Power plant boiler heating surface advanced diagnosis and early warning method based on three-dimensional model

Abstract

The invention discloses a power plant boiler heating surface advanced diagnosis and early warning method based on a three-dimensional model, and belongs to the technical field of power plant boiler heating surface monitoring. According to the method, the problems that an existing method is large in individual subjectivity and hard to ensure early warning accuracy are solved, and the three-dimensional boiler model and the intelligent prediction model are constructed by obtaining point cloud data and operation basic data of the heating surface of the power plant boiler; basic data are integrated into the boiler model for data docking, and real-time monitoring of the operation state of the boiler heating surface is achieved; performing abnormal early warning on the pipeline to which the boiler heating surface belongs according to the intelligent prediction model, and accurately predicting whether the heating surface pipeline has a fault or not; based on the method, the boiler operation data can be effectively integrated into the three-dimensional model, so that the operation efficiency, the safety and the maintenance efficiency of the boiler are improved; meanwhile, through intelligent diagnosis and prediction, measures can be taken in advance, production interruption caused by faults is reduced, and the production efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of monitoring heating surfaces of power plant boilers, and in particular to an advanced diagnosis and early warning method for heating surfaces of power plant boilers based on a three-dimensional model. Background Art

[0002] The heating surface of a power plant boiler usually refers to the metal surface area on one side that contacts the flame or flue gas, and the other side is used to contact water or heat transfer oil. The heat exchange of the boiler is carried out through such a metal surface area; the heating surface of a power plant boiler is the interface that absorbs heat from the exothermic medium and transfers it to the heating medium. These interfaces include convection heating surfaces and radiation heating surfaces; its main function is to complete the conversion of thermal energy by absorbing heat and transferring it to the working medium. In order to ensure the stability of thermal energy conversion, it is necessary to conduct advanced diagnosis and early warning of the boiler heating surface, so as to improve the safety and reliability of boiler operation, timely discover potential faults and hidden dangers, and avoid accidents.

[0003] In the prior art, most of the advanced diagnosis and early warning methods for the heating surface of power plant boilers are based on early warning models based on worker experience. Although the knowledge and experience of experts can be used for fault early warning, this method is highly dependent on personal experience and judgment, and is subject to great personal subjectivity, making it difficult to ensure the accuracy of the early warning method.

[0004] Therefore, the existing needs are not met. For this reason, we propose an advanced diagnosis and early warning method for the heating surface of power plant boilers based on a three-dimensional model. Summary of the invention

[0005] The purpose of the present invention is to provide an advanced diagnosis and early warning method for the heating surface of a power plant boiler based on a three-dimensional model. By acquiring the point cloud data and basic operating data of the heating surface of the power plant boiler, and constructing a three-dimensional boiler model and an intelligent prediction model, and integrating the basic data into the boiler model for data docking, real-time monitoring of the operating status of the boiler heating surface can be achieved; abnormal early warning of the boiler heating surface pipeline is carried out according to the intelligent prediction model, and it is accurately predicted whether there is a fault in the heating surface pipeline; based on this, this method can not only effectively integrate the boiler operation data into the three-dimensional model, improve the operating efficiency, safety and maintenance efficiency of the boiler, and provide technical support for the development of smart boilers; at the same time, through intelligent diagnosis and prediction, measures can be taken in advance to reduce production interruptions caused by faults, improve production efficiency, and solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The advanced diagnosis and early warning method of the heating surface of a power plant boiler based on a three-dimensional model includes the following steps:

[0008] Step 1: Obtain detailed data of the heating surface of the power plant boiler through laser scanning and point cloud data technology as data samples for 3D modeling; the detailed data includes: the types, functions, layout characteristics and technical parameters of various heating surfaces;

[0009] Step 2: Use Creo 3D modeling software to perform 3D modeling on the boiler heating surface, including: separately modeling each major component and part in the boiler heating surface, and then assembling them into a complete boiler model;

[0010] Step 3: Collect basic data of boiler operation and integrate the basic data into the boiler model for data docking; the basic data includes: temperature, pressure, water level, flow rate and flue gas composition;

[0011] Step 4: Use the boiler model combined with visualization technology to monitor the boiler heating surface in real time to obtain the operating status of the boiler heating surface; the monitoring objects include: monitoring the temperature, pressure and water level parameters of the boiler heating surface, and distinguishing different areas and pipe materials by color;

[0012] Step 5: Build an intelligent prediction model based on the basic data of boiler operation, and use the intelligent prediction model to issue abnormal warnings to the boiler heating surface pipelines to predict whether there are any faults in the heating surface pipelines.

[0013] Furthermore, in step 5, an intelligent prediction model is constructed based on the basic data of boiler operation, which specifically includes the following steps:

[0014] Through various sensors installed on the power plant boiler body, multi-dimensional operating data of power plant boiler temperature, pressure, flow and flue gas composition are collected;

[0015] The collected basic data are validated and preprocessed by data transformation, and the preprocessed basic data are cleaned, including: removing abnormal data, data standardization and normalization; the processed basic data are then divided into training sets and test sets as data samples for the intelligent prediction model;

[0016] Use neural network algorithm to establish intelligent prediction model, import training set and test set into the intelligent prediction model in turn for training and testing, and output test results; then compare the test results with the actual boiler operation results to ensure the accuracy of the intelligent prediction model;

[0017] The real-time monitoring data is imported into the intelligent prediction model after the test to predict faults, and the prediction results are output to achieve real-time monitoring of the boiler heating surface pipelines; and the combustion control strategy is automatically adjusted according to the prediction results to achieve the optimal fuel ratio and maximize the combustion efficiency.

[0018] Furthermore, in the step 1, the detailed data of the heating surface of the power plant boiler is obtained by laser scanning and point cloud data technology, which specifically includes the following steps:

[0019] A 3D laser scanner is used to scan the heating surface of the power plant boiler to obtain point cloud data and 3D coordinate data of its surface and generate point cloud data. The obtained point cloud data is then preprocessed, including: denoising, registration and stitching operations, to obtain detailed data of the heating surface of the power plant boiler.

[0020] Furthermore, in the step 2, the three-dimensional modeling of the boiler heating surface is performed using Creo three-dimensional modeling software, which specifically includes the following steps:

[0021] Open the Creo software to create a new part file, set the corresponding units and dimensions, select the sketch plane to draw the basic shape and outline of the boiler heating surface; use the stretch and rotate commands according to the sketch to create the basic features of the heating surface, and add detail features on the basic features; use Creo's assembly function to assemble the various parts according to the actual position; use Creo's pipe routing function to create a piping system on the boiler heating surface, and set the start, end and path of the pipe; use Creo to create an attribute table to add attribute information to each component of the boiler heating surface; use Creo's detection function to optimize the boiler model, check for omissions or errors, and check the model's geometric clarity and assembly rationality.

[0022] Furthermore, in step three, after the basic data is integrated into the boiler model for data docking, the boiler model needs to be verified using the coal-fired power plant virtual simulation system to ensure the accuracy of the boiler model, which specifically includes the following steps:

[0023] Familiarize yourself with the boiler heating surface model: log in to the 3D virtual reality simulation system of the coal-fired power plant to obtain the layout and structure of the boiler heating surface;

[0024] Divide the boiler heating surface system into subsystems and thermal equipment: According to the characteristics of the boiler heating surface system and the basic modules of the virtual simulation software, divide the thermal system of the whole plant into subsystems and thermal equipment;

[0025] Establish a boiler heating surface simulation model: Select appropriate modules from the graphic module library of the virtual simulation software to form thermal equipment, set various attribute parameters, and establish a boiler heating surface model;

[0026] Carry out coupling and steady-state verification: Carry out steady-state verification on the main equipment, and make its temperature, pressure and enthalpy values ​​consistent with the real equipment by adjusting the heat exchange area and streamline admittance; Couple the boiler equipment that meets the steady-state verification requirements according to the thermodynamic process, and realize its steady-state verification by changing the streamline admittance and heat exchange area at the coupling point;

[0027] Input control parameters and thermal parameters for dynamic simulation: Input the set control parameters and thermal parameters, and output the dynamic changes of each parameter over time on the real-time simulation platform;

[0028] Data processing and performance evaluation: Process the data collected during the simulation, evaluate the performance and energy consumption characteristics of the boiler heating surface, and verify the accuracy and reliability of the model by comparing the simulation results with the actual operating data.

[0029] Furthermore, in step 4, different areas and pipe materials are distinguished by color, which specifically includes the following steps:

[0030] The boiler heating surface is divided into the boiler part and the furnace part. The boiler part includes: economizer in blue, steam drum in green, downcomer in yellow, water wall in red, superheater in purple, and reheater in orange.

[0031] The furnace parts include: the furnace is brown, the burner is gray, the ignition device is white, the air preheater is light blue, and the smoke and air duct and furnace wall are dark blue.

[0032] Furthermore, the multi-dimensional operating data of the power plant boiler temperature, pressure, flow and flue gas composition are collected, and after cleaning and preprocessing, the above basic data are stored in time series, and the basic data are encrypted using the symmetric key method to obtain the boiler database.

[0033] Furthermore, when establishing a boiler heating surface simulation model, the model needs to include water-cooled walls, superheaters, and reheaters.

[0034] Furthermore, after coupling and steady-state verification, it is necessary to ensure that the error of key parameters does not exceed ±2%, and the error of non-key parameters is within ±10%.

[0035] Furthermore, when differentiating the pipe materials in different areas by color, the pipe materials are differentiated according to the general properties of the medium transported by the pipes, and basic identification colors are assigned to them.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The present invention obtains detailed data of the heating surface of the power plant boiler through laser scanning and point cloud data technology, uses Creo 3D modeling software to perform 3D modeling of the boiler heating surface, and integrates the basic data of the boiler operation into the boiler model for data docking; the boiler heating surface is monitored in real time through the boiler model to obtain the operating status of the boiler heating surface; and an intelligent prediction model is constructed according to the basic data, and the intelligent prediction model is relied upon to provide early warning for abnormalities of the boiler heating surface pipeline, and accurately predict whether there is a fault in the heating surface pipeline; based on this, the method can not only effectively integrate the boiler operation data into the 3D model, improve the operation efficiency, safety and maintenance efficiency of the boiler, and provide technical support for the development of smart boilers; at the same time, through intelligent diagnosis and prediction, measures can be taken in advance to reduce production interruptions caused by faults and improve production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 The present invention is a flow chart of the advanced diagnosis and early warning method for the heating surface of a power plant boiler based on a three-dimensional model. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] In order to solve the technical problem that the advanced diagnosis and early warning methods of power plant boiler heating surfaces are mostly based on early warning models based on work experience, although the knowledge and experience of experts can be used for fault early warning, this method is highly dependent on personal experience and judgment, and personal subjectivity is relatively large, so it is difficult to ensure the accuracy of the early warning method. Figure 1 , this embodiment provides the following technical solutions:

[0041] The advanced diagnosis and early warning method of the heating surface of a power plant boiler based on a three-dimensional model includes the following steps:

[0042] Step 1: Obtain detailed data of the heating surface of the power plant boiler through laser scanning and point cloud data technology as data samples for 3D modeling; the detailed data includes: the types, functions, layout characteristics and technical parameters of various heating surfaces; specifically, the following steps are included:

[0043] A 3D laser scanner is used to scan the heating surface of the power plant boiler to obtain point cloud data and 3D coordinate data of its surface, and generate point cloud data. This process requires the use of high-precision scanning equipment. In this embodiment, for example, the point cloud data of the heating surface of the power plant boiler is obtained by a Trimble X9 scanner. The scanner records the 3D coordinates (X-axis, Y-axis, and Z-axis) and reflection intensity of each sampling point, thereby ensuring the accuracy of the data. The obtained point cloud data is preprocessed, including denoising, registration, and splicing operations. Point cloud post-processing software such as Trimble RealWorks is used to process the point cloud data to ensure the accuracy and integrity of the point cloud data. Secondly, based on the characteristics of lasers and the principle of light reflection, the 3D laser scanner emits a narrow and powerful laser, and detects the reflected or scattered light signals through a receiver, thereby obtaining the geometric shape and texture information of the object surface. The above steps and techniques together constitute a complete process for obtaining the heating surface data of the power plant boiler through laser scanning and point cloud data technology, ensuring the accuracy and efficiency of detection.

[0044] Step 2: Use Creo 3D modeling software to perform 3D modeling on the boiler heating surface, including: separately modeling each major component and part in the boiler heating surface, and then assembling them into a complete boiler model; specifically, the following steps are included:

[0045] Open the Creo software to create a new part file, set the corresponding units and dimensions, and select the sketch plane to draw the basic shape and outline of the boiler heating surface; you can use basic graphic elements such as straight lines and arcs to draw. Use the stretch and rotate commands based on the sketch to create the basic features of the heating surface; for example, you can use the stretch command to stretch the sketch into a solid, or use the rotate command to rotate the sketch into a cylinder. Add detail features to the basic features, such as holes, grooves, and ribs. These features can be achieved through trimming, chamfering, punching, and other commands. If the boiler heating surface is composed of multiple parts, use Creo's assembly function to assemble the parts according to the actual position. Use Creo's pipe routing function to create a pipe system on the boiler heating surface and set the starting point, end point, and path of the pipe. Among them, the pipes include but are not limited to: water inlet pipes, water outlet pipes, and steam pipes. Use Creo to create an attribute table to add attribute information to each component of the boiler heating surface, such as material, size, production date, etc., and add the information to each component. Use Creo's detection function to optimize the boiler model, check for omissions or errors, and check the model's geometric clarity and assembly rationality. Based on this, through the above steps, you can accurately create a three-dimensional model of the boiler heating surface, including various complex structures and details, so as to complete the detailed modeling of the boiler heating surface. Creo software provides powerful modeling tools and functions to help users efficiently complete complex three-dimensional modeling tasks.

[0046] Step 3: Collect basic data of boiler operation, integrate the basic data into the boiler model for data docking, ensure that the equipment information in the boiler model is consistent with the actual situation, and realize real-time data monitoring and visualization; the basic data includes: temperature, pressure, water level, flow rate and flue gas composition; specifically, by integrating relevant data of boiler operation into the three-dimensional model, real-time monitoring of the boiler can be realized, providing operators with a more intuitive decision-making basis, so as to timely discover abnormal situations, thereby improving the safety and efficiency of boiler operation;

[0047] After integrating the basic data into the boiler model for data docking, the boiler model needs to be verified using the coal-fired power plant virtual simulation system to ensure the accuracy of the boiler model. The specific steps include:

[0048] First, be familiar with the boiler heating surface model: log in to the three-dimensional virtual reality simulation system of the coal-fired power plant, familiarize yourself with the environment of the entire plant and the location and layout of each equipment, especially obtain the layout and structure of the boiler heating surface, so as to establish a three-dimensional model diagram of the power plant, and link the status information of the heating surface with the three-dimensional model, so that the operation and maintenance personnel can intuitively obtain the risk level information of the heating surface, which is convenient for the operation and maintenance personnel to formulate maintenance strategies; secondly, divide the boiler heating surface system into subsystems and thermal equipment: according to the characteristics of the boiler heating surface system and the basic modules of the virtual simulation software, the thermal equipment of the entire plant The system is divided into subsystems and thermal equipment; in this embodiment, for example: the boiler heating surface is divided into water-cooled wall, superheater, reheater and other parts, and the basic modules of GSE software are used for simulation modeling; then, a boiler heating surface simulation model is established: appropriate modules are selected from the graphic module library of the virtual simulation software to form thermal equipment, and various attribute parameters are set to establish a boiler heating surface model. The boiler heating surface model needs to include water-cooled wall, superheater, and reheater equipment; the main equipment is checked for steady state, and its temperature, pressure and Enthalpy values ​​and other parameters are consistent with the real equipment; then, coupling and steady-state verification are carried out: the boiler equipment that meets the steady-state verification requirements are coupled according to the thermal process, and the steady-state verification is achieved by changing the streamline admittance and heat exchange area at the coupling point to ensure that the error of key parameters does not exceed ±2%, and the error of non-key parameters is within ±10%; then, input control parameters and thermal parameters for dynamic simulation: input the set control parameters and thermal parameters, and output the dynamic changes of each parameter over time on the real-time simulation platform; by monitoring and processing these parameters, the performance and energy consumption characteristics of the boiler heating surface can be evaluated; finally, data processing and performance evaluation: the data collected during the simulation process are processed to evaluate the performance and energy consumption characteristics of the boiler heating surface, and the accuracy and reliability of the model are verified by comparing the simulation results with the actual operation data; based on this, through the three-dimensional visualization technology of the three-dimensional virtual reality simulation system of the coal-fired power plant, the internal structure and working principle of the boiler heating surface can be intuitively understood; secondly, through virtual simulation technology, the status of the heating surface pipes can be understood in real time, the degree of damage and hidden dangers can be analyzed, and prediction and control can be carried out. This method is based on offline monitoring and online analysis, combined with mathematical methods for wall temperature calculation and creep life analysis, to help formulate a reasonable maintenance plan; virtual simulation technology can be used to comprehensively verify the boiler heating surface model to ensure the accuracy and reliability of the model, providing strong technical support for actual operation.

[0049] Step 4: Use the boiler model combined with visualization technology to monitor the boiler heating surface in real time to obtain the operating status of the boiler heating surface; the monitoring objects include: monitoring the temperature, pressure and water level parameters of the boiler heating surface, and distinguishing different areas and pipe materials by color; specifically, the following steps are included:

[0050] The boiler heating surface is divided into the pot part and the furnace part. The pot part includes: the economizer is usually displayed in blue, which uses the waste heat of flue gas to heat the boiler feed water, reduce the exhaust gas temperature and improve the boiler efficiency; the steam drum is displayed in green, which is a cylindrical pressure container responsible for water circulation and steam generation; the downcomer is displayed in yellow, which is responsible for introducing the water in the steam drum into the lower header and then distributing it to each water-cooled wall tube; the water-cooled wall is displayed in red, located around the furnace, and its main task is to absorb the radiant heat in the furnace to evaporate water; the superheater is displayed in purple, which is responsible for heating saturated steam into superheated steam with a certain temperature; the reheater is displayed in orange, which is responsible for heating and raising the temperature of steam that has done part of the work again, and then continue to do work; the furnace part includes: the furnace is displayed in brown, and its function is to provide a suitable space for fuel combustion; the burner is displayed in gray, which is responsible for fuel combustion; the ignition device is displayed in white to ensure stable combustion of the fuel; the air preheater is displayed in light blue to improve combustion efficiency; the smoke and air duct and furnace wall are displayed in dark blue to protect the furnace wall structure;

[0051] The pipe materials are distinguished according to the general properties of the medium transported by the pipe, and basic identification colors are assigned to them; including: water is bright green, water vapor is bright red, air is light gray, gas is medium yellow, acid or alkali is purple, flammable liquids are brown, other liquids are black, and oxygen is light blue.

[0052] Step 5: Build an intelligent prediction model based on the basic data of boiler operation, and use the intelligent prediction model to warn of abnormalities on the boiler heating surface pipeline, predict whether there is a fault in the heating surface pipeline, and help operation and maintenance personnel to diagnose the fault; specifically, the following steps are included:

[0053] Through the various sensors installed on the power plant boiler body, the multi-dimensional operating data of the power plant boiler temperature, pressure, flow and flue gas composition are collected in real time; the collected basic data are tested for validity, pre-processed for data transformation, and cleaned after pre-processing, including: removing abnormal data, data standardization and normalization; the processed basic data are then divided into training sets and test sets as data samples for the intelligent prediction model; due to the wide variety of sensors in the boiler system, the data has problems such as sudden abnormal values ​​and inconsistent collection accuracy of different parameters, so the basic data needs to be pre-processed and cleaned to ensure the accuracy and reliability of the basic operating data. In order to facilitate model training; after cleaning and preprocessing the collected multi-dimensional operating data of power plant boiler temperature, pressure, flow and flue gas composition, the above basic data are stored in time series, and the basic data are encrypted using the symmetric key method to obtain the boiler database; specifically, the symmetric key method uses the same key held by both parties for decryption. By using the same key for encryption and decryption, the symmetric key method ensures that only those holding the correct key can access and decrypt the data, thereby protecting the confidentiality of the data; using the neural network algorithm to establish an intelligent prediction model, the training set and the test set are successively imported into the intelligent prediction model for training and testing, and the test results are output; then the test results are The results are compared with the actual boiler operation results to ensure the accuracy of the intelligent prediction model; in this embodiment, the real-time monitoring of the boiler heating surface pipeline is realized by using the neural network algorithm, so as to more accurately evaluate the actual wall temperature and damage of the furnace tube; secondly, the real-time status and detection data are intuitively displayed through three-dimensional modeling and virtual reality technology to help operation and maintenance personnel better understand the operation status of the furnace tube; in addition, the intelligent prediction model can also assist in offline detection of the status of key parts through technical means such as machine vision and ultrasonic detection, thereby improving the accuracy and efficiency of detection; the real-time monitoring data is imported into the intelligent prediction model after the test for fault prediction, and the prediction results are output to realize the prediction of the boiler damage Real-time monitoring of hot surface pipelines; and automatically adjust the combustion control strategy according to the prediction results to achieve the optimal fuel ratio and maximize the combustion efficiency; based on this, the big data is analyzed through the intelligent prediction model, so that the abnormalities of the boiler heating surface pipelines can be effectively discovered from the massive data and early warnings can be given, thereby improving the performance and reliability of the boiler, reducing operation and maintenance costs, and improving the overall operational efficiency; secondly, the deep laws and trends behind the equipment operation data are analyzed through the intelligent prediction model, providing enterprises with decision-making support in energy efficiency evaluation, cost analysis, predictive maintenance and other aspects, which helps enterprises discover potential energy-saving potential and room for improvement, and provides data support for subsequent energy-saving transformation and equipment upgrades.

[0054] The beneficial effects achieved by the above content: Through the above operation, intelligent advanced diagnosis and early warning of the heating surface of the power plant boiler can be realized, adjustment measures can be taken in advance, and production interruptions of the boiler due to faults can be reduced, thereby improving the boiler production efficiency, reducing energy waste, and meeting the requirements of sustainable development.

[0055] Working principle: Detailed data of the heating surface of the power plant boiler is obtained through laser scanning and point cloud data technology, and the boiler heating surface is 3D modeled using Creo 3D modeling software, and the basic data of the boiler operation is integrated into the boiler model for data docking; the boiler heating surface is monitored in real time through the boiler model to obtain the operating status of the boiler heating surface; and an intelligent prediction model is built based on the basic data. The intelligent prediction model is used to provide early warning for abnormalities in the boiler heating surface pipelines and accurately predict whether there are any faults in the heating surface pipelines.

[0056] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0057] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A three-dimensional model-based advanced diagnosis and early warning method for heating surfaces of power plant boilers, characterized in that: The following steps are involved: Step 1: Obtain detailed data of the heating surface of the power plant boiler through laser scanning and point cloud data technology as data samples for 3D modeling; the detailed data includes: the type, function, layout characteristics and technical parameters of the heating surface; Step 2: Use Creo 3D modeling software to perform 3D modeling on the boiler heating surface, including: separately modeling the components and parts in the boiler heating surface, and then assembling them into a complete boiler model; Step 3: Collect basic data of boiler operation and integrate the basic data into the boiler model for data docking; the basic data includes: temperature, pressure, water level, flow rate and flue gas composition; Step 4: Use the boiler model and visualization technology to monitor the boiler heating surface in real time to obtain the operating status of the boiler heating surface; the monitoring objects include: monitoring the temperature, pressure and water level parameters of the boiler heating surface, and distinguishing different areas and pipe materials by color; Step 5: Build an intelligent prediction model based on the basic data of boiler operation, and use the intelligent prediction model to issue abnormal warnings to the boiler heating surface pipelines to predict whether there are any faults in the heating surface pipelines.

2. The method for advanced diagnosis and early warning of heating surface of power plant boiler based on three-dimensional model according to claim 1 is characterized by: In step 5, an intelligent prediction model is constructed based on the basic data of boiler operation, which specifically includes the following steps: The sensors installed on the power plant boiler body collect the multi-dimensional operating data of the power plant boiler temperature, pressure, flow and flue gas composition in real time; The collected basic data are validated and preprocessed by data transformation, and the preprocessed basic data are cleaned, including: removing abnormal data, data standardization and normalization; the processed basic data are then divided into training sets and test sets as data samples for the intelligent prediction model; Use neural network algorithm to establish intelligent prediction model, import training set and test set into the intelligent prediction model in turn for training and testing, and output test results; then compare the test results with the actual boiler operation results to ensure the accuracy of the intelligent prediction model; The real-time monitoring data is imported into the tested intelligent prediction model for fault prediction, and the prediction results are output, and the combustion control strategy is automatically adjusted according to the prediction results.

3. The method for advanced diagnosis and early warning of heating surface of power plant boiler based on three-dimensional model according to claim 1 is characterized by: In the step 1, the detailed data of the heating surface of the power plant boiler is obtained by laser scanning and point cloud data technology, which specifically includes the following steps: A 3D laser scanner is used to scan the heating surface of the power plant boiler to obtain point cloud data and 3D coordinate data of its surface and generate point cloud data. The obtained point cloud data is then preprocessed, including: denoising, registration and stitching operations, to obtain detailed data of the heating surface of the power plant boiler.

4. The method for advanced diagnosis and early warning of heating surface of power plant boiler based on three-dimensional model according to claim 1 is characterized by: In the step 2, the three-dimensional modeling of the boiler heating surface is performed using Creo three-dimensional modeling software, which specifically includes the following steps: Open the Creo software to create a new part file, set the corresponding units and dimensions, select the sketch plane to draw the basic shape and outline of the boiler heating surface; use the stretch and rotate commands according to the sketch to create the basic features of the heating surface, and add detail features on the basic features; use Creo's assembly function to assemble the various parts according to the actual position; use Creo's pipe routing function to create a piping system on the boiler heating surface, and set the start, end and path of the pipe; use Creo to create an attribute table to add attribute information to each component of the boiler heating surface; use Creo's detection function to optimize the boiler model, check for omissions or errors, and check the model's geometric clarity and assembly rationality.

5. The method for advanced diagnosis and early warning of heating surface of power plant boiler based on three-dimensional model according to claim 1 is characterized by: In step 3, after the basic data is integrated into the boiler model for data docking, the boiler model needs to be verified using the coal-fired power plant virtual simulation system, which specifically includes the following steps: Familiarize yourself with the boiler heating surface model: log in to the 3D virtual reality simulation system of the coal-fired power plant to obtain the layout and structure of the boiler heating surface; Divide the boiler heating surface system into subsystems and thermal equipment: According to the characteristics of the boiler heating surface system and the basic modules of the virtual simulation software, divide the thermal system of the whole plant into subsystems and thermal equipment; Establish a boiler heating surface simulation model: Select appropriate modules from the graphic module library of the virtual simulation software to form thermal equipment, set various attribute parameters, and establish a boiler heating surface model; Carry out coupling and steady-state verification: Carry out steady-state verification on the main equipment, and make its temperature, pressure and enthalpy values ​​consistent with the real equipment by adjusting the heat exchange area and streamline admittance; Couple the boiler equipment that meets the steady-state verification requirements according to the thermodynamic process, and realize its steady-state verification by changing the streamline admittance and heat exchange area at the coupling point; Input control parameters and thermal parameters for dynamic simulation: Input the set control parameters and thermal parameters, and output the dynamic changes of each parameter over time on the real-time simulation platform; Data processing and performance evaluation: Process the data collected during the simulation, evaluate the performance and energy consumption characteristics of the boiler heating surface, and verify the accuracy and reliability of the model by comparing the simulation results with the actual operating data.

6. The method for advanced diagnosis and early warning of heating surface of power plant boiler based on three-dimensional model according to claim 1 is characterized by: In step 4, different areas and pipe materials are distinguished by color, which specifically includes the following steps: The boiler heating surface is divided into the boiler part and the furnace part. The boiler part includes: economizer in blue, steam drum in green, downcomer in yellow, water wall in red, superheater in purple, and reheater in orange. The furnace parts include: the furnace is brown, the burner is gray, the ignition device is white, the air preheater is light blue, and the smoke and air duct and furnace wall are dark blue.

7. The method for advanced diagnosis and early warning of heating surface of power plant boiler based on three-dimensional model according to claim 2 is characterized by: The multi-dimensional operating data of the power plant boiler temperature, pressure, flow and flue gas composition are collected, and after cleaning and preprocessing, the basic data are stored in time series and encrypted using the symmetric key method to obtain the boiler database.

8. The method for advanced diagnosis and early warning of heating surface of power plant boiler based on three-dimensional model according to claim 5 is characterized by: When establishing a boiler heating surface simulation model, the model must include water-cooled walls, superheaters, and reheaters.

9. The method for advanced diagnosis and early warning of heating surfaces of power plant boilers based on three-dimensional models according to claim 5 is characterized by: After coupling and steady-state verification, it is necessary to ensure that the error of key parameters does not exceed ±2%, and the error of non-key parameters is within ±10%.

10. The method for advanced diagnosis and early warning of heating surface of power plant boiler based on three-dimensional model according to claim 6, characterized in that: When distinguishing the pipe materials of different areas by color, the pipe materials are distinguished according to the general properties of the medium transported by the pipe, and basic identification colors are assigned to different pipes.

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