Vibration suppression method and system for program-controlled tool multi-axis cooperative machining path

Abstract

The invention provides a vibration suppression method and system for a program control tool multi-axis cooperative machining path. The method comprises the following steps: firstly, collecting a vibration stress wave signal and a mechanical vibration signal at a multi-axis joint of a program-controlled cutter, and constructing a multi-axis vibration transmission path topological graph in combination with a pre-stored multi-axis modal rule base; a multi-source vibration signal is matched with the topological graph through a space-time alignment algorithm to generate a vibration characteristic data set, and the inter-axis vibration energy transmissibility is calculated by fusing propagation time delay and energy attenuation characteristics; then, the resonant frequency of the dominant path is extracted based on the energy transfer rate, and a phase inversion technology is adopted to generate an anti-phase vibration suppression waveform; and finally, accurately injecting the encoded inter-axis vibration anti-phase offset signal into a target transmission path to realize dynamic suppression of resonance energy in the machining process. According to the technical scheme provided by the invention, the vibration suppression efficiency and precision of the program-controlled tool multi-axis cooperative machining path can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of vibration suppression of programmable tools, and in particular to a vibration suppression method and system for a multi-axis collaborative machining path of a programmable tool. Background Art

[0002] During multi-axis machining, the composite vibration caused by the transmission of inter-axis structural resonance can significantly affect machining accuracy and equipment stability. Especially in scenarios involving five-axis high-speed machining centers or dual-robot collaborative operations, the differences in the rigidity of the machine tool spindle, guide rails, and fixture systems may cause vibrations to spread through structural coupling paths, forming a superposition effect of complex frequency bands. Such scenarios require the following technical goals: real-time identification and blocking of the energy transmission path of inter-axis vibrations, dynamic adjustment of the motion parameters of each axis to avoid resonant frequency excitation, and reduction of vibration accumulation caused by tool cutting in and out. Such technical requirements play a decisive role in the efficiency of high-precision complex surface machining and the quality of finished products.

[0003] To address the problem of inter-axis resonance transmission, a vibration suppression method based on cross-coupling control and adaptive path optimization has been proposed. This method introduces a cross-coupling compensation algorithm into the servo control system to perform real-time corrections to the vibration coupling effects between axes. Simultaneously, combined with an online cutting force prediction model and structural dynamics simulation results, the tool path's feed rate, cutting depth, and attitude angle are dynamically adjusted to avoid the resonant frequency range of the machine tool's weak rigidity areas. For example, in five-axis machining, by changing the tool attitude angle, the cutting force direction deviates from the machine tool's structural areas with lower rigidity, thereby reducing vibration transmission efficiency. This method has been initially applied in some high-end CNC equipment, improving the stability of complex trajectory machining.

[0004] Although existing methods can suppress inter-axis vibration transmission to a certain extent, they still have obvious limitations. The cross-coupling control and path optimization process requires reliance on high-precision dynamic models, which has high computational complexity and is difficult to cope with sudden vibration disturbances during the processing process. The suppression effect of this method is highly dependent on the accuracy of the machine tool structural parameters and the cutting force prediction model. However, in actual processing, the state of the machine tool may change dynamically due to factors such as wear and loose fixtures, resulting in model mismatch. In addition, the existing scheme mainly focuses on low-frequency resonance optimization, and the ability to suppress high-frequency vibrations is insufficient, which may still cause surface quality defects. It is necessary to further expand the coverage of the suppression frequency band. Summary of the Invention

[0005] The present application provides a method and system for suppressing vibration of a multi-axis collaborative machining path of a programmable tool, so as to solve the problems of low efficiency and poor precision of vibration suppression of a multi-axis collaborative machining path of a programmable tool in the prior art.

[0006] In a first aspect, the present application provides a method for suppressing vibration of a multi-axis collaborative machining path of a programmable tool, comprising:

[0007] Acquire multi-source vibration signals at the multi-axis joint of the programmable knife, wherein the multi-source vibration signals include vibration stress wave signals and mechanical vibration signals;

[0008] Based on the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool, combined with a pre-stored multi-axis modal rule library, a multi-axis vibration transmission path topology diagram is generated;

[0009] performing spatiotemporal alignment of the multi-source vibration signals with the multi-axis vibration transmission path topology to obtain a vibration feature dataset, and fusing the propagation delay characteristics and energy attenuation characteristics of the vibration feature dataset in the multi-axis vibration transmission path topology to generate an inter-axis vibration energy transfer rate;

[0010] extracting the resonant frequency of the dominant vibration transfer path in the multi-axis vibration transfer path topology diagram based on the inter-axis vibration energy transfer rate, and performing phase flipping on the resonant frequency to generate an anti-phase vibration suppression waveform;

[0011] The anti-phase vibration suppression waveform is encoded to obtain an inter-axis vibration anti-phase cancellation signal, and the inter-axis vibration anti-phase cancellation signal is associated with the target transfer path corresponding to the processing path in the multi-axis vibration transfer path topology diagram to dynamically suppress the resonance energy of the target transfer path.

[0012] Optionally, extracting the resonant frequency of the dominant vibration transfer path in the multi-axis vibration transfer path topology diagram based on the inter-axis vibration energy transfer rate, and performing phase flipping on the resonant frequency to generate an anti-phase vibration suppression waveform includes:

[0013] Calculating a path weight coefficient set for each machining path based on the multi-axis vibration transmission path topology map, screening weight coefficients exceeding a preset value from the path weight coefficient set, and defining the machining path corresponding to the screened weight coefficient as a dominant vibration transmission path;

[0014] extracting a vibration energy spectrum of the dominant vibration transfer path from the inter-axis vibration energy transfer rate, and identifying a vibration energy peak region in the vibration energy spectrum as a resonant frequency of the dominant vibration transfer path;

[0015] Based on the phase spectrum data of the inter-axis vibration energy transfer rate, the original phase angle corresponding to the resonant frequency is calculated, and the original phase angle is subjected to an anti-phase shift to generate an anti-phase vibration suppression waveform.

[0016] Optionally, the calculating the original phase angle corresponding to the resonant frequency based on the phase spectrum data of the inter-axis vibration energy transfer rate includes:

[0017] Locating the spectrum bandwidth range of the resonant frequency in the phase spectrum data based on the phase spectrum data of the inter-axial vibration energy transfer rate, and extracting the center frequency point position in the spectrum bandwidth range;

[0018] The phase value record corresponding to the center frequency point position in the phase spectrum data is extracted, and the phase value record is phase corrected in combination with the propagation delay characteristics in the multi-axis vibration transmission path topology diagram. The corrected phase value record is converted into an angle dimension representation to obtain the original phase angle.

[0019] Optionally, the generating of a multi-axis vibration transmission path topology diagram based on the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool in combination with a pre-stored multi-axis modal rule library includes:

[0020] Calculating vibration transmission direction indication parameters between adjacent physical nodes in the programmable knife multi-axis motion chain based on the propagation time sequence of the vibration stress wave signal in the programmable knife multi-axis motion chain;

[0021] Determining an energy attenuation ratio value based on a variation range of peak amplitudes of the mechanical vibration signal between the physical nodes, and quantifying the energy attenuation ratio value as a connection strength parameter between the physical nodes;

[0022] Calling a structural connection relationship in a pre-stored multi-axis modal rule library to establish a spatial mapping relationship between the structural connection relationship and the physical node;

[0023] The vibration transmission direction indication parameter, the connection strength parameter and the spatial mapping relationship are combined to generate a multi-axis vibration transmission path topology diagram.

[0024] Optionally, fusing the propagation delay feature and the energy attenuation feature of the vibration feature data set in the multi-axis vibration transfer path topology diagram to generate the inter-axis vibration energy transfer rate includes:

[0025] Extracting propagation delay features of the vibration feature data set in the multi-axis vibration transmission path topology diagram, and calculating a path vibration transmission efficiency index based on the numerical distribution of the propagation delay features between the transmission path nodes in the multi-axis vibration transmission path topology diagram;

[0026] Extracting energy attenuation characteristics of the vibration feature data set in the multi-axis vibration transmission path topology diagram, and determining a vibration energy loss coefficient based on a change gradient of the energy attenuation characteristics between nodes of the transmission path;

[0027] Proportionally integrating the path vibration transmission efficiency index and the vibration energy loss coefficient to generate a basic transmission rate parameter;

[0028] Based on the connection strength between the transmission path nodes, a transmission path correction factor is calculated, and the basic transmissibility parameter is adjusted using the transmission path correction factor to generate the inter-axis vibration energy transmissibility.

[0029] Optionally, the calculating the transfer path correction factor based on the connection strength between the transfer path nodes includes:

[0030] Integrating the connection strengths between the nodes of each transmission path to obtain a path connection strength parameter set, and calculating the intensity distribution dispersion of the connection strengths in the path connection strength parameter set;

[0031] Comparing the intensity distribution dispersion with a preset stability grade classification rule to determine a transfer path stability grade identifier, and matching a correction coefficient from a predefined correction rule library based on the transfer path stability grade identifier;

[0032] The correction coefficient is associated with a pre-stored reference correction factor to generate a transfer path correction factor.

[0033] Optionally, encoding the anti-phase vibration suppression waveform to obtain an inter-axis vibration anti-phase cancellation signal includes:

[0034] extracting waveform frequency parameters based on the periodic oscillation characteristics of the anti-phase vibration suppression waveform, and converting the waveform frequency parameters into drive frequency control instructions;

[0035] Acquiring waveform phase parameters according to the phase offset characteristics of the anti-phase vibration suppression waveform, and converting the waveform phase parameters into a driving phase control instruction containing a phase offset code;

[0036] The driving frequency control instruction and the driving phase control instruction are combined in time sequence to generate an inter-axis vibration anti-phase cancellation signal.

[0037] In a second aspect, the present application provides a vibration suppression system for a multi-axis collaborative machining path of a programmable tool, comprising:

[0038] An acquisition module is used to acquire multi-source vibration signals at the multi-axis joints of the programmable knife, wherein the multi-source vibration signals include vibration stress wave signals and mechanical vibration signals;

[0039] A generation module generates a multi-axis vibration transmission path topology diagram based on the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool and in combination with a pre-stored multi-axis modal rule library;

[0040] a fusion module that performs spatiotemporal alignment of the multi-source vibration signals with the multi-axis vibration transmission path topology map to obtain a vibration feature dataset, and fuses the propagation delay characteristics and energy attenuation characteristics of the vibration feature dataset in the multi-axis vibration transmission path topology map to generate an inter-axis vibration energy transfer rate;

[0041] a flip module, which extracts the resonant frequency of the dominant vibration transfer path in the multi-axis vibration transfer path topology diagram based on the inter-axis vibration energy transfer rate, and performs a phase flip on the resonant frequency to generate an anti-phase vibration suppression waveform;

[0042] The encoding module encodes the anti-phase vibration suppression waveform to obtain an inter-axis vibration anti-phase cancellation signal, and associates the inter-axis vibration anti-phase cancellation signal with the target transfer path corresponding to the processing path in the multi-axis vibration transfer path topology diagram, thereby dynamically suppressing the resonance energy of the target transfer path.

[0043] In a third aspect, an embodiment of the present application provides a computing device comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a vibration suppression method for a multi-axis collaborative machining path of a programmable tool as described in the first aspect above.

[0044] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program. When the computer program is executed by a computer, it implements a vibration suppression method for a multi-axis collaborative machining path of a programmable tool as described in the first aspect.

[0045] In an embodiment of the present application, a multi-source vibration signal is obtained at a multi-axis joint of a programmable tool, wherein the multi-source vibration signal includes a vibration stress wave signal and a mechanical vibration signal; based on the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool, combined with a pre-stored multi-axis modal rule library, a multi-axis vibration transmission path topology map is generated; the multi-source vibration signal is aligned with the multi-axis vibration transmission path topology map in time and space to obtain a vibration feature data set, and the propagation delay characteristics and energy attenuation characteristics of the vibration feature data set in the multi-axis vibration transmission path topology map are fused to generate an inter-axis vibration energy transfer rate; based on the inter-axis vibration energy transfer rate, the resonant frequency of the dominant vibration transmission path in the multi-axis vibration transmission path topology map is extracted, and the phase of the resonant frequency is flipped to generate an anti-phase vibration suppression waveform; the anti-phase vibration suppression waveform is encoded to obtain an inter-axis vibration anti-phase cancellation signal, and the inter-axis vibration anti-phase cancellation signal is associated with the target transmission path corresponding to the machining path in the multi-axis vibration transmission path topology map to dynamically suppress the resonance energy of the target transmission path.

[0046] The technical solution of this application has the following beneficial effects:

[0047] This application realizes comprehensive monitoring of vibrations of different physical mechanisms in the multi-axis system of programmable tools by collecting vibration stress wave signals and mechanical vibration signals, providing a high-precision data basis for subsequent analysis. Combining the vibration propagation characteristics with the pre-stored modal rule library, a system-level vibration transfer network model is constructed to clarify the vibration coupling relationship between the axes, providing a structural basis for accurately locating the vibration transmission path. By fusion of spatiotemporal alignment with propagation delay and energy attenuation characteristics, the transmission efficiency of vibration energy between axes is quantified, the main propagation channels and attenuation laws of vibration energy are revealed, and key parameters are provided for the suppression strategy. Based on the energy transfer rate, the resonant frequency of the dominant path is identified, and the anti-phase vibration signal is designed by phase reversal to achieve active cancellation of vibrations of specific frequencies and improve the suppression efficiency. The anti-phase cancellation signal is accurately associated with the target transfer path to achieve real-time dynamic regulation during the processing process, significantly reduce the accumulation of resonance energy, and improve processing stability and accuracy.

[0048] Furthermore, by calculating the path weight coefficient set of the processing path and screening the paths above the threshold, the dominant vibration transmission path is determined, and the resonant frequency is further identified by combining the vibration energy spectrum. Based on the phase spectrum data, an anti-phase vibration suppression waveform is generated, thereby achieving precise suppression of the key vibration path. This method accurately locates the main propagation channels of vibration energy in the multi-axis system through quantified path weights and energy spectrum analysis, avoiding the blind suppression of the entire path by traditional methods. At the same time, the phase reversal technology is used to generate an anti-phase waveform to specifically offset the resonant energy of the dominant path, significantly improving the efficiency and accuracy of vibration suppression, reducing vibration interference during the processing process, extending equipment life and improving processing quality.

[0049] These and other aspects of the present application will become more readily apparent from the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0051] Figure 1 A flow chart showing a method for suppressing vibration of a multi-axis collaborative machining path of a programmable tool provided by the present application is shown;

[0052] Figure 2 A schematic structural diagram of a vibration suppression system for a multi-axis collaborative machining path of a programmable tool provided by the present application is shown;

[0053] Figure 3 A schematic structural diagram of a computing device provided by the present application is shown. DETAILED DESCRIPTION

[0054] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0055] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to being different types.

[0056] During multi-axis linkage machining, the composite vibration caused by the transmission of structural resonance between axes will significantly affect machining accuracy and equipment stability. In the existing technology, although the vibration suppression method based on cross-coupling control and adaptive path optimization can achieve low-frequency resonance suppression by dynamically adjusting cutting parameters and tool posture angles, it relies on high-precision dynamic models and structural parameters, has high computational complexity, and is difficult to cope with sudden vibration disturbances during machining. In addition, such methods lack robustness to dynamic state changes caused by machine tool wear, loose fixtures, etc., and have insufficient ability to suppress high-frequency vibrations, resulting in frequent surface quality defects. For example, in a multi-axis high-speed machining center, the vibration superposition effect caused by the difference in rigidity between the spindle and the guide rail, as well as the complex structural coupling path in the dual-robot collaborative operation scenario, are beyond the adaptability of existing methods. There is an urgent need for an innovative technology that can identify the vibration transmission path in real time and dynamically block the diffusion of resonance energy.

[0057] In response to the above problems, the present application proposes a vibration suppression method for multi-axis collaborative machining paths of programmable tools, which realizes accurate modeling and dynamic suppression of inter-axis vibration energy transfer paths through spatiotemporal alignment and energy transfer rate analysis of multi-source vibration signals. Specifically, the method first collects the vibration stress wave signals and mechanical vibration signals at the multi-axis joints of the programmable tool, generates a vibration transfer path topology map based on the pre-stored multi-axis modal rule library, quantifies the propagation delay and attenuation characteristics of the vibration energy between each axis, and thus identifies the resonant frequency of the dominant vibration transfer path. Subsequently, an anti-phase vibration suppression waveform is generated by phase flipping the resonant frequency, and it is encoded into an inter-axis vibration anti-phase cancellation signal, which is dynamically associated with the target transfer path to block the diffusion of resonant energy. This solution breaks through the traditional method's reliance on dynamic models and cutting parameter predictions, and realizes active suppression of wide-band vibrations through real-time monitoring and phase cancellation technology, showing stronger robustness in high-frequency vibration scenarios. At the same time, the dynamic adjustment mechanism based on the multi-axis vibration transmission path topology map can adapt to changes in machine tool status, significantly improving the stability and surface quality of complex surface processing, and providing key technical support for high-precision multi-axis collaborative processing.

[0058] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0059] Figure 1 A flowchart of a method for suppressing vibration of a multi-axis collaborative machining path of a programmable tool is provided for an embodiment of the present application. Figure 1 As shown, the method includes:

[0060] 101. Acquire a multi-source vibration signal at a multi-axis joint of a programmable knife, wherein the multi-source vibration signal includes a vibration stress wave signal and a mechanical vibration signal;

[0061] In this step, the programmable tool multi-axis joint refers to the core component in the programmable tool system for realizing multi-axis linkage, and its structure and function are similar to the multi-degree-of-freedom motion characteristics of human joints.

[0062] The vibration stress wave signal originates from the elastic deformation caused by the force inside the material, and can reflect the internal response characteristics of mechanical components under dynamic load.

[0063] Mechanical vibration signals are caused by external excitations, such as cutting force and periodic motion of the drive motor, and reflect the changes in displacement, velocity or acceleration of components during the movement of the equipment.

[0064] The multi-source vibration signal collection integrates the above two types of signals and ensures the consistency of the data in time and space dimensions through timestamp alignment and spatial position matching.

[0065] In the embodiment of the present application, first, a three-axis acceleration sensor and a fiber Bragg grating stress sensor are arranged at the joints of the programmable knife multi-axis system to collect vibration stress wave signals and mechanical vibration signals in real time. Subsequently, the two types of signals are time-stamp aligned by synchronous sampling technology to ensure the consistency of multi-source data in the time domain and space domain. Next, the original signal is subjected to noise reduction processing using a wavelet transform algorithm to remove high-frequency noise and interference components. Finally, the vibration stress wave signal after noise reduction is preliminarily fused with the mechanical vibration signal to generate a multi-source vibration signal containing the vibration characteristics of multiple physical mechanisms, providing basic data support for subsequent analysis.

[0066] In a five-axis machining center, when a tool cuts thin-walled parts at high speed, the spindle bearing generates mechanical vibration signals due to the cutting force, while the guideway slider generates stress wave signals due to the elastic deformation of the material. Using sensors placed on the spindle and guideway, the system collects both vibration stress wave signals and mechanical vibration signals in real time, providing a data foundation for subsequent analysis.

[0067] 102. Based on the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool, combined with a pre-stored multi-axis modal rule library, generate a multi-axis vibration transmission path topology diagram;

[0068] In this step, the multi-axis motion chain of the programmable tool refers to a linkage system formed by connecting multiple motion axes in the programmable tool system in series through mechanical structure or control logic.

[0069] Propagation characteristics refer to the physical laws exhibited by vibration signals when they are transmitted in the multi-axis motion chain of a programmable tool, including characteristics such as propagation path, time delay, energy attenuation and coupling effect.

[0070] The multi-axis modal rule library refers to a database built based on machine tool structure design parameters and historical vibration test data, which stores the modal vibration shapes and coupling relationships of each axis joint.

[0071] The multi-axis vibration transmission path topology diagram is a graph structure with multi-axis joints as nodes and vibration energy propagation paths as edges. The edge weights are determined by the amplitude and phase difference of the signal transfer function, which intuitively displays the propagation direction and intensity of the vibration energy.

[0072] In an embodiment of the present application, first, the frequency domain characteristics and time domain characteristics of the signal are extracted by fast Fourier transform from the vibration stress wave signal and the mechanical vibration signal. Subsequently, the extracted vibration characteristics are matched with the modal vibration shapes in the pre-stored multi-axis modal rule library to identify the modal vibration shape and coupling relationship corresponding to the current vibration signal. Next, with each axis joint as a node, a graph structure is constructed based on the propagation direction and coupling strength of the modal vibration shape. The nodes represent the joints, and the edge weights are determined by the transfer function amplitude and phase difference, forming a multi-axis vibration transfer path topology diagram.

[0073] In a five-axis machining center, spectrum analysis revealed that the spindle's vibration energy is primarily concentrated within a specific frequency range. Combining data from a multi-axis modal rule library confirmed that this frequency corresponds to a coupled mode between the spindle and the guideway, where spindle bending causes guideway slippage. A topological diagram was constructed using the spindle, guideway, and coupling as nodes. Edge weights were calculated using the amplitude and phase difference of the transfer function, resulting in a vibration transmission topology diagram encompassing the coupled paths of the spindle, guideway, and coupling.

[0074] 103. Performing spatiotemporal alignment on the multi-source vibration signals and the multi-axis vibration transmission path topology map to obtain a vibration feature dataset, and fusing the propagation delay characteristics and energy attenuation characteristics of the vibration feature dataset in the multi-axis vibration transmission path topology map to generate an inter-axis vibration energy transfer rate;

[0075] In this step, spatiotemporal alignment refers to synchronizing and matching multi-source data in the time and space dimensions to ensure that information from different data sources can be associated in the same spatiotemporal coordinate system.

[0076] The vibration feature dataset is a set of vibration signals collected and preprocessed by multi-source sensors, which contains feature parameters in the time domain, frequency domain, and time-frequency domain.

[0077] The propagation delay feature describes the time delay of the vibration signal propagating along the edge of the topology graph, and the timing offset of the signal between adjacent nodes is calculated through the cross-correlation function.

[0078] The energy attenuation characteristics reflect the loss of vibration energy along the path and are estimated based on material properties and axis spacing.

[0079] The inter-axis vibration energy transfer rate refers to the ratio of input energy to output energy, quantifies the transmission efficiency of vibration energy between axes, and provides a basis for subsequent suppression strategies.

[0080] In the embodiments of the present application, a generalized cross-correlation algorithm is first used to calculate the propagation delay of multi-source vibration signals in a multi-axis vibration transfer path topology diagram, and dynamic time warping techniques are used to map the signal features to corresponding topological nodes. Subsequently, a cross-correlation function is used to calculate the propagation delay characteristics of the vibration feature dataset along the edges of the multi-axis vibration transfer path topology diagram, and the energy decay characteristics are quantified using an exponential decay model. Finally, the inter-axis vibration energy transfer rate between each axis is calculated by fusing the propagation delay characteristics with the energy decay characteristics.

[0081] In the spindle-to-guideway path of a five-axis machining center, a cross-correlation function was used to calculate the time difference between the spindle vibration signal and the guideway slider, revealing a delay of several milliseconds in signal propagation. The damping properties of the guideway material and the distance between the spindle and the guideway were combined to estimate the vibration energy attenuation along the path. If the input energy is high while the energy at the guideway is significantly reduced, the vibration energy transfer rate of this path is considered low, and the coupling relationship requires special attention.

[0082] 104. Extracting the resonant frequency of the dominant vibration transfer path in the multi-axis vibration transfer path topology diagram based on the inter-axis vibration energy transfer rate, and performing phase flipping on the resonant frequency to generate an anti-phase vibration suppression waveform;

[0083] In this step, the dominant vibration transmission path refers to a path with a higher vibration energy transmission rate, which is usually the main propagation channel of vibration energy.

[0084] The resonant frequency refers to the frequency with the highest energy concentration in the vibration signal spectrum, which corresponds to the natural vibration mode of the equipment.

[0085] Phase reversal refers to the phenomenon in which the phase of a signal wave is reversed during propagation or reflection.

[0086] The anti-phase vibration suppression waveform refers to a sine wave with the same amplitude and opposite phase as the resonant frequency, which is used to actively offset the resonant energy and weaken the impact of vibration.

[0087] In this embodiment, the transmissibility matrix is ​​first used to identify paths with inter-axis vibration energy transfer rates exceeding a threshold, marking them as the dominant vibration transfer paths. Spectral analysis is then performed on the vibration signals of these dominant vibration transfer paths, extracting the resonant frequencies from the energy spectrum. Subsequently, the original phase angles corresponding to the resonant frequencies are calculated from the phase spectrum data and a phase flip is performed on these phase angles to generate an inverted vibration suppression waveform.

[0088] In a five-axis machining center, spectrum analysis reveals a concentrated energy concentration near the spindle's vibration signal along the guideway path. This frequency is identified as the spindle's resonant frequency. The original phase angle corresponding to this frequency is calculated based on the phase spectrum data, and a sinusoidal wave with the opposite phase to the original signal is generated as an anti-phase vibration suppression waveform. This waveform, by superposition, offsets the spindle's resonant energy, reducing the impact of vibration on machining accuracy.

[0089] 105. Encode the anti-phase vibration suppression waveform to obtain an inter-axis vibration anti-phase cancellation signal, and associate the inter-axis vibration anti-phase cancellation signal with a target transfer path corresponding to the processing path in the multi-axis vibration transfer path topology diagram to dynamically suppress the resonance energy of the target transfer path.

[0090] In this step, the inter-axis vibration anti-phase cancellation signal refers to the control signal after the anti-phase vibration suppression waveform is encoded, and is output to the key parts of the equipment through piezoelectric ceramics or electromagnetic actuators.

[0091] The machining path refers to the movement trajectory of the tool relative to the workpiece during the machining process of the CNC machine tool.

[0092] The target transfer path is the actual vibration propagation path corresponding to the current processing path in the topology diagram, and its resonance energy needs to be suppressed first.

[0093] Resonance energy refers to the additional stability energy caused by the resonance effect of a molecule.

[0094] In an embodiment of the present application, first, the anti-phase vibration suppression waveform is converted into a pulse width modulation signal, which is output to the piezoelectric ceramic or electromagnetic actuator through a digital-to-analog converter to obtain an inter-axis vibration anti-phase cancellation signal. According to the current processing path, the corresponding target transfer path is matched in the multi-axis vibration transfer path topology diagram, and the inter-axis vibration anti-phase cancellation signal is injected into the key nodes of the target transfer path, such as the guide rail slider. By monitoring the vibration signal residual in real time, the amplitude and phase of the anti-phase vibration suppression waveform are adjusted to form a closed-loop control. Ultimately, the resonance energy of the target transfer path is dynamically suppressed, the diffusion of vibration energy is blocked, and the processing stability and accuracy are improved.

[0095] In a five-axis machining center, an anti-phase vibration suppression waveform is injected into the electromagnetic actuator near the guideway slider in the spindle-to-guideway path. Based on the anti-phase signal, the actuator generates vibrations at a phase opposite to the spindle's resonant frequency, counteracting the resonant energy at the guideway. By monitoring the residual vibration of the guideway slider in real time, the amplitude and phase of the anti-phase waveform are dynamically adjusted to ensure the stability of the suppression effect. Ultimately, the resonant energy in the target path is effectively reduced, improving the smoothness of the machining process.

[0096] In summary, steps 101 to 105 achieve precise control of the vibration energy of a multi-axis system using programmable tooling through multi-source vibration signal acquisition, topology mapping, energy transfer rate analysis, and anti-phase suppression technology. In multi-axis machining center applications, this approach significantly reduces vibration interference during machining, improving both precision and stability by suppressing the resonance energy of the spindle-to-guideway path.

[0097] To address the problem of vibration transmission path analysis and suppression in multi-axis machining centers, this solution analyzes the path weight coefficients in the multi-axis vibration transmission path topology to screen the dominant vibration transmission path, identifies the resonant frequency in combination with the vibration energy spectrum, and generates an anti-phase vibration suppression waveform based on the phase spectrum data, thereby achieving directional suppression of the key vibration path. In some embodiments, step 104 extracts the resonant frequency of the dominant vibration transmission path in the multi-axis vibration transmission path topology based on the inter-axis vibration energy transfer rate, and performs a phase flip on the resonant frequency to generate the anti-phase vibration suppression waveform, including:

[0098] 201. Calculating a path weight coefficient set for each machining path based on the multi-axis vibration transmission path topology map, screening weight coefficients exceeding a preset value from the path weight coefficient set, and defining the machining path corresponding to the screened weight coefficient as a dominant vibration transmission path;

[0099] In step 201, the path weight coefficient set refers to a set of quantitative parameters that describe the energy transfer efficiency of each machining path in the multi-axis vibration transmission path topology. A higher weight coefficient indicates that the path transfers more vibration energy. The dominant vibration transmission path is a machining path whose path weight coefficient exceeds a preset threshold and is the primary propagation channel for resonant energy. The preset value is a threshold set based on engineering experience or experimental data and is used to screen paths that significantly impact vibration.

[0100] In an embodiment of the present application, first, based on the multi-axis vibration transfer path topology map, the vibration signals of each axis are collected by sensors, and the path weight coefficient set of each path is calculated in combination with the transfer function matrix. Subsequently, a preset value is set as a threshold, and the paths with weight coefficients exceeding the threshold are screened out through the threshold comparison algorithm. The screening results are used as the dominant vibration transfer path for subsequent analysis. For example, if the weight coefficient of a path in the topology map is significantly higher than that of other paths, it is marked as the dominant path and becomes the focus of optimization. This process is completed through three steps: data collection, weight calculation, and threshold screening, and finally the dominant path set is output.

[0101] 202. Extracting a vibration energy spectrum of the dominant vibration transfer path from the inter-axis vibration energy transfer rate, and identifying a vibration energy peak region in the vibration energy spectrum as a resonant frequency of the dominant vibration transfer path;

[0102] In step 202, the vibration energy spectrum refers to a frequency domain graph with frequency as the horizontal axis and energy amplitude as the vertical axis, reflecting the distribution of vibration energy at different frequencies. The vibration energy peak region refers to the local area in the energy spectrum where the energy is significantly higher than the surrounding frequencies in the frequency domain analysis of the vibration signal. The resonant frequency refers to the frequency point corresponding to the energy peak in the vibration energy spectrum, indicating that the system is prone to resonance at this frequency.

[0103] In an embodiment of the present application, first, the corresponding inter-axis vibration energy transfer rate data is extracted from the dominant vibration transfer path. The time domain vibration signal is converted into a frequency domain signal using fast Fourier transform to generate a vibration energy spectrum. Subsequently, the peak detection algorithm is used to identify the vibration energy peak area in the vibration energy spectrum whose amplitude is significantly higher than the surrounding frequency, and the resonance frequency of the dominant vibration transfer path is determined. For example, if the vibration energy spectrum of a certain path has a peak at a specific frequency, then the frequency is determined to be the resonance frequency. This process is completed through three steps: data extraction, frequency domain conversion, and peak recognition, and the resonance frequency information is finally output.

[0104] 203. Calculate the original phase angle corresponding to the resonant frequency based on the phase spectrum data of the inter-axis vibration energy transfer rate, and perform an anti-phase shift on the original phase angle to generate an anti-phase vibration suppression waveform.

[0105] In step 203, phase spectrum data refers to the phase information describing the vibration signal at different frequencies, typically obtained through Fourier transform. The original phase angle refers to the phase value corresponding to the resonant frequency, reflecting the starting position of the vibration waveform. Phase shifting involves adjusting the original phase angle to the opposite value, generating a suppressed waveform with the opposite phase to the original vibration waveform.

[0106] In the embodiments of the present application, first, based on the phase spectrum data of the inter-axial vibration energy transfer rate, the original phase angle corresponding to the resonant frequency is directly read from the phase spectrum data of the vibration signal using a Fourier transform algorithm. Subsequently, the original phase angle is numerically processed using a phase compensation algorithm to ensure that the new phase angle after the anti-phase shift forms a phase difference of 180° with the original phase angle. Finally, the anti-phase vibration suppression waveform is generated using signal synthesis technology by combining the phase angle after the anti-phase shift with the amplitude information of the original vibration signal.

[0107] Here's a specific example:

[0108] In a five-axis machining center, abnormal Z-axis vibration was found during the machining of a workpiece. By constructing a multi-axis vibration transmission path topology map, it was found that the path weight coefficient between the Z-axis and the X-axis was high, exceeding the set threshold, and was marked as a critical vibration transmission path. The vibration energy spectrum was extracted from the inter-axis vibration energy transfer rate corresponding to the path, and the frequency point corresponding to the energy peak was identified as the resonant frequency. The original phase angle was calculated based on the phase spectrum data of the resonant frequency, and the original phase angle was reversed to generate a suppressed waveform with a phase opposite to the original vibration waveform. The suppressed waveform was injected into the machine tool through the active vibration control system to achieve vibration cancellation, and the surface roughness met the process standards.

[0109] In summary, steps 201 to 203 analyze the vibration transmission paths during multi-axis machining, screen the dominant path, and accurately identify its resonant frequency. Combined with the generation and injection of an anti-phase vibration suppression waveform, this method effectively reduces the vibration amplitude of the critical axis. This method not only improves machining accuracy and surface quality, but also extends the service life of key machine tool components while reducing vibration-related workpiece scrap and maintenance costs.

[0110] In order to solve the problem of excessive surface roughness caused by abnormal vibration during multi-axis machining, the solution uses phase spectrum data to locate the spectrum bandwidth corresponding to the resonant frequency, combines the propagation delay characteristics to correct the phase value, and finally converts it into the original phase angle in the angular dimension to ensure the precise phase matching of the anti-phase vibration suppression waveform. By introducing a propagation delay correction mechanism, the phase deviation caused by path structure differences is effectively eliminated, providing a high-precision phase reference for subsequent anti-phase cancellation. In some embodiments, the calculation of the original phase angle corresponding to the resonant frequency based on the phase spectrum data of the inter-axis vibration energy transfer rate in step 203 includes:

[0111] 301. Locate the spectrum bandwidth range of the resonant frequency in the phase spectrum data based on the phase spectrum data of the inter-axial vibration energy transfer rate, and extract the center frequency point position in the spectrum bandwidth range;

[0112] In step 301, phase spectrum data refers to the frequency domain phase information set generated by Fourier transform after the vibration signals of each axis are collected by the sensor. It describes the phase distribution characteristics of the vibration energy at different frequencies. The spectrum bandwidth range refers to the local frequency band corresponding to the resonant frequency in the phase spectrum, where the energy is concentrated and the phase changes significantly. The center frequency point position refers to the frequency point with the most dramatic phase change within the spectrum bandwidth, which usually corresponds to the core position of the resonant frequency.

[0113] In the embodiment of the present application, first, the inter-axis vibration energy transfer rate is converted into a frequency domain signal by a Fourier transform algorithm, generating phase spectrum data containing the phase information of each frequency point. Subsequently, the spectrum bandwidth analysis technology is used to identify the spectrum bandwidth range corresponding to the resonant frequency in the phase spectrum data. That is, in the phase spectrum, the area where the phase change rate exceeds the preset threshold is searched to locate the energy concentration bandwidth of the resonant frequency. Finally, within the identified spectrum bandwidth, the peak detection algorithm is used to extract the frequency point with the most significant phase change as the center frequency point position.

[0114] 302. Extract the phase value record corresponding to the center frequency point position in the phase spectrum data, and perform phase correction on the phase value record in combination with the propagation delay characteristics in the multi-axis vibration transmission path topology diagram, and convert the corrected phase value record into an angle dimension representation to obtain the original phase angle.

[0115] In step 302, the phase value record refers to the set of phase values ​​corresponding to the center frequency point position in the phase spectrum, which reflects the starting angle of the vibration waveform at the resonant frequency. The propagation delay characteristic refers to the difference in vibration propagation time of each path in the multi-axis vibration transmission path topology diagram, which is determined by factors such as the distance between axes and the stiffness of the material. Phase correction refers to the process of adjusting the phase of the signal through technical means to meet specific requirements or eliminate phase deviation. Angle dimension representation refers to the conversion of the corrected phase value record into an angle unit representation.

[0116] In an embodiment of the present application, first, the phase value record corresponding to the center frequency point position is extracted from the phase spectrum data. The phase value record includes the starting angle of the vibration waveform at the resonant frequency. Subsequently, the phase value record is corrected using cross-correlation analysis technology in combination with the propagation delay characteristics of each path in the multi-axis vibration transmission path topology diagram. During the correction process, the phase value is adjusted by calculating the delay difference of each vibration transmission path to eliminate the phase offset caused by path propagation. Finally, the corrected phase value is converted into an angular dimension by converting radians and degrees to obtain the original phase angle.

[0117] Here's a specific example:

[0118] In a five-axis machining center, the Z-axis vibrated abnormally during machining of a certain workpiece, and the surface roughness exceeded the standard. The vibration signals of the X-axis and Z-axis were collected and phase spectrum data was generated. The spectrum bandwidth range corresponding to the resonant frequency and the position of its center frequency point were identified. The corresponding phase value records were extracted and combined with the propagation delay characteristics between multiple axes in the multi-axis vibration transmission path topology diagram. Due to the delay caused by the difference in path length, the phase value was corrected using cross-correlation analysis to eliminate the phase offset caused by the delay. Finally, the corrected phase value was converted to the original phase angle. Based on this phase angle, an anti-phase vibration suppression waveform was generated. After being injected into the machine tool, vibration cancellation was achieved, which reduced the vibration amplitude of the Z-axis and achieved the surface roughness standard.

[0119] In summary, steps 301 to 302 precisely locate the spectral bandwidth and center frequency of the resonant frequency and perform phase correction based on propagation delay characteristics. This accurately obtains the original phase angle and generates an efficient anti-phase vibration suppression waveform. This method significantly improves the accuracy and efficiency of vibration control, effectively reduces vibration interference during machining, improves workpiece surface quality, and extends equipment life.

[0120] In order to solve the complexity problem of vibration transmission path in the multi-axis machining process, the solution determines the vibration transmission direction through the propagation time series of the vibration stress wave signal, quantifies the amplitude attenuation of the mechanical vibration signal as a connection strength parameter, and combines it with the spatial mapping relationship of the pre-stored modal rule library to construct a complete multi-axis vibration transmission path topology diagram. This method integrates dynamic propagation characteristics with static structural parameters to form a topological model with both directionality and intensity characteristics to support subsequent energy transfer analysis. In some embodiments, the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool described in step 102 are combined with the pre-stored multi-axis modal rule library to generate a multi-axis vibration transmission path topology diagram, including:

[0121] 401. Calculate vibration transmission direction indication parameters between adjacent physical nodes in the programmable tool multi-axis motion chain based on a propagation time sequence of the vibration stress wave signal in the programmable tool multi-axis motion chain;

[0122] In step 401, the vibration transmission direction indicator parameter is used to describe the propagation direction characteristics of the vibration stress wave between adjacent physical nodes. It includes phase difference information and delay characteristics in the time series data. Physical nodes refer to components with independent motion functions in a multi-axis machining center. The propagation time series refers to an ordered data sequence that describes the temporal changes of a physical quantity, signal, or phenomenon during the propagation process.

[0123] In the embodiments of the present application, the vibration stress wave signals of each physical node in the multi-axis motion chain of a programmable tool are first collected and aligned to the same time base using timestamp alignment technology. Subsequently, a cross-correlation analysis algorithm is used to calculate the time delay between adjacent physical nodes corresponding to the timestamped vibration stress wave signals. Fourier transform is then used to extract the phase difference characteristics of the timestamped vibration stress wave signals. A weighted fusion model based on time delay and phase difference is then used to generate a vibration transmission direction indicator parameter.

[0124] 402. Determine an energy attenuation ratio value based on a variation range of the peak amplitude of the mechanical vibration signal between the physical nodes, and quantify the energy attenuation ratio value into a connection strength parameter between the physical nodes.

[0125] In step 402, the peak amplitude variation range refers to the fluctuation range of the vibration signal's peak value within a specific time period, specifically the difference between the maximum and minimum peak values ​​within that time period. The energy attenuation ratio reflects the amplitude loss characteristics of the vibration signal during transmission between physical nodes and is calculated as the ratio of the peak amplitude values. The connection strength parameter quantifies the tightness of the structural connection between physical nodes.

[0126] In this embodiment, the peak amplitude variation range of the mechanical vibration signal between adjacent physical nodes is first extracted, and the ratio of the peak amplitude of the maximum node to the peak amplitude of the minimum node is calculated as the energy attenuation ratio. Subsequently, a linear mapping algorithm is used to normalize the energy attenuation ratio to a connection strength parameter within the interval range. A larger value of the connection strength parameter indicates a tighter connection.

[0127] 403. Calling a pre-stored structural connection relationship in a multi-axis modal rule library to establish a spatial mapping relationship between the structural connection relationship and the physical node;

[0128] In step 403, the structural connection relationship refers to the fixed or dynamic connection between physical nodes in the five-axis machining center, which is defined by a pre-existing multi-axis modal rule library. The spatial mapping relationship is used to associate the structural connection relationship with the three-dimensional coordinate positions of the physical nodes.

[0129] In this embodiment, a pre-existing multi-axis modal rule library is first called to extract the structural connection relationships between physical nodes, such as rigid connections and flexible couplings. Subsequently, a spatial coordinate conversion algorithm is used to match the structural connection relationships with the installation position data of the physical nodes to generate a spatial mapping relationship.

[0130] 404. Combine the vibration transmission direction indication parameter, the connection strength parameter, and the spatial mapping relationship to generate a multi-axis vibration transmission path topology diagram.

[0131] In step 404 , the multi-axis vibration transmission path topology graph is a three-dimensional network model that integrates vibration transmission direction, connection strength, and spatial position, and includes nodes, edges, and attribute labels.

[0132] In this embodiment, the vibration transmission direction indicator parameter is first used as the direction attribute of the edge, the connection strength parameter is used as the weight attribute of the edge, and the spatial mapping relationship is used as the coordinate attribute of the node. Subsequently, a graph modeling algorithm is used to integrate the vibration transmission direction indicator parameter, connection strength parameter, and spatial mapping relationship into a graph structure with direction, weight, and coordinates, ultimately generating a multi-axis vibration transmission path topology map.

[0133] Here's a specific example:

[0134] To address abnormal vibration issues on the X and Z axes in a five-axis machining center, the vibration stress wave signals of the servo motor, ball screw, guide rail, and drive module were first collected. Cross-correlation analysis revealed that the vibration transmission direction indicator parameters from the servo motor to the drive module indicated the dominant direction was the X-axis, ball screw, and Z-axis guide rail. Subsequently, the peak amplitude variation range and energy attenuation ratio between the X and Z axes were calculated to quantify the connection strength parameters. After invoking the multi-axis modal rule library, it was confirmed that the X and Z axes were rigidly connected via the ball screw, with the spatial mapping relationship being the X axis at the front and the Z axis at the back. Finally, the direction parameters, strength parameters, and spatial position were integrated into a topological map, demonstrating that vibration energy is strongly transmitted to the guide rail via the ball screw, and located as the primary path of the vibration anomaly.

[0135] In summary, steps 401 to 404 accurately locate the energy propagation path through the vibration transmission direction indication parameter, quantify the coupling degree between nodes by combining the energy attenuation ratio and the connection strength parameter, and realize three-dimensional visualization using the spatial mapping relationship. The resulting multi-axis vibration transmission path topology map provides data support for the vibration suppression strategy of the multi-axis machining center, effectively reducing machining errors and improving surface quality.

[0136] In order to solve the problem of quantitative analysis of multi-axis vibration energy transfer paths during multi-axis machining, the solution generates a basic transfer rate parameter by fusing the propagation delay and energy attenuation characteristics of the vibration feature data set, and adjusts the transfer rate in combination with the correction factor of the path connection strength to form an inter-axis vibration energy transfer rate that reflects the vibration energy transfer characteristics. Through a dynamic correction mechanism, the impact of changes in the path connection state on energy transfer is compensated, thereby improving the accuracy and adaptability of the transfer rate calculation. In some embodiments, the step 103 described in which the propagation delay characteristics and energy attenuation characteristics of the vibration feature data set in the multi-axis vibration transfer path topology diagram are fused to generate the inter-axis vibration energy transfer rate includes:

[0137] 501. Extracting propagation delay features of the vibration feature data set in the multi-axis vibration transmission path topology diagram, and calculating a path vibration transmission efficiency index based on the numerical distribution of the propagation delay features between the transmission path nodes in the multi-axis vibration transmission path topology diagram;

[0138] In step 501, the propagation delay characteristic refers to the difference in propagation time between adjacent nodes in the multi-axis vibration transmission path topology. This data is derived from the timestamp alignment information in the vibration feature dataset. The path vibration transfer efficiency index characterizes the efficiency of vibration energy transfer between path nodes. Its value is calculated as the ratio of the propagation delay characteristic to the path geometric length, reflecting the real-time response capability of the vibration signal within the path.

[0139] In an embodiment of the present application, first, the original time series signals between the nodes of each transmission path are extracted from the vibration feature data set, and the deviation of the acquisition time of different sensors is eliminated by the timestamp alignment algorithm to ensure data synchronization. Subsequently, the propagation delay characteristics between adjacent nodes are calculated using the cross-correlation analysis algorithm, and the signal similarity is compared by sliding windows to determine the time difference of the vibration energy from the source to the target node. Then, according to the physical distance between adjacent nodes in the path multi-axis vibration transmission path topology diagram, the propagation delay characteristics and the distance value are normalized to generate the propagation delay density per unit length. Finally, combined with the vibration frequency characteristics, the propagation delay density is associated with the frequency response function to calculate the path vibration transmission efficiency index.

[0140] 502. Extracting energy attenuation characteristics of the vibration feature data set in the multi-axis vibration transmission path topology diagram, and determining a vibration energy loss coefficient based on a change gradient of the energy attenuation characteristics between nodes of the transmission path;

[0141] In step 502, the energy attenuation characteristic refers to the attenuation pattern of the peak amplitude of the vibration signal between path nodes. Its data is derived from the peak amplitude variation range of the vibration characteristic dataset. The vibration energy loss coefficient is used to quantify the degree of vibration energy loss between path nodes. Its value is calculated from the gradient change of the energy attenuation characteristic and reflects the energy dissipation characteristics of the vibration signal along the path. The gradient of change describes the rate of change of a physical quantity or data in space or time. It is essentially a mathematical representation of the gradient vector.

[0142] In the embodiments of the present application, the amplitude peak sequence between each transmission path node is first extracted from the vibration characteristic data set. The energy attenuation ratio between adjacent nodes is calculated using a sliding window statistical method. The energy attenuation characteristics are quantified by the ratio of the maximum to minimum values ​​within the sliding window. The energy attenuation characteristics are then subjected to a gradient analysis, and the rate of change along the path direction is calculated using the finite difference method to identify the sudden change points or trend characteristics of energy attenuation. The gradient change rate is then correlated with the material dissipation coefficient in combination with the material damping characteristic model to generate the vibration energy loss coefficient.

[0143] 503. Proportionally integrate the path vibration transmission efficiency index and the vibration energy loss coefficient to generate a basic transmission rate parameter;

[0144] In step 503, proportional integration refers to the process of integrating or coordinating multiple parameters, variables, or elements according to specific proportional relationships to achieve overall optimization or balance. The basic transmissibility parameter is the weighted fusion result of the path vibration transmission efficiency index and the vibration energy loss coefficient. Its value is generated by the proportional integration algorithm and is used to represent the comprehensive transmission capability of vibration energy in the path.

[0145] In the embodiments of the present application, the path vibration transmission efficiency index and the vibration energy loss coefficient are first normalized to be within a uniform dimension range. Subsequently, based on the physical characteristics of each node in the multi-axis vibration transmission path topology, a weight distribution rule for the efficiency index and the loss coefficient is set. For example, the rigid connection path emphasizes the efficiency weight, while the flexible coupling path emphasizes the loss weight. Finally, a linear weighted algorithm is used to fuse the normalized efficiency index and the loss coefficient according to the weight ratio to generate the basic transmission rate parameter.

[0146] 504. Calculate a transfer path correction factor based on the connection strength between the transfer path nodes, and use the transfer path correction factor to adjust the basic transmissibility parameter to generate an inter-axis vibration energy transmissibility.

[0147] In step 504, connection strength refers to the ability of two or more objects, components, materials, or systems to resist external forces after being physically, chemically, or mechanically connected. The transfer path correction factor is a dynamic adjustment coefficient generated based on the connection strength parameters between path nodes. Its value is calculated through a nonlinear mapping relationship between connection strength and base transmissibility parameters and is used to modify the base transmissibility to adapt to the actual structural coupling characteristics.

[0148] In this embodiment, the connection strength parameters in the multi-axis modal rule library are first used, combined with the spatial mapping relationships between nodes in the multi-axis vibration transfer path topology diagram, to generate a correlation matrix between the connection strength and the basic transmissibility parameters. Subsequently, a nonlinear regression algorithm is used to establish a mapping model between the connection strength and the transfer path correction factor. The model parameters are then iteratively optimized using actual vibration test data. Finally, the correction factor is applied to the basic transmissibility parameters to generate the inter-axis vibration energy transfer ratio.

[0149] Here's a specific example:

[0150] In a five-axis machining center, to address abnormal vibration issues on the X and Z axes, the vibration stress wave signals of the X-axis servo motor, ball screw, guide rail, and Z-axis drive module are first collected. The propagation delay characteristics of the axis guide rail path are then calculated to determine the path vibration transmission efficiency index. The amplitude peak variation range is analyzed to generate a vibration energy loss coefficient. The efficiency index and loss coefficient are weighted and integrated to generate a basic transmission rate parameter. The rigid connection strength parameters of the ball screw are used, combined with a nonlinear regression model to generate a correction factor, and the inter-axis vibration energy transmission rate is finally calculated. This transmission rate indicates that vibration energy is efficiently transferred from the ball screw to the guide rail, identifying it as the critical path for vibration anomalies.

[0151] In summary, steps 501 to 504 extract propagation delay and energy attenuation characteristics, quantify path vibration transmission efficiency and energy loss, and combine them with the connection strength correction model to generate the inter-axis vibration energy transfer rate. This solution accurately identifies the main transmission paths of vibration energy, optimizes vibration suppression strategies, reduces machining errors, and improves equipment stability.

[0152] To address the issue of insufficient vibration energy transfer path stability during multi-axis machining, this solution analyzes the distribution dispersion of path connection strength to classify stability levels, matches correction coefficients from a predefined correction rule library, and combines these with baseline correction factors to generate a transfer path correction factor to compensate for the impact of path connection characteristics on energy transfer. This method quantifies connection uniformity and stability and dynamically adjusts correction parameters to achieve adaptive compensation for complex path characteristics. In some embodiments, calculating the transfer path correction factor based on the connection strength between transfer path nodes in step 504 includes:

[0153] 601. Integrate the connection strengths between the nodes of each transmission path to obtain a path connection strength parameter set, and calculate the intensity distribution dispersion of the connection strengths in the path connection strength parameter set;

[0154] In step 601, the path connection strength parameter set is a collection of connection strength data between nodes on each transmission path, including the quantified values ​​of the connection strength between each node. Strength distribution dispersion is a statistical indicator that reflects the degree of dispersion of connection strength values ​​in the set.

[0155] In the embodiment of the present application, first, the connection strength data between each transmission path node, including physical quantities such as bolt tightening force and weld cross-sectional area, are collected to form an original data set. Subsequently, these data are standardized according to the path order, and after eliminating unit differences, they are integrated into a path connection strength parameter set. On this basis, a statistical method is used to calculate the strength distribution dispersion of the connection strength in the path connection strength parameter set. For example, if the connection strength of a certain path node is, the dispersion value is calculated by the standard deviation formula to reflect the concentration or divergence of its numerical distribution.

[0156] 602. Compare the intensity distribution dispersion with a preset stability level classification rule to determine a transfer path stability level identifier, and match a correction coefficient from a predefined correction rule library based on the transfer path stability level identifier;

[0157] In step 602, the stability level identifier is a path stability evaluation result determined by comparing the intensity distribution dispersion with a preset grading rule. The correction coefficient is a quantitative factor used to adjust the path parameters after matching the level identifier.

[0158] In this embodiment, the intensity distribution dispersion is first compared with a pre-defined stability classification rule using a threshold or decision tree model to determine the transfer path stability level. For example, if the dispersion value falls within the medium stability range, a "medium stability level" is output. Subsequently, a pre-defined correction rule library is invoked, using a keyword query or association rule algorithm to match the transfer path stability level with a corresponding correction factor. The correction rule library stores a mapping between different level identifiers and correction factors, such as the correction factor corresponding to "medium stability level." Finally, the matching correction factor in the correction rule library is output.

[0159] 603. Associate the correction coefficient with a pre-stored reference correction factor to generate a transfer path correction factor.

[0160] In step 603, the reference correction factor, a set of pre-stored standardized correction coefficients, is used to correlate the correction coefficients to generate a transfer path correction factor applicable to the current path. The transfer path correction factor compensates for systematic errors in the transfer path of programmable tool vibration. By correlating the correction coefficients obtained during measurement with the pre-stored reference correction factors, correction parameters are generated for correcting a specific transfer path.

[0161] In this embodiment, a baseline correction factor, comprising standardized adjustment values ​​for different operating conditions, is first created. This correction factor is then combined with a pre-stored baseline correction factor through linear interpolation or a weighted average algorithm to generate a transfer path correction factor specific to the current path. For example, a weighted average of the correction factor and the high-temperature adjustment value in the baseline factor is calculated as the final correction factor. This correction factor is then used to adjust the connection parameters of the path nodes, achieving dynamic optimization of path stability.

[0162] Here's a specific example:

[0163] In the connection path between the X-axis and Y-axis of a five-axis machining center, the connection strength data for each node, including bolt tightening force and weld cross-sectional area, is first collected and integrated into a path connection strength parameter set. The dispersion of the strength distribution of this parameter set is calculated, and its standard deviation is found, corresponding to a "medium stability level." A correction factor is then matched to this level based on a predefined rule base. Subsequently, a transfer path correction factor is generated, combining the high-temperature environment adjustment value in the baseline correction factor. Finally, the transfer path correction factor is applied to the bolt preload adjustment at each axis connection, increasing the connection strength, thereby reducing the volatility of vibration energy transmission and improving machining accuracy.

[0164] In summary, steps 601 to 603, by quantitatively analyzing the distribution characteristics of path connection strength, dynamically matching correction coefficients, and generating targeted correction factors, effectively balance the differences in connection strength between path nodes and improve the stability of vibration energy transfer. This method combines statistical analysis with rule matching to achieve intelligent optimization of transfer path parameters in multi-axis machining centers, thereby enhancing equipment reliability and machining quality.

[0165] In order to solve the problem of reduced accuracy caused by vibration during multi-axis machining, the solution converts the frequency and phase parameters of the anti-phase vibration suppression waveform into drive control instructions respectively, and combines them in time sequence to generate inter-axis vibration anti-phase cancellation signals, ensuring that the servo drive output is precisely anti-phase to the original vibration signal to achieve vibration cancellation. Through the timing synchronization strategy, the dynamic matching of frequency and phase is coordinated to ensure the accurate superposition of the cancellation signal in the time domain and enhance the suppression effect. In some embodiments, the encoding of the anti-phase vibration suppression waveform described in step 105 to obtain the inter-axis vibration anti-phase cancellation signal includes:

[0166] 701. Extracting waveform frequency parameters based on the periodic oscillation characteristics of the anti-phase vibration suppression waveform, and converting the waveform frequency parameters into drive frequency control instructions;

[0167] In step 701, the waveform frequency parameter refers to the core frequency value extracted from the periodic oscillation characteristics, which is used to characterize the dominant frequency of the vibration. The drive frequency control instruction converts the waveform frequency parameter into a frequency control signal that can be recognized by the motor or actuator, and is used to adjust the output frequency of the drive system to match the vibration frequency.

[0168] In this embodiment, the periodic oscillation characteristics of the anti-phase vibration suppression waveform are first collected. Its spectral characteristics are extracted using a fast Fourier transform algorithm, and the dominant frequency with the largest amplitude is identified as the waveform frequency parameter. Subsequently, a frequency mapping algorithm is used to convert the waveform frequency parameter into a drive frequency control instruction recognizable by the drive system. For example, the detected vibration frequency is mapped to the reverse output frequency of a servo motor.

[0169] 702. Acquire waveform phase parameters according to the phase offset characteristics of the anti-phase vibration suppression waveform, and convert the waveform phase parameters into a driving phase control instruction containing a phase offset code;

[0170] In step 702, the phase offset characteristic refers to the change in the phase position of the signal waveform relative to a reference point or another signal on the time axis. The waveform phase parameter refers to the phase difference between the anti-phase vibration suppression waveform and the original vibration signal, and is used to characterize the time offset of the cancellation signal. The drive phase control instruction containing the phase offset encoding converts the phase parameter into a phase adjustment instruction executable by the drive system, such as by generating a delayed or advanced trigger signal through a phase encoder or digital signal processor.

[0171] In the embodiment of the present application, first, the phase offset characteristics of the anti-phase vibration suppression waveform are used to calculate the phase difference between it and the original vibration signal through a cross-correlation analysis algorithm to obtain the waveform phase parameters. Subsequently, the waveform phase parameter difference is converted into a drive phase control instruction using phase encoding technology, for example, the phase difference is encoded as a phase offset signal for the drive motor. This process requires the combination of key phase sensor synchronous sampling technology, and the accuracy of the phase difference calculation is ensured by timestamp alignment. The drive phase control instruction works in conjunction with the drive frequency control instruction.

[0172] 703. Combine the driving frequency control instruction and the driving phase control instruction in time sequence to generate an inter-axis vibration anti-phase cancellation signal.

[0173] In step 703, chronological order refers to a logical organization method for describing, explaining, or analyzing events in the order in which they develop. The inter-axis vibration anti-phase cancellation signal is a complete control signal generated by combining the aforementioned instructions in chronological order. It is used to drive the actuator to output vibration energy that is anti-phase with the original vibration signal to achieve cancellation.

[0174] In an embodiment of the present application, the drive frequency control instruction and the drive phase control instruction are first synchronized using a time series alignment algorithm. Subsequently, a sinusoidal signal superposition method is used to combine the two into an inter-axis vibration anti-phase cancellation signal. For example, the signal synthesis algorithm converts the frequency and phase parameters into a time domain signal and injects it into the servo system driver. The anti-phase cancellation signal acts directly on the axis system of the multi-axis machining center, achieving vibration cancellation by outputting energy that is anti-phase to the original vibration signal, thereby improving machining accuracy.

[0175] Here's a specific example:

[0176] When finishing thin-walled titanium alloy parts on a five-axis machining center, the system extracts waveform frequency parameters from the anti-phase vibration suppression waveform and converts them into frequency commands recognized by the driver. The waveform phase parameters are simultaneously detected and encoded into a phase control code. These two commands are time-stamped and aligned to create a combined anti-phase cancellation signal for inter-axis vibration. This signal is then output in real time to the linear motors of the rotating axes, reducing vibration amplitude in the thin-walled areas.

[0177] In summary, steps 701 to 703 extract the frequency and phase characteristics of the vibration signal to generate precise anti-phase cancellation signals, achieving dynamic vibration suppression for a multi-axis machining center. This reduces surface roughness errors caused by vibration during machining, improving machining accuracy and minimizing vibration-induced wear on machine tool components, thereby extending equipment life.

[0178] Figure 2 The present invention provides a schematic structural diagram of a vibration suppression system for a multi-axis collaborative machining path of a programmable tool, as shown in FIG. Figure 2 As shown, the system includes:

[0179] An acquisition module 21 acquires a multi-source vibration signal at a multi-axis joint of a programmable knife, wherein the multi-source vibration signal includes a vibration stress wave signal and a mechanical vibration signal;

[0180] A generating module 22 generates a multi-axis vibration transmission path topology diagram based on the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool and in combination with a pre-stored multi-axis modal rule library;

[0181] a fusion module 23 that performs spatiotemporal alignment of the multi-source vibration signals with the multi-axis vibration transmission path topology to obtain a vibration feature dataset, and fuses the propagation delay characteristics and energy attenuation characteristics of the vibration feature dataset in the multi-axis vibration transmission path topology to generate an inter-axis vibration energy transfer rate;

[0182] a flip module 24 for extracting the resonant frequency of the dominant vibration transfer path in the multi-axis vibration transfer path topology diagram based on the inter-axis vibration energy transfer rate, and performing a phase flip on the resonant frequency to generate an anti-phase vibration suppression waveform;

[0183] The encoding module 25 encodes the anti-phase vibration suppression waveform to obtain an inter-axis vibration anti-phase cancellation signal, and associates the inter-axis vibration anti-phase cancellation signal with the target transfer path corresponding to the processing path in the multi-axis vibration transfer path topology diagram, dynamically suppressing the resonance energy of the target transfer path.

[0184] Figure 2 The vibration suppression system of a multi-axis collaborative machining path of a programmable tool can be executed Figure 1 The implementation principles and technical effects of the vibration suppression method for a multi-axis collaborative machining path using a programmable tool are not described in detail here. The specific manner in which each module and unit performs operations in the vibration suppression system for a multi-axis collaborative machining path using a programmable tool in the above embodiment has been described in detail in the relevant embodiments of the method and will not be elaborated on here.

[0185] In one possible design, Figure 2 The vibration suppression system for a multi-axis collaborative machining path of a programmable tool in the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0186] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0187] The processing component 32 is used for the above Figure 1 The embodiment provides a method for suppressing vibration of a multi-axis collaborative machining path of a programmable tool.

[0188] The processing component 32 may include one or more processors to execute computer instructions to perform all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0189] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0190] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0191] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0192] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0193] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0194] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The embodiment shown is a method for suppressing vibration of a multi-axis collaborative machining path using a programmable tool.

[0195] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0196] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0197] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0198] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for suppressing vibration of a multi-axis collaborative machining path of a programmable tool, characterized in that: include: Acquire multi-source vibration signals at the multi-axis joint of the programmable knife, wherein the multi-source vibration signals include vibration stress wave signals and mechanical vibration signals; Based on the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool, combined with a pre-stored multi-axis modal rule library, a multi-axis vibration transmission path topology diagram is generated; performing spatiotemporal alignment of the multi-source vibration signals with the multi-axis vibration transmission path topology to obtain a vibration feature dataset, and fusing the propagation delay characteristics and energy attenuation characteristics of the vibration feature dataset in the multi-axis vibration transmission path topology to generate an inter-axis vibration energy transfer rate; extracting the resonant frequency of the dominant vibration transfer path in the multi-axis vibration transfer path topology diagram based on the inter-axis vibration energy transfer rate, and performing phase flipping on the resonant frequency to generate an anti-phase vibration suppression waveform; The anti-phase vibration suppression waveform is encoded to obtain an inter-axis vibration anti-phase cancellation signal, and the inter-axis vibration anti-phase cancellation signal is associated with the target transfer path corresponding to the processing path in the multi-axis vibration transfer path topology diagram to dynamically suppress the resonance energy of the target transfer path.

2. The method according to claim 1, characterized in that The extracting the resonant frequency of the dominant vibration transfer path in the multi-axis vibration transfer path topology diagram based on the inter-axis vibration energy transfer rate, and performing phase reversal on the resonant frequency to generate an anti-phase vibration suppression waveform includes: Calculating a path weight coefficient set for each machining path based on the multi-axis vibration transmission path topology map, screening weight coefficients exceeding a preset value from the path weight coefficient set, and defining the machining path corresponding to the screened weight coefficient as a dominant vibration transmission path; extracting a vibration energy spectrum of the dominant vibration transfer path from the inter-axis vibration energy transfer rate, and identifying a vibration energy peak region in the vibration energy spectrum as a resonant frequency of the dominant vibration transfer path; Based on the phase spectrum data of the inter-axis vibration energy transfer rate, the original phase angle corresponding to the resonant frequency is calculated, and the original phase angle is subjected to an anti-phase shift to generate an anti-phase vibration suppression waveform.

3. The method according to claim 2, characterized in that The calculating the original phase angle corresponding to the resonant frequency based on the phase spectrum data of the inter-axis vibration energy transfer rate includes: Locating the spectrum bandwidth range of the resonant frequency in the phase spectrum data based on the phase spectrum data of the inter-axial vibration energy transfer rate, and extracting the center frequency point position in the spectrum bandwidth range; The phase value record corresponding to the center frequency point position in the phase spectrum data is extracted, and the phase value record is phase corrected in combination with the propagation delay characteristics in the multi-axis vibration transmission path topology diagram. The corrected phase value record is converted into an angle dimension representation to obtain the original phase angle.

4. The method according to claim 1, wherein The method generates a multi-axis vibration transmission path topology diagram based on the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool, in combination with a pre-stored multi-axis modal rule library, including: Calculating vibration transmission direction indication parameters between adjacent physical nodes in the programmable knife multi-axis motion chain based on the propagation time sequence of the vibration stress wave signal in the programmable knife multi-axis motion chain; Determining an energy attenuation ratio value based on a variation range of peak amplitudes of the mechanical vibration signal between the physical nodes, and quantifying the energy attenuation ratio value as a connection strength parameter between the physical nodes; Calling a structural connection relationship in a pre-stored multi-axis modal rule library to establish a spatial mapping relationship between the structural connection relationship and the physical node; The vibration transmission direction indication parameter, the connection strength parameter and the spatial mapping relationship are combined to generate a multi-axis vibration transmission path topology diagram.

5. The method according to claim 1, characterized in that The step of fusing the propagation delay feature and the energy attenuation feature of the vibration feature data set in the multi-axis vibration transmission path topology diagram to generate the inter-axis vibration energy transfer rate includes: Extracting propagation delay features of the vibration feature data set in the multi-axis vibration transmission path topology diagram, and calculating a path vibration transmission efficiency index based on the numerical distribution of the propagation delay features between the transmission path nodes in the multi-axis vibration transmission path topology diagram; Extracting energy attenuation characteristics of the vibration feature data set in the multi-axis vibration transmission path topology diagram, and determining a vibration energy loss coefficient based on a change gradient of the energy attenuation characteristics between nodes of the transmission path; Proportionally integrating the path vibration transmission efficiency index and the vibration energy loss coefficient to generate a basic transmission rate parameter; Based on the connection strength between the transmission path nodes, a transmission path correction factor is calculated, and the basic transmissibility parameter is adjusted using the transmission path correction factor to generate the inter-axis vibration energy transmissibility.

6. The method according to claim 5, characterized in that The calculating of the transfer path correction factor based on the connection strength between the transfer path nodes includes: Integrating the connection strengths between the nodes of each transmission path to obtain a path connection strength parameter set, and calculating the intensity distribution dispersion of the connection strengths in the path connection strength parameter set; Comparing the intensity distribution dispersion with a preset stability grade classification rule to determine a transfer path stability grade identifier, and matching a correction coefficient from a predefined correction rule library based on the transfer path stability grade identifier; The correction coefficient is associated with a pre-stored reference correction factor to generate a transfer path correction factor.

7. The method according to claim 1, characterized in that The step of encoding the anti-phase vibration suppression waveform to obtain an inter-axis vibration anti-phase cancellation signal includes: extracting waveform frequency parameters based on the periodic oscillation characteristics of the anti-phase vibration suppression waveform, and converting the waveform frequency parameters into drive frequency control instructions; Acquiring waveform phase parameters according to the phase offset characteristics of the anti-phase vibration suppression waveform, and converting the waveform phase parameters into a driving phase control instruction containing a phase offset code; The driving frequency control instruction and the driving phase control instruction are combined in time sequence to generate an inter-axis vibration anti-phase cancellation signal.

8. A vibration suppression system for multi-axis collaborative machining paths using a programmable tool, characterized in that: include: An acquisition module is used to acquire multi-source vibration signals at the multi-axis joint of the programmable knife, wherein the multi-source vibration signals include vibration stress wave signals and mechanical vibration signals; A generation module generates a multi-axis vibration transmission path topology diagram based on the propagation characteristics of the vibration stress wave signal and the mechanical vibration signal in the multi-axis motion chain of the programmable tool and in combination with a pre-stored multi-axis modal rule library; a fusion module that performs spatiotemporal alignment of the multi-source vibration signals with the multi-axis vibration transmission path topology map to obtain a vibration feature dataset, and fuses the propagation delay characteristics and energy attenuation characteristics of the vibration feature dataset in the multi-axis vibration transmission path topology map to generate an inter-axis vibration energy transfer rate; a flip module, which extracts the resonant frequency of the dominant vibration transfer path in the multi-axis vibration transfer path topology diagram based on the inter-axis vibration energy transfer rate, and performs a phase flip on the resonant frequency to generate an anti-phase vibration suppression waveform; The encoding module encodes the anti-phase vibration suppression waveform to obtain an inter-axis vibration anti-phase cancellation signal, and associates the inter-axis vibration anti-phase cancellation signal with the target transfer path corresponding to the processing path in the multi-axis vibration transfer path topology diagram, thereby dynamically suppressing the resonance energy of the target transfer path.

9. A computing device, characterized in that It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a vibration suppression method for a multi-axis collaborative machining path of a programmable tool as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the vibration suppression method of a programmable tool multi-axis collaborative machining path according to any one of claims 1 to 7 is implemented.

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