A GIS isolating switch mechanism state evaluation method based on laser Doppler global plane vibration measurement

Abstract

The present application relates to a kind of GIS disconnecting switch mechanism state evaluation method based on laser Doppler global plane vibration measurement, belong to GIS disconnecting switch vibration measurement technical field, first, build the GIS disconnecting switch vibration measurement platform based on laser Doppler vibration meter, and adjust the layout of measuring point and vibration meter by operating state and switching state, in combination with GIS disconnecting switch finite element simulation model, obtain the vibration acceleration information of multiple measuring points under normal and fault state;Second, the vibration acceleration information obtained is extracted by EWT and COV-SSI to obtain vibration feature vector;Finally, the vibration characteristic information obtained is processed into state evaluation parameter, and the state evaluation model based on random forest is trained, and the effectiveness of the model is verified by carrying out test.

Description

Technical Field

[0001] This invention belongs to the field of vibration measurement technology for GIS disconnect switches, and relates to a method for assessing the condition of GIS disconnect switch mechanisms based on laser Doppler global surface vibration measurement. Background Technology

[0002] Traditional vibration measurement methods for GIS disconnect switches utilize contact accelerometers, which are mounted on the GIS casing using a clamp-on method. This signal detection method suffers from numerous problems, such as added mass issues, difficulty in installing measurement points, limited frequency response range for high-frequency signals, and susceptibility to electromagnetic interference. In contrast, laser Doppler vibration meters offer a non-contact vibration measurement method. Their all-fiber structure improves the portability, robustness, and anti-interference capabilities of the vibration measurement system, resulting in higher detection accuracy and better performance compared to accelerometer-based methods. Furthermore, this patent employs a multi-measurement point joint analysis approach for state assessment, focusing on key areas prone to failure. It utilizes highly stable Empirical Wavelet Transform (EWT) and Covariance-Driven Random Subspace Identification (COV-SSI) algorithms to extract features from the vibration signals, obtaining vibration characteristic information such as modal frequencies, mode shapes, and modal curvatures. This is crucial for the construction of the vibration database and the accuracy of the state assessment model. Summary of the Invention

[0003] In view of this, the purpose of this invention is to provide a method for assessing the condition of a GIS disconnector mechanism based on laser Doppler global surface vibration measurement.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A method for assessing the condition of a GIS disconnector mechanism based on laser Doppler global surface vibration measurement includes the following steps:

[0006] S1: Build a vibration measurement platform for GIS disconnect switches based on laser Doppler vibration meters, and set up vibration measurement points and laser Doppler vibration meters for the disconnect switch in both operating and open / closed states; acquire vibration acceleration signals under normal and fault states of the switch;

[0007] S2: Model the GIS disconnect switch, conduct transient electromagnetic structure finite element simulation, simulate typical faults in the simulation, and obtain vibration acceleration information of the disconnect switch under normal and fault conditions;

[0008] S3: The vibration acceleration signal obtained by laser Doppler vibration meter and finite element simulation is decomposed by empirical wavelet transform (EWT) to remove noise from the signal;

[0009] S4: Input the vibration information processed by EWT signal into the Covariance-Driven Stochastic Subspace Identification (COV-SSI) algorithm to extract vibration feature information, compare the measured information with the simulation information, and verify the effectiveness of the simulation model.

[0010] S5: Divide the obtained vibration characteristic information into normal state and various fault states, and calculate the state assessment information under fault and normal states.

[0011] S6: Divide the state evaluation information into a training set and a test set. Use the training set to train the random forest state evaluation model and use the test set to verify the effectiveness of the random forest state evaluation model.

[0012] S7: Use a trained random forest state assessment model to assess the state of the GIS disconnector mechanism.

[0013] Furthermore, in step S1, the vibration measurement points are arranged as follows during the operation of the GIS disconnector: vibration measurement point ① is arranged on the insulating basin connected to the stationary contact; vibration measurement points ② and ③ are arranged at the center of the moving and stationary contacts; vibration measurement points ④-⑦ are arranged on the side of the moving contact.

[0014] When the GIS disconnector is opened or closed, the vibration measurement points are arranged as follows: vibration measurement point ① is arranged at the center of the stationary contact; when fully open, vibration measurement points ② and ③ are arranged at the center of the moving contact.

[0015] Furthermore, in step S2, the finite element simulation model includes a metal shell, moving and stationary contacts, moving and stationary guide rods, springs, and an insulating basin; by changing the contact ratio of the moving and stationary contacts, the travel of the moving guide rod, the spring damping coefficient, and the friction at the connection of the moving guide rod, the model simulates poor contact of the disconnecting switch contacts, incomplete closing, spring failure, and mechanism jamming; and obtains the vibration acceleration information of each measuring point in the simulation model under normal and fault conditions.

[0016] Furthermore, step S3 specifically includes the following steps:

[0017] S31: Preprocess the acquired vibration acceleration signal;

[0018] S32: Perform EWT decomposition on the preprocessed signal: Calculate the signal power spectrum using FFT, construct the EWT filter band using an automatic segmentation method, and decompose the signal x at each vibration measurement point. i (t) is decomposed into 8 modes:

[0019]

[0020] Where i is the measurement point number, k is the corresponding IMF component number, and the IMF component reflects the structural response characteristics of different frequency bands;

[0021] S33: Calculate the energy contribution rate for each IMF component:

[0022]

[0023] IMFs with an energy contribution rate of less than 2% will be removed.

[0024] Furthermore, step S4 specifically includes the following steps:

[0025] S41: Reorganize the IMF signals filtered by energy contribution rate into an input matrix, and input the reconstructed matrix into COV-SSI to construct the delay embedding matrix required by SSI.

[0026] S42: Use the COV-SSI algorithm to extract modal parameters, calculate the delay state covariance matrix sequence, construct the Hankel covariance matrix, perform singular value decomposition (SVD) on the matrix, and extract the state matrix A and output matrix C from it. Extract the modal frequency f from matrix A. i Damping ratio ζ i The 30th mode shape vector φ of the vibration acceleration signal at the measuring point is obtained from matrix C. ij , used to represent the relative motion of each measuring point;

[0027] S43: Based on modal shape vector φ ij Modal curvature is calculated using the central difference method:

[0028]

[0029] Where, φ ij Let j be the mode shape at the j-th measurement point in the i-th mode. Let h be the modal curvature value of the j-th vibration measurement point in the i-th mode, and h be the distance between the two vibration measurement points.

[0030] Furthermore, step S5, which involves calculating the state assessment information under fault and normal conditions, specifically includes:

[0031] Calculate the absolute value of the difference between the modal curvature of each vibration measurement point under fault conditions and the modal curvature under normal conditions:

[0032]

[0033] in, For modal curvature difference, and These represent the modal curvatures at each vibration measurement point under normal and fault conditions, respectively.

[0034] Similarly, the modal frequency change Δf at each vibration measurement point under fault and normal conditions is calculated. i Modal damping variation Δζ i And the consistency of the location of the maximum curvature and the multimodal curvature under each state.

[0035] Furthermore, step S6 specifically includes the following steps:

[0036] S61: Divide the state evaluation information calculated in step S5 into a training set and a test set, and use the training set to train the random forest model;

[0037] S62: Use a test set to test the effectiveness of the model, and classify the health level corresponding to the vibration measurement point into normal, warning, minor fault and serious fault to achieve state assessment.

[0038] The beneficial effects of this invention are as follows:

[0039] This patent achieves non-contact detection of vibration signals of GIS disconnect switches by using a laser Doppler vibration meter. Compared with the traditional detection method using accelerometers, it uses a multi-point joint vibration measurement method, which has higher detection accuracy and stability, and greatly improves the judgment accuracy of the condition assessment model.

[0040] This patent uses a combination of EWT and COV-SSI to extract vibration characteristic signals from GIS disconnect switches. Compared with the traditional feature signal extraction method using FDD, the feature extraction algorithm of this patent has stronger non-stationary signal processing capabilities and higher modal recognition accuracy and stability, making it more suitable for multi-point collaborative analysis.

[0041] The vibration signal detection method for GIS disconnect switches based on laser Doppler vibration meter (LDV) proposed in this patent fills the gap in the application of LDV in gas-insulated equipment to a certain extent, broadens the detection methods and means of GIS vibration information, and provides a new research direction for subsequent non-contact detection of the mechanical characteristics of disconnect switches based on GIS vibration signals.

[0042] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0043] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0044] Figure 1 The flowchart shows the condition assessment method for GIS disconnector mechanisms based on laser Doppler global surface vibration measurement.

[0045] Figure 2 This is a schematic diagram of the vibration measurement principle of a laser Doppler vibration meter.

[0046] Figure 3 The arrangement of vibration measurement points and vibration meters during the operation of the GIS disconnect switch;

[0047] Figure 4 The arrangement of vibration measurement points and vibration meters during the opening and closing of the GIS disconnector switch;

[0048] Figure 5 Flowchart of finite element simulation for GIS disconnector switch;

[0049] Figure 6 Flowchart for obtaining vibration characteristic information of GIS disconnect switches;

[0050] Figure 7 Flowchart for training a random forest model;

[0051] Figure 8 This is a flowchart of the GIS disconnector status assessment model based on vibration signals. Detailed Implementation

[0052] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0053] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0054] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0055] Example 1:

[0056] This invention provides a method for assessing the condition of a GIS disconnector mechanism based on laser Doppler full-area surface vibration measurement. The research object is a 220kV GIS disconnector. By using a laser Doppler vibration meter to perform multi-point vibration measurement on the GIS disconnector, the method acquires vibration acceleration signals and extracts vibration characteristic information from multiple measurement points, thereby achieving a condition assessment of the disconnector mechanism. The specific implementation process is as follows: Figure 1 As shown, it includes the following steps:

[0057] Step 1: Construct a vibration measurement platform for GIS disconnect switches based on a laser Doppler vibrometer, and arrange vibration measurement points and laser Doppler vibrometers separately for the disconnect switch's operating state and open / closed state. Acquire vibration acceleration signals under normal and fault conditions of the switch;

[0058] Step 2: Model the GIS disconnect switch and conduct transient electromagnetic structure finite element simulation. Simulate typical faults in the simulation and obtain vibration acceleration information of the disconnect switch under normal and fault conditions.

[0059] Step 3: Perform EWT decomposition on the vibration acceleration signal obtained by laser Doppler vibration meter and finite element simulation to remove noise from the signal;

[0060] Step 4: Input the vibration information processed by EWT signal into COV-SSI and extract vibration feature information: modal frequency, damping ratio, mode shape vector, and modal curvature. Compare the measured information with the simulation information to verify the effectiveness of the simulation model.

[0061] Step 5: Divide the obtained vibration characteristic information into normal state and various fault states, and calculate the state assessment information such as modal curvature difference, modal frequency change, and modal damping change under fault and normal states;

[0062] Step 6: Divide the data into training and test sets. Use the training set to train the random forest state evaluation model and use the test set to verify the effectiveness of the model.

[0063] A laser Doppler vibration meter is a typical optical vibration measuring instrument that achieves non-contact vibration measurement based on the laser Doppler effect and the principle of optical heterodyne interference. For example... Figure 2 As shown, when a laser beam (frequency f0) illuminates the surface of a vibrating object, the reflected beam (the beam being measured) will experience a frequency shift Δf due to the vibration of the object's surface. By detecting this shift, the precise vibration velocity of the object can be obtained. The laser emitted by the vibrometer is split into two beams: one beam illuminates the surface of the object being measured, and the other beam passes through an acousto-optic modulator, where its frequency is raised by a fixed value f. sAs a reference light, the reference light and the light being measured interfere with each other at the light coupler and then enter the balanced detector.

[0064] This patent uses a laser Doppler vibration meter to measure the vibration of GIS disconnect switches, and arranges vibration measurement points and laser Doppler vibration meters for two different situations: disconnect switch operation and opening / closing. Figure 3 The table shows the arrangement of the vibration measurement platform when the switch is in operation. The vibration meter checks the pre-set vibration measurement points one by one. The location of each vibration measurement point is selected when the switch is in operation, as shown in Table 1.

[0065] Because loose fixing bolts on the stationary contact base frequently cause tripping faults, the insulating basin connected to the stationary contact is designated as vibration measurement point ①. Laser vibration measurement points ② and ③ are located at the center of the moving and stationary contacts. Due to the high incidence of contact failures such as contact erosion and poor contact in the disconnecting switch, points ② and ③ are key vibration measurement areas. Vibration measurement points ④-⑦ are all located on the moving contact side. Since the opening and closing of the disconnecting switch is accomplished by the moving guide rod pulling the moving contact, the shielding cover and moving guide rod connected to the moving contact are more prone to mechanical failures than the stationary contact side. Therefore, laser vibration measurement points are set on the moving contact side. The single test duration for vibration measurement points ①-⑦ is 120 seconds, and a total of 3 tests are conducted, with the average value taken.

[0066] Table 1

[0067]

[0068] Figure 4 The diagram shows the arrangement of the vibration measurement platform during the opening and closing of the switch. Since the vibration of the moving and stationary contacts should be the focus during the opening and closing of the switch, the vibration meter is placed at the center of the stationary contact ①, or at the center of the moving contact when the switch is fully open. During the opening and closing of the contacts, the vibration meter can scan the vibration information from the measurement point ② to the measurement point ③, which can better monitor the contact status.

[0069] To obtain the vibration characteristics of GIS disconnect switches under normal and mechanical defect conditions and to construct a simulation database, a multi-field coupled finite element simulation model of the transient electromagnetic structure of the GIS disconnect switch was built. Typical faults of the disconnect switch were simulated to obtain the vibration signal characteristics under typical mechanical defects, and a simulation database was constructed. The specific implementation process is as follows: Figure 5 As shown.

[0070] This patent focuses on a 220kV GIS disconnector switch, using the finite element simulation software Ansys. Given the compact and complex internal structure of the GIS, this patent only analyzes structures closely related to typical disconnector switch faults. Therefore, the simulation model primarily consists of a metal casing, moving and stationary contacts, moving and stationary guide rods, springs, and an insulating basin. By varying the contact ratio of the moving and stationary contacts, the travel distance of the moving guide rod, the spring damping coefficient, and the friction at the connection point of the moving guide rod, the patent simulates poor contact of the disconnector switch contacts, incomplete closing, spring failure, and mechanism jamming. Vibration characteristics of each measuring point in the GIS disconnector switch simulation model under normal and fault conditions are obtained, including vibration waveform, natural frequency, mode shape, modal curvature, energy spectrum characteristics, and time-frequency characteristics. The obtained vibration characteristics are compared with those obtained using a laser Doppler vibration meter to verify the model's effectiveness.

[0071] This patent utilizes Empirical Wavelet Transform (EWT) and Covariance-Driven Stochastic Subspace Identification (COV-SSI) to acquire vibration characteristic information of GIS disconnect switches. EWT, as a non-stationary signal processing method, combines the adaptivity of Empirical Mode Decomposition (EMD) with the mathematical stability of wavelet transform, exhibiting superior signal separation and noise immunity. The COV-SSI algorithm is a method based on Structural System Identification (SSI) theory. It uses environmental vibration data to identify the modal parameters of the structure, extracting these parameters through correlation analysis between the structure's dynamic response and the environmental excitation signal.

[0072] like Figure 6 As shown, the specific implementation steps are as follows:

[0073] Step 1: Use a laser Doppler vibration meter to collect data at 7 vibration measurement points during normal operation of the GIS disconnector switch and 2 vibration measurement points during opening and closing. The sampling frequency is set to 2kHz during normal operation and 2MHz during opening and closing.

[0074] Step 2: Preprocess the collected vibration acceleration signals.

[0075] Step 3: Perform EWT decomposition on the preprocessed signal. Calculate the signal power spectrum using FFT and construct the EWT filter band using an automatic segmentation method. Divide the signal x at each vibration measurement point... i (t) is decomposed into 8 modes:

[0076]

[0077] Where i is the measurement point number and k is the corresponding IMF component number. The IMF component reflects the structural response characteristics of different frequency bands.

[0078] Calculate the energy contribution rate for each IMF component:

[0079]

[0080] Calculate E i,k The aim is to reduce invalid noise modes, lower the computational burden, and improve the accuracy of subsequent COV-SSI mode identification. During calculation, IMFs with an energy contribution rate below 2% are removed.

[0081] Step 4: Reorganize the IMF signals that have been filtered by energy contribution rate into an input matrix, and input the reconstructed matrix into COV-SSI to construct the delay embedding matrix required for SSI.

[0082] Step 5: Use the COV-SSI algorithm to extract modal parameters, calculate the delay state covariance matrix sequence, construct the Hankel covariance matrix, perform singular value decomposition (SVD) on the matrix, and extract the state matrix A and output matrix C from it. Extract the modal frequency f from matrix A. i Damping ratio ζ i The 30th mode shape vector φ of the vibration acceleration signal at the measuring point is obtained from matrix C. ij It represents the relative motion of each measuring point.

[0083] Step 6: Based on the modal shape vector φ ij Modal curvature is calculated using the central difference method:

[0084]

[0085] Where, φ ij Let j be the mode shape at the j-th measurement point in the i-th mode. Let h be the modal curvature value of the j-th vibration measurement point in the i-th mode, and h be the distance between the two vibration measurement points.

[0086] After obtaining vibration characteristic information of the GIS disconnector under normal and fault conditions, the obtained vibration characteristic information is divided into normal state and various fault states. The state assessment information under fault and normal states is calculated, specifically, the absolute value of the difference between the modal curvature of each vibration measurement point under fault state and the modal curvature under normal state is calculated:

[0087]

[0088] in, For modal curvature difference, and These represent the modal curvatures at each vibration measurement point under normal and fault conditions, respectively.

[0089] Similarly, the modal frequency change Δf at each vibration measurement point under fault and normal conditions is calculated. i Modal damping variation Δζ i And the consistency of the location of the maximum curvature and the multimodal curvature under each state.

[0090] The next step is to build a GIS disconnect switch status assessment model.

[0091] Step 1: Divide the obtained state assessment information of multiple vibration measurement points under normal and fault conditions into training and test sets. Use a random forest model to train the training set. The random forest construction process is as follows: Figure 7 As shown.

[0092] Step 2: Input the test set into the training model to test its effectiveness. Classify the health levels corresponding to the vibration measurement points into normal, warning, minor fault, and severe fault to achieve state assessment. Finally, verify the effectiveness of the state assessment model through experimental testing, such as... Figure 8 As shown.

[0093] Example 2:

[0094] An electronic device, comprising a memory and a processor;

[0095] The memory is used to store computer programs;

[0096] The processor is configured to implement the method described in Embodiment 1 when executing the computer program.

[0097] Example 3:

[0098] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in Embodiment 1.

[0099] Example 4:

[0100] A computer program product includes a computer program that, when executed by a processor, implements the method described in Example 1.

[0101] In the above embodiments, the reference to "this embodiment" in the specification indicates that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple appearances of "this embodiment" do not necessarily refer to the same embodiment.

[0102] In the above embodiments, the reference to "this embodiment" in the specification indicates that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple appearances of "this embodiment" do not necessarily refer to the same embodiment.

[0103] In the above embodiments, although the invention has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory structures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed. The embodiments of the invention are intended to cover all such substitutions, modifications, and variations falling within the broad scope of the appended claims.

[0104] As will be understood by those skilled in the art, the computer-readable storage medium described in this embodiment allows for the implementation of all or part of the steps in the above method embodiments by computer program-related hardware. The aforementioned computer program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0105] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver, and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication between them. The memory is used to store computer programs, the communication interface is used to perform communication, and the processor and the transceiver are used to run the computer programs, so that the electronic terminal performs the steps of the above method.

[0106] In this embodiment, the memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0107] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0108] This invention can be used in a wide range of general-purpose or special-purpose computing system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0109] This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for assessing the condition of a GIS disconnector mechanism based on laser Doppler global surface vibration measurement, characterized in that: Includes the following steps: S1: Build a vibration measurement platform for GIS disconnect switches based on laser Doppler vibration meters, and set up vibration measurement points and laser Doppler vibration meters for the disconnect switch in both operating and open / closed states; acquire vibration acceleration signals under normal and fault states of the switch; S2: Model the GIS disconnect switch, conduct transient electromagnetic structure finite element simulation, simulate typical faults in the simulation, and obtain vibration acceleration information of the disconnect switch under normal and fault conditions; S3: Perform Empirical Wavelet Transform (EWT) decomposition on the vibration acceleration signal obtained by laser Doppler vibration meter and finite element simulation to remove noise from the signal; S4: Input the vibration information processed by EWT signal into the COV-SSI algorithm based on covariance-driven random subspace identification to extract vibration feature information, compare the measured information with the simulation information, and verify the effectiveness of the simulation model; S5: Divide the obtained vibration characteristic information into normal state and various fault states, and calculate the state assessment information under fault and normal states. S6: Divide the state evaluation information into a training set and a test set. Use the training set to train the random forest state evaluation model and use the test set to verify the effectiveness of the random forest state evaluation model. S7: Use a trained random forest state assessment model to assess the state of the GIS disconnector mechanism; Step S3 specifically includes the following steps: S31: Preprocess the acquired vibration acceleration signal; S32: Perform EWT decomposition on the preprocessed signal: Use FFT to calculate the signal power spectrum, and construct the EWT filter band using an automatic segmentation method, dividing the signal from each vibration measurement point... x i ( t It is decomposed into 8 modes: in, i Number the measurement points. k The corresponding IMF component is numbered, and the IMF component reflects the structural response characteristics of different frequency bands; S33: Calculate the energy contribution rate for each IMF component: Remove IMFs with an energy contribution rate of less than 2%; Step S4 specifically includes the following steps: S41: Reorganize the IMF signals filtered by energy contribution rate into an input matrix, and input the reconstructed matrix into COV-SSI to construct the delay embedding matrix required by SSI. S42: Use the COV-SSI algorithm to extract modal parameters, calculate the delay-state covariance matrix sequence, construct the Hankel covariance matrix, perform singular value decomposition (SVD) on the matrix, and extract the state matrix from it. A and output matrix C Modal frequencies are extracted from matrix A. f i Damping ratio ζ i , by matrix C The 30th mode shape vector of the vibration acceleration signal at the measurement point was obtained. φ ij , used to represent the relative motion of each measuring point; S43: Based on modal shape vectors φ ij Modal curvature is calculated using the central difference method: in, φ ij For the first i The first mode in the second mode j The mode shapes at each vibration measurement point For the first i The first mode in the second mode j Modal curvature values ​​at each vibration measurement point h The distance between the two vibration measurement points; Step S5, which calculates the state assessment information under fault and normal conditions, specifically includes: Calculate the absolute value of the difference between the modal curvature of each vibration measurement point under fault conditions and the modal curvature under normal conditions: in, For modal curvature difference, and These represent the modal curvatures at each vibration measurement point under normal and fault conditions, respectively. Similarly, the modal frequency change Δ at each vibration measurement point under fault and normal conditions is calculated. f i Modal damping variation Δ ζ i And the consistency of the location of the maximum curvature and the multimodal curvature under each state.

2. The method for assessing the condition of a GIS disconnector mechanism based on laser Doppler global surface vibration measurement according to claim 1, characterized in that: In step S1, the vibration measurement points of the GIS disconnector switch are arranged as follows: vibration measurement point ① is arranged on the insulating basin connected to the stationary contact; vibration measurement points ② and ③ are arranged at the center of the moving and stationary contacts; vibration measurement points ④-⑦ are arranged on the side of the moving contact. When the GIS disconnector is opened or closed, the vibration measurement points are arranged as follows: vibration measurement point ① is arranged at the center of the stationary contact; when fully open, vibration measurement points ② and ③ are arranged at the center of the moving contact.

3. The method for assessing the condition of a GIS disconnector mechanism based on laser Doppler global surface vibration measurement according to claim 1, characterized in that: In step S2, the finite element simulation model includes a metal shell, moving and stationary contacts, moving and stationary guide rods, springs, and an insulating basin. By changing the contact ratio of the moving and stationary contacts, the travel of the moving guide rod, the spring damping coefficient, and the friction at the connection of the moving guide rod, the model simulates poor contact of the disconnecting switch contacts, incomplete closing, spring failure, and mechanism jamming. Vibration acceleration information of each measuring point in the simulation model under normal and fault conditions is obtained respectively.

4. The method for assessing the condition of a GIS disconnector mechanism based on laser Doppler global surface vibration measurement according to claim 1, characterized in that: Step S6 specifically includes the following steps: S61: Divide the state evaluation information calculated in step S5 into a training set and a test set, and use the training set to train the random forest model; S62: Use a test set to test the effectiveness of the model, and classify the health level corresponding to the vibration measurement point into normal, warning, minor fault and serious fault to achieve state assessment.

5. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to, when executing the computer program, implement the GIS disconnector mechanism state assessment method based on laser Doppler global surface vibration measurement as described in any one of claims 1-4.

6. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the GIS disconnector mechanism state assessment method based on laser Doppler global surface vibration measurement as described in any one of claims 1-4.

7. A computer program product, characterized in that: The method includes a computer program that, when executed by a processor, implements the GIS disconnector mechanism condition assessment method based on laser Doppler global surface vibration measurement as described in any one of claims 1-4.

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