components in the initial phase compensation waveform parameters based on the compensation phase angle;

[0043] In the disclosed embodiments, initial phase compensation waveform parameters are calculated based on the requirements of the dynamic suppression strategy set, particularly the phase adjustment requirements of the current waveform optimization strategy and the magnetic field compensation strategy. For example, by analyzing the phase relationship between harmonics and the magnetic field, the current phase value that needs to be adjusted is determined to optimize the synergy between the current waveform and the magnetic field distribution. This parameter is used to subsequently adjust the output current waveform of the current controller to achieve a better match between the current and the magnetic field.

[0044] In the disclosed embodiment, a pre-set harmonic suppression algorithm is invoked to perform iterative optimization based on the amplitude attenuation coefficients k_1, k_2, and the compensation phase angles Δφ_1, Δφ_2 in the phase compensation waveform parameter set. For example, for a harmonic of a specified order, such as the n_1th harmonic, its amplitude is suppressed based on the amplitude attenuation coefficient k_1, thereby reducing the amplitude of the harmonic.

[0045] Meanwhile, phase cancellation is performed on the remaining harmonic components based on the corresponding compensation phase angles. Assume that in one iteration, the phase of the n_2th harmonic is adjusted based on the compensation phase angle Δφ_2, causing it to partially cancel out the energy of the other harmonics. Through multiple iterations of this process, the harmonic components are gradually optimized, ultimately generating optimized target current waveform parameters. These parameters more effectively suppress harmonics in the current, improve the current waveform, and thus reduce motor noise caused by harmonics.

[0046] In step S15, according to the dynamic suppression strategy set and based on the excitation parameters of the multi-stage compensation coils, the target current value and the power-on timing of each compensation coil in the magnetic field adjustment device are calculated, and according to the target current value and the power-on timing of each compensation coil, a magnetic field adjustment instruction set is generated;

[0047] In the disclosed embodiments, the requirements of the magnetic field compensation strategy for each compensation coil are considered based on a dynamic suppression strategy set and multi-stage compensation coil excitation parameters. Using a magnetic field analysis model and compensation algorithm, the target current value for each compensation coil in the magnetic field regulation device is calculated to generate the required compensation magnetic field to offset or weaken spatial magnetic field inhomogeneities. Simultaneously, the power-on sequence for each compensation coil is determined so that the compensation magnetic field can be applied in a specific temporal and spatial order, achieving effective magnetic field regulation. Information such as the target current value and power-on sequence is integrated to generate a set of magnetic field regulation instructions, which are used to control the operation of each compensation coil in the magnetic field regulation device.

[0048] In the disclosed embodiments, the target current values ​​for each compensation coil in the magnetic field regulation device are calculated based on the multi-stage compensation coil excitation parameters determined in the magnetic field compensation strategy, such as the excitation currents I_1 and I_2 for compensation coils at different locations. For example, for a specific compensation coil, its target current value, I_target, is determined based on its location and excitation parameters. Furthermore, the energization sequence for each compensation coil is determined, taking into account the motor's operating state and magnetic field variations.

[0049] For example, during different motor operation phases (t_1, t_2, etc.), different compensation coils are energized in a predefined sequence. These target current values ​​and energization timing information are integrated to generate coil control signals within the magnetic field regulation instruction set. This coil control signal precisely controls the operating state of each compensation coil in the magnetic field regulation device, ensuring that it generates a suitable reverse magnetic field, effectively correcting the spatial magnetic field distribution and reducing noise caused by magnetic field non-uniformity.

[0050] In the embodiment of the present disclosure, the target current waveform parameters and the coil control signal are time-synchronized and calibrated to ensure that the coordinated operation timing of the current controller and the magnetic field adjustment device meets the preset delay tolerance.

[0051] To ensure coordinated operation between the current controller and magnetic field regulator, the target current waveform parameters and the coil control signal are time-synchronized and calibrated. For example, a preset delay tolerance is set to T_limit. Through detection and adjustment, the current control operation corresponding to the target current waveform parameters and the magnetic field regulation operation corresponding to the coil control signal are precisely timed. Assume that at a certain time t, the current controller adjusts the output current waveform according to the target current waveform parameters, while the magnetic field regulator controls the compensation coil according to the coil control signal.

[0052] Through time synchronization calibration, the delay time between the two is ensured to be within the preset delay tolerance T_limit, avoiding the impact of noise suppression due to inconsistent operation timing, ensuring that the motor can operate stably and efficiently, and achieving the best noise suppression effect.

[0053] In step S16, the target current waveform parameters are input to the current controller of the axial magnetic field motor to adjust the output current waveform, and the magnetic field adjustment instruction set is sent to the magnetic field adjustment device of the axial magnetic field motor to correct the spatial magnetic field distribution.

[0054] In the disclosed embodiment, initial phase compensation waveform parameters are input into the current controller of the axial magnetic field motor. Based on these parameters, the current controller adjusts the phase and waveform of its output current, ensuring that the motor's output current waveform meets optimization requirements, reducing harmonic content and improving current quality. Simultaneously, a set of magnetic field adjustment instructions is sent to the magnetic field adjustment device of the axial magnetic field motor. Based on the target current value and power-on sequence in the instruction set, the magnetic field adjustment device controls the current and power-on state of each compensation coil, thereby correcting the spatial magnetic field distribution, making the magnetic field distribution more uniform and improving the performance and stability of the motor.

[0055] By collecting multi-dimensional operating status data of the axial magnetic field motor and performing synchronous coupling analysis, the above technical solution can comprehensively and accurately identify noise-related characteristics in various aspects such as current, vibration, and magnetic field. Based on these characteristics, a set of dynamic suppression strategies is constructed to generate phase compensation waveform parameters and a set of magnetic field adjustment instructions, while adjusting the current waveform and spatial magnetic field distribution. This all-round, coordinated noise suppression method fundamentally solves the drawbacks of the one-sided treatment of traditional methods, greatly improves the noise suppression effect, effectively reduces the operating noise of the axial magnetic field motor, and improves its operating stability and reliability.

[0056] In a possible implementation, in step S13, constructing a dynamic suppression strategy set based on the harmonic component characteristics, the resonant frequency characteristics, and the spatial inhomogeneity characteristics includes:

[0057] In step S131, a correlation model between the harmonic component characteristics and the spatial inhomogeneity characteristics is established, and a magnetic field compensation strategy for describing the enhancement effect of a harmonic current of a specific order on the radial magnetic field gradient is generated through the correlation model;

[0058] In the disclosed embodiments, a correlation model between harmonic component characteristics and spatial inhomogeneity characteristics is constructed based on the electromagnetic principles of motors and extensive experimental data. For a specific harmonic in the harmonic component characteristics, such as the nth harmonic, the characteristics of the harmonic current, such as the amplitude In and phase θn, are set in a relationship with the radial magnetic field gradient in the spatial inhomogeneity characteristics.

[0059] The authors experimentally measured the variation in the radial magnetic field gradient ▽B_r(x, y, z) under different operating conditions when the nth harmonic current amplitude In changed, collecting a large number of data points (In, ▽B_r(x, y, z)). Using this data, a functional relationship M(In, θn, ▽B_r(x, y, z)) was established through data fitting or theoretical derivation. This functional relationship is the required correlation model, which can accurately describe the enhancement effect of harmonic currents of a specific order on the radial magnetic field gradient, providing a basis for further analysis of the relationship between magnetic field inhomogeneity and harmonics.

[0060] In the embodiment of the present disclosure, for the harmonic components, characteristic parameters such as frequency, amplitude, phase, etc. of harmonics of different orders are extracted from the power signal through signal analysis means (such as Fourier transform, etc.). These parameters can fully describe the composition and characteristics of the harmonic components.

[0061] For spatial inhomogeneity characteristics, multi-point magnetic field measurements are performed within a specific spatial range with the help of magnetic field measurement equipment (such as Hall sensor arrays, etc.) to obtain data on magnetic field strength at different positions in space, and then analyze the uneven distribution of the magnetic field in radial and other directions, such as the size of the magnetic field gradient, the change trend and other characteristics.

[0062] Furthermore, using data analysis and modeling methods (such as regression analysis and neural networks), a correlation model was established using harmonic component characteristics as input variables and spatial inhomogeneity characteristics as output variables. This model, by learning the inherent laws between harmonics and magnetic field inhomogeneity from a large amount of actual measurement data, established a mathematical relationship between the two. It can predict the corresponding spatial inhomogeneity characteristics based on given harmonic component characteristics.

[0063] In the disclosed embodiments, a correlation model is constructed, and characteristic parameters associated with harmonic currents of a specific order are input. The model outputs the corresponding spatial inhomogeneity characteristics, focusing on changes in the radial magnetic field gradient. By analyzing the model output, the enhancement effect of harmonic currents of a specific order on the radial magnetic field gradient is clarified, specifically, how the harmonic current causes the radial magnetic field gradient to increase, and to what extent.

[0064] Based on the analysis of the radial magnetic field gradient enhancement effect of specific harmonic currents, a corresponding magnetic field compensation strategy is developed. The core goal of the compensation strategy is to offset or weaken this enhancement effect, restoring the radial magnetic field gradient to an ideal state or within the range that meets system requirements. For example, if a specific harmonic current causes the radial magnetic field gradient to increase in a certain area, the compensation strategy may include arranging a compensation coil near this area and precisely controlling the current magnitude, direction, and other parameters of the compensation coil so that the magnetic field it generates can offset the abnormal magnetic field caused by the harmonic current, thereby achieving effective magnetic field compensation.

[0065] In step S132, a magnetic field distortion coefficient corresponding to the harmonic order is calculated according to the association model. When the magnetic field distortion coefficient exceeds a preset threshold, a priority adjustment instruction in the magnetic field compensation strategy is triggered to generate a current waveform optimization strategy for preferentially suppressing the current component corresponding to the harmonic order.

[0066] In the disclosed embodiment, the magnetic field distortion coefficient corresponding to each harmonic is calculated based on the established correlation model M(In, θn, ▽B_r(x, y, z)). Assuming that for the nth harmonic, the magnetic field distortion coefficient Dn is calculated using the functional relationship in the correlation model, combined with the currently measured harmonic current amplitude In and phase θn, and the radial magnetic field gradient ▽B_r(x, y, z). A threshold value MaxD for the magnetic field distortion coefficient is preset.

[0067] When the calculated magnetic field distortion coefficient Dn exceeds MaxD, indicating that the subharmonic has a significant impact on magnetic field distortion, a priority adjustment command in the magnetic field compensation strategy is triggered. This command changes the execution priority of the magnetic field compensation strategy, prioritizing the suppression of the current component corresponding to the subharmonic. For example, when adjusting the current waveform, the amplitude attenuation coefficient of the subharmonic can be increased or its compensation phase angle can be adjusted more precisely to prioritize the impact of the subharmonic on magnetic field inhomogeneity, thereby effectively improving the motor's magnetic field distribution and reducing the noise generated by magnetic field distortion.

[0068] In step S133, the high-frequency noise bandwidth in the vibration spectrum data is determined according to the frequency domain energy distribution. When there is an overlapping area between the high-frequency noise bandwidth and the harmonic electromagnetic excitation frequency in the harmonic component characteristics, a bandwidth expansion instruction in the vibration frequency matching strategy is generated according to the resonance frequency characteristics to disperse the resonance energy, thereby obtaining a vibration frequency matching strategy.

[0069] In the embodiment of the present disclosure, the frequency domain energy distribution E(f) of the vibration spectrum data is analyzed to determine the high-frequency noise bandwidth. For example, by setting an energy threshold Eth, in the frequency domain energy distribution E(f), a continuous frequency range [f_start, f_end] with an energy value greater than Eth and a higher frequency is searched. This frequency range is the high-frequency noise bandwidth. For the harmonic electromagnetic excitation frequencies in the harmonic component characteristics, such as f_e1, f_e2, etc. When it is found that the high-frequency noise bandwidth [f_start, f_end] overlaps with a certain harmonic electromagnetic excitation frequency f_en, it means that energy concentration may occur due to resonance, resulting in greater noise.

[0070] At this point, a bandwidth expansion instruction is generated within the vibration frequency matching strategy. This instruction aims to disperse resonant energy by adjusting the motor's drive frequency so that it fluctuates within a set range, preventing energy from concentrating in overlapping areas and causing strong resonance. For example, by controlling the motor's drive frequency to fluctuate within the range [f_d - Δf, f_d + Δf], where f_d is the current drive frequency and Δf is the fluctuation range parameter determined based on the high-frequency noise bandwidth and motor characteristics, the goal is to disperse resonant energy and reduce noise.

[0071] In a possible implementation, in step S133, generating a bandwidth extension instruction in the vibration frequency matching strategy to disperse the resonance energy based on the resonance frequency characteristics to obtain the vibration frequency matching strategy includes:

[0072] In step S1331, according to the resonance frequency characteristics, a random frequency fine-tuning signal is injected into the speed control loop of the axial magnetic field motor to make the driving frequency fluctuate randomly within a preset range to destroy the resonance condition;

[0073] In the disclosed embodiment, a random frequency fine-tuning signal is introduced into the speed control loop of an axial-field motor. The frequency of this signal is set to f_random, and its fluctuation range is within a preset range, assuming the preset range is [Δf_min, Δf_max]. This random frequency fine-tuning signal is generated by a dedicated signal generation device, and the frequency f_random of this signal randomly varies within [Δf_min, Δf_max].

[0074] Furthermore, this random frequency fine-tuning signal is superimposed on the motor's drive frequency f_d, resulting in the motor's actual drive frequency becoming f_d + f_random. Since f_random varies randomly, this causes the drive frequency to fluctuate randomly within a dynamic range. Resonance conditions typically require the drive frequency to precisely match a specific frequency. This random fluctuation disrupts this precise matching requirement, preventing the motor from resonating at a specific frequency and reducing the noise generated by resonance.

[0075] In step S1332, the fluctuation amplitude of the random frequency fine-tuning signal is adjusted according to the width of the high-frequency noise bandwidth to ensure that the fluctuation range of the driving frequency covers the overlapping area of ​​the high-frequency noise bandwidth;

[0076] In the disclosed embodiment, the high-frequency noise bandwidth is Δf_noise = f_end - f_start. The amplitude of the random frequency fine-tuning signal is adjusted based on this width. If the high-frequency noise bandwidth is wide, i.e., Δf_noise is large, the amplitude of the random frequency fine-tuning signal needs to be increased to ensure that the driving frequency fluctuation range covers the overlap between the high-frequency noise bandwidth and the harmonic electromagnetic excitation frequency.

[0077] For example, an adjustment algorithm calculates the appropriate amplitude adjustment ΔA based on the magnitude of Δf_noise, adjusting the fluctuation range of the random frequency fine-tuning signal from [Δf_min, Δf_max] to [Δf_min + ΔA, Δf_max + ΔA]. This allows the fluctuation range of the drive frequency f_d + f_random to effectively cover the overlapping area, further dispersing the resonant energy and reducing the risk of noise caused by resonance.

[0078] In step S1333, the vibration spectrum changes after the random frequency fine-tuning signal is injected are monitored in real time. When it is detected that the energy amplitude ratio of the main resonance frequency point decreases, a vibration frequency matching strategy is obtained to lock the current fluctuation amplitude as the optimal parameter and stop frequency fine-tuning.

[0079] In the disclosed embodiment, after injecting a random frequency fine-tuning signal, a vibration spectrum monitoring device is used to monitor changes in the vibration spectrum in real time. The focus is on changes in the energy amplitude ratio at the main resonant frequency point f_m1. Assuming the energy amplitude at the main resonant frequency point f_m1 is E_m1, the total energy in the entire vibration spectrum is E_total, and the energy amplitude ratio is R = E_m1 / E_total. As the random frequency fine-tuning signal acts, the vibration spectrum will change, and R will also change accordingly.

[0080] When a decrease in R is detected, it indicates that the random frequency fine-tuning signal is effectively dispersing the resonant energy. At this point, the current fluctuation amplitude of the random frequency fine-tuning signal is locked and used as the optimal parameter. This means that the current fluctuation amplitude effectively disrupts the resonant condition and reduces the energy concentration at the main resonant frequency. At the same time, frequency fine-tuning is stopped, and the motor operates within the current optimized drive frequency fluctuation state to maintain good noise suppression and ensure stable, low-noise operation of the axial magnetic field motor in large ventilation systems.

[0081] In a possible implementation, in step S13, constructing a dynamic suppression strategy set based on the harmonic component characteristics, the resonant frequency characteristics, and the spatial inhomogeneity characteristics includes:

[0082] In step S1301, a frequency offset instruction in the vibration frequency matching strategy is generated based on a first matching degree between the harmonic electromagnetic excitation frequency in the harmonic component characteristic and the main resonant frequency point in the resonant frequency characteristic, wherein the frequency offset instruction is used to adjust the driving frequency of the axial magnetic field motor to deviate from the main resonant frequency point;

[0083] In the embodiment of the present disclosure, the first matching degree between the known harmonic electromagnetic excitation frequencies f_e1, f_e2, etc. and the main resonant frequency point f_m1 is M_1, M_2, etc. When the first matching degree Mi_i is high, it means that the subharmonic electromagnetic excitation frequency is close to the main resonant frequency point, which is easy to cause resonance, thereby generating a large noise. At this time, based on this matching degree information, a frequency offset instruction in the vibration frequency matching strategy is generated. For example, if M_1 is high, the frequency offset Δf_1 is calculated by the set algorithm, so that the driving frequency f_d is adjusted from the current value to f_d+Δf_1 or f_d-Δf_1, thereby deviating the driving frequency from the main resonant frequency point f_m1, avoiding the increase in noise caused by resonance, and ensuring that the motor can run stably and with low noise.

[0084] In step S1302, based on the superposition analysis results of the harmonic phase offset and the axial magnetic field offset, a phase compensation waveform parameter set in the current waveform optimization strategy is determined, wherein the phase compensation waveform parameter set includes the compensation phase angle and amplitude attenuation coefficient of each harmonic;

[0085] In the disclosed embodiment, the harmonic phase offsets φ_1, φ_2, etc. and the axial magnetic field offset ΔB_a are superimposed and analyzed. For example, considering the harmonic phase offset φ_1 and the axial magnetic field offset ΔB_a corresponding to the harmonic order n_1, a certain analysis method, which may be a calculation based on electromagnetic principles or a statistical analysis of experimental data, is used to determine the compensation phase angles Δφ_1, Δφ_2, etc. corresponding to each harmonic and the amplitude attenuation coefficients k_1, k_2, etc. These compensation phase angles and amplitude attenuation coefficients together constitute a set of phase compensation waveform parameters in the current waveform optimization strategy. When the motor is running, the current waveform is adjusted according to these parameters. For example, for the n_1th harmonic, its phase is adjusted according to the compensation phase angle Δφ_1, and its amplitude is reduced according to the amplitude attenuation coefficient k_1, thereby optimizing the current waveform and reducing the noise caused by harmonics and magnetic field inhomogeneity.

[0086] In step S1303, based on the radial magnetic field gradient distribution map and the axial magnetic field offset, the multi-stage compensation coil excitation parameters in the magnetic field compensation strategy are generated, and the multi-stage compensation coil excitation parameters are used to control the magnetic field adjustment device to generate a reverse magnetic field to offset the spatial inhomogeneity;

[0087] In the disclosed embodiments, the excitation parameters for the multi-stage compensation coils in the magnetic field compensation strategy are generated based on the radial magnetic field gradient distribution map ▽B_r(x, y, z) and the axial magnetic field offset ΔB_a. For example, the magnitude and direction of the excitation currents I_1, I_2, and so on, at different locations in the multi-stage compensation coils are determined based on the magnitude and direction of the gradient values ​​at different locations in the radial magnetic field gradient distribution map, as well as the axial magnetic field offset. These excitation parameters enable the magnetic field regulation device to generate a reverse magnetic field. The gradient direction of this reverse magnetic field is opposite to that in the radial magnetic field gradient distribution map, and the amplitude is adjusted based on actual conditions to offset spatial magnetic field inhomogeneities.

[0088] For example, at a certain position, based on the radial magnetic field gradient value ▽B_r(x_0, y_0, z_0), the excitation current I_0 required for the compensation coil at that position is calculated, so that the generated reverse magnetic field can effectively compensate for the magnetic field inhomogeneity at that position, thereby optimizing the magnetic field distribution of the motor and reducing the noise caused by the magnetic field inhomogeneity.

[0089] In step S1304, a dynamic suppression strategy set is constructed according to the frequency offset instruction, the phase compensation waveform parameter set, and the multi-stage compensation coil excitation parameters.

[0090] Among them, the frequency offset instruction indicates the specific requirements for adjusting the system frequency, which may be due to external interference, system performance optimization needs, etc., and provides the direction and target of frequency adjustment for the dynamic suppression strategy.

[0091] The phase compensation waveform parameter set contains a series of waveform parameters used for phase compensation. These parameters define the characteristics of different phase compensation waveforms, such as waveform shape, amplitude, frequency, etc., and are an important basis for building compensation strategies to adjust phase relationships.

[0092] The multi-stage compensation coil excitation parameters can provide the parameters required to excite the multi-stage compensation coils, such as current, voltage, excitation frequency, etc. By reasonably setting these parameters, the compensation coils can be controlled to generate a specific magnetic field, thereby achieving suppression of electromagnetic interference and other aspects.

[0093] Then, a set of dynamic suppression strategies is constructed based on the above input factors: according to the frequency offset instruction, the operating frequency of the motor is determined to eliminate or reduce the adverse effects of the frequency offset. For example, precise frequency control can be achieved by changing the power supply output frequency, adjusting the oscillation circuit parameters, etc.

[0094] The phase compensation waveform parameter set is used to generate the corresponding phase compensation waveform, and it is applied to the part of the system that requires phase adjustment, so that the phase relationship of each part of the system reaches an ideal state and the interference and error caused by the phase difference are reduced.

[0095] According to the excitation parameters of the multi-stage compensation coils, the excitation state of each compensation coil is precisely controlled so that they generate appropriate magnetic fields to offset or weaken the interference magnetic field in the system, thereby achieving dynamic suppression of electromagnetic interference.

[0096] Finally, these various strategies are integrated and optimized to form a complete set of dynamic suppression strategies. The individual strategies in this set work together to dynamically adjust the frequency, phase, and excitation of the multi-stage compensation coils based on the system's real-time status and interference conditions, effectively suppressing various interferences and ensuring stable and reliable motor operation.

[0097] In one possible implementation, in step S12, performing synchronous coupling analysis processing on the multi-dimensional operating status data set to identify harmonic component features in the current waveform data, resonant frequency features in the vibration spectrum data, and spatial inhomogeneity features in the magnetic field distribution data includes:

[0098] In step S121, a time-frequency decomposition process is performed on the current waveform data to extract the fundamental wave amplitude, harmonic order and harmonic phase offset in the harmonic component characteristics;

[0099] In the disclosed embodiments, a time-frequency decomposition algorithm is used to process the current waveform data. For example, a time-frequency decomposition method tailored to the motor's current characteristics is employed to analyze the current waveform in both time and frequency dimensions. After processing, the fundamental component and its harmonic components can be clearly distinguished.

[0100] Assume the fundamental amplitude is A_0, which represents the amplitude of the primary energy component in the current waveform. Harmonic orders, such as n_1, n_2, and n_3, are also identified. These harmonic orders reflect the components in the current that have frequencies multiples of the fundamental frequency. Corresponding harmonic phase offsets, such as φ_1, φ_2, and φ_3, are also obtained. These phase offsets reflect the phase difference of each harmonic relative to the fundamental. These fundamental amplitudes, harmonic orders, and harmonic phase offsets together constitute the harmonic component characteristics of the current waveform data.

[0101] In step S122, peak detection processing is performed on the vibration spectrum data to determine the main resonant frequency point, the secondary resonant frequency point and the energy amplitude ratio of the corresponding frequency in the resonant frequency characteristics;

[0102] In the embodiment of the present disclosure, a special peak detection algorithm is used to analyze the vibration spectrum data. In the vibration spectrum data E(f), frequency points with relatively prominent energy amplitudes are found. For example, after detection, the main resonance frequency point is determined to be f_m1, which is the frequency point where the motor vibration energy is most concentrated and plays a dominant role in the vibration state of the motor. At the same time, the secondary resonance frequency points f_s1, f_s2, etc. are identified. Although the energy amplitudes of these secondary resonance frequency points are smaller than the main resonance frequency points, they also have a certain impact on the motor vibration. And the energy amplitude ratio of the corresponding frequencies is calculated, such as the energy amplitude at the main resonance frequency point f_m1 is E_m1, and the energy amplitude at the secondary resonance frequency point f_s1 is E_s1. The energy amplitude ratio can be expressed as E_s1 / E_m1, etc.

[0103] It can be explained that these main resonant frequency points, secondary resonant frequency points and the energy amplitude ratios of the corresponding frequencies constitute the resonant frequency characteristics of the vibration spectrum data, which helps to understand the frequency characteristics of motor vibration and the impact of resonance on motor operation, and provides a basis for the subsequent formulation of vibration frequency matching strategies.

[0104] In step S123, a spatial gradient calculation process is performed on the magnetic field distribution data to generate a radial magnetic field gradient distribution map and an axial magnetic field offset in the spatial inhomogeneity feature;

[0105] In the disclosed embodiment, the spatial gradient calculation method is used to analyze the spatial variation of the magnetic field based on the magnetic field distribution data. The radial magnetic field gradient is calculated based on the radial magnetic flux density B_r and axial magnetic flux density B_a measured in the air gap area.

[0106] For example, the radial magnetic field gradient ▽B_r(x, y, z) is calculated at different locations (x_1, y_1, z_1) and (x_2, y_2, z_2). These gradient values ​​form a radial magnetic field gradient distribution map as they change with spatial position. Simultaneously, the axial magnetic field offset ΔB_a is determined, reflecting the degree of deviation of the axial magnetic field from the ideal uniform distribution. Together, the radial magnetic field gradient distribution map and the axial magnetic field offset characterize the spatial inhomogeneity of the magnetic field distribution data, which is crucial for understanding the spatial characteristics of the motor magnetic field and developing magnetic field compensation strategies.

[0107] In step S124, the harmonic order in the harmonic component characteristic is multiplied by the fundamental frequency to obtain a harmonic electromagnetic excitation frequency, and the harmonic electromagnetic excitation frequency is correlated and mapped with the main resonant frequency point in the resonant frequency characteristic to determine a first matching degree between the harmonic electromagnetic excitation frequency and the main resonant frequency point;

[0108] In the disclosed embodiment, the harmonic orders in the harmonic component feature are known to be n_1, n_2, and so on, and the fundamental frequency is assumed to be f_0. The harmonic electromagnetic excitation frequency f_e1 is calculated by multiplying n_1 by f_0, and the harmonic electromagnetic excitation frequency f_e2 is calculated by multiplying n_2 by f_0, and so on. These harmonic electromagnetic excitation frequencies are then mapped to the primary resonant frequency point f_m1 in the resonant frequency feature.

[0109] For example, by comparing the difference between f_e1 and f_m1, a quantitative method can be used to determine the first matching degree M_1 between them. If f_e1 and f_m1 are very close, then the first matching degree M_1 is high, indicating that the subharmonic electromagnetic excitation frequency has a strong correlation with the main resonant frequency point. This correlation is of great significance for subsequently formulating vibration frequency matching strategies and adjusting the motor drive frequency to avoid resonance.

[0110] In step S125, a dynamic correlation model is established between the harmonic phase offset in the harmonic component characteristics and the axial magnetic field offset in the magnetic field distribution data, the modulation effect of the harmonic phase on the magnetic field distribution is calculated through the dynamic correlation model, and the initial phase adjustment amount in the phase compensation waveform parameter set is determined based on the modulation effect.

[0111] In the disclosed embodiments, a dynamic correlation model is established between harmonic phase offsets φ_1, φ_2, and so on, and the axial magnetic field offset ΔB_a, based on the theoretical electromagnetic characteristics of the motor and actual operating data. For example, this model may be a functional relationship fitted from a series of experimental data, or a theoretical model derived from electromagnetic principles. Using this dynamic correlation model, the harmonic phase offset φ_i is input and the modulation effect M_ei of the harmonic phase on the magnetic field distribution is calculated.

[0112] Furthermore, based on these modulation effect values, the initial phase adjustment Δθ_0 in the phase compensation waveform parameter set is determined. For example, if the modulation effect value M_e1 is large, indicating that the subharmonic phase has a significant impact on the magnetic field distribution, then the initial phase adjustment Δθ_0 will also be significantly adjusted based on the model calculation results, providing a basis for subsequent adjustments to the current waveform to suppress magnetic field inhomogeneity and noise.

[0113] In a possible implementation, in step S16, inputting the target current waveform parameter into the current controller of the axial magnetic field motor to adjust the output current waveform includes:

[0114] In step S161, the PWM modulation signal of the current controller is reconstructed according to the target current waveform parameters so that the harmonic components of the output current waveform meet the preset amplitude threshold and phase symmetry conditions;

[0115] In the disclosed embodiments, for axial magnetic field motor scenarios such as automated guided vehicles (AGVs), the target current waveform parameters include amplitude adjustment parameters for each harmonic, such as A1 and A2, and phase adjustment parameters, such as θ1 and θ2. The PWM modulation signal of the current controller typically consists of a series of pulses, whose characteristics, such as duty cycle and frequency, determine the shape of the output current waveform.

[0116] First, consider the amplitude. The preset amplitude threshold is set to MaxA. For each harmonic, such as the nth harmonic, its amplitude in the target current waveform parameter is An. It is necessary to change the amplitude of the harmonic in the output current waveform by adjusting the duty cycle of the PWM modulation signal. Assume that the period of the PWM modulation signal is T, the high level duration is t, and the duty cycle D=t / T. Through a certain correspondence, such as establishing a functional relationship F(An, D), where An is the amplitude of the nth harmonic in the target current waveform parameter, and D is the duty cycle of the PWM modulation signal, the functional relationship is derived through a series of experiments or based on the electromagnetic characteristics theory of the motor. By adjusting the duty cycle D, the amplitude of the nth harmonic in the output current waveform meets the requirement of not exceeding the preset amplitude threshold MaxA.

[0117] Next, let's look at the phase aspect. The preset phase symmetry condition requires that each harmonic satisfy a set phase relationship. Assuming that the phases of the mth and nth harmonics in the target current waveform parameters are θm and θn, respectively, the phase symmetry condition to be satisfied is a certain functional relationship G(θm, θn) = 0. This condition is also achieved by adjusting the PWM modulation signal. For example, the starting phase of the PWM modulation signal affects the phase of the harmonics in the output current waveform. By changing the starting phase β of the PWM modulation signal, another functional relationship H(β, θm, θn) is established. By adjusting β, the phases of the mth and nth harmonics can satisfy the phase symmetry condition G(θm, θn) = 0.

[0118] In actual operation, the duty cycle and starting phase of the PWM modulation signal are continuously adjusted, and the amplitude and phase requirements are comprehensively considered, so that the harmonic components of the output current waveform meet the preset amplitude threshold and phase symmetry conditions, thereby optimizing the current waveform and reducing the motor noise caused by harmonics.

[0119] In step S162, the actual harmonic content of the output current waveform is monitored in real time. When it is detected that the actual harmonic content exceeds the amplitude threshold, the compensation phase angle and the amplitude attenuation coefficient are dynamically adjusted to generate updated target current waveform parameters.

[0120] In the disclosed embodiment, a specialized harmonic detection device is used to monitor the actual harmonic content of the output current waveform in real time during continuous motor operation. This harmonic detection device analyzes the output current waveform to obtain the actual amplitude and phase information of each harmonic. The actual amplitude of the detected nth harmonic is denoted by An_real, and the actual phase is denoted by θn_real.

[0121] When the actual amplitude An_real of a harmonic is detected to exceed the preset amplitude threshold MaxA, the compensation phase angle and amplitude attenuation coefficient need to be dynamically adjusted. Assume that the compensation phase angle corresponding to the original nth harmonic is θn_c, and the amplitude attenuation coefficient is kn. For the amplitude attenuation coefficient kn, an adjustment rule can be implemented. For example, when An_real > MaxA, the amplitude attenuation coefficient is increased by a set ratio α, i.e., the new amplitude attenuation coefficient kn_new = kn * (1 + α), where α is a proportional parameter determined based on motor characteristics and experiments. For the compensation phase angle θn_c, a phase adjustment algorithm is used to determine the adjustment amount Δθn based on the difference between the actual phase θn_real and the target phase (determined by phase symmetry). For example, the difference between the actual and target phases is calculated, and the adjustment amount Δθn is calculated using a functional relationship. The new compensation phase angle θn_c_new = θn_c + Δθn.

[0122] Furthermore, the adjusted compensation phase angle θn_c_new and amplitude attenuation coefficient kn_new are substituted into the calculation of the target current waveform parameters to generate updated target current waveform parameters. These updated parameters take into account the actual harmonic content of the current output current waveform and are intended to further optimize the current waveform so that the harmonic content meets the preset requirements and continuously reduce motor operating noise.

[0123] In step S163 , the updated target current waveform parameters are fed back to the harmonic suppression algorithm for secondary optimization processing until the actual harmonic content is stabilized within the range of the amplitude threshold.

[0124] In the embodiment of the present disclosure, the updated target current waveform parameters are inputted again into the preset harmonic suppression algorithm. After receiving the new parameters, the harmonic suppression algorithm will re-analyze and optimize the current waveform.

[0125] The algorithm first re-applies amplitude suppression and phase cancellation to each harmonic based on the new compensation phase angle and amplitude reduction coefficient. For example, for a single harmonic, its amplitude is further suppressed using the new amplitude reduction coefficient kn_new, and its phase is re-adjusted using the new compensation phase angle θn_c_new. During this process, the algorithm comprehensively considers the interactions between harmonics, as adjustments to a single harmonic may have a ripple effect on other harmonics.

[0126] After the secondary optimization process, the harmonic content of the output current waveform is recalculated. If the actual harmonic content still exceeds the amplitude threshold, the algorithm adjusts the compensation phase angle and amplitude attenuation coefficient based on the excess, generates a new round of target current waveform parameters, and then repeats the secondary optimization process. This cycle continues, with each optimization process finely adjusting the current waveform so that the actual harmonic content gradually approaches and eventually stabilizes within the amplitude threshold. This continuous feedback and optimization mechanism ensures that the output current waveform of the axial magnetic field motor always maintains a low harmonic content state, effectively suppressing noise during motor operation and ensuring the stable operation of the axial magnetic field motor.

[0127] In a possible implementation, in step S11, the current waveform, vibration spectrum, and magnetic field distribution data of the axial magnetic field motor in operation are collected to construct a multi-dimensional operation status data set, including:

[0128] In step S111, a high-precision current sensor is deployed in the three-phase winding loop of the axial magnetic field motor to collect instantaneous current value and phase information in the current waveform data at a preset sampling frequency;

[0129] In the embodiment of the present disclosure, in order to accurately collect the current waveform data of the motor of an AGV unmanned vehicle, for example, a high-precision current sensor is carefully deployed in the three-phase winding loop of the axial magnetic field motor. For example, the preset sampling frequency is set to F_s1, which is determined by comprehensively considering the motor operating characteristics and the data acquisition accuracy requirements. During the operation of the motor, the sensor continues to work. For example, at a certain moment t1, the instantaneous current values ​​collected in the three-phase winding are I_a1, I_b1, and I_c1, respectively, and the corresponding phase information is obtained as θ_a1, θ_b1, and θ_c1. These data reflect the specific state of the three-phase current of the motor at that moment, and are an important basis for subsequent analysis of the motor's operating status.

[0130] In step S112, a vibration acceleration sensor array is installed on the surface of the stator housing of the axial magnetic field motor, and a spectrum analyzer is used to obtain the time domain vibration signal and frequency domain energy distribution in the vibration spectrum data;

[0131] In the disclosed embodiments, an array of vibration acceleration sensors is mounted on the surface of the stator housing in a predetermined layout. This array layout is designed based on the motor structure and vibration propagation characteristics to ensure comprehensive and accurate capture of vibration information generated during motor operation. The signals collected by the sensors are analyzed using a spectrum analyzer.

[0132] For example, over a certain period of time, a time-domain vibration signal V(t) is obtained. This is a multidimensional signal that varies with time and contains the vibration conditions of different parts of the motor at different times. After spectral analysis, the frequency-domain energy distribution E(f) is obtained, where f represents frequency. E(f) is a function of frequency, representing the distribution of vibration energy at each frequency point. For example, the energy value at frequency f1 is E1, the energy value at f2 is E2, and so on. These energy values ​​constitute the multidimensional frequency-domain energy distribution result, reflecting the concentration and distribution characteristics of the motor's vibration energy at different frequencies.

[0133] In step S113, a Hall sensor matrix is ​​arranged in the air gap region of the axial magnetic field motor to measure the radial magnetic flux density and the axial magnetic flux density in the magnetic field distribution data;

[0134] In the disclosed embodiment, a matrix of multiple Hall sensors is arranged in the air gap region. These Hall sensors are arranged according to a predetermined geometric pattern to accurately measure the magnetic field in the air gap region. During motor operation, for example, at a specific position and time, the Hall sensor matrix measures the radial magnetic flux density B_r1 and the axial magnetic flux density B_a1. As the motor rotates and its operating state changes, a series of radial and axial magnetic flux density data are obtained at different positions and times.

[0135] In step S114, timestamp alignment processing is performed on the instantaneous current value, the time domain vibration signal, and the radial magnetic flux density to ensure time synchronization of the multi-dimensional operating status data set;

[0136] In the embodiment of the present disclosure, the collected instantaneous current value, time domain vibration signal and radial magnetic flux density come from different types of sensors. In order to accurately perform a comprehensive analysis of these data, timestamp alignment processing is required. Specifically, each data point is marked with its corresponding precise time information. For example, the current data point I_a1 is marked at time t1, the vibration signal data point V(t1) is marked at time t1, and the radial magnetic flux density data point B_r1 is also marked at time t1. In this way, the data collected by different sensors can correspond one to one in the time dimension, ensuring the accuracy of subsequent synchronous coupling analysis.

[0137] In step S115 , the aligned multi-dimensional operating status data set is normalized to eliminate amplitude deviations caused by sensor range differences, thereby obtaining the multi-dimensional operating status data set.

[0138] In the disclosed embodiments, different sensors have different ranges. For example, the current sensor range is [I_min, I_max], the vibration acceleration sensor range is [V_min, V_max], and the Hall sensor range is [B_min, B_max]. This can lead to differences in the magnitude of the collected data amplitudes, making it difficult to directly analyze and compare them. Therefore, the aligned multi-dimensional operating status data set is standardized. For current data, the formula (I-I_min) / (I_max-I_min) is used for standardization, converting the collected current value I into a standardized value I_norm between 0 and 1. For vibration data V, the formula (V-V_min) / (V_max-V_min) is used for standardization to obtain the standardized vibration value V_norm. For magnetic field data B, the formula (B-B_min) / (B_max-B_min) is used for standardization to B_norm. After such standardization, the amplitude deviation caused by the difference in sensor range is eliminated, making the multi-dimensional operating status data set comparable in amplitude, laying the foundation for subsequent synchronous coupling analysis.

[0139] In a possible implementation, in step S16, sending the magnetic field adjustment instruction set to the magnetic field adjustment device of the axial magnetic field motor to correct the spatial magnetic field distribution includes:

[0140] In step S1601, the auxiliary compensation coils in the magnetic field adjustment device are activated according to the multi-stage compensation coil excitation parameters;

[0141] In step S1602, a reverse compensation magnetic field is generated that is spatially synchronized with the rotating main magnetic field of the axial magnetic field motor based on the radial magnetic field gradient distribution map and the axial magnetic field offset in the magnetic field distribution data, wherein the gradient direction and amplitude of the reverse compensation magnetic field are opposite to the spatial inhomogeneity characteristics;

[0142] In this disclosed embodiment, the magnetic field adjustment instruction set includes multi-stage compensation coil excitation parameters, such as the magnitude and direction of the excitation currents I1 and I2 for compensation coils at different locations. Based on these parameters, the auxiliary compensation coils in the magnetic field adjustment device are activated. The reverse compensation magnetic field is designed based on the radial magnetic field gradient distribution map ▽B_r(x, y, z) and the axial magnetic field offset ΔB_a.

[0143] For each position (x, y, z), the direction of the radial magnetic field gradient ▽B_r(x, y, z) at that location is used to determine the direction of the reverse magnetic field gradient generated by the compensation coil. Based on the magnitude of the gradient and the axial magnetic field offset ΔB_a, the amplitude of the reverse magnetic field generated by the compensation coil at that location is calculated.

[0144] For example, through a computational relationship based on electromagnetic principles, the excitation current I(x, y, z) for the compensation coil at that location is calculated, combining the magnetic field parameters at the current location with the characteristic parameters of the compensation coil. This allows the reverse magnetic field generated by the compensation coil to be superimposed on the main magnetic field at that location, effectively offsetting the spatial inhomogeneity of the magnetic field. Furthermore, by controlling the energization timing of the compensation coil, the generated reverse compensation magnetic field is spatially synchronized with the rotating main magnetic field of the axial magnetic field motor, thereby optimizing the magnetic field distribution and reducing the noise generated by the magnetic field inhomogeneity.

[0145] In step S1603, the radial magnetic flux density change in the air gap region is detected in real time. When it is detected that the gradient distribution of the radial magnetic flux density does not reach a preset uniformity, the excitation current of the auxiliary compensation coil is increased until the preset uniformity is met.

[0146] In the disclosed embodiments, a detection device positioned in the air gap region detects changes in radial magnetic flux density in real time. The detected radial magnetic flux density data is analyzed to calculate its gradient distribution. A preset uniformity standard, designated as the U standard, is used to measure the uniformity of the radial magnetic flux density gradient distribution. If the actual radial magnetic flux density gradient distribution does not meet the U standard, this indicates that magnetic field inhomogeneity persists, necessitating further adjustment of the excitation current of the auxiliary compensation coil.

[0147] For example, the excitation current of the auxiliary compensation coil is increased by a fixed increment ΔI. After each increment, the radial magnetic flux density in the air gap region is re-evaluated, and its gradient distribution is recalculated to determine whether it meets the preset uniformity standard U. This process is repeated until the radial magnetic flux density gradient distribution meets the preset uniformity standard U. In this way, the magnetic field regulation effect is continuously optimized, making the magnetic field distribution within the motor more uniform and further reducing the noise caused by the uneven magnetic field.

[0148] In step S1604, during the change of the speed of the axial magnetic field motor, the power-on timing of the auxiliary compensation coil is dynamically adjusted to match the phase offset of the rotating magnetic field to ensure spatial synchronization between the compensation magnetic field and the main magnetic field.

[0149] In the disclosed embodiment, when the speed of the axial magnetic field motor changes, the phase of its rotating magnetic field will also shift accordingly. In order to ensure that the compensation magnetic field and the main magnetic field always maintain good spatial synchronization, it is necessary to dynamically adjust the energization timing of the auxiliary compensation coil.

[0150] For example, by monitoring changes in motor speed, assuming the current speed is ω1, the phase offset Δθ1 of the rotating magnetic field at that speed is calculated based on the motor's structural parameters and electromagnetic characteristics. Then, based on this phase offset, the power-on timing parameters, such as the start time and duration of the auxiliary compensation coil's energization, are adjusted. By establishing a functional relationship between speed and phase offset, the power-on timing can be accurately adjusted in real time based on speed changes. This ensures that the compensation magnetic field remains spatially synchronized with the main magnetic field during changes in motor speed, maintaining the effectiveness of magnetic field regulation, continuously reducing motor operating noise, and ensuring the stable operation of large-scale ventilation systems.

[0151] The present disclosure also provides an axial magnetic field motor noise suppression system, see Figure 2 As shown, the system includes:

[0152] The first constructing module 210 is configured to collect current waveform, vibration spectrum and magnetic field distribution data of the axial magnetic field motor in operation, and construct a multi-dimensional operation status data set;

[0153] an analysis module 220 configured to perform synchronous coupling analysis processing on the multi-dimensional operating status data set to identify harmonic component characteristics in the current waveform data, resonant frequency characteristics in the vibration spectrum data, and spatial inhomogeneity characteristics in the magnetic field distribution data;

[0154] A second construction module 230 is configured to construct a dynamic suppression strategy set based on the harmonic component characteristics, the resonant frequency characteristics, and the spatial inhomogeneity characteristics, wherein the dynamic suppression strategy set includes a current waveform optimization strategy, a vibration frequency matching strategy, and a magnetic field compensation strategy;

[0155] a generation module 240 configured to generate initial phase compensation waveform parameters according to the dynamic suppression strategy set, and to call a preset harmonic suppression algorithm to iteratively optimize the initial phase compensation waveform parameters to generate optimized target current waveform parameters, wherein the iterative optimization includes amplitude suppression of harmonic components of a specified order in the initial phase compensation waveform parameters based on an amplitude attenuation coefficient, and phase cancellation of remaining harmonic components in the initial phase compensation waveform parameters based on a compensation phase angle;

[0156] a calculation module 250 configured to calculate, according to the dynamic suppression strategy set and based on the excitation parameters of the multi-stage compensation coils, a target current value and a power-on sequence for each compensation coil in the magnetic field adjustment device, and generate a magnetic field adjustment instruction set based on the target current value and the power-on sequence for each compensation coil;

[0157] The control module 260 is configured to input the target current waveform parameters into the current controller of the axial magnetic field motor to adjust the output current waveform, and send the magnetic field adjustment instruction set to the magnetic field adjustment device of the axial magnetic field motor to correct the spatial magnetic field distribution.

[0158] In a possible implementation, the second building module 230 is configured to:

[0159] Establishing a correlation model between the harmonic component characteristics and the spatial inhomogeneity characteristics, and generating a magnetic field compensation strategy for describing the enhancement effect of harmonic currents of a specific order on the radial magnetic field gradient through the correlation model;

[0160] Calculating a magnetic field distortion coefficient corresponding to the harmonic order according to the association model, and when the magnetic field distortion coefficient exceeds a preset threshold, triggering a priority adjustment instruction in the magnetic field compensation strategy to generate a current waveform optimization strategy for preferentially suppressing a current component corresponding to the harmonic order;

[0161] The high-frequency noise bandwidth in the vibration spectrum data is determined based on the frequency domain energy distribution. When there is an overlapping area between the high-frequency noise bandwidth and the harmonic electromagnetic excitation frequency in the harmonic component characteristics, a bandwidth expansion instruction in the vibration frequency matching strategy is generated based on the resonance frequency characteristics to disperse the resonance energy, thereby obtaining a vibration frequency matching strategy.

[0162] In a possible implementation, the second building module 230 is configured to:

[0163] injecting a random frequency fine-tuning signal into the speed control loop of the axial magnetic field motor according to the resonant frequency characteristics, so that the driving frequency fluctuates randomly within a preset range to destroy the resonance condition;

[0164] adjusting the fluctuation amplitude of the random frequency fine-tuning signal according to the width of the high-frequency noise bandwidth to ensure that the fluctuation range of the driving frequency covers the overlapping area of ​​the high-frequency noise bandwidth;

[0165] The vibration spectrum changes after the random frequency fine-tuning signal is injected are monitored in real time. When a decrease in the energy amplitude ratio of the main resonant frequency point is detected, a vibration frequency matching strategy is obtained to lock the current fluctuation amplitude as the optimal parameter and stop frequency fine-tuning.

[0166] In a possible implementation, the second building module 230 is configured to:

[0167] generating a frequency offset instruction in the vibration frequency matching strategy based on a first matching degree between the harmonic electromagnetic excitation frequency in the harmonic component characteristic and the main resonant frequency point in the resonant frequency characteristic, wherein the frequency offset instruction is used to adjust the driving frequency of the axial magnetic field motor to deviate from the main resonant frequency point;

[0168] Determining a phase compensation waveform parameter set in the current waveform optimization strategy based on a superposition analysis result of the harmonic phase offset and the axial magnetic field offset, wherein the phase compensation waveform parameter set includes a compensation phase angle and an amplitude attenuation coefficient of each harmonic;

[0169] generating, based on the radial magnetic field gradient distribution diagram and the axial magnetic field offset, a multi-stage compensation coil excitation parameter in the magnetic field compensation strategy, wherein the multi-stage compensation coil excitation parameter is used to control the magnetic field adjustment device to generate a reverse magnetic field to offset spatial inhomogeneity;

[0170] A dynamic suppression strategy set is constructed according to the frequency offset instruction, the phase compensation waveform parameter set, and the multi-stage compensation coil excitation parameters.

[0171] In a possible implementation, the analysis module 220 is configured to:

[0172] Performing time-frequency decomposition processing on the current waveform data to extract the fundamental wave amplitude, harmonic order and harmonic phase offset from the harmonic component characteristics;

[0173] Performing peak detection processing on the vibration spectrum data to determine the primary resonant frequency point, the secondary resonant frequency point, and the energy amplitude ratio of the corresponding frequencies in the resonant frequency characteristics;

[0174] Performing spatial gradient calculation processing on the magnetic field distribution data to generate a radial magnetic field gradient distribution map and an axial magnetic field offset in the spatial inhomogeneity feature;

[0175] Multiplying the harmonic order in the harmonic component feature by the fundamental frequency to obtain a harmonic electromagnetic excitation frequency, and performing correlation mapping with a main resonant frequency point in the resonant frequency feature to determine a first matching degree between the harmonic electromagnetic excitation frequency and the main resonant frequency point;

[0176] A dynamic correlation model is established between the harmonic phase offset in the harmonic component characteristics and the axial magnetic field offset in the magnetic field distribution data. The modulation effect of the harmonic phase on the magnetic field distribution is calculated through the dynamic correlation model, and the initial phase adjustment amount in the phase compensation waveform parameter set is determined based on the modulation effect.

[0177] In a possible implementation, the control module 260 is configured to:

[0178] Reconstructing the PWM modulation signal of the current controller according to the target current waveform parameters so that the harmonic components of the output current waveform meet the preset amplitude threshold and phase symmetry conditions;

[0179] monitoring the actual harmonic content of the output current waveform in real time, and dynamically adjusting the compensation phase angle and the amplitude attenuation coefficient when it is detected that the actual harmonic content exceeds the amplitude threshold to generate updated target current waveform parameters;

[0180] The updated target current waveform parameters are fed back to the harmonic suppression algorithm for secondary optimization processing until the actual harmonic content is stabilized within the range of the amplitude threshold.

[0181] In a possible implementation, the first building module 210 is configured to:

[0182] Deploying a high-precision current sensor in the three-phase winding loop of the axial magnetic field motor to collect instantaneous current value and phase information in the current waveform data at a preset sampling frequency;

[0183] A vibration acceleration sensor array is installed on the surface of the stator housing of the axial magnetic field motor, and a spectrum analyzer is used to obtain the time domain vibration signal and frequency domain energy distribution in the vibration spectrum data;

[0184] Arranging a Hall sensor matrix in the air gap region of the axial magnetic field motor to measure the radial magnetic flux density and the axial magnetic flux density in the magnetic field distribution data;

[0185] Performing timestamp alignment processing on the instantaneous current value, the time domain vibration signal, and the radial magnetic flux density to ensure time synchronization of the multi-dimensional operating status data set;

[0186] The aligned multi-dimensional operating status data set is standardized to eliminate amplitude deviation caused by sensor range differences, thereby obtaining the multi-dimensional operating status data set.

[0187] In a possible implementation, the control module 260 is configured to:

[0188] activating the auxiliary compensation coil in the magnetic field adjustment device according to the multi-stage compensation coil excitation parameters;

[0189] generating, based on the radial magnetic field gradient distribution diagram and the axial magnetic field offset in the magnetic field distribution data, a reverse compensation magnetic field that is spatially synchronized with the rotating main magnetic field of the axial magnetic field motor, wherein the gradient direction and amplitude of the reverse compensation magnetic field are opposite to the spatial inhomogeneity characteristics;

[0190] detecting changes in radial magnetic flux density in the air gap region in real time, and when detecting that the gradient distribution of the radial magnetic flux density does not reach a preset uniformity, increasing the excitation current of the auxiliary compensation coil until the preset uniformity is met;

[0191] During the speed change of the axial magnetic field motor, the energization timing of the auxiliary compensation coil is dynamically adjusted to match the phase offset of the rotating magnetic field, thereby ensuring spatial synchronization between the compensation magnetic field and the main magnetic field.

[0192] The present disclosure also provides an electronic device, including:

[0193] a memory having a computer program stored thereon;

[0194] A processor is used to execute the computer program in the memory to implement the steps of the method in any one of the aforementioned embodiments.

[0195] Figure 3The axial magnetic field motor noise suppression device 100 shown includes: a processor 1001 and a memory 1003. The processor 1001 and the memory 1003 are connected, such as through a bus 1002. Optionally, the axial magnetic field motor noise suppression device 100 may also include a communication component 1004, which can be used for data interaction between the device 100 and other devices, such as data transmission and / or data reception. It should be noted that in actual scheduling, the communication component 1004 is not limited to one, and the structure of the axial magnetic field motor noise suppression device 100 does not constitute a limitation on the embodiments of the present application.

[0196] Processor 1001 may be a CPU (Central Processing Unit), 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 device, transistor logic device, hardware component, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 1001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, or a combination of a DSP and a microprocessor.

[0197] Bus 1002 may include a path for transmitting information between the above components. Bus 1002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. Bus 1002 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0198] The memory 1003 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, other magnetic storage devices, or any other medium that can be used to carry or store program code and can be read by a computer, without limitation herein.

[0199] The memory 1003 is used to store program codes for executing the embodiments of the present disclosure, and the execution is controlled by the processor 1001. The processor 1001 is used to execute the program codes stored in the memory 1003 to implement the steps shown in the embodiment of the axial magnetic field motor noise suppression method.

[0200] The embodiment of the present disclosure further provides a computer-readable storage medium having program code stored thereon. When the program code is executed by a processor, the steps and corresponding contents of the aforementioned embodiment of the method for suppressing noise of an axial magnetic field motor can be implemented.

[0201] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, various changes, modifications, replacements and variations can be made to these embodiments, and these changes, modifications, replacements and variations all fall within the scope of protection of the present disclosure.

[0202] It should also be noted that the various specific technical features described in the above specific embodiments may be combined in any suitable manner, unless there is any contradiction, and these combinations shall also be considered as the contents disclosed in this disclosure. To avoid unnecessary repetition, this disclosure will not further describe various possible combinations. The technical scope of this application is not limited to the contents of the specification and must be determined based on the scope of the claims.

Claims

1. A method for suppressing noise of an axial magnetic field motor, characterized in that: The method comprises: Collecting current waveform data, vibration spectrum data, and magnetic field distribution data of the axial magnetic field motor in operation to construct a multi-dimensional operation status data set; performing synchronous coupling analysis processing on the multi-dimensional operating status data set to identify harmonic component characteristics in the current waveform data, resonant frequency characteristics in the vibration spectrum data, and spatial inhomogeneity characteristics in the magnetic field distribution data; Based on the harmonic component characteristics, the resonant frequency characteristics and the spatial inhomogeneity characteristics, a dynamic suppression strategy set is constructed, wherein the dynamic suppression strategy set includes a current waveform optimization strategy, a vibration frequency matching strategy and a magnetic field compensation strategy; generating initial phase compensation waveform parameters according to the dynamic suppression strategy set, and calling a preset harmonic suppression algorithm to iteratively optimize the initial phase compensation waveform parameters to generate optimized target current waveform parameters, wherein the iterative optimization includes amplitude suppression of harmonic components of a specified order in the initial phase compensation waveform parameters based on an amplitude attenuation coefficient, and phase cancellation of remaining harmonic components in the initial phase compensation waveform parameters based on a compensation phase angle; Calculating target current values ​​and power-on timings of each compensation coil in the magnetic field adjustment device according to the dynamic suppression strategy set and based on the excitation parameters of the multi-stage compensation coils, and generating a magnetic field adjustment instruction set according to the target current values ​​and power-on timings of each compensation coil; inputting the target current waveform parameters into a current controller of the axial magnetic field motor to adjust the output current waveform, and sending the magnetic field adjustment instruction set to a magnetic field adjustment device of the axial magnetic field motor to correct the spatial magnetic field distribution; The collecting of current waveform data, vibration spectrum data and magnetic field distribution data of the axial magnetic field motor in operation to construct a multi-dimensional operation status data set includes: Deploying a high-precision current sensor in the three-phase winding loop of the axial magnetic field motor to collect instantaneous current value and phase information in the current waveform data at a preset sampling frequency; A vibration acceleration sensor array is installed on the surface of the stator housing of the axial magnetic field motor, and a spectrum analyzer is used to obtain the time domain vibration signal and frequency domain energy distribution in the vibration spectrum data; Arranging a Hall sensor matrix in the air gap region of the axial magnetic field motor to measure the radial magnetic flux density and the axial magnetic flux density in the magnetic field distribution data; Performing timestamp alignment processing on the instantaneous current value, the time domain vibration signal, and the radial magnetic flux density to ensure time synchronization of the multi-dimensional operating status data set; Standardizing the aligned multi-dimensional operating status data set to eliminate amplitude deviations caused by sensor range differences, thereby obtaining the multi-dimensional operating status data set; The performing of synchronous coupling analysis on the multi-dimensional operating status data set to identify harmonic component characteristics in the current waveform data, resonant frequency characteristics in the vibration spectrum data, and spatial inhomogeneity characteristics in the magnetic field distribution data includes: Performing time-frequency decomposition processing on the current waveform data to extract the fundamental wave amplitude, harmonic order and harmonic phase offset from the harmonic component characteristics; Performing peak detection processing on the vibration spectrum data to determine the primary resonant frequency point, the secondary resonant frequency point, and the energy amplitude ratio of the corresponding frequencies in the resonant frequency characteristics; Performing spatial gradient calculation processing on the magnetic field distribution data to generate a radial magnetic field gradient distribution map and an axial magnetic field offset in the spatial inhomogeneity feature; Multiplying the harmonic order in the harmonic component feature by the fundamental frequency to obtain a harmonic electromagnetic excitation frequency, and performing correlation mapping with a main resonant frequency point in the resonant frequency feature to determine a first matching degree between the harmonic electromagnetic excitation frequency and the main resonant frequency point; A dynamic correlation model is established between the harmonic phase offset in the harmonic component characteristics and the axial magnetic field offset in the magnetic field distribution data. The modulation effect of the harmonic phase on the magnetic field distribution is calculated through the dynamic correlation model, and the initial phase adjustment amount in the phase compensation waveform parameter set is determined based on the modulation effect.

2. The method for suppressing noise of an axial magnetic field motor according to claim 1, characterized in that: The constructing of a dynamic suppression strategy set based on the harmonic component characteristics, the resonant frequency characteristics, and the spatial inhomogeneity characteristics includes: Establishing a correlation model between the harmonic component characteristics and the spatial inhomogeneity characteristics, and generating a magnetic field compensation strategy for describing the enhancement effect of harmonic currents of a specific order on the radial magnetic field gradient through the correlation model; Calculating a magnetic field distortion coefficient corresponding to the harmonic order according to the association model, and when the magnetic field distortion coefficient exceeds a preset threshold, triggering a priority adjustment instruction in the magnetic field compensation strategy to generate a current waveform optimization strategy for preferentially suppressing a current component corresponding to the harmonic order; The high-frequency noise bandwidth in the vibration spectrum data is determined based on the frequency domain energy distribution. When there is an overlapping area between the high-frequency noise bandwidth and the harmonic electromagnetic excitation frequency in the harmonic component characteristics, a bandwidth expansion instruction in the vibration frequency matching strategy is generated based on the resonance frequency characteristics to disperse the resonance energy, thereby obtaining a vibration frequency matching strategy.

3. The method for suppressing noise of an axial magnetic field motor according to claim 2, characterized in that: Generating a bandwidth extension instruction in the vibration frequency matching strategy according to the resonance frequency characteristics to disperse the resonance energy to obtain the vibration frequency matching strategy includes: Injecting a random frequency fine-tuning signal into the speed control loop of the axial magnetic field motor according to the resonant frequency characteristics to cause the driving frequency to fluctuate randomly within a preset range to destroy the resonance condition; adjusting the fluctuation amplitude of the random frequency fine-tuning signal according to the width of the high-frequency noise bandwidth to ensure that the fluctuation range of the driving frequency covers the overlapping area of ​​the high-frequency noise bandwidth; The vibration spectrum changes after the random frequency fine-tuning signal is injected are monitored in real time. When a decrease in the energy amplitude ratio of the main resonance frequency point in the resonance frequency characteristic is detected, a vibration frequency matching strategy is obtained to lock the current fluctuation amplitude as the optimal parameter and stop frequency fine-tuning.

4. The method for suppressing noise of an axial magnetic field motor according to claim 1, characterized in that: The constructing of a dynamic suppression strategy set based on the harmonic component characteristics, the resonant frequency characteristics, and the spatial inhomogeneity characteristics includes: generating a frequency offset instruction in the vibration frequency matching strategy based on a first matching degree between the harmonic electromagnetic excitation frequency in the harmonic component characteristic and the main resonant frequency point in the resonant frequency characteristic, wherein the frequency offset instruction is used to adjust the driving frequency of the axial magnetic field motor to deviate from the main resonant frequency point; Determining a phase compensation waveform parameter set in the current waveform optimization strategy based on a superposition analysis result of the harmonic phase offset and the axial magnetic field offset, wherein the phase compensation waveform parameter set includes a compensation phase angle and an amplitude attenuation coefficient of each harmonic; generating, according to the radial magnetic field gradient distribution diagram and the axial magnetic field offset, a multi-stage compensation coil excitation parameter in the magnetic field compensation strategy, wherein the multi-stage compensation coil excitation parameter is used to control the magnetic field adjustment device to generate a reverse magnetic field to offset the spatial inhomogeneity; A dynamic suppression strategy set is constructed according to the frequency offset instruction, the phase compensation waveform parameter set, and the multi-stage compensation coil excitation parameters.

5. The method for suppressing noise of an axial magnetic field motor according to claim 1, characterized in that: Inputting the target current waveform parameter into the current controller of the axial magnetic field motor to adjust the output current waveform includes: Reconstructing the PWM modulation signal of the current controller according to the target current waveform parameters so that the harmonic components of the output current waveform meet the preset amplitude threshold and phase symmetry conditions; monitoring the actual harmonic content of the output current waveform in real time, and dynamically adjusting the compensation phase angle and the amplitude attenuation coefficient when it is detected that the actual harmonic content exceeds the amplitude threshold to generate updated target current waveform parameters; The updated target current waveform parameters are fed back to the harmonic suppression algorithm for secondary optimization processing until the actual harmonic content is stabilized within the range of the amplitude threshold.

6. The method for suppressing noise of an axial magnetic field motor according to any one of claims 1 to 5, characterized in that: The step of sending the magnetic field adjustment instruction set to the magnetic field adjustment device of the axial magnetic field motor to correct the spatial magnetic field distribution includes: activating the auxiliary compensation coil in the magnetic field adjustment device according to the multi-stage compensation coil excitation parameters; generating, based on the radial magnetic field gradient distribution diagram and the axial magnetic field offset in the magnetic field distribution data, a reverse compensation magnetic field that is spatially synchronized with the rotating main magnetic field of the axial magnetic field motor, wherein the gradient direction and amplitude of the reverse compensation magnetic field are opposite to the spatial inhomogeneity characteristics; detecting changes in radial magnetic flux density in the air gap region in real time, and when detecting that the gradient distribution of the radial magnetic flux density does not reach a preset uniformity, increasing the excitation current of the auxiliary compensation coil until the preset uniformity is met; During the speed change of the axial magnetic field motor, the energization timing of the auxiliary compensation coil is dynamically adjusted to match the phase offset of the rotating magnetic field, thereby ensuring spatial synchronization between the compensation magnetic field and the main magnetic field.

7. An axial magnetic field motor noise suppression system, characterized in that: The system comprises: A first building module is configured to collect current waveform data, vibration spectrum data, and magnetic field distribution data of the axial magnetic field motor in an operating state, and build a multi-dimensional operating state data set; an analysis module configured to perform synchronous coupling analysis processing on the multi-dimensional operating status data set to identify harmonic component characteristics in the current waveform data, resonant frequency characteristics in the vibration spectrum data, and spatial inhomogeneity characteristics in the magnetic field distribution data; A second building module is configured to build a dynamic suppression strategy set based on the harmonic component characteristics, the resonant frequency characteristics, and the spatial inhomogeneity characteristics, wherein the dynamic suppression strategy set includes a current waveform optimization strategy, a vibration frequency matching strategy, and a magnetic field compensation strategy; a generation module configured to generate initial phase compensation waveform parameters according to the dynamic suppression strategy set, and call a preset harmonic suppression algorithm to iteratively optimize the initial phase compensation waveform parameters to generate optimized target current waveform parameters, wherein the iterative optimization includes amplitude suppression of harmonic components of a specified order in the initial phase compensation waveform parameters based on an amplitude attenuation coefficient, and phase cancellation of remaining harmonic components in the initial phase compensation waveform parameters based on a compensation phase angle; a calculation module configured to calculate, according to the dynamic suppression strategy set and based on the excitation parameters of the multi-stage compensation coils, a target current value and a power-on sequence for each compensation coil in the magnetic field adjustment device, and generate a magnetic field adjustment instruction set according to the target current value and the power-on sequence for each compensation coil; a control module configured to input the target current waveform parameters into a current controller of the axial magnetic field motor to adjust the output current waveform, and to send the magnetic field adjustment instruction set to a magnetic field adjustment device of the axial magnetic field motor to correct the spatial magnetic field distribution; The first building block is configured as follows: Deploying a high-precision current sensor in the three-phase winding loop of the axial magnetic field motor to collect instantaneous current value and phase information in the current waveform data at a preset sampling frequency; A vibration acceleration sensor array is installed on the surface of the stator housing of the axial magnetic field motor, and a spectrum analyzer is used to obtain the time domain vibration signal and frequency domain energy distribution in the vibration spectrum data; Arranging a Hall sensor matrix in the air gap region of the axial magnetic field motor to measure the radial magnetic flux density and the axial magnetic flux density in the magnetic field distribution data; Performing timestamp alignment processing on the instantaneous current value, the time domain vibration signal, and the radial magnetic flux density to ensure time synchronization of the multi-dimensional operating status data set; Standardizing the aligned multi-dimensional operating status data set to eliminate amplitude deviations caused by sensor range differences, thereby obtaining the multi-dimensional operating status data set; Wherein, the analysis module is configured to: Performing time-frequency decomposition processing on the current waveform data to extract the fundamental wave amplitude, harmonic order and harmonic phase offset from the harmonic component characteristics; Performing peak detection processing on the vibration spectrum data to determine the primary resonant frequency point, the secondary resonant frequency point, and the energy amplitude ratio of the corresponding frequencies in the resonant frequency characteristics; Performing spatial gradient calculation processing on the magnetic field distribution data to generate a radial magnetic field gradient distribution map and an axial magnetic field offset in the spatial inhomogeneity feature; Multiplying the harmonic order in the harmonic component feature by the fundamental frequency to obtain a harmonic electromagnetic excitation frequency, and performing correlation mapping with a main resonant frequency point in the resonant frequency feature to determine a first matching degree between the harmonic electromagnetic excitation frequency and the main resonant frequency point; A dynamic correlation model is established between the harmonic phase offset in the harmonic component characteristics and the axial magnetic field offset in the magnetic field distribution data. The modulation effect of the harmonic phase on the magnetic field distribution is calculated through the dynamic correlation model, and the initial phase adjustment amount in the phase compensation waveform parameter set is determined based on the modulation effect.

8. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 6.

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