Power transformer vibration noise online monitoring system and method

Abstract

The invention provides an online monitoring system and method for vibration noise of a power transformer, and belongs to the technical field of online monitoring of power equipment.The online monitoring system comprises an entity layer, a data management layer, a sensor layout layer, a three-dimensional model layer and a function application layer, the sensor layout layer is used for carrying out simulation analysis on vibration of the power transformer by utilizing a multi-body dynamics technology and designing layout of sensors on the power transformer according to an analysis result, and the three-dimensional model layer is used for carrying out three-dimensional scanning on the power transformer by utilizing an MR technology and constructing a digital twin model of the transformer; the function application layer uses VR equipment to carry out VR inspection work on the power transformer. The problems that regular power failure inspection affects normal operation of a power system, manpower and material resource cost of maintenance is increased, and characteristics of vibration and noise signals cannot be accurately extracted in a strong noise environment are solved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of online monitoring of power equipment, and in particular relates to an online monitoring system and method for vibration and noise of a power transformer. BACKGROUND

[0002] A power transformer is an important power equipment in a power system. According to statistics, mechanical faults such as winding deformation, winding loosening and core loosening account for a large proportion in various internal mechanical faults of the transformer. During operation of the transformer, periodic vibration signals will be generated due to influences of periodic ampere force of the winding, magnetic strain of the core and opening of the cooling equipment, and the vibration signals are transmitted to the oil tank via the transformer oil and the bottom support base, carrying state information of the internal mechanical structure. When a mechanical fault occurs in the transformer, the vibration signals of the oil tank will change accordingly. Therefore, by arranging a vibration sensor on the surface of the oil tank wall of the transformer, the vibration waveform can be collected to effectively reflect the internal mechanical state and discover structural defects in time, which is of great significance to ensure normal operation of the transformer.

[0003] Traditional maintenance strategies usually adopt methods of periodic power-off inspection and offline test. Although these methods can discover potential problems of the transformer to a certain extent, the following disadvantages exist: Periodic power-off inspection will affect normal operation of the power system, reduce power supply reliability, increase manpower and material costs of maintenance, and cannot accurately extract features of vibration and noise signals in a strong noise environment. Therefore, an online monitoring system and method for vibration and noise of a power transformer are designed. SUMMARY

[0004] The online monitoring system and method for vibration and noise of a power transformer provided by the embodiments of the present application solve the problems that periodic power-off inspection will affect normal operation of the power system, reduce power supply reliability, increase manpower and material costs of maintenance, and cannot accurately extract features of vibration and noise signals in a strong noise environment.

[0005] In view of the above problems, the technical scheme provided by the present application is: The present application provides an online monitoring system for vibration and noise of a power transformer, comprising a physical layer, a data management layer, a sensor layout layer, a three-dimensional model layer and a functional application layer. The physical layer is a plurality of power transformers. The data management layer collects vibration and noise data of the power transformer by using a sensor, stores and processes the data, and provides data support. The sensor layout layer simulates and analyzes the vibration of the power transformer by using multi-body dynamics technology, designs the layout of the sensor on the power transformer according to the analysis result, and comprises a multi-body dynamics model, a vibration simulation unit, a vibration analysis unit and a sensor design unit. The multi-body dynamics model establishes a dynamic model of the power transformer by using multi-body dynamics software. The vibration simulation unit simulates the vibration of the transformer based on the dynamic model, sets different operating conditions, and runs the simulation. The vibration analysis unit analyzes the vibration response of the transformer under each operating condition according to the simulation of the vibration simulation unit, and identifies the natural frequency and vibration mode of the transformer. The sensor design unit determines the installation position of the sensor according to the vibration analysis result. The three-dimensional model layer uses MR technology to perform three-dimensional scanning on the power transformer, and constructs a digital twin model of the power transformer based on the scanned data, and synchronously predicts the state of the power transformer in real time. The functional application layer uses VR equipment to perform VR inspection work on the power transformer based on the model established by the three-dimensional model layer.

[0006] As a preferred technical solution of the present application, the data management layer comprises a data acquisition module, a data blockchain processing module and a data processing module. The data acquisition module uses sensors to collect vibration noise of the power transformer in real time, and obtains vibration noise data, the data acquisition module comprises a sensor unit and a data transmission unit, the sensor unit installs sensors based on the sensor layout scheme designed by the sensor layout layer, and the data transmission unit is used for transmitting sensor data to the data blockchain processing module and the data processing module for subsequent processing. The data blockchain processing module stores the collected power transformer data by using blockchain technology, and the data blockchain processing module comprises a data encryption unit, a data uploading unit and a data decryption unit. The data encryption unit uses the distributed ledger technology of the blockchain to package the encrypted data into blocks, and adds the blocks to the blockchain network through the consensus algorithm. The data uploading unit encrypts the collected data, and stores the data in a distributed manner through the blockchain network, and builds a distributed network based on the blockchain. The data decryption unit decrypts the data through the consensus mechanism in the blockchain network, and the decrypted data is used for subsequent analysis. The data processing module processes and analyzes the collected data by using wavelet transform and logistic regression algorithm.

[0007] As a preferred embodiment of the present invention, the data processing module includes a data preprocessing unit, a feature extraction unit, and a data classification unit; The data preprocessing unit performs routine preprocessing on the collected data; The feature extraction unit selects wavelet basis functions that are compatible with the vibration and noise data of power transformers, performs multi-level wavelet decomposition on the data, obtains approximate signals and detail signals at different scales, extracts features from the approximate signals and detail signals at each scale, calculates the statistical features of the wavelet coefficients at each scale, and uses principal component analysis to select features that contribute to the classification. The data classification unit uses a logistic regression algorithm to classify the state of power transformers based on the extracted feature data.

[0008] As a preferred embodiment of the present invention, the three-dimensional model layer includes a three-dimensional scanning unit, a twin model construction unit, a data mapping unit, and a real-time update unit; The three-dimensional scanning unit receives sensor data by setting up an MR device and uses the 3D scanning function in MR technology to obtain the actual structural data of the power transformer, which is used to capture the position and movement of the power transformer, as well as the spatial information of the surrounding environment. The twin model construction unit constructs a twin model based on the associated data using digital twin technology, and uses physical laws and algorithms to simulate the behavior of the entity; The data mapping unit converts the data from the 3D scanning unit into 3D point cloud data that can be used for digital model construction, and associates the data with the digital model. The real-time update unit is used to feed real-time data back into the digital twin model to maintain the model's real-time performance.

[0009] As a preferred embodiment of the present invention, the functional application layer includes a VR inspection module and a positioning module; The VR inspection module utilizes VR wearable devices, such as VR headsets, to view and interact with a virtual power transformer environment. The positioning module is used to accurately capture the user's position and movement in the virtual environment; The detailed inspection steps of the VR inspection module are as follows: Step a: Use a VR software development kit to integrate the digital twin model and VR wearable devices, import the digital twin model into the VR environment, and have staff wear VR wearable devices to enter the virtual power transformer environment; Step b: Familiarize yourself with the structure and layout of the transformer in the VR environment, and understand the sensor locations and monitoring data in different areas; Step c: Use a positioning device to walk in the virtual environment, simulate the actual inspection path, view the real-time feedback of vibration and noise data, and use a VR controller to interact with the power transformer components in the virtual environment. Step d: In the VR environment, based on the diagnostic results output by the 3D model, locate the fault area and analyze the cause of the fault.

[0010] As a preferred embodiment of the present invention, the detailed processing steps for sensor distribution in the sensor layout layer are as follows: Step 1: Define the components, connection methods, constraints and external forces of the multibody dynamics model, establish the dynamic equations based on the Newton-Euler or Lagrange equations, and determine the geometric parameters, mass and inertia matrix of each part. Step 2: Define the magnitude, direction, and point of application of the excitation force, and use a multibody dynamics model to simulate vibration and calculate the system's natural frequencies, modes, and response. Step 3: Determine the required physical quantities, range, and accuracy; select the appropriate sensor type; design the sensor installation method and electrical interface; and integrate them into the model. Step four: Collect vibration data using sensors for vibration analysis, and optimize the sensor design based on the analysis results.

[0011] On the other hand, a method for an online monitoring system for vibration and noise of a power transformer includes the following steps: S1. Use MR equipment to scan the actual structure of the transformer, generate a 3D model, import the 3D model into the digital twin platform, and establish a twin model of the transformer. S2, based on the actual structural data of the transformer, multibody dynamics is used to simulate and analyze the vibration of the transformer, and the position of the sensor for monitoring the transformer is optimized according to the vibration of the transformer. S3, based on the designed installation location, install the corresponding sensors to collect vibration and noise data of the power transformer; S4. The collected data is stored using blockchain technology, and the data processing module is used to extract and classify the data to output fault diagnosis results. S5, at the same time, uses VR technology to simultaneously construct a virtual environment for free inspection of the transformer model, thus completing the virtual and real monitoring of the power transformer.

[0012] Compared with the prior art, the beneficial effects of the present invention are: (1) This invention uses multibody dynamics to simulate the vibration of power transformers, and optimizes the layout of sensors based on the results. It determines which areas on the transformer have the largest or most critical vibration amplitude, thereby optimizing the layout of sensors in these areas to ensure that the sensors are placed in the positions that can capture the most useful vibration information, reducing redundant data acquisition, improving the correlation of data and the overall efficiency of the monitoring system. (2) The present invention scans the actual structure of the transformer using MR equipment and establishes a digital twin model based on the three-dimensional data. By simulating the behavior of the actual transformer and synchronizing the status data of the physical transformer in real time, it is used to predict future performance, simulate different operating conditions, and perform virtual testing and fault analysis to achieve real-time status monitoring and prediction. (3) This invention enables staff to inspect various parts of the transformer and view sensor data in a virtual environment through VR technology and digital twin model, thereby reducing on-site inspection time, improving maintenance efficiency, and enhancing inspection efficiency and safety.

[0013] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the structure of an online monitoring system for vibration and noise of a power transformer disclosed in this invention; Figure 2 This is a schematic diagram of the method flow of an online monitoring system for vibration and noise of a power transformer disclosed in this invention; Explanation of reference numerals in the attached figures: 101, Entity Layer; 102, Data Management Layer; 1021, Data Acquisition Module; 10211, Sensor Unit; 10212, Data Transmission Unit; 1022, Data Blockchain Processing Module; 10221, Data Encryption Unit; 10222, Data Upload Unit; 10223, Data Decryption Unit; 1023, Data Processing Module; 10231, Data Preprocessing Unit; 10232, Feature Extraction Unit; 10233, Data Classification Unit; 103, Sensor Layout Layer; 1031, Multibody Dynamics Model; 1032, Vibration Simulation Unit; 1033, Vibration Analysis Unit; 1034, Sensor Design Unit; 104, 3D Model Layer; 1041, 3D Scanning Unit; 1042, Twin Model Construction Unit; 1043, Data Mapping Unit; 1044, Real-time Update Unit; 105, Functional Application Layer; 1051, VR Inspection Module; 1052, Positioning Module. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0017] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0018] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0019] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0020] Example 1 See attached document Figure 1 As shown, the present invention provides a technical solution: an online monitoring system for vibration and noise of power transformers, comprising a physical layer 101, a data management layer 102, a sensor layout layer 103, a three-dimensional model layer 104, and a functional application layer 105; The physical layer 101 consists of several power transformers; The data management layer 102 uses sensors to collect data on vibration and noise from the power transformer, and stores and processes the data to provide data support. The sensor layout layer 103 uses multibody dynamics technology to simulate and analyze the vibration of the power transformer. Based on the analysis results, the layout of the sensors on the power transformer is designed. The sensor layout layer 103 includes a multibody dynamics model 1031, a vibration simulation unit 1032, a vibration analysis unit 1033, and a sensor design unit 1034. Multibody dynamics model 1031: A dynamic model of a power transformer is established using multibody dynamics software; The vibration simulation unit 1032 simulates the vibration of a transformer based on a dynamic model, sets different operating conditions, and runs the simulation. Based on the simulation results of the vibration simulation unit 1032, the vibration analysis unit 1033 analyzes the vibration response of the transformer under various operating conditions, identifies the natural frequency and vibration mode of the transformer, and determines the area with large vibration amplitude, i.e. the vibration hot spot area. Based on the vibration analysis results of sensor design unit 1034, and considering the sensor's performance parameters such as sensitivity and frequency response range, the installation location of the sensor is determined according to the vibration hotspot area. The 3D model layer 104 uses MR technology to perform 3D scanning of the power transformer and constructs a digital twin model of the power transformer based on the scanned data, synchronizing the power transformer status in real time and making predictions. The functional application layer 105 is based on the model established by the three-dimensional model layer 104, and uses VR equipment to carry out VR inspection of power transformers.

[0021] The embodiments of the present invention are also implemented through the following technical solutions.

[0022] In an embodiment of the present invention, the data management layer 102 includes a data acquisition module 1021, a data blockchain processing module 1022, and a data processing module 1023. The data acquisition module 1021 uses sensors to collect vibration and noise data of the power transformer in real time. The data acquisition module 1021 includes a sensor unit 10211 and a data transmission unit 10212. The sensor unit 10211 installs the sensors based on the sensor layout scheme designed by the sensor layout layer 103. The data transmission unit 10212 is used to transmit the sensor data to the data blockchain processing module 1022 and the data processing module 1023 for subsequent processing. The data blockchain processing module 1022 uses blockchain technology to store the collected power transformer data. The data blockchain processing module 1022 includes a data encryption unit 10221, a data uploading unit 10222, and a data decryption unit 10223. The data encryption unit 10221 uses the distributed ledger technology of blockchain to ensure that the data is immutable and traceable, packages the encrypted data into blocks, and adds the blocks to the blockchain network through a consensus algorithm; The data upload unit 10222 encrypts the collected data and then stores it in a distributed manner through a blockchain network. It builds a distributed network based on blockchain, including node configuration and network protocol settings, to provide a decentralized storage and transmission platform for the data. The data decryption unit 10223 verifies the integrity and authenticity of the data through the consensus mechanism in the blockchain network. After ensuring the reliability of the data source, it decrypts the data for subsequent analysis. The data processing module 1023 uses wavelet transform and logistic regression algorithms to process and analyze the collected data.

[0023] In an embodiment of the present invention, the data processing module 1023 includes a data preprocessing unit 10231, a feature extraction unit 10232, and a data classification unit 10233; The data preprocessing unit 10231 performs routine preprocessing on the collected data to remove noise and outliers; The feature extraction unit 10232 selects wavelet basis functions that are compatible with the vibration and noise data of power transformers, performs multi-level wavelet decomposition on the data, and obtains approximate signals and detail signals at different scales. Functions such as pywt.wavedec can be used for decomposition to extract features from the approximate signals and detail signals at each scale, calculate the statistical features of the wavelet coefficients at each scale, and use principal component analysis to select features that contribute to the classification. Data classification unit 10233 uses logistic regression algorithm to classify the state of power transformers based on extracted feature data, such as normal or abnormal. It provides a basis for classification by setting thresholds to determine the real-time state of the transformer.

[0024] In an embodiment of the present invention, the three-dimensional model layer 104 includes a three-dimensional scanning unit 1041, a twin model construction unit 1042, a data mapping unit 1043, and a real-time update unit 1044; The 3D scanning unit 1041 receives sensor data by setting up MR equipment, including accelerometer, gyroscope, magnetometer, depth camera and position sensor. Using the 3D scanning function in MR technology, it obtains the actual structural data of the power transformer through methods such as laser scanning or structured light scanning, in order to capture the position and movement of the power transformer, as well as the spatial information of the surrounding environment. The twin model building unit 1042 constructs a twin model based on the associated data using digital twin technology. It simulates the behavior of the entity using physical laws and algorithms, and creates an accurate digital model using the results of 3D scanning and data mapping. Physical properties, such as material characteristics and thermodynamic properties, are added to the digital model. Simulations are run on the digital model to simulate the behavior of the physical object under different conditions, ensuring real-time data synchronization between the digital twin model and the physical object to reflect the actual operating status. Predictive models are used to predict the operating status of power transformers, allowing for proactive solutions when problems are predicted. These models include machine learning or deep learning models such as regression models, time series models, and neural networks. The data mapping unit 1043 converts the data from the 3D scanning unit 1041 into 3D point cloud data that can be used for digital model construction, and associates the data with the digital model, such as a CAD model or a virtual reality model, to facilitate subsequent analysis and simulation, and to ensure the correspondence between the physical model and the digital model, including geometric, structural and behavioral features. The real-time update unit 1044 is used to feed real-time data back into the digital twin model to maintain the model's real-time performance.

[0025] In an embodiment of the present invention, the data mapping unit 1043 associates data with the model in the following details: Step A: Determine the architecture of the digital model, including its variables, parameters, and states; list the correspondence between physical data (such as temperature, pressure, vibration, etc.) and digital model parameters (such as material properties, boundary conditions, etc.); and formulate the priority and conditions for data mapping. For example, some data may only be associated with the model under specific operating conditions. Step B involves defining a mapping function from data features to model parameters, which can be linear or non-linear, and determining the parameters of the mapping function. This requires training using machine learning techniques. Step C: Input the preprocessed data into the digital twin model in real time or periodically through a mapping mechanism, and update the state of the digital model with the new data to keep the model synchronized with the physical entity; Real-time update unit 1044 begins synchronously when the mapping rules are defined. This process involves transforming the real-time acquired data through predefined mapping rules and immediately applying it to the digital twin model. Real-time update is the practical application of data mapping, ensuring that the digital twin model always reflects the latest state of the physical entity. In practice, data mapping and real-time update are tightly coupled and performed synchronously. Once the data is acquired and preprocessed, it is immediately transformed through the mapping rules and updated to the model in real time. This process is continuous and may be completed within milliseconds to seconds to ensure the real-time performance and accuracy of the model.

[0026] In an embodiment of the present invention, the functional application layer 105 includes a VR inspection module 1051 and a positioning module 1052; The VR inspection module 1051 utilizes VR wearable devices, such as VR headsets, to view and interact with a virtual power transformer environment. The positioning module 1052 utilizes a UWB locator to accurately capture the user's position and movement in the virtual environment; The detailed inspection steps for VR inspection module 1051 are as follows: Step a: Use a VR software development kit to integrate the digital twin model and VR wearable devices, import the digital twin model into the VR environment, and have staff wear VR wearable devices to enter the virtual power transformer environment; Step b: Familiarize yourself with the structure and layout of the transformer in the VR environment, and understand the sensor locations and monitoring data in different areas; Step c: Use the positioning device to walk in the virtual environment, simulate the actual inspection path, and view the real-time feedback of vibration and noise data, including vibration amplitude, frequency and noise level. Use the VR controller to interact with the power transformer components in the virtual environment, such as opening the maintenance door, checking the cooling system, etc. Zoom in, zoom out and rotate the suspected fault area for more detailed observation. Step d: In the VR environment, based on the diagnostic results output by the 3D model, locate the fault area and analyze the cause of the fault, such as structural defects, loose parts, etc.

[0027] The detailed steps for importing the digital twin model into the VR environment in step a are as follows: Step a1: Convert the digital twin model into a format supported by VR software, such as FBX, OBJ, or GLB; Step a2: Import the converted model into the VR software and make necessary adjustments to ensure that the model is displayed correctly in the VR environment; Step a3: Use the interactive tools of VR software to enable the interaction between staff and the digital twin model.

[0028] In an embodiment of the present invention, the detailed processing steps of the sensor distribution by the sensor layout layer 103 are as follows: Step 1: Define the components, connection methods, constraints and external forces of the multibody dynamics model 1031, establish the dynamic equations based on the Newton-Euler or Lagrange equations, and determine the geometric parameters, mass and inertia matrix of each part. Step 2: Define the magnitude, direction, and point of application of the excitation force, and use the multibody dynamics model 1031 to perform vibration simulation and calculate the natural frequency, modes, and response of the system; Step 3: Determine the required physical quantities, range, and accuracy; select the appropriate sensor type; design the sensor installation method and electrical interface; and integrate them into the model. Step four: Collect vibration data using sensors for vibration analysis, and optimize the sensor design based on the analysis results.

[0029] Example 2 See attached document Figure 2 As shown in the figure, another embodiment of the present invention provides a method for an online monitoring system for vibration and noise of a power transformer, comprising the following steps: S1. Use MR equipment to scan the actual structure of the transformer, generate a 3D model, import the 3D model into the digital twin platform, and establish a twin model of the transformer. S2, based on the actual structural data of the transformer, multibody dynamics is used to simulate and analyze the vibration of the transformer, and the position of the sensor for monitoring the transformer is optimized according to the vibration of the transformer. S3, based on the designed installation location, install the corresponding sensors to collect vibration and noise data of the power transformer; S4 stores the collected data using blockchain technology and uses the data processing module 1023 to extract features and classify the data, outputting fault diagnosis results; S5, at the same time, uses VR technology to synchronously construct a virtual environment for free inspection of the transformer model, completes the virtual and real monitoring of the power transformer, and realizes the status analysis of the production site through data collection during the virtual and real mapping process, such as equipment and object placement rate, equipment operation and charging status, and supports managers to make decisions and controls based on the production site status, and notify personnel to coordinate the execution of equipment to complete the decision.

[0030] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the invention should be included within the scope of protection of the invention.

[0031] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0032] In the detailed description above, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than are explicitly stated in each claim. Rather, as reflected in the appended claims, the invention is presented with fewer features than all of the features in a single disclosed embodiment. Therefore, the appended claims are hereby explicitly incorporated into the detailed description, with each claim representing a separate preferred embodiment of the invention.

[0033] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0034] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0035] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0036] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term "comprising" as used in the specification or claims is interpreted in a manner similar to the term "including," as interpreted when used as a conjunction in the claims. Additionally, the use of any term "or" in the specification of the claims is intended to mean "non-exclusive or."

Claims

1. An online monitoring system for vibration and noise of power transformers, characterized in that, It includes a physical layer (101), a data management layer (102), a sensor layout layer (103), a 3D model layer (104), and a functional application layer (105). The physical layer (101) consists of several power transformers; The data management layer (102) uses sensors to collect data on vibration and noise from the power transformer, and stores and processes the data to provide data support. The sensor layout layer (103) uses multibody dynamics technology to simulate and analyze the vibration of the power transformer, and designs the layout of the sensors on the power transformer based on the analysis results. The sensor layout layer (103) includes a multibody dynamics model (1031), a vibration simulation unit (1032), a vibration analysis unit (1033), and a sensor design unit (1034). The multibody dynamics model (1031) uses multibody dynamics software to establish a dynamic model of the power transformer; The vibration simulation unit (1032) simulates the vibration of the transformer based on the dynamic model, sets different operating conditions, and runs the simulation. The vibration analysis unit (1033) analyzes the vibration response of the transformer under various operating conditions based on the simulation results of the vibration simulation unit (1032), and identifies the natural frequency and vibration mode of the transformer. The vibration analysis results of the sensor design unit (1034) determine the installation position of the sensor; The three-dimensional model layer (104) uses MR technology to perform three-dimensional scanning of the power transformer and constructs a digital twin model of the power transformer based on the scanned data, and synchronizes the power transformer status in real time and makes predictions. The functional application layer (105) is based on the model established by the three-dimensional model layer (104) and uses VR equipment to carry out VR inspection work on the power transformer.

2. The online monitoring system for vibration and noise of a power transformer according to claim 1, characterized in that, The data management layer (102) includes a data acquisition module (1021), a data blockchain processing module (1022), and a data processing module (1023). The data acquisition module (1021) uses sensors to collect vibration and noise data of the power transformer in real time. The data acquisition module (1021) includes a sensor unit (10211) and a data transmission unit (10212). The sensor unit (10211) installs the sensor based on the sensor layout scheme designed by the sensor layout layer (103). The data transmission unit (10212) is used to transmit the sensor data to the data blockchain processing module (1022) and the data processing module (1023) for subsequent processing. The data blockchain processing module (1022) uses blockchain technology to store the collected power transformer data. The data blockchain processing module (1022) includes a data encryption unit (10221), a data upload unit (10222), and a data decryption unit (10223), which are used to encrypt, upload, and decrypt the data. The data processing module (1023) uses wavelet transform and logistic regression algorithms to process and analyze the collected data.

3. The online monitoring system for vibration and noise of a power transformer according to claim 2, characterized in that, The data processing module (1023) includes a data preprocessing unit (10231), a feature extraction unit (10232), and a data classification unit (10233). The data preprocessing unit (10231) performs routine preprocessing on the collected data; The feature extraction unit (10232) uses wavelet transform technology to extract features; The data classification unit (10233) classifies the state of the power transformer based on the extracted feature data using a logistic regression algorithm.

4. The online monitoring system for vibration and noise of a power transformer according to claim 3, characterized in that, The three-dimensional model layer (104) includes a three-dimensional scanning unit (1041), a twin model construction unit (1042), a data mapping unit (1043), and a real-time update unit (1044). The three-dimensional scanning unit (1041) receives sensor data by setting up an MR device and uses the 3D scanning function in MR technology to obtain the actual structural data of the power transformer, which is used to capture the position and movement of the power transformer, as well as the spatial information of the surrounding environment. The twin model construction unit (1042) constructs a twin model based on the associated data using digital twin technology, and uses physical laws and algorithms to simulate the behavior of the entity; The data mapping unit (1043) converts the data into three-dimensional point cloud data that can be used for digital model construction based on the data from the three-dimensional scanning unit (1041), and associates the data with the digital model. The real-time update unit (1044) is used to feed real-time data back to the digital twin model to maintain the real-time performance of the model.

5. The online monitoring system for vibration and noise of a power transformer according to claim 4, characterized in that, The functional application layer (105) includes a VR inspection module (1051) and a positioning module (1052). The VR inspection module (1051) uses VR wearable devices, such as VR headsets, to view and interact with a virtual power transformer environment; The positioning module (1052) is used to accurately capture the user's position and movement in the virtual environment; The detailed inspection steps of the VR inspection module (1051) are as follows: Step a: Use a VR software development kit to integrate the digital twin model and VR wearable devices, import the digital twin model into the VR environment, and have staff wear VR wearable devices to enter the virtual power transformer environment; Step b: Familiarize yourself with the structure and layout of the transformer in the VR environment, and understand the sensor locations and monitoring data in different areas; Step c: Use a positioning device to walk in the virtual environment, simulate the actual inspection path, view the real-time feedback of vibration and noise data, and use a VR controller to interact with the power transformer components in the virtual environment. Step d: In the VR environment, based on the diagnostic results output by the 3D model, locate the fault area and analyze the cause of the fault.

6. The online monitoring system for vibration and noise of a power transformer according to claim 5, characterized in that, The detailed processing steps for sensor distribution in the sensor layout layer (103) are as follows: Step 1: Define the components, connection methods, constraints, and external forces of the multibody dynamics model (1031), and establish the dynamic equations; Step 2: Define the magnitude, direction, and point of application of the excitation force, and use the multibody dynamics model (1031) to perform vibration simulation and calculate the natural frequency, modes, and response of the system; Step 3: Determine the required physical quantities, range, and accuracy; select the appropriate sensor type; design the sensor installation method and electrical interface; and integrate them into the model. Step four: Collect vibration data using sensors for vibration analysis, and optimize the sensor design based on the analysis results.

7. A method for an online monitoring system for vibration and noise of a power transformer, applied to the online monitoring system for vibration and noise of a power transformer as described in any one of claims 1 to 6, characterized in that, Includes the following steps: S1. Use MR equipment to scan the actual structure of the transformer, generate a 3D model, import the 3D model into the digital twin platform, and establish a twin model of the transformer. S2, based on the actual structural data of the transformer, multibody dynamics is used to simulate and analyze the vibration of the transformer, and the position of the sensor for monitoring the transformer is optimized according to the vibration of the transformer. S3, based on the designed installation location, install the corresponding sensors to collect vibration and noise data of the power transformer; S4, the collected data is stored using blockchain technology, and the data processing module (1023) is used to extract and classify the data to output the fault diagnosis results; S5, at the same time, uses VR technology to simultaneously construct a virtual environment for free inspection of the transformer model, thus completing the virtual and real monitoring of the power transformer.

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