GIS switching station monitoring method and device and electronic equipment

Abstract

The invention provides a GIS switching station monitoring method and device and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring a sound field interference image for a GIS switching station; acquiring a light field image for the GIS switching station; fusing the sound field interference image and the light field image to generate a health state holographic image; and monitoring the GIS switching station through the health state holographic image. By implementing the technical scheme provided by the invention, the GIS switching station can be monitored conveniently.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and in particular to a monitoring method, device and electronic equipment for a GIS switch station. Background Art

[0002] With the continuous development of power systems, GIS switch stations are widely used in various substations due to their high reliability, compactness and low maintenance requirements. However, the complex structure and operating environment of GIS switch stations make their fault monitoring and status assessment an important technical challenge.

[0003] At present, existing monitoring technologies usually rely on information from a single physical quantity. For example, partial discharge detection focuses on electrical insulation failures, temperature rise detection mainly reflects thermal anomalies, and gas leakage detection focuses on changes in gas pressure. These technologies lack the ability to fully evaluate the overall operating status of the equipment, especially when multiple faults exist at the same time or in the hidden fault stage, which may cause abnormal signals to be ignored. Therefore, they cannot meet the needs of comprehensive evaluation and accurate diagnosis of equipment status, which is not conducive to monitoring GIS switch stations.

[0004] Therefore, there is an urgent need for a monitoring method, device and electronic equipment for a GIS switch station. Summary of the invention

[0005] The present application provides a monitoring method, device and electronic equipment for a GIS switch station, which are convenient for monitoring a GIS switch station.

[0006] In the first aspect of the present application, a monitoring method for a GIS switch station is provided, the method comprising: obtaining an acoustic field interference image for the GIS switch station; obtaining a light field image for the GIS switch station; fusing the acoustic field interference image with the light field image to generate a health status holographic image; and monitoring the GIS switch station through the health status holographic image.

[0007] By adopting the above technical solutions, the acoustic field interference image provides an accurate analysis of the internal dynamic characteristics of the equipment. The light field image captures the external structure and apparent changes of the equipment. The two are fused to generate a healthy state holographic image, which integrates the internal dynamic and external static information, and truly realizes a panoramic assessment of the equipment status, covering a variety of physical phenomena. The monitoring method of a single data source tends to ignore the interaction between different anomalies, making it difficult to accurately locate the root cause of the fault. However, the above solution associates the acoustic field and light field data through a data fusion algorithm to provide a multi-dimensional abnormal feature analysis. The healthy state holographic image can intuitively display the distribution of abnormal signals in space and characteristics, helping to locate the specific location and possible causes of the fault. The acoustic field interference image can capture weak vibrations and abnormal acoustic reflection patterns. The light field image identifies subtle surface cracks and deformations through high-precision imaging. By fusing the generated holographic image, subtle anomalies are enhanced from multiple angles, improving the detection sensitivity of early faults, and helping to intervene in advance to prevent small problems from evolving into major faults. Therefore, it is convenient to monitor the GIS switch station.

[0008] Optionally, the acquisition of the sound field interference image for the GIS switch station specifically includes: emitting sound waves into the interior of the GIS switch station through a sound wave transmitter; receiving sound wave reflection signals according to the sound waves, wherein the sound wave reflection signals include time delay, waveform characteristics, and energy attenuation; performing time-frequency domain analysis on the sound wave reflection signals to extract vibration mode characteristics; and using a sound field interference algorithm to perform spatial distribution reconstruction processing on the vibration mode characteristics to obtain the sound field interference image.

[0009] By adopting the above technical solutions, the time delay reflects the distance difference of the sound wave propagation path, which can be used to infer the structural characteristics and spatial relationship between different components inside the GIS switch station. The waveform characteristics can identify abnormal changes in the reflected signal, and the energy attenuation can reveal the physical state of the internal material, such as abnormal gas density or insulation aging. The acquisition of these multi-dimensional signals provides high-quality data support for the subsequent refined analysis and reconstruction of fault characteristics. Time domain analysis can capture the transient characteristics of the reflected signal, and frequency domain analysis can separate the frequency components contained in the reflected signal to help identify the frequency characteristics of specific faults. The time-frequency joint analysis method can comprehensively describe the frequency change and time distribution of the signal, and is particularly suitable for capturing abnormal characteristics in dynamic signals. The acoustic field interference algorithm uses the coherence and interference characteristics of sound waves in space to accurately locate the vibration signal to the specific area of ​​the GIS switch station. Through spatial reconstruction, the vibration distribution state of different components inside the equipment is reconstructed to reveal potential abnormal areas. This spatialized result can provide an intuitive sound field image, which is convenient for technicians to quickly determine the problem location and fault type.

[0010] Optionally, acquiring the light field image for the GIS switch station specifically includes: scanning the outer shell surface of the GIS switch station by a laser beam of a laser holographic device to obtain reflected light intensity and light phase changes; and generating the light field image according to the reflected light intensity and the light phase changes.

[0011] By adopting the above technical solutions, laser scanning can generate detailed light field images by capturing the intensity and phase changes of reflected light with high precision. High-resolution detection can identify tiny defects on the surface of the shell, which is difficult to achieve with traditional visual inspection or low-resolution monitoring methods. By accurately positioning and scanning the laser beam, the surface changes at the micron level are captured, which helps to detect early minor damage. It effectively supports the integrity assessment of the equipment shell and ensures the safe operation of the GIS switch station. Laser scanning can not only detect static cracks, but also monitor dynamic deformation. Dynamic monitoring capabilities can be used to track the trend of deformation development and help predict potential risks. The non-contact method is particularly suitable for GIS switch stations in operation, realizing online monitoring of equipment without downtime detection, and improving operation and maintenance efficiency. Early cracks on the surface of the shell or material aging may cause tiny changes in light intensity or phase, which can be magnified and clearly presented through light field images. It can detect hidden dangers at an early stage and provide longer intervention time, thereby preventing small problems from evolving into major failures.

[0012] Optionally, generating the light field image according to the reflected light intensity and the light phase change specifically includes: determining a target image according to the reflected light intensity and the light phase change; acquiring three-dimensional deformation and crack information of the outer shell of the GIS switch station; adding the three-dimensional deformation and the crack information to the target image to obtain a holographic image; and processing the holographic image using a phase unpacking algorithm to obtain the light field image.

[0013] By adopting the above technical solutions, laser holography technology can accurately capture the tiny deformation of the GIS switch station shell through the change of light phase, which helps to evaluate the stress, deformation and potential structural problems of the equipment under working conditions. Through the change of reflected light intensity, microcracks or damaged areas on the shell surface can be accurately identified. This is of great significance for discovering hidden cracks or material fatigue, especially after the equipment has been running for a long time. This step can simultaneously display the deformation and cracks of the equipment shell in the image, providing rich surface feature information for subsequent fault diagnosis. By integrating three-dimensional deformation, crack information, light intensity and phase, the generated holographic image presents a complete image of the surface state of the equipment. This fusion can provide a more comprehensive assessment of the health status of the equipment. The holographic image can simultaneously reflect multi-dimensional monitoring information such as deformation and cracks, presenting a real and three-dimensional equipment appearance, which is convenient for technicians to analyze and judge the status of the equipment from multiple angles and dimensions. Combining these multiple information can more accurately locate the defective area of ​​the shell, especially the accurate description of microcracks and deformation, and improve the accuracy of fault location. The optical phase is measured by interference effect, and there is a phase ambiguity phenomenon. The phase unpacking algorithm can effectively eliminate this blur and restore more accurate light field information. This is crucial for high-precision monitoring, especially in the detection of small deformations or cracks on the surface. Through the unpacked phase data, more detailed deformation and crack information on the device surface can be restored, the spatial resolution and accuracy of the image can be improved, and it helps to analyze small defects. Phase unpacking technology can effectively reduce the impact of external noise on light field images and avoid measurement errors caused by environmental interference.

[0014] Optionally, the sound field interference image is fused with the light field image to generate a health status holographic image, which specifically includes: using a multimodal convolutional neural network, taking the sound field interference image as the first input, and obtaining a vibration feature vector through convolution extraction; using the multimodal convolutional neural network, taking the light field image as the second input, and obtaining a surface deformation feature vector through convolution extraction; fusing the vibration feature vector and the surface deformation feature vector in a fully connected layer, and strengthening the weights of important areas through an attention mechanism to obtain a fused image; in the fused image, marking abnormal areas and abnormal categories to obtain the health status holographic image.

[0015] By adopting the above technical solution, the light field image and the acoustic field interference image respectively reflect different types of equipment status information. The light field image can provide deformation and crack information on the surface of the equipment, while the acoustic field interference image reflects the vibration mode inside the equipment. By fusing these two types of information, the health status of the equipment can be comprehensively evaluated to avoid the deviation and omission that may be caused by a single information source. A single image cannot fully evaluate the health status of the equipment. The multimodal convolutional neural network can learn the features of the two images at the same time and generate a comprehensive diagnostic image by fusion, which enhances the accuracy and reliability of the diagnosis. The acoustic field interference image is extracted by convolution to obtain the vibration feature vector, and the light field image is extracted by convolution to obtain the surface deformation feature vector. In the acoustic field interference image, the convolutional neural network can identify small abnormal signals in the vibration mode, and in the light field image, it can identify subtle differences in surface deformation. Such precise extraction is helpful for subsequent abnormality detection and fault diagnosis. Since the convolutional neural network can automatically learn the complex patterns in the data, it enables the network to identify potential, non-significant fault signals when processing these two types of images.

[0016] Optionally, the method further includes: sending the health status holographic image to AR glasses worn by a user; and displaying, through the AR glasses, to the user the coupling relationship between the internal discharge and the shell deformation marked in the health status holographic image.

[0017] By adopting the above technical solutions, AR technology can superimpose fault status images on the user's field of view in real time, so that users can check the health status of the equipment without leaving the work site. This allows maintenance personnel to quickly understand the current status of the equipment and respond. AR glasses directly present holographic images in front of the user, so that complex fault information can be displayed clearly and intuitively. Traditional monitoring results are usually presented in the form of text, numbers or charts, which may require professional knowledge to interpret. With AR glasses, users can directly observe dynamic information superimposed on real-world scenes on site, reducing dependence on professional knowledge and enhancing the ease of operation. With AR glasses, users can clearly see the relationship between internal discharge and shell deformation of the equipment, and then determine the coupling mode of these faults. This helps to improve the accuracy of fault diagnosis and avoid relying solely on a certain type of fault signal and missing other important information. Because the health status holographic image combines fault information of multiple dimensions, AR glasses can show the mutual influence between these different faults. Users can judge whether the equipment has potential more complex fault modes from an overall perspective, which helps to make decisions more forward-looking. With AR glasses, users can immediately obtain comprehensive equipment health status and make reasonable repair or replacement decisions based on more detailed information. This immediate feedback can greatly improve response efficiency, reduce equipment downtime and reduce maintenance costs.

[0018] Optionally, the method also includes: if it is determined that there is an abnormal distribution of vibration intensity in the acoustic field interference image, then the abnormality category is determined to be internal looseness and / or partial discharge; if it is determined that there are surface microcracks or uneven deformation in the light field image, then the abnormality category is determined to be shell stress concentration and / or reduced sealing.

[0019] By adopting the above technical solution, the fault type can be determined by clear classification criteria, and the source of the fault can be judged more clearly. Since different fault categories can be clearly distinguished, operators can avoid confusing different types of faults, thereby reducing misjudgments and missed judgments and ensuring the reliability of monitoring results. After clarifying the fault category, maintenance personnel can take more targeted maintenance measures to directly solve specific types of problems without spending a lot of time on irrelevant or minor faults. Acoustic field interference images and light field images reflect different physical phenomena and equipment states respectively. Through their comprehensive analysis, a comprehensive judgment of the equipment state can be made. By combining acoustic and optical data, more comprehensive fault information can be obtained. Multi-dimensional monitoring can help discover potential multiple faults at an early stage. Fusion analysis based on multi-source data can provide a comprehensive view of the equipment status instead of relying solely on a single information source. Therefore, when facing multiple faults or hidden problems, this method can effectively improve the accuracy of system health assessment. Through anomaly detection in acoustic field and light field images, potential problems can be discovered before the fault evolves to a serious stage. Clarifying the specific fault type according to the anomaly category helps maintenance personnel quickly formulate maintenance plans. Since the fault type has been accurately located, maintenance personnel can directly carry out the most relevant maintenance work, saving unnecessary time and labor costs. In addition, the ability to quickly eliminate and handle identified faults can improve the efficiency of the entire operation and maintenance process.

[0020] In a second aspect of the present application, a monitoring device for a GIS switch station is provided, the monitoring device comprising an acquisition module and a processing module, wherein the acquisition module is used to acquire an acoustic field interference image for the GIS switch station; the acquisition module is also used to acquire a light field image for the GIS switch station; the processing module is also used to fuse the acoustic field interference image with the light field image to generate a health status holographic image; the processing module is also used to monitor the GIS switch station through the health status holographic image.

[0021] In the third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs the method described above.

[0022] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, the method described above is executed.

[0023] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: The acoustic field interference image provides an accurate analysis of the internal dynamic characteristics of the equipment. The light field image captures the external structure and apparent changes of the equipment. The two are fused to generate a healthy state holographic image, which integrates the internal dynamic and external static information, and truly realizes a panoramic assessment of the equipment status, covering a variety of physical phenomena. The monitoring method of a single data source tends to ignore the interaction between different anomalies, making it difficult to accurately locate the root cause of the fault. However, the above scheme associates the acoustic field and light field data through a data fusion algorithm to provide a multi-dimensional abnormal feature analysis. The healthy state holographic image can intuitively display the distribution of abnormal signals in space and characteristics, helping to locate the specific location and possible causes of the fault. The acoustic field interference image can capture weak vibrations and abnormal acoustic reflection patterns. The light field image identifies subtle surface cracks and deformations through high-precision imaging. Through the fusion of the generated holographic image, the subtle anomalies are enhanced from multiple angles, the detection sensitivity of early faults is improved, and it is helpful to intervene in advance to prevent small problems from evolving into major faults. Therefore, it is convenient to monitor the GIS switch station. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flow chart of a monitoring method for a GIS switch station provided in an embodiment of the present application.

[0025] Figure 2 Another flowchart of a monitoring method for a GIS switch station provided in an embodiment of the present application.

[0026] Figure 3 A module schematic diagram of a monitoring device for a GIS switch station provided in an embodiment of the present application.

[0027] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0028] Explanation of the reference numerals: 31, acquisition module; 32, processing module; 41, processor; 42, communication bus; 43, user interface; 44, network interface; 45, memory. DETAILED DESCRIPTION

[0029] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0030] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0031] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0032] With the continuous development of power systems and increasingly complex power demands, gas-insulated switchgear (GIS) has become one of the core equipment in power transmission and substations due to its high reliability, compact design and low maintenance requirements. However, the structural complexity and diversity of the working environment of GIS switch stations, especially in the operating environment under extreme conditions such as high voltage and high current, make fault monitoring and health status assessment a severe technical challenge.

[0033] Existing monitoring technologies mainly rely on a single physical quantity information for detection, targeting a specific fault type. For example, partial discharge detection technology mainly focuses on electrical insulation faults. It reflects whether there are insulation problems in electrical equipment by monitoring partial discharge phenomena, but this method cannot fully reflect the overall health status of the equipment. Other technologies, such as temperature rise monitoring, focus on thermal anomalies inside the equipment, monitor changes in equipment temperature, and then infer possible thermal overloads or equipment failures. However, these technologies can often only reflect a single dimension of equipment problems, and it is difficult to comprehensively and systematically evaluate the overall operating status of the GIS switch station. Therefore, it is not conducive to monitoring GIS switch stations.

[0034] In order to solve the above technical problems, the present application provides a monitoring method for a GIS switch station. Figure 1 , Figure 1 A flow chart of a monitoring method for a GIS switch station provided in an embodiment of the present application. The method is applied to a server and includes steps S110 to S140, which are as follows: S110: Acquire an acoustic field interference image of a GIS switch station.

[0035] Specifically, the server refers to a computing and data processing center that is responsible for receiving, storing, processing, and analyzing data collected from sensors and devices. The server can be a local server, a cloud server, or a server cluster, and is mainly responsible for processing tasks. The server receives data from the sensor device, specifically the acoustic field interference image data collected from certain acoustic sensors or acoustic wave transmitting devices. This process includes the acoustic wave signal captured by the sensor, which is processed by the server to generate the corresponding acoustic field interference image. GIS switch station is an important equipment in the power system, mainly used for electrical switching and control. It is enclosed in a gas-insulated environment, so it has high stability and reliability. The acoustic field interference image can help monitor the abnormal state of its internal structure, such as possible partial discharge or structural looseness. The acoustic field interference image is an image reflecting the state of the equipment generated by analyzing the reflection, refraction or scattering of the sound wave when it propagates in the object based on the principle of acoustic wave interference. The acoustic wave reflection signal will be affected by internal structural changes, such as looseness, cracks, defects, etc., and the interference image is generated to display these changes.

[0036] In a possible implementation, an acoustic field interference image for a GIS switch station is obtained, specifically comprising: transmitting acoustic waves into the interior of the GIS switch station through an acoustic wave transmitter; receiving acoustic wave reflection signals according to the acoustic waves, the acoustic wave reflection signals including time delay, waveform characteristics, and energy attenuation; performing time-frequency domain analysis on the acoustic wave reflection signals to extract vibration mode characteristics; and using an acoustic field interference algorithm to perform spatial distribution reconstruction processing on the vibration mode characteristics to obtain an acoustic field interference image.

[0037] Specifically, an acoustic wave transmitter is a device that generates and transmits sound waves of a specific frequency. These sound waves are sent into the GIS switch station and are transmitted in the form of ultrasound. The propagation of sound waves is affected by the different materials and structures inside the equipment, so it can reveal the internal status of the equipment. Assume that a sound wave transmitter is installed inside the GIS switch station. This transmitter transmits a high-frequency ultrasonic signal, which propagates through the metal shell, insulating materials, switchgear, etc. of the GIS switch station. When the sound wave is emitted into the GIS switch station, it encounters different objects and materials. The physical properties of these materials, such as density and elasticity, will change the propagation path of the sound wave, causing the sound wave to be reflected, refracted or scattered. The receiver will receive these reflected signals. Assume that there are loose metal parts or cracks inside the GIS switch station. When the sound wave encounters these defects, the reflected signal will be different from the normal signal. Loose parts may cause time delays and abnormal waveforms of the reflected signal, while cracks may cause more obvious signal attenuation.

[0038] Among them, time-frequency domain analysis is a signal processing technology that analyzes the reflected signal in the time domain and frequency domain simultaneously, and can extract the detailed features in the signal more clearly. For example, the frequency distribution and time domain changes of the signal are analyzed to extract the pattern reflecting the vibration characteristics of the object. The vibration pattern characteristics can reveal abnormalities inside the equipment, such as loose parts, cracks, partial discharge, etc. These abnormalities will cause the equipment to produce different vibration modes. For example, after performing time-frequency domain analysis on the reflected signal, it can be found that if a part is loose, the frequency characteristics of the reflected signal may have a significant offset. If cracks or other defects exist, the vibration pattern of the signal may become irregular. Through this analysis, the vibration pattern characteristics related to the health status of the equipment can be extracted from the signal. The acoustic field interference algorithm is a technology that reconstructs the internal state of a device or object by analyzing the propagation and reflection characteristics of sound waves on different object surfaces or structures. Using this algorithm, the extracted vibration pattern characteristics can be converted into a spatial distribution image of the device. This image can show the vibration mode inside the device and the spatial distribution of abnormal areas. For example, high vibration intensity in certain areas of the image may indicate that the device is loose, cracked, or has other structural problems. Suppose that through acoustic wave detection, it is found that the reflected signal of a certain area is obviously abnormal. After processing through the acoustic field interference algorithm, the system can generate an image of the area, which may show that the vibration intensity in this area is large, and then infer that the area may be loose or damaged. Based on the specific performance of the image, the operation and maintenance personnel can accurately locate the fault area and carry out repairs or further inspections.

[0039] S120: Acquire a light field image of the GIS switch station.

[0040] Specifically, the laser sensor scanning device installed outside the GIS switch station transmits the light field data of the device, including information such as light intensity and phase, to the server, and the server uses the received data to generate a light field image. The light field image is an image generated by collecting the intensity and phase changes of the light reflected from the object. It can reflect the shape, deformation, cracks and other characteristics of the surface of the object. In this case, the generation of the light field image is based on the light reflection of the GIS switch station shell. The light field image can help identify small changes on the surface of the object, including deformation, cracks, stress concentration, etc. These changes are often signs of potential failures. Assume that the shell of the GIS switch station has microcracks due to long-term use or changes in the external environment. When the switch station shell is scanned using laser holography technology, the reflected light waves will change with the presence of cracks, deformations, etc. By analyzing the light intensity and light phase, the generated light field image can intuitively display these abnormal areas. The shell of the GIS switch station is scanned by a laser device, and the laser beam is reflected after being irradiated on the surface of the device. The reflected light signal carries the surface information of the device, including surface deformation, cracks or other abnormal conditions. The reflected light waves will be affected by the surface condition of the device. For example, cracks will change the propagation path of the light waves, causing the phase of the light to change, and surface deformation may cause the intensity of the light to change. These changes are key to analyzing and evaluating the status of the device. The server generates a light field image using the corresponding algorithm based on the received light intensity and phase information. The light field image can show the subtle deformation and crack location of the device surface, allowing operation and maintenance personnel to detect potential problems in a timely manner.

[0041] In a possible implementation, obtaining a light field image for a GIS switch station specifically includes: scanning the outer shell surface of the GIS switch station by a laser beam of a laser holographic device to obtain reflected light intensity and light phase changes; generating a light field image based on the reflected light intensity and light phase changes.

[0042] Specifically, a laser holographic device is a device that uses lasers for precise measurement and image generation. The laser holographic device can emit a laser beam, which is projected onto the surface of an object. When the laser irradiates the surface of an object, part of the laser will be reflected back, and the reflected laser carries some key information about the surface of the object. Suppose a GIS switch station has a tiny crack or uneven deformation on its shell. In order to detect these potential defects, a laser holographic device is used to scan the shell. The device emits laser beams, which irradiate the surface of the shell, and the irradiation point may change with the different surface morphology of the shell. When the laser beam irradiates the surface of an object, part of the light will be reflected back. The physical properties of the surface will affect the intensity of the reflected light. For example, if there is a crack or deformation on the surface, the intensity of the reflected light may change. The phase of the light wave will change during propagation, especially when encountering surface changes, the phase of the reflected light will change. This change reflects the degree of surface deformation or unevenness. Suppose a part of the shell of the GIS switch station has a crack. The light reflected back from the cracked surface will show different intensity and phase compared with the part without cracks. Cracks may reduce the reflection intensity of light waves or change the phase of light waves. This information can be accurately captured by laser holography. The reflected light intensity and phase information are analyzed, and an image reflecting the surface state of the object, namely a light field image, is generated through calculation and image processing algorithms. This image presents information such as surface morphological changes, cracks, and stress concentration. By analyzing these images, operation and maintenance personnel can detect the health status of the GIS switch station. After scanning the shell of the GIS switch station with a laser holographic device, the device generates a light field image. In the image, changes in the intensity and phase of reflected light will appear as different colors or brightness changes in the image. For example, a certain area in the image may have reduced brightness or color changes, indicating that there may be cracks, deformations, or other abnormalities in the area. These images will help operation and maintenance personnel make fault diagnosis and maintenance decisions.

[0043] In a possible implementation, a light field image is generated according to changes in reflected light intensity and light phase, specifically including: determining a target image according to changes in reflected light intensity and light phase; obtaining three-dimensional deformation and crack information of the outer shell of the GIS switch station; adding the three-dimensional deformation and crack information to the target image to obtain a holographic image; and processing the holographic image using a phase unpacking algorithm to obtain a light field image.

[0044] Specifically, the reflected light intensity and light phase change are the key data recorded by the optical sensor during the scanning process. The reflected light intensity describes the intensity of the light reflected back from different areas of the surface, while the light phase change reflects the phase change caused by the change in surface morphology during the propagation of the light wave. Using this information, a target image can be initially generated. This target image shows the reflection intensity and phase change of each part of the surface. Although it may not fully show the three-dimensional deformation or crack information, it already contains the preliminary condition of the equipment surface. Suppose the shell of a GIS switch station is scanned by a laser holographic device. During the scanning process, the light intensity reflected back from certain areas of the shell is low, and the light phase changes significantly, indicating that these areas may have cracks or surface deformations. Based on the intensity and phase changes of these reflected lights, a preliminary target image is generated, showing the abnormal conditions in these areas.

[0045] By analyzing the reflected light intensity and phase changes of the light field image, the three-dimensional deformation of the shell can be further inferred. Specifically, if the surface is deformed, the path of the reflected light will be offset, resulting in changes in light intensity and phase, so that the spatial distribution of these changes can be inferred. Through image processing and calculation algorithms, the three-dimensional deformation information of the shell surface can be extracted from the reflected light data, and defects such as cracks can be identified. Based on the target image, further analysis by the algorithm can identify microcracks on a certain part of the shell surface. The location, size and shape of the crack can be obtained from the light intensity and phase changes in the image, thereby obtaining the details of the three-dimensional deformation and cracks of the shell. Once the three-dimensional deformation and crack information is obtained, this information can be fused into the target image to generate a holographic image. The holographic image not only contains the reflected light information of the surface, but also integrates the spatial distribution characteristics of the shell deformation and cracks, presenting a more comprehensive equipment status. The holographic image is a comprehensive image that reflects the spatial distribution of small changes and defects on the surface, allowing operation and maintenance personnel to understand the health status of the equipment more intuitively.

[0046] In the generated holographic image, the color of a certain area may be darker, indicating a decrease in light intensity, and the light phase change in this area has also changed significantly, indicating that there may be cracks or deformations. These crack information and three-dimensional deformation information are added to the target image, and the generated holographic image shows these details. The phase unpacking algorithm is used to recover the accurate information of surface deformation from the holographic image. Since the phase information in the holographic image may be blurred or ambiguous, the phase unpacking algorithm can eliminate these ambiguities and restore the accurate surface state. The phase unpacking algorithm processes the phase data in the holographic image through mathematical methods, converts the blurred phase information into clear three-dimensional surface data, and thus obtains the final light field image. The light field image shows the detailed deformation, cracks and other status information of the equipment surface, providing support for further fault diagnosis and monitoring. After obtaining the holographic image, the phase unpacking algorithm is applied to accurately restore the phase information in the light field image, thereby clarifying the scope of surface deformation and the location of the crack. The unpacked light field image is not only clearer, but also can show more details, such as the depth and length of the crack.

[0047] S130, fusing the acoustic field interference image with the light field image to generate a health status holographic image.

[0048] Specifically, the acoustic field interference image is an image obtained by analyzing the acoustic wave reflection signal, such as time delay, waveform characteristics and energy attenuation. It mainly reflects the vibration mode, structural abnormality and other information inside the equipment. Through the interference effect of acoustic wave propagation, it can be judged whether there are problems such as looseness, cracks, partial discharge, etc. inside. The light field image obtains the intensity and phase changes of the reflected light through laser scanning, which can reveal the deformation, cracks and surface stress of the equipment shell. Through the light field image, some microcracks, corrosion or other deformations on the external surface can be found, and then the health status of the equipment can be diagnosed. These two types of images start from different physical phenomena and provide health information of GIS switch stations at different levels. The acoustic field image focuses more on internal structural problems, while the light field image focuses on surface and external defects. By fusing these two images, the system can combine the information of the two to generate a holographic image of the health status. The holographic image not only includes the information of internal vibration modes, such as looseness or partial discharge, but also integrates the characteristics of external deformation, such as cracks or surface stress concentration. The health status holographic image can present the overall health status of the GIS switch station in a more comprehensive and integrated manner, helping operation and maintenance personnel to more clearly identify potential fault risks. Compared with a single image, the holographic image provides more diagnostic dimensions and can significantly improve the accuracy and timeliness of fault detection.

[0049] For example, suppose a potential fault occurs in a GIS switch station, which may manifest as internal looseness and surface cracks. At this point, the server first scans the switch station with an acoustic wave sensor to obtain an acoustic field interference image. The image may show abnormal vibration intensity in a certain area, indicating that there is an internal looseness or partial discharge problem at that location. Next, the server uses a laser scanning device to obtain a light field image and finds that there are cracks or slight deformations on the surface of the area, which may cause stress concentration on the shell. The acoustic field image shows the location of internal looseness or partial discharge. The light field image reveals cracks or deformations on the surface of the shell. The server then fuses the two images together through a multimodal algorithm to form a health status holographic image. In this holographic image, users can not only see the location of surface cracks, but also intuitively understand the relationship between these cracks and internal looseness or partial discharge. This image may mark different colors or marks in different areas to indicate the severity of the abnormality, helping staff to quickly locate the source of the fault. With this fused image, the server can judge the health status of the GIS switch station in a more comprehensive dimension. For example, an abnormal area in the image may be marked as internal looseness and surface cracks at the same time, indicating that the area needs to be inspected and repaired. Holographic images can also display abnormal information in different areas, helping operation and maintenance personnel make judgments and take corresponding measures in the shortest time.

[0050] In a possible implementation, the acoustic field interference image is fused with the light field image to generate a health status holographic image, specifically including: using a multimodal convolutional neural network, taking the acoustic field interference image as the first input, and obtaining a vibration feature vector through convolution extraction; using a multimodal convolutional neural network, taking the light field image as the second input, and obtaining a surface deformation feature vector through convolution extraction; fusing the vibration feature vector and the surface deformation feature vector in a fully connected layer, and strengthening the weights of important areas through an attention mechanism to obtain a fused image; in the fused image, marking abnormal areas and abnormal categories to obtain a health status holographic image.

[0051] Specifically, the acoustic field interference image is an image obtained through the propagation and reflection of sound waves, which reflects the vibration mode and abnormal signals inside the device. In this step, the acoustic field interference image is used as the first input of the network. The convolution layer of the multimodal convolutional neural network automatically extracts features related to the vibration mode from these images, such as vibration intensity, time delay, waveform characteristics, etc. This information can reveal possible faults inside the device, such as looseness, partial discharge, etc. The light field image is obtained by a laser scanning device, revealing external features such as deformation and cracks on the surface of the device. It provides information on deformation features of the device surface, such as microcracks and uneven deformation. The light field image is used as the second input. After being processed by the convolution layer of the convolutional neural network, feature vectors related to surface deformation can be extracted. These features help to determine whether there are problems such as stress concentration and reduced sealing on the outside of the device. The extracted vibration feature vector and surface deformation feature vector are fused in the fully connected layer. The fully connected layer is responsible for combining these two feature vectors to form a comprehensive feature representation. The attention mechanism plays an important role in this step. Through the attention mechanism, the network can give higher weights to important areas in the image and ignore irrelevant information. For example, there may be obvious internal looseness and surface cracks in an area. The attention mechanism will emphasize this area, making the abnormality in this area more significant. In the fused image, the server will mark the abnormal area and further determine the category of the abnormality, such as whether it is internal looseness, partial discharge, surface cracks, etc. These abnormal categories and areas ultimately form a health status holographic image, which can comprehensively display the health status of the equipment, indicate which parts have problems, and point out possible causes of failures. The annotation of holographic images helps operation and maintenance personnel locate problems more accurately and take measures.

[0052] For example, through the sound wave reflection signal, the server finds that the vibration of a certain area is abnormal, which may be due to internal looseness or partial discharge. The convolution network of the acoustic field interference image extracts the vibration feature vector of the area and passes it to the subsequent processing layer. At the same time, the laser scanning device captures microcracks or uneven deformation on the surface of the area, which indicates that there may be stress concentration or sealing problems in this part. The convolution layer of the light field image extracts the deformation feature vector of the area and also passes it to the subsequent processing. At this time, the two feature vectors are input into the fully connected layer for fusion. The fully connected layer combines the information from these two different sources into a comprehensive feature representation. The attention mechanism helps to focus on more important areas in this process, such as abnormal vibration and deformation in the area at the same time. Finally, the fused image generates a holographic image of the health status with abnormal areas marked. The server may display a specific area in the image in red and indicate that the problem is "internal looseness and surface cracks."

[0053] S140. Monitor the GIS switch station through the health status holographic image.

[0054] Specifically, the health status holographic image is generated by fusing the acoustic field interference image and the light field image, integrating information from multiple dimensions such as internal vibration, surface deformation, cracks, and partial discharge. This image helps to show the overall health status of the GIS switch station, and by marking abnormal areas, it helps staff quickly locate possible faults. The server uses holographic images to monitor the GIS switch station in real time, which means that the server will regularly or continuously obtain holographic images and analyze them. The server will process these images, analyze the abnormal areas marked in them, check their changing trends, and determine whether new faults have occurred. If an abnormality is detected in a certain area, the server can issue an alarm in time to remind the operation and maintenance personnel to inspect and maintain it. When the equipment of the GIS switch station is in operation, some potential faults may occur, such as cracks on the surface of the equipment, loose internal components, partial discharge, etc. Using the health status holographic image, the server can identify these problems in time and monitor them to ensure that the equipment is handled before the failure occurs. During the monitoring process, the server will focus on the abnormal areas marked in the holographic image. For example, if abnormal vibration is detected in a certain area and accompanied by surface cracks, the system will analyze whether this situation poses a danger and may prompt the operation and maintenance personnel that the area needs emergency maintenance or shutdown inspection.

[0055] In a possible implementation, a health status holographic image is sent to AR glasses worn by a user; and through the AR glasses, the coupling relationship between the internal discharge and the shell deformation marked in the health status holographic image is displayed to the user.

[0056] Specifically, during the monitoring process, the server generates a holographic image of the health status by analyzing the sound field and light field data of the GIS switch station. This image contains information in multiple dimensions, such as internal faults of the equipment, surface cracks, vibration intensity, deformation, etc. The holographic image of the health status can be transmitted to the AR glasses worn by the user through the network. After receiving these images, the AR glasses will superimpose the image content on the field of view of the real world in the form of virtual elements and display them in real time. AR glasses can not only display the holographic image of the health status, but also highlight the abnormal conditions of the equipment through the marked areas in the image. For example, abnormal areas of internal discharge and shell deformation will be marked in the image. AR technology allows users to see these marks at the actual location of the equipment, helping operation and maintenance personnel to analyze the equipment status in real time without relying on traditional displays or paper reports. Through holographic images, AR glasses can show the coupling relationship between internal faults and surface deformation of the equipment. This relationship refers to how these two faults affect each other or occur at the same time, and may lead to an increased risk of equipment failure. In the image, maintenance personnel can see the location of internal discharge and the specific location of shell surface deformation. The system can directly link these two areas through the display of AR glasses to provide a complete picture of the fault.

[0057] For example, suppose that a problem occurs in the equipment of a GIS switch station during the operation and maintenance process, and the operation and maintenance personnel wear AR glasses for real-time monitoring and analysis. The server has generated a holographic image of the health status and transmitted the image to the AR glasses worn by the operation and maintenance personnel through a wireless network. The image seen by the operation and maintenance personnel through the AR glasses is superimposed on the equipment, showing the location of the cracks on the surface of the equipment and the possible local discharge area. The AR glasses highlight the area of ​​internal discharge of the equipment in red through image marking, and the location of the surface cracks is marked in yellow. At the same time, text labels are displayed on the glasses to explain what type of faults these areas represent, for example, "internal discharge" indicates an electrical insulation problem, and "surface cracks" indicate stress concentration problems. In the image, the AR glasses display a visual connection line or overlapping area, clearly indicating the relationship between the discharge area inside the equipment and the crack area of ​​the shell. For example, local discharge may have occurred at the edge of the crack, indicating that the crack may have caused local damage to the electrical insulation. A warning box may also pop up in the AR glasses, indicating that the coupling relationship between the two may cause further damage to the equipment and need to be repaired first. With the guidance of AR glasses, maintenance personnel can quickly locate the problem and understand the relationship between these anomalies, so as to make more accurate repair decisions, such as shutting down certain equipment areas for inspection, or repairing cracks and electrical insulation problems.

[0058] In one possible implementation, refer to Figure 2 , Figure 2Another flow chart of a monitoring method for a GIS switch station provided in an embodiment of the present application. Specifically, it includes step S210 to step S220, and the above steps are as follows: S210, if it is determined that there is an abnormal distribution of vibration intensity in the acoustic field interference image, the abnormal category is determined to be internal looseness and / or partial discharge; S220, if it is determined that there are surface microcracks or uneven deformation in the light field image, the abnormal category is determined to be shell stress concentration and / or reduced sealing.

[0059] Specifically, the acoustic reflection signal provides detailed information about the vibration inside the device. If an abnormal distribution of vibration intensity is found in the acoustic field interference image, it means that there is a problem inside the device, such as loose parts, unstable structure, or partial discharge caused by electrical faults. Loose parts or loose connections inside the device may cause abnormal vibration of the device during operation, increasing the risk of wear or failure of the device. Abnormal vibration may also be caused by partial discharge, which occurs at the point where electrical insulation is broken or poorly connected, and may cause serious consequences such as electrical damage or fire to the device. The surface of the device is scanned by a laser holographic device to obtain light reflection intensity and light phase changes, thereby generating a light field image. If the light field image shows microcracks or uneven deformation on the surface, this indicates that the device housing may be affected by external forces or stress concentration, which may affect the sealing or structural integrity of the device. When stress concentration occurs on the surface of the device, it will cause local cracks or deformations, which may further develop into more serious damage. Stress concentration may be caused by design problems of the device, poor operating environment, or long-term load. Surface cracks or deformation may cause the sealing of the equipment casing to decrease, especially in high-voltage electrical equipment such as GIS switch stations. Sealing problems may cause risks such as gas leakage and pollutant intrusion, which in turn affect the safety and stability of the equipment.

[0060] For example, suppose a device in a GIS switch station, such as a circuit breaker, is being monitored. In the acoustic field interference image, the operation and maintenance server detects abnormal vibration intensity in a certain area, which is located at the connection part of the equipment. The vibration signal shows that the vibration amplitude of this part exceeds the normal range, which may be caused by a loose component or electrical failure. The server determines the abnormality category as internal looseness or partial discharge based on the analysis results. The operation and maintenance personnel can confirm whether there are loose parts inside the equipment or whether there is electrical insulation damage that causes partial discharge through further inspection. At the same time, the light field image obtained by scanning the surface of the equipment with a laser holographic device shows that there are tiny cracks on the surface of the equipment shell, and uneven deformation occurs in some areas. This indicates that the equipment shell may be subjected to excessive mechanical stress, resulting in cracks or uneven deformation on the surface. Based on these anomalies in the light field image, the server determines the abnormality category as shell stress concentration and reduced sealing. The operation and maintenance personnel can further check the location of the surface cracks to determine whether the cracks in the shell need to be repaired and check whether the sealing performance is affected.

[0061] The present application also provides a monitoring device for a GIS switch station, referring to Figure 3 , Figure 3 A module schematic diagram of a monitoring device for a GIS switch station provided in an embodiment of the present application. The monitoring device is a server, and the server includes an acquisition module 31 and a processing module 32, wherein the acquisition module 31 acquires an acoustic field interference image for the GIS switch station; the acquisition module 31 acquires a light field image for the GIS switch station; the processing module 32 fuses the acoustic field interference image with the light field image to generate a health status holographic image; the processing module 32 monitors the GIS switch station through the health status holographic image.

[0062] In a possible implementation, the acquisition module 31 acquires the sound field interference image for the GIS switch station, specifically including: the processing module 32 transmits sound waves to the inside of the GIS switch station through a sound wave transmitter; the processing module 32 receives the sound wave reflection signal according to the sound wave, and the sound wave reflection signal includes time delay, waveform characteristics and energy attenuation; the processing module 32 performs time-frequency domain analysis on the sound wave reflection signal to extract the vibration mode characteristics; the processing module 32 uses the sound field interference algorithm to perform spatial distribution reconstruction processing on the vibration mode characteristics to obtain the sound field interference image.

[0063] In a possible implementation, the acquisition module 31 acquires a light field image for a GIS switch station, specifically including: a processing module 32 scans the outer shell surface of the GIS switch station through a laser beam of a laser holographic device to obtain reflected light intensity and light phase changes; the processing module 32 generates a light field image based on the reflected light intensity and light phase changes.

[0064] In a possible implementation, the processing module 32 generates a light field image according to the reflected light intensity and light phase changes, specifically including: the processing module 32 determines the target image according to the reflected light intensity and light phase changes; the acquisition module 31 acquires the three-dimensional deformation and crack information of the shell of the GIS switch station; the processing module 32 adds the three-dimensional deformation and crack information to the target image to obtain a holographic image; the processing module 32 uses a phase unpacking algorithm to process the holographic image to obtain a light field image.

[0065] In a possible implementation, the processing module 32 fuses the sound field interference image with the light field image to generate a health status holographic image, which specifically includes: the processing module 32 uses a multimodal convolutional neural network to take the sound field interference image as the first input, and obtains a vibration feature vector through convolution extraction; the processing module 32 uses a multimodal convolutional neural network to take the light field image as the second input, and obtains a surface deformation feature vector through convolution extraction; the processing module 32 fuses the vibration feature vector and the surface deformation feature vector in the fully connected layer, and strengthens the weight of important areas through the attention mechanism to obtain a fused image; the processing module 32 marks abnormal areas and abnormal categories in the fused image to obtain a health status holographic image.

[0066] In a possible implementation, the processing module 32 sends a health status holographic image to the AR glasses worn by the user; the processing module 32 displays the coupling relationship between the internal discharge and the shell deformation marked in the health status holographic image to the user through the AR glasses.

[0067] In one possible implementation, if the processing module 32 determines that there is an abnormal distribution of vibration intensity in the acoustic field interference image, the abnormality category is determined to be internal looseness and / or local discharge; if the processing module 32 determines that there are surface microcracks or uneven deformation in the light field image, the abnormality category is determined to be shell stress concentration and / or reduced sealing.

[0068] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0069] The present application also provides an electronic device, referring to Figure 4 , Figure 4The electronic device may include: at least one processor 41 , at least one network interface 44 , a user interface 43 , a memory 45 , and at least one communication bus 42 .

[0070] The communication bus 42 is used to realize the connection and communication between these components.

[0071] The user interface 43 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 43 may also include a standard wired interface and a wireless interface.

[0072] The network interface 44 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0073] Among them, the processor 41 may include one or more processing cores. The processor 41 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 45, and calling data stored in the memory 45. Optionally, the processor 41 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 41 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 41, and it can be implemented separately through a chip.

[0074] Among them, the memory 45 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 45 includes a non-transitory computer-readable storage medium. The memory 45 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 45 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 45 may also be optionally at least one storage device located away from the aforementioned processor 41. As Figure 4 As shown, the memory 45 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a monitoring method for a GIS switch station.

[0075] exist Figure 4 In the electronic device shown, the user interface 43 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 41 can be used to call an application program for a GIS switch station monitoring method stored in the memory 45. When executed by one or more processors, the electronic device executes one or more methods in the above-mentioned embodiments.

[0076] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0077] The present application also provides a computer-readable storage medium, which stores instructions. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0078] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0079] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0080] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0081] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0082] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0083] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A monitoring method for a GIS switch station, characterized in that: The method comprises: Acquire the acoustic field interference image for GIS switch station; Acquire a light field image for the GIS switch station; Fusing the acoustic field interference image with the light field image to generate a health status holographic image; The GIS switch station is monitored by means of the health status holographic image.

2. The monitoring method of GIS switch station according to claim 1, characterized in that: The step of obtaining the acoustic field interference image for the GIS switch station specifically includes: The acoustic wave transmitter emits acoustic waves into the interior of the GIS switch station; According to the sound wave, receiving a sound wave reflection signal, wherein the sound wave reflection signal includes a time delay, a waveform characteristic, and an energy attenuation; Performing time-frequency domain analysis on the sound wave reflection signal to extract vibration mode characteristics; The acoustic field interference algorithm is used to perform spatial distribution reconstruction processing on the vibration mode characteristics to obtain the acoustic field interference image.

3. The monitoring method of GIS switch station according to claim 1, characterized in that: The acquiring of the light field image for the GIS switch station specifically includes: Scanning the shell surface of the GIS switch station by means of a laser beam of a laser holographic device to obtain reflected light intensity and light phase changes; The light field image is generated according to the reflected light intensity and the light phase change.

4. The monitoring method of GIS switch station according to claim 3, characterized in that: Generating the light field image according to the reflected light intensity and the light phase change specifically includes: Determining a target image according to the reflected light intensity and the light phase change; Acquiring three-dimensional deformation and crack information of the shell of the GIS switch station; Adding the three-dimensional deformation and the crack information to the target image to obtain a holographic image; The holographic image is processed using a phase unpacking algorithm to obtain the light field image.

5. The monitoring method of GIS switch station according to claim 1, characterized in that: The fusing the acoustic field interference image with the light field image to generate a health status holographic image specifically includes: Using a multimodal convolutional neural network, the sound field interference image is used as a first input, and a vibration feature vector is obtained through convolution extraction; Using the multimodal convolutional neural network, the light field image is used as a second input, and a surface deformation feature vector is obtained through convolution extraction; The vibration feature vector and the surface deformation feature vector are fused in a fully connected layer, and the weights of important areas are strengthened through an attention mechanism to obtain a fused image; In the fused image, abnormal areas and abnormal categories are marked to obtain the health status holographic image.

6. The monitoring method of GIS switch station according to claim 1, characterized in that: The method further comprises: Sending the health status holographic image to the AR glasses worn by the user; The coupling relationship between the internal discharge and the shell deformation marked in the health status holographic image is displayed to the user through the AR glasses.

7. The monitoring method of GIS switch station according to claim 5, characterized in that: The method further comprises: If it is determined that there is an abnormal distribution of vibration intensity in the acoustic field interference image, then determining that the abnormal category is internal looseness and / or partial discharge; If it is determined that there are surface microcracks or uneven deformation in the light field image, the abnormality category is determined to be shell stress concentration and / or reduced sealing.

8. A monitoring device for a GIS switch station, characterized in that: The monitoring device comprises an acquisition module (31) and a processing module (32), wherein: The acquisition module (31) is used to acquire an acoustic field interference image for a GIS switch station; The acquisition module (31) is further used to acquire a light field image for the GIS switch station; The processing module (32) is further used to fuse the acoustic field interference image with the light field image to generate a health status holographic image; The processing module (32) is also used to monitor the GIS switch station through the health status holographic image.

9. An electronic device, characterized in that: The electronic device comprises a processor (41), a memory (45), a user interface (43) and a network interface (44), wherein the memory (45) is used to store instructions, the user interface (43) and the network interface (44) are both used to communicate with other devices, and the processor (41) is used to execute the instructions stored in the memory (45) so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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