Frequency identification method, device, computer equipment and computer readable storage medium

Abstract

The embodiments of the present application disclose a frequency identification method, apparatus, computer equipment and computer-readable storage medium, which obtain a target vibration signal sequence of a device; perform autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence; divide the correlation sequence to obtain at least two sub-correlation sequences; perform self-difference analysis on the sub-correlation sequences within a preset time-shift information range to obtain self-difference of the sub-correlation sequences; determine the target time-shift information within the preset time-shift information range based on the self-difference; and determine the vibration frequency of the device based on the target time-shift information, thereby accurately extracting the vibration frequency of the device from the target vibration signal sequence.

Description

Technical Field

[0001] The present application relates to the field of signal processing, and in particular to a frequency identification method, device, computer equipment and computer-readable storage medium. Background Art

[0002] The vibration frequency of a device can be used as an important indicator to detect whether the device is operating normally. Therefore, it is very important to accurately identify the vibration frequency of the device in the vibration signal of the device. Summary of the invention

[0003] The embodiments of the present application provide a frequency identification method, apparatus, computer device, and computer-readable storage medium, which can accurately identify the vibration frequency of a device from a target vibration signal sequence of the device.

[0004] A frequency identification method provided in an embodiment of the present application includes:

[0005] Acquire a target vibration signal sequence of the device;

[0006] Performing autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence;

[0007] Dividing the correlation sequence to obtain at least two sub-correlation sequences;

[0008] Performing self-difference analysis on the sub-correlation sequence within a preset time shift information range to obtain self-difference of the sub-correlation sequence;

[0009] Determining target time shift information within the preset time shift information range according to the self-difference;

[0010] The vibration frequency of the device is determined according to the target time-shift information.

[0011] Accordingly, an embodiment of the present application further provides a frequency identification device, including:

[0012] A signal acquisition unit, used to acquire a target vibration signal sequence of the device;

[0013] A correlation analysis unit, used for performing autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence;

[0014] A division unit, used for performing division processing on the correlation sequence to obtain at least two sub-correlation sequences;

[0015] A difference analysis unit, used for performing self-difference analysis on the sub-correlation sequence within a preset time shift information range to obtain the self-difference of the sub-correlation sequence;

[0016] An information determining unit, configured to determine target time shift information within the preset time shift information range according to the self-difference;

[0017] A frequency determination unit is used to determine the vibration frequency of the device according to the target time shift information.

[0018] Correspondingly, an embodiment of the present application also provides a computer device, including a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute any frequency identification method provided in the embodiment of the present application.

[0019] Accordingly, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and the computer program is loaded by a processor to execute any frequency identification method provided in the embodiment of the present application.

[0020] The embodiment of the present application obtains a target vibration signal sequence of the device; performs autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence; divides the correlation sequence to obtain at least two sub-correlation sequences; performs self-difference analysis on the sub-correlation sequences within a preset time-shift information range to obtain self-difference of the sub-correlation sequences; determines the target time-shift information within the preset time-shift information range based on the self-difference; and determines the vibration frequency of the device based on the target time-shift information, thereby achieving accurate extraction of the vibration frequency of the device from the target vibration signal sequence.

[0021] In the embodiment of the present application, the degree of autocorrelation of the target vibration signal sequence at different time steps can be determined through autocorrelation analysis, and the degree of difference of the sub-correlation degree of the target vibration signal at different time steps can be determined through self-difference analysis, and then the periodic frequency in the signal sequence can be determined. In the process of frequency recognition, the characteristics of the target vibration signal sequence will not be lost, and signals with different periodic fluctuations can be processed, and the recognition accuracy of the vibration frequency is high. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 is a flow chart of a frequency identification method provided in an embodiment of the present application;

[0024] Figure 2is a schematic diagram of a vibration signal sequence provided in an embodiment of the present application;

[0025] Figure 3 is a spectrum diagram provided by an embodiment of the present application;

[0026] Figure 4 It is the envelope spectrum provided in the embodiment of the present application;

[0027] Figure 5 is a signal schematic diagram provided in an embodiment of the present application;

[0028] Figure 6 Another signal diagram provided in the embodiment of the present application is

[0029] Figure 7 is a flow chart for determining vibration frequency provided in an embodiment of the present application;

[0030] Figure 8 is a schematic diagram of a frequency identification device provided in an embodiment of the present application;

[0031] Fig. 9 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0033] The embodiments of the present application provide a frequency identification method, device, computer equipment and computer readable storage medium. The frequency identification device can be integrated in a computer equipment, which can be a server or a terminal.

[0034] The terminal may include a mobile phone, a wearable smart device, a tablet computer, a laptop computer, a personal computer (PC), and a vehicle-mounted computer.

[0035] Among them, the server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, as well as big data and artificial intelligence platforms.

[0036] It should be noted that the description order of the following embodiments is not intended to limit the preferred order of the embodiments.

[0037] This embodiment will be described from the perspective of a frequency identification device. The frequency identification device may be integrated into a computer device, which may be a server or a terminal.

[0038] The present application provides a frequency identification method, such as Figure 1 As shown, the specific process of the frequency identification method can be as follows:

[0039] 101. Obtain a target vibration signal sequence of the device.

[0040] The equipment may include a device that can perform a specified function, for example, a generator, a steam turbine, an aircraft engine, a water pump, a ventilator, etc.

[0041] The target vibration signal sequence may include multiple data points collected by the sensor during the operation of the device. The target vibration signal sequence may also be a signal sequence obtained by preprocessing the data points collected by the sensor. That is, in one embodiment, the step of "obtaining the target vibration signal sequence of the device" may include:

[0042] Obtaining an initial vibration signal sequence of the device;

[0043] Performing filtering on the initial vibration signal sequence to obtain a filtered vibration signal sequence;

[0044] The filtered vibration signal sequence is amplified to obtain a target vibration signal sequence.

[0045] Among them, the initial vibration signal sequence may include multiple data points collected by the sensor during the operation of the equipment, filtering the initial vibration signal sequence according to the frequency range corresponding to the vibration signal to obtain a filtered vibration signal sequence, and amplifying the filtered vibration signal sequence for subsequent signal analysis to obtain a target vibration signal sequence. It can be understood that the order of filtering and amplification can be flexibly adjusted as needed, and is not limited here.

[0046] Among them, the signal amplification processing of the filtered vibration signal sequence can include power processing, linear amplification processing, logarithmic amplification processing, etc. The power processing can also include even power processing and odd power processing. Through signal amplification processing, possible pulse signals can be enhanced and the accuracy of the vibration frequency extraction equipment can be improved.

[0047] For example, the initial vibration signal sequence of a mechanical device can be as follows: Figure 2As shown in Figure 1, the frequency of the initial vibration signal sequence can be determined by performing spectrum analysis or envelope analysis after Fourier transform, but this method is difficult to extract quantitative eigenvalues. Figure 2 The initial vibration signal sequence shown in the figure is divided into the Fourier transform, and the following can be obtained: Figure 3 The spectrum diagram shown is Figure 3 It can be seen that the obvious features are in the range of 2000Hz to 2500Hz, which shows that the periodic fault features are not directly extracted and there are high-intensity interference signals.

[0048] and Figure 4 for Figure 2 The initial vibration signal sequence shown is first subjected to envelope analysis to obtain the envelope line, and then the envelope spectrum is obtained by fast Fourier transform. In the final envelope spectrum, periodic characteristic frequencies can be found, but due to the low resolution of the spectrum line, there is a certain error between the identification result 293.7 Hz and the true result 295.6 Hz.

[0049] 102. Perform autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence.

[0050] The target vibration signal sequence is subjected to autocorrelation analysis to determine the correlation between the values ​​of the target vibration signal sequence at different times. For example, the target vibration signal sequence is , is the target vibration signal sequence data points, time-shifted After that, the data points in the target vibration signal sequence , in the time-shifted vibration signal sequence, Data points with overlapping positions, and data points in the target vibration signal sequence Same, time-shifted The correlation of the target vibration signal sequence can be , since there are n data points in the target vibration signal sequence, The value range of can be [1, n-1]. According to the correlation corresponding to each time-shift information within the value range, the correlation sequence of the target vibration signal sequence can be obtained.

[0051] The autocorrelation analysis of the target vibration signal sequence can be considered as controlling the target vibration signal sequence to move based on the time shift information, obtaining the moved vibration signal sequence, and then determining the correlation between the overlapping parts of the target vibration signal sequence and the moved vibration signal sequence. The time shift information can indicate the distance the target vibration signal sequence moves. Assuming that the target vibration signal sequence has n data points, the time shift information τ The value range of can be 1 to n-1. =1 can indicate that the target vibration signal sequence moves backward by a distance of one data point. At this time, the target vibration signal sequence and the vibration signal sequence after the movement are offset by one data point.

[0052] The target vibration signal sequence can be time-shifted within the range of [1, n-1] to obtain a shifted vibration signal sequence corresponding to each time-shift information within the range of [1, n-1].

[0053] For each moved vibration signal sequence, the data points overlapping every two positions in the overlapping part of the target vibration signal sequence and the moved vibration signal sequence are multiplied and added to obtain the correlation between the target vibration signal sequence and the moved vibration signal sequence. According to the correlation between each moved vibration signal sequence and the target vibration signal sequence, a correlation sequence is obtained.

[0054] Optionally, if the target vibration signal sequence is subjected to signal amplification processing, the target vibration signal sequence may have a large drift trend. After obtaining the correlation sequence, the correlation in the correlation sequence may be smoothed to remove the drift trend, and the autocorrelation of the target vibration signal sequence under different time shift information may be measured by the same standard. That is, in one embodiment, after the step of "performing autocorrelation analysis on the target vibration signal sequence to obtain the correlation sequence of the target vibration signal sequence", the frequency extraction method provided in the embodiment of the present application may further include:

[0055] Controlling the preset window to slide in the correlation sequence, and generating a mean sequence according to the means of multiple correlations in the preset window;

[0056] The correlation sequence is smoothed according to the mean sequence to obtain the processed correlation sequence.

[0057] The preset window size may refer to the data length corresponding to the preset window. For example, the preset window size may be 3. Then, based on the preset window, 3 data points may be determined from the correlation sequence each time.

[0058] The initial starting position of the preset window can be located at the first data point in the correlation sequence, and the mean of multiple correlations (two or more) in the preset window is calculated. Then the preset window is controlled to slide backward continuously, and the mean of the correlations in the preset window after each sliding is calculated. Based on these means, the mean sequence can be obtained. .

[0059] The correlation sequence is smoothed by the mean sequence. For example, the correlation sequence and the mean sequence can be subtracted bit by bit to obtain the processed correlation sequence. , where A is the correlation sequence and M is the correlation sequence.

[0060] Optionally, a mean sequence can also be generated by cumulative moving average, specifically by merging the mean calculated in the current window with the calculation result of the previous window to obtain the calculation result of the current window, which can be weighted summation. For example, the weight of the mean calculated in the current window is 0.5, and the weight of the calculation result of the previous window is also 0.5, and so on, to obtain a mean sequence.

[0061] For example, by Figure 2 The target vibration signal obtained by quadratically processing the initial vibration signal sequence shown in FIG. 1 can be represented by the following correlation sequence: Figure 5 As shown in the first figure from top to bottom in the figure, the processed correlation sequence can be Figure 5 As shown in the second picture from top to bottom.

[0062] Through Figure 2 The target vibration signal obtained by performing cubic processing on the initial vibration signal sequence shown in FIG. 1 can be represented by the corresponding correlation sequence as follows: Figure 6 As shown in the first figure from top to bottom in the figure, the processed correlation sequence can be Figure 6 As shown in the second picture from top to bottom. Figure 5 and Figure 6 It can be seen that the periodic characteristics of the processed correlation sequence are very obvious.

[0063] Based on Figure 5 The target frequency of the processed correlation sequence output shown is 295.4 Hz, based on Figure 6 The target frequency of the processed correlation sequence output shown is 296.2 Hz, which is very close to the true value of 295.6 Hz.

[0064] 103. Divide the correlation sequence to obtain at least two sub-correlation sequences.

[0065] For example, the correlation sequence may be divided to obtain multiple sub-correlation sequences.

[0066] Optionally, after step 102, the correlation sequence may be smoothed to obtain a processed correlation sequence, and step 103 may be to divide the correlation sequence, specifically to divide the processed correlation sequence to obtain at least two sub-correlation sequences.

[0067] The correlation sequence is divided to obtain at least two sub-correlation sequences, including:

[0068] The processed correlation sequence is divided to obtain a plurality of sub-correlation sequences.

[0069] It can also be considered that the processed correlation sequence is divided into frames to obtain multiple frames of correlation data, and the data length of each frame is the same.

[0070] 104. Perform self-difference analysis on the sub-correlation sequence within a preset time shift information range to obtain the self-difference of the sub-correlation sequence.

[0071] The time-shift information range can be determined according to the number of data points in the correlation sequence. For example, if there are n data points in the correlation sequence, the time-shift information range can be [1, n-1].

[0072] The self-difference of the sub-correlation sequence under each time shift information within the preset time shift information range can be determined, and then the target time shift information is determined according to the self-difference of the sub-correlation sequence under each time shift information. The self-difference of the sub-correlation sequence can also be determined one by one within the preset time shift information range, that is, the step of "performing self-difference analysis on the sub-correlation sequence within the preset time shift information range to obtain the self-difference of the sub-correlation sequence" includes:

[0073] Determine the current time shift information within the preset time shift information range;

[0074] Under the current time shift information, for the first correlation in the sub-correlation sequence, calculate the first correlation and the first error of the correlation whose distance satisfies the time shift information;

[0075] For a second correlation in the sequence of sub-correlations, determining a second error based on the second correlation;

[0076] The self-difference of the sub-correlation sequence under the current time shift information is determined according to the first error and the second error.

[0077] For example, starting from the first time shift information in the time shift information range, the self-difference of each sub-correlation sequence under the time shift information can be calculated.

[0078] The correlation in the sub-correlation sequence can be divided into a first correlation and a second correlation. The first correlation is that in the sub-correlation sequence, there is a correlation whose distance satisfies the current time shift information. The second correlation is that in the sub-correlation sequence, there is no correlation whose distance satisfies the current time shift information.

[0079] If the sub-correlation sequence is controlled to move backward based on the current time-shift information to obtain the sub-correlation sequence after moving, the first correlation in the sub-correlation sequence may be a correlation overlapping with the sub-correlation sequence after moving, and the second correlation may be a correlation in the sub-correlation sequence that does not overlap with the sub-correlation sequence after moving.

[0080] Assume that the correlation sequence is divided into multiple wThe sub-correlation sequence of data points, for the j sub-correlation sequence, for time-shifted information i , No. j The first k The position of the data point in the correlation sequence is , if we move the correlation sequence backward i data points, assuming that in the correlation sequence after the shift, and the data points of the correlation sequence Overlapping data point A, then data point A and the data point of the correlation sequence Based on this, for the correlation sequence , the data points that overlap with their positions in the moved correlation sequence correspond to the data points in the correlation sequence .

[0081] For j A sequence of sub-correlations, the first correlation can be j In the sub-correlation sequence The first correlation can be j In the sub-correlation sequence If , ;like , , for each data point in the autocorrelation sequence, the corresponding .

[0082] exist i Time-shift information j The self-difference of the sub-correlation sequence is: ,in, Indicates the time shift information i for the 1st to i-th Sum.

[0083] 105. Determine target time shift information within a preset time shift information range according to the self-differentiation.

[0084] For example, the time shift information corresponding to the self-difference being less than a preset threshold value may be determined as the target vibration signal sequence time shift information.

[0085] In one embodiment, if the self-difference of the sub-correlation sequence is determined one by one within the preset time shift information range until the target time shift information is determined, the step of “determining the target time shift information within the preset time shift information range according to the self-difference” includes:

[0086] If the self-difference of the sub-correlation sequence is less than a preset threshold under the current time-shift information, the current time-shift information is used as the target time-shift information;

[0087] If the self-difference of the sub-correlation sequence is not less than a preset threshold under the current time-shift information, the current time-shift information is updated;

[0088] Return to the step of calculating, for the first correlation in the sub-correlation sequence under the current time shift information, a first error of the first correlation and a correlation whose distance therefrom satisfies the time shift information.

[0089] If under the current time-shift information, the self-difference of the sub-correlation sequence is less than the preset threshold, it means that the sub-correlation sequence has a small difference under the current time-shift information. The current time-shift information is used as the target time-shift information. If under the current time-shift information, the self-difference of the sub-correlation sequence is not less than the preset threshold, the current time-shift information is updated, and then based on the updated time-shift information, the self-difference of the sub-correlation sequence is determined based on the updated time-shift information. The iteration is continued until the self-difference of the sub-correlation sequence is less than the preset threshold.

[0090] If the sub-difference of the sub-correlation sequence is not less than the preset threshold value under each time shift information in the preset time shift information range, the sub-correlation sequence can be discarded. Optionally, the time shift information that minimizes the self-difference of the sub-correlation sequence within the preset time shift information range can also be determined. That is, in one embodiment, the frequency identification method provided in the embodiment of the present application can also include:

[0091] If the self-difference of the sub-correlation sequence is not less than the preset threshold value under each time shift information within the preset time shift information range, then determine the time shift information within the preset time shift information range that minimizes the self-difference of the sub-correlation sequence;

[0092] The time shift information that minimizes the difference is determined as the target time shift information.

[0093] Optionally, the self-difference of the sub-correlation sequence when the time-shift information is 0 and when the time-shift information is the maximum value can also be calculated. If, within the preset time-shift information range, the self-difference of the sub-correlation sequence is greater than the corresponding self-difference when the time-shift information is 0 or when the time-shift information is the maximum value, that is, if the minimum value of the time-shift information that minimizes the difference appears when the time-shift information is zero and when the time-shift information is the maximum, the time-shift information is meaningless because the data completely overlap or do not overlap at all at this time.

[0094] 106. Determine the vibration frequency of the device according to the target time-shift information.

[0095] After the target time shift information is determined, the frequency of the target vibration signal sequence, that is, the vibration frequency of the device, can be obtained by taking the ratio of the sampling frequency to the target time shift information.

[0096] Optionally, since there may be certain fluctuation errors in the analysis of discrete data points, after determining the target time-shift information, interpolation processing may be performed based on the time-shift information adjacent to the target information to obtain processed time-shift information, and the vibration frequency of the device may be determined based on the processed time-shift information. That is, in one embodiment, the step of "determining the vibration frequency of the device based on the target time-shift information" includes:

[0097] Determine at least one adjacent time shift information of the target time shift information;

[0098] Performing interpolation processing according to the target time-shift information and at least one adjacent time-shift information to obtain processed time-shift information;

[0099] The vibration frequency of the device is determined based on the time-shift information.

[0100] The adjacent time shift information may have a value close to the target time shift information, for example, the adjacent time shift information=target time shift information+1, or the adjacent time shift information=target time shift information-1.

[0101] Exemplarily, the process of determining the vibration frequency of the device according to the target time shift information can be as follows: Figure 7 As shown, the target time shift information , two adjacent time-shift information can be determined ， , , perform parabolic interpolation processing based on the target time-shift information and the two adjacent time-shift information to obtain the processed time-shift information, and then calculate the sampling frequency The ratio of the processed time-shift information to obtain the target frequency F , which is the vibration frequency of the device.

[0102] The vibration frequency of equipment can be used to detect, identify and predict whether the equipment is faulty, so as to ensure production efficiency, reduce maintenance costs and prevent equipment failure.

[0103] As can be seen from the above, the embodiments of the present application obtain the target vibration signal sequence of the device; perform autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence; divide the correlation sequence to obtain at least two sub-correlation sequences; perform self-difference analysis on the sub-correlation sequences within a preset time-shift information range to obtain the self-difference of the sub-correlation sequences; determine the target time-shift information within the preset time-shift information range according to the self-difference; and determine the vibration frequency of the device according to the target time-shift information, so as to achieve accurate extraction of the vibration frequency of the device from the target vibration signal sequence.

[0104] In the embodiment of the present application, the degree of autocorrelation of the target vibration signal sequence at different time steps can be determined through autocorrelation analysis, and the degree of difference of the sub-correlation degree of the target vibration signal at different time steps can be determined through self-difference analysis, and then the periodic frequency in the signal sequence can be determined. In the process of frequency recognition, the characteristics of the target vibration signal sequence will not be lost, and signals with different periodic fluctuations can be processed, and the recognition accuracy of the vibration frequency is high.

[0105] In order to better implement the frequency identification method provided in the embodiment of the present application, a frequency identification device is also provided in one embodiment. The meanings of the terms are the same as those in the above-mentioned frequency identification method, and the specific implementation details can refer to the description in the method embodiment.

[0106] The frequency identification device can be integrated into a computer device, such as Figure 8 As shown, the frequency identification device may include: a signal acquisition unit 301, a correlation analysis unit 302, a division unit 303, a difference analysis unit 304, an information determination unit 305 and a frequency determination unit 306, as follows:

[0107] (1) A signal acquisition unit 301 is used to acquire a target vibration signal sequence of the device.

[0108] In one embodiment, the signal acquisition unit 301 may also be used for:

[0109] Obtaining an initial vibration signal sequence of the device;

[0110] Performing filtering on the initial vibration signal sequence to obtain a filtered vibration signal sequence;

[0111] The vibration signal sequence is subjected to signal amplification processing to obtain a target vibration signal sequence.

[0112] (2) A correlation analysis unit 302 is used to perform autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence.

[0113] (3) A division unit 303 is used to divide the correlation sequence to obtain at least two sub-correlation sequences.

[0114] In one embodiment, the frequency identification device may further include:

[0115] Controlling the preset window to slide in the correlation sequence, and generating a mean sequence according to the means of multiple correlations in the preset window;

[0116] The correlation sequence is smoothed according to the mean sequence to obtain the processed correlation sequence;

[0117] The division unit 303 may also be used for:

[0118] The processed correlation sequence is divided to obtain a plurality of sub-correlation sequences.

[0119] (4) A difference analysis unit 304 is used to perform self-difference analysis on the sub-correlation sequence within a preset time shift information range to obtain the self-difference of the sub-correlation sequence.

[0120] In one embodiment, the difference analysis unit 304 may also be used to:

[0121] Determine the current time shift information within the preset time shift information range;

[0122] Under the current time shift information, for the first correlation in the sub-correlation sequence, calculate the first correlation and the first error of the correlation whose distance satisfies the time shift information;

[0123] For a second correlation in the sequence of sub-correlations, determining a second error based on the second correlation;

[0124] The self-difference of the sub-correlation sequence under the current time shift information is determined according to the first error and the second error.

[0125] (5) An information determination unit 305, configured to determine target time shift information within a preset time shift information range according to the self-difference.

[0126] In one embodiment, the information determination unit 305 may also be used to:

[0127] If the self-difference of the sub-correlation sequence is less than a preset threshold under the current time-shift information, the current time-shift information is used as the target time-shift information;

[0128] If the self-difference of the sub-correlation sequence is not less than a preset threshold under the current time-shift information, the current time-shift information is updated;

[0129] Return to the step of calculating, for the first correlation in the sub-correlation sequence under the current time shift information, a first error of the first correlation and a correlation whose distance therefrom satisfies the time shift information.

[0130] In one embodiment, the information determination unit 305 may also be used to:

[0131] If the self-difference of the sub-correlation sequence is not less than the preset threshold value under each time shift information within the preset time shift information range, then determine the time shift information within the preset time shift information range that minimizes the self-difference of the sub-correlation sequence;

[0132] The time shift information that minimizes the difference is determined as the target time shift information.

[0133] (6) A frequency determination unit 306, configured to determine a vibration frequency of the device according to the target time shift information.

[0134] In one embodiment, the frequency determination unit 306 may also be configured to:

[0135] Determine at least one adjacent time shift information of the target time shift information;

[0136] Performing interpolation processing according to the target time-shift information and at least one adjacent time-shift information to obtain processed time-shift information;

[0137] The vibration frequency of the device is determined based on the time-shift information.

[0138] As can be seen from the above, the frequency identification device of the embodiment of the present application obtains the target vibration signal sequence of the device through the signal acquisition unit 301; the correlation analysis unit 302 performs autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence; the division unit 303 divides the correlation sequence to obtain at least two sub-correlation sequences; the difference analysis unit 304 performs self-difference analysis on the sub-correlation sequence within the preset time shift information range to obtain the self-difference of the sub-correlation sequence; the information determination unit 305 determines the target time shift information within the preset time shift information range according to the self-difference; the frequency determination unit 306 determines the vibration frequency of the device according to the target time shift information, so as to realize accurate extraction of the vibration frequency of the device from the target vibration signal sequence.

[0139] In the embodiment of the present application, the degree of autocorrelation of the target vibration signal sequence at different time steps can be determined through autocorrelation analysis, and the degree of difference of the sub-correlation degree of the target vibration signal at different time steps can be determined through self-difference analysis, and then the periodic frequency in the signal sequence can be determined. In the process of frequency recognition, the characteristics of the target vibration signal sequence will not be lost, and signals with different periodic fluctuations can be processed, so the recognition accuracy of the vibration frequency is high.

[0140] The present application also provides a computer device, which may be a terminal or a server. Fig. 9 As shown, it shows a schematic diagram of the structure of the computer device involved in the embodiment of the present application, specifically:

[0141] The computer device may include components such as a processor 1001 with one or more processing cores, a memory 1002 with one or more computer-readable storage media, a power supply 1003, and an input unit 1004. Those skilled in the art will appreciate that Fig. 9The computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. Among them:

[0142] The processor 1001 is the control center of the computer device. It uses various interfaces and lines to connect various parts of the entire computer device. By running or executing software programs and / or modules stored in the memory 1002 and calling data stored in the memory 1002, it executes various functions of the computer device and processes data, thereby monitoring the computer device as a whole. Optionally, the processor 1001 may include one or more processing cores; preferably, the processor 1001 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and computer programs, etc., and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 1001.

[0143] The memory 1002 can be used to store software programs and modules. The processor 1001 executes various functional applications and data processing by running the software programs and modules stored in the memory 1002. The memory 1002 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, a computer program required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 1002 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 1002 may also include a memory controller to provide the processor 1001 with access to the memory 1002.

[0144] The computer device also includes a power supply 1003 for supplying power to various components. Preferably, the power supply 1003 can be logically connected to the processor 1001 through a power management system, so as to manage charging, discharging, and power consumption through the power management system. The power supply 1003 can also include any components such as one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators.

[0145] The computer device may further include an input unit 1004, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0146] Although not shown, the computer device may further include a display unit, etc., which will not be described in detail herein. Specifically, in this embodiment, the processor 1001 in the computer device will load the executable files corresponding to the processes of one or more computer programs into the memory 1002 according to the following instructions, and the processor 1001 will run the computer programs stored in the memory 1002, thereby realizing various functions, as follows:

[0147] Acquire a target vibration signal sequence of the device;

[0148] Performing autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence;

[0149] Dividing the correlation sequence to obtain at least two sub-correlation sequences;

[0150] Performing self-difference analysis on the sub-correlation sequence within a preset time shift information range to obtain the self-difference of the sub-correlation sequence;

[0151] Determine the target time shift information within a preset time shift information range according to the self-differentiation;

[0152] The vibration frequency of the device is determined based on the target time-shift information.

[0153] The specific implementation of the above operations can be found in the previous embodiments and will not be described in detail here.

[0154] From the above, it can be seen that in the embodiment of the present application, the degree of autocorrelation of the target vibration signal sequence at different time steps can be determined through autocorrelation analysis, and the degree of difference between the sub-correlation degrees of the target vibration signal at different time steps can be determined through self-difference analysis, and then the periodic frequency in the signal sequence can be determined, and the features in the target vibration signal sequence will not be lost during the frequency recognition process, and signals with different periodic fluctuations can be processed, so the recognition accuracy of the vibration frequency is high.

[0155] According to one aspect of the present application, a computer program product or a computer program is provided, the computer program product or the computer program including computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in various optional implementations in the above-mentioned embodiments.

[0156] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by a computer program, or by controlling related hardware through a computer program. The computer program may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0157] To this end, an embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. The computer program can be loaded by a processor to execute any frequency identification method provided in the embodiment of the present application.

[0158] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0159] The computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0160] Since the computer program stored in the computer-readable storage medium can execute any frequency identification method provided in the embodiments of the present application, the beneficial effects that can be achieved by any frequency identification method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0161] The above is a detailed introduction to a frequency identification method, device, computer equipment and computer-readable storage medium provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A frequency identification method, characterized in that: The method comprises: Acquire a target vibration signal sequence of the device; Performing autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence; Dividing the correlation sequence to obtain at least two sub-correlation sequences; Determine the current time shift information within the preset time shift information range; Under the current time shift information, for a first correlation in the sub-correlation sequence, calculate a first error between the first correlation and a correlation whose distance therefrom satisfies the current time shift information; For a second correlation in the sub-correlation sequence, determining a second error according to the second correlation; Determining, according to the first error and the second error, the self-difference of the sub-correlation sequence under the current time shift information; Determining target time shift information within the preset time shift information range according to the self-difference; The vibration frequency of the device is determined according to the target time-shift information.

2. The method according to claim 1, characterized in that After performing autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence, the method further includes: Controlling a preset window to slide in the correlation sequence, and generating a mean value sequence according to the means of multiple correlations in the preset window; Performing smoothing processing on the correlation sequence according to the mean sequence to obtain a processed correlation sequence; The dividing process of the correlation sequence to obtain at least two sub-correlation sequences includes: The processed correlation sequence is divided to obtain a plurality of sub-correlation sequences.

3. The method according to claim 1, characterized in that The determining of target time shift information within the preset time shift information range according to the self-difference includes: If, under the current time-shift information, the self-difference of the sub-correlation sequence is less than a preset threshold, the current time-shift information is used as the target time-shift information; If, under the current time-shift information, the self-differentiation of the sub-correlation sequence is not less than a preset threshold, the current time-shift information is updated, and the step of calculating, for the first correlation in the sub-correlation sequence under the current time-shift information, a first error whose distance from the first correlation satisfies the correlation of the time-shift information is returned to be executed.

4. The method according to claim 3, characterized in that The method further comprises: If the self-difference of the sub-correlation sequence is not less than the preset threshold value under each time shift information within the preset time shift information range, then determine the time shift information within the preset time shift information range that minimizes the self-difference of the sub-correlation sequence; The time shift information that minimizes the self-discrepancy is determined as the target time shift information.

5. The method according to claim 1, characterized in that: The determining the vibration frequency of the device according to the target time-shift information comprises: Determine at least one adjacent time shift information of the target time shift information; Performing interpolation processing according to the target time-shift information and the at least one adjacent time-shift information to obtain processed time-shift information; A vibration frequency of the device is determined based on the time-shift information.

6. The method according to any one of claims 1 to 5, characterized in that: The target vibration signal sequence of the acquisition device includes: Obtaining the initial vibration signal sequence of the device; Performing filtering on the initial vibration signal sequence to obtain a filtered vibration signal sequence; The filtered vibration signal sequence is subjected to signal amplification processing to obtain the target vibration signal sequence.

7. A frequency identification device, characterized in that: include: A signal acquisition unit, used to acquire a target vibration signal sequence of the device; A correlation analysis unit, used for performing autocorrelation analysis on the target vibration signal sequence to obtain a correlation sequence of the target vibration signal sequence; A division unit, used for performing division processing on the correlation sequence to obtain at least two sub-correlation sequences; A difference analysis unit, used to determine the current time shift information within a preset time shift information range; Under the current time shift information, for a first correlation in the sub-correlation sequence, calculate a first error between the first correlation and the correlation whose distance satisfies the current time shift information; for a second correlation in the sub-correlation sequence, determine a second error according to the second correlation; and determine the self-difference of the sub-correlation sequence under the current time shift information according to the first error and the second error; An information determining unit, configured to determine target time shift information within the preset time shift information range according to the self-difference; A frequency determination unit is used to determine the vibration frequency of the device according to the target time shift information.

8. A computer device, characterized in that: It comprises a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute the frequency identification method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store a computer program, and the computer program is loaded by a processor to execute the frequency identification method according to any one of claims 1 to 6.

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