GIS isolation switch displacement defect diagnosis system based on acoustic signal analysis

Abstract

The GIS isolation switch dislocation defect diagnosis system based on acoustic signal analysis comprises a signal acquisition module which transmits and receives an ultrasonic signal into a three-phase common box type GIS cavity to be tested; the simulation model building module is used for building a standard model of the three-phase common box type GIS through simulation and experimental data; the diagnosis module is used for constructing a spatial spectrum based on the received ultrasonic signals and calculating spatial frequency band energy; calculating the integrating degree of the layout of the isolating switch in the GIS to be tested and the layout of the standard model based on the space coordinates; meanwhile, the effective length of a disconnecting switch contact is calculated, the overall conformity of the GIS to be tested is calculated, and a diagnosis threshold value is obtained based on the overall conformity scaling standard spatial frequency band energy threshold value; if the spatial frequency band energy exceeds the diagnosis threshold value, determining that the disconnecting switch is in an opening state; the system automatically diagnoses whether the actual opening and closing state of the disconnecting switch is consistent with the expectation or not by analyzing the space sound field characteristics of ultrasonic waves after the ultrasonic waves are transmitted in the GIS cavity, so that the dislocation defect is detected.

Description

Technical Field

[0001] This application relates to the field of power equipment condition monitoring and fault diagnosis, and in particular to a GIS disconnector switch displacement defect diagnosis system based on acoustic signal analysis. Background Technology

[0002] Disconnect switches, as a key component of GIS equipment, work in conjunction with circuit breakers to perform switching operations in power systems, changing the operating mode. During maintenance, they isolate energized and de-energized sections, creating a clear disconnection point to ensure the safety of personnel and equipment. During GIS equipment operation, frequent opening and closing of disconnect switches and prolonged service life cause degradation in their mechanical and electrical connection performance, leading to problems such as contact wear, relaxation of contact springs, insufficient conductor insertion depth, and incomplete opening / closing. Among these, disconnect switch misalignment defects pose a significant hazard: due to the invisibility of the internal opening / closing state of the disconnect switch in GIS equipment, inaccurate external status indicators cannot determine whether the disconnect switch is misaligned, resulting in multiple accidents in field applications; the switch indicator may show an open state while the actual disconnect switch is closed, posing a major safety hazard and endangering power system stability and human safety. However, current research on methods for detecting disconnect switch misalignment defects is scarce, and effective and convenient online detection methods are lacking, urgently requiring further research. To address the issues of frequent structural displacement defects in GIS systems and the lack of effective and convenient online detection methods, this study investigates a live-line detection technology for displaced GIS disconnector structures based on ultrasonic signal detection and analysis. A displaced criterion for GIS disconnector structures based on ultrasonic signal detection and analysis is proposed, enabling effective and convenient live-line detection of displaced defects in GIS disconnector structures. Summary of the Invention

[0003] To address the aforementioned technical issues, this application provides a diagnostic system for misalignment defects in GIS disconnect switches based on acoustic signal analysis. The signal acquisition module is responsible for transmitting and receiving ultrasonic signals into and within the three-phase common-enclosure GIS cavity. Specifically, it includes an ultrasonic transmitting unit and an ultrasonic receiving unit. The ultrasonic transmitting unit consists of a signal generator and a first piezoelectric sensor, capable of generating both pulse waves and continuous sine waves. The pulse wave is preferably a Gaussian modulated pulse with a pulse width of 1 to 100 microseconds and a center frequency of 40 kHz to 180 kHz; the continuous sine wave has a frequency range of 40 kHz to 180 kHz and a frequency stability better than 0.1%. The ultrasonic receiving unit consists of a second piezoelectric sensor array and a data acquisition card. Four piezoelectric sensors are fixed to the circumferential surface of the basin-type insulator in a 2×2 grid configuration, forming a spatial array. The data acquisition card supports four-channel synchronous acquisition with a sampling rate of no less than 2 MS / s and an ADC resolution of no less than 16 bits.

[0004] The simulation model building module establishes a standard model through a combination of simulation and experimentation. Based on CAD drawings, this module creates a 1:1 three-dimensional geometric model in COMSOL, configures interfaces for three core physical fields—solid mechanics, pressure acoustics, and piezoelectric effect—and refines the mesh in key areas to ensure the minimum mesh size is less than one-sixth of the wavelength of the highest frequency sound wave. By simulating the ultrasonic wave propagation process under normal opening and closing states, a standard model library including linear and triangular layout models is established, and the standard spatial frequency band energy threshold is determined.

[0005] The diagnostic module is the core of this system. First, it constructs a spatial spectrum and calculates the spatial frequency band energy based on the received ultrasonic signals. This process includes signal time alignment, windowing, Fourier transform, and beamforming. The spatial power spectral density is calculated using a Capon beamformer, and the spatial spectrum of each key analysis frequency point is incoherently averaged to obtain the final comprehensive spatial spectrum. The azimuth range is divided into three sectors, and the spatial frequency band energy of each phase is calculated separately. Second, the spatial coordinates of the disconnecting switch are obtained using the time-difference positioning method. Based on the known coordinates of the four sensors and the acoustic wave propagation speed, the three-dimensional coordinates of the contacts are obtained by solving a system of hyperbolic equations. A time-division excitation strategy is used to obtain the coordinates of the A, B, and C phase contacts respectively. Then, the layout fit and effective contact length are calculated. The measured contact coordinates are compared with the standard layout model, and the root mean square error is calculated after optimal matching through Protodyakonov analysis. Finally, the geometric fit is calculated using an exponential decay function. Simultaneously, based on the spatial spectrum energy distribution characteristics, the energy focusing degree is obtained by calculating the ratio of energy in each phase sector to the total energy, and then the effective contact length is calculated according to its ratio with the standard value. Finally, the overall compliance is calculated using the distance fusion method, and the diagnostic threshold is adjusted accordingly. In the two-dimensional state space composed of layout fit and contact wear degree, the normalized geometric distance from the device state point to the ideal state point is calculated, and its complement is used as the overall compliance. The standard spatial frequency band energy threshold is adaptively scaled according to the overall compliance; the lower the overall compliance, the greater the threshold relaxation. Finally, the state determination is completed by comparing the real-time spatial frequency band energy with the diagnostic threshold. Attached Figure Description

[0006] Figure 1 This is a structural diagram of the GIS disconnector switch displacement defect diagnosis system based on acoustic signal analysis provided in the embodiments of this application; Figure 2 This is a flowchart of the simulation model construction of the GIS disconnector switch displacement defect diagnosis system based on acoustic signal analysis provided in the embodiments of this application; Figure 3 This is a flowchart of the time difference localization method in the diagnostic module provided in the embodiments of this application; Figure 4This is a flowchart of the diagnostic logic provided in the embodiments of this application. Detailed Implementation

[0007] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions "a," "an," "the," "this," and "this" are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the terms used in this application refer to any or all possible combinations that include one or more of the listed items.

[0008] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0009] This application provides a diagnostic system for misalignment defects in GIS disconnectors based on acoustic signal analysis. The invention is based on the core physical phenomenon that the internal physical structure of a GIS disconnector changes fundamentally between its open and closed states, leading to a change in the ultrasonic wave propagation path. In the closed state, the moving and stationary contacts are connected, allowing ultrasonic waves to propagate efficiently along the conductor. In the open state, an opening exists between the contacts, blocking the ultrasonic wave propagation path, which relies primarily on the GIS metal casing for propagation. These two different physical paths result in systematic and measurable differences in the frequency domain energy distribution, spectral centroid, structural resonant frequency, and damping characteristics of the ultrasonic signal received by the second piezoelectric sensor. These differences are used to determine the actual open / closed state of the disconnector. The system includes: The signal acquisition module is used to transmit and receive ultrasonic signals. Specifically, this module includes an ultrasonic transmitting unit, which generates and transmits a special ultrasonic signal that can effectively characterize the status of the GIS disconnect switch. This unit mainly consists of a signal generator and a first piezoelectric sensor, and is reliably coupled to the GIS body through a special fixture.

[0010] The signal generator serves as the core excitation source, employing a dual-mode waveform output capable of generating two basic waveforms: pulse waves and continuous sine waves. Specifically, it outputs pulse signals and sine waves. The pulse wave output by the signal generator is preferably a Gaussian modulated pulse, with a pulse width configurable from 1 to 100 microseconds, a center frequency covering 40kHz to 180kHz, and a peak voltage exceeding 10V to ensure sufficient excitation energy. The continuous sine wave output by the signal generator operates within the 40kHz to 180kHz range in either fixed or swept-frequency mode, with frequency stability better than 0.1% and harmonic distortion less than 1%. In swept-frequency mode, the frequency step can be set to 5kHz, and the stable output duration at each frequency point is no less than 10 milliseconds. In practical implementations, any generator capable of outputting the desired waveform, such as the AFG102, can be used.

[0011] The first piezoelectric sensor is the core component for electroacoustic energy conversion. Its effective operating frequency band should cover 40kHz-180kHz to ensure efficient transmission of pulse waves and continuous sine waves generated by the signal generator. The first piezoelectric sensor uses piezoelectric ceramic materials with low aging rate and high Curie temperature, such as the PZT-5 series ceramic materials, to guarantee long-term measurement repeatability and stability. The first piezoelectric sensor features a metal housing and a standard RF interface, facilitating connection to the signal generator via a coaxial cable. In practical implementations, the first piezoelectric sensor can be used with devices such as the GXC-201.

[0012] The first piezoelectric sensor is firmly fixed to the surface of the GIS basin insulator using a specialized clamp, with the contact pressure steadily controlled between 50 and 300 kPa. This installation creates a stable acoustic coupling channel between the sensor and the cavity, minimizing energy loss of the sound waves at the entry point.

[0013] The ultrasonic receiving unit is the sensing core of the system. It captures ultrasonic signals carrying status information with high fidelity and synchronously. This unit consists of a second piezoelectric sensor array and a data acquisition card.

[0014] Four piezoelectric sensors are tightly secured to the outer edge of the insulator's circumference using precision clamps in a 2x2 grid layout. They are arranged in the same plane perpendicular to the air chamber axis, forming a cross-sectional area covering the sound field measurement.

[0015] The second piezoelectric sensor array, arranged along a specific radial cross-section of the air chamber circumference, can simultaneously capture complex sound fields formed by multiple reflections from the conductor, shell, and interior from different azimuth angles. Since the open and closed states of the disconnecting switch fundamentally alter the main propagation path of ultrasonic waves within the cavity, this cross-sectionally distributed array can significantly enhance the signal spatial distribution variation caused by path differences by measuring the phase difference of sound waves reaching different sensors. Furthermore, all second piezoelectric sensors are of the same model and batch, employing the same clamping and coupling methods to ensure consistent acoustic-electric response characteristics.

[0016] The data acquisition card uses multiple shielded coaxial cables to connect one-to-one with four second piezoelectric sensors distributed on the surface of a basin-type insulator to complete signal transmission. This data acquisition card supports fully synchronous parallel acquisition across four channels, with timing deviations between channels less than 1 nanosecond. Simultaneously, the sampling rate is no less than 2 MS / s, and the ADC resolution is no less than 16 bits, ensuring that ultrasonic signals from 40 kHz to 180 kHz are recorded without distortion and providing sufficient dynamic range.

[0017] The simulation model building module is used to establish standard models by combining simulation and experimental approaches. See [link / reference]. Figure 2 Specifically, this module first uses CAD drawings to create a 1:1 three-dimensional geometric model in COMSOL. Key components include the disconnector contacts, linkage mechanism, metal housing, basin insulator, and SF6 gas domain. Standard physical parameters are assigned to each material from the software library or supplier datasheets; for example, density, elastic modulus, sound velocity, and damping loss factor are assigned to aluminum housing, copper contacts, epoxy resin insulators, and SF6 gas.

[0018] In COMSOL simulation software, this module first needs to introduce and configure three core physics interfaces: the solid mechanics interface is used to simulate the vibration of piezoelectric ultrasonic sensors and the propagation of sound waves in solid structures such as metal shells and epoxy resin insulators; the pressure acoustics interface is used to simulate the propagation behavior of sound waves in SF6 gas medium; and the piezoelectric effect multiphysics coupling seamlessly connects solid mechanics and electrostatics, thereby accurately describing the energy conversion mechanism of ultrasonic sensors and converting the received mechanical vibrations into electrical signals.

[0019] In the model discretization stage, this module employs a physics-controlled mesh generation method, where the software automatically generates the initial mesh based on the solved physics field. Building upon this, the module manually refines the mesh in key regions. These key regions include the vicinity of the ultrasonic sensor, the gap between the disconnector switches, and the main propagation paths of the sound waves. Mesh quality directly determines the solution accuracy; the minimum mesh size must be less than one-sixth of the wavelength of the highest frequency sound wave being simulated. For example, if the highest effective frequency component of the excitation signal is 300 kHz, and the speed of sound in SF6 gas is approximately 140 m / s, the corresponding minimum wavelength is approximately 0.47 mm. Therefore, the mesh size should be refined to at least 0.078 mm. Failure to meet this criterion will result in numerical distortion of sound wave propagation and unreliable calculation results.

[0020] After modeling and mesh generation are completed, this module enters the solution and feature extraction stage. A transient solver is selected, and the Gaussian pulse, modulated by a sinusoidal pulse, is expressed as: , Subsequently, this module performs full transient calculations for both normal opening and normal closing states to simulate the complete propagation process of ultrasonic waves within a complex GIS cavity.

[0021] This module constructs a spatial spectrum based on the ultrasonic signals received by the second piezoelectric sensor array to reflect the distribution of ultrasonic energy in different directions in space. This process is compatible with both pulse wave and sine wave excitation modes and generates spatial features that can be used for condition diagnosis through a unified framework.

[0022] First, this module performs time alignment of the ultrasonic signals. Because the four sensors in the second piezoelectric sensor array have physical spacing on the surface of the basin insulator, even if the excitation signal arrives at each sensor simultaneously, the complex multipath propagation of the ultrasonic wave within the GIS cavity will cause a slight time delay in the arrival time of the signal at each sensor. This time delay caused by the path difference, if not corrected, will introduce a significant phase error in subsequent spatial spectrum calculations, leading to inaccurate azimuth estimation. This module uses a cross-correlation method for high-precision time alignment, taking the signal from channel one... For reference, calculate the signals of the remaining channels. The cross-correlation function between (i=2,3,4) and the reference signal is used to accurately estimate the relative time delay by finding the peak position of the cross-correlation function. Subsequently, according to right Perform the appropriate time shift to ensure that the signal points representing the same physical wavefront in all channels are aligned in time, laying the foundation for subsequent coherent processing.

[0023] Subsequently, this module performs windowing and Fourier transform on the aligned time-domain signal. When performing a Fast Fourier Transform (FFT) on the aligned signal to obtain frequency domain information, the implicit assumption of periodic extension of a finite-length signal can introduce discontinuities at the beginning and end of the data, leading to non-real frequency components in the spectrum, i.e., spectral leakage. To suppress this effect, this module multiplies the aligned time-domain signal of each channel by a Hanning window before the FFT. The Hanning window function smoothly transitions to zero at both ends of the data segment, effectively reducing the boundary discontinuities caused by data truncation, thereby significantly reducing spectral leakage and improving the accuracy of spectrum estimation. After windowing, this module performs an FFT on the signal of each channel separately, transforming it from the time domain... Transform to the frequency domain to obtain its complex spectrum. (i=1,2,3,4). These complex spectra not only contain amplitude information for each frequency component, but more importantly, they preserve accurate phase information. This phase information is the basis for subsequent beamforming algorithms to calculate the direction of arrival of the sound waves. This module further selects several key analysis frequencies. As a basis for subsequent spatial spectrum calculations, for example, in the range of 40kHz to 180kHz, intervals of 5kHz are selected.

[0024] This module uses beamforming to calculate the spatial spectrum. Based on the known geometric layout of the second piezoelectric sensor array, i.e., a 2x2 grid, it calculates the spatial spectrum for each possible direction of incoming waves. Calculate the steering vector . The azimuth angle is usually expressed as... For intervals at arrive Scan within the range. First calculate the array's frequency range. The covariance matrix below: ,in .

[0025] This module uses the Capon beamformer to calculate the direction of the frequency point. Spatial power spectral density on: This module analyzes all key frequency points. The spatial spectrum is incoherently averaged to obtain the final comprehensive spatial spectrum. : , in This spatial spectrum represents the total number of key analysis frequency points. It clearly shows which azimuth angle the ultrasonic energy mainly originates from.

[0026] This module is based on the obtained spatial spectrum. This module calculates the spatial frequency band energy across the entire azimuth range, i.e. arrive The system is divided into three sectors, corresponding to the A, B, and C phase disconnect switches of a three-phase common-box GIS. This module first calculates the values ​​for each sector. Internal spatial frequency band energy: , in, This is the sampling interval for the azimuth angle. Through this step, this module obtains three spatial frequency band energy values: , , These represent the degree of concentration of ultrasonic energy in three different directions.

[0027] This module simulates two ideal states of the disconnector switch: standard open and standard closed, within the established accurate COMSOL model. For each state, the module processes it according to the aforementioned procedure, ultimately calculating the spatial frequency band energy under the open state. Spatial frequency band energy under closed state .

[0028] Based on statistical analysis of a large amount of simulation and experimental data, the standard spatial frequency band energy threshold is determined. The energy value set between the open and closed states is typically given by the following formula: , in This is a weighting coefficient between 0 and 1, which can be optimized based on the discriminative power between the two states to ensure the reliability of the judgment. In real-time diagnosis, the system will use the calculated real-time spatial frequency band energy... With this standard threshold Comparison: If ≥ If the circuit is determined to be in the tripped state; < It is determined to be in the closed state.

[0029] The diagnostic module processes and analyzes the real-time acquired ultrasonic signals to achieve accurate diagnosis of the status of the GIS disconnector. Specifically, this module uses the same method as the simulation model construction module to construct the spatial spectrum and calculate the spatial frequency band energy. Then, this module obtains the spatial coordinates of the disconnector using the time-difference positioning method, see... Figure 3 This module is based on a precisely known second piezoelectric sensor array, whose four sensors have pre-calibrated coordinates in three-dimensional space. The coordinates of these four sensors are as follows: When a contact, for example, phase A vibrates and generates ultrasonic waves, these sound waves propagate through the SF6 gas and reach four sensors sequentially. The arrival time of the sound waves at other sensors relative to their arrival at a reference sensor is calculated. The time difference is denoted as Assume the position of the contact is... The speed of sound in SF6 gas is v. Therefore, the distance difference between the sound source and each sensor can be expressed as the time difference multiplied by the speed of sound: , , .

[0030] in, It is from the sound source P to the sensor The straight-line distance. By solving this system of nonlinear equations, the unique coordinates of the sound source can be determined. .

[0031] To distinguish the contacts of phases A, B, and C, a time-division excitation strategy can be adopted. That is, the first piezoelectric sensor at the A-phase basin insulator emits ultrasonic waves, and then a receiving array receives the signals. The calculated location of the sound source at this time is the coordinate of the A-phase contact. Similarly, by transmitting sequentially in phase B and phase C, the coordinates of the contact in phase B can be obtained. and C phase contact coordinates Thus, the actual spatial coordinates of the three disconnector contacts were obtained. Then, this module calculates the root mean square error (RMSE): , in, These are the ideal coordinates of the i-th contact in the standard layout model. i can be A, B, or C.

[0032] This module calculates the average distance between the measured point and the standard point. Then, it calculates the geometric fit, which should be inversely proportional to the error. This module uses an exponential decay function to quantify this relationship. , Where σ is the tolerance parameter, a threshold preset based on manufacturing tolerances and measurement errors, for example, σ=5mm. When RMSE=0, the fit is 1; when RMSE=5mm, the fit is approximately 0.37; when RMSE is very large, the fit approaches 0.

[0033] This module will display the measured coordinates of the disconnector switch. The above-mentioned fit calculations were performed with both the standard linear model and the standard trigonometric model. The fit with the linear model was obtained. And its fit with the triangular model. Final layout fit It is the maximum of the two: Meanwhile, the model that achieves the maximum value is determined to be the layout type of the GIS device being tested.

[0034] After identifying the spatial layout type, this module further analyzes the effective length of the disconnector switch contacts. Based on the physical mechanism of ultrasonic wave propagation, this module establishes a mapping relationship between contact length and spatial spectrum characteristics. When the contacts are in different positions, they alter the propagation path and reflection characteristics of ultrasonic waves within the GIS cavity, thus affecting the energy distribution pattern of the spatial spectrum. Specifically, longer contacts result in more ultrasonic energy propagating along the conductor, manifesting as a more concentrated energy distribution within that phase sector in the spatial spectrum; conversely, when the contacts shorten due to wear, the proportion of propagation along the casing and multiple reflections increases, leading to a more dispersed spatial distribution of received energy. In practical implementation, this module calculates the energy distribution of each phase sector... Intra-space frequency band energy Total energy in all directions The ratio of these values ​​is defined as the degree of energy focusing in that phase. : ,in, .

[0035] During the simulation model construction phase, the standard contact length has been established. A defined proportional relationship between energy focusing degree and the actual energy focusing degree. In real-time diagnostics, this module will use the measured energy focusing degree... Compared with standard value By comparison, the real-time effective length of the contact can be directly calculated using the following formula: .

[0036] After completing layout type identification and effective contact length calculation, this module dynamically adjusts the standard spatial frequency band energy threshold based on the disconnector layout and effective length of the GIS equipment under test. (See...) Figure 4 This module selects the contact with the shortest effective length and calculates the effective contact length R to ensure high sensitivity even in the face of severe wear in any phase. R = Then, the overall compliance C is calculated using the distance fusion method. This parameter comprehensively reflects the standardization of the spatial layout of the device under test and the wear condition of the contacts. First, this module constructs the state vector and the ideal point, then... In the two-dimensional state space formed by R, the state point of the device under test is defined as ( Let (R) be the ideal point of the standard model, and (1,1) be the ideal point. Calculate the Euclidean distance d from the state point of the device under test to the ideal state point, and normalize this distance to its maximum value to ensure that its range is between [0,1]. The calculation formula is as follows: , , in, It is the maximum distance from the theoretically worst-case state (0,0) in the state space to the ideal state (1,1). This step ensures that the overall compliance C is a normalized value between 0 and 1.

[0037] Subsequently, this module, based on the overall compliance C, sets the standard spatial frequency band energy threshold in the standard model. Adaptive scaling is performed to generate diagnostic thresholds suitable for the current device under test. The formula is adjusted as follows: , in, This is a preset tolerance gain coefficient used to control the magnitude of threshold adjustment. The degree of non-compliance is indicated by the overall compliance C. When the overall compliance C is low, meaning the equipment condition deviates significantly from the standard model, the adjustment formula will correspondingly relax the diagnostic threshold.

[0038] In the final state determination stage, this module compares the spatial frequency band energy value calculated in real time for each phase with the determined diagnostic threshold: when the energy value of a phase is greater than or equal to the threshold, the isolating switch of that phase is determined to be in the open state; when the energy value is lower than the threshold, it is determined to be in the closed state.

[0039] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0040] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application of the technical solution and the constraints of the invention. Furthermore, the functional modules in the various embodiments of this application can be integrated into a single processing module, or each module can exist physically separately, or two or more modules can be integrated into a single module.

[0041] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0042] In conclusion, the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. GIS disconnector off-site defect diagnosis system based on acoustic signal analysis, characterized in that, Comprising: a signal acquisition module that transmits and receives ultrasonic signals into a three-phase common tank type GIS cavity to be tested; a simulation model construction module that establishes a standard model of the three-phase common tank type GIS through simulation and experimental data, the standard model including a straight-line layout model and a triangular layout model, and the standard model including a standard spatial frequency band energy threshold; a diagnosis module that constructs a spatial spectrum based on the received ultrasonic signals and calculates spatial frequency band energy, obtains the spatial coordinates of the disconnecting switch in the GIS to be tested through a time difference positioning method, and calculates the layout coincidence degree of the disconnecting switch in the GIS to be tested based on the spatial coordinates and the layout of the standard model; simultaneously calculates the effective length of the disconnecting switch contact based on the energy distribution characteristics of the spatial spectrum, and calculates the overall coincidence degree of the GIS to be tested through distance fusion method combined with the layout coincidence degree and the effective length, and scales the standard spatial frequency band energy threshold based on the overall coincidence degree to obtain a diagnosis threshold; if the spatial frequency band energy exceeds the diagnosis threshold, it is determined that the disconnecting switch is in the open state; if it is lower than the diagnosis threshold, it is determined that the disconnecting switch is in the closed state.

2. The GIS disconnector off-site defect diagnosis system based on acoustic signal analysis according to claim 1, characterized in that, The signal acquisition module comprises: an ultrasonic transmitting unit for generating and transmitting ultrasonic signals in two waveforms of pulse wave and continuous sine wave; an ultrasonic receiving unit comprising a piezoelectric sensor array fixed on the surface of the basin-type insulator in a specific spatial configuration, and a multi-channel synchronous data acquisition card connected with the array.

3. The GIS disconnector off-site defect diagnosis system based on acoustic signal analysis according to claim 2, characterized in that, Comprising: The piezoelectric sensor array in the ultrasonic receiving unit forms a four-element spatial array, and the four sensors are installed on the outer edge surface of the basin-type insulator of the same gas chamber in a grid configuration and on the same plane perpendicular to the axis of the gas chamber.

4. The GIS disconnector off-site defect diagnosis system based on acoustic signal analysis according to claim 1, characterized in that, The simulation model construction module establishes the standard model by the following ways: Based on the physical structure of the GIS, a three-dimensional simulation model is established, and the characteristics of the ultrasonic signals under normal open and closed states are obtained through numerical simulation; The simulation model is calibrated using experimental data to reduce the error between simulation and reality; Based on the calibrated model, a large amount of normal state data is generated by introducing manufacturing tolerances and environmental variable parameters to establish the standard spatial frequency band energy threshold.

5. The GIS disconnector off-site defect diagnosis system based on acoustic signal analysis according to claim 1, characterized in that, The diagnosis module calculates the layout coincidence degree by the following steps: align the measured spatial coordinates of the disconnecting switch with the ideal coordinates in the standard layout model for best matching; calculate the root mean square error between the aligned measured coordinates and the ideal coordinates; based on the root mean square error, the layout coincidence degree is calculated through an exponential decay function.

6. The GIS disconnector off-site defect diagnosis system based on acoustic signal analysis according to claim 1, characterized in that, Comprising: The diagnosis module calculates the energy focusing degree by analyzing the ratio of the energy of each phase sector in the spatial spectrum to the total energy in the whole circumference, and calculates the real-time effective length of the contact based on the proportional relationship between the energy focusing degree and the standard value.

7. The GIS disconnector off-site defect diagnosis system based on acoustic signal analysis according to claim 1, characterized in that, The specific process of the distance fusion method includes: In the two-dimensional state space composed of the layout coincidence degree and the contact wear degree, the normalized geometric distance between the device state point and the ideal state point is calculated; the complement of the normalized geometric distance is defined as the overall coincidence degree.

8. The GIS disconnector off-site defect diagnosis system based on acoustic signal analysis according to claim 1, characterized in that, Comprising: Based on the overall coincidence degree, the standard spatial frequency band energy threshold is scaled, the lower the overall coincidence degree, the greater the relaxation amplitude of the standard spatial frequency band energy threshold; the higher the overall coincidence degree, the smaller the relaxation amplitude.

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