A peak value orientation-based vibration characteristic frequency calculation method and device

Abstract

The application provides a peak value orientation-based vibration characteristic frequency calculation method and device. The peak value orientation-based vibration characteristic frequency calculation method comprises: obtaining a target frequency spectrum corresponding to a device acceleration signal; determining a scanning range on the target frequency spectrum according to a characteristic frequency range of a preset component in the device; calculating characteristic frequencies of each component corresponding to each position in the scanning range according to frequencies corresponding to the positions; determining a peak value number of each position according to the characteristic frequencies of each component corresponding to the positions; and determining a target characteristic frequency of each component according to a position with the most peak values in the scanning range. Through the application, the characteristic frequency can be determined based on the peak value attribute of the characteristic frequency, the operation can be simplified, the calculation accuracy of the characteristic frequency can be improved, the fault recognition rate can be improved, and the fault characteristic frequency can be found early.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of signal analysis, and in particular to a method and apparatus for calculating vibration characteristic frequencies based on peak guidance. Background Technology

[0002] Vibration spectrum analysis is one of the most important methods for conducting equipment vibration testing and fault diagnosis. Accurately identifying and locating the main frequency components, i.e., the characteristic frequencies of key components, is a prerequisite for vibration analysts and computers to perform vibration spectrum analysis. The flexible application of the correspondence between characteristic frequency patterns and typical faults can effectively assist in fault mode identification, determining the presence or absence of faults and the degree of component damage, thereby guiding industrial production in developing maintenance and repair processes. Therefore, accurate location of vibration characteristic frequencies is the cornerstone of equipment fault diagnosis.

[0003] Due to the inherent characteristics of the Discrete Fourier Transform, after converting the vibration time series signal into a discrete spectrum, the spectrum exhibits a grating effect, with spectral lines distributed at equal intervals with a frequency resolution Δf. This results in a persistent deviation between the characteristic frequencies read from the spectrum and the actual vibration frequencies of the equipment. When performing spectrum analysis using the cursor function in professional vibration analysis software, if the characteristic frequency is taken as the fundamental frequency, the deviation of its harmonics will be magnified exponentially with increasing order.

[0004] In existing technologies, the cursor movement method of the fundamental frequency is improved by utilizing the cursor analysis function of vibration analysis software to overcome the inherent frequency resolution Δf interval limitation of discrete spectrum. The fundamental frequency cursor is moved with a new step length of integer fractions of Δf, such as Δf / 10, and its harmonic and sideband cursors move proportionally accordingly. Alternatively, any order harmonic cursor can be dragged for fine-tuning, and the fundamental frequency and other order harmonic cursors move proportionally. While these two methods improve the spectrum's grid limitations to some extent, they fail to simultaneously consider the positioning of other characteristic frequencies. This is because the transmission coefficients between key components within the equipment are fixed, and the ratios of different vibration characteristic frequencies are also fixed. However, simultaneously searching for multiple characteristic frequencies and their harmonics and sidebands is cumbersome by both manual and visual means. Furthermore, publicly available automatic vibration characteristic frequency positioning methods are generally developed based on the high amplitude characteristics of characteristic frequencies, easily neglecting the precise distribution characteristics of these frequencies. When early failures occur in rolling bearings, the vibration spectrum will show fault characteristic frequencies and their harmonics, but the amplitude level is often low and the vibration energy is small. They are easily buried by other characteristic frequencies or background noise, resulting in a low fault identification rate. Summary of the Invention

[0005] To improve the accuracy of characteristic frequency calculation, simplify operation, and detect fault characteristic frequencies early, this invention proposes a peak-guided vibration characteristic frequency calculation method and device.

[0006] In a first aspect, the present invention provides a method for calculating vibration characteristic frequencies based on peak guidance, the method comprising:

[0007] Obtain the target spectrum corresponding to the device's acceleration signal;

[0008] The scanning range on the target spectrum is determined based on the characteristic frequency range of the preset components in the equipment;

[0009] Based on the frequencies corresponding to each position within the scanning range, calculate the characteristic frequencies of each component at each position. Each position within the scanning range corresponds to the characteristic frequencies of each component.

[0010] The number of peak values ​​at each location is determined based on the characteristic frequencies of each component at each location.

[0011] The target feature frequency of each component is determined based on the location with the highest number of peaks within the scanning range.

[0012] This invention provides a peak-guided method for calculating vibration characteristic frequencies. After determining the scanning range for scanning the vibration spectrum, the characteristic frequency of each component is determined based on the number of peaks at each position within the scanning range. Since the peaks in the vibration spectrum are mainly concentrated at the characteristic frequencies of each component, the characteristic frequency determined based on the position with the most peaks within the scanning range is more accurate, allowing for earlier detection of fault characteristic frequencies and thus improving the fault identification rate. Furthermore, the target characteristic frequencies of each component obtained through this invention are determined by a transmission coefficient. After determining the final position on the vibration spectrum, the target characteristic frequency of the preset component corresponding to that position can be obtained. The target characteristic frequencies of other components can also be obtained based on the transmission coefficient. Compared to manual adjustment methods such as micro-step movement of the base frequency or dragging a single characteristic frequency multiplier, this method determines the scanning range with a specific characteristic frequency range and uses a micro-step scanning method with multiple characteristic frequencies synchronized. This simplifies operation and effectively eliminates the drawback of the characteristic frequency multiplying with the multiplication error of the multiplier, significantly improving the efficiency and accuracy of characteristic frequency calculation. Compared to amplitude-guided automatic search methods, the peak-guided method for calculating vibration characteristic frequencies provided by this invention is unaffected by the magnitude of vibration energy and exhibits outstanding resistance to background noise amplitude interference.

[0013] In conjunction with the first aspect, in the first embodiment of the first aspect, calculating the characteristic frequency of each component corresponding to each position within the scanning range based on the frequency corresponding to each position includes:

[0014] Obtain the transmission coefficients between each component and the preset component;

[0015] The frequencies corresponding to each position within the scanning range are respectively used as the characteristic frequencies of the preset components at each position;

[0016] Based on the characteristic frequency and transmission coefficient of the preset components at each position, the characteristic frequency of each component at each position is calculated.

[0017] In conjunction with the first embodiment of the first aspect, in the second embodiment of the first aspect, the step of calculating the characteristic frequency of each component at each position based on the characteristic frequency and transmission coefficient of the preset component at each position includes:

[0018] Based on the characteristic frequencies and transmission coefficients of the components at each position, the initial characteristic frequencies of each component at each position are calculated respectively.

[0019] Based on the amplitude of the adjacent spectral lines corresponding to the initial characteristic frequencies of each component in the target spectrum, the initial characteristic frequencies of each component are corrected, and the corrected initial characteristic frequencies of each component are used as the characteristic frequencies of the corresponding components.

[0020] In conjunction with the second embodiment of the first aspect, in the third embodiment of the first aspect, before the step of determining the number of peak values ​​at each position based on the characteristic frequencies of each component corresponding to each position, the method further includes:

[0021] Mark the peak attributes of each spectral line in the target spectrum.

[0022] In conjunction with the third embodiment of the first aspect, in the fourth embodiment of the first aspect, the characteristic frequency of each component is determined according to the corrected initial characteristic frequency of each component, and the initial characteristic frequency of each component is corrected according to the amplitude of the adjacent spectral lines corresponding to the initial characteristic frequency of each component in the target spectrum, and the corrected initial characteristic frequency of each component is used as the characteristic frequency of the corresponding component, including:

[0023] For any component, compare the amplitudes of adjacent spectral lines of the component's initial characteristic frequency in the target spectrum, and determine the frequency corresponding to the spectral line with the largest amplitude among the adjacent spectral lines as the component's characteristic frequency. The peak attribute of the component's characteristic frequency is the same as the peak attribute of the spectral line with the largest amplitude among the corresponding adjacent spectral lines.

[0024] In conjunction with the fourth embodiment of the first aspect, in the fifth embodiment of the first aspect, determining the number of peak values ​​at each position based on the characteristic frequencies of each component corresponding to each position includes:

[0025] Based on the peak value of the characteristic frequency of each component at each location, determine the number of peak values ​​of the characteristic frequency of each component at each location.

[0026] The number of peak values ​​of the characteristic frequencies of each component at each position is weighted and summed to obtain the number of peak values ​​at each position.

[0027] Through the above embodiments, the characteristic frequencies of different components have different importance to the equipment. The corresponding peak values ​​are weighted and summed according to the importance of the characteristic frequencies of each component, so that the characteristic frequencies calculated by this method can better reflect the vibration characteristics of the equipment.

[0028] In conjunction with the fifth embodiment of the first aspect, in the sixth embodiment of the first aspect, determining the target feature frequency of each component based on the location with the highest number of peaks within the scanning range includes:

[0029] The frequency corresponding to the position with the most peaks is determined as the target characteristic frequency of the preset component;

[0030] The target characteristic frequency of each component is calculated based on the target characteristic frequency and transmission coefficient of the preset components.

[0031] In conjunction with the first aspect, in the seventh embodiment of the first aspect, obtaining the target spectrum corresponding to the device acceleration signal includes:

[0032] Acquire multiple acceleration signals from the device;

[0033] Perform Fast Fourier Transform on multiple acceleration signals to obtain multiple initial spectra corresponding to the device acceleration signals;

[0034] The target spectrum is obtained by linearly averaging multiple initial spectra.

[0035] By performing linear averaging on multiple vibration spectra as described above, the impact of random noise on a single vibration spectrum can be reduced, thus suppressing noise interference input from the signal source.

[0036] In conjunction with the first aspect or the sixth embodiment of the first aspect, in the eighth embodiment of the first aspect, the scanning range is determined according to a positive integer multiple of the characteristic frequency range of the preset component.

[0037] Through the above embodiments, the larger the frequency corresponding to the scanning range determined by positive integer multiples of the characteristic frequency range, the higher the accuracy of the corresponding characteristic frequency can be obtained when moving on the vibration spectrum with frequency resolution.

[0038] Secondly, the present invention also provides a peak-guided vibration characteristic frequency calculation device, the device comprising:

[0039] The acquisition module is used to acquire the target spectrum corresponding to the device's acceleration signal;

[0040] The first determining module is used to determine the scanning range on the target spectrum based on the characteristic frequency range of the preset components in the device;

[0041] The calculation module is used to calculate the characteristic frequency of each component at each position within the scanning range based on the frequency corresponding to each position. Each position within the scanning range corresponds to the characteristic frequency of each component.

[0042] The second determining module is used to determine the number of peak values ​​at each position based on the characteristic frequencies of each component corresponding to each position.

[0043] The third determining module is used to determine the target characteristic frequency of each component based on the location with the most peaks within the scanning range.

[0044] This invention provides a peak-guided vibration characteristic frequency calculation device. After determining the scanning range when scanning the vibration spectrum, the characteristic frequency of each component is determined based on the number of peaks at each position within the scanning range. Since the peaks in the vibration spectrum are mainly concentrated at the characteristic frequencies of each component, the characteristic frequency determined based on the position with the most peaks within the scanning range is more accurate, allowing for earlier detection of fault characteristic frequencies and thus improving the fault identification rate. Furthermore, the target characteristic frequencies of each component obtained through this invention are determined by a transmission coefficient. After determining the final position on the vibration spectrum, the target characteristic frequency of the preset component corresponding to that position can be obtained. The target characteristic frequencies of other components can also be obtained based on the transmission coefficient. Compared to manual adjustment methods such as micro-step movement of the base frequency and dragging a single characteristic frequency multiplier, this device determines the scanning range with a specific characteristic frequency range. The micro-step scanning method, with multiple characteristic frequencies synchronized, simplifies operation and effectively eliminates the drawback of the characteristic frequency multiplying with the multiplier error, significantly improving the efficiency and accuracy of characteristic frequency calculation. Compared to amplitude-guided automatic search methods, the peak-guided vibration characteristic frequency calculation device provided by this invention is unaffected by the magnitude of vibration energy and exhibits outstanding resistance to background noise amplitude interference. Attached Figure Description

[0045] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0046] Figure 1 This is a flowchart of a peak-guided vibration characteristic frequency calculation method according to an exemplary embodiment;

[0047] Figure 2(a) is a schematic diagram illustrating the definition of a peak value in an example;

[0048] Figure 2(b) is a schematic diagram illustrating the definition of a peak value in yet another example;

[0049] Figure 3(a) is a schematic diagram of selecting the left spectral line as the correction point in an example;

[0050] Figure 3(b) is a schematic diagram of selecting the left spectral line as the correction point in yet another example;

[0051] Figure 3(c) is a schematic diagram of selecting the right spectral line as the correction point in an example;

[0052] Figure 3(d) is a schematic diagram of selecting the right spectral line as the correction point in yet another example;

[0053] Figure 3(e) is a schematic diagram in an example where the initial landing point is maintained without correction;

[0054] Figure 4 This is a schematic diagram of a peak-guided vibration characteristic frequency calculation device according to an exemplary embodiment.

[0055] Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an exemplary embodiment. Detailed Implementation

[0056] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0058] To improve the accuracy of characteristic frequency calculation, simplify operation, and detect fault characteristic frequencies early, this invention proposes a peak-guided vibration characteristic frequency calculation method and device.

[0059] Figure 1 This is a flowchart illustrating a peak-guided vibration characteristic frequency calculation method according to an exemplary embodiment. Figure 1 As shown, the peak-guided vibration characteristic frequency calculation method includes the following steps S101 to S105.

[0060] Step S101: Obtain the target spectrum corresponding to the acceleration signal of the device.

[0061] In one alternative embodiment, the device can be a gearbox, motor, fan, hydraulic pump, or belt-driven rotating mechanical device. The acceleration signal of the device refers to the overall vibration acceleration signal of the device.

[0062] Step S102: Determine the scanning range on the target spectrum based on the characteristic frequency range of the preset components in the device.

[0063] In one alternative embodiment, the device includes multiple components, and the preset component can be any component in the device.

[0064] In one optional embodiment, the scanning range on the target spectrum can be determined based on the characteristic frequency range of a preset component in the device, or it can be determined based on a positive integer multiple of the characteristic frequency range of the preset component. The higher the characteristic frequency of the component, or the larger the positive integer multiple of the characteristic frequency, the higher the frequency corresponding to the scanning range will be. Correspondingly, when moving the position on the vibration spectrum according to the resolution of the vibration spectrum, the moving interval of the characteristic frequency calculation value will be smaller, and the calculation result will be more accurate.

[0065] Step S103: Calculate the characteristic frequency of each component corresponding to each position within the scanning range based on the frequency corresponding to each position. Each position within the scanning range corresponds to the characteristic frequency of each component.

[0066] In one optional embodiment, the scanning range is determined based on the characteristic frequency range of a preset component, and the interval between each position within the scanning range is the frequency resolution of the vibration spectrum. Each position within the scanning range corresponds to a frequency. For one position, when calculating the characteristic frequency of each component at that position, the characteristic frequency of the preset component is first determined based on the frequency corresponding to that position. Then, the characteristic frequencies of other components are calculated based on the transmission coefficients between the components, thereby obtaining the characteristic frequencies corresponding to each component at that position. This process is repeated to obtain the characteristic frequencies corresponding to each component at other positions within the scanning range.

[0067] Specifically, since the conversion relationship between the characteristic frequencies of each component can be obtained through the transmission coefficient, if the characteristic frequency of one component is known, the characteristic frequencies of other components can be obtained based on the transmission coefficient. Therefore, in this embodiment of the invention, after determining the characteristic frequency of a preset component, the characteristic frequencies of other components can be calculated based on the characteristic frequency of that component and the transmission coefficients between the components. For different devices, the components they contain are different, and the transmission coefficients of each component are also different.

[0068] Specifically, the characteristic frequency of the device can include the characteristic frequency of each component, or it can include a harmonic of the characteristic frequency of each component. In this case, the harmonic can also be regarded as a characteristic frequency of the component. When the scanning range is a preset characteristic frequency range of the component, the frequency at a certain position in the scanning range is determined as the characteristic frequency of the component at the current position. When the scanning range is a positive integer multiple of the preset characteristic frequency range of the component, each position in the scanning range corresponds to a positive integer multiple of the characteristic frequency of the component.

[0069] Step S104: Determine the number of peak values ​​at each position based on the characteristic frequencies of each component corresponding to each position.

[0070] In one optional embodiment, each location within the scanning range corresponds to a plurality of characteristic frequencies of individual components. The number of peaks at a location is determined based on the peak attribute of the characteristic frequencies of all components at that location.

[0071] In an alternative embodiment, at a location within the scanning range, the peak attribute of the characteristic frequency of each component is determined based on the peak attribute of the two spectral lines adjacent to the characteristic frequency in the vibration spectrum.

[0072] Step S105: Determine the target characteristic frequency of each component based on the location with the highest number of peaks within the scanning range. The target characteristic frequency is used for component fault detection.

[0073] In one alternative embodiment, at a location within the scanning range, different components correspond to their respective target feature frequencies.

[0074] This invention provides a peak-guided method for calculating vibration characteristic frequencies. After determining the scanning range for scanning the vibration spectrum, the characteristic frequency of each component is determined based on the number of peaks at each position within the scanning range. Since the peaks in the vibration spectrum are mainly concentrated at the characteristic frequencies of each component, the characteristic frequency determined based on the position with the most peaks within the scanning range is more accurate, allowing for earlier detection of fault characteristic frequencies and thus improving the fault identification rate. Furthermore, the target characteristic frequencies of each component obtained through this invention are determined by a transmission coefficient. After determining the final position on the vibration spectrum, the target characteristic frequency of the preset component corresponding to that position can be obtained. The target characteristic frequencies of other components can also be obtained based on the transmission coefficient. Compared to manual adjustment methods such as micro-step movement of the base frequency or dragging a single characteristic frequency multiplier, this method determines the scanning range based on the characteristic frequency range of the preset component. The micro-step scanning method with multiple characteristic frequencies synchronized simplifies operation and effectively eliminates the drawback of the characteristic frequency multiplying with the multiplier error, significantly improving the efficiency and accuracy of characteristic frequency calculation. Compared to amplitude-guided automatic search methods, the peak-guided method for calculating vibration characteristic frequencies provided by this invention is unaffected by the magnitude of vibration energy and exhibits outstanding resistance to background noise amplitude interference.

[0075] In one example, in step S101 above, the target spectrum corresponding to the device acceleration signal can be obtained in the following manner, specifically including:

[0076] First, acquire multiple acceleration signals from the device. For example, vibration acceleration signals from the device can be acquired using a vibration sensor.

[0077] Then, fast Fourier transforms are performed on the multiple acceleration signals to obtain multiple initial spectra corresponding to the device acceleration signals.

[0078] Finally, the target spectrum is obtained by linear averaging of multiple initial spectra.

[0079] In one optional embodiment, the number of averages can be selected from 1 to 6. The number of averages can be adjusted according to the actual operating conditions of the equipment. If the rotation speed and load are relatively stable during the vibration acquisition period, a larger number of averages is selected, and vice versa. If the operating conditions of the equipment change significantly in a short period of time, no averaging is performed, that is, the number of averages is selected as 1.

[0080] By linearly averaging multiple vibration spectra, the impact of random noise on individual vibration spectra can be reduced, suppressing noise interference at the signal source. To shorten the acquisition time, each set of vibration time series can be used with a 50% overlap between the beginning and end.

[0081] In one example, background noise or random vibrations often cause an increase in the energy at the bottom of the vibration spectrum (noise floor). Although the noise floor amplitude is small, it is uneven, resembling "undulating mountain peaks." Therefore, mean filtering or smoothing filtering is used to smooth the noise floor of the target spectrum, while ensuring that the amplitude of spectral lines with amplitudes exceeding a predetermined value remains unchanged; that is, spectral lines with relatively large amplitudes are not included in the smoothing process. The proportion of spectral lines with unchanged amplitudes to the total number of spectral lines in the analysis band can be adjusted according to actual needs and is not specifically limited here. Noise floor smoothing preprocessing can specifically smooth out the messy noise floor, achieving a "peak-shaving and valley-filling" effect and reducing the risk of misjudging the peak attributes of subsequent spectral lines.

[0082] In one example, the method provided by this embodiment of the invention further includes the following step: marking the peak attributes of each spectral line in the target spectrum.

[0083] In an alternative embodiment, the peak attribute is defined as follows:

[0084] As shown in Figure 2(a), there are 5 adjacent spectral lines with amplitudes of Y, ... i-2 Y i-1 Y i Y i+1 Y i+2 , such as (Y i-2 <Y i-1 Y i-1 <Y i And (Y) i >Y i+1 Y i+1 >Y i+2 If Y is the correct answer, then Y is called Y. iThe spectral lines represent peak values. Considering the possibility of two true peaks being adjacent, as shown in Figure 2(b), a supplementary definition of a peak value is given: there are 7 adjacent spectral lines with amplitudes Y... i-3 Y i-2 Y i-1 Y i Y i+1 Y i+2 Y i+3 , such as (Y i-3 <Y i-2 Y i-2 <Y i-1 Y i-1 >Y i And (Y) i <Y i+1 Y i+1 >Y i+2 Y i+2 >Y i+3 If Y is the correct answer, then Y is called Y. i-1 Y i+1 The spectral lines represent peak values. The peak attribute is defined as 1, and the non-peak attribute as 0.

[0085] In another example, in step S103 above, the characteristic frequencies of each component at each position can be calculated using the following steps:

[0086] First, obtain the transmission coefficients between each component and the preset component. Given the characteristic frequency of the preset component, the characteristic frequencies of all other components in the device can be determined using the transmission coefficients.

[0087] Then, the frequencies corresponding to each position within the scanning range are used as the characteristic frequencies of the preset components at each position.

[0088] Finally, based on the characteristic frequencies and transmission coefficients of the preset components at each position, the characteristic frequencies of each component at each position are calculated respectively.

[0089] In an optional embodiment, the step of calculating the characteristic frequency of each component at each position based on the characteristic frequency and transmission coefficient of the preset component at each position can be implemented by the following steps: First, calculate the initial characteristic frequency of each component at each position based on the characteristic frequency and transmission coefficient of the preset component at each position; then, correct the initial characteristic frequency of each component according to the amplitude of the adjacent spectral lines corresponding to the initial characteristic frequency of each component in the target spectrum, and use the corrected initial characteristic frequency of each component as the characteristic frequency of the corresponding component.

[0090] Specifically, for any component, the amplitudes of the component's initial characteristic frequency in the target spectrum of adjacent spectral lines are compared, and the frequency corresponding to the spectral line with the largest amplitude among the adjacent spectral lines is determined as the characteristic frequency of the component. The peak attribute of the component's characteristic frequency is the same as the peak attribute of the spectral line with the largest amplitude among the corresponding adjacent spectral lines.

[0091] In this embodiment of the invention, when the initial characteristic frequency falls between two adjacent spectral lines, the landing point is reset to the side with the larger amplitude based on the peak-oriented principle. If the amplitude of the left spectral line is higher, the left spectral line is selected as the correction point, that is, the frequency corresponding to the left spectral line is selected as the corrected initial characteristic frequency; otherwise, the right spectral line is selected as the correction point. When the initial characteristic frequency coincides with a certain spectral line, it is necessary to combine the left and right spectral lines of that spectral line for comprehensive judgment, and select the frequency corresponding to the spectral line with the larger amplitude as the corrected initial characteristic frequency. Figures 3(a) and 3(b) select the left spectral line as the correction point, Figures 3(c) and 3(d) select the right spectral line as the correction point, and Figure 3(e) maintains the initial landing point without correction. After the initial characteristic frequency completes the landing point correction, the peak attribute of the spectral line at the correction point is used as the peak attribute of the corrected initial characteristic frequency.

[0092] In one example, in step S104 above, the number of peaks at each location is determined based on the characteristic frequencies of each component corresponding to each location. The specific steps include:

[0093] First, based on the peak value of the characteristic frequency of each component at each location, determine the number of peak values ​​of the characteristic frequency of each component at each location.

[0094] Then, the number of peak values ​​of the characteristic frequencies of each component at each position is weighted and summed to obtain the number of peak values ​​at each position.

[0095] For equipment fault detection, the characteristic frequencies of different components have varying degrees of importance. Therefore, in this embodiment of the invention, the peak attribute corresponding to the characteristic frequency of important components has a greater weight.

[0096] In one example, in step S105 above, the target feature frequency of each component is determined based on the location with the highest number of peaks within the scanning range. Specific steps include:

[0097] First, the frequency corresponding to the position with the most peaks is determined as the target characteristic frequency of the preset component;

[0098] Then, based on the target characteristic frequency and transmission coefficient of the preset components, the target characteristic frequency of each component is calculated.

[0099] Based on the same inventive concept, embodiments of the present invention also provide a peak-guided vibration characteristic frequency calculation device, such as... Figure 4As shown, the device includes:

[0100] The acquisition module 401 is used to acquire the target spectrum corresponding to the device acceleration signal; for details, please refer to the description of step S101 in the above embodiment, which will not be repeated here.

[0101] The first determining module 402 is used to determine the scanning range on the target spectrum based on the characteristic frequency range of the preset components in the device; for details, please refer to the description of step S102 in the above embodiment, which will not be repeated here.

[0102] The calculation module 403 is used to calculate the characteristic frequency of each component corresponding to each position within the scanning range based on the frequency corresponding to each position within the scanning range. Each position within the scanning range corresponds to the characteristic frequency of each component. For details, please refer to the description of step S103 in the above embodiment, which will not be repeated here.

[0103] The second determining module 404 is used to determine the number of peak values ​​at each position based on the characteristic frequencies of each component corresponding to each position; for details, please refer to the description of step S104 in the above embodiment, which will not be repeated here.

[0104] The third determining module 405 is used to determine the target feature frequency of each component based on the position with the most peaks within the scanning range. For details, please refer to the description of step S105 in the above embodiments, which will not be repeated here.

[0105] In one example, module 401 also includes:

[0106] The first acquisition submodule is used to acquire multiple acceleration signals from the device; for details, please refer to the description in the above embodiments, which will not be repeated here.

[0107] The transformation submodule is used to perform fast Fourier transform on multiple acceleration signals to obtain multiple initial spectra corresponding to the device acceleration signals; for details, please refer to the description in the above embodiments, which will not be repeated here.

[0108] The averaging submodule is used to perform a linear average of multiple initial spectra to obtain the target spectrum. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0109] In one example, the scanning range in the device is determined based on a positive integer multiple of the characteristic frequency range of a preset component. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0110] In one example, the calculation module 403 includes:

[0111] The second acquisition submodule is used to acquire the transmission coefficient between each component and the preset component; for details, please refer to the description in the above embodiments, which will not be repeated here.

[0112] The first determining submodule is used to take the frequency corresponding to each position within the scanning range as the characteristic frequency of the preset component at each position; for details, please refer to the description in the above embodiments, which will not be repeated here.

[0113] The first calculation submodule is used to calculate the characteristic frequency of each component at each position based on the characteristic frequency and transmission coefficient of the preset components at each position. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0114] In an optional embodiment, the first computing submodule includes:

[0115] The calculation unit is used to calculate the initial characteristic frequency of each component at each position based on the characteristic frequency and transmission coefficient of the preset component at each position; for details, please refer to the description in the above embodiments, which will not be repeated here.

[0116] The correction unit is used to correct the initial characteristic frequency of each component based on the amplitude of the adjacent spectral lines corresponding to the initial characteristic frequency of each component in the target spectrum, and to use the corrected initial characteristic frequency of each component as the corresponding characteristic frequency of each component. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0117] In an optional embodiment, the correction unit includes:

[0118] The correction subunit is used to compare the amplitudes of adjacent spectral lines of the component's initial characteristic frequency in the target spectrum for any component, and determine the frequency corresponding to the spectral line with the largest amplitude among the adjacent spectral lines as the component's characteristic frequency. The peak attribute of the component's characteristic frequency is the same as the peak attribute of the corresponding adjacent spectral line with the largest amplitude. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0119] In one example, the device also includes:

[0120] The labeling module is used to label the peak attributes of each spectral line in the target spectrum. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0121] In one example, the second determining module 404 includes:

[0122] The second determining submodule is used to determine the number of peak values ​​of the characteristic frequencies of each component at each position based on the peak value attributes of the characteristic frequencies of each component at each position; for details, please refer to the description in the above embodiments, and will not be repeated here.

[0123] The summation submodule is used to sum the peak values ​​of the characteristic frequencies of each component at each location using weighted summation to obtain the peak value at each location. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0124] In one example, the third determining module 405 includes:

[0125] The third determining submodule is used to determine the frequency corresponding to the position with the most peaks as the target characteristic frequency of the preset component; for details, please refer to the description in the above embodiments, and will not be repeated here.

[0126] The second calculation submodule is used to calculate the target characteristic frequency of each component based on the preset target characteristic frequency and transmission coefficient of the component. For details, please refer to the description in the above embodiments, which will not be repeated here.

[0127] The specific limitations and beneficial effects of the aforementioned device can be found in the above description of the limitations of the peak-guided vibration characteristic frequency calculation method, and will not be repeated here. Each of the above modules can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0128] Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an exemplary embodiment. For example... Figure 5 As shown, the device includes one or more processors 510 and memory 520, which includes persistent memory, volatile memory, and a hard disk. Figure 5 Taking a processor 510 as an example, the device may also include an input device 530 and an output device 540.

[0129] The processor 510, memory 520, input device 530, and output device 540 can be connected via a bus or other means. Figure 5 Taking the example of a connection between China and Israel via a bus.

[0130] Processor 510 can be a Central Processing Unit (CPU). Processor 510 can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof. The general-purpose processor can be a microprocessor or any conventional processor.

[0131] The memory 520, as a non-transitory computer-readable storage medium, includes persistent memory, volatile memory, and a hard disk. It can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the peak-oriented vibration characteristic frequency calculation method in this embodiment. The processor 510 executes various server functions and data processing by running the non-transitory software programs, instructions, and modules stored in the memory 520, thereby implementing any of the above-mentioned peak-oriented vibration characteristic frequency calculation methods.

[0132] The memory 520 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data that is needed and required. Furthermore, the memory 520 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 520 may optionally include memory remotely located relative to the processor 510, and these remote memories can be connected to the data processing device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0133] Input device 530 can receive input digital or character information, and generate signal inputs related to user settings and function control. Output device 540 may include display devices such as a display screen.

[0134] One or more modules are stored in memory 520, and when executed by one or more processors 510, they perform actions such as... Figure 1 The method shown.

[0135] The above-described product can execute the method provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in this embodiment can be found in [reference 1]. Figure 1 The relevant descriptions in the illustrated embodiments.

[0136] This invention also provides a non-transitory computer storage medium storing computer-executable instructions that can execute the computation methods in any of the above-described method embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0137] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0138] The above are merely specific embodiments of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A peak-orientation-based method of calculating a vibration characteristic frequency, characterized by, The method includes: Obtain the target spectrum corresponding to the device's acceleration signal; The scanning range on the target spectrum is determined based on the characteristic frequency range of a preset component in the device; the scanning range is determined as a positive integer multiple of the characteristic frequency range of the preset component. Based on the frequencies corresponding to each position within the scanning range, the characteristic frequencies of each component corresponding to each position are calculated, and each position within the scanning range corresponds to the characteristic frequencies of each component. The number of peak values ​​at each location is determined based on the characteristic frequencies of each component at each location. The target characteristic frequency of each component is determined based on the location with the highest number of peaks within the scanning range; Based on the frequencies corresponding to each position within the scanning range, the characteristic frequencies of each component at each position are calculated, including: Obtain the transmission coefficients between each component and the preset component; The frequencies corresponding to each position within the scanning range are respectively used as the characteristic frequencies of the preset components at each position; Based on the characteristic frequency of the preset component at each position and the transmission coefficient, the characteristic frequency of each component at each position is calculated respectively.

2. The method of claim 1, wherein, The steps for calculating the characteristic frequency of each component at each position based on the characteristic frequency of the preset component at each position and the transmission coefficient include: Based on the characteristic frequency of the preset component at each position and the transmission coefficient, the initial characteristic frequency of each component at each position is calculated respectively; Based on the amplitude of the adjacent spectral lines corresponding to the initial characteristic frequencies of each component in the target spectrum, the initial characteristic frequencies of each component are corrected, and the corrected initial characteristic frequencies of each component are used as the characteristic frequencies of the corresponding components.

3. The method according to claim 2, characterized in that, Before determining the number of peak values ​​at each location based on the characteristic frequencies of each component at each location, the following steps are also included: Mark the peak attribute of each spectral line in the target spectrum.

4. The method according to claim 3, characterized in that, Based on the amplitudes of the adjacent spectral lines corresponding to the initial characteristic frequencies of each component in the target spectrum, the initial characteristic frequencies of each component are corrected, and the corrected initial characteristic frequencies of each component are used as the characteristic frequencies of the corresponding components, including: For any component, the amplitudes of adjacent spectral lines in the target spectrum are compared with the initial characteristic frequency of the component. The frequency corresponding to the spectral line with the largest amplitude among the adjacent spectral lines is determined as the characteristic frequency of the component. The peak attribute of the characteristic frequency of the component is the same as the peak attribute of the spectral line with the largest amplitude among the corresponding adjacent spectral lines.

5. The method according to claim 4, characterized in that, Based on the characteristic frequencies of each component at each location, determine the number of peak values ​​at each location, including: Based on the peak value of the characteristic frequency of each component at each location, determine the number of peak values ​​of the characteristic frequency of each component at each location. The number of peak values ​​of the characteristic frequencies of each component at each position is weighted and summed to obtain the number of peak values ​​at each position.

6. The method according to claim 5, characterized in that, The target feature frequencies of each component are determined based on the location with the highest number of peaks within the scanning range, including: The frequency corresponding to the position with the most peaks is determined as the target characteristic frequency of the preset component; Based on the target characteristic frequency of the preset component and the transmission coefficient, the target characteristic frequency of each component is calculated.

7. The method according to claim 1, characterized in that, The acquisition of the target spectrum corresponding to the device acceleration signal includes: Acquire multiple acceleration signals from the device; Perform a Fast Fourier Transform on each of the multiple acceleration signals to obtain multiple initial spectra corresponding to the device acceleration signals; The target spectrum is obtained by linearly averaging multiple initial spectra.

8. A vibration characteristic frequency calculation device based on peak guidance, characterized in that, The device includes: The acquisition module is used to acquire the target spectrum corresponding to the device's acceleration signal; The first determining module is used to determine the scanning range on the target spectrum based on the characteristic frequency range of a preset component in the device; the scanning range is determined according to a positive integer multiple of the characteristic frequency range of the preset component. The calculation module is used to calculate the characteristic frequency of each component corresponding to each position within the scanning range based on the frequency corresponding to each position within the scanning range. Each position within the scanning range corresponds to the characteristic frequency of each component. The second determining module is used to determine the number of peak values ​​at each position based on the characteristic frequencies of each component corresponding to each position. The third determining module is used to determine the target feature frequency of each component based on the location with the most peaks within the scanning range; Based on the frequencies corresponding to each position within the scanning range, the characteristic frequencies of each component at each position are calculated, including: Obtain the transmission coefficients between each component and the preset component; The frequencies corresponding to each position within the scanning range are respectively used as the characteristic frequencies of the preset components at each position; Based on the characteristic frequency of the preset component at each position and the transmission coefficient, the characteristic frequency of each component at each position is calculated respectively.

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