Generator set operation maintenance data analysis system and method based on three-dimensional modeling

Abstract

The invention discloses a generator set operation maintenance data analysis system and method based on three-dimensional modeling, and belongs to the technical field of data processing.The generator set operation maintenance data analysis system comprises the steps that generator set data are obtained, the structure, the working principle and operation parameters of a generator set are obtained, and a generator set three-dimensional model is constructed; fusing the three-dimensional model of the water electric field, the three-dimensional model of the generator set and an electromagnetic field simulation environment into an integral digital twinborn model, constructing a stator electromagnetic characteristic extraction and loss evaluation model, carrying out feature extraction on the obtained electromagnetic parameters, carrying out generator set electromagnetic loss evaluation, constructing a generator set electromagnetic diagnosis and early warning model, and carrying out generator set electromagnetic diagnosis and early warning. According to the method, through the functions of fault feature extraction, electromagnetic calculation, loss evaluation and intelligent early warning, comprehensive quantification and fault diagnosis of electromagnetism in the stator of the generator set are achieved, and the fault diagnosis accuracy is improved. And the operation safety and the maintenance efficiency of equipment are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and specifically relates to a data analysis system and method for the operation and maintenance of a generator set based on three-dimensional modeling. Background Art

[0002] With the continuous development of the power system and the increasing requirements for the reliability of power supply, the operation and maintenance of generator sets have become crucial. As one of the core equipment of the power system, the operation status of generator sets directly affects the stable power supply and the safe operation of the system. Effective operation and maintenance can timely detect potential faults, prevent equipment accidents, extend the service life of equipment, reduce maintenance costs, improve power generation efficiency and power quality, and ensure the reliability and economy of the power system. Existing monitoring means mainly collect data such as temperature, vibration, current, and voltage in real time through single or a few sensors, but these data often lack comprehensiveness and are difficult to fully reflect the operation status of equipment. There is an island effect among the data of different monitoring systems, and it is impossible to form a systematic and continuous basis for fault judgment. When the generator set is running, due to the action of electromagnetic force, components such as the stator will generate electromagnetic vibration. Electromagnetic vibration will not only affect the operation stability of the generator set, but may also cause mechanical damage and insulation aging of the equipment. Electromagnetic loss will lead to a reduction in the efficiency of the generator set and serious energy waste. At the same time, electromagnetic loss will also cause the equipment to heat up, affecting the insulation performance and service life of the equipment. The existing technology lacks the detection of stator electromagnetic vibration faults and the evaluation of energy consumption.

[0003] The present invention aims to build a fault diagnosis system for generator sets based on three-dimensional modeling and multi-field coupling simulation, integrate functions such as data acquisition, real-time monitoring, fault feature extraction, electromagnetic force calculation, loss evaluation, and intelligent early warning, and realize the comprehensive quantification and online fault diagnosis of the internal electromagnetism of the stator of the generator set, so as to improve the operation safety and maintenance efficiency of the equipment. Summary of the Invention

[0004] Aiming at the deficiencies of the existing technology, the present invention proposes a data analysis system and method for the operation and maintenance of a generator set based on three-dimensional modeling.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] Obtain the data of the generator set, including the structure, working principle, and operation parameters of the generator set;

[0007] Build a three-dimensional model of the generator set, and integrate the three-dimensional model of the water-electric field, the three-dimensional model of the generator set, and the electromagnetic field simulation environment into an overall digital twin model;

[0008] Build a stator electromagnetic characteristic extraction and loss evaluation model, extract the characteristics of the obtained electromagnetic parameters, and evaluate the electromagnetic loss of the generator set;

[0009] Build an electromagnetic diagnosis and early warning model for the generator set. By establishing a normal working benchmark and a fault database, compare the model prediction with the actual situation, and trigger an early warning when an anomaly is detected.

[0010] A method for analyzing the operation and maintenance data of a generator set based on 3D modeling, which includes the following specific steps:

[0011] Preferably, for the step of obtaining the data of the generator set, obtaining the structure, working principle and operation parameters of the generator set includes the following specific steps:

[0012] S11. Obtain the equipment structure data of the generator set. Real-time collect the operation data and environmental data of the generator set through sensors and monitoring instruments, and store the obtained data in the generator set operation database;

[0013] S12. Obtain the historical fault data and establish a generator set fault database;

[0014] S13. Through electromagnetic sensors, obtain the vibration conditions and electromagnetic-related parameters caused by electromagnetic factors.

[0015] Preferably, for the step of building a 3D model of the generator set, integrating the 3D model of the hydropower field, the 3D model of the generator set and the electromagnetic field simulation environment into an overall digital twin model includes the following specific steps:

[0016] S21. Take the actually measured natural data as boundary conditions and input them into the computational fluid dynamics software (CFD software) to perform 3D modeling on the hydropower field, and obtain the hydraulic information inside and around the hydropower field;

[0017] S22. Import the structure data, working principle and operation parameters of the generator set into the modeling software (such as BIM, CAD, etc.) to perform 3D modeling on the generator set, and map the real-time collected data to the 3D model;

[0018] S23. Build an electromagnetic field simulation environment in the 3D model of the generator set. Set the corresponding boundary conditions and physical parameters according to the electromagnetic field theory and the vibration field theory, simulate and analyze the electromagnetic field distribution inside the generator set, and associate the electromagnetic parameters with each component of the 3D model;

[0019] S24. Integrate the 3D model of the hydropower field, the 3D model of the generator set and the electromagnetic field simulation environment to build an overall digital twin model of the generator set.

[0020] Preferably, for the step of building a stator electromagnetic characteristic extraction and loss assessment model, extracting the characteristics of the obtained electromagnetic parameters and performing electromagnetic loss assessment of the generator set includes the following specific steps:

[0021] S31. Preprocess the collected electromagnetic data, and extract the electromagnetic vibration characteristic parameters through wavelet transform. The wavelet transform denoising function is as follows: where x(t) is the time-domain signal, W(a, b) is the wavelet transform denoising function, a is the scale parameter, b is the translation parameter, ψ(t) is the mother wavelet function, and the characteristic frequency, amplitude, and phase of the stator electromagnetic vibration are extracted through wavelet transform;

[0022] S32. Calculate the local electromagnetic forces on the stator surface and inside according to the electromagnetic simulation results. The electromagnetic force calculation formula is: F = ∫ S J × BdS, where S is the stator surface area, J is the local current density, B is the magnetic induction intensity. Apply the calculated electromagnetic force distribution as an external load to the stator three-dimensional model and perform subsequent static structural analysis in the simulation software;

[0023] S33. Evaluate the energy efficiency of the generator set through the calculation of electromagnetic losses. The total electromagnetic loss calculation formula is: P = P e + P h + P c , where P e is the eddy current loss, and the eddy current loss calculation formula is: P h is the hysteresis loss, and the hysteresis loss calculation formula is: P h = ηB n f, P c is the resistance loss, and the resistance loss calculation formula is: P c = I 2 R, where B is the magnetic flux density, d is the core thickness, f is the alternating magnetic field frequency, ρ is the resistivity of the core material, η is the hysteresis coefficient, n is the hysteresis index, I is the current, and R is the winding resistance.

[0024] Preferably, for constructing the electromagnetic diagnosis and early warning model of the generator set, by establishing a normal working benchmark and a fault database, comparing the model prediction situation with the actual situation, and triggering an early warning when an anomaly is detected, it includes the following specific steps:

[0025] S41. Obtain the normal operation parameters of the generator set, determine the natural frequency and vibration mode of the stator, and establish a normal working state benchmark;

[0026] S42. Establish a database for the electromagnetic vibration fault modes of the generator set, import the historical fault types of the generator into the database for the electromagnetic vibration fault modes of the generator set, compare the extracted characteristic values with the fault types in the database through machine learning to obtain the coupling simulation results in the 3D model, locate the fault position through the 3D model, compare the electromagnetic force distribution and electromagnetic loss simulation data obtained from the 3D model with the actual situation data, and calibrate the model parameters through historical fault cases. Measure the average deviation between the model prediction value and the actual measurement value by the root mean square error. Compare the electromagnetic loss data of the current generator set with the normal average data of the same type of generator set to evaluate the electromagnetic performance of the current generator set at the level of the same generator set. The formula for the root mean square error is as follows: where m is the number of prediction values, P i is the model prediction value, and M i is the actual measurement value;

[0027] S43. Set the thresholds for electromagnetic force distribution and electromagnetic loss. When the evaluated electromagnetic force distribution and electromagnetic loss values exceed the set thresholds, immediately trigger an alarm, mark the abnormal area on the digital twin platform, automatically generate maintenance suggestions based on the fault diagnosis results and the calculation of the root mean square error, and achieve collaborative optimization in combination with the cross-site data sharing platform.

[0028] The operation and maintenance data analysis system for the generator set based on 3D modeling is implemented based on the above-mentioned operation and maintenance data analysis method for the generator set based on 3D modeling, and specifically includes:

[0029] The data acquisition module is used to obtain the structure, working principle, and operation parameters of the generator set;

[0030] The 3D model construction module is used to integrate the 3D model of the hydropower field, the 3D model of the generator set, and the electromagnetic field simulation environment into an overall digital twin model;

[0031] The stator electromagnetic characteristic extraction and loss evaluation module is used to extract the characteristics of the obtained electromagnetic parameters and evaluate the electromagnetic loss of the generator set;

[0032] The electromagnetic diagnosis and warning module is used to establish a normal working benchmark and a fault database, compare the model prediction situation with the actual situation, and trigger an alarm when an abnormality is detected.

[0033] An electronic device includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory;

[0034] The processor executes the above-mentioned operation and maintenance data analysis method for the generator set based on 3D modeling by calling the computer program stored in the memory.

[0035] A computer-readable storage medium, characterized in that it stores instructions, which, when run on a computer, cause the computer to execute the above-mentioned method for analyzing the operation and maintenance data of a generator set based on 3D modeling.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0037] The present invention obtains the data of the generator set, obtains the structure, working principle and operation parameters of the generator set, constructs a 3D model of the generator set, integrates the 3D model of the hydropower station, the 3D model of the generator set and the electromagnetic field simulation environment into an overall digital twin model, constructs a stator electromagnetic characteristic extraction and loss evaluation model, extracts the characteristics of the obtained electromagnetic parameters, evaluates the electromagnetic loss of the generator set, constructs an electromagnetic diagnosis and early warning model for the generator set, establishes a normal working benchmark and a fault database, compares the model prediction situation with the actual situation and triggers an early warning when an anomaly is detected. Through the functions of fault feature extraction, electromagnetic calculation, loss evaluation and intelligent early warning, the present invention realizes the comprehensive quantification and fault diagnosis of the internal electromagnetism of the stator of the generator set, and improves the operation safety and maintenance efficiency of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the overall process of the method for analyzing the operation and maintenance data of a generator set based on 3D modeling according to the present invention;

[0039] Figure 2 It is a schematic diagram of 3D modeling of the method for analyzing the operation and maintenance data of a generator set based on 3D modeling according to the present invention;

[0040] Figure 3 It is a schematic diagram of the overall framework of the system for analyzing the operation and maintenance data of a generator set based on 3D modeling according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0042] Embodiment 1

[0043] Please refer to Figure 1-2 , an embodiment provided by the present invention: a method for analyzing the operation and maintenance data of a generator set based on 3D modeling, which includes the following specific steps:

[0044] Obtain the data of the generator set, and obtain the structure, working principle and operation parameters of the generator set;

[0045] Construct a 3D model of the generator set, and integrate the 3D model of the hydropower station, the 3D model of the generator set and the electromagnetic field simulation environment into an overall digital twin model;

[0046] Build a stator electromagnetic characteristic extraction and loss evaluation model, extract the characteristics of the obtained electromagnetic parameters, and evaluate the electromagnetic loss of the generator set;

[0047] Build an electromagnetic diagnosis and early warning model for the generator set. By establishing a normal working benchmark and a fault database, compare the model prediction with the actual situation, and trigger an early warning when an anomaly is detected.

[0048] It should be specifically noted in this embodiment that obtaining the data of the generator set, including the structure, working principle, and operating parameters of the generator set, includes the following specific steps:

[0049] S11. Obtain the generator set equipment structure data. Real-time collect the operating data and environmental data of the generator set through sensors and monitoring instruments, and store the obtained data in the generator set operation database. Among them, the generator set equipment structure data includes the generator set structure, working principle, and operating parameters, the operating data includes vibration, current, voltage, etc., and the environmental data includes humidity, air pressure, temperature, etc.;

[0050] S12. Obtain the historical fault data and establish a generator set fault database;

[0051] S13. Through electromagnetic sensors, obtain the vibration conditions and electromagnetic-related parameters caused by electromagnetic factors.

[0052] It should be specifically noted in this embodiment that building a three-dimensional model of the generator set and integrating the three-dimensional model of the hydropower field, the three-dimensional model of the generator set, and the electromagnetic field simulation environment into an overall digital twin model includes the following specific steps:

[0053] S21. Input the actually measured natural data as boundary conditions into the computational fluid dynamics software (CFD software) to perform three-dimensional modeling of the hydropower field and obtain the hydraulic information inside and around the hydropower field;

[0054] S22. Import the structure data, working principle, and operating parameters of the generator set into the modeling software (such as BIM, CAD, etc.) to perform three-dimensional modeling of the generator set, and map the real-time collected data to the three-dimensional model;

[0055] S23. Build an electromagnetic field simulation environment in the three-dimensional model of the generator set, and set the corresponding boundary conditions and physical parameters according to the electromagnetic field theory and the vibration field theory. Among them, the calculation formula for the relationship between the magnetic field and the magnetic induction intensity is: B = μH, and the calculation formula for the magnetic flux is: φ = ∫ S B·dS, where μ is the magnetic permeability of the medium, H is the magnetic field strength, B is the magnetic induction intensity, dS is the differential area vector, simulate and analyze the electromagnetic field distribution inside the generator set, and associate the electromagnetic parameters with each component of the three-dimensional model;

[0056] S24. Integrate the three-dimensional model of the hydropower field, the three-dimensional model of the generator set and the electromagnetic field simulation environment to construct an overall digital twin model of the generator set.

[0057] In this embodiment, it should be specifically explained that constructing a stator electromagnetic characteristic extraction and loss assessment model, extracting features from the acquired electromagnetic parameters, and performing electromagnetic loss assessment on the generator set includes the following specific steps:

[0058] S31, preprocessing the collected electromagnetic data, extracting electromagnetic vibration characteristic parameters through wavelet transform, wherein the wavelet transform denoising function is: Among them, x(t) is the time domain signal, W(a,b) is the wavelet transform denoising function, a is the scale parameter, b is the translation parameter, ψ(t) is the mother wavelet function, and the characteristic frequency, amplitude and phase of the stator electromagnetic vibration are extracted by wavelet transform. Wavelet transform has denoising ability. By calculating the wavelet transform coefficients and selecting the appropriate threshold for denoising, the noise component can be suppressed and the useful information in the signal can be enhanced.

[0059] S32. Calculate the local electromagnetic force on the surface and inside of the stator according to the electromagnetic simulation results, where the electromagnetic force calculation formula is: F = ∫ S J×BdS, where S is the stator surface area, J is the local current density, and B is the magnetic induction intensity. The calculated electromagnetic force distribution is applied to the stator three-dimensional model as an external load, and subsequent static structural analysis is performed in the simulation software. This formula is derived from the Lorentz force law, which quantifies the magnitude and direction of the electromagnetic force. During the calculation process, the total electromagnetic force borne by each area is obtained by integration, and the direction of force is determined according to the current direction and magnetic field distribution. Through calculation, the area with higher electromagnetic load can be identified, which becomes the location of structural stress concentration. The electromagnetic force distribution is compared with the actual measurement data, and the three-dimensional model parameters are corrected, thereby providing reliable data support for the real-time early warning system. Once the electromagnetic force in a certain area is found to exceed the normal range, the system can trigger an early warning;

[0060] S33. Evaluate the energy efficiency of the generator set by calculating the electromagnetic loss, wherein the total electromagnetic loss calculation formula is: P = P e +P h +P c , where P e is the eddy current loss, and the eddy current loss calculation formula is: P h is the hysteresis loss, and the calculation formula for hysteresis loss is: P h =ηB n f,P c is the resistance loss, and the resistance loss calculation formula is: P c =I2 R, where B is the magnetic flux density, d is the core thickness, f is the alternating magnetic field frequency, ρ is the resistivity of the core material, η is the hysteresis coefficient, n is the hysteresis exponent, I is the current, and R is the winding resistance.

[0061] In this embodiment, it should be specifically noted that to construct an electromagnetic diagnosis and early warning model for a generator set, by establishing a normal operation benchmark and a fault database, comparing the model prediction situation with the actual situation, and triggering an early warning when an anomaly is detected, the following specific steps are included:

[0062] S41. Obtain the normal operation parameters of the generator set, determine the natural frequency and vibration mode of the stator, and establish a normal operation state benchmark;

[0063] S42. Establish an electromagnetic vibration fault mode database for the generator set, import the historical fault types of the generator into the electromagnetic vibration fault mode database of the generator set, compare the extracted eigenvalue with the fault types in the database through machine learning (such as convolutional neural network, random forest), obtain the coupled simulation results in the three-dimensional model, locate the fault position through the three-dimensional model, compare the electromagnetic force distribution and electromagnetic loss simulation data obtained from the three-dimensional model with the actual situation data, and correct the model parameters through historical fault cases. Measure the average deviation between the model prediction value and the actual measurement value by the root mean square error, compare the electromagnetic loss data of the current generator set with the normal average data of the same type of generator set, and evaluate the electromagnetic performance of the current generator set at the level of the same generator set. Among them, the root mean square error calculation formula is: where m is the number of prediction values, P i is the model prediction value, M i is the actual measurement value;

[0064] S421. Compare the current electromagnetic loss data with the historical data, analyze the change trend of the electromagnetic loss, and judge whether there are signs of aging, wear or faults in the generator set. If the electromagnetic loss of the current generator set is significantly higher than that of the same type of unit, analyze the electromagnetic loss situation of the generator set under different working conditions (such as different loads, different speeds, different cooling conditions, etc.), and find the fault type through the fault database;

[0065] S422. Use the offline historical data for cross-validation, evaluate the stability of the model on different data sets, conduct parameter sensitivity analysis, test the preset faults in the actual operating environment, and record the timing and amplitude errors between the model prediction and the actual faults.

[0066] S43. Set the electromagnetic force distribution and electromagnetic loss threshold. When the evaluated electromagnetic force distribution and electromagnetic loss value exceed the set threshold, an early warning is immediately triggered, and the abnormal area is marked on the digital twin platform. According to the fault diagnosis result and the calculation of the root mean square error, maintenance suggestions (such as local insulation detection, winding replacement, or structural optimization) are automatically generated, and collaborative optimization is achieved by combining with the cross-site data sharing platform.

[0067] In this embodiment, it should be specifically noted that the method for obtaining the values of the electromagnetic force distribution and electromagnetic loss threshold is as follows: Obtain the electromagnetic force distribution and electromagnetic loss data of representative generator sets, and evaluate whether they meet the fault assessment requirements through a three-dimensional model, machine learning, and expert manual evaluation. At the same time, substitute the historical data of the generator set related to electromagnetic factors obtained into the calculation results and judgment results of each step in this embodiment into the fitting software, and output the threshold that meets the highest judgment accuracy rate.

[0068] The advantages of this embodiment compared with the prior art are:

[0069] The present invention obtains the data of the generator set, obtains the structure, working principle, and operating parameters of the generator set, constructs a three-dimensional model of the generator set, integrates the three-dimensional model of the hydropower field, the three-dimensional model of the generator set, and the electromagnetic field simulation environment into an overall digital twin model, constructs a stator electromagnetic characteristic extraction and loss assessment model, extracts the characteristics of the obtained electromagnetic parameters, conducts electromagnetic loss assessment of the generator set, constructs an electromagnetic diagnosis and early warning model of the generator set, establishes a normal working benchmark and a fault database, compares the model prediction situation with the actual situation, and triggers an early warning when an abnormality is detected. Through the functions of fault feature extraction, electromagnetic calculation, loss assessment, and intelligent early warning, the present invention realizes the comprehensive quantification and fault diagnosis of the internal electromagnetism of the stator of the generator set, and improves the operation safety and maintenance efficiency of the equipment.

[0070] Embodiment 2

[0071] As Figure 3 shown, the operation and maintenance data analysis system of the generator set based on three-dimensional modeling is implemented based on the above-mentioned operation and maintenance data analysis method of the generator set based on three-dimensional modeling, and specifically includes a data acquisition module, a three-dimensional model construction module, a stator electromagnetic characteristic extraction and loss assessment module, and an electromagnetic diagnosis and early warning module. The data acquisition module is used to obtain the structure, working principle, and operating parameters of the generator set; the three-dimensional model construction module is used to integrate the three-dimensional model of the hydropower field, the three-dimensional model of the generator set, and the electromagnetic field simulation environment into an overall digital twin model; the stator electromagnetic characteristic extraction and loss assessment module is used to extract the characteristics of the obtained electromagnetic parameters and conduct electromagnetic loss assessment of the generator set; the electromagnetic diagnosis and early warning module is used to establish a normal working benchmark and a fault database, compare the model prediction situation with the actual situation, and trigger an early warning when an abnormality is detected.

[0072] Example 3

[0073] This embodiment provides an electronic device, including: a processor and a memory, wherein, a computer program that can be called by the processor is stored in the memory;

[0074] The processor executes the above-mentioned method for analyzing the operation and maintenance data of a generator set based on 3D modeling by calling the computer program stored in the memory.

[0075] This electronic device may have relatively large differences due to different configurations or performances, and can include one or more processors (Central Processing Units, CPU) and one or more memories. Among them, at least one computer program is stored in the memory, and this computer program is loaded and executed by the processor to implement the method for analyzing the operation and maintenance data of a generator set based on 3D modeling provided by the above method embodiment. This electronic device can also include other components for implementing the functions of the device. For example, this electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for inputting and outputting data. This embodiment will not be elaborated here.

[0076] Example 4

[0077] This embodiment proposes a computer-readable storage medium, on which a rewritable computer program is stored;

[0078] When the computer program runs on a computer device, it enables the computer device to execute the above-mentioned method for analyzing the operation and maintenance data of a generator set based on 3D modeling.

[0079] For example, the computer-readable storage medium can be a read-only memory (Read-Only Memory, abbreviated as: ROM), a random access memory (Random Access Memory, abbreviated as: RAM), a compact disc read-only memory (Compact Disc Read-Only Memory, abbreviated as: CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.

[0080] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more collections of available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

Claims

1. A method for analyzing the operation and maintenance data of a generator set based on three-dimensional modeling, characterized in that It includes the following specific steps: Obtain the data of the generator set, and obtain the structure, working principle and operation parameters of the generator set; Construct a three-dimensional model of the generator set, and integrate the three-dimensional model of the hydropower plant, the three-dimensional model of the generator set and the electromagnetic field simulation environment into an overall digital twin model; Construct a stator electromagnetic characteristic extraction and loss assessment model, extract the characteristics of the obtained electromagnetic parameters, and conduct an electromagnetic loss assessment of the generator set; Construct an electromagnetic diagnosis and early warning model for the generator set. By establishing a normal working benchmark and a fault database, compare the model prediction situation with the actual situation, and trigger an early warning when an anomaly is detected.

2. The method for analyzing the operation and maintenance data of a generator set based on 3D modeling according to claim 1, wherein The step of constructing a three-dimensional model of the generator set and integrating the three-dimensional model of the hydropower plant, the three-dimensional model of the generator set and the electromagnetic field simulation environment into an overall digital twin model includes the following specific steps: S11. Input the actually measured natural data as boundary conditions into the fluid dynamics software to conduct three-dimensional modeling of the hydropower plant, and obtain the hydraulic information inside and around the hydropower plant; S12. Import the structural data, working principle and operation parameters of the generator set into the modeling software to conduct three-dimensional modeling of the generator set, and map the real-time collected data to the three-dimensional model; S13. Construct an electromagnetic field simulation environment in the three-dimensional model of the generator set. According to the electromagnetic field theory and the vibration field theory, set the corresponding boundary conditions and physical parameters, simulate and analyze the electromagnetic field distribution inside the generator set, and associate the electromagnetic parameters with each component of the three-dimensional model; S14. Integrate the three-dimensional model of the hydropower plant, the three-dimensional model of the generator set and the electromagnetic field simulation environment to construct an overall digital twin model of the generator set.

3. The method for analyzing the operation and maintenance data of a generator set based on 3D modeling according to claim 2, wherein The step of constructing a stator electromagnetic characteristic extraction and loss assessment model, extracting the characteristics of the obtained electromagnetic parameters, and conducting an electromagnetic loss assessment of the generator set includes the following specific steps: S21. Preprocess the collected electromagnetic data, extract the electromagnetic vibration characteristic parameters through wavelet transform, and extract the characteristic frequency, amplitude and phase of the stator electromagnetic vibration through wavelet transform; S22. According to the electromagnetic simulation results, calculate the local electromagnetic force on the stator surface and inside. Calculate the electromagnetic force through the Lorentz force calculation formula transformation, quantify the magnitude and direction of the electromagnetic force, apply the calculated electromagnetic force distribution as an external load to the stator three-dimensional model, and conduct subsequent static structure analysis in the simulation software; S23. Evaluate the energy efficiency of the generator set by calculating the electromagnetic losses. Among them, the total electromagnetic loss calculation formula is: P = P e + P h + P c , where P e is the eddy current loss, and the eddy current loss calculation formula is: P h is the hysteresis loss, and the hysteresis loss calculation formula is: P h = ηB n f, P c is the resistance loss, and the resistance loss calculation formula is: P c = I 2 R, where B is the magnetic flux density, d is the core thickness, f is the alternating magnetic field frequency, ρ is the resistivity of the core material, η is the hysteresis coefficient, n is the hysteresis index, I is the current, and R is the winding resistance.

4. The method for analyzing the operation and maintenance data of a generator set based on 3D modeling according to claim 3, wherein The step of constructing an electromagnetic diagnosis and early warning model for the generator set. By establishing a normal working benchmark and a fault database, compare the model prediction situation with the actual situation, and trigger an early warning when an anomaly is detected includes the following specific steps: S31. Obtain the normal operation parameters of the generator set, determine the natural frequency and vibration mode of the stator, and establish a normal working state benchmark; S32. Establish an electromagnetic vibration fault mode database for the generator set, import the historical fault types of the generator into the electromagnetic vibration fault mode database of the generator set, compare the extracted eigenvalue with the fault types in the database through machine learning to obtain the coupling simulation results in the three-dimensional model, locate the fault position through the three-dimensional model, compare the electromagnetic force distribution and electromagnetic loss simulation data obtained from the three-dimensional model with the actual situation data, and calibrate the model parameters through historical fault cases. Measure the average deviation between the model prediction value and the actual measurement value by the root mean square error, and compare the electromagnetic loss data of the current generator set with the normal average data of the same type of generator set to evaluate the electromagnetic performance of the current generator set at the level of the same generator set; S33. Set the thresholds for electromagnetic force distribution and electromagnetic loss. When the evaluated electromagnetic force distribution and electromagnetic loss values exceed the set thresholds, immediately trigger an alarm, mark the abnormal area on the digital twin platform, automatically generate maintenance suggestions according to the fault diagnosis results and the calculation of the root mean square error, and achieve collaborative optimization in combination with the cross-site data sharing platform.

5. The method for analyzing the operation and maintenance data of a generator set based on 3D modeling according to claim 4, wherein The acquisition of the generator set data, and the acquisition of the structure, working principle and operation parameters of the generator set include the following specific steps: S41. Acquire the equipment structure data of the generator set, and collect the operation data and environmental data of the generator set in real time through sensors and monitoring instruments, and store the acquired data in the operation database of the generator set; S42. Acquire the historical fault data and establish a fault database for the generator set; S43. Through electromagnetic sensors, acquire the vibration conditions and electromagnetic-related parameters caused by electromagnetic factors.

6. A data analysis system for the operation and maintenance of a generator set based on 3D modeling, which is implemented based on the 3D modeling-based data analysis method for the operation and maintenance of a generator set according to any one of claims 1-5, characterized in that, Specifically, it includes: A data acquisition module for acquiring the structure, working principle and operation parameters of the generator set; A three-dimensional model construction module for integrating the three-dimensional model of the hydropower field, the three-dimensional model of the generator set and the electromagnetic field simulation environment into an overall digital twin model; A stator electromagnetic characteristic extraction and loss evaluation module for extracting the characteristics of the acquired electromagnetic parameters and evaluating the electromagnetic loss of the generator set; An electromagnetic diagnosis and warning module for establishing a normal working benchmark and a fault database, comparing the model prediction situation with the actual situation, and triggering an alarm when an abnormality is detected.

7. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the method for analyzing the operation and maintenance data of the generator set based on three-dimensional modeling according to any one of claims 1-5 by calling the computer program stored in the memory.

8. A computer-readable storage medium, characterized in that, Instructions are stored, and when the instructions run on a computer, the computer executes a method for analyzing the operation and maintenance data of the generator set based on three-dimensional modeling according to any one of claims 1-5.

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