Method and device for extracting characteristic quantity of unbalanced vibration signal

Abstract

The present invention provides a method and device for extracting characteristic quantities of unbalanced vibration signals. The method includes: simultaneously collecting unbalanced vibration signals and rotational speed pulse signals of a main shaft; performing modal decomposition on the unbalanced vibration signals, determining the number of modal components according to the energy loss coefficient, and obtaining multiple modal components of the unbalanced vibration signals; determining the rotational frequency according to the rotational speed pulse signals and constructing a reference vibration signal according to the rotational frequency, calculating the correlation coefficients between the multiple modal components and the reference vibration signal, and obtaining the modal component with the largest correlation coefficient; and obtaining the characteristic quantity according to the modal component with the largest correlation coefficient. The method provided by the present invention can accurately extract the amplitude and phase of the rotational frequency signal in the vibration signal under strong background noise, and has high application value in the field of dynamic balance testing of the main shaft.

Description

Technical Field

[0001] The present invention relates to the technical field of spindle dynamic balancing, and particularly to a method and device for extracting characteristic quantities of unbalanced vibration signals. Background Art

[0002] Modern numerically controlled machine tools are basic equipment in the manufacturing industry, and the spindle is its core component. The performance of the spindle will have a greater impact on the machining performance of the machine tool. However, during the operation of the spindle, unbalanced centrifugal forces will be generated due to factors such as manufacturing and assembly errors, causing spindle vibration, thereby greatly reducing the machining accuracy of the machine tool and affecting the machining quality. Therefore, dynamic balancing of the machine tool spindle is required.

[0003] To achieve spindle dynamic balancing, mass compensation for the unbalanced mass is required, and calculating the unbalanced mass of the spindle requires obtaining the rotational frequency vibration signal contained in the spindle vibration signal. Among them, accurate acquisition of the amplitude and phase of the rotational frequency vibration signal is a prerequisite for correctly calculating the unbalanced mass. During the on-site dynamic balancing process of the spindle, strong background noise interference often exists, and it is difficult for traditional methods to accurately extract the characteristic quantities of the spindle rotational frequency signal under strong noise backgrounds. Summary of the Invention

[0004] The present invention provides a method and device for extracting characteristic quantities of unbalanced vibration signals, which are used to solve the defect that it is difficult to extract the characteristic quantities of the spindle rotational frequency signal under strong noise backgrounds in the prior art, so as to accurately extract the characteristic quantities and achieve spindle dynamic balancing.

[0005] The present invention provides a method for extracting characteristic quantities of unbalanced vibration signals, including:

[0006] Simultaneously collecting the unbalanced vibration signal and the rotational speed pulse signal of the spindle;

[0007] Performing modal decomposition on the unbalanced vibration signal, determining the number of modal components according to the energy loss coefficient, and obtaining multiple modal components of the unbalanced vibration signal;

[0008] Determining the rotational frequency according to the rotational speed pulse signal and constructing a reference vibration signal according to the rotational frequency, calculating the correlation coefficients between the multiple modal components and the reference vibration signal, and obtaining the modal component with the largest correlation coefficient

[0009] Obtaining the characteristic quantity according to the modal component with the largest correlation coefficient.

[0010] According to the method for extracting characteristic quantities of unbalanced vibration signals provided by the present invention, the performing modal decomposition on the unbalanced vibration signal and determining the number of modal components according to the energy loss coefficient includes:

[0011] The variational mode decomposition method is used to perform modal decomposition on the unbalanced vibration signal, and the number of modal components increases with the number of iterations.

[0012] An iteration stop condition is set according to the energy loss coefficient, and the number of modal components at the stop of iteration is obtained.

[0013] According to a method for extracting characteristic quantities of an unbalanced vibration signal provided by the present invention, the iteration stop condition is that the energy loss coefficient is less than a threshold value, and the value range of the threshold value is [0.02, 0.06].

[0014] According to a method for extracting characteristic quantities of an unbalanced vibration signal provided by the present invention, the energy loss coefficient is calculated by Equation 1:

[0015]

[0016] where ξ represents the energy loss coefficient, f represents the unbalanced vibration signal, u k represents the k-th modal component, and K represents the total number of modal components.

[0017] According to a method for extracting characteristic quantities of an unbalanced vibration signal provided by the present invention, obtaining the characteristic quantity according to the modal component with the largest correlation coefficient includes:

[0018] Taking the modal component with the largest correlation coefficient as the component containing the rotational frequency vibration signal, obtaining the amplitude and phase of the rotational frequency vibration signal, and obtaining the characteristic quantity.

[0019] According to a method for extracting characteristic quantities of an unbalanced vibration signal provided by the present invention, before performing modal decomposition on the unbalanced vibration signal, it further includes:

[0020] Preprocessing the unbalanced vibration signal, and the preprocessing includes low-pass filtering and downsampling processing.

[0021] The present invention also provides a device for extracting characteristic quantities of an unbalanced vibration signal, including:

[0022] An acquisition module for simultaneously acquiring the unbalanced vibration signal and the rotational speed pulse signal of the main shaft;

[0023] A decomposition module for performing modal decomposition on the unbalanced vibration signal, determining the number of modal components according to the energy loss coefficient, and obtaining multiple modal components of the unbalanced vibration signal;

[0024] A correlation calculation module for determining the rotational frequency according to the rotational speed pulse signal, constructing a reference vibration signal according to the rotational frequency, calculating the correlation coefficients of the multiple modal components and the reference vibration signal, and obtaining the modal component with the largest correlation coefficient;

[0025] A feature extraction module, configured to obtain a feature quantity according to the modal component with the largest correlation coefficient.

[0026] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the method for extracting the feature quantity of the balanced vibration signal as described in any one of the above are implemented.

[0027] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for extracting the feature quantity of the balanced vibration signal as described in any one of the above are implemented.

[0028] The present invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the method for extracting the feature quantity of the balanced vibration signal as described in any one of the above are implemented.

[0029] A method and device for extracting the feature quantity of an unbalanced vibration signal provided by the present invention decompose and denoise the unbalanced vibration signal to obtain a plurality of intrinsic modal components with different center frequencies, then calculate the magnitude of the rotational frequency through a rotational speed pulse signal, construct a reference vibration signal, calculate the correlation coefficient between each component and the reference vibration signal, select the component with the largest correlation coefficient, and accurately extract the amplitude and phase of the signal through correlation analysis. This method can accurately extract the amplitude and phase of the rotational frequency vibration signal in the vibration signal under strong background noise, and has high application value in the field of spindle dynamic balance testing. Description of the Drawings

[0030] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0031] Figure 1 is one of the flow diagrams of the method for extracting the feature quantity of the unbalanced vibration signal provided by the embodiment of the present invention;

[0032] Figure 2 is the second flow diagram of the method for extracting the feature quantity of the unbalanced vibration signal provided by the embodiment of the present invention;

[0033] Figure 3 is the experimental signal waveform diagram in the embodiment of the present invention;

[0034] Figure 4 is the experimental signal frequency spectrum diagram in the embodiment of the present invention;

[0035] Figure 5 Schematic diagrams of several IMF components obtained after the experimental signal is decomposed in the embodiment of the present invention;

[0036] Figure 6 Spectrum diagram of each component obtained by decomposing the experimental signal in the embodiment of the present invention;

[0037] Figure 7 Comparison diagram of the amplitude results of the rotational frequency vibration signals obtained from multiple groups of experimental data at the same rotational speed by the method in the embodiment of the present invention and the processing results of other methods;

[0038] Figure 8 Comparison diagram of the phase results of the rotational frequency vibration signals obtained from multiple groups of experimental data at the same rotational speed by the method in the embodiment of the present invention and the processing results of other methods;

[0039] Figure 9 Comparison diagram of the amplitude results of the rotational frequency vibration signals in the simulation signal obtained by the method in the embodiment of the present invention at different signal-to-noise ratios and the processing results of other methods;

[0040] Figure 10 Comparison diagram of the phase results of the rotational frequency vibration signals in the simulation signal obtained by the method in the embodiment of the present invention at different signal-to-noise ratios and the processing results of other methods;

[0041] Figure 11 Schematic diagram of the structure of the device for extracting the characteristic quantity of the unbalanced vibration signal provided by the embodiment of the present invention;

[0042] Figure 12 Schematic diagram of the structure of the electronic device provided by the embodiment of the present invention. Detailed implementation manners

[0043] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the protection scope of the present invention.

[0044] The spindle dynamic balance mentioned in the embodiment of the present invention refers to a technology that reduces the spindle vibration caused by uneven mass distribution during the operation of the spindle to the range allowed by the technology by changing the mass distribution of the spindle. The specific implementation steps are as follows:

[0045] (1) Start the spindle. After the rotational speed is stable, measure the amplitude and phase of its initial unbalanced vibration:

[0046]

[0047] (2) Stop the machine, add a trial weight at a certain position at the end of the spindle, and record the magnitude and phase of the trial weight:

[0048]

[0049] (3) Repeat step ① to measure the amplitude and phase of the unbalanced vibration signal of the spindle after adding the trial weight:

[0050]

[0051] (4) After obtaining the above parameters, calculate the influence coefficient according to the definition of the influence coefficient:

[0052]

[0053] (5) Finally, calculate the spindle unbalance according to the initial unbalanced vibration and the influence coefficient, and obtain the magnitude and phase of the unbalanced mass:

[0054]

[0055] (6) Add the corresponding mass in the opposite direction at the corresponding position of the spindle to achieve the dynamic balancing process of the spindle.

[0056] As can be seen from the above steps, in the process of spindle dynamic balancing, the key technology is the acquisition of the characteristic quantities of spindle unbalanced vibration. Spindle unbalance is the key factor causing spindle vibration, which is often caused by many factors such as manufacturing, assembly, and workpiece clamping. When rotating at high speed, unbalanced centrifugal force will be generated. As the rotational speed increases, the vibration caused by unbalance will gradually intensify, that is, the unbalanced vibration signal. The following combines Figures 1-10 Describe the method for extracting the characteristic quantities of the unbalanced vibration signal of the embodiments of the present invention. As Figure 1 shown, the method includes:

[0057] Step 101. Simultaneously collect the unbalanced vibration signal and the rotational speed pulse signal of the spindle;

[0058] It should be noted that the unbalanced vibration signal of the spindle is obtained by starting the machine tool and collecting it with an acceleration sensor installed on the bearing seat after the spindle runs stably. The rotational speed pulse signal is synchronously collected with the unbalanced vibration signal by an optical sensor. Synchronously collecting the rotational speed pulse signal and the unbalanced vibration signal can achieve the phase calibration of the spindle vibration signal, and at the same time, the vibration signal can be intercepted based on the rotational speed pulse signal.

[0059] Step 102. Perform modal decomposition on the unbalanced vibration signal, determine the number of modal components according to the energy loss coefficient, and obtain multiple modal components of the unbalanced vibration signal;

[0060] Step 103: Determine the rotational frequency based on the rotational speed pulse signal, construct a reference vibration signal according to the rotational frequency, calculate the correlation coefficients between the multiple modal components and the reference vibration signal, and obtain the modal component with the maximum correlation coefficient.

[0061] Step 104: Obtain the characteristic quantity based on the modal component with the maximum correlation coefficient.

[0062] The method for extracting the characteristic quantity of the unbalance vibration signal in the embodiment of the present invention decomposes and denoises the unbalance vibration signal to obtain multiple intrinsic mode functions (IMFs) with different central frequencies, accurately identifies the components containing the rotational frequency in each component through the correlation coefficient method, effectively eliminates the influence of the remaining interference signals, and realizes the accurate extraction of the amplitude and phase of the rotational frequency signal in the spindle vibration signal under a strong noise background.

[0063] In at least one embodiment of the present invention, the modal decomposition of the unbalance vibration signal and the determination of the number of modal components according to the energy loss coefficient include:

[0064] Perform modal decomposition on the unbalance vibration signal by using the variational mode decomposition method, and the number of modal components increases with the number of iterations;

[0065] Set the iteration stop condition according to the energy loss coefficient, and obtain the number of modal components when the iteration stops.

[0066] The method for extracting the characteristic quantity of the unbalance vibration signal in the embodiment of the present invention applies the variational mode decomposition method to vibration signal processing in order to reduce the noise interference of the vibration signal collected during the on-site dynamic balancing process, and innovatively introduces the energy loss coefficient, solves the problem of difficult determination of the decomposition layer number in practical applications, and effectively improves the signal decomposition effect.

[0067] It should be noted that the variational mode decomposition method includes the following steps:

[0068] Step 201: Construct a variational problem as shown in Equation 2:

[0069]

[0070] where, u k represents the k-th modal component, and ω k is the central frequency corresponding to u k

[0071] Step 202: Introduce the Lagrange operator λ(t) and the quadratic multiplication factor α, and solve the variational problem as shown in Equation 3;

[0072]

[0073] ​Step 203: adaptively determine the number of modal components using the energy loss coefficient.

[0074] In at least one embodiment of the present invention, the iteration stop condition is that the energy loss coefficient is less than a threshold value, and the value range of the threshold is [0.02, 0.06]. Through a large number of simulations and experiments, better decomposition results can be obtained within this range.

[0075] Preferably, the threshold is 0.04, that is, when the energy loss coefficient is less than 0.04, the iteration process is stopped to obtain an adaptive decomposition result.

[0076] In at least one embodiment of the present invention, the energy loss coefficient is calculated using Equation 1:

[0077]

[0078] where ξ represents the energy loss coefficient, f represents the unbalanced vibration signal, and u k represents the k-th modal component, and K represents the total number of modal components.

[0079] It should be noted that the algorithm flow for adaptively determining the number of modal components using the energy loss coefficient is as follows:

[0080] Step 301: Initialize K = 1, where K represents the number of intrinsic modal components u k obtained after decomposition;

[0081] Step 302: Let K = K + 1 and start the outermost loop;

[0082] Step 303: Initialize and n, where is the frequency domain representation of each modal component, and n is the number of loop iterations;

[0083] Step 304: Let n = n + 1 and start the inner loop;

[0084] Step 305: For k = 1:K, update

[0085]

[0086]

[0087]

[0088] where k ∈ {1, K}, τ is the time constant, and usually takes the value of 0.

[0089] Step 306: Repeat the above steps 303 to 305 until the internal loop termination condition is met, and end the inner loop. The internal loop termination condition is shown in Equation 7:

[0090]

[0091] Step 307: Repeat steps 302 to 306 until the energy loss coefficient is less than the set threshold, end the outer loop, and obtain the K modal components at this time.

[0092] In at least one embodiment of the present invention, after the decomposition is completed, to implement the signal denoising process, first remove the interference components, and calculate the correlation coefficient between the multiple modal components and the reference vibration signal using Equation 8:

[0093]

[0094] where r k represents the correlation coefficient of the k-th modal component, N represents the number of points of the unbalanced vibration signal, R IMFk (i) represents the autocorrelation sequence of each component, and R x (i) represents the autocorrelation sequence of the reference vibration signal.

[0095] The larger the correlation coefficient, the greater the degree of association between the component and the rotating frequency vibration signal. Select the component with the largest correlation coefficient, which is the component containing the rotating frequency component, and discard the remaining components to obtain the rotating frequency vibration signal.

[0096] In at least one embodiment of the present invention, obtaining the characteristic quantity according to the modal component with the largest correlation coefficient includes:

[0097] Taking the modal component with the largest correlation coefficient as the component containing the rotating frequency vibration signal, obtaining the amplitude and phase of the rotating frequency vibration signal to obtain the characteristic quantity.

[0098] It should be noted that obtaining the above characteristic quantity includes the following steps:

[0099] Step 401: If the frequency of the fundamental frequency vibration signal obtained from the rotational speed pulse signal is ω, then set the standard sine signal and cosine signal with frequency ω and phase 0 to be g(t) and h(t) respectively, where,

[0100] Step 402: Perform cross-correlation operations on the standard sine and cosine signals g(t) and h(t) and the modal component with the largest correlation coefficient obtained in the above process, as shown in Equations 9 and 10:

[0101]

[0102]

[0103] Step 403: Obtain the amplitude e and phase φ of the vibration rotating frequency signal, as shown in Equation 11 and Equation 12:

[0104]

[0105]

[0106] The method of the embodiment of the present invention can accurately extract the amplitude and phase of the rotating frequency signal under a strong noise background and has strong stability. Obtaining stable amplitude and phase can improve the accuracy of the finally calculated unbalance mass and phase, thereby effectively improving the subsequent dynamic balancing effect.

[0107] In at least one embodiment of the present invention, before performing modal decomposition on the unbalance vibration signal, it further includes:

[0108] Preprocess the unbalance vibration signal, and the preprocessing includes low-pass filtering and downsampling processing.

[0109] It should be noted that since the spindle rotating frequency is generally small, low-pass filtering can effectively avoid high-frequency interference in the vibration signal and avoid aliasing during the downsampling process. The downsampling process can reduce the calculation amount and improve the vibration signal decomposition efficiency.

[0110] The embodiment of the present invention also extracts the characteristic quantities of the unbalance vibration signal under specific working conditions. The experimental operations include:

[0111] Start the spindle of the machine tool, set the experimental speed to 1000 r / min. After the speed is stable, synchronously collect the spindle vibration signal and speed signal by using the acceleration sensor installed on the spindle bearing block and the photoelectric sensor on the spindle. Convert the electrical signal into a digital signal through the data acquisition system. When conducting the experiment, use JM5936L to synchronously collect the rotational speed pulse signal and acceleration signal. Specifically, during sampling, the sampling frequency (f s ) should satisfy f s > 2f h (the highest signal frequency). Under the condition of meeting the hardware limitations, it should be as large as possible, which can ensure that the reference signal is more accurate, and the sampling time should be greater than the signal period. To ensure the integrity of the reference signal, intercept the reference signal with the rising edge of the reference signal as a mark. Set the sampling frequency to 4000 Hz and the sampling frequency to 8000.

[0112] As Figure 2 shown, for extracting the characteristic quantities of the unbalance vibration signal, after obtaining the vibration signal, first perform low-pass filtering and downsampling processing on the vibration signal, as Figure 3The figure shows the waveform diagram of the vibration signal obtained after preprocessing. Figure 4 The corresponding spectrogram is shown. As can be seen from the figure, the signal contains multiple signal frequency components and certain noise interference, which will interfere with the subsequent extraction of the rotating frequency amplitude and phase.

[0113] The vibration signal is decomposed by the variational mode decomposition method of the above embodiment, and the result is as Figure 5 shown. It is difficult to select the component containing the rotating frequency vibration signal from the decomposition result. The rotating frequency is calculated to be 16.63 Hz from the rotational speed pulse signal. Thus, a rotating frequency reference vibration signal is constructed, and the correlation coefficients between the rotational speed reference signal and each component are calculated. The results are shown in Table 1. The component with the largest correlation coefficient is selected, which is the component containing the rotating frequency. As can be seen from the table, IMF2 is the required component.

[0114] Table 1 Correlation coefficients between each component obtained by decomposing the experimental signal and the rotating frequency signal reference

[0115]

[0116] Figure 6 The spectrograms of each component are shown. As can be seen from the figure, IMF2 is indeed the component containing the rotating frequency, and the screening result by the correlation coefficient method is accurate.

[0117] After screening out the component containing the rotating frequency, the interference of the original signal is effectively suppressed. By performing cross-correlation analysis on this component, the amplitude and phase of the rotating frequency vibration signal can be obtained. For the component containing the rotating frequency vibration signal obtained by screening, cross-correlation analysis is performed, and the amplitude of the rotating frequency signal is 0.4293 (mm / s), and the phase is -107.7302°. To verify the accuracy and stability of the method of the present invention, 10 groups of experimental data are collected at a rotational speed of 1000 r / min, and the rotating frequency amplitude and phase are obtained by using the method of this article. As Figure 7 shown, it is a comparison of the amplitude results obtained by the method of the present invention and the results of other methods under different groups of tests. Figure 8 It is a comparison of the phase results obtained by the method of the present invention and the results of other methods under different groups of tests. As can be seen from the amplitude results, the accuracy and stability of the method of the present invention are significantly better than other methods. As can be seen from the phase results, stable results can be obtained except for the filtering - APFFT method.

[0118] Table 2 Comparison of multiple groups of experimental data at the same rotational speed

[0119]

[0120] From the average values, standard deviations, and error rates of the 10 groups of measurement results of each method in Table 2, it can be seen that among the 10 measurement results, the standard deviations and error rates of the amplitude and phase results of the method of the present invention are both the smallest. The amplitude error rate is 2.9%, and the phase error rate is 2.1%. It can be seen that the method of the present invention has obvious advantages in amplitude and phase extraction compared with other methods.

[0121] To further verify the anti-noise performance of the method of the embodiment of the present invention, a simulation signal is designed, and the signal model is as shown in Equation 13:

[0122] x(t) = 0.7sin(2π×15t) + sin(2π×30t + 60°) + 0.8sin(2π×50t) + s(t) Equation 13

[0123] In the formula: s(t) represents Gaussian white noise. The signal contains frequency components of 15Hz, 30Hz, and 50Hz. The signal-to-noise ratio of the signal is changed from -10 - 5dB. Based on the method of the present invention, the amplitude and phase extraction results at different signal-to-noise ratios are respectively as Figure 9 , Figure 10 shown. It can be seen from the figure that as the signal-to-noise ratio of the signal increases, the amplitude and phase of the method of the present invention always have very stable measurement results. However, the filtering-APFFT method and the resampling-FFT method have poor anti-noise performance and it is difficult to obtain accurate measurement results under strong noise. Due to the mode mixing phenomenon occurring during the decomposition process of the EMD-CA method, the amplitude is significantly reduced.

[0124] Table 3 shows the average values, standard deviations, and error rates of the amplitude and phase results of the rotating frequency signal obtained at different signal-to-noise ratios:

[0125] Comparison of simulation signals obtained at different signal-to-noise ratios in Table 3

[0126]

[0127] It can be seen from Table 3 that the error rates of the amplitude and phase results of the method of the present invention are both within 3%, which is significantly better than other methods. From the above analysis, it can be seen that the method of the present invention can accurately obtain the amplitude and phase information of the rotating frequency component in the vibration signal under a strong noise background, can meet the subsequent dynamic balance requirements, and effectively improve the dynamic balance effect.

[0128] Next, the feature quantity extraction device for unbalanced vibration signals provided by the present invention will be described. The feature quantity extraction device for unbalanced vibration signals described below can be mutually referred to corresponding to the feature quantity extraction method for unbalanced vibration signals described above.

[0129] As Figure 11 shown, a feature quantity extraction device for unbalanced vibration signals is characterized in that it includes:

[0130] The acquisition module 501 is used to simultaneously acquire the unbalanced vibration signal and the rotational speed pulse signal of the main shaft;

[0131] The decomposition module 502 is used to perform modal decomposition on the unbalanced vibration signal, determine the number of modal components according to the energy loss coefficient, and obtain multiple modal components of the unbalanced vibration signal;

[0132] The correlation calculation module 503 is used to determine the rotational frequency according to the rotational speed pulse signal, construct a reference vibration signal according to the rotational frequency, calculate the correlation coefficients between the multiple modal components and the reference vibration signal, and obtain the modal component with the largest correlation coefficient;

[0133] The feature extraction module 504 is used to obtain feature quantities according to the modal component with the largest correlation coefficient.

[0134] The device for extracting the feature quantity of the unbalanced vibration signal according to the embodiment of the present invention decomposes and denoises the unbalanced vibration signal to obtain multiple intrinsic mode functions (IMFs) with different central frequencies, accurately identifies the rotational frequency components in each component by the correlation coefficient method, effectively eliminates the influence of the remaining interference signals, and realizes the accurate extraction of the amplitude and phase of the rotational frequency signal in the main shaft vibration signal under the strong noise background.

[0135] In at least one embodiment of the present invention, the performing modal decomposition on the unbalanced vibration signal and determining the number of modal components according to the energy loss coefficient includes:

[0136] Performing modal decomposition on the unbalanced vibration signal by using the variational mode decomposition method, and the number of modal components increases with the increase of the number of iterations;

[0137] Setting an iteration stop condition according to the energy loss coefficient, and obtaining the number of modal components when the iteration stops.

[0138] In at least one embodiment of the present invention, the iteration stop condition is that the energy loss coefficient is less than a threshold value, and the value range of the threshold value is [0.02, 0.06].

[0139] In at least one embodiment of the present invention, the energy loss coefficient is calculated by Equation 1:

[0140]

[0141] where ξ represents the energy loss coefficient, f represents the unbalanced vibration signal, u k represents the kth modal component, and K represents the total number of modal components.

[0142] In at least one embodiment of the present invention, the obtaining feature quantities according to the modal component with the largest correlation coefficient includes:

[0143] Take the modal component with the largest correlation coefficient as the component containing the rotational frequency vibration signal, obtain the amplitude and phase of the rotational frequency vibration signal, and obtain the characteristic quantity.

[0144] In at least one embodiment of the present invention, the device further includes a preprocessing module for preprocessing the unbalance vibration signal, and the preprocessing includes low-pass filtering and downsampling processing.

[0145] Figure 12 An example of the physical structure diagram of an electronic device is shown as Figure 12 As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630, and a communication bus 640. Among them, the processor 610, the communication interface 620, and the memory 630 complete mutual communication through the communication bus 640. The processor 610 can call the logical instructions in the memory 630 to execute the method for extracting the characteristic quantity of the unbalance vibration signal, and the method includes:

[0146] Simultaneously collect the unbalance vibration signal and the rotational speed pulse signal of the main shaft;

[0147] Perform modal decomposition on the unbalance vibration signal, determine the number of modal components according to the energy loss coefficient, and obtain multiple modal components of the unbalance vibration signal;

[0148] Determine the rotational frequency according to the rotational speed pulse signal and construct a reference vibration signal according to the rotational frequency, calculate the correlation coefficients between the multiple modal components and the reference vibration signal, and obtain the modal component with the largest correlation coefficient;

[0149] Obtain the characteristic quantity according to the modal component with the largest correlation coefficient.

[0150] In addition, when the logical instructions in the above-mentioned memory 630 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0151] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for extracting characteristic quantities of unbalanced vibration signals provided by the above-mentioned various methods. The method includes:

[0152] Simultaneously collect the unbalanced vibration signal and the rotational speed pulse signal of the main shaft;

[0153] Perform modal decomposition on the unbalanced vibration signal, determine the number of modal components according to the energy loss coefficient, and obtain multiple modal components of the unbalanced vibration signal;

[0154] Determine the rotational frequency according to the rotational speed pulse signal and construct a reference vibration signal according to the rotational frequency, calculate the correlation coefficients of the multiple modal components and the reference vibration signal, and obtain the modal component with the largest correlation coefficient;

[0155] Obtain the characteristic quantity according to the modal component with the largest correlation coefficient.

[0156] On another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it realizes the method for extracting characteristic quantities of unbalanced vibration signals provided by the above-mentioned various methods. The method includes:

[0157] Simultaneously collect the unbalanced vibration signal and the rotational speed pulse signal of the main shaft;

[0158] Perform modal decomposition on the unbalanced vibration signal, determine the number of modal components according to the energy loss coefficient, and obtain multiple modal components of the unbalanced vibration signal;

[0159] Determine the rotational frequency based on the rotational speed pulse signal and construct a reference vibration signal based on the rotational frequency, calculate the correlation coefficients of the multiple modal components and the reference vibration signal, and obtain the modal component with the largest correlation coefficient;

[0160] Obtain the characteristic quantity based on the modal component with the largest correlation coefficient.

[0161] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0162] 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, and of course also by hardware. Based on this understanding, the above technical solutions, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0163] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for extracting characteristic quantities of unbalanced vibration signals, characterized in that, Including: Simultaneously collecting the unbalanced vibration signal and the rotational speed pulse signal of the main shaft; Performing modal decomposition on the unbalanced vibration signal, determining the number of modal components according to the energy loss coefficient, and obtaining multiple modal components of the unbalanced vibration signal; Determining the rotational frequency according to the rotational speed pulse signal, constructing a reference vibration signal according to the rotational frequency, calculating the correlation coefficients of the multiple modal components and the reference vibration signal, and obtaining the modal component with the maximum correlation coefficient; Obtaining a feature quantity according to the modal component with the maximum correlation coefficient, where the feature quantity includes the amplitude and phase of the rotational frequency signal; The energy loss coefficient is calculated using Equation 1: Among them, ξ represents the energy loss coefficient, f represents the unbalanced vibration signal, and u k represents the k-th modal component, and K represents the total number of modal components.

2. The method for extracting the characteristic quantity of the unbalanced vibration signal according to claim 1, wherein The performing modal decomposition on the unbalanced vibration signal and determining the number of modal components according to the energy loss coefficient includes: Performing modal decomposition on the unbalanced vibration signal using the variational mode decomposition method, and the number of modal components increases with the number of iterations; Setting an iteration stop condition according to the energy loss coefficient, and obtaining the number of modal components when the iteration stops.

3. The method for extracting the characteristic quantity of the unbalanced vibration signal according to claim 2, wherein The iteration stop condition is that the energy loss coefficient is less than a threshold, and the value range of the threshold is [0.02, 0.06].

4. The method for extracting the characteristic quantity of the unbalanced vibration signal according to any one of claims 1 to 3, characterized in that, The obtaining a feature quantity according to the modal component with the maximum correlation coefficient includes: Taking the modal component with the maximum correlation coefficient as the component containing the rotational frequency vibration signal, obtaining the amplitude and phase of the rotational frequency vibration signal, and obtaining the feature quantity.

5. The method for extracting the characteristic quantity of the unbalanced vibration signal according to any one of claims 1 to 3, characterized in that, Before performing modal decomposition on the unbalanced vibration signal, it further includes: Performing preprocessing on the unbalanced vibration signal, and the preprocessing includes low-pass filtering and downsampling processing.

6. An apparatus for extracting characteristic quantities of unbalanced vibration signals, characterized in that, Including: An acquisition module for simultaneously collecting the unbalanced vibration signal and the rotational speed pulse signal of the main shaft; A decomposition module for performing modal decomposition on the unbalanced vibration signal, determining the number of modal components according to the energy loss coefficient, and obtaining multiple modal components of the unbalanced vibration signal; A correlation calculation module for determining the rotational frequency according to the rotational speed pulse signal, constructing a reference vibration signal according to the rotational frequency, calculating the correlation coefficients of the multiple modal components and the reference vibration signal, and obtaining the modal component with the maximum correlation coefficient; A feature extraction module for obtaining a feature quantity according to the modal component with the maximum correlation coefficient, where the feature quantity includes the amplitude and phase of the rotational frequency signal; Wherein, the energy loss coefficient is calculated using Equation 1: Among them, ξ represents the energy loss coefficient, f represents the unbalanced vibration signal, and u k represents the k-th modal component, and K represents the total number of modal components.

7. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method for extracting the feature quantity of the unbalanced vibration signal according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for extracting the feature quantity of the unbalanced vibration signal according to any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for extracting the feature quantity of the unbalanced vibration signal according to any one of claims 1 to 5.

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