A method, device and system for locating and diagnosing mechanical defects inside GIL

Abstract

The present invention provides a method, device and system for positioning and diagnosing mechanical defects inside a GIL. The method includes the following steps: constructing the temporal and spatial characteristic association between acoustic imaging of the GIL shell and mechanical vibration under different types of mechanical defects through numerical modeling and physical experiments; obtaining the acoustic spectrum of the GIL shell; segmenting and extracting the sensitive area of ​​the spectrum; finely measuring the mechanical vibration signal in the sensitive area of ​​the acoustic vibration spectrum; and classifying, identifying and diagnosing the types of mechanical defects inside the GIL through characteristic correlation analysis of acoustic imaging and mechanical vibration. The present invention can realize multi-scale positioning and diagnosis of GIL mechanical defects, can more accurately locate mechanical defects during equipment operation, and can also diagnose defect types. The present invention also has the advantages of flexible measurement and easy mobility, and can effectively ensure the safe operation of related electrical equipment.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power equipment, and in particular to a method, device and system for locating and diagnosing mechanical defects inside a GIL. Background Art

[0002] Gas-insulated transmission lines (GIL) are an important type of power transmission equipment that realizes ultra-high voltage, high current, and long-distance power transmission. They have the advantages of high reliability, high environmental utilization, large capacity, and no electromagnetic interference. GIL mechanical defects refer to structural damage caused by the degradation of the mechanical connection state inside the GIL. These defects include loosening and abnormal vibration of the internal electrical connections, internal bolt connections, internal slippage, and external bolt connections of the GIL. GIL mechanical defects can cause abnormal vibrations in the equipment in addition to normal vibrations, thereby causing damage to the equipment itself, causing the internal connectors of the GIL to fall off, gas leakage, contact overheating, etc. In severe cases, insulation accidents may occur, endangering the safe operation of the equipment and power system.

[0003] At present, the methods for locating and diagnosing mechanical defects inside GIL include vibration testing, acoustic testing, and partial discharge testing. Due to the complex types of mechanical defects inside GIL, unclear vibration and acoustic propagation laws, the contact vibration sensor itself is prone to interfere with the measurement results, and the point measurement vibration and acoustic detection methods cannot obtain the overall acoustic and vibration characteristics of GIL, resulting in limited on-site application effects of the above methods. In addition, when the partial discharge signal is generated, serious mechanical defects have already appeared inside the GIL, resulting in insufficient warning time. Therefore, the existing methods cannot meet the requirements of accurate positioning of internal defects in GIL and diagnosis of defect types. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects of the above-mentioned technology and provide a method, device and system for locating and diagnosing mechanical defects inside a GIL.

[0005] In a first aspect, the present invention provides a method for locating and diagnosing mechanical defects inside a GIL, comprising the following steps:

[0006] S01: Through numerical modeling and physical experiments, establish the temporal and spatial characteristics of the GIL shell acoustic imaging and mechanical vibration under different mechanical defect types;

[0007] S02: Obtain an acoustic imaging map of the GIL interval, and segment and extract sensitive areas of the acoustic imaging map;

[0008] S03: Finely measure the mechanical vibration signal in the sensitive area of ​​the acoustic imaging spectrum;

[0009] S04: Classify, identify and diagnose the types of mechanical defects inside the GIL through characteristic correlation analysis of acoustic imaging and mechanical vibration.

[0010] In a second aspect, the present invention further provides a device for locating and diagnosing mechanical defects inside a GIL for implementing the above method, the device comprising:

[0011] The feature correlation unit constructs the temporal and spatial feature correlation between the acoustic imaging of the GIL shell and the mechanical vibration under different mechanical defect types through numerical modeling and physical experiments;

[0012] A sensitive area recognition unit is used to segment and extract the sensitive area of ​​the acoustic imaging spectrum;

[0013] Laser vibrometer unit, used to precisely measure the mechanical vibration signal in the sensitive area of ​​the acoustic imaging spectrum;

[0014] The defect diagnosis unit is used to classify, identify and diagnose the types of mechanical defects inside the GIL through characteristic correlation analysis of acoustic imaging and mechanical vibration.

[0015] In a third aspect, the present invention further provides a system for locating and diagnosing mechanical defects inside a GIL for implementing the above method, the system comprising:

[0016] GIL interval to be tested, acoustic imaging module, sensitive area identification module, laser vibration measurement module, information fusion and feature association module, defect location and diagnosis module, acoustic measurement point;

[0017] The GIL intervals to be tested include typical GIL intervals such as flange side, bellows side and pot insulator side;

[0018] The acoustic imaging module measures the acoustic distribution characteristics of the GIL shell at the measuring point 7; the sensitive area identification module is connected to the acoustic imaging module; the laser vibration measurement module is connected to the sensitive area identification module; the information fusion and feature association module is connected to the laser vibration measurement module; the defect location and diagnosis module is connected to the information fusion and feature association module.

[0019] In the application, the acoustic imaging module is first used to obtain the acoustic imaging map of the on-site GIL shell, and then the sensitive area of ​​the GIL shell acoustic map is segmented and extracted through the sensitive area identification module to obtain the distribution of the GIL shell amplitude and determine the location of the abnormal vibration source.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] The present invention realizes the positioning and diagnosis of GIL mechanical defects at multiple scales, adopts a non-contact measurement method, and avoids the influence of contact sensors on the detection results. In addition, the present invention can determine the initial position and type of mechanical defects, and can provide early warning time for GIL mechanical defects to ensure the safe operation of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flow chart of a method for locating and diagnosing mechanical defects inside a GIL provided by an embodiment of the present invention;

[0023] Figure 2 A schematic diagram of a device for locating and diagnosing mechanical defects inside a GIL provided by an embodiment of the present invention;

[0024] Figure 3 A schematic diagram of a system for locating and diagnosing mechanical defects inside a GIL provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0027] See also Figure 1 An embodiment of the present invention provides a method for locating and diagnosing a mechanical defect inside a GIL. The method for locating and diagnosing a mechanical defect inside a GIL of the embodiment includes the following steps:

[0028] S01: Through numerical modeling and physical experiments, establish the temporal and spatial characteristics of the GIL shell acoustic imaging and mechanical vibration under different mechanical defect types;

[0029] As an embodiment, the acoustic-mechanical vibration coupling numerical modeling is performed on the GIL, and the mechanical defects of the GIL are simulated by setting preload and vibration sources at the internal electrical connections, internal bolt connections, internal sliding connections, and external bolt connections of the GIL, and the acoustic numerical calculation and vibration numerical calculation of the GIL shell are performed; physical experiments of the GIL prototype under different mechanical defect types are performed, and the numerical calculation results are verified, so as to obtain the temporal and spatial characteristic correlation between the mechanical defect type and the acoustic imaging and mechanical vibration of the GIL shell;

[0030] S02: Obtain an acoustic imaging map of the GIL interval, and segment and extract sensitive areas of the acoustic imaging map;

[0031] Obtain the acoustic imaging map of the GIL shell on site, segment and extract the sensitive area of ​​the GIL shell acoustic map, and then determine the location of the abnormal vibration source, and make a preliminary measurement of the mechanical vibration signal in the map;

[0032] S03: Finely measure the mechanical vibration signal in the sensitive area of ​​the acoustic imaging spectrum;

[0033] After initially obtaining the location of the abnormal vibration source inside the GIL, the mechanical vibration signal in the sensitive area of ​​the acoustic spectrum is precisely measured by laser vibrometer;

[0034] S04: The GIL shell vibration and acoustic signals are fused through information fusion and feature association analysis algorithms; a defect sample data set is constructed based on the GIL shell vibration and acoustic fusion features under different mechanical defects, and a deep learning neural network model is constructed based on the labeled mechanical defect sample library to achieve classification, identification and diagnosis of mechanical defects inside the GIL.

[0035] As an example, Figure 2 A schematic diagram of a device for locating and diagnosing mechanical defects inside a GIL is shown. The device implements the above-mentioned method for locating and diagnosing mechanical defects inside a GIL, including:

[0036] The feature correlation unit 210 constructs the temporal and spatial feature correlation between the acoustic imaging of the GIL shell and the mechanical vibration under different mechanical defect types through numerical modeling and physical experiments;

[0037] Sensitive area identification unit 220, for segmenting and extracting the sensitive area of ​​the acoustic imaging map;

[0038] Laser vibrometer unit 230, for fine measurement of mechanical vibration signals in the sensitive area of ​​the acoustic imaging spectrum;

[0039] The defect diagnosis unit 240 is used to classify, identify and diagnose the mechanical defect types inside the GIL through acoustic imaging and characteristic correlation analysis of mechanical vibration.

[0040] It should be understood that the device corresponds to the above-mentioned GIL internal mechanical defect positioning and diagnosis method embodiment, and can perform the various steps involved in the above-mentioned method embodiment. The specific functions of the device can be found in the above description, and the detailed description is appropriately omitted here to avoid repetition. The device includes at least one software function module that can be stored in a memory in the form of software or firmware or fixed in the operating system (OS) of the device.

[0041] As an example, Figure 3 A positioning and diagnosis system for mechanical defects inside a GIL is shown. The system implements the positioning and diagnosis method for mechanical defects inside a GIL, and includes: a GIL interval 1 to be measured, an acoustic imaging module 2, a sensitive area identification module 3, a laser vibration measurement module 4, an information fusion and feature association module 5, a defect positioning and diagnosis module 6, and an acoustic measurement point 7. The GIL interval 1 includes typical GIL intervals such as the flange side, the bellows side, and the pot-type insulator side; the acoustic imaging module 2 measures the acoustic distribution characteristics of the GIL shell at the measurement point 7; the sensitive area identification module 3 is connected to the acoustic imaging module 2, and is responsible for extracting the sensitive area from the spectrum obtained by the acoustic imaging module; the laser vibration measurement module 4 is connected to the sensitive area identification module 3, and is responsible for fine measurement of the mechanical vibration signal in the sensitive area; the information fusion and feature association module 5 is connected to the laser vibration measurement module 4, and is responsible for the feature fusion of vibration and acoustic signals; the defect positioning and diagnosis module 6 is connected to the information fusion and feature association module 5, and is responsible for positioning, classifying, identifying, and diagnosing mechanical defects inside the GIL.

[0042] In the application, the acoustic imaging module 2 is used to obtain the acoustic imaging map of the GIL shell on site, and then the sensitive area of ​​the GIL shell acoustic map is segmented and extracted through the sensitive area identification module 3 to obtain the distribution of the GIL shell amplitude and determine the location of the abnormal vibration source.

[0043] Furthermore, the location of the abnormal vibration source inside the GIL is preliminarily determined by segmenting the extracted acoustic spectrum, and the mechanical vibration signal in the sensitive area of ​​the acoustic spectrum is precisely measured by the laser vibration measurement module 4.

[0044] Furthermore, through the information fusion and feature association module 5, the GIL shell vibration signal and acoustic signal are subjected to information fusion and feature association analysis, a defect sample data set is constructed based on the GIL shell vibration and acoustic fusion characteristics under different mechanical defects, and a deep learning neural network model is constructed based on the labeled mechanical defect sample library to achieve classification, identification and diagnosis of mechanical defects inside the GIL.

[0045] The above is only a preferred specific implementation manner of the present invention, and the protection scope of the present invention is not limited thereto. Any simple change or equivalent replacement of the technical solution that can be obviously obtained by any technician familiar with the technical field within the technical scope disclosed in the present invention falls within the protection scope of the present invention.

Claims

1. A method for locating and diagnosing mechanical defects inside a GIL, characterized in that the method comprises the following steps: S01: Through numerical modeling and physical experiments, establish the temporal and spatial characteristics of the GIL shell acoustic imaging and mechanical vibration under different mechanical defect types; The acoustic-mechanical vibration coupling numerical modeling of GIL is carried out. The mechanical defects of GIL are simulated by setting preload and vibration source at the internal electrical connection, internal bolt connection, internal sliding connection and external bolt connection of GIL, and the acoustic and vibration numerical calculations of GIL shell are carried out. Conduct physical experiments on GIL prototypes with different mechanical defect types, verify the numerical calculation results, and obtain the temporal and spatial characteristics of the correlation between mechanical defect types and GIL shell acoustic imaging and mechanical vibration; S02: Acquire the acoustic imaging map of the GIL shell interval, and segment and extract the sensitive area of ​​the acoustic imaging map; Acquire the acoustic imaging map of the GIL shell on site, segment and extract the sensitive areas of the acoustic imaging map, determine the location of the abnormal vibration source, and achieve preliminary measurement of the mechanical vibration signal; S03: Finely measure the mechanical vibration signal in the sensitive area of ​​the acoustic imaging spectrum; By segmenting the extracted sensitive area of ​​the acoustic imaging spectrum, the location of the abnormal vibration source inside the GIL is preliminarily determined. The mechanical vibration signal of the maximum value, i.e., the adjacent point, in the sensitive area of ​​the acoustic imaging spectrum is scanned point by point by laser vibration measurement to achieve precise measurement. S04: Classify, identify and diagnose the types of mechanical defects inside the GIL through characteristic correlation analysis of acoustic imaging and mechanical vibration; The information fusion and feature association analysis algorithm are used to fuse the GIL shell vibration and acoustic signals. A defect sample data set is constructed based on the GIL shell vibration and acoustic fusion characteristics under different mechanical defects. A deep learning neural network model is constructed based on the labeled defect sample data set to achieve classification, identification and diagnosis of GIL internal mechanical defects.

2. A device for locating and diagnosing mechanical defects inside a GIL, characterized in that: The device adopts the method for locating and diagnosing mechanical defects inside the GIL as described in claim 1, comprising: The feature correlation unit constructs the temporal and spatial feature correlation between the acoustic imaging of the GIL shell and the mechanical vibration under different mechanical defect types through numerical modeling and physical experiments; A sensitive area recognition unit is used to segment and extract the sensitive area of ​​the acoustic imaging spectrum; Laser vibrometer unit, used to precisely measure the mechanical vibration signal in the sensitive area of ​​the acoustic imaging spectrum; The defect diagnosis unit is used to classify, identify and diagnose the types of mechanical defects inside the GIL through characteristic correlation analysis of acoustic imaging and mechanical vibration.

3. A system for locating and diagnosing mechanical defects inside a GIL, characterized in that: The system adopts the method for locating and diagnosing mechanical defects inside the GIL as described in claim 1 above, comprising: GIL interval to be tested, acoustic imaging module, sensitive area identification module, laser vibration measurement module, information fusion and feature association module, defect location and diagnosis module, acoustic measurement point; The acoustic imaging module measures the acoustic distribution characteristics of the GIL shell at the acoustic measurement point; the sensitive area identification module is connected to the acoustic imaging module and is responsible for extracting the sensitive area from the spectrum obtained by the acoustic imaging module; the laser vibration measurement module is connected to the sensitive area identification module and is responsible for fine measurement of the mechanical vibration signal in the sensitive area; the information fusion and feature association module is connected to the laser vibration measurement module and is responsible for the feature fusion of vibration and acoustic signals; the defect location and diagnosis module is connected to the information fusion and feature association module and is responsible for locating, classifying, identifying and diagnosing mechanical defects inside the GIL.

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