A method, system, device and medium for expanding diversity of guided wave signals

Abstract

The present invention discloses a diversity expansion method, system, device and medium for waveguide signals. S1, continuous wavelet transform is performed on the waveguide signal to obtain M groups of scale signals; S2, M groups of amplitude coefficients and frequency coefficients are randomly generated within a specific value range; S3, M groups of new scale signal power spectra are calculated according to the scale signal, the amplitude coefficient and the frequency coefficient; S4, the power spectra of the M groups of new scale signals are calculated by using average scale power, the average power of all new scale signals is calculated, and an expanded wave packet signal of the waveguide signal is obtained; S5, S2-S4 are repeated, various waveguide signals can be expanded, and the expansion has physical meaning and interpretability.

Description

Technical Field

[0001] The invention belongs to the field of digital signal processing and relates to a method, system, equipment and medium for expanding the diversity of waveguide signals. Background Art

[0002] Ultrasonic guided wave technology is widely used in the field of nondestructive testing and structural health monitoring. In the field of nondestructive testing, ultrasonic guided wave testing is applied to pipelines, rails, steel, ships and aircraft. Its common application cases are defect damage location detection of pipelines, wings and rails. Compared with traditional ultrasonic applications, the main advantage of ultrasonic guided waves is that it can apply excitation signals from a fixed probe and collect guided wave signals from other locations to detect a larger range without the need for multi-point scanning, and has the characteristics of long propagation distance and fast propagation speed. Ultrasonic guided waves are formed by superposition interference and geometric dispersion after multiple complex reflections of ultrasonic waves at various interfaces in the medium. Processing the received ultrasonic guided waves and analyzing the structural damage information they carry is an important prerequisite for the application of this technology in the field of nondestructive testing and structural health monitoring.

[0003] At present, there are two main analysis methods for structural health detection using ultrasonic guided waves: analysis through ultrasonic guided wave propagation theory and analysis through machine learning methods. Due to the complex behavior of ultrasonic guided waves on the interface, if the workpiece structure is complex, it is difficult to analyze the received signal through ultrasonic guided wave propagation theory. Therefore, the former method is mainly used for the detection of relatively regular workpieces (plates, tubes, rods, etc.). For workpieces with complex structures (rails, gears, etc.), the latter method is mainly used for detection.

[0004] The training of machine learning models requires a large amount of diverse data to improve the accuracy of fault identification and classification and avoid overfitting. However, ultrasonic guided waves lack diversity in simulation and repeated experiments. In addition, in actual diagnosis scenarios, especially online diagnosis, it is usually difficult to obtain a large amount of fault data from the equipment to be diagnosed in advance. Only a small amount of fault data of a specific device under specific working conditions can be obtained to train the model. Therefore, in order to better apply ultrasonic guided wave technology to structural health detection and non-destructive testing, it is necessary to enhance the diversity of the obtained guided wave signals.

[0005] At present, there are two main methods to enhance the diversity of waveguide signals: 1) Based on the existing data, digital signal processing methods are used to enhance the data to generate diverse data. 2) Diverse data is generated through data generation models such as auto-encoders (AE) and generative adversarial networks (GAN).

[0006] However, the first method can only process relatively simple ideal waveguide signals, and has great limitations in processing waveguide signals obtained in real scenarios. The second method using deep learning cannot be expressed by specific mathematical formulas, but only processes numerically, which has no physical meaning and interpretability. Summary of the invention

[0007] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a method, system, device and medium for expanding the diversity of waveguide signals, which can expand various waveguide signals and have physical meaning and interpretability.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] A method for expanding the diversity of a waveguide signal includes the following steps:

[0010] S1, perform continuous wavelet transform on the waveguide signal to obtain M groups of scale signals;

[0011] S2, randomly generates M groups of amplitude coefficients and frequency coefficients within a specific value range;

[0012] S3, calculating and obtaining M groups of new scale signal power spectra according to the scale signal, amplitude coefficient and frequency coefficient;

[0013] S4, using the average scale power to calculate the power spectrum of the M groups of new scale signals, calculate the average power of all new scale signals, and obtain an expanded wave packet signal of the waveguide signal;

[0014] S5, repeat S2-S4 to obtain an envelope signal with an expanded number of repetitions, thereby completing the diversity expansion of the waveguide signal.

[0015] Preferably, in S1, the M groups of scale signals are recorded as CWT (a i , n), i=1, 2, 3...M, where a i represents the scale number, and n represents the number of signal samples.

[0016] Preferably, in S2, the amplitude coefficient and the frequency coefficient have a value range of 0.4-1.6.

[0017] Preferably, in S3, the scaled signal is transformed in amplitude and frequency according to the amplitude coefficient and the frequency coefficient by using amplitude transformation, FFT and iFFT transformation.

[0018] Furthermore, the power spectrum of the M group of new scale signals The calculation process is:

[0019]

[0020] Among them, CWT (a i , n), i = 1, 2, 3...M is M groups of scale signals, a i is the scale number, n is the number of signal samples, A i is the amplitude coefficient, F i is the frequency coefficient, FFT is the fast Fourier transform, and iFFT is the inverse fast Fourier transform.

[0021] Preferably, in S4, the calculation process of the wave packet signal SAP(n) is:

[0022]

[0023] in, are M groups of new scaled signal power spectra, i = 1, 2, 3…M.

[0024] Preferably, in S1, M represents the resolution of the wavelet signal in the frequency domain, the minimum and maximum scales of the continuous wavelet transform are determined based on the energy extension of the wavelet signal in frequency and time, and an integer value between the minimum and maximum scales is selected as the value of M.

[0025] A diversity expansion system for waveguide signals, characterized in that it comprises:

[0026] A scale signal acquisition module is used to perform continuous wavelet transform on the waveguide signal to obtain M groups of scale signals;

[0027] A coefficient generation module, used for randomly generating M groups of amplitude coefficients and frequency coefficients within a specific value range;

[0028] A scale signal power spectrum calculation module is used to calculate M groups of new scale signal power spectra according to the scale signal, the amplitude coefficient and the frequency coefficient;

[0029] The wave packet signal calculation module is used to calculate the power spectrum of M groups of new scale signals by using the average scale power, calculate the average power of all new scale signals, and obtain an expanded wave packet signal of the waveguide signal;

[0030] The diversity expansion module is used for the repetition coefficient generation module, the scale signal power spectrum calculation module and the wave packet signal calculation module to obtain the envelope signal after the expansion of the number of repetitions, thereby completing the diversity expansion of the waveguide signal.

[0031] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the diversity expansion method of the waveguide signal as described in any one of the above items when executing the computer program.

[0032] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the diversity expansion method of the waveguide signal as described in any one of the above items.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention transforms the amplitude and frequency of the wavelet signal at different frequency scales into diversity under the action of the amplitude coefficient and the frequency coefficient in the process of obtaining the envelope signal of the guided wave. Since the present invention can control the degree of diversity of the expanded signal by controlling the value range of the amplitude coefficient and the frequency coefficient, it has good controllability and stability. In addition, the present invention can expand on more scales with interpretable physical meanings in the digital signal processing method, and introduce more expansion coefficients to increase the interpretability and diversity of the expanded data. Therefore, the present method avoids the problem of insufficient interpretability of the general generation model, is suitable for the diversity amplification of ultrasonic guided wave data, and is not limited by the complexity of the guided wave signal. The envelope signal of the expanded guided wave signal provides support for the establishment of a machine learning diagnostic model for irregular workpieces. An effective data diversity expansion method is provided for the development of digital twin technology in the field of structural health monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A flow chart of the waveguide detection data described in an example of the present invention;

[0036] Figure 2 It is a time domain diagram of the waveguide signal described in the example of the present invention;

[0037] Figure 3 A time-frequency diagram of the waveguide signal described in the example of the present invention after wavelet transformation;

[0038] Figure 4 A is described in the examples of the present invention i ∈[0.6, 1.4], F i = 1, 30 groups of expanded envelope signal diagrams;

[0039] Figure 5 A is described in the examples of the present invention i =1, F i ∈[0.6, 1.4] when 30 groups of expanded envelope signal diagrams;

[0040] Figure 6 A is described in the examples of the present invention i ∈[0.6, 1.4], F i ∈[0.6, 1.4] when 30 groups of expanded envelope signal diagrams;

[0041] Figure 7 A described in the examples of the present invention i and F i The waveguide envelope diagram after expanding 30 groups under three different value ranges. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0043] It should be noted that the words "front", "rear", "left", "right", "up" and "down" used in the following description refer to directions in the drawings, and the words "inside" and "outside" refer to directions toward or away from the geometric center of a specific component, respectively.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0045] like Figure 1 As shown, the method for expanding the guided wave signal described in the present invention can quickly and conveniently expand the ultrasonic guided wave signal.

[0046] First, the continuous wavelet transform (CWT) of the waveguide signal is calculated, and the amplitude and frequency of each scale signal in the continuous wavelet transform of the waveguide signal are changed by introducing the amplitude coefficient and the frequency coefficient. Then, the average scale power (SAP) of the waveguide signal is calculated to obtain the wave packet signal of the waveguide signal. By repeating the above method for many times, multiple wave packets from the same waveguide signal are obtained; wherein the amplitude coefficient and the frequency coefficient are both random values ​​within a certain range, and their number is equal to the number of scale signals in the continuous wavelet transform; each scale signal is a time domain signal corresponding to each frequency taken in the continuous wavelet transform; then, the amplitude coefficient is used to change the amplitude of the scale signal by multiplying each scale signal with the amplitude coefficient; the frequency coefficient is used to change the frequency of the scale signal by multiplying each scale signal with the frequency coefficient in the frequency domain; by averaging the power of each scale signal, a diverse expanded envelope signal of the waveguide signal is obtained; finally, by generating a specific number of amplitude coefficients and frequency coefficients, the corresponding number of expanded signals of the waveguide signal is obtained.

[0047] The expanded envelope signal with the number of repetitions obtained avoids the problem of insufficient interpretability of general generative models, is suitable for diversity amplification of ultrasonic guided wave data, and is not limited by the complexity of the guided wave signal. The expanded envelope signal of the guided wave signal provides support for establishing a machine learning diagnostic model for irregular workpieces.

[0048] The basic process of implementing the method of the present invention is as follows Figure 1 As shown, the following steps are included:

[0049] 1) Perform continuous wavelet transform on the waveguide signal to obtain M groups of scale signals, denoted as CWT(a i , n), i=1, 2, 3...M, where a i represents the scale number, and n represents the number of signal samples.

[0050] M is the number of scale signals, which indicates the resolution of the wavelet signal in the frequency domain and can be selected according to the characteristics of the processed signal. The selection criteria are based on the energy spread of the wavelet signal in frequency and time, and the minimum and maximum scales of the CWT are automatically determined. An integer value between the minimum and maximum scales can be selected as the number of scale signals.

[0051] 2) Randomly generate M groups of amplitude coefficients A within a specific value range i and frequency coefficient F i , i=1,2,3…M。

[0052] Amplitude coefficient A i and frequency coefficient F i Value range: When the two parameters are in the range of [0.4, 1.6], the waveguide signal expansion can achieve better results.

[0053] 3) Using the amplitude coefficient A obtained in 2) i and frequency coefficient F i The corresponding continuous wavelet transform scale signal CWT(a i , n) calculate the following formula to obtain M groups of new scale signal power spectra

[0054]

[0055] FFT is Fast Fourier Transform, which can reduce the number of multiplications when calculating discrete Fourier transform and improve the calculation speed from time domain signal to frequency domain signal. iFFT is Inverse Fast Fourier Transform, which is an algorithm that uses FFT to quickly calculate time domain signal from frequency domain signal.

[0056] 4) The average power of all new scaled signals is calculated using the following SAP calculation formula to obtain an expanded wave packet signal of the waveguide signal.

[0057]

[0058] 5) Repeat steps 2) to 4) N times to obtain N expanded envelope signals. Since the coefficients selected for each expansion are random, the diversity expansion of the waveguide signal can be completed.

[0059] The following is an actual example of the calculation of the above method.

[0060] Step 1: Perform continuous wavelet transform on the ultrasonic guided wave signal S(n) with n sampling points. The Morlet function is used as the wavelet basis in the continuous wavelet transform, and the minimum and maximum scales and the scale number M are automatically determined in Matlab according to the energy propagation of the wavelet in frequency and time. This step obtains the data CWT(a) after S(n) is transformed by continuous wavelet transform. i , n), i = 1, 2, 3 ... M. a i are different scales obtained from continuous wavelet transform. Figure 2 is the time domain diagram of the waveguide signal S(n), Figure 3 is the time-frequency diagram of S(n) after continuous wavelet transform;

[0061] Step 2, in the amplitude coefficient and frequency coefficient ( A , F and The amplitude coefficient A is set i and frequency coefficient F i Within the range of the upper and lower bounds of , randomly select M groups of values;

[0062] Step 3: Substitute the CWT (a) obtained in step 1 i , n), i = 1, 2, 3 ... M and the M groups of amplitude coefficients A obtained in step 2 i and frequency coefficient F i , perform the operation shown in the following formula, and the obtained M groups of new scale signal power spectra are recorded as

[0063]

[0064] Step 4: Use the CWT (a) obtained in step 3 i , n) new , i = 1, 2, 3 ... M, the average power of all new scale signals is calculated by the average scale power (SAP) calculation formula to obtain an expanded envelope signal of the waveguide signal;

[0065]

[0066] Step 5, repeating steps 2 to 4 N times, and by writing a Matlab program, N groups of envelope signals of the same ultrasonic guided wave signal after diversity expansion can be obtained. Figure 4 The expanded 30 sets of waveguide envelope diagrams, A i ∈[0.6, 1.4], F i =1. Figure 5 The expanded 30 sets of waveguide envelope diagrams, A i =1, F i ∈[0.6, 1.4]. Figure 6 The expanded 30 sets of waveguide envelope diagrams, A i ∈[0.6, 1.4], F i ∈[0.6, 1.4]. Figure 7 A i and F i The expansion of 30 groups of waveguide envelope diagrams under three different value ranges demonstrates the stability of the invention in expanding the diversity of waveguide signal data.

[0067] The following are device embodiments of the present invention, which can be used to perform method embodiments of the present invention. For details not disclosed in the device embodiments, please refer to the method embodiments of the present invention.

[0068] In another embodiment of the present invention, a diversity expansion system for a waveguide signal is provided, and the diversity expansion system for a waveguide signal can be used to implement the above-mentioned diversity expansion method for a waveguide signal. Specifically, the diversity expansion system for a waveguide signal includes a scale signal acquisition module, a coefficient generation module, a scale signal power spectrum calculation module, a wave packet signal calculation module and a diversity expansion module.

[0069] The scale signal acquisition module is used to perform continuous wavelet transform on the waveguide signal to obtain M groups of scale signals.

[0070] The coefficient generation module is used to randomly generate M groups of amplitude coefficients and frequency coefficients within a specific value range.

[0071] The scale signal power spectrum calculation module is used to calculate M groups of new scale signal power spectra according to the scale signal, the amplitude coefficient and the frequency coefficient.

[0072] The wave packet signal calculation module is used to calculate the power spectra of M groups of new scale signals by using the average scale power, calculate the average power of all new scale signals, and obtain an expanded wave packet signal of the waveguide signal.

[0073] The diversity expansion module is used in the repetition coefficient generation module, the scale signal power spectrum calculation module and the wave packet signal calculation module to obtain the envelope signal after the expansion of the number of repetitions, thereby completing the diversity expansion of the waveguide signal.

[0074] In another embodiment of the present invention, a terminal device is provided, the terminal device includes a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGAs), or other processors. GateArray, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding functions; the processor described in the embodiment of the present invention can be used for the operation of the diversity expansion method of the waveguide signal, including: S1, performing continuous wavelet transform on the waveguide signal to obtain M groups of scale signals; S2, randomly generating M groups of amplitude coefficients and frequency coefficients within a specific value range respectively; S3, calculating M groups of new scale signal power spectra according to the scale signal, the amplitude coefficient and the frequency coefficient; S4, using the average scale power to calculate the M groups of new scale signal power spectra, calculating the average power of all new scale signals, and obtaining an expanded wave packet signal of the waveguide signal; S5, repeating S2-S4, obtaining the expanded envelope signal of the number of repetitions, and completing the diversity expansion of the waveguide signal.

[0075] In another embodiment, the present invention further provides a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory.

[0076] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the diversity expansion method of the waveguide signal in the above-mentioned embodiment; one or more instructions in the computer-readable storage medium are loaded by the processor and the following steps are executed: S1, continuous wavelet transform is performed on the waveguide signal to obtain M groups of scale signals; S2, M groups of amplitude coefficients and frequency coefficients are randomly generated within a specific value range; S3, M groups of new scale signal power spectra are calculated based on the scale signal, amplitude coefficient and frequency coefficient; S4, the power spectra of the M groups of new scale signals are calculated using the average scale power, the average power of all new scale signals is calculated, and an expanded wave packet signal of the waveguide signal is obtained; S5, S2-S4 is repeated to obtain an expanded envelope signal with the number of repetitions, and the diversity expansion of the waveguide signal is completed.

[0077] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0078] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0079] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0080] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0081] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0082] It should be understood that the above description is for illustration and not for limitation. Many embodiments and many applications beyond the examples provided will be apparent to those skilled in the art upon reading the above description. Therefore, the scope of this patent should not be determined with reference to the above description, but rather with reference to the preceding claims and the full scope of equivalents to which such claims are entitled. For the purpose of comprehensiveness, all articles and references, including disclosures of patent applications and publications, are incorporated herein by reference. The omission of any aspect of the subject matter disclosed herein in the preceding claims is not intended to be a waiver of such subject matter, nor should it be considered that the applicant has not considered such subject matter to be part of the disclosed inventive subject matter.

Claims

1. A method for expanding the diversity of a waveguide signal, characterized in that: The process includes: S1, perform continuous wavelet transform on the waveguide signal to obtain Group scale signal; The group scale signal is denoted as ,in Indicates the scale number, Indicates the number of signal samples; S2, randomly generated within a specific range of values group amplitude coefficients and frequency coefficients; The amplitude coefficient and frequency coefficient range from 0.4 to 1.6; S3, calculated based on the scale signal, amplitude coefficient and frequency coefficient, Set up a new scale signal power spectrum; Specifically: using amplitude transformation, and Transformation: transform the scale signal in amplitude and frequency according to the amplitude coefficient and frequency coefficient; New scale signal power spectrum The calculation process is: in, for Group scale signal, is the scale number, is the number of signal samples, is the amplitude coefficient, is the frequency coefficient, is the fast Fourier transform, is the inverse fast Fourier transform; S4, using the average scale power A new scale signal power spectrum is calculated, and the average power of all new scale signals is calculated to obtain an expanded wave packet signal of the waveguide signal; S5, repeat S2-S4 to obtain an envelope signal with an expanded number of repetitions, thereby completing the diversity expansion of the waveguide signal.

2. The method for expanding the diversity of waveguide signals according to claim 1, characterized in that: In S4, wave packet signal The calculation process is: in, for Set up a new scale signal power spectrum, .

3. The method for expanding the diversity of waveguide signals according to claim 1, characterized in that: In S1, Represents the resolution of the wavelet signal in the frequency domain. The minimum and maximum scales of the continuous wavelet transform are determined based on the energy extension of the wavelet signal in frequency and time. The integer value between the minimum and maximum scales is selected as The value of .

4. A diversity expansion system for waveguide signals, characterized in that: include: A scale signal acquisition module is used to perform continuous wavelet transform on the waveguide signal to obtain M groups of scale signals; The group scale signal is denoted as ,in Indicates the scale number, Indicates the number of signal samples; A coefficient generation module, used for randomly generating M groups of amplitude coefficients and frequency coefficients within a specific value range; The amplitude coefficient and frequency coefficient range from 0.4 to 1.6; A scale signal power spectrum calculation module is used to calculate M groups of new scale signal power spectra according to the scale signal, the amplitude coefficient and the frequency coefficient; Specifically: using amplitude transformation, and Transformation: transform the scale signal in amplitude and frequency according to the amplitude coefficient and frequency coefficient; New scale signal power spectrum The calculation process is: in, for Group scale signal, is the scale number, is the number of signal samples, is the amplitude coefficient, is the frequency coefficient, is the fast Fourier transform, is the inverse fast Fourier transform; The wave packet signal calculation module is used to calculate the power spectrum of M groups of new scale signals by using the average scale power, calculate the average power of all new scale signals, and obtain an expanded wave packet signal of the waveguide signal; The diversity expansion module is used for the repetition coefficient generation module, the scale signal power spectrum calculation module and the wave packet signal calculation module to obtain the envelope signal after the expansion of the number of repetitions, thereby completing the diversity expansion of the waveguide signal.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the diversity expansion method of the waveguide signal as described in any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for expanding the diversity of the waveguide signal as described in any one of claims 1 to 3 are implemented.

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