A method, device and apparatus for determining the instantaneous angular velocity of a rotating machine

Abstract

The present invention provides a method, device, and apparatus for determining the instantaneous angular velocity of a rotating machine, wherein the method includes: obtaining a time-frequency diagram corresponding to an acceleration signal of the rotating machine within a preset time period; determining multiple first continuous ridge structures within the first sub-time period based on the local peak value of the spectrum corresponding to any moment in the time-frequency diagram; updating the multiple first continuous ridge structures based on a preset global optimization algorithm and the second ridge point of the time-frequency diagram in the second sub-time period to determine multiple second continuous ridge structures of the time-frequency diagram within the preset time period; determining a target instantaneous frequency within the preset time period based on a preset frequency domain sparsity evaluation index and the multiple second continuous ridge structures, and determining a target instantaneous angular velocity based on the target instantaneous frequency. The solution of the present invention can improve the accuracy of extracting the instantaneous angular velocity.

Description

Technical Field

[0001] The present invention relates to the field of signal processing technology, and in particular to a method, device and equipment for determining the instantaneous angular velocity of a rotating machine. Background Art

[0002] Faults in bearings operating at a constant speed can produce periodic impulses in the vibration signal. Detecting the frequency of fault pulses is fundamental to rolling bearing health monitoring. However, frequency-domain analysis methods face challenges in practical industrial applications, primarily due to the spectral smearing that occurs when industrial machinery operates under non-stationary conditions. To overcome this challenge, instantaneous angular speed (IAS) information has become a crucial component for accurate fault diagnosis.

[0003] Order tracking effectively accounts for speed variations and overcomes spectral ambiguity by resampling the signal in the angular domain, treating it as a function of rotation angle. However, direct IAS measurement is often impractical due to limitations such as installation space and cost. Consequently, numerous speedless order tracking (TLOT) methods have emerged, aiming to estimate IAS from vibration signals. The primary contribution of these methods focuses on extracting speed information by tracking harmonics of varying complexity in a time-frequency representation (TFR).

[0004] In recent years, instantaneous frequency (IF) extraction techniques based on time-frequency representation (TFR) have become a research hotspot in the field of non-stationary signal analysis and are widely used in fault diagnosis of rotating machinery such as rolling bearings and gears. Existing TFR-based IF estimation methods can be divided into two main categories: single-ridge extraction-based IF estimation methods and multi-band fusion-based enhanced IF extraction methods. The first category estimates the IF by identifying ridges within the TFR where signal energy is concentrated. Early methods include peak search (PS) and local cost function (CF) search. The PS method determines the IF by finding the maximum TFR amplitude at each time point, but ignores the temporal continuity of frequency, which can lead to discontinuous frequency traces. The CF method builds on this by introducing a penalty term for frequency jumps to enhance the smoothness of the frequency trace. However, its optimization process only considers the TFR information at the current moment, which can lead to local optimal solutions and affect the accuracy of the estimation. Researchers in another category have proposed multi-band fusion strategies, which enhance the energy characteristics of the target signal by superimposing multiple sub-TFRs. Representative methods include the Multi-Order Probabilistic Approach (MOPA) and the Weighted Multi-Order Viterbi Algorithm (WMOVA). While fusing information from multiple frequency bands, these methods still rely on single-ridge extraction techniques such as PS or CF to extract the instantaneous frequency. However, the frequency band fusion process may introduce interference signals from other frequency bands, affecting the purity of the extraction results. In addition, these methods usually require pre-setting the target frequency range and number of sub-bands, relying on expert experience, which limits their widespread application in practical engineering projects.

[0005] To address the shortcomings of the aforementioned methods in IAS estimation, global optimization algorithms have been widely used in recent years. Global CF optimization methods comprehensively consider the cost information of the entire historical data and can use the global cost at the final moment to backtrack and construct a continuous target ridge. This not only overcomes the shortcomings of traditional local CF optimization but also reduces reliance on prior information. Because this method enhances noise immunity while accumulating previous costs, its overall robustness surpasses that of traditional methods. However, global CF optimization methods also face challenges in situations with large speed fluctuations: large speed fluctuations can introduce excessive frequency hopping penalties and introduce unnecessary interference into the search process, leading to misselection of target ridges in the presence of noise. Specifically, if the search bandwidth is set too wide, more noise will be included in the search range; if the search bandwidth is too narrow, the actual target ridge may be missed. Based on the above analysis, it can be seen that extracting IAS from low signal-to-noise ratio signals under large speed fluctuations remains an unresolved problem. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a method, device and equipment for determining the instantaneous angular velocity of a rotating machine, and to improve the tracking strategy of the ridge structure based on the time-frequency chirp rate and the adaptive broadband search mechanism to improve the robustness and accuracy of the instantaneous angular velocity estimation.

[0007] To solve the above technical problems, an embodiment of the present invention provides a method for determining the instantaneous angular velocity of a rotating machine, comprising: obtaining a time-frequency diagram corresponding to an acceleration signal of the rotating machine within a preset time period;

[0008] Determining, based on a local peak value of the spectrum corresponding to any moment in the first sub-period, the time-frequency graph, a plurality of first continuous ridge line structures within the first sub-period; each of the plurality of first continuous ridge line structures includes a plurality of first ridge points, and the first ridge points correspond one-to-one to a local peak value of the spectrum at any moment in the first sub-period;

[0009] Based on a preset global optimization algorithm and a second ridge point of the time-frequency graph in a second sub-period, updating the plurality of first continuous ridge line structures to determine a plurality of second continuous ridge line structures of the time-frequency graph in a preset period; the second ridge point corresponds one-to-one to a local peak of the spectrum at any moment in the second sub-period; the plurality of consecutive moments are both included in the second sub-period and the first sub-period, and the first moment in the second sub-period is a moment subsequent to the last moment in the first sub-period;

[0010] The target instantaneous frequency within the preset time period is determined according to the preset frequency domain sparsity evaluation index and the plurality of second continuous ridge structures, and the target instantaneous angular velocity is determined according to the target instantaneous frequency.

[0011] In one embodiment, determining a plurality of first continuous ridge structures within the first sub-period according to a local peak value of the spectrum corresponding to any moment within the first sub-period of the time-frequency graph includes:

[0012] Determining a first generation value between a first ridge point corresponding to the current moment in the first sub-period and a first ridge point corresponding to a moment before the current moment in the first sub-period based on a preset cost function, a preset global optimal algorithm, and a local peak value of the spectrum corresponding to the current moment in the first sub-period;

[0013] A plurality of first continuous ridge structures within the first sub-period is determined according to the first generation value.

[0014] In one embodiment, determining a first generation value between a first ridge point corresponding to the current moment in the first sub-period and a first ridge point corresponding to the moment before the current moment based on a preset cost function, a preset global optimal algorithm, and a local peak value of the spectrum corresponding to the current moment in the first sub-period includes:

[0015] Determining a first local cost value between a first ridge point corresponding to the current moment and a first ridge point corresponding to the previous moment in the first sub-period based on the preset cost function and a local peak value of the spectrum corresponding to the current moment in the first sub-period;

[0016] Based on the first preset global optimal algorithm and the first local cost value, determine the first global cost value between the first ridge point corresponding to the current moment in the first sub-period and the first ridge point corresponding to the previous moment of the current moment, and determine the first global cost value as the first cost value.

[0017] In one embodiment, based on a preset global optimization algorithm and a second ridge point of the time-frequency graph in a second sub-period, updating the plurality of first continuous ridge line structures to determine a plurality of second continuous ridge line structures of the time-frequency graph in a preset period includes:

[0018] Constructing a dynamic time-frequency ridge line window, and using the plurality of first ridge points in the first continuous ridge line structure as initial ridge points in the dynamic time-frequency ridge line window; wherein the dynamic time-frequency ridge line window corresponds to the first continuous ridge line structure in a one-to-one manner;

[0019] Determine the predicted ridge point of each of the first continuous ridge lines at the first moment in the second sub-period according to the initial ridge point in the dynamic time-frequency ridge line window and a preset prediction algorithm;

[0020] Determining, based on the predicted ridge point of each of the first continuous ridge line structures at the first moment in the second sub-period and a second preset global optimal algorithm, a target second ridge point within a dynamic bandwidth search range for each of the first continuous ridge line structures at the first moment; the dynamic bandwidth search range is dynamically adjusted based on the predicted ridge point at the current moment in the second sub-period;

[0021] updating the first continuous ridge line structure according to the target second ridge point, and updating the dynamic time-frequency ridge line window according to the updated first continuous ridge line structure;

[0022] According to the ridge points in the updated dynamic time-frequency ridge window and the prediction of the preset prediction algorithm, the above steps are repeated to determine the predicted ridge points and the target second ridge points at each moment in the second sub-period, and after determining the target second ridge points at each moment, the first continuous ridge line structure and the dynamic time-frequency ridge line window are updated until the target second ridge points at all moments in the second sub-period are determined, and the first continuous ridge line structure updated at the last moment is determined to determine the second continuous ridge line structure.

[0023] In one embodiment, determining the predicted ridge point of the first moment of each of the first continuous ridge structures in the second sub-period according to the initial ridge point in the dynamic time-frequency ridge window and a preset prediction algorithm includes:

[0024] Determining the chirp rate of the first predicted ridge point in the second sub-period according to the ridge frequency vector of the first ridge point in the dynamic time-frequency ridge line window and the preset prediction algorithm;

[0025] Based on the chirp rate of the predicted ridge point at the first moment and the first ridge point corresponding to the moment before the first moment, the predicted ridge point at the first moment of each first continuous ridge line structure in the second sub-period is determined.

[0026] In one embodiment, determining a target second ridge point of each of the first continuous ridge line structures within a dynamic bandwidth search range at the first moment in the second sub-period based on the predicted ridge point of each of the first continuous ridge line structures at the first moment in the second sub-period and a second preset global optimal algorithm includes:

[0027] Determining, based on the second preset global optimal algorithm, a second generation value between the predicted ridge point and each second ridge point within the dynamic bandwidth search range at the first moment;

[0028] According to the second generation value, a target second ridge point of each of the first continuous ridge line structures is determined within the dynamic bandwidth search range at the first moment.

[0029] In one embodiment, determining the second generation value between the predicted ridge point and each second ridge point within the dynamic bandwidth search range at the first moment based on the second preset global optimal algorithm includes:

[0030] Determining a second jump penalty term between a second ridge point and the predicted ridge point within the dynamic bandwidth search range at the first moment in the second sub-period based on the local peak hospital of the spectrum at the first moment in the second sub-period;

[0031] According to the second jump penalty item, the second preset global optimal algorithm and the local peak value of the spectrum corresponding to the first moment in the second sub-time period, the second generation value between the predicted ridge point and each second ridge point within the dynamic bandwidth search range at the first moment is determined.

[0032] In one embodiment, determining a target instantaneous frequency within the preset time period based on a preset frequency domain sparsity evaluation index and a plurality of the second continuous ridge structures, and determining a target instantaneous angular velocity based on the target instantaneous frequency includes:

[0033] Screening the plurality of second continuous ridge structures based on the frequency domain sparsity evaluation index to determine the target instantaneous frequency;

[0034] The target instantaneous angular velocity is determined according to the target instantaneous frequency and order information of the target instantaneous frequency and the instantaneous angular velocity.

[0035] An embodiment of the present invention further provides a device for determining the instantaneous angular velocity of a rotating machine, comprising:

[0036] An acquisition module, configured to acquire a time-frequency diagram corresponding to an acceleration signal of the rotating machinery within a preset time period;

[0037] A processing module is used to determine multiple first continuous ridge structures within the first sub-period based on the local peak of the spectrum corresponding to any moment in the first sub-period of the time-frequency graph; each of the multiple first continuous ridge structures includes multiple first ridge points, and the first ridge points correspond one-to-one with the local peak of the spectrum at any moment in the first sub-period; based on a preset global optimization algorithm and the second ridge point of the time-frequency graph in the second sub-period, the multiple first continuous ridge structures are updated to determine multiple second continuous ridge structures of the time-frequency graph within the preset period; the second ridge point corresponds one-to-one with the local peak of the spectrum at any moment in the second sub-period; the second sub-period and the first sub-period both contain multiple continuous moments, and the first moment in the second sub-period is the subsequent moment of the last moment in the first sub-period; according to a preset frequency domain sparsity evaluation index and the multiple second continuous ridge structures, a target instantaneous frequency within the preset period is determined, and a target instantaneous angular velocity is determined based on the target instantaneous frequency.

[0038] An embodiment of the present invention further provides a computing device, comprising:

[0039] a memory for storing one or more programs;

[0040] One or more processors are used to execute the one or more programs to implement the method described above.

[0041] The above solution of the present invention includes at least the following beneficial effects:

[0042] The above-mentioned solution of the present invention provides a method, apparatus, and device for determining the instantaneous angular velocity of a rotating machine, which obtains a time-frequency graph corresponding to an acceleration signal of the rotating machine within a preset time period; determines multiple first continuous ridge structures within a first sub-time period based on a local spectral peak corresponding to any moment in the time-frequency graph; each of the multiple first continuous ridge structures includes multiple first ridge points, and the first ridge points have a one-to-one correspondence with a local spectral peak at any moment in the first sub-time period; updates the multiple first continuous ridge structures based on a preset global optimization algorithm and a second ridge point in a second sub-time period of the time-frequency graph to determine multiple second continuous ridge structures within the time-frequency graph within the preset time period; the second ridge points have a one-to-one correspondence with a local spectral peak at any moment in the second sub-time period; the second sub-time period and the first sub-time period both include multiple consecutive moments, and the first moment in the second sub-time period is a moment subsequent to the last moment in the first sub-time period; determines a target instantaneous frequency within the preset time period based on a preset frequency domain sparsity evaluation index and the multiple second continuous ridge structures, and determines a target instantaneous angular velocity based on the target instantaneous frequency. The ridge tracking strategy is improved by introducing the chirp rate. The chirp rate is used to predict the most likely position of the target ridge at the next moment, and the search range is dynamically adjusted based on the predicted ridge, thereby effectively suppressing the penalty caused by frequency hopping and improving the noise resistance. The continuous ridge selection is optimized by introducing the frequency domain sparsity evaluation index. The spectrum quantitative analysis of the resampled signals of multiple continuous ridges extracted from the time-frequency diagram is performed to ensure the selection of the optimal continuous ridge, thereby enhancing the robustness and accuracy of the instantaneous angular velocity estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a flow chart of a method for determining the instantaneous angular velocity of a rotating machine provided by an embodiment of the present invention;

[0044] Figure 2 An optional embodiment of the present invention provides a TFR of a numerically simulated signal under a wide range of speed variations and different signal-to-noise ratios;

[0045] Figure 3 This is a comparison result of extracting the target instantaneous frequency by various methods under conditions of a wide range of rotational speed changes and different signal-to-noise ratios, provided by an optional embodiment of the present invention;

[0046] Figure 4 is a schematic block diagram of a module block of a device for determining the instantaneous angular velocity of a rotating machine provided by an embodiment of the present invention;

[0047] Figure 5 is a schematic block diagram of an electronic device provided by an embodiment of the present invention;

[0048] Figure 6is a schematic block diagram of a computing device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0050] In the following description, for the purpose of illustrating the various disclosed embodiments, certain specific details are set forth in order to provide a thorough understanding of the various disclosed embodiments. However, those skilled in the relevant art will recognize that the embodiments may be practiced without one or more of these specific details. In other cases, well-known devices, structures, and techniques associated with this application may not be shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0051] Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any manner in one or more embodiments.

[0052] In the following description, in order to clearly show the structure and working mode of the present invention, many directional words will be used for description, but words such as "front", "back", "left", "right", "outside", "inside", "outward", "inward", "up", and "down" should be understood as convenient terms and should not be understood as restrictive terms.

[0053] like Figure 1 As shown, an embodiment of the present invention provides a method 10 for determining the instantaneous angular velocity of a rotating machine, comprising:

[0054] Step 11, obtaining a time-frequency diagram corresponding to the acceleration signal of the rotating machinery within a preset time period;

[0055] Step 12: determining a plurality of first continuous ridge structures within the first sub-period based on the local peak value of the spectrum corresponding to any moment in the first sub-period of the time-frequency graph; each of the plurality of first continuous ridge structures includes a plurality of first ridge points, and the first ridge points correspond one-to-one to the local peak value of the spectrum at any moment in the first sub-period of the time-frequency graph;

[0056] Step 13: Based on the preset global optimization algorithm and the second ridge point of the time-frequency graph in the second sub-period, the multiple first continuous ridge line structures are updated to determine multiple second continuous ridge line structures of the time-frequency graph in the preset period; the second ridge point corresponds one-to-one to the local peak of the spectrum at any moment in the second sub-period; the multiple consecutive moments are included in both the second sub-period and the first sub-period, and the first moment in the second sub-period is the subsequent moment of the last moment in the first sub-period;

[0057] Step 14: Determine the target instantaneous frequency within a preset time period based on the preset frequency domain sparsity evaluation index and the plurality of second continuous ridge structures, and determine the target instantaneous angular velocity based on the target instantaneous frequency.

[0058] In this embodiment, the acceleration signal within the preset time period is time series data, and the acceleration signal can be collected in real time by an acceleration sensor installed on the rotating machinery; by converting the acceleration signal into a time-frequency diagram, the time-frequency characteristics of the time-frequency diagram can be extracted and analyzed, providing a basis for fault diagnosis and status monitoring; each moment in the time-frequency diagram corresponds to a frequency axis, and multiple different local spectrum peaks can be distributed on the frequency axis, that is, at the same moment, there can be multiple different local spectrum peaks, each local spectrum peak corresponds to a different frequency component, and each local spectrum peak corresponds to a ridge point, and the ridge points at consecutive time points in the preset time period are connected to form a continuous ridge line structure in the preset time period;

[0059] Since the chirp rate of the time-frequency spectrum cannot be accurately obtained in the initial stage (first sub-period) within the preset time period, in order to ensure that the extracted first continuous ridge structure balances the amplitude and frequency continuity, a preset cost function is constructed in the process of obtaining multiple first continuous ridge structures within the first sub-period, and the matching relationship between the first ridge points corresponding to the local peak values ​​of the spectrum at two adjacent moments in the first sub-period is calculated based on the preset cost function to connect the first ridge points corresponding to the local peak values ​​of the spectrum at the two adjacent moments; the preset cost function can be adjusted in real time according to the local peak characteristics of the spectrum at different moments in the time-frequency graph to retain the key frequency characteristics while suppressing the discontinuous jumps of the ridge points;

[0060] Furthermore, based on a preset global optimization algorithm, the tracking strategy of the second ridge point in the second sub-period is improved. In the process of tracking the second ridge point, the chirp rate is used to predict the most likely position of the second ridge point that may be connected to the first continuous ridge line structure at the current moment in the second sub-period, and an adaptive method is used to dynamically adjust and obtain the dynamic bandwidth search range, so that it can effectively cover the target second ridge point while suppressing noise interference, thereby achieving high-quality connection and extraction of ridge points on the entire time-frequency plane; by tracking the local peak of the spectrum in the time-frequency diagram through time division and different methods and determining the target ridge point corresponding to the local peak of the spectrum, the instantaneous frequency can be accurately extracted;

[0061] Furthermore, based on the multiple second continuous ridge structures obtained after the update, multiple complete continuous ridge structures within the preset time period can be obtained; and the frequency domain sparsity evaluation index is introduced to perform spectral quantitative analysis of the resampled signals of the multiple complete continuous ridge structures extracted from the time-frequency diagram to ensure the selection of the optimal target instantaneous frequency, thereby enhancing the robustness and accuracy of the instantaneous angular velocity estimation.

[0062] In an optional embodiment of the present invention, the above step 11 may include:

[0063] Step 111: collect the acceleration signal Perform Hilbert transform envelope calculations and use STFT (Short Time Fourier Transform) for TFR (Time-Frequency Representation) analysis, and record the amplitude and frequency corresponding to the local peak of the spectrum at each moment. This may include:

[0064] Step 1111: The acceleration signal is calculated using the following formula: Perform Hilbert envelope calculation:

[0065] ;

[0066] ;

[0067] in, Express Perform Hilbert transform, represents the envelope signal;

[0068] Step 1112: Envelope signal Calculate STFT and extract the local peak of the spectrum in TFR and its corresponding frequency ;here, Indicates the preset time period The moment A local peak in the spectrum.

[0069] ;

[0070] ;

[0071] in, represents the envelope signal, which represents the The low-frequency signal part of the signal is obtained by removing the interference of the high-frequency part, which can be obtained by step 1111; Indicates the Fourier basis for transforming the time domain signal into the frequency domain, j is the imaginary unit (i.e. ); Indicates time, the frequency is The time-frequency domain energy, represents the sliding window for calculating STFT; and Respectively expressed on the time-frequency plane, corresponding to The moment The local peak value and frequency of the spectrum.

[0072] In an optional embodiment of the present invention, the above step 12 may include:

[0073] Step 121, determining a first generation value between two first ridge points at any two adjacent moments in the first sub-period based on a preset cost function, a preset global optimal algorithm, and a local peak value of the spectrum corresponding to any moment in the first sub-period;

[0074] Step 122 : determining a plurality of first continuous ridge structures within a first sub-period according to the first generation value.

[0075] In this embodiment, IF (instantaneous frequency) extraction is achieved by tracking the local peak of the spectrum in TFR; to ensure the balanced amplitude and frequency continuity of the extracted first continuous ridge structure, the matching relationship between the two first ridge points at any two adjacent moments in the first sub-period is evaluated by a preset cost function, that is, the first generation value, which suppresses the discontinuous jump of the first ridge point while retaining the key frequency characteristics of the first ridge point, thereby achieving a balance between peak amplitude and IF continuity.

[0076] Here, to calculate the first generation value between two first ridge points at two adjacent moments, the first generation value is calculated in turn between any first ridge point at the current moment and each first ridge point corresponding to the moment before the current moment; further, according to the first generation value between any first ridge point at the current moment and each first ridge point corresponding to the moment before the current moment, the two first ridge points with the largest first generation value are connected; further, the current moment is taken as the previous moment, and the next moment after the current moment is taken as the current moment, and the first cost value of any first ridge point at the new round of the current moment and each first ridge point corresponding to the previous moment are judged and connected according to the same method as above, until all the first ridge points at all moments are traversed, and then multiple first continuous ridge line structures in the first sub-period are obtained.

[0077] In an optional embodiment of the present invention, the above step 121 may include:

[0078] Step 1211: Based on a preset cost function and a local peak value of the spectrum corresponding to the current moment in the first sub-period, determine a first local cost value between a first ridge point corresponding to the current moment in the first sub-period and a first ridge point corresponding to the previous moment in the first sub-period. Specifically, as shown in the following formula:

[0079] ;

[0080] in, is the amplitude term, which represents all the local peak values ​​of the spectrum extracted from TFR Normalize; N represents the number of time points in the entire time period, that is, m represents the number of time points for determining the first sub-period; Indicates a positive integer sign; Represents the time-frequency plane Moment The local peak corresponds to the frequency; express Time-frequency plane The local peak corresponds to the frequency; express The gradient mean of the frequency corresponding to the local peak in the time-frequency plane at the moment represents a reasonable frequency jump value; Indicates The number of local peaks in the time-frequency plane at time , different, The values ​​are also different; Indicates the first sub-period Moment Candidate ridge points and Moment The first jump penalty term of the candidate ridge point, whose denominator is the local peak value of the spectrum extracted from TFR The mean of the gradient corresponding to the frequency; express Moment The frequency corresponding to the candidate ridge points; express Moment The frequency corresponding to the candidate ridge points; Indicates the first sub-period Moment The first ridge point and Moment The first local cost value between the first ridge points.

[0081] Step 1212: Based on the first preset global optimal algorithm and the first local cost value, determine the first global cost value between the first ridge point corresponding to the current moment in the first sub-period and the first ridge point corresponding to the previous moment, and determine the first global cost value as the first cost value.

[0082] To ensure that the first ridge point confirmed at the current moment in the first sub-period achieves global optimization and avoids falling into a local optimal solution; here, based on the first preset global optimal algorithm and the first local cost value between the first ridge point corresponding to the current moment and the first ridge point corresponding to the previous moment, the first global cost value between the first ridge point corresponding to the current moment and the first ridge point corresponding to the previous moment can be determined, thereby ensuring the accuracy of the final determination of the target instantaneous frequency; here, the first preset global optimization algorithm is as follows:

[0083] ;

[0084] in, express Moment The ridge point cost of the first ridge point, express Moment First ridge point to Moment The first global cost of the first ridge point. Indicates that the first ridge point position of the previous moment is recorded according to the first global cost value, which is used to trace the first ridge point path of the previous moment; wherein, at the initial moment of the first sub-period, the initial condition is , .

[0085] In an optional embodiment of the present invention, the above step 13 may include:

[0086] Step 131: construct a dynamic time-frequency ridge window, and use the first ridge points in the first continuous ridge structure as initial ridge points in the dynamic time-frequency ridge window; the dynamic time-frequency ridge window corresponds to the first continuous ridge structure one-to-one;

[0087] Step 132: determining the predicted ridge point of each first continuous ridge line structure at the first moment in the second sub-period based on the initial ridge point in the dynamic time-frequency ridge line window and a preset prediction algorithm;

[0088] Step 133: Determine a target second ridge point within a dynamic bandwidth search range at the first moment for each first continuous ridge line structure based on the predicted ridge point at the first moment in the second sub-period and a second preset global optimal algorithm; the dynamic bandwidth search range is dynamically adjusted based on the predicted ridge point at the current moment in the second sub-period.

[0089] Step 134, updating the first continuous ridge line structure according to the target second ridge point, and updating the dynamic time-frequency ridge line window according to the updated first continuous ridge line structure;

[0090] Step 135: Based on the ridge points in the updated dynamic time-frequency ridge window and the prediction of the preset prediction algorithm, the above steps are repeated to determine the predicted ridge point and the target second ridge point at each moment in the second sub-period, and after determining the target second ridge point at each moment, the first continuous ridge line structure and the dynamic time-frequency ridge line window are updated until the target second ridge points at all moments in the second sub-period are determined, and the second continuous ridge line structure is determined based on the first continuous ridge line structure updated at the last moment;

[0091] In this embodiment, the predicted ridge point corresponding to the first moment in the second sub-period is the ridge point corresponding to the first moment in the second sub-period that can be connected to the first continuous ridge line structure (the predicted ridge point can be the ridge point corresponding to the local peak of the spectrum at that moment, or it can be any position between the ridge points corresponding to the local peak of the spectrum at that moment); here, the preset prediction algorithm can be a maximum estimated likelihood algorithm, which estimates the ridge point on the continuous ridge line structure in the preceding moment of the current moment in the second sub-period based on the maximum estimated likelihood algorithm to predict the predicted ridge point position corresponding to the current moment, so as to ensure the accuracy of the predicted ridge point at each moment in the second sub-period.

[0092] In this embodiment, a dynamic time-frequency ridge window is first constructed using multiple first ridge points in the first continuous ridge structure (each first continuous ridge structure corresponds to a dynamic time-frequency ridge window), and the predicted ridge point corresponding to the first moment in the second sub-period is determined based on the initial dynamic time-frequency ridge window and a preset prediction algorithm; here, a dynamic time-frequency ridge window is constructed using multiple first ridge points in the first continuous ridge structure as the initial dynamic time-frequency ridge window. After predicting the predicted ridge point corresponding to the first moment, the target second ridge point of the current first continuous ridge structure within the dynamic bandwidth search range can be determined based on the predicted ridge point, and the target second ridge point is connected to the first continuous ridge structure to achieve an update of the first continuous ridge structure;

[0093] Furthermore, after completing the update of the first continuous ridge structure, the initial dynamic time-frequency ridge window is updated; specifically: the initial dynamic time-frequency ridge window is slid over a preset time period with a target second ridge point determined in the second sub-period as a step size, thereby obtaining an updated dynamic time-frequency ridge window; it should be known that after each prediction of a predicted ridge point corresponding to a moment in the second sub-period and completing the first continuous ridge structure, the dynamic time-frequency ridge window is updated (the dynamic time-frequency ridge window is formed by the ridge point corresponding to the local peak of the spectrum in the preceding continuous moments of the current moment) to ensure the accuracy of subsequent predicted ridge points;

[0094] Furthermore, the predicted ridge point corresponding to the next moment of the first moment is predicted based on the continuous ridge points in the updated dynamic time-frequency ridge window, and then the target second ridge point of the next moment is determined based on the predicted ridge point of the next moment, and the first continuous ridge line structure and the dynamic time-frequency ridge line window are updated again. The above steps are repeated until the update of the first continuous ridge line structure by the target second ridge point at all moments in the second sub-period is completed, and then all moments in the preset period are traced back, and the updated multiple first continuous ridge line structures are determined as the second continuous ridge line structure in the preset period.

[0095] In an optional embodiment of the present invention, the above step 132 may include:

[0096] Step 1321: Determine the chirp rate of the first predicted ridge point in the second sub-period based on the ridge frequency vector of the first ridge point in the dynamic time-frequency ridge line window and a preset prediction algorithm;

[0097] Step 1322 : Determine the predicted ridge point corresponding to the first moment based on the chirp rate of the predicted ridge point at the first moment and the position of the first ridge point corresponding to the previous moment of the first moment.

[0098] Here, based on the ridge frequency vector of the first ridge point and a preset prediction algorithm, the chirp rate of the predicted ridge point at the first moment in the second sub-period is determined, and the predicted ridge point corresponding to the first moment is further determined. The specific implementation method is as follows:

[0099] ;

[0100] ;

[0101] ;

[0102] ;

[0103] Here, select , to ensure the rationality of the first-order approximation; Represents the ridge points of 5 consecutive moments contained in the dynamic time-frequency ridge window;

[0104] represents the design matrix in the preset prediction algorithm, represents the ridge frequency vector in the dynamic time-frequency ridge window, where represents the vector obtained by the prediction algorithm, represents the initial frequency of the prediction algorithm in the process of fitting the ridge frequency vector, represents the chirp rate, Represented by the ridge frequency vector Predicted ridge positions.

[0105] To minimize noise interference, the second ridge point in the second sub-period is typically tracked within a narrowband. An excessively large bandwidth search range may introduce additional interference, while an excessively small bandwidth search range may miss the second ridge point. Therefore, in the present invention, a dynamic bandwidth search range can be determined based on the TFR peak amplitude characteristics, ensuring that the search range is small enough to reduce interference while avoiding missing the target second ridge point.

[0106] The dynamic bandwidth search range corresponds to the predicted ridge point at the current moment. Here, the dynamic bandwidth search range corresponding to the moment can be determined based on the predicted ridge point corresponding to the current moment in the second sub-period and the amplitude corresponding to the predicted ridge point at the moment.

[0107] In this embodiment, based on the predicted ridge point corresponding to the current moment in the second sub-period and the amplitude corresponding to the predicted ridge point at that moment, the dynamic bandwidth search range corresponding to that moment is adaptively adjusted to avoid missing the target ridge while ensuring that the search range is small enough to reduce interference. The specific process is as follows:

[0108] ;

[0109] ;

[0110] here, represents the frequency of predicted ridge points, To predict the TFR amplitude corresponding to the ridge point; represents the ridge frequency between the predicted ridge point and the search edge, and Represent the upper and lower boundary ridge point indexes of the dynamic bandwidth search range respectively; Represents the energy of the i-th local peak in the time-frequency plane at time instant; express The energy of the u-th local peak in the time-frequency plane at time instant, and it also represents the energy of the ridge point on the search edge; express The energy of the lth local peak in the time-frequency plane at time t, and it also represents the ridge energy of the search lower edge.

[0111] Further, based on and Forming dynamic bandwidth search range ; It should be noted that the search ranges for different consecutive ridges may be the same.

[0112] In an optional embodiment of the present invention, the above step 133 may further include:

[0113] Step 1331 , based on a second preset global optimal algorithm, determining a second generation value between the predicted ridge point and each second ridge point within the dynamic bandwidth search range at the first moment;

[0114] Specifically, it may include:

[0115] Step 13311: Determine a second transition penalty term between a second ridge point within the dynamic bandwidth search range and the predicted ridge point at the first moment in the second sub-period based on the local peak value of the spectrum at the first moment in the second sub-period;

[0116] Step 13312, based on the second jump penalty term, the second preset global optimal algorithm and the local peak value of the spectrum corresponding to the first moment in the second sub-period, determine the second generation value between the predicted ridge point and each second ridge point within the dynamic bandwidth search range at the first moment.

[0117] Here, the second jump penalty term between the second ridge point and the predicted ridge point within the dynamic bandwidth search range at the first moment can be expressed as follows:

[0118] ;

[0119] in, ; M represents The number of local peaks in the time-frequency plane at time .

[0120] In this embodiment, the second preset global optimization algorithm is the same as the first preset global optimization algorithm, and the two differ only in the specific expression of the jump penalty term; it should be noted that the second jump penalty term between the predicted ridge point and the second ridge point at other times in the second sub-period is calculated using the above formula;

[0121] After determining the second jump penalty term, determining a second local cost value between the predicted ridge point at the first moment in the second sub-period and each second ridge point at the first moment within the dynamic bandwidth search range based on the second jump penalty term, a preset cost function, and a local peak value of the spectrum corresponding to the first moment in the second sub-period;

[0122] Furthermore, based on the second preset global optimal algorithm and the second local cost value, the second global cost value between the predicted ridge point at the first moment in the second sub-period and each second ridge point within the dynamic bandwidth search range of the first moment is determined, and the second global cost value is determined as the second generation value; here, it should be known that the second generation values ​​between the predicted ridge point at other moments in the second sub-period and the second ridge point within its dynamic search range can all be obtained through the above process.

[0123] Furthermore, the above step 133 may further include:

[0124] Step 1332: Determine the target second ridge point of each first continuous ridge structure within the dynamic bandwidth search range at the first moment based on the second generation value.

[0125] Here, the second ridge point at the first moment corresponding to the maximum cost value is determined as the target second ridge point, and the target second ridge point is connected to the corresponding first continuous ridge line structure to update the first continuous ridge line structure, thereby obtaining multiple second continuous ridge line structures within a preset time period.

[0126] In an optional embodiment of the present invention, the above step 14 may include:

[0127] Step 141 , screening multiple second continuous ridge structures based on a frequency domain sparsity evaluation index to determine a target instantaneous frequency;

[0128] Step 142 : determining the target instantaneous angular velocity according to the target instantaneous frequency and the order information of the target instantaneous frequency and the instantaneous angular velocity.

[0129] In this embodiment, a complete continuous ridge line structure within a preset time period is formed based on the first continuous ridge line structure and the second continuous ridge line structure, and the ridge point index corresponding to the maximum cost at the last moment of the preset time period is selected. The entire time period path can be backtracked to achieve the purpose of extracting multiple candidate instantaneous frequencies; the specific expression is as follows:

[0130] ;

[0131] ;

[0132] in, Represents the ridge point index of the first candidate instantaneous frequency extracted; Indicates The first candidate instantaneous frequency is recorded at The ridge index at the moment is equivalent to , use the ridge point index to estimate the corresponding first candidate instantaneous frequency :

[0133] ;

[0134] in, Indicates Time-frequency plane The frequency value corresponding to the local peak, similarly, Indicates Time-frequency plane The frequency value corresponding to the local peak, It constitutes a complete instantaneous frequency curve.

[0135] Furthermore, selecting high-order harmonics helps reduce the estimation error of the instantaneous angular velocity. Based on the maximum cost, high-order harmonics are found for IAS estimation, and the path index at the final moment is defined as:

[0136] ;

[0137] Furthermore, it is possible to obtain , that is, multiple candidate instantaneous frequencies can be obtained; in order to select the optimal target instantaneous frequency for instantaneous angular velocity estimation, the frequency domain sparsity evaluation index is introduced here:

[0138] ;

[0139] in, It is represented as the spectrum of the acceleration signal resampled at equal intervals of candidate instantaneous frequency and phase; here, The smaller the norm, the sparser the frequency domain, which means that the current instantaneous frequency is more consistent with the estimation requirements of the instantaneous angular velocity; finally, the minimum The corresponding instantaneous frequency estimates the instantaneous angular velocity; i ranges from 1 to N / 2, N represents the number of data points of the acceleration signal, and F is the frequency domain signal of the acceleration signal (that is, the time domain signal is converted into a frequency signal), and its data length (number of points) is half of the acceleration signal.

[0140] Here, the order information K of the instantaneous frequency IF and the instantaneous angular velocity IAS is obtained by resampling the frequency spectrum of the acceleration signal at equal phase intervals of the optimal target instantaneous frequency IF. Preferably, the target instantaneous angular velocity is determined based on the target instantaneous frequency and the order information of the target instantaneous frequency and the instantaneous angular velocity, which can be expressed by the following formula:

[0141] ;

[0142] here, represents the instantaneous angular velocity of the target; Indicates the target instantaneous frequency.

[0143] The method of the above embodiment is described below using a specific numerical simulation example:

[0144] like Figure 2 The figure shows the time-frequency diagram TFR of the numerical simulation signal with signal-to-noise ratios of -4dB, -7dB, and -10dB respectively. The specific implementation method of the simulation signal is as follows:

[0145] ;

[0146] In this example, the relevant parameters are set as follows:

[0147] is the amplitude modulation parameter, set to 0.5, is the rotation frequency of the shaft, see Figure 3 Encoder acquisition status, is the structural damping coefficient, set to 1000, Indicates the The time when the fault vibration occurs, is the resonant frequency of the rolling bearing, which is 3000Hz, is a unit step function, describes the random slip effect of the rolling element, which is equivalent to 0.01 times the time to failure, and is Gaussian white noise; the sampling frequency of the rolling bearing simulation signal is set to 12000 Hz, and the order relationship between the fault IF and IAS is set to 5.

[0148] The target instantaneous angular velocity obtained by the method of the above embodiment is as follows: Figure 3 The comparison of the root mean square error of different methods under different signal-to-noise ratio conditions is shown in Table 1 below.

[0149] Table 1. Comparison of the root mean square error of target instantaneous frequency extracted by various methods under wide range of speed changes and different signal-to-noise ratio conditions.

[0150]

[0151] As can be seen from the results in Table 1, the present invention exhibits superior extraction performance regardless of high or low signal-to-noise ratio environments. Under high signal-to-noise ratio conditions, the present invention effectively improves the accuracy of target instantaneous angular velocity estimation by introducing high-order harmonics, showing higher accuracy compared to other technologies. Under low signal-to-noise ratio conditions, the present invention also maintains stable performance, can effectively suppress noise interference, and achieve effective separation of the instantaneous frequency component of the real target from the noise component, further highlighting its excellent noise resistance. Compared with the prior art, the present invention obtains smaller estimation errors and higher extraction accuracy at different noise levels, fully verifying its practical value in non-stationary signal analysis.

[0152] like Figure 4 As shown, an embodiment of the present invention further provides a device 40 for determining the instantaneous angular velocity of a rotating machine, comprising:

[0153] An acquisition module 41 is used to acquire a time-frequency diagram corresponding to an acceleration signal of a rotating machine within a preset time period;

[0154] Processing module 42 is used for processing module, which is used to determine multiple first continuous ridge structures in the first sub-period according to the local peak of the spectrum corresponding to any moment in the first sub-period of the time-frequency graph; each of the multiple first continuous ridge structures includes multiple first ridge points, and the first ridge point corresponds one-to-one to the local peak of the spectrum at any moment in the first sub-period; based on the preset global optimization algorithm and the second ridge point of the time-frequency graph in the second sub-period, the multiple first continuous ridge structures are updated to determine multiple second continuous ridge structures of the time-frequency graph in the preset period; the second ridge point corresponds one-to-one to the local peak of the spectrum at any moment in the second sub-period; the second sub-period and the first sub-period both contain multiple continuous moments, and the first moment in the second sub-period is the subsequent moment of the last moment in the first sub-period; according to the preset frequency domain sparsity evaluation index and the multiple second continuous ridge structures, the target instantaneous frequency in the preset period is determined, and the target instantaneous angular velocity is determined according to the target instantaneous frequency.

[0155] It should be noted that this device is a device corresponding to the above-mentioned method for determining the instantaneous angular velocity of a rotating machine. All implementation methods in the above-mentioned method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0156] like Figure 4 As shown, an embodiment of the present invention further provides an electronic device 50, comprising: a memory 51 for storing one or more computer programs; one or more processors 52 for executing one or more computer programs, wherein when the computer programs are executed by the processors, the method for determining the instantaneous angular velocity of the rotating machinery as described above is executed. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects. The electronic device 50 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown in the present invention, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required in the present invention.

[0157] like Figure 5As shown, electronic device 50 is a computing device or computer system that may include a CPU 501 (computing unit) that can perform various appropriate actions and processes based on a computer program stored in a ROM 502 (read-only memory) or a computer program loaded from a storage unit 508 into a random access RAM 503 (memory). RAM 503 may also store various programs and data required for the operation of device 500. CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An I / O interface 505 (input / output interface) is also connected to bus 504.

[0158] Multiple components in the electronic device 500 are connected to the I / O interface 505, including an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a magnetic disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0159] The CPU 501 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the CPU 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The CPU 501 performs the various methods and processes described above. For example, in some embodiments, the method 10 for determining the instantaneous angular velocity of a rotating machine can be implemented as a computer software program tangibly embodied in a computer-readable storage medium, such as the storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the CPU 501, one or more steps of the method 10 for synchronous data sensing based on edge multi-point collaboration described above can be performed. Alternatively, in other embodiments, the CPU 501 may be configured to execute the method for determining the instantaneous angular velocity of a rotating machine in any other appropriate manner (eg, by means of firmware).

[0160] An embodiment of the present invention further provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to execute the method 10 for determining the instantaneous angular velocity of a rotating machine as described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0161] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0162] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0163] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0164] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0165] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0166] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the existing technology, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, ROM, RAM, disk or optical disk, etc. Various media that can store program code.

[0167] In addition, it should be pointed out that in the apparatus and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present invention. Moreover, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but they do not necessarily need to be performed in chronological order, and some steps can be performed in parallel or independently of each other. For those of ordinary skill in the art, it can be understood that all or any steps or components of the method and apparatus of the present invention can be implemented in hardware, firmware, software or a combination thereof in any computing device (including a processor, storage medium, etc.) or a network of computing devices. This can be achieved by those of ordinary skill in the art using their basic programming skills after reading the description of the present invention.

[0168] Therefore, the purpose of the present invention can also be achieved by running a program or a group of programs on any computing device. The computing device can be a well-known general-purpose device. Therefore, the purpose of the present invention can also be achieved simply by providing a program product containing program code for implementing the method or device. That is to say, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any well-known storage medium or any storage medium developed in the future. It should also be pointed out that in the device and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. In addition, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but do not necessarily need to be performed in chronological order. Certain steps can be performed in parallel or independently of each other.

[0169] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for determining the instantaneous angular velocity of a rotating machine, characterized in that: include: Obtaining a time-frequency diagram corresponding to an acceleration signal of the rotating machinery within a preset time period; Determining, based on a local peak value of the spectrum corresponding to any moment in the first sub-period, the time-frequency graph, a plurality of first continuous ridge line structures within the first sub-period; each of the plurality of first continuous ridge line structures includes a plurality of first ridge points, and the first ridge points correspond one-to-one to a local peak value of the spectrum at any moment in the first sub-period; Based on a preset global optimization algorithm and a second ridge point of the time-frequency graph in a second sub-period, updating the plurality of first continuous ridge line structures to determine a plurality of second continuous ridge line structures of the time-frequency graph in a preset period; the second ridge point corresponds one-to-one to a local peak of the spectrum at any moment in the second sub-period; the plurality of consecutive moments are both included in the second sub-period and the first sub-period, and the first moment in the second sub-period is a moment subsequent to the last moment in the first sub-period; The target instantaneous frequency within the preset time period is determined according to the preset frequency domain sparsity evaluation index and the plurality of second continuous ridge structures, and the target instantaneous angular velocity is determined according to the target instantaneous frequency.

2. The method for determining the instantaneous angular velocity of a rotating machine according to claim 1, wherein: Determining a plurality of first continuous ridge structures within the first sub-period according to a local peak value of a spectrum corresponding to any moment within the first sub-period of the time-frequency graph includes: Determining a first generation value between a first ridge point corresponding to the current moment in the first sub-period and a first ridge point corresponding to a moment before the current moment in the first sub-period based on a preset cost function, a preset global optimal algorithm, and a local peak value of the spectrum corresponding to the current moment in the first sub-period; A plurality of first continuous ridge structures within the first sub-period is determined according to the first generation value.

3. The method for determining the instantaneous angular velocity of a rotating machine according to claim 2, wherein: Determining a first generation value between a first ridge point corresponding to the current moment in the first sub-period and a first ridge point corresponding to a moment before the current moment in the first sub-period based on a preset cost function, a preset global optimal algorithm, and a local peak value of a spectrum corresponding to the current moment in the first sub-period includes: Determining a first local cost value between a first ridge point corresponding to the current moment and a first ridge point corresponding to the previous moment in the first sub-period based on the preset cost function and a local peak value of the spectrum corresponding to the current moment in the first sub-period; Based on the first preset global optimal algorithm and the first local cost value, determine the first global cost value between the first ridge point corresponding to the current moment in the first sub-period and the first ridge point corresponding to the previous moment of the current moment, and determine the first global cost value as the first cost value.

4. The method for determining the instantaneous angular velocity of a rotating machine according to claim 1, wherein: Based on a preset global optimization algorithm and a second ridge point of the time-frequency graph in a second sub-period, updating the plurality of first continuous ridge line structures to determine a plurality of second continuous ridge line structures of the time-frequency graph in a preset period, comprising: Constructing a dynamic time-frequency ridge line window, and using the plurality of first ridge points in the first continuous ridge line structure as initial ridge points in the dynamic time-frequency ridge line window; wherein the dynamic time-frequency ridge line window corresponds to the first continuous ridge line structure in a one-to-one manner; Determine the predicted ridge point of each of the first continuous ridge lines at the first moment in the second sub-period according to the initial ridge point in the dynamic time-frequency ridge line window and a preset prediction algorithm; Determining, based on the predicted ridge point of each of the first continuous ridge line structures at the first moment in the second sub-period and a second preset global optimal algorithm, a target second ridge point within a dynamic bandwidth search range for each of the first continuous ridge line structures at the first moment; the dynamic bandwidth search range is dynamically adjusted based on the predicted ridge point at the current moment in the second sub-period; updating the first continuous ridge line structure according to the target second ridge point, and updating the dynamic time-frequency ridge line window according to the updated first continuous ridge line structure; According to the ridge points in the updated dynamic time-frequency ridge window and the prediction of the preset prediction algorithm, the above steps are repeated to determine the predicted ridge points and the target second ridge points at each moment in the second sub-period, and after determining the target second ridge points at each moment, the first continuous ridge line structure and the dynamic time-frequency ridge line window are updated until the target second ridge points at all moments in the second sub-period are determined, and the first continuous ridge line structure updated at the last moment is determined to determine the second continuous ridge line structure.

5. The method for determining the instantaneous angular velocity of a rotating machine according to claim 4, wherein: Determining the predicted ridge point of the first moment of each of the first continuous ridge line structures in the second sub-period according to the initial ridge point in the dynamic time-frequency ridge line window and a preset prediction algorithm includes: Determining the chirp rate of the first predicted ridge point in the second sub-period according to the ridge frequency vector of the first ridge point in the dynamic time-frequency ridge line window and the preset prediction algorithm; Based on the chirp rate of the predicted ridge point at the first moment and the first ridge point corresponding to the moment before the first moment, the predicted ridge point at the first moment of each first continuous ridge line structure in the second sub-period is determined.

6. The method for determining the instantaneous angular velocity of a rotating machine according to claim 4, wherein: Determining a target second ridge point of each of the first continuous ridge line structures within a dynamic bandwidth search range at the first moment in the second sub-period based on the predicted ridge point of each of the first continuous ridge line structures at the first moment in the second sub-period and a second preset global optimal algorithm, including: Determining, based on the second preset global optimal algorithm, a second generation value between the predicted ridge point and each second ridge point within the dynamic bandwidth search range at the first moment; According to the second generation value, a target second ridge point of each of the first continuous ridge line structures is determined within the dynamic bandwidth search range at the first moment.

7. The method for determining the instantaneous angular velocity of a rotating machine according to claim 6, wherein: Determining, based on the second preset global optimal algorithm, a second generation value between the predicted ridge point and each second ridge point within the dynamic bandwidth search range at the first moment, comprising: Determining a second jump penalty term between a second ridge point and the predicted ridge point within the dynamic bandwidth search range at the first moment in the second sub-period based on the local peak hospital of the spectrum at the first moment in the second sub-period; According to the second jump penalty item, the second preset global optimal algorithm and the local peak value of the spectrum corresponding to the first moment in the second sub-time period, the second generation value between the predicted ridge point and each second ridge point within the dynamic bandwidth search range at the first moment is determined.

8. The method for determining the instantaneous angular velocity of a rotating machine according to claim 1, wherein: Determining a target instantaneous frequency within the preset time period according to a preset frequency domain sparsity evaluation index and a plurality of the second continuous ridge structures, and determining a target instantaneous angular velocity according to the target instantaneous frequency, including: Screening the plurality of second continuous ridge structures based on the frequency domain sparsity evaluation index to determine the target instantaneous frequency; The target instantaneous angular velocity is determined according to the target instantaneous frequency and order information of the target instantaneous frequency and the instantaneous angular velocity.

9. A device for determining the instantaneous angular velocity of a rotating machine, characterized in that: include: An acquisition module, configured to acquire a time-frequency diagram corresponding to an acceleration signal of the rotating machinery within a preset time period; A processing module is used to determine multiple first continuous ridge structures within the first sub-period based on the local peak of the spectrum corresponding to any moment in the first sub-period of the time-frequency graph; each of the multiple first continuous ridge structures includes multiple first ridge points, and the first ridge points correspond one-to-one with the local peak of the spectrum at any moment in the first sub-period; based on a preset global optimization algorithm and the second ridge point of the time-frequency graph in the second sub-period, the multiple first continuous ridge structures are updated to determine multiple second continuous ridge structures of the time-frequency graph within the preset period; the second ridge point corresponds one-to-one with the local peak of the spectrum at any moment in the second sub-period; the second sub-period and the first sub-period both contain multiple continuous moments, and the first moment in the second sub-period is the subsequent moment of the last moment in the first sub-period; according to a preset frequency domain sparsity evaluation index and the multiple second continuous ridge structures, a target instantaneous frequency within the preset period is determined, and a target instantaneous angular velocity is determined based on the target instantaneous frequency.

10. A computing device, characterized in that include: a memory for storing one or more programs; One or more processors, configured to execute the one or more programs to implement the method according to any one of claims 1 to 8.

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