Main shaft dynamic balance detection method and system

Abstract

The invention relates to the technical field of precise spindle detection, in particular to a spindle dynamic balance detection method and system, and the method comprises the steps: configuring a vibration information collection point location, and obtaining a vibration component signal related to a balance state in the operation process of a spindle, the vibration component signal comprising a multi-dimensional vibration component and a spindle dynamic parameter; performing feature extraction and parameterization analysis on the vibration component signal, analyzing the motion state of the main shaft, and generating an unbalance feature set describing the unbalance state of the main shaft if the unbalance state occurs; dynamic balance mapping is established according to the imbalance characteristic set, and a parameterized balance analysis model is generated based on dynamic balance mapping integration analysis; and constructing closed-loop dynamic feedback, monitoring the running state of the main shaft, iteratively parameterizing the balance analysis model according to a monitoring result, and correcting the movement of the main shaft until the balance of the main shaft meets a preset target. According to the invention, the problems of poor adaptability, feedback lagging and low data utilization rate of the existing spindle dynamic balance detection method are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of precision spindle detection, and in particular to a spindle dynamic balance detection method and system. Background Art

[0002] In mechanical rotating equipment, the spindle is a key component, and its dynamic balance state is crucial to the stability of equipment operation, processing accuracy and service life. However, due to factors such as manufacturing errors, assembly errors and material unevenness, the spindle often becomes unbalanced during operation, resulting in increased vibration, reduced processing quality, and even equipment failure. Existing spindle dynamic balancing detection methods are mainly based on single static correction, lack of real-time dynamic feedback mechanism to adapt to complex working conditions, and low data utilization, which makes it difficult to meet the needs of modern industry for high-precision, high-efficiency and intelligent dynamic balancing detection.

[0003] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present disclosure, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art known to those skilled in the art. Summary of the invention

[0004] The present invention provides a spindle dynamic balance detection method and system, which can effectively solve the problems in the background technology.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is: A spindle dynamic balance detection method, the method comprising: Configure vibration information collection points to obtain vibration component signals related to the balance state during the operation of the spindle, wherein the vibration component signals include multi-dimensional vibration components and spindle dynamic parameters; Performing feature extraction and parameter analysis on the vibration component signal to analyze the motion state of the spindle, and if an imbalance state occurs, generating an imbalance feature set describing the imbalance state of the spindle; Establishing a dynamic balance map according to the imbalance feature set, and generating a parameterized balance analysis model based on the integrated analysis of the dynamic balance map; A closed-loop dynamic feedback is constructed to monitor the spindle operation status, and the parameterized balance analysis model is iterated according to the monitoring results and the spindle motion is corrected until the spindle balance meets the preset target.

[0006] Further, generating a parameterized equilibrium analysis model based on the dynamic equilibrium mapping integrated analysis includes: Performing vibration mode analysis on the imbalance feature set, associating the spindle dynamic parameters with corresponding vibration modes, and forming a dynamic balance map; Based on the dynamic balance mapping, the vibration characteristics of the multi-dimensional vibration components are analyzed, the spatial distribution and intensity of the imbalance sources are identified, and the imbalance source spatial matrix is ​​generated; Based on the imbalance source space matrix, a multi-dimensional imbalance mapping algorithm is used to construct a parameterized balance analysis model, to perform spatial analysis on the influence of different imbalance sources and quantify their contribution to the spindle vibration, and to predict the dynamic balance state of the spindle under specific working conditions; By comparing with the vibration component signal, the parameters of the parameterized balance analysis model are calibrated.

[0007] Furthermore, the impact of different imbalance sources is spatially analyzed, including: Performing frequency-time feature analysis on the imbalance feature set, combining the dynamic balance mapping, identifying the spatial distribution position and position vibration parameters of the spindle imbalance source, and determining the specific contribution of each imbalance source to the dynamic behavior of the spindle; Based on the spatial distribution position and the position vibration parameters, the unbalance torque generated by the different unbalance sources is calculated to quantify the influence of the unbalance source on the spindle motion; Based on the unbalanced torque, analyzing the dynamic response characteristics of the unbalanced source during the spindle movement process, and generating an unbalanced source analysis result; According to the imbalance source analysis result, a balance compensation scheme is established in combination with the position vibration parameters and the imbalance torque.

[0008] Furthermore, a balanced compensation plan is established, including: Based on the imbalance source analysis result and in combination with the dynamic response characteristics, a preliminary balance compensation parameter is calculated and generated; Simulating the dynamic balance state of the spindle under different operating conditions by means of the parameterized balance analysis model, analyzing the adaptability of the preliminary balance compensation parameters under various operating conditions, and generating optimized balance compensation parameters; Generate a primary balance compensation scheme according to the optimized balance compensation parameters, and verify the balance compensation scheme through the parameterized balance analysis model to evaluate the suppression effect on the spindle vibration amplitude; If the suppression effect does not reach the preset balance target, the optimized balance compensation parameters are corrected according to data feedback until a balance compensation scheme that meets the preset target is generated.

[0009] Furthermore, feature extraction and parameter analysis are performed on the vibration component signal, including: Performing transform envelope analysis on the vibration component signal to extract the spindle dynamic parameters, wherein the spindle dynamic parameters include energy distribution, frequency band characteristics and vibration mode index; In combination with the multi-dimensional vibration components, the dynamic response of the main shaft under different operating conditions is analyzed, abnormal vibration modes are identified, and a dynamic response data set is generated; Analyzing the correlation between the parameters of the dynamic response data set, establishing coupling links between the parameters, and establishing a primary dynamic balance mapping of the multi-dimensional vibration components and the main shaft dynamic parameters based on the coupling links; Based on the primary dynamic balance map, the vibration component signal is parameterized and reorganized, and a correlation analysis is performed with the spindle motion state to generate a vibration correlation result.

[0010] Furthermore, coupling links between parameters are established, including: Selecting the multi-dimensional vibration components and the main shaft dynamic parameters under the abnormal vibration mode from the dynamic response data set; Based on the abnormal vibration mode, a correlation calculation is performed between the multidimensional vibration components in each of the vibration component signals and the main shaft dynamic parameters, wherein the correlation calculation uses a time-delay cross-correlation analysis to determine the correlation strength between the parameters; According to the calculation result of the correlation calculation, the vibration component signals are sorted according to the correlation strength, and the core parameter pairs with the highest correlation are screened out; The interactive relationship between the core parameter pairs is analyzed, the coupling link between the multi-dimensional vibration components and the main axis dynamic parameters is established, and the coupling relationship is characterized for constructing a primary dynamic balance map.

[0011] Further, iterating the parameterized balance analysis model according to the monitoring result and correcting the spindle motion includes: The vibration component signals under the operation state of the spindle are collected through the vibration information collection points, and are integrated with the operation timestamp to generate regular monitoring data; Comparing the timed monitoring data with the balance prediction result of the parameterized balance analysis model, and calculating the error between the current spindle vibration characteristic and the balance prediction result of the parameterized balance analysis model; A balance satisfaction target is preset, and based on the error analysis result, characteristic prediction parameters in the parameterized balance analysis model are adjusted and the parameterized balance analysis model is updated; Generate a spindle balance correction scheme according to the parameterized balance analysis model, the balance correction scheme includes instructions for adjusting the mass and position of the balance block and the spindle motion path optimization, and establish a balance correction database according to the balance correction scheme; According to the balance correction scheme, the spindle motion adjustment operation is performed, and the balance meets the target through the timed monitoring data of the running spindle.

[0012] Furthermore, a balance correction database is established according to the balance correction scheme, including: Collecting balance correction information included in the balance correction scheme, wherein the balance correction information includes an effective correction scheme in the spindle motion and the spindle vibration characteristics; Associating the balance correction information with the operating conditions to generate a correction scheme experience record; Based on the empirical records of the correction scheme, the characteristic performance of the spindle imbalance under different operating conditions and the effective correction scheme are summarized, and the empirical rules of balance correction are extracted; The balance correction empirical rules and the balance correction schemes are classified and stored in the balance correction empirical library according to the operating status, and a unique correction scheme is matched for each operating condition; After the correction scheme is executed, new data is dynamically added to the balance correction experience library, and the matching of the correction scheme and the operating conditions is further optimized by updating the experience rules.

[0013] A spindle dynamic balance detection system, the system comprising: An information acquisition module is configured with vibration information acquisition points to obtain vibration component signals related to the balance state during the operation of the spindle. The vibration component signals include multi-dimensional vibration components and spindle dynamic parameters. The parameter analysis module performs feature extraction and parameter analysis on the vibration component signal, analyzes the spindle motion state, and generates an imbalance feature set describing the spindle imbalance state if an imbalance state occurs; The model generation module establishes a dynamic balance map according to the imbalance feature set, and generates a parameterized balance analysis model based on the dynamic balance map integration analysis; The monitoring and correction module builds a closed-loop dynamic feedback to monitor the spindle operation status. It iterates the parameterized balance analysis model based on the monitoring results and corrects the spindle motion until the spindle balance meets the preset target.

[0014] Furthermore, the model generation module includes: A balance mapping unit performs vibration mode analysis on the unbalanced feature set, associates the spindle dynamic parameters with the corresponding vibration modes, and forms a dynamic balance map; The matrix building unit analyzes the vibration characteristics of multi-dimensional vibration components based on dynamic balance mapping, identifies the spatial distribution and intensity of the imbalance source, and generates the imbalance source space matrix; The spatial analysis unit, based on the imbalance source spatial matrix, adopts a multi-dimensional imbalance mapping algorithm to construct a parametric balance analysis model, spatially analyzes the impact of different imbalance sources and quantifies their contribution to the spindle vibration, and predicts the dynamic balance state of the spindle under specific working conditions; Compare the calibration unit with the vibration component signals and calibrate the parameters of the parameterized balance analysis model.

[0015] The technical solution of the present invention can achieve the following technical effects: It solves the problems of poor adaptability, feedback lag and low data utilization of existing spindle dynamic balancing detection methods, realizes the adaptation to dynamic balancing requirements of different speeds and load conditions, and improves the efficiency, accuracy and intelligence level of detection and correction.

[0016] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flow chart of a spindle dynamic balancing detection method; Figure 2 It is a structural diagram of the parametric equilibrium analysis model; Figure 3 A schematic diagram of the process for generating vibration correlation results; Figure 4 This is a schematic diagram of the process of spindle motion correction. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0021] Embodiment 1 like Figure 1As shown, the present application provides a spindle dynamic balance detection method, the method comprising: S10: configuring vibration information collection points to obtain vibration component signals related to the balance state during the operation of the spindle, where the vibration component signals include multi-dimensional vibration components and spindle dynamic parameters; S20: extracting features and performing parameter analysis on the vibration component signal, analyzing the motion state of the spindle, and if an imbalance state occurs, generating an imbalance feature set describing the imbalance state of the spindle; S30: establishing a dynamic balance map according to the imbalance feature set, and generating a parameterized balance analysis model based on the dynamic balance map integration analysis; S40: Build a closed-loop dynamic feedback loop to monitor the spindle operation status, iterate the parameterized balance analysis model based on the monitoring results, and correct the spindle motion until the spindle balance meets the preset target.

[0022] Specifically, vibration sensors are installed at key positions of the spindle movement (such as the bearing seat, shaft end and shaft body) to collect vibration component signals related to the balance state during the operation of the spindle in real time. The vibration sensors can be three-axis accelerometers and angular velocity sensors, etc., to capture multi-dimensional vibration components. According to the structural characteristics and operating environment of the spindle, the collection points are reasonably arranged to ensure that the collected data fully covers the dynamic behavior of the spindle; the vibration component signals during the operation of the spindle are collected by the vibration sensor. The vibration component signals include the vibration amplitude, frequency, phase difference and acceleration of the spindle, etc. The dynamic parameters of the spindle, such as speed, load and axis trajectory, are collected synchronously to ensure the correspondence between the signal and the operating state; the collected vibration component signals are preprocessed, including denoising, filtering and normalization operations, and the time domain and frequency domain characteristic parameters of the signal are extracted using time-frequency analysis methods (such as short-time Fourier transform or wavelet transform), the vibration mode of the spindle under different operating conditions is analyzed, the imbalance state is identified, and a signal is generated. A set of imbalance features is used to describe the imbalance state of the spindle, and the imbalance feature set includes parameters such as imbalance amplitude, phase and imbalance source position; based on the imbalance feature set, a dynamic balance mapping is established to describe the distribution of spindle imbalance sources and their impact on the overall vibration, and a parameterized balance analysis model is generated to quantify the contribution of different imbalance sources to the dynamic behavior of the spindle and predict the dynamic balance state of the spindle under different operating conditions; during the operation of the spindle, the vibration component signal is monitored in real time, and the actual monitoring results are compared with the predicted results of the parameterized balance analysis model. If there is an error, a spindle balance correction plan is generated, and the spindle balance correction plan includes operations such as adjusting the mass and position of the balance block and optimizing the spindle motion path; the spindle balance correction operation is performed according to the correction plan, and the correction effect is verified during the operation process. By monitoring the spindle vibration signal in real time, it is determined whether the balance state meets the preset target. If the balance is insufficient, the model adjustment step is returned and the correction is repeated until the spindle reaches the ideal balance state.

[0023] The technical solution of the present invention solves the problems of poor adaptability, feedback lag and low data utilization rate of existing spindle dynamic balancing detection methods, realizes the adaptation of dynamic balancing requirements for different speeds and load conditions, and improves the efficiency, accuracy and intelligence level of detection and correction.

[0024] Further, if Figure 2 As shown, a parameterized equilibrium analysis model is generated based on dynamic equilibrium mapping integrated analysis, including: Perform vibration mode analysis on the unbalanced feature set, associate the spindle dynamic parameters with the corresponding vibration modes, and form a dynamic balance map; Based on dynamic balance mapping, the vibration characteristics of multi-dimensional vibration components are analyzed, the spatial distribution and intensity of the imbalance source are identified, and the imbalance source space matrix is ​​generated; Based on the imbalance source space matrix, a multi-dimensional imbalance mapping algorithm is used to construct a parametric balance analysis model, which spatially analyzes the impact of different imbalance sources and quantifies their contribution to the spindle vibration, and predicts the dynamic balance state of the spindle under specific working conditions; By comparing with the vibration component signals, the parameters of the parameterized balance analysis model are calibrated.

[0025] As a preferred embodiment of the above embodiment, an imbalance feature set is extracted from the vibration component signal collected during the operation of the spindle, the set including the imbalance amplitude, frequency, phase and vibration energy distribution, etc., and a vibration mode analysis is performed on the imbalance feature set using modal analysis (such as modal superposition method or empirical mode decomposition method) to identify the main vibration modes in the operation of the spindle, including first-order, second-order and high-order modal vibration shapes, and the dynamic parameters of the spindle (such as speed, load and axis trajectory) are correlated with the vibration mode results to form a dynamic balance map describing the imbalance state, which is used to show the relationship between the imbalance source and the vibration mode; based on the dynamic balance map, the spatial characteristics of the spindle vibration signal are analyzed to identify the position distribution and intensity of the main imbalance source, and a spatial distribution modeling method (such as finite element modeling or distributed imbalance modeling) is used to generate an imbalance source space matrix, the rows of which represent different imbalance source positions, and the columns represent the amplitude, phase and contribution intensity of the imbalance source to the overall vibration; Based on the imbalance source space matrix, a multi-dimensional imbalance mapping algorithm (such as an orthogonal decomposition algorithm or a multi-objective optimization algorithm) is used to construct a parameterized balance analysis model. The input of the parameterized balance analysis model is the imbalance source position, vibration amplitude and spindle dynamic parameters, and the output is the predicted value of the spindle vibration response, which is used to quantify the contribution of different imbalance sources to the overall vibration behavior of the spindle. In the process of establishing the model, the accuracy of the parameterized balance analysis model is optimized by piecewise linear fitting or nonlinear regression method to ensure that it can reflect the dynamic balance state of the spindle under various operating conditions; the predicted result of the parameterized balance analysis model is compared with the actual collected vibration component signal, and the error between the output of the parameterized balance analysis model and the measured data is calculated. The error feedback mechanism is used to dynamically calibrate the parameterized balance analysis model by adjusting the key parameters in the model (such as the imbalance source intensity coefficient and the spatial distribution weight) to ensure that the model can accurately describe the current dynamic balance state of the spindle.

[0026] Furthermore, a spatial analysis of the impact of different imbalance sources is performed, including: Perform frequency-time feature analysis on the imbalance feature set, combine it with dynamic balance mapping, identify the spatial distribution position and position vibration parameters of the spindle imbalance source, and determine the specific contribution of each imbalance source to the dynamic behavior of the spindle; Based on the spatial distribution position and position vibration parameters, the unbalance torque generated by different unbalance sources is calculated to quantify the impact of the unbalance source on the spindle motion; Based on the unbalanced torque, the dynamic response characteristics of the unbalanced source during the spindle movement are analyzed to generate the unbalanced source analysis results; According to the analysis results of the imbalance source, a balance compensation scheme is established in combination with the position vibration parameters and imbalance torque.

[0027] As a preferred embodiment of the above embodiment, by performing frequency-time feature analysis on the collected imbalance feature set, using short-time Fourier transform (STFT) or continuous wavelet transform (CWT) to decompose the vibration signal, extracting key parameters in the imbalance feature set, including vibration amplitude, frequency, phase and vibration energy distribution, etc., combining with dynamic balance mapping, determine the spatial distribution position of different imbalance sources and position-related vibration parameters (such as amplitude and phase), and mark the main imbalance source area in the spindle system; for each imbalance source, according to its spatial distribution position and position vibration parameters, establish a geometric relationship model, calculate the imbalance torque generated by the imbalance source on the spindle, and use the following formula to calculate the imbalance torque: M=r×F in, M is the unbalanced torque, r is the position vector of the imbalance source, FThe product of the vibration amplitude and the unbalanced mass (i.e., the force caused by vibration) is obtained by summarizing all unbalanced moments and generating the unbalanced moment distribution of the entire spindle. Based on the calculated unbalanced moment, the dynamic response characteristics of each unbalanced source during the spindle movement are analyzed. The modal response analysis method is used to quantify the specific impact of each unbalanced source on the vibration behavior of the spindle under different speeds and load conditions in combination with the structural characteristics and speed parameters of the spindle. The results of the frequency-time characteristics, spatial distribution, and dynamic response analysis are summarized to form an unbalanced source analysis report, which includes the position distribution of each unbalanced source, the vibration parameters (amplitude, frequency, phase) of each unbalanced source, and the quantitative results of the impact of each unbalanced source on the dynamic behavior of the spindle (such as unbalanced moment, vibration energy contribution rate). According to the unbalanced source analysis results, combined with the position vibration parameters and unbalanced moment information, a balance compensation scheme is designed. The compensation scheme includes adjusting the mass and position of the balancing block so that the overall vibration of the spindle reaches the preset target, and optimizing the spindle running path and speed for specific unbalanced sources to reduce high-frequency vibration in the dynamic response.

[0028] Further, establish a balanced compensation plan, including: Based on the analysis results of the imbalance source and combined with the dynamic response characteristics, the preliminary balance compensation parameters are calculated and generated; The dynamic balance state of the spindle under different operating conditions is simulated through the parametric balance analysis model, the adaptability of the preliminary balance compensation parameters under various operating conditions is analyzed, and the optimized balance compensation parameters are generated; Generate a primary balance compensation scheme based on the optimized balance compensation parameters, and verify the balance compensation scheme through a parameterized balance analysis model to evaluate the suppression effect on the spindle vibration amplitude; If the suppression effect does not reach the preset balance target, the balance compensation parameters are corrected and optimized according to the data feedback until a balance compensation scheme that meets the preset target is generated.

[0029] As a preferred embodiment of the above, based on the analysis result of the imbalance source and in combination with the dynamic response characteristics of the spindle, the preliminary balance compensation parameters are calculated, wherein the parameters include the mass and installation position of the balance block and the recommended values ​​for adjusting the spindle rotation path or dynamic parameters (such as rotation speed and angular acceleration). The mass and position of the balance block are calculated using the following formula: ; Among them, m 补偿 is the mass of the balance block, M 失衡 is the unbalanced moment, r 补偿 is the radius from the compensation block to the spindle center, ω is the angular velocity of the spindle; Use a parametric balance analysis model to simulate the dynamic balance state of the spindle under different operating conditions (such as high load, low speed, variable speed operation, etc.). Under each operating condition, analyze the adaptability of the preliminary balance compensation parameters, including the impact on the vibration amplitude, frequency and dynamic response stability, record the balancing effect and adaptability evaluation index of the preliminary balance compensation parameters under each operating condition, and screen out the preliminary balance compensation parameters that have a greater impact on the dynamic balance of the spindle; based on the operating condition analysis results, adjust the preliminary balance compensation parameters through an optimization algorithm (such as a genetic algorithm or a particle swarm optimization algorithm) to generate optimized balance compensation parameters. The optimization objectives include global minimization of the vibration amplitude, minimization of the compensation block mass, and maximization of the multi-condition adaptability of the compensation parameters. ; Based on the optimized balance compensation parameters, generate a primary balance compensation scheme, including the installation position, mass configuration and operation adjustment scheme of the compensation block; use a parametric balance analysis model to simulate the implementation effect of the primary balance compensation scheme, and evaluate the suppression effect on the spindle vibration amplitude and frequency response. If the vibration suppression effect does not reach the preset balance target, record the deficiencies of the compensation scheme to provide feedback basis for the next parameter correction; based on the feedback results of the balance verification, correct and optimize the balance compensation parameters, including adjusting the compensation block position, mass or dynamic parameters, and repeat the simulation and verification process until the final balance compensation scheme that meets the preset balance target is generated, which can significantly reduce the spindle vibration amplitude and improve the dynamic balance performance under all operating conditions.

[0030] Further, if Figure 3 As shown, feature extraction and parameter analysis of vibration component signals are performed, including: Perform transform envelope analysis on the vibration component signal to extract the spindle dynamic parameters, which include energy distribution, frequency band characteristics and vibration mode indicators; Combine multi-dimensional vibration components to analyze the dynamic response of the spindle under different operating conditions, identify abnormal vibration modes, and generate dynamic response data sets; Analyze the correlation between the parameters of the dynamic response data set, establish coupling links between the parameters, and establish the primary dynamic balance mapping of multi-dimensional vibration components and spindle dynamic parameters based on the coupling links; Based on the primary dynamic balance mapping, the vibration component signals are parameterized and reorganized, and the vibration correlation results are generated by correlation analysis with the spindle motion state.

[0031] As a preferred embodiment of the above embodiment, the collected vibration component signal is subjected to transform envelope analysis. First, a bandpass filter is used to preprocess the signal to filter out noise and irrelevant frequency band signals. The Hilbert transform is used to generate an envelope signal for the vibration signal, and the dynamic parameters of the spindle are extracted, including analyzing the energy change of the signal in the time domain, identifying the energy distribution in the high vibration area of ​​the spindle, analyzing the spectrum distribution of the signal by fast Fourier transform (FFT), extracting the main frequency band characteristics, analyzing the harmonic components of the envelope signal, and extracting the modal eigenvalues ​​representing the imbalance state; combining multi-dimensional vibration components (such as X, Y, and Z axis components of the acceleration signal), analyzing the dynamic response of the spindle under different operating conditions (such as speed, load changes, etc.), using the frequency domain feature analysis method to identify abnormal vibration modes, including high-frequency harmonics, low-frequency oscillations, etc., and generating a dynamic response data set, which includes key parameters such as the vibration frequency, amplitude, and phase of the spindle under different conditions; performing correlation analysis on the parameters of the dynamic response data set (such as frequency, amplitude, phase, and energy), and using the Pearson correlation coefficient or cross-correlation coefficient to calculate the correlation coefficient of the dynamic response data set. The information volume is used to calculate the correlation between parameters, screen out high-correlation parameter pairs, and establish a coupling link between multidimensional vibration components and spindle dynamic parameters in combination with the spindle motion characteristics (such as the correlation between speed fluctuation and vibration amplitude); based on the high-correlation parameter pairs, the vibration components are mapped to the spindle dynamic parameters to form a primary dynamic balance map, which is used to describe the initial impact of the spindle imbalance source on the overall vibration state, including the correlation between the amplitude change of the vibration component and the dynamic parameters; on the basis of the primary dynamic balance map, the vibration component signals are parametrically decomposed and reorganized, and the principal component analysis (PCA) is used to reduce the dimension of the vibration data, extract the main vibration features, and group the high-frequency vibration and low-frequency vibration components separately for subsequent analysis. Combined with the spindle motion state, the decomposed signal is correlated with the spindle operation state to generate vibration correlation results; the vibration correlation results include: the relationship between the vibration mode and the spindle speed, load, and the main dynamic characteristics of the imbalance source. The vibration correlation results provide data support for the subsequent dynamic balance mapping optimization and correction plan formulation.

[0032] Furthermore, coupling links between parameters are established, including: Selecting multi-dimensional vibration components and main shaft dynamic parameters in abnormal vibration modes from the dynamic response data set; Based on the abnormal vibration mode, the correlation between the multi-dimensional vibration components in each vibration component signal and the dynamic parameters of the main shaft is calculated. The correlation calculation uses time-delay cross-correlation analysis to determine the correlation strength between the parameters. According to the calculation results of the correlation calculation, the vibration component signals are sorted according to the correlation strength, and the core parameter pairs with the highest correlation are screened out; The interactive relationships between the core parameter pairs are analyzed, the coupling links between the multidimensional vibration components and the main axis dynamic parameters are established, and the coupling relationships are characterized for constructing the primary dynamic balance map.

[0033] As a preferred embodiment of the above, data related to abnormal vibration modes are screened from the dynamic response data set, including multidimensional vibration components such as abnormal vibration amplitude, frequency, phase, and spindle dynamic parameters (such as speed, load, temperature, etc.). The abnormal vibration mode is extracted by a time-frequency analysis method (such as short-time Fourier transform or wavelet transform), and its corresponding characteristic data range is marked to ensure that the selected data can fully reflect the characteristics of the abnormal vibration mode; the selected multidimensional vibration components and spindle dynamic parameters are correlated, and the time-delay cross-correlation analysis method is used to evaluate the correlation strength between different parameters, specifically, the change of the correlation between two groups of time series with time lag is calculated, and the lag effect of the spindle dynamic parameters on the vibration components is identified. By constructing a time-delay correlation function, the maximum correlation value and the corresponding lag time at different lag times are determined. The correlation calculation results include the correlation strength, time lag and directional characteristics between the parameters; according to the correlation calculation results, all parameter pairs are arranged in descending order of correlation strength, and the core parameter pairs with the highest correlation are screened out. The core parameter pairs reflect the key coupling relationship between spindle vibration and dynamic behavior, such as the strong correlation between vibration amplitude and speed fluctuation, and vibration frequency and spindle load. , set the threshold of correlation strength, eliminate parameter pairs with low or insignificant correlation, and optimize the screening results; perform interactive relationship analysis on the screened core parameter pairs, use partial correlation analysis or multivariate regression analysis methods to quantify the direct and indirect effects between parameter pairs, and identify the main interactive modes between parameter pairs (such as synchronous change relationship or lag drive relationship). The analysis results show that there may be complex multidimensional interactive characteristics between different core parameter pairs; based on the core parameter pairs and their interactive relationships, construct coupling links between multidimensional vibration components and spindle dynamic parameters, characterize the coupling strength, interaction direction and time lag relationship between parameters, use directed weighted networks to represent coupling links, in which nodes represent parameters, edge weights represent correlation strength, and directions represent lag relationships, visualize coupling links, and form interactive network diagrams between parameters. The coupling links describe the intrinsic coupling relationship between multidimensional vibration components and spindle dynamic parameters, providing data support for constructing primary dynamic balance mapping; input the established coupling links into the primary dynamic balance mapping construction module to describe the influence of spindle imbalance sources on the overall dynamic behavior. The primary dynamic balance mapping can be further used for imbalance source positioning, dynamic behavior prediction and balance compensation scheme optimization.

[0034] Further, if Figure 4 As shown, the parameterized balance analysis model is iterated based on the monitoring results and the spindle motion is corrected, including: Through the vibration information collection points, the vibration component signals of the spindle under running state are collected, and the timed monitoring data is generated by integrating the running timestamp; Compare the regular monitoring data with the balance prediction results of the parameterized balance analysis model, and calculate the error between the current spindle vibration characteristics and the balance prediction results of the parameterized balance analysis model; The preset balance satisfies the target, and based on the error analysis results, the characteristic prediction parameters in the parameterized balance analysis model are adjusted and the parameterized balance analysis model is updated; Generate a spindle balance correction plan based on the parameterized balance analysis model. The balance correction plan includes instructions for adjusting the mass and position of the balance block and the spindle motion path optimization. Establish a balance correction database based on the balance correction plan. According to the balance correction plan, the spindle motion adjustment operation is performed, and the balance meets the target through the regular monitoring data of the running spindle.

[0035] As a preferred embodiment of the above-mentioned embodiment, during the operation of the spindle, multi-dimensional vibration component signals are collected in real time by configuring vibration sensors at the bearing seat, the spindle end or the key support points, etc., and the collected vibration signals are time-stamped synchronously, and combined with the spindle operation status parameters (such as speed, load, temperature, etc.), the timing monitoring data are integrated to generate the timing monitoring data, and the timing monitoring data is recorded in a time series format to provide data support for the subsequent update and correction of the parametric balance analysis model; the collected timing monitoring data is input into the parametric balance analysis model, and compared with the spindle balance state predicted by the parametric balance analysis model, and the deviation between the actual vibration characteristics and the prediction result of the parametric balance analysis model is calculated by the error analysis method, including the vibration amplitude deviation, frequency deviation and phase deviation, and based on the error calculation result, the characteristic prediction parameters in the parametric balance analysis model (such as the imbalance source strength, position and dynamic behavior) are adjusted, and the parametric balance analysis model is dynamically updated to improve the prediction accuracy, and the updated The parametric balance analysis model generates a spindle balance correction plan, including balance block adjustment parameters, spindle motion path optimization instructions, and establishes a balance correction database based on the correction plan to record the correction plan and corresponding vibration characteristics under the current operating state for reference in subsequent correction and optimization; according to the generated balance correction plan, the spindle balance correction operation is performed, including adjusting the installation position and mass of the balance block and optimizing the dynamic operating parameters of the spindle; during the correction process, the real-time collection of vibration signals is used to monitor the immediate effect of the correction operation to ensure that the correction steps are performed according to the preset plan; after completing the correction operation, the vibration component signals of the spindle in operation continue to be collected, and compared with the predicted results of the parametric balance analysis model to verify whether the corrected spindle vibration amplitude reaches the preset balance target; if the correction effect does not meet the target, the parametric balance analysis model is further adjusted based on the historical records of the correction plan and the current error data, and a new balance correction plan is iteratively generated, and the correction and verification process is repeated until the balance requirements are met.

[0036] Further, a balance correction database is established according to the balance correction scheme, including: Collecting the balance correction information contained in the balance correction scheme, the balance correction information includes the effective correction scheme in the spindle motion and the spindle vibration characteristics; Associate the balance correction information with the operating conditions to generate correction scheme experience records; Based on the empirical records of correction schemes, the characteristics of spindle imbalance under different operating conditions and effective correction schemes are summarized, and the empirical rules for balance correction are extracted; The balance correction experience rules and balance correction schemes are classified and stored in the balance correction experience library according to the operating status, and a unique correction scheme is matched for each operating condition; After the correction scheme is executed, the new data is dynamically added to the balance correction experience library, and the matching between the correction scheme and the operating conditions is further optimized by updating the experience rules.

[0037] As a preferred embodiment of the above, during the spindle correction process, key information of the balance correction scheme is collected, including an effective correction scheme, that is, parameters adjusted during the correction process, such as the mass, position, installation angle of the balancing block and the spindle motion path optimization instructions, the spindle vibration characteristics before and after correction, including the spindle vibration amplitude, frequency and phase change data, and the correction effect is recorded. The collected information is recorded in the form of structured data to ensure the integrity and traceability of the data; the balance correction information is associated with the operating conditions of the spindle (including dynamic parameters such as speed, load, temperature, etc.) to generate a correction scheme experience record; based on the correction scheme experience record, the characteristic performance of the spindle imbalance under different operating conditions and the corresponding effective correction schemes are summarized, and the balance correction experience rules are extracted. The rule content includes the correlation between the imbalance characteristics and the operating conditions, and the optimal correction parameter configuration recommended for different imbalance characteristics. , prediction of correction effect under specific working conditions; based on the extracted experience rules and correction schemes, the data are classified according to the operating conditions and stored in the balance correction experience library; the balance correction experience library supports fast retrieval of the best correction scheme according to the working conditions, such as matching the unique correction parameter configuration according to the speed range or load conditions. In the balance correction experience library, efficient correction schemes and optimization suggestions are marked to quickly guide subsequent correction operations. After the new correction scheme is executed, the correction information is dynamically collected and updated to the balance correction experience library, the new data is classified and the rules are optimized, the experience rules are updated, and the matching accuracy and adaptability of the experience library are further improved; each correction scheme record stored in the experience library verifies its applicability and correction effect under similar working conditions. For schemes that do not meet the standards, the correction parameters under the corresponding operating conditions are further optimized by analyzing the trends and deviations of the new data to improve the accuracy of the experience library.

[0038] Embodiment 2 Based on the same inventive concept as the spindle dynamic balancing detection method in the aforementioned embodiment, the present invention further provides a spindle dynamic balancing detection system, the system comprising: An information acquisition module is configured with vibration information acquisition points to obtain vibration component signals related to the balance state during the operation of the spindle. The vibration component signals include multi-dimensional vibration components and spindle dynamic parameters. The parameter analysis module performs feature extraction and parameter analysis on the vibration component signal, analyzes the spindle motion state, and generates an imbalance feature set describing the spindle imbalance state if an imbalance state occurs; The model generation module establishes a dynamic balance map according to the imbalance feature set, and generates a parameterized balance analysis model based on the dynamic balance map integration analysis; The monitoring and correction module builds a closed-loop dynamic feedback to monitor the spindle operation status. It iterates the parameterized balance analysis model based on the monitoring results and corrects the spindle motion until the spindle balance meets the preset target.

[0039] The above-mentioned adjustment system in the present invention can effectively implement a spindle dynamic balance detection method, and the technical effects that can be achieved are as described in the above-mentioned embodiments, which will not be repeated here.

[0040] Specifically, the model generation module includes: A balance mapping unit performs vibration mode analysis on the unbalanced feature set, associates the spindle dynamic parameters with the corresponding vibration modes, and forms a dynamic balance map; The matrix building unit analyzes the vibration characteristics of multi-dimensional vibration components based on dynamic balance mapping, identifies the spatial distribution and intensity of the imbalance source, and generates the imbalance source space matrix; The spatial analysis unit, based on the imbalance source spatial matrix, adopts a multi-dimensional imbalance mapping algorithm to construct a parametric balance analysis model, spatially analyzes the impact of different imbalance sources and quantifies their contribution to the spindle vibration, and predicts the dynamic balance state of the spindle under specific working conditions; Compare the calibration unit with the vibration component signals and calibrate the parameters of the parameterized balance analysis model.

[0041] Similarly, the above-mentioned optimization schemes for the system can also respectively achieve the optimization effects corresponding to the method in Example 1, which will not be repeated here.

[0042] Although the present application has been described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the accompanying drawings are merely exemplary illustrations of the present application as defined therein, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A spindle dynamic balance detection method, characterized in that: The method comprises: Configure vibration information collection points to obtain vibration component signals related to the balance state during the operation of the spindle, wherein the vibration component signals include multi-dimensional vibration components and spindle dynamic parameters; Performing feature extraction and parameter analysis on the vibration component signal to analyze the motion state of the spindle, and if an imbalance state occurs, generating an imbalance feature set describing the imbalance state of the spindle; Establishing a dynamic balance map according to the imbalance feature set, and generating a parameterized balance analysis model based on the integrated analysis of the dynamic balance map; A closed-loop dynamic feedback is constructed to monitor the spindle operation status, and the parameterized balance analysis model is iterated according to the monitoring results and the spindle motion is corrected until the spindle balance meets the preset target.

2. A spindle dynamic balance detection method according to claim 1, characterized in that: Based on the dynamic balance mapping integrated analysis, a parameterized balance analysis model is generated, including: Performing vibration mode analysis on the imbalance feature set, associating the main shaft dynamic parameters with corresponding vibration modes, and forming a dynamic balance map; Based on the dynamic balance mapping, the vibration characteristics of the multi-dimensional vibration components are analyzed, the spatial distribution and intensity of the imbalance sources are identified, and the imbalance source spatial matrix is ​​generated; Based on the imbalance source space matrix, a multi-dimensional imbalance mapping algorithm is used to construct a parameterized balance analysis model, to perform spatial analysis on the influence of different imbalance sources and quantify their contribution to the spindle vibration, and to predict the dynamic balance state of the spindle under specific working conditions; By comparing with the vibration component signal, the parameters of the parameterized balance analysis model are calibrated.

3. A spindle dynamic balance detection method according to claim 2, characterized in that: Spatial analysis of the impact of the different imbalance sources described, including: Performing frequency-time feature analysis on the imbalance feature set, combining the dynamic balance mapping, identifying the spatial distribution position and position vibration parameters of the spindle imbalance source, and determining the specific contribution of each imbalance source to the dynamic behavior of the spindle; Based on the spatial distribution position and the position vibration parameters, the unbalance torque generated by the different unbalance sources is calculated to quantify the influence of the unbalance source on the spindle motion; Based on the unbalanced torque, analyzing the dynamic response characteristics of the unbalanced source during the spindle movement process, and generating an unbalanced source analysis result; According to the imbalance source analysis result, a balance compensation scheme is established in combination with the position vibration parameters and the imbalance torque.

4. A spindle dynamic balance detection method according to claim 3, characterized in that: Establish a balanced compensation plan that includes: Based on the imbalance source analysis result and in combination with the dynamic response characteristics, a preliminary balance compensation parameter is calculated and generated; Simulating the dynamic balance state of the spindle under different operating conditions by means of the parameterized balance analysis model, analyzing the adaptability of the preliminary balance compensation parameters under various operating conditions, and generating optimized balance compensation parameters; Generate a primary balance compensation scheme according to the optimized balance compensation parameters, and verify the balance compensation scheme through the parameterized balance analysis model to evaluate the suppression effect on the spindle vibration amplitude; If the suppression effect does not reach the preset balance target, the optimized balance compensation parameters are corrected according to data feedback until a balance compensation scheme that meets the preset target is generated.

5. A spindle dynamic balance detection method according to claim 1, characterized in that: Performing feature extraction and parameter analysis on the vibration component signal, including: Performing transform envelope analysis on the vibration component signal to extract the spindle dynamic parameters, wherein the spindle dynamic parameters include energy distribution, frequency band characteristics and vibration mode index; In combination with the multi-dimensional vibration components, the dynamic response of the main shaft under different operating conditions is analyzed, abnormal vibration modes are identified, and a dynamic response data set is generated; Analyzing the correlation between the parameters of the dynamic response data set, establishing coupling links between the parameters, and establishing a primary dynamic balance mapping of the multi-dimensional vibration components and the main shaft dynamic parameters based on the coupling links; Based on the primary dynamic balance map, the vibration component signal is parameterized and reorganized, and a correlation analysis is performed with the spindle motion state to generate a vibration correlation result.

6. A spindle dynamic balance detection method according to claim 5, characterized in that: Establish coupling links between parameters, including: Selecting the multi-dimensional vibration components and the main shaft dynamic parameters under the abnormal vibration mode from the dynamic response data set; Based on the abnormal vibration mode, a correlation calculation is performed between the multidimensional vibration components in each of the vibration component signals and the main shaft dynamic parameters, wherein the correlation calculation uses a time-delay cross-correlation analysis to determine the correlation strength between the parameters; According to the calculation result of the correlation calculation, the vibration component signals are sorted according to the correlation strength, and the core parameter pairs with the highest correlation are screened out; The interactive relationship between the core parameter pairs is analyzed, the coupling link between the multi-dimensional vibration components and the main axis dynamic parameters is established, and the coupling relationship is characterized for constructing a primary dynamic balance map.

7. A spindle dynamic balance detection method according to claim 1, characterized in that: Iterating the parameterized balance analysis model and correcting the spindle motion according to the monitoring results, including: The vibration component signals under the operation state of the spindle are collected through the vibration information collection points, and are integrated with the operation timestamp to generate regular monitoring data; Comparing the timed monitoring data with the balance prediction result of the parameterized balance analysis model, and calculating the error between the current spindle vibration characteristic and the balance prediction result of the parameterized balance analysis model; A balance satisfaction target is preset, and based on the error analysis result, characteristic prediction parameters in the parameterized balance analysis model are adjusted and the parameterized balance analysis model is updated; Generate a balance correction scheme for the spindle according to the parameterized balance analysis model, the balance correction scheme including instructions for adjusting the mass and position of the balance block and the spindle motion path optimization, and establish a balance correction database according to the balance correction scheme; According to the balance correction scheme, the spindle motion adjustment operation is performed, and the balance meets the target through the timed monitoring data of the running spindle.

8. A spindle dynamic balance detection method according to claim 7, characterized in that: Establishing a balance correction database according to the balance correction scheme includes: Collecting balance correction information included in the balance correction scheme, wherein the balance correction information includes an effective correction scheme in the spindle motion and the spindle vibration characteristics; Associating the balance correction information with the operating conditions to generate a correction scheme experience record; Based on the empirical records of the correction scheme, the characteristic performance of the spindle imbalance under different operating conditions and the effective correction scheme are summarized, and the empirical rules of balance correction are extracted; The balance correction empirical rules and the balance correction schemes are classified and stored in the balance correction empirical library according to the operating status, and a unique correction scheme is matched for each operating condition; After the correction scheme is executed, new data is dynamically added to the balance correction experience library, and the matching of the correction scheme and the operating conditions is further optimized by updating the experience rules.

9. A spindle dynamic balance detection system, characterized in that: The system comprises: An information acquisition module is configured with vibration information acquisition points to obtain vibration component signals related to the balance state during the operation of the spindle. The vibration component signals include multi-dimensional vibration components and spindle dynamic parameters. The parameter analysis module performs feature extraction and parameter analysis on the vibration component signal, analyzes the spindle motion state, and generates an imbalance feature set describing the spindle imbalance state if an imbalance state occurs; A model generation module establishes a dynamic balance map according to the imbalance feature set, and generates a parameterized balance analysis model based on the dynamic balance map integration analysis; The monitoring and correction module builds a closed-loop dynamic feedback to monitor the spindle operation status. It iterates the parameterized balance analysis model based on the monitoring results and corrects the spindle motion until the spindle balance meets the preset target.

10. A spindle dynamic balancing detection system according to claim 9, characterized in that: The model generation module includes: A balance mapping unit performs vibration mode analysis on the unbalanced feature set, associates the spindle dynamic parameters with the corresponding vibration modes, and forms a dynamic balance map; The matrix building unit analyzes the vibration characteristics of multi-dimensional vibration components based on dynamic balance mapping, identifies the spatial distribution and intensity of the imbalance source, and generates the imbalance source space matrix; The spatial analysis unit, based on the imbalance source spatial matrix, adopts a multi-dimensional imbalance mapping algorithm to construct a parametric balance analysis model, spatially analyzes the impact of different imbalance sources and quantifies their contribution to the spindle vibration, and predicts the dynamic balance state of the spindle under specific working conditions; Compare the calibration unit with the vibration component signals and calibrate the parameters of the parameterized balance analysis model.

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