Shaft frequency extraction method, shaft frequency extraction system and storage medium

Abstract

The present application relates to a shaft frequency extraction method, shaft frequency extraction system, and storage medium. The method includes: obtaining a DEMON line spectrum and a line spectrum sequence of the DEMON line spectrum based on the array element domain data to be identified, and obtaining a difference frequency array based on the frequency difference between each two line spectra in the line spectrum sequence; widening the frequency range corresponding to each difference frequency in the difference frequency array based on the resolution of the DEMON line spectrum, and reducing the frequency interval between each difference frequency in the difference frequency array based on the resolution of the DEMON line spectrum to obtain a shaft frequency array; calculating the harmonics of different orders corresponding to each shaft frequency in the shaft frequency array to obtain multiple harmonic cluster spectra; matching the DEMON line spectrum with a pre-constructed recognition template, and determining the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum based on the matching result; wherein the recognition template is constructed based on the harmonic cluster spectrum. The use of this method can solve the problem of low accuracy and robustness in shaft frequency feature extraction.

Description

Technical Field

[0001] The present application relates to the field of underwater target recognition, and in particular to an axis frequency extraction method, an axis frequency extraction system, and a storage medium. Background Art

[0002] Using target radiated noise to classify targets is a crucial research topic in the field of underwater acoustics. When a propeller rotates in a non-uniform wake, its cavitation noise exhibits modulation. Propeller cavitation noise consists of two components: one, generated by the collapse and rebound of numerous transient cavitation bubbles in the area immediately adjacent to the propeller blades, has a continuous spectrum; the other, generated by the periodic forced vibrations of numerous stable cavitation bubbles in the vicinity of the propeller, has a discrete line spectrum. The propeller's size, shape, speed, and number of blades are closely related to the type of underwater target. Detection of Envelope Modulation on Noise (DEMON) spectrum analysis of the target reveals physical characteristics such as propeller speed and number of blades. These characteristics are often used as a key basis for underwater target identification.

[0003] When extracting target shaft frequency characteristics, the traditional greatest common divisor algorithm can only process simple data with a small number of targets and a high signal-to-noise ratio when identifying target characteristics. However, when faced with the complex and changeable underwater acoustic data of the actual ocean, due to the insufficient resolution of the DEMON spectrum, there is a situation where the shaft frequency characteristics cannot be extracted.

[0004] There is currently no effective solution to the problem of low accuracy and robustness in shaft frequency feature extraction in related technologies. Summary of the Invention

[0005] Based on this, it is necessary to provide a shaft frequency extraction method, a shaft frequency extraction system and a storage medium that can solve the problems of low accuracy and robustness of shaft frequency feature extraction in response to the above technical problems.

[0006] In a first aspect, this embodiment provides a shaft frequency extraction method, the method comprising:

[0007] Obtaining a DEMON line spectrum and a line spectrum sequence of the DEMON line spectrum according to the array element domain data to be identified, and obtaining a difference frequency array according to the frequency difference between every two line spectra in the line spectrum sequence;

[0008] Broadening the frequency range corresponding to each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum, and reducing the frequency interval between each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum, to obtain an axis frequency array;

[0009] Calculating harmonics of different orders corresponding to each axis frequency in the axis frequency array to obtain multiple harmonic cluster spectra;

[0010] The DEMON line spectrum is matched with a pre-constructed recognition template, and the axial frequency and its harmonic sequence corresponding to the DEMON line spectrum are determined according to the matching result; wherein the recognition template is constructed based on the harmonic cluster spectrum.

[0011] In some embodiments, before matching the DEMON line spectrum with a pre-built recognition template, the method further includes:

[0012] interpolating the DEMON line spectrum;

[0013] The resolution of the harmonic cluster spectrum is adjusted so that the resolution of the harmonic cluster spectrum is consistent with the resolution of the DEMON line spectrum obtained after interpolation processing.

[0014] In some embodiments, before adjusting the resolution of the harmonic cluster spectrum so that the resolution of the harmonic cluster spectrum is consistent with the resolution of the DEMON line spectrum obtained after interpolation processing, the method further includes:

[0015] The upper limit and lower limit of the frequency range of the DEMON line spectrum are respectively widened by a specified multiple of resolution.

[0016] In some embodiments, matching the DEMON line spectrum with the recognition template and determining the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum according to the matching result includes:

[0017] Calculating the inner products of the DEMON line spectrum and the sequences in the plurality of recognition templates respectively to obtain a matching degree sequence corresponding to each recognition template;

[0018] Obtaining an integrity sequence corresponding to each of the recognition templates according to the number and frequency positions of peak signals in the matching sequence;

[0019] According to the matching degree sequence and the corresponding integrity sequence, the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum are determined.

[0020] In some embodiments, obtaining the integrity sequence corresponding to each recognition template according to the number and frequency position of the peak signals in the matching sequence includes:

[0021] When the number of the peak signals is not zero, obtaining the frequency position;

[0022] In the case where the frequency position and the resolution satisfy a multiple relationship, the frequency corresponding to the peak is used as a harmonic of the shaft frequency corresponding to the recognition template;

[0023] In the case where the frequency position and the resolution do not satisfy a multiple relationship, obtaining the distance between the peak and multiple multiples of the resolution, and taking the frequency corresponding to the peak with the closest distance as the harmonic of the shaft frequency corresponding to the identification template;

[0024] The integrity sequence is obtained according to the number of the harmonics obtained by matching.

[0025] In some embodiments, before matching the DEMON line spectrum with a pre-built recognition template, the method further includes:

[0026] The harmonic cluster spectra are respectively convolved according to the signal conforming to the Gaussian distribution to obtain a plurality of the recognition templates.

[0027] In some embodiments, widening the frequency range corresponding to each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum includes:

[0028] Subtracting the resolution of the DEMON line spectrum from the frequency value of each element in the difference frequency array to obtain a lower limit of the frequency value of each element;

[0029] The resolution of the DEMON line spectrum is increased based on the frequency value of each element in the difference frequency array to obtain the upper limit of the frequency value of each element.

[0030] In some embodiments, reducing the frequency interval between the difference frequencies in the difference frequency array according to the resolution of the DEMON line spectrum includes:

[0031] Obtaining a new frequency interval according to the resolution of the DEMON line spectrum;

[0032] Elements are added between the difference frequencies of the difference frequency array based on the frequency interval, so that the frequency interval of the difference frequency array after the added elements is reduced.

[0033] In some embodiments, the receiving array includes a sonar array, a buoy, a float, and a detection payload, wherein the sonar array includes one or more of the following: a towed linear array, a shore-based array, a conformal array, a planar array, and a bow array. The DEMON line spectrum and the line spectrum sequence of the DEMON line spectrum are obtained according to the array element domain data to be identified, including:

[0034] Obtaining array element domain data collected by the receiving array;

[0035] Converting the array element domain data into synthetic wave data, and demodulating the synthetic wave data;

[0036] Performing Fourier transform on the demodulated synthetic wave data to obtain a DEMON spectrum;

[0037] The line spectrum in the DEMON spectrum is extracted to obtain the DEMON line spectrum and the line spectrum sequence.

[0038] In some embodiments, after matching the DEMON line spectrum with a pre-built recognition template and determining the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum according to the matching result, the shaft frequency extraction method further includes:

[0039] The propeller parameters corresponding to the array element domain data are obtained based on the shaft frequency and its harmonic sequence analysis.

[0040] In a second aspect, a shaft frequency extraction system is provided in this embodiment, comprising: a receiving array and a processing device; the receiving array comprises a sonar array, a buoy, a buoy, and a detection payload; the sonar array comprises one or more of the following: a towed linear array, a shore-based array, a conformal array, a planar array, and a bow array; wherein,

[0041] The receiving array is used to obtain array element domain data of the acquisition source;

[0042] The processing device is used to implement the spectrum identification method described in the first aspect above.

[0043] In a third aspect, a computer-readable storage medium is provided in this embodiment, on which a computer program is stored. When the computer program is executed by a processor, the shaft frequency extraction method described in the first aspect is implemented.

[0044] The above-mentioned shaft frequency extraction method, shaft frequency extraction system and storage medium obtain a shaft frequency array by adjusting the frequency range and frequency interval of the difference frequency data, thereby improving the resolution during shaft frequency matching; the recognition template constructed based on the shaft frequency array is matched to the DEMON line spectrum, which can obtain the shaft frequencies and harmonic sequences of multiple targets, and achieve the effect of improving the accuracy and robustness of shaft frequency feature extraction. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A diagram showing an application environment of a shaft frequency extraction method in one embodiment;

[0046] Figure 2 Schematic diagram of a flow chart of a shaft frequency extraction method in one embodiment;

[0047] Figure 3 A schematic flow chart of a schematic diagram of a method for shaft frequency extraction and harmonic determination based on a DEMON spectrum in one embodiment;

[0048] Figure 4 Schematic diagram of DEMON line spectrum in one embodiment;

[0049] Figure 5 is a harmonic sequence template of a shaft frequency of 4.47 Hz in one embodiment;

[0050] Figure 6 is a schematic diagram of an axis frequency matching sequence in one embodiment;

[0051] Figure 7 is a schematic diagram of the quality factor in one embodiment;

[0052] Figure 8 is a structural block diagram of a shaft frequency extraction system in one embodiment;

[0053] Figure 9 is a structural block diagram of a shaft frequency extraction device in one embodiment;

[0054] Figure 10 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0056] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 1 FIG. 1 is a block diagram of the hardware structure of a terminal of the shaft frequency extraction method according to an embodiment of the present application. Figure 1 As shown, the terminal may include one or more ( Figure 1 The processor 102 (only one is shown) and a memory 104 for storing data, wherein the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The terminal may also include a transmission device 106 for communication functions and an input / output device 108. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above terminal. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0057] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the shaft frequency extraction method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above-mentioned method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely located relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0058] Transmission device 106 is used to receive or transmit data via a network. This network may include a wireless network provided by the terminal's communications provider. In one embodiment, transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0059] In this embodiment, a shaft frequency extraction method is provided. Figure 2 is a flow chart of the shaft frequency extraction method of this embodiment. Figure 2 As shown, the process includes the following steps:

[0060] Step S202 : obtaining a DEMON line spectrum and a line spectrum sequence of the DEMON line spectrum according to the array element domain data to be identified, and obtaining a difference frequency array according to the frequency difference between every two line spectra in the line spectrum sequence.

[0061] Array elements are the basic units in an array, including antennas, sensors, and other devices capable of receiving signals. Element-domain data refers to the signal data received by an array element. A DEMON line spectrum is the spectrum of a discrete signal extracted using DEMON technology. A line spectrum sequence is a signal sequence derived from the discretized frequency components of a DEMON line spectrum.

[0062] Optionally, frequency domain beamforming is performed on the time domain data of each array element channel to obtain synthetic wave data. In the synthetic wave data, the low-frequency modulation spectrum information is demodulated in the medium and high frequency bands using the DEMON spectrum extraction technology, and line spectrum extraction is performed to obtain the DEMON line spectrum and its line spectrum sequence.

[0063] Optionally, calculate the line spectrum sequence f mThe difference frequency F is calculated for each two line spectrum corresponding frequency points. i,j :

[0064] F i,j =f i -f j ,i,j=1,2,…M;i>j

[0065] Arrange the difference frequency array elements from small to large to obtain the difference frequency array {F i,j By calculating the difference frequency, we can obtain the axial frequency characteristics of the line spectra in the line spectrum sequence. Where M is the number of line spectra in the line spectrum sequence. If the difference frequency of each two line spectra corresponding to the frequency points is the same, then the difference frequency value can be combined.

[0066] Optionally, if the accuracy of the difference frequency array needs to be further improved, the line spectrum sequences can be merged first. The merging principle is as follows: for a DEMON line spectrum sequence f containing N ordered line spectra, n , where the line spectrum frequency is greater than f th1 hz, the line spectrum clusters with an interval less than or equal to one spectrum resolution are merged into a single line spectrum, and the line spectrum with the largest amplitude in the line spectrum cluster is retained. The line spectrum sequence f is obtained. m , a total of M ordered line spectra.

[0067] Step S204 , widening the frequency range corresponding to each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum, and reducing the frequency interval between each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum, to obtain an axis frequency array.

[0068] The resolution of the DEMON line spectrum is consistent with that of the difference frequencies. When performing DEMON spectrum analysis, insufficient resolution may result in the harmonic sequence frequencies in the spectrum obtained based on the array element domain data not being exactly integer multiples, leading to inaccurate frequency ranges corresponding to the difference frequencies in the difference frequency array.

[0069] Optionally, based on the resolution of the DEMON line spectrum, the upper limit of the frequency range corresponding to the difference frequency is increased, and / or the lower limit of the frequency range corresponding to the difference frequency is lowered, so as to reduce the possibility that insufficient resolution will lead to inaccurate line spectrum sequence and make it impossible to match the real line spectrum difference frequency with the difference frequency array.

[0070] Optionally, a new frequency interval is obtained based on the resolution of the DEMON line spectrum. Based on this new frequency interval, denser data points are generated within the frequency range of the difference frequency array. The data points with the modified frequency range and interval are used as all possible first harmonic frequencies of the original difference frequency data to obtain the axis frequency data. The resolution of the calculated axis frequency array can be improved by reducing the frequency interval of the data; the value of the frequency interval can be set as required.

[0071] Step S206 , calculating harmonics of different orders corresponding to the frequencies of the respective axis frequencies in the axis frequency array, and obtaining a plurality of harmonic cluster spectra.

[0072] The harmonic cluster spectrum is a collection of the fundamental frequency and its harmonics. Optionally, for each axis frequency in the axis frequency array, the line spectrum frequencies of the first L orders are calculated to obtain the harmonic cluster spectrum of that frequency. Based on the harmonic calculation results of multiple axis frequencies, multiple harmonic cluster spectra are obtained. The order of harmonic calculation can be set according to actual needs; the order L of the line spectrum frequency can be pre-set or modified.

[0073] Step S208 , matching the DEMON line spectrum with a pre-constructed recognition template, and determining the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum according to the matching result; wherein the recognition template is constructed based on the harmonic cluster spectrum.

[0074] The similarity between the DEMON line spectrum and multiple recognition templates is determined separately to determine the degree of match between the DEMON line spectrum and the multiple recognition templates. The multiple recognition templates are sorted according to the degree of match. Based on the order of matching from high to low, the axial frequency and its harmonic sequence corresponding to one or more recognition templates ranked highly are obtained, and the axial frequency and its harmonic sequence are used as the recognition result of the DEMON line spectrum. The identified axial frequency and its harmonic sequence are the features of the array element domain data to be identified, thereby achieving recognition of the array element domain data.

[0075] Alternatively, multiple harmonic cluster spectra can be directly used as multiple pre-constructed recognition templates. Alternatively, to improve recognition accuracy, the waveform distribution of the harmonic cluster spectra can be modified to increase the template matching range, and the processed harmonic cluster spectra can be used as multiple pre-constructed recognition templates. For example, the harmonic cluster spectra can be processed using a Gaussian function as a convolution kernel, a window function, or other custom convolution kernel.

[0076] In the above-mentioned shaft frequency extraction method, the frequency range and frequency interval of the difference frequency array are adjusted to improve the resolution of shaft frequency matching and the tolerance to phenomena such as Doppler frequency shift. The recognition template pre-built based on the shaft frequency data is compared with the DEMON line spectrum to accurately identify the shaft frequencies and harmonic sequences of multiple targets, thereby achieving the effect of improving the accuracy and robustness of shaft frequency feature extraction.

[0077] In one embodiment, before matching the DEMON line spectrum with a pre-built recognition template, the method further comprises: performing convolution processing on the harmonic cluster spectrum according to a signal conforming to Gaussian distribution to obtain a plurality of recognition templates.

[0078] The frequency of the Gaussian-distributed signal is consistent with the resolution of the harmonic cluster spectrum. The harmonic cluster spectrum contains a line spectrum. Due to the Doppler shift phenomenon, the DEMON line spectrum obtained based on array element-domain data experiences frequency offset. In this embodiment, convolution processing is performed on the harmonic cluster spectrum based on signals that conform to the Gaussian distribution. This can change the signal distribution of the discrete signals in the harmonic cluster spectrum to conform to the Gaussian distribution, increase the template matching range, and improve tolerance to spectral frequency offsets such as Doppler shift.

[0079] In one embodiment, before matching the DEMON line spectrum with the pre-built recognition template, the method further includes: interpolating the DEMON line spectrum; and adjusting the resolution of the harmonic cluster spectrum so that the resolution of the harmonic cluster spectrum is consistent with the resolution of the DEMON line spectrum obtained after the interpolation process.

[0080] Among them, the resolution of the DEMON line spectrum is improved by interpolating the frequency of the DEMON line spectrum to prevent the Doppler shift from causing the DEMON line spectrum to be unable to match the recognition template. Optionally, the frequency resolution of the DEMON line spectrum after interpolation is less than or equal to the resolution of the axial frequency array to avoid insufficient resolution of the axial frequency array. Optionally, the resolution of the harmonic cluster spectrum is unified with the resolution of the DEMON line spectrum by rounding off, and the harmonic cluster spectrum and the DEMON line spectrum are adjusted to the same scale inner product, so as to facilitate the matching of the DEMON line spectrum and the recognition template obtained based on the harmonic cluster spectrum.

[0081] For example, for the axis frequency array {F shaft Each frequency f in i , calculate the line spectrum frequencies of the first L (L=3,4,5,6,7,8,9…,16) orders and obtain the axis frequency sequence f i The harmonic cluster spectrum {F i,h},h=1,2,…8. Interpolate the original DEMON line spectrum frequency by N2 times (N2≤N1), and increase the spectrum resolution from Promoted to The resolution of the axis frequency array is , correspondingly, the resolution of the harmonic cluster spectrum is By rounding off the harmonic cluster spectrum {F i,h The resolution of} is consistent with the DEMON line spectrum, The harmonic cluster spectrum resolution of the axis frequency sequence is adjusted to .

[0082] Optionally, after adjusting the resolution of the harmonic cluster spectrum, the harmonic cluster spectrum can be convolved according to the signal that conforms to the Gaussian distribution. In this case, the frequency of the Gaussian distribution signal can be set to , the signal width of the Gaussian distribution is set to twice the interpolation multiple, that is, .

[0083] In this embodiment, the resolution of the DEMON line spectrum is improved by interpolation; by unifying the resolution of the DEMON line spectrum after interpolation and the resolution of the harmonic cluster spectrum, the resolutions of the two are consistent when matching the DEMON line spectrum and the identification template obtained according to the harmonic cluster spectrum; this is beneficial to improving the accuracy of shaft frequency extraction.

[0084] Furthermore, in one embodiment, before adjusting the resolution of the harmonic cluster spectrum so that the resolution of the harmonic cluster spectrum is consistent with the resolution of the DEMON line spectrum obtained after interpolation processing, the method also includes: widening the upper and lower limits of the frequency range of the DEMON line spectrum by a specified multiple of the resolution.

[0085] Optionally, widen the upper and lower limits of the frequency range of the DEMON line spectrum ,L=1,2,…8. Among them, L is the harmonic order corresponding to the widened DEMON line spectrum. The higher the harmonic order, the larger the widening width and the greater the tolerable error.

[0086] In this embodiment, the resolution of the DEMON line spectrum is improved by interpolation processing of the DEMON line spectrum. By widening the DEMON line spectrum sequence, the possibility of the frequency deviation caused by Doppler frequency shift causing the DEMON line spectrum to fail to match the recognition template is reduced, thereby improving the robustness of the axis frequency feature extraction.

[0087] In one embodiment, the DEMON line spectrum is matched with a pre-built recognition template, and the axial frequency and its harmonic sequence corresponding to the DEMON line spectrum are determined based on the matching results, including: calculating the inner products of the DEMON line spectrum and the sequences in multiple recognition templates respectively to obtain a matching degree sequence corresponding to each recognition template; obtaining an integrity sequence corresponding to each recognition template based on the number and frequency position of peak signals in the matching degree sequence; and determining the axial frequency and its harmonic sequence corresponding to the DEMON line spectrum based on the matching degree sequence and the corresponding integrity sequence.

[0088] The matching degree sequence represents the degree of similarity between each signal in the DEMON line spectrum and each axial frequency in the recognition template. The integrity sequence represents the number of signals in the DEMON line spectrum that match each axial frequency in the recognition template. The higher the matching degree and integrity, the greater the likelihood that the axial frequency corresponding to the recognition template belongs to the axial frequency characteristics of the DEMON line spectrum.

[0089] After calculating the inner product of the DEMON line spectrum and the sequences in multiple recognition templates, if there is no peak in the spectrum corresponding to the matching sequence, the DEMON line spectrum does not match the recognition template; if the number of peaks in the spectrum generated after the dot product is greater than 0, the DEMON line spectrum matches the harmonics in the recognition template.

[0090] Optionally, based on the multiple relationship between the peak position and the resolution, the order of the harmonics matching the peak is determined, the first L harmonics are selected as required, and the number of the first L harmonics matched to each axis frequency in the recognition template is counted as a sequence to measure the integrity of the harmonics, thereby obtaining an integrity sequence.

[0091] Optionally, the interpolated and broadened DEMON line spectrum is compared with the recognition template {M i}Do the inner product, and the value obtained by the inner product is used as the recognition template {M i}Corresponding shaft frequency f i The matching degree q of the harmonic sequence i , get the matching degree sequence {q n According to the harmonic corresponding to the peak of the spectrum generated after the dot product, the axis frequency array corresponding to the recognition template is determined {F shaft}, each axis frequency f i The number of matched first L-order harmonics is used as the integrity sequence {s n}. Use the matching degree sequence {q n} multiplied by the integrity sequence {s n}, get the quality factor , according to the quality factor m n Sort the axis frequencies corresponding to the recognition templates to obtain the axis frequency sequence. n The larger the value is, the more likely this axis frequency is the characteristic axis frequency of the target. Based on the axis frequency sequence, the axis frequency and its harmonic sequence corresponding to the DEMON line spectrum can be obtained.

[0092] Optionally, the method of matching the DEMON line spectrum with the pre-constructed recognition template to obtain a matching degree sequence corresponding to each recognition template also includes: calculating the similarity between the DEMON line spectrum and the signal of the pre-constructed recognition template at different frequency shifts to generate a matching degree sequence; or, obtaining a matching degree sequence based on the statistical coincidence of the peak position and amplitude difference between the DEMON line spectrum and the template; or, obtaining a matching degree sequence based on envelope similarity.

[0093] Furthermore, in order to improve the accuracy of recognition, before obtaining the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum based on the shaft frequency sequence, the shaft frequencies corresponding to the same target and the shaft frequencies that are in a multiple frequency relationship with each other can be combined, including:

[0094] Subtract the elements in this axis frequency sequence from each other to obtain the axis frequency difference sequence S i,j :

[0095] ;

[0096] like , then determine whether the two shaft frequencies belong to the same target by judging their harmonic sequences. If more than half of the harmonic sequences of the two shaft frequencies are consistent, then the harmonic sequences of the two shaft frequencies are judged to correspond to the same target, and {s n}larger axis frequency sequence. Among them, is the resolution of the original DEMON line spectrum.

[0097] Take the quotient of the axis frequency sequence and get the remainder sequence D of the frequency multiplication i,j :

[0098] ;

[0099] K is The rounded value of . , then it is considered that there is a frequency multiplication relationship between the two shaft frequencies, and then it is determined whether the harmonic sequences of the two shaft frequencies are consistent. j The harmonic sequence of f i If more than half of the harmonic sequences of the two shaft frequencies are consistent, it is determined that the harmonic sequences of the two shaft frequencies correspond to the same target, and only s is retained. n Larger shaft frequency.

[0100] The shaft frequency and its harmonic sequence are finally retained {F shaft}That is, the target feature recognition result based on the DEMON line spectrum.

[0101] In this embodiment, inner product calculations and dot product calculations are performed on the DEMON line spectrum and the sequences in multiple recognition templates. The possibility that the sequences in the recognition templates correspond to the axial frequency features of the DEMON line spectrum is evaluated through the two aspects of matching similarity and completeness. The accuracy of axial frequency feature extraction is improved through multi-angle evaluation.

[0102] Furthermore, in one embodiment, an integrity sequence corresponding to each identification template is obtained based on the number and frequency position of peak signals in the matching degree sequence, including: when the number of peak signals is not zero, obtaining the frequency position; when the frequency position and the resolution satisfy a multiple relationship, using the frequency corresponding to the peak as the harmonic of the axial frequency corresponding to the identification template; when the frequency position and the resolution do not satisfy a multiple relationship, obtaining the distance between the peak and multiple multiple values ​​of the resolution, and using the frequency corresponding to the peak with the closest distance as the harmonic of the axial frequency corresponding to the identification template; and obtaining the integrity sequence based on the number of harmonics obtained by matching.

[0103] Among them, if the frequency corresponding to the peak satisfies a multiple relationship with the resolution, or the distance between the frequency corresponding to the peak and a certain multiple value of the resolution is close, then the DEMON line spectrum may match the harmonics in the recognition template, and the multiple value corresponding to the resolution corresponds to the harmonic order.

[0104] For example, the interpolated and broadened DEMON line spectrum is compared with the axis frequency f i Sequence recognition template M i Do a dot product to get the matching sequence and calculate the peak value in the matching sequence. Get the number of peaks and the frequency position of the peaks. The number of peaks is used to determine whether the harmonic is matched: if there is no peak, it is determined that the harmonic is not matched, and the Kth harmonic is 0; if the number of peaks is greater than 0, it is determined that the harmonic is matched. The peak frequency position is used to determine the order of the matched harmonic: if the peak frequency position f m yes An integer multiple of Then f m It is the Kth harmonic; if the peak frequency position f m no If the distance is an integer multiple of The frequency position of the nearest DEMON line spectrum is taken as the Kth harmonic.

[0105] The axis frequency array corresponding to the statistical recognition template {F shaft}, each axis frequency f i The number of matched first L-order harmonics is used as the integrity sequence to measure the integrity of harmonics. n}, that is, the frequency and harmonic sequence of the shaft frequency corresponding to the identification template. In order to reduce the amount of calculation, the integrity sequence can be screened first: for the integrity sequence {s n}, delete {s n} is less than the specified frequency The axis frequency sequence of . Specify the frequency It is a preset value used to delete shaft frequencies that are too small and reduce the impact of noise and burrs on the accuracy of shaft frequency sequence recognition.

[0106] In this embodiment, when the peak value is consistent with multiple multiples of the resolution, or the difference between the peak value and multiple multiples of the resolution is small, it is judged that there is a possibility of matching the DEMON line spectrum with the harmonics in the identification template, thereby reducing the possibility that the axis frequency feature cannot be extracted due to the phenomenon that the frequency multiple relationship of the harmonic sequence is not an exact integer multiple relationship, thereby improving the robustness of the axis frequency extraction.

[0107] In one embodiment, the frequency range corresponding to each difference frequency in the difference frequency array is broadened according to the resolution of the DEMON line spectrum, including: subtracting the resolution of the DEMON line spectrum from the frequency value of each element in the difference frequency array to obtain the lower limit of the frequency value of each element; and increasing the resolution of the DEMON line spectrum based on the frequency value of each element in the difference frequency array to obtain the upper limit of the frequency value of each element.

[0108] Among them, the resolution of DEMON line spectrum is , then the resolution of the difference frequency array is also , the difference frequency array is {F i,j}.according to Adjust the frequency range of all difference frequency arrays to obtain the expanded difference frequency array as follows: In this embodiment, the frequency range of all difference frequency arrays is adjusted to improve the tolerance to phenomena such as Doppler shift.

[0109] In one embodiment, the frequency interval between each difference frequency in the difference frequency array is reduced according to the resolution of the DEMON line spectrum, including: obtaining a new frequency interval according to the resolution of the DEMON line spectrum; and inserting elements between each difference frequency in the difference frequency array based on the frequency interval, so that the frequency interval of the difference frequency array after the elements are inserted is reduced.

[0110] The step size is smaller than the resolution of the DEMON line spectrum. Optionally, adjust the frequency interval of the array to , get all possible first harmonic frequencies in the difference frequency array, and form the axis frequency array {F shaft}.

[0111] In this embodiment, by adjusting the frequency range of all difference frequency arrays and increasing the number of elements in the difference frequency arrays, the resolution corresponding to the difference frequency arrays is improved, thereby improving the resolution of the recognition template and achieving the effect of improving the accuracy of axis frequency feature extraction.

[0112] In one embodiment, the receiving array includes a sonar array, a buoy, a buoy and a detection payload, and the sonar array includes one or more of the following: a towed linear array, a shore-based array, a conformal array, a planar array, and a bow array. A DEMON line spectrum and a line spectrum sequence of the DEMON line spectrum are obtained based on the array element domain data to be identified, including: acquiring the array element domain data collected by the receiving array; converting the array element domain data into synthetic wave data, and demodulating the synthetic wave data; performing Fourier transform on the demodulated synthetic wave data to obtain a DEMON spectrum; and extracting the line spectrum in the DEMON spectrum to obtain the DEMON line spectrum and a line spectrum sequence.

[0113] Towed linear arrays, shore-based arrays, conformal arrays, area arrays, and bow arrays are all different types of sonar arrays. A buoy is a measurement system deployed underwater, while a buoy is an observation platform floating on the sea surface. Detection payloads are the technical equipment used to perform detection missions. These payloads can include autonomous underwater vehicles (AUVs) and unmanned underwater vehicles (UUVs).

[0114] Optionally, array element domain data emitted by a signal source is collected through a receiving array; the array element domain data is preprocessed; beam synthesis is performed on the array element domain data; the synthesized beam in the azimuth is demodulated; Fourier transform is performed on the demodulated synthesized beam data to obtain a DEMON spectrum, and then line spectrum extraction is performed to obtain a DEMON line spectrum and its line spectrum sequence.

[0115] Preprocessing the array-domain data involves detecting bad sectors on each array channel and removing problematic channel data. Bad sectors can be screened using one or more of the following methods: rapid screening of candidate bad sectors based on statistical characteristics, screening through frequency-domain analysis, or screening through correlation analysis.

[0116] The rapid screening of candidate bad tracks based on statistical characteristics includes: calculating the statistical characteristic parameters of the time domain data of each array element channel, such as mean, variance or energy value. Among them, the time domain data sequence of the i-th array element channel is x i (t), i=1,2,…,M, M represents the number of array elements, t=1,2,…,N, N is the number of sampled data points. Then the data mean of the i-th array element channel is: , the variance is , the energy value is .

[0117] According to the calculated statistical characteristic parameters, dynamic thresholds are set and the 3σ principle is used to screen bad sectors. For the mean, variance or energy value, the overall mean is calculated respectively. 、 、 and the population standard deviation 、 、 If the statistical characteristic parameters of a certain array channel exceed the following ranges, it will be considered a candidate bad sector: or ; or ; or .

[0118] Screening bad tracks through frequency domain analysis methods includes: performing frequency domain analysis on the channel data of each array element, calculating the power spectral density (PSD) or performing spectrum flatness measurement (SFM) to locate abnormal channels. The power spectral density can be calculated using the periodogram method or the Welch method. Taking the Welch method as an example, the data sequence is segmented, and each segment of data is processed by a window function and then a fast Fourier transform (FFT) is performed. The power spectral density of each segment is then calculated and averaged to obtain the power spectral density estimate P for the channel. i (f).

[0119] Spectral flatness can be measured by calculating the ratio of the geometric mean to the arithmetic mean of the power spectral density. The specific formula is:

[0120] ;

[0121] Where N is the number of frequency points. If F i If it deviates significantly from the normal range, the channel will be considered a candidate bad sector.

[0122] The correlation analysis method for screening bad sectors includes:

[0123] Calculate the correlation coefficient matrix of each channel data to further determine the bad track. Let the correlation coefficient of the data between the i-th channel and the j-th channel be ρ ij , the calculation formula is:

[0124] ;

[0125] in, is the time domain data sequence of the j-th array element channel, is the data mean of the j-th array element channel.

[0126] Calculate the average correlation coefficient across all channels:

[0127] ;

[0128] Among them, ρ mj is the data correlation coefficient between the mth channel and the jth channel, and M is the number of ordered line spectra.

[0129] Set the correlation coefficient threshold ρ th If the average correlation coefficient of a channel with other channels is significantly lower than ρ th , then the channel is determined to be a bad track.

[0130] After filtering out bad sectors, pre-processing the array domain data may also include: performing signal consistency check and correction on the data of each array channel to ensure that each array channel maintains consistency in time, amplitude, and phase.

[0131] Optionally, the delay of each array element is calibrated by the array element position, and the delay correction is performed based on the least mean square (LMS) algorithm. Assume that the reference channel is the kth channel, and the delay of other channels relative to the reference channel is :

[0132] ;

[0133] Where x is the position coordinate of the array element channel on the x-axis, y is the position coordinate of the array element channel on the y-axis, and z is the position coordinate of the array element channel on the z-axis; the subscripts k and i refer to the kth array element channel and the i-th array element channel, respectively; and c is the speed of sound.

[0134] The algorithm adjusts the delay estimate by iterative :

[0135] ;

[0136] Where μ is the step size factor and e(t) is the error signal.

[0137] Calculate the energy E of each channel data i and the reference channel data energy E k The ratio of detection amplitude deviates from the threshold channel. Assuming the reference channel is the kth channel, the energy ratio of the i-th channel is:

[0138] ;

[0139] Set the amplitude ratio threshold R th If it exceeds the range, it is considered that the channel amplitude has deviation. Channel equalization is performed based on algorithms such as minimum mean square error (MMSE) and blind equalization. Taking the MMSE algorithm as an example, the equalization filter coefficient ω is solved by minimizing the objective function:

[0140] ;

[0141] Where d(t) is the desired signal and x(t) is the input signal vector.

[0142] Phase consistency is tested by phase difference statistics, and phase correction is performed based on the minimum mean square error (MMSE) algorithm. The phase difference between each channel and the reference channel is calculated. :

[0143] ;

[0144] in, is the conjugate of the reference channel data. If the phase difference exceeds the set phase threshold , then it is considered that there is a phase deviation in the channel. The MMSE algorithm corrects the phase by minimizing the mean square value of the phase error.

[0145] Detect and suppress abnormally strong transient signals in each channel. Methods such as wavelet transform and empirical mode decomposition (EMD) are proposed to decompose the signal and extract transient signal components. For example, using wavelet transform, an appropriate wavelet basis is selected and the signal is decomposed at multiple scales to obtain wavelet coefficients at different scales. Abnormal peaks are detected in the detail coefficients to capture strong transient signals.

[0146] Beamforming of the meta-domain data specifically includes:

[0147] The time domain signal of each array element is , M represents the number of array elements, which is transformed into the frequency domain through Fourier transform ;

[0148] ;

[0149] Where f is the frequency.

[0150] Perform phase compensation on the frequency domain signal of each array element, and the compensation vector is:

[0151] ;

[0152] Among them, d i is the distance from the ith array element to the first array element; c is the speed of sound; θ is the scanning angle 0≤θ≤π;

[0153] After compensation, the element domain frequency domain signals at each azimuth angle are converted into beam domain frequency domain signals. , K represents the number of scanned azimuth angles.

[0154] Demodulating the synthetic beam in azimuth specifically includes:

[0155] Signals are detected in 1, 2, ..., K directions. exist To perform bandpass filtering in the frequency domain, the following Butterworth filter can be used:

[0156] ;

[0157] Where n is the order of the filter, w c is the cutoff frequency.

[0158] The frequency domain signal after bandpass filtering After inverse Fourier transform, it is transformed into time domain .

[0159] ;

[0160] Then perform absolute value detection on the signal and get The time domain signal is a pre-beamed time domain signal containing modulation information.

[0161] Performing Fourier transform on the demodulated synthetic beam data to obtain the DEMON spectrum, and then performing line spectrum extraction to obtain the DEMON line spectrum and its line spectrum sequence specifically includes:

[0162] Pre-beamed time domain signal containing modulation information Fourier transform to frequency domain , we get [0,f th ]Hz DEMON spectrum; suppress the noise in the DEMON spectrum to the vicinity of the continuous spectrum and highlight the signal; remove the noise according to the distribution law of the noise spectrum in the DEMON spectrum to achieve the effect of enhancing the target line spectrum; set the dynamic threshold and use the 3σ principle to extract the DEMON line spectrum sequence.

[0163] In this embodiment, the DEMON line spectrum and the corresponding line spectrum sequence are obtained by processing the array element domain data collected by the receiving array, which is suitable for underwater acoustic data processing in the underwater acoustic field.

[0164] In one embodiment, after matching the DEMON line spectrum with a pre-built recognition template and determining the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum based on the matching results, the shaft frequency extraction method also includes: obtaining propeller parameters corresponding to the array element domain data based on the shaft frequency and its harmonic sequence analysis.

[0165] Propeller parameters include parameters such as the propeller main shaft's rotational frequency, number of blades, and blade frequency. Optionally, the propeller main shaft's rotational frequency can be derived from the shaft frequency, and the propeller blade number can be derived from the harmonic sequence. In this embodiment, the propeller parameters accurately derived from the shaft frequency and its harmonic sequence are less susceptible to noise and have high accuracy.

[0166] In one embodiment, a method for shaft frequency extraction and harmonic determination based on DEMON spectra is provided. The method includes: performing frequency-domain beamforming on the time-domain data of each array element channel, demodulating the low-frequency modulation spectrum information in the mid- and high-frequency bands using DEMON spectrum extraction techniques, and performing line spectrum extraction to obtain a DEMON line spectrum sequence. A harmonic sequence template for all possible shaft frequencies is generated and matched with the widened and interpolated DEMON line spectrum. Based on the matching degree, the harmonic sequence of all shaft frequencies is obtained. Finally, the same target and targets with a frequency multiplication relationship are merged to screen out the final target shaft frequency feature. Figure 3 A flow chart of the shaft frequency extraction and harmonic determination method based on the DEMON spectrum in this embodiment is provided, as shown in FIG. Figure 3 Shown, including:

[0167] Step S301: Acquire a line spectrum sequence.

[0168] Optionally, collect the raw data of a fiber optic passive sonar towed array sea trial array element, with a sampling rate of 32kHz and 192 array elements; preprocess, beamform and demodulate the array domain data, and extract the line spectrum to obtain the DEMON line spectrum, including: beamforming the noise signal radiated by the underwater target received by the receiving array, picking out the beam X of interest t (n), represents the time domain signal of this beam at this moment t; the signal Xt (n) FFT transforms to the frequency domain, in [f l ,f h ] frequency band is used for bandpass filtering in the frequency domain. The frequency domain signal after bandpass filtering is inversely transformed into the time domain, and then the absolute value detection of the signal is performed to obtain the time domain signal Y t (n); the time domain signal Y t (n) FFT transforms to the frequency domain and feeds into a Butterworth low-pass filter with a cutoff frequency of f T , get the modulated frequency domain signal Y t (ω); use the DEMON spectrum analysis method to fit its continuous spectrum and extract the line spectrum to obtain the DEMON line spectrum sequence. Figure 4 A schematic diagram of the DEMON line spectrum is provided, such as Figure 4 As shown, the line spectrum resolution is 0.1 Hz.

[0169] Step S302: Merge the line spectrum sequences. n (N ordered line spectra) are preliminarily merged. The merging principle is as follows: merge the line spectrum clusters with a line spectrum frequency greater than 2 Hz and an interval less than or equal to one spectrum resolution into a single line spectrum, and retain the line spectrum with the largest amplitude in the line spectrum cluster. The line spectrum sequence f is obtained. m (M ordered line spectra). Figure 4 Taking the DEMON line spectrum as an example, there are 61 DEMON line spectrums in total, and after merging, 51 line spectrum sequences are left.

[0170] Step S303: Calculate the difference frequency array. m Find the difference frequency F between each other i,j :F i,j =f i -f j ,i,j=1,2,…M;i>j. Arrange the difference frequency array elements from small to large to obtain the difference frequency array {F i,j}.

[0171] Step S304, obtain the axis frequency array {F shaft}: Arrange the difference frequency array and all the combined line spectrum sequences from small to large, and use them as all possible first harmonic frequencies to obtain the axis frequency array {F shaft}.

[0172] Continue to refer to Figure 4 DEMON line spectrum: If M is 51, then the difference frequencies of the 51 combined line spectrum sequences are calculated and arranged from small to large to obtain the difference frequency array {F i,j}438 groups. Get the axis frequency array with a resolution of 0.01Hz {F shaft}, a total of 9198 groups.

[0173] Step S305: interpolate and widen the original DEMON line spectrum. Interpolate the original DEMON line spectrum frequency by 2 times, increase the spectrum resolution from 0.1Hz to 0.05Hz, and then widen the frequency of the DEMON line spectrum to the left and right. , L = 1, 2, ... 8. Among them, the resolution of the improved DEMON line spectrum is greater than the resolution of the axis frequency array. It is understandable that the resolution of the DEMON line spectrum frequency can also be increased to other values ​​besides 0.05 Hz.

[0174] Step S306, generate an axis frequency array harmonic sequence template {M i}. The axis frequency array harmonic sequence template is the identification module in the above embodiment. shaft Each frequency f in i , calculate the line spectrum frequencies of the first 16 orders and obtain the axis frequency sequence f i The harmonic cluster spectrum {F i,h}; Use Gaussian distribution waveform as filter to convolve harmonic cluster spectrum {F i,h}, get the axis frequency array harmonic sequence template {M i}. Optionally, use a width of indivual The Gaussian distribution waveform is used as a filter to convolve the harmonic cluster spectrum {F i,h}, get the axis frequency array harmonic sequence template {M i}. The resolution of the harmonic sequence template is . Figure 5 This is a harmonic sequence template with a shaft frequency of 4.47 Hz in this embodiment.

[0175] Step S307, calculate the interpolation and broadening of the DEMON line spectrum and the sequence template {M i}. The DEMON line spectrum after interpolation and broadening is compared with the template sequence {M i}Do the inner product to get the axis frequency matching degree sequence {q n}, Figure 6 Schematic diagram of the axis frequency matching sequence.

[0176] Step S308, calculate the number of peaks and peak positions of the axis frequency matching sequence, determine the axis frequency matched by the axis frequency array, and calculate the integrity sequence. n}, the peak value, number of peaks, and peak position, a total of 125 peaks. If the number of peaks is greater than 0, it means that it matches the harmonic, and then the frequency of the first 16 harmonics is determined. Statistical axis frequency array {F shaft Each axis frequency f i The number of the first 16 harmonics matched is used as a sequence to measure the integrity of the harmonics.n}. Delete s n Shaft frequency sequence less than 0.5 Hz.

[0177] Step S309, calculate the quality factor. n} multiplied by the integrity sequence {s n}, get the quality factor According to the quality factor m n Sort the axis frequency sequence, m n The larger the value, the more likely this shaft frequency is the target's characteristic shaft frequency. Delete the shaft frequency sequences with quality factors less than 3σ. This yields three target shaft frequencies: 1.49Hz, 2.24Hz, and 4.47Hz. Figure 7 Schematic diagram of the quality factor in this embodiment.

[0178] Step S310 , merging the axis frequency sequence of the same target and the axis frequency sequences in a multiple relationship.

[0179] Subtract the two shaft frequency sequences to obtain the shaft frequency difference sequence:

[0180] ;

[0181] If S i,j ≤0.1Hz, the harmonic sequences of the two shaft frequencies are determined. If more than half of the harmonic sequences are consistent, they are determined to be the same target, and only s is retained. n Larger shaft frequency.

[0182] Taking the quotient of the two axial frequency sequences, we can get the remainder sequence of the multiplied frequencies:

[0183] ;

[0184] K is The rounded value of D i,j ≤0.1Hz, it is considered that there is a frequency multiplication relationship between the two shaft frequencies, and then the harmonic sequence is determined. If Kf j The harmonic sequence of f i If more than half of the harmonic sequences are consistent, only s n A larger shaft frequency. 2.24Hz and 4.47Hz have a frequency multiplication relationship, and the 4.47Hz shaft frequency has a higher quality factor, so the 4.47Hz shaft frequency is retained.

[0185] The resulting shaft frequency and its harmonic sequence {F shaft This is the target feature recognition result based on the DEMON line spectrum. As shown in Table 1, the DEMON line spectrum contains the shaft frequencies and harmonic sequences of two targets, 1.49 Hz and 4.47 Hz, respectively.

[0186] Table 1: Final shaft frequency characteristics

[0187]

[0188] In this embodiment, the resolution of the axial frequency matching is improved by expanding the axial frequency array; the tolerance to phenomena such as Doppler frequency shift is improved by widening the DEMON line spectrum sequence and performing Gaussian convolution; the axial frequencies and their harmonic sequences of multiple targets are retained through matching degree sorting, greatly improving the accuracy and robustness of axial frequency feature extraction.

[0189] The method in this embodiment can be used for propeller identification. The continuous spectrum in propeller noise is modulated by the propeller shaft frequency and blade frequency and contains information about the propeller's structural characteristics. DEMON spectrum extraction has a clear, stable, and separable physical meaning and does not require prior information. Therefore, DEMON analysis (Detection of Envelope Modulation on Noise) can be used to demodulate the high-frequency continuous spectrum and extract the ultra-low-frequency line spectrum, including the shaft frequency and its harmonic components.

[0190] Based on the same inventive concept, the present application also provides a shaft frequency extraction system for implementing the shaft frequency extraction method mentioned above. The implementation solution provided by this system is similar to the implementation solution described in the above method, so the specific limitations in one or more shaft frequency extraction system embodiments provided below can be found in the above limitations on the shaft frequency extraction method, and will not be repeated here.

[0191] In one embodiment, Figure 8 As shown, a shaft frequency extraction system is provided, which includes: a receiving array and a processing device; the receiving array includes a sonar array, a buoy, a buoy and a detection payload, and the sonar array includes one or more of the following: a towed linear array, a shore-based array, a conformal array, a planar array, and a bow array; wherein the receiving array is used to obtain array element domain data of the acquisition source; the processing device is used to implement the steps in the above-mentioned method embodiments.

[0192] Optionally, the processing device includes, but is not limited to, a signal processing algorithm module, an AI accelerated computing algorithm module, and a heterogeneous computing scheduling system. The steps in the above-described method embodiments are collaboratively performed by the signal processing algorithm module, the AI ​​accelerated computing algorithm module, and the heterogeneous computing scheduling system. Optionally, the processing device can be provided on a signal processing service platform, with the heterogeneous computing servers and AI computing acceleration chips on the signal processing service platform providing computing power for the execution of the processing device.

[0193] Each module in the above-mentioned shaft frequency extraction system can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0194] Based on the same inventive concept, an embodiment of the present application further provides a shaft frequency extraction device for implementing the shaft frequency extraction method involved above. The implementation solution provided by this device is similar to the implementation solution described in the above method, so the specific limitations in one or more shaft frequency extraction device embodiments provided below can be found in the above limitations on the shaft frequency extraction method, and will not be repeated here.

[0195] In one embodiment, Figure 9 A schematic diagram of a shaft frequency extraction device is provided, such as Figure 9 As shown, the shaft frequency extraction device includes: a difference frequency processing module, a shaft frequency processing module, a harmonic calculation module and a matching module.

[0196] Among them, the difference frequency processing module is used to obtain the DEMON line spectrum and the line spectrum sequence of the DEMON line spectrum according to the array element domain data to be identified, and obtain the difference frequency array according to the frequency difference between each two line spectra in the line spectrum sequence; the axial frequency processing module is used to broaden the frequency range corresponding to each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum, and reduce the frequency interval between each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum to obtain the axial frequency array; the harmonic calculation module is used to calculate the harmonics of different orders corresponding to each axial frequency in the axial frequency array to obtain multiple harmonic cluster spectra; the matching module is used to match the DEMON line spectrum with the pre-constructed recognition template, and determine the axial frequency frequency and its harmonic sequence corresponding to the DEMON line spectrum according to the matching results; wherein, the recognition template is constructed based on the harmonic cluster spectrum.

[0197] In one embodiment, the shaft frequency extraction device further includes a template processing module for performing convolution processing on the harmonic cluster spectra according to the signal conforming to the Gaussian distribution before matching the DEMON line spectrum with the pre-built recognition template to obtain multiple recognition templates.

[0198] In one embodiment, before matching the DEMON line spectrum with a pre-built recognition template, the harmonic calculation module executes the method further comprising: interpolating the DEMON line spectrum; and adjusting the resolution of the harmonic cluster spectrum so that the resolution of the harmonic cluster spectrum is consistent with the resolution of the DEMON line spectrum obtained after the interpolation. Optionally, before adjusting the resolution of the harmonic cluster spectrum so that the resolution of the harmonic cluster spectrum is consistent with the resolution of the DEMON line spectrum obtained after the interpolation, the harmonic calculation module executes the method further comprising: widening the upper and lower limits of the frequency range of the DEMON line spectrum by a specified multiple of the resolution.

[0199] In one embodiment, the matching module matches the DEMON line spectrum with a pre-built recognition template, and determines the axial frequency and its harmonic sequence corresponding to the DEMON line spectrum based on the matching result, including: calculating the inner product of the DEMON line spectrum and the sequences in multiple recognition templates respectively to obtain a matching degree sequence corresponding to each recognition template; obtaining an integrity sequence corresponding to each recognition template based on the number and frequency position of peak signals in the matching degree sequence; and determining the axial frequency and its harmonic sequence corresponding to the DEMON line spectrum based on the matching degree sequence and the corresponding integrity sequence.

[0200] Optionally, the matching module obtains an integrity sequence corresponding to each identification template based on the number and frequency position of peak signals in the matching degree sequence, including: when the number of peak signals is not zero, obtaining the frequency position; when the frequency position and the resolution satisfy a multiple relationship, using the frequency corresponding to the peak as the harmonic of the axial frequency corresponding to the identification template; when the frequency position and the resolution do not satisfy a multiple relationship, obtaining the distance between the peak and multiple multiple values ​​of the resolution, and using the frequency corresponding to the peak with the closest distance as the harmonic of the axial frequency corresponding to the identification template; and obtaining the integrity sequence based on the number of harmonics obtained by matching.

[0201] In one embodiment, the axial frequency processing module broadens the frequency range corresponding to each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum, including: subtracting the resolution of the DEMON line spectrum from the frequency value of each element in the difference frequency array to obtain the lower limit of the frequency value of each element; increasing the resolution of the DEMON line spectrum based on the frequency value of each element in the difference frequency array to obtain the upper limit of the frequency value of each element.

[0202] In one embodiment, the axial frequency processing module reduces the frequency intervals between the difference frequencies in the difference frequency array based on the resolution of the DEMON line spectrum, including: obtaining a step size based on the resolution of the DEMON line spectrum; inserting elements between the difference frequencies in the difference frequency array based on the step size, so that the frequency intervals of the difference frequency array after the inserted elements are reduced. In one embodiment, the array element domain data collected by the receiving array is obtained; the array element domain data is converted into synthetic wave data and the synthetic wave data is demodulated; the demodulated synthetic wave data is Fourier transformed to obtain a DEMON spectrum; and the line spectrum in the DEMON spectrum is extracted to obtain a DEMON line spectrum and a line spectrum sequence.

[0203] Each module in the shaft frequency extraction device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0204] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 10 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface, the display unit and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a shaft frequency extraction method is implemented. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device, etc. The input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse, etc.

[0205] Those skilled in the art will understand that Figure 10The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0206] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0207] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0208] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0209] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0210] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0211] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A shaft frequency extraction method, characterized in that: The method comprises: Obtaining a DEMON line spectrum and a line spectrum sequence of the DEMON line spectrum according to the array element domain data to be identified, and obtaining a difference frequency array according to the frequency difference between every two line spectra in the line spectrum sequence; Broadening the frequency range corresponding to each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum, and reducing the frequency interval between each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum, to obtain an axis frequency array; Calculating harmonics of different orders corresponding to each axis frequency in the axis frequency array to obtain multiple harmonic cluster spectra; Match the DEMON line spectrum with a pre-constructed recognition template, and determine the axial frequency and its harmonic sequence corresponding to the DEMON line spectrum according to the matching result; wherein the recognition template is constructed based on the harmonic cluster spectrum; match the DEMON line spectrum with a pre-constructed recognition template, and determine the axial frequency and its harmonic sequence corresponding to the DEMON line spectrum according to the matching result, including: separately judging whether the DEMON line spectrum is similar to multiple recognition templates, and obtaining the degree of matching between the DEMON line spectrum and multiple recognition templates; sorting the multiple recognition templates according to the matching degree, and obtaining the axial frequency and its harmonic sequence of one or more recognition templates that are ranked higher based on the order of the matching degree from high to low.

2. The shaft frequency extraction method according to claim 1, characterized in that: Before matching the DEMON line spectrum with a pre-built recognition template, the method further includes: interpolating the DEMON line spectrum; The resolution of the harmonic cluster spectrum is adjusted so that the resolution of the harmonic cluster spectrum is consistent with the resolution of the DEMON line spectrum obtained after interpolation processing.

3. The shaft frequency extraction method according to claim 2, characterized in that: Before adjusting the resolution of the harmonic cluster spectrum so that the resolution of the harmonic cluster spectrum is consistent with the resolution of the DEMON line spectrum obtained after interpolation processing, the method further includes: The upper limit and lower limit of the frequency range of the DEMON line spectrum are respectively widened by a specified multiple of resolution.

4. The shaft frequency extraction method according to claim 1, characterized in that: Matching the DEMON line spectrum with the recognition template, and determining the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum according to the matching result, including: Calculating the inner products of the DEMON line spectrum and the sequences in the plurality of recognition templates respectively to obtain a matching degree sequence corresponding to each recognition template; According to the number and frequency positions of the peak signals in the matching degree sequence, an integrity sequence corresponding to each of the identification templates is obtained; wherein, when the number of the peak signals is not zero, the frequency position is obtained; when the frequency position satisfies a multiple relationship with the resolution, the frequency corresponding to the peak is used as a harmonic of the shaft frequency corresponding to the identification template; when the frequency position does not satisfy a multiple relationship with the resolution, the distance between the peak and multiple multiple values ​​of the resolution is obtained, and the frequency corresponding to the peak with the closest distance is used as a harmonic of the shaft frequency corresponding to the identification template; the integrity sequence is obtained according to the number of the harmonics obtained by matching; According to the matching degree sequence and the corresponding integrity sequence, the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum are determined.

5. The shaft frequency extraction method according to claim 1, characterized in that: Before matching the DEMON line spectrum with a pre-built recognition template, the method further includes: The harmonic cluster spectra are respectively convolved according to the signal conforming to the Gaussian distribution to obtain a plurality of the recognition templates.

6. The shaft frequency extraction method according to claim 1, characterized in that: Broadening the frequency range corresponding to each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum includes: Subtracting the resolution of the DEMON line spectrum from the frequency value of each element in the difference frequency array to obtain a lower limit of the frequency value of each element; The resolution of the DEMON line spectrum is increased based on the frequency value of each element in the difference frequency array to obtain the upper limit of the frequency value of each element.

7. The shaft frequency extraction method according to claim 1, characterized in that: Reducing the frequency interval between each difference frequency in the difference frequency array according to the resolution of the DEMON line spectrum includes: Obtaining a new frequency interval according to the resolution of the DEMON line spectrum; Elements are added between the difference frequencies of the difference frequency array based on the new frequency interval, so that the frequency interval of the difference frequency array after the added elements is reduced.

8. The shaft frequency extraction method according to claim 1, characterized in that: The receiving array includes a sonar array, a buoy, a buoy, and a detection payload. The sonar array includes one or more of the following: a towed linear array, a shore-based array, a conformal array, a planar array, and a bow array. A DEMON line spectrum and a line spectrum sequence of the DEMON line spectrum are obtained based on the array element domain data to be identified, including: Obtaining array element domain data collected by the receiving array; Converting the array element domain data into synthetic wave data, and demodulating the synthetic wave data; Performing Fourier transform on the demodulated synthetic wave data to obtain a DEMON spectrum; The line spectrum in the DEMON spectrum is extracted to obtain the DEMON line spectrum and the line spectrum sequence.

9. The shaft frequency extraction method according to claim 1, characterized in that: After matching the DEMON line spectrum with a pre-built recognition template and determining the shaft frequency and its harmonic sequence corresponding to the DEMON line spectrum according to the matching result, the shaft frequency extraction method further includes: The propeller parameters corresponding to the array element domain data are obtained based on the shaft frequency and its harmonic sequence analysis.

10. A shaft frequency extraction system, characterized in that: The system includes: a receiving array and a processing device; the receiving array includes a sonar array, a buoy, a buoy and a detection payload, and the sonar array includes one or more of the following: a towed linear array, a shore-based array, a conformal array, a surface array, and a bow array; wherein, The receiving array is used to obtain array element domain data of the acquisition source; The processing device is used to implement the method according to any one of claims 1 to 9.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

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