A method for sparse decomposition of catenary non-stationary vibration signals

Abstract

The present application relates to the technical field of signal processing, and provides a kind of catenary non-stationary vibration signal sparse decomposition method, the method comprises: collecting impact vibration response signal, and carrying out denoising pretreatment;Establish parametric impact response atom model, and construct over-complete parametric atom dictionary;Using matching pursuit algorithm and combining sparse decomposition algorithm, obtain a series of linear combination of sparse atom components;According to the best matching atom set and its corresponding parameter vector obtained in iteration process, the incident wave component set and the reflected wave component set are obtained, and the decoupled incident wave signal and reflected wave signal are reconstructed.The present application realizes the accurate separation and reconstruction of rigid catenary mixed vibration waveform by constructing over-complete parametric atom library containing frequency modulation factor, combined with matching pursuit algorithm.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, specifically to a non-stationary vibration signal processing method for fault diagnosis of rigid contact wires, which is particularly suitable for sparse representation and feature analysis of pantograph-catenary impact response signals. Background Technology

[0002] Rigid overhead contact lines, with their compact structure and high current-carrying capacity, are widely used in tunnel sections of subways and high-speed railways. However, due to the high bending stiffness of their busbars, the system exhibits significant beam-like vibration characteristics during operation. When the pantograph passes over uneven surfaces or experiences a momentary impact, the resulting vibration waves propagate along the busbars, accompanied by significant dispersion. During this process, the propagation speed of high-frequency components is often higher than that of low-frequency components, causing the wave packets to gradually spread in the time domain and the waveform to become distorted. This poses a challenge to the accurate analysis and condition identification of vibration signals.

[0003] Currently, common methods for processing overhead contact line vibration signals include Fast Fourier Transform (FFT), Wavelet Transform (WFT), and Variational Mode Decomposition (VMD). While FFT effectively reveals the frequency domain characteristics of the signal, it cannot provide information on the distribution of frequency components over time, making it difficult to characterize transient impacts and propagation processes. Wavelet Transform compensates for this deficiency to some extent through time-frequency localization analysis, but it relies on pre-selected basis functions. When faced with complex impact waveforms and dispersion modulation effects in rigid overhead contact lines, its adaptive capability is limited, and its analytical accuracy is easily constrained. VMD has made progress in solving mode aliasing problems through adaptive mode extraction, but it is essentially based on the narrowband assumption. For broadband linear frequency modulated signals caused by dispersion in rigid overhead contact lines, this method often struggles to accurately separate the components. Furthermore, VMD requires pre-setting the number of modes, which can easily lead to over-decomposition or under-decomposition due to improper parameter selection in practical applications, affecting the reliable extraction of features.

[0004] In summary, existing signal processing methods still have significant limitations when dealing with complex vibration signals in rigid contact networks characterized by multi-wave reflection aliasing and accompanying dispersion distortion. Therefore, there is an urgent need to develop a new method capable of adaptively capturing dispersion characteristics and achieving high-precision sparse decomposition to improve the accuracy and reliability of vibration signal analysis and condition monitoring of rigid contact networks. Summary of the Invention

[0005] To address the above issues, this invention constructs a fully-featured parameterized atom library containing frequency modulation factors and combines it with a matching pursuit algorithm to achieve precise separation and reconstruction of the aliased vibration waveform of rigid contact wires.

[0006] According to an embodiment of the present invention, a method for sparse decomposition of non-stationary vibration signals of overhead contact lines is provided.

[0007] In a first aspect of the invention, a method for sparse decomposition of non-stationary vibration signals of overhead contact lines is provided. The method includes: Step S01: Acquire the impact vibration response signal by using an accelerometer array installed on the rigid contact wire busbar, and perform noise reduction preprocessing; Step S02: Based on the physical mechanism of wave propagation in rigid contact wires, establish a parameterized impact response atomic model, and construct a complete parameterized atomic dictionary by setting the parameter value range; Step S03: Using the matching pursuit algorithm, find the best matching atom with the highest matching degree to the current residual signal within the set parameter value range. Update the residual signal according to the best matching atom and repeat the matching pursuit algorithm until the iteration termination condition is met, and obtain a linear combination of a series of sparse atomic components. Step S04: Based on all the best matching atom sets and their corresponding parameter vectors obtained during the iteration process, obtain the incident wave component set and the reflected wave component set, and reconstruct the decoupled incident wave signal and reflected wave signal.

[0008] Furthermore, the specific steps of step S02 are as follows: Step S021: Based on the physical mechanism of wave propagation in rigid contact wires, establish a parameterized atomic model of impact response. : , In the formula, This is the parameter vector used to define atoms; The amplitude coefficient of the atom; It is the time shift factor; It is the attenuation factor; The center frequency; Frequency modulation factor; For time variables; Step S022: Set the value range of each parameter in the parameterized impact response atomic model and construct a complete parameterized atom dictionary.

[0009] Furthermore, the specific steps of step S03 are as follows: Step S031: Initialize residual signal , The preprocessed impact vibration response signal; the current iteration number is set. ; Step S032: Construct the fitness function : , in, No. The residual signal obtained after the next iteration; Step S033: Use an optimization algorithm to search within the parameter space for a fitness function that satisfies the given condition. The largest optimal parameter vector ,Right now: ; Step S034: Substitute the searched optimal parameter vector into the atomic model to generate the first... The best matching atom in the next iteration ; Step S035: Subtract the first from the current residual signal The projection component of the best-matching atom onto the signal in the next iteration updates the residual signal: ; Step S036: Calculate the energy ratio of the current residual signal. : ; Step S037: Determine if the iteration termination condition is met: If Less than the preset energy threshold or number of iterations Reaching the preset maximum number of iterations If the iteration stops, then stop; otherwise, let Continue with steps S033-S034.

[0010] Furthermore, the specific steps of step S033 are as follows: Step S0331: For the current residual signal Perform Hilbert transform to extract the envelope, and obtain the peak time of the envelope as the time shift factor. The initial estimate is obtained; an FFT transform is performed on the residual signal to obtain the peak frequency of the spectrum as the center frequency. The initial estimate; Step S0332: Using the coarse estimate as the initial value, use the optimization algorithm to adjust the amplitude coefficient. Attenuation factor and frequency modulation factor Perform joint iterative optimization until the fitness function is found. convergence.

[0011] Furthermore, the specific steps of step S04 are as follows: Step S041: Obtain the set of all best-matching atoms extracted during the iteration process. and its corresponding set of parameter vectors ; Step S042: Based on the time shift factor in the parameter vector Perform temporal clustering of atoms; set a time threshold. , time shift factor Located in the interval The atoms within are categorized into the set of incident wave components, and the time shift factor is... Located in the interval The atoms within are classified as a set of reflected wave components. This is the predicted value for the initial time of the incident wave. This is the predicted value for the start time of the reflected wave.

[0012] Step S043: Linearly superimpose the atoms in the incident wave component set and the reflected wave component set respectively to reconstruct the decoupled incident wave signal. and reflected wave signal : , , in, and These are sets of indices for atoms representing incident and reflected waves, respectively. These are the corresponding projection coefficients.

[0013] Furthermore, it also includes step S05: utilizing the separated incident wave signal and reflected wave signal Calculate the reflection coefficient at the positioning support of the rigid contact wire to assess the constraint state of the positioning support structure or diagnose structural faults.

[0014] In a second aspect of the invention, an apparatus for sparse decomposition of non-stationary vibration signals of overhead contact lines is provided. The apparatus includes: Signal acquisition module: used to acquire impact vibration response signals through an array of accelerometers mounted on the rigid contact wire busbar, and to perform noise reduction preprocessing; Model building module: used to build a parameterized impact response atomic model based on the physical mechanism of wave propagation in rigid contact wires, and to construct a complete parameterized atomic dictionary by setting the parameter value range; Sparse decomposition module: Used to find the best matching atom with the highest matching degree to the current residual signal within the set parameter value range using the matching pursuit algorithm. The residual signal is updated according to the best matching atom and the matching pursuit algorithm is repeatedly executed until the iteration termination condition is met, resulting in a linear combination of a series of sparse atom components. Decoupling and Reconstruction Module: This module is used to obtain the incident wave component set and the reflected wave component set based on all the best matching atom sets and their corresponding parameter vectors obtained during the iteration process, and then reconstructs the decoupled incident wave signal and reflected wave signal.

[0015] In a third aspect of the invention, an electronic device is provided. The electronic device includes a memory and a processor, the memory storing a computer program, the processor executing the program to implement the method according to a first aspect of the invention.

[0016] In a fourth aspect of the invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method according to a first aspect of the invention.

[0017] This invention achieves precise separation and reconstruction of the aliased vibration waveform of rigid contact wires by constructing a fully parameterized atom library containing frequency modulation factors and combining it with a matching pursuit algorithm.

[0018] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of the present invention, nor is it intended to restrict the scope of the invention. Other features of the invention will become readily apparent from the following description.

[0019] The beneficial effects of this invention are: 1. The frequency modulation factor is innovatively introduced into the decomposition basis function, which closely matches the dispersion physical mechanism of wave propagation in rigid contact network. This enables the algorithm to more fundamentally describe and capture the diffusion and waveform evolution characteristics of wave packets during propagation, thus laying a more reliable physical foundation for subsequent accurate analysis and fault diagnosis. 2. By adopting the idea of ​​sparse decomposition and iterative optimization, it can gradually and clearly separate independent waveform components from complex signals with severe reflection aliasing and overlapping time and frequency domains. This effectively solves the inherent problem that traditional fixed filters or methods based on narrowband assumptions are difficult to separate overlapping time and frequency signals, and significantly improves the accuracy and resolution of signal component separation. 3. The entire decomposition process is fully adaptive, requiring no pre-setting of the number of modes or decomposition layers. It automatically determines the termination condition of the decomposition based solely on the energy convergence characteristics of the signal itself, fundamentally avoiding over-decomposition or under-decomposition problems caused by human experience intervention, thus enhancing the robustness and engineering practical value of the method. Attached Figure Description

[0020] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent from the accompanying drawings and the following detailed description. Wherein: Figure 1 A flowchart of a method for sparse decomposition of non-stationary vibration signals of a contact network according to an embodiment of the present invention is shown. Figure 2 A schematic diagram of the implementation process according to an embodiment of the present invention is shown; Figure 3A schematic diagram of a rigid contact wire testing apparatus and sensor arrangement according to an embodiment of the present invention is shown; Figure 4 A comparison diagram of the impact vibration response signal before and after preprocessing according to an embodiment of the present invention is shown; Figure 5 A waveform comparison diagram before and after aliasing signal decomposition according to an embodiment of the present invention is shown; Figure 6 A comparison diagram of dispersion waveforms according to an embodiment of the present invention and a conventional VMD decomposition method is shown; Figure 7 A comparison diagram of the time-frequency characteristics of a parameterized impact response atom according to an embodiment of the present invention and a conventional Gabor atom is shown. Figure 8 A block diagram of an apparatus for sparse decomposition of non-stationary vibration signals of a contact network according to an embodiment of the present invention is shown. Figure 9 A schematic diagram of a device for sparse decomposition of non-stationary vibration signals of a contact network according to an embodiment of the present invention is shown. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] According to an embodiment of the present invention, a method for sparse decomposition of non-stationary vibration signals of overhead contact lines is proposed. By constructing an ultra-complete parameterized atom library containing frequency modulation factors and combining it with a matching pursuit algorithm, the method achieves accurate separation and reconstruction of the aliased vibration waveforms of rigid overhead contact lines.

[0023] The principles and spirit of the present invention will be explained in detail below with reference to several representative embodiments.

[0024] Figure 1 This is a schematic flowchart of a method for sparse decomposition of non-stationary vibration signals of overhead contact lines according to an embodiment of the present invention. The method includes: Step S01: Acquire the impact vibration response signal by using an accelerometer array installed on the rigid contact wire busbar, and perform noise reduction preprocessing; Step S02: Based on the physical mechanism of wave propagation in rigid contact wires, establish a parameterized impact response atomic model, and construct a complete parameterized atomic dictionary by setting the parameter value range; Step S03: Using the matching pursuit algorithm, find the best matching atom with the highest matching degree to the current residual signal within the set parameter value range. Update the residual signal according to the best matching atom and repeat the matching pursuit algorithm until the iteration termination condition is met, and obtain a linear combination of a series of sparse atomic components. Step S04: Based on all the best matching atom sets and their corresponding parameter vectors obtained during the iteration process, obtain the incident wave component set and the reflected wave component set, and reconstruct the decoupled incident wave signal and reflected wave signal.

[0025] It should be noted that although the operation of the method of the present invention has been described in a specific order in the above embodiments and figures, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0026] To provide a clearer explanation of the above-mentioned method for sparse decomposition of non-stationary vibration signals of overhead contact lines, a specific embodiment will be used for illustration below. However, it is worth noting that this embodiment is only for better illustrating the present invention and does not constitute an improper limitation of the present invention.

[0027] The following example will further illustrate the method of sparse decomposition of non-stationary vibration signals of overhead contact lines in more detail.

[0028] The implementation process of this embodiment is as follows: Figure 2 As shown. Figure 3 As shown, for a rigid contact wire test bench, an instantaneous impact excitation is applied at position d1. The wave is reflected at the positioning supports (p1~p5), resulting in complex aliased waveforms collected by sensors S1~S8. In order to calculate the reflection coefficient of the positioning supports, the incident wave and the reflected wave at S6 and S7 need to be separated.

[0029] Step S01: Acquire the impact vibration response signal using an accelerometer array installed on the rigid contact wire busbar, and perform noise reduction preprocessing, such as... Figure 4 As shown.

[0030] Step S02: Based on the physical mechanism of wave propagation in rigid contact wires, establish a parameterized impact response atomic model, and construct a complete parameterized atomic dictionary by setting the parameter value range.

[0031] The specific steps are as follows: Step S021: Based on the physical mechanism of wave propagation in rigid contact wires, establish a parameterized atomic model of impact response. Its mathematical expression is: , In the formula, This is the parameter vector used to define atoms; The amplitude coefficient of the atom; This is a time shift factor used to characterize the time center of arrival of the wave packet; The attenuation factor is used to characterize the energy dissipation characteristics of the impact response; The center frequency is used to characterize the main frequency band of the wave packet; The frequency modulation factor is used to characterize the linear frequency drift over time caused by the dispersion effect of the rigid contact wire. It is a time variable.

[0032] Step S022: Set the value range of each parameter in the parameterized impact response atomic model and construct a complete parameterized atomic dictionary to cover the broadband impact response characteristics of rigid contact networks at different frequencies.

[0033] In this embodiment, considering the dispersion characteristics of the rigid bus, the high-frequency components have a fast wave velocity, while the low-frequency components have a slow wave velocity, resulting in a linear frequency modulation characteristic of "high frequency at the beginning, low frequency at the end" in the impulse response. The dictionary atoms are defined as: , In this embodiment, Gaussian envelope is used as the window function. .

[0034] Step S03: Using the matching pursuit algorithm, find the best matching atom with the highest matching degree to the current residual signal within the set parameter value range. Update the residual signal according to the best matching atom and repeat the matching pursuit algorithm until the iteration termination condition is met, and obtain a linear combination of a series of sparse atomic components.

[0035] The specific steps are as follows: Step S031: Initialize residual signal , The preprocessed impact vibration response signal; the current iteration number is set. .

[0036] Step S032: Construct the fitness function This is used to measure the correlation between candidate atoms and the current residual signal, and its expression is: , in, No. The residual signal obtained after the iteration.

[0037] Step S033: Use an optimization algorithm to search within the parameter space for a fitness function that satisfies the given condition. The largest optimal parameter vector ,Right now: .

[0038] Step S034: Substitute the searched optimal parameter vector into the atomic model to generate the first... The best matching atom in the next iteration .

[0039] Step S035: Subtract the first from the current residual signal The projection component of the best-matching atom onto the signal in the next iteration updates the residual signal: .

[0040] Step S036: Calculate the energy ratio of the current residual signal. : .

[0041] Step S037: Determine if the iteration termination condition is met: If Less than the preset energy threshold or number of iterations Reaching the preset maximum number of iterations If the iteration stops, then stop; otherwise, let Continue with steps S033-S034.

[0042] The specific steps of step S033 are as follows: Step S0331: For the current residual signal Perform Hilbert transform to extract the envelope, and obtain the peak time of the envelope as the time shift factor. The initial estimate is obtained; an FFT transform is performed on the residual signal to obtain the peak frequency of the spectrum as the center frequency. The initial estimate.

[0043] Step S0332: Using the coarse estimate as the initial value, use the optimization algorithm to adjust the amplitude coefficient. Attenuation factor and frequency modulation factor Perform joint iterative optimization until the fitness function converges.

[0044] In this embodiment, the sampling frequency is set. f, input signal Acceleration data acquired by sensor S7. Initialize residuals. Number of iterations The best-matching atom is found using algorithms such as Sparrow Search (SSA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA). The fitness function is defined as the absolute value of the cross-correlation coefficient between the atom and the residual. , The SSA algorithm quickly locks down the globally optimal parameter combination through iterative updates of the discoverer, joiner, and watcher. .

[0045] No. In the next iteration, the optimal atom is obtained. Sum of coefficients Update residuals: .

[0046] Set the termination condition as follows: (That is, the residual energy is less than 5%). After 20 iterations, the process stops, resulting in 20 atomic components.

[0047] Step S04: Based on all the best matching atom sets and their corresponding parameter vectors obtained during the iteration process, obtain the incident wave component set and the reflected wave component set, and reconstruct the decoupled incident wave signal and reflected wave signal.

[0048] The specific steps are as follows: Step S041: Obtain the set of all best-matching atoms extracted during the iteration process. and its corresponding set of parameter vectors .

[0049] Step S042: Based on the time shift factor in the parameter vector Perform temporal clustering of atoms; set a time threshold. , time shift factor Located in the interval The atoms within are categorized into the set of incident wave components, and the time shift factor is... Located in the interval The atoms within are classified as a set of reflected wave components. This is the predicted value for the initial time of the incident wave. This is the predicted value for the start time of the reflected wave.

[0050] Step S043: Linearly superimpose the atoms in the incident wave component set and the reflected wave component set respectively to reconstruct the decoupled incident wave signal. and reflected wave signal : , , in, and These are sets of indices for atoms representing incident and reflected waves, respectively. These are the corresponding projection coefficients.

[0051] In this embodiment, the time shift factor of the extracted 20 atoms was analyzed. Set A (incident wave): This corresponds to the time window during which the wave propagates directly from d1 to S7; Set B (reflected wave): The time window corresponding to the wave reflected back to S7 via p4, such as Figure 5 As shown.

[0052] By linearly superimposing the atoms in set A, a pure incident waveform is obtained. By superimposing the atoms in set B, a pure reflected waveform is obtained. .

[0053] Step S05: Utilize the separated incident wave signal and reflected wave signal Calculate the reflection coefficient at the positioning support of the rigid contact wire to assess the constraint state of the positioning support structure or diagnose structural faults.

[0054] Comparing the separated waveform with the theoretical dispersed waveform, it was found that the waveform extracted by this method retains the complete "tail" feature (oscillation caused by dispersion), while the traditional VMD (Variational Mode Decomposition) method exhibits spurious mode splitting at the tail, such as... Figure 6 As shown. Compared with the results of traditional Gabor atom extraction, the rigid mesh waveform obtained by this invention exhibits obvious asymmetry, showing a characteristic of being sparse at the beginning and dense at the end. Its spectral analysis results show a distinct sloping band curve (traditional Gabor atoms produce a horizontal straight line with a fixed frequency), indicating that the method of this invention can effectively preserve the dispersion effect of wave propagation on the rigid mesh, such as... Figure 7 As shown.

[0055] Based on the same inventive concept, this invention also proposes a device for sparse decomposition of non-stationary vibration signals of overhead contact lines. The implementation of this device can be found in the implementation of the method described above, and repeated details will not be elaborated further. Figure 8 As shown, the device 100 includes: Signal acquisition module 101: used to acquire impact vibration response signals through an accelerometer array installed on the rigid contact wire busbar, and to perform noise reduction preprocessing; Model building module 102: used to establish a parameterized impact response atomic model based on the physical mechanism of wave propagation in rigid contact wires, and to build a complete parameterized atomic dictionary by setting the parameter value range; Sparse decomposition module 103: Used to use the matching pursuit algorithm to find the best matching atom with the highest matching degree with the current residual signal within the set parameter value range, update the residual signal according to the best matching atom and repeatedly execute the matching pursuit algorithm until the iteration termination condition is met, and obtain a linear combination of a series of sparse atom components; Decoupling and Reconstruction Module 104: This module is used to obtain the incident wave component set and the reflected wave component set based on all the best matching atom sets and their corresponding parameter vectors obtained during the iteration process, and to reconstruct the decoupled incident wave signal and reflected wave signal.

[0056] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the described module can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0057] like Figure 9 As shown, the device includes a central processing unit (CPU), which can perform various appropriate actions and processes based on computer program instructions stored in read-only memory (ROM) or loaded from storage units into random access memory (RAM). The RAM can also store various programs and data required for device operation. The CPU, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0058] Multiple components in the device are connected to the I / O interface, including: input units such as keyboards and mice; output units such as various types of displays and speakers; storage units such as disks and optical discs; and communication units such as network interface cards (NICs), modems, and wireless transceivers. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0059] The processing unit executes the various methods and processes described above, such as method steps S01 to S04. For example, in some embodiments, method steps S01 to S04 may be implemented as a computer software program tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the device via ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of method steps S01 to S04 described above may be performed. Alternatively, in other embodiments, the CPU may be configured to execute method steps S01 to S04 by any other suitable means (e.g., by means of firmware).

[0060] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload programmable logic devices (CPLDs), and so on.

[0061] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0062] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0063] Furthermore, although the operations are described in a specific order, this should be understood as requiring that such operations be performed in the specific order shown or in sequential order, or requiring that all illustrated operations be performed to achieve the desired result. In certain environments, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the invention. Certain features described in the context of individual embodiments may also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation may also be implemented individually or in any suitable sub-combination in multiple implementations.

[0064] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for sparse decomposition of non-stationary vibration signals of overhead contact lines, characterized in that, The method includes: Step S01: Acquire the impact vibration response signal by using an accelerometer array installed on the rigid contact wire busbar, and perform noise reduction preprocessing; Step S02: Based on the physical mechanism of wave propagation in rigid contact wires, establish a parameterized impact response atomic model, and construct a complete parameterized atomic dictionary by setting the parameter value range; Step S03: Using the matching pursuit algorithm, find the best matching atom with the highest matching degree to the current residual signal within the set parameter value range. Update the residual signal according to the best matching atom and repeat the matching pursuit algorithm until the iteration termination condition is met, and obtain a linear combination of a series of sparse atomic components. Step S04: Based on all the best matching atom sets and their corresponding parameter vectors obtained during the iteration process, obtain the incident wave component set and the reflected wave component set, and reconstruct the decoupled incident wave signal and reflected wave signal.

2. The method for sparse decomposition of non-stationary vibration signals of overhead contact lines according to claim 1, characterized in that, The specific steps of step S02 are as follows: Step S021: Based on the physical mechanism of wave propagation in rigid contact wires, establish a parameterized atomic model of impact response. : ， In the formula, This is the parameter vector used to define atoms; The amplitude coefficient of the atom; It is the time shift factor; It is the attenuation factor; The center frequency; Frequency modulation factor; For time variables; Step S022: Set the value range of each parameter in the parameterized impact response atomic model and construct a complete parameterized atom dictionary.

3. The method for sparse decomposition of non-stationary vibration signals of overhead contact lines according to claim 1, characterized in that, The specific steps of step S03 are as follows: Step S031: Initialize residual signal , The preprocessed impact vibration response signal; the current iteration number is set. ; Step S032: Construct the fitness function : ， in, No. The residual signal obtained after the next iteration; Step S033: Use an optimization algorithm to search within the parameter space for a fitness function that satisfies the given condition. The largest optimal parameter vector ,Right now: ； Step S034: Substitute the searched optimal parameter vector into the atomic model to generate the first... The best matching atom in the next iteration ; Step S035: Subtract the first from the current residual signal The projection component of the best-matching atom onto the signal in the next iteration updates the residual signal: ； Step S036: Calculate the energy ratio of the current residual signal. : ； Step S037: Determine if the iteration termination condition is met: If Less than the preset energy threshold or number of iterations Reaching the preset maximum number of iterations If the iteration stops, then stop; otherwise, let Continue with steps S033-S034.

4. The method for sparse decomposition of non-stationary vibration signals of overhead contact lines according to claim 3, characterized in that, The specific steps of step S033 are as follows: Step S0331: For the current residual signal Perform Hilbert transform to extract the envelope, and obtain the peak time of the envelope as the time shift factor. The initial estimate is obtained; an FFT transform is performed on the residual signal to obtain the peak frequency of the spectrum as the center frequency. The initial estimate; Step S0332: Using the coarse estimate as the initial value, use the optimization algorithm to adjust the amplitude coefficient. Attenuation factor and frequency modulation factor Perform joint iterative optimization until the fitness function is found. convergence.

5. The method for sparse decomposition of non-stationary vibration signals of overhead contact lines according to claim 1, characterized in that, The specific steps of step S04 are as follows: Step S041: Obtain the set of all best-matching atoms extracted during the iteration process. and its corresponding set of parameter vectors ; Step S042: Based on the time shift factor in the parameter vector Perform temporal clustering of atoms; set a time threshold. , time shift factor Located in the interval The atoms within are categorized into the set of incident wave components, and the time shift factor is... Located in the interval The atoms within are classified as a set of reflected wave components. This is the predicted value for the initial time of the incident wave. This is the predicted value for the start time of the reflected wave. Step S043: Linearly superimpose the atoms in the incident wave component set and the reflected wave component set respectively to reconstruct the decoupled incident wave signal. and reflected wave signal : ， ， in, and These are sets of indices for atoms representing incident and reflected waves, respectively. These are the corresponding projection coefficients.

6. The method for sparse decomposition of non-stationary vibration signals of overhead contact lines according to claim 1, characterized in that, It also includes step S05: using the separated incident wave signal and reflected wave signal Calculate the reflection coefficient at the positioning support of the rigid contact wire to assess the constraint state of the positioning support structure or diagnose structural faults.

7. A device for sparse decomposition of non-stationary vibration signals of overhead contact lines, characterized in that, The device implements the method as described in any one of claims 1 to 6, comprising: Signal acquisition module: used to acquire impact vibration response signals through an array of accelerometers mounted on the rigid contact wire busbar, and to perform noise reduction preprocessing; Model building module: used to build a parameterized impact response atomic model based on the physical mechanism of wave propagation in rigid contact wires, and to construct a complete parameterized atomic dictionary by setting the parameter value range; Sparse decomposition module: Used to find the best matching atom with the highest matching degree to the current residual signal within the set parameter value range using the matching pursuit algorithm. The residual signal is updated according to the best matching atom and the matching pursuit algorithm is repeatedly executed until the iteration termination condition is met, resulting in a linear combination of a series of sparse atom components. Decoupling and Reconstruction Module: This module is used to obtain the incident wave component set and the reflected wave component set based on all the best matching atom sets and their corresponding parameter vectors obtained during the iteration process, and then reconstructs the decoupled incident wave signal and reflected wave signal.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 6.

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