CN117390811A - Heating surface tube health degree calculation method and device, electronic equipment and storage medium - Google Patents

Heating surface tube health degree calculation method and device, electronic equipment and storage medium Download PDF

Info

Publication number
CN117390811A
CN117390811A CN202311461754.2A CN202311461754A CN117390811A CN 117390811 A CN117390811 A CN 117390811A CN 202311461754 A CN202311461754 A CN 202311461754A CN 117390811 A CN117390811 A CN 117390811A
Authority
CN
China
Prior art keywords
heating surface
damage
determining
health degree
influence
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202311461754.2A
Other languages
Chinese (zh)
Inventor
张作贵
王峥
田根起
王延峰
赵双群
杨昌顺
倪一帆
侍克献
王苗苗
孙康
邓志成
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shanghai Power Equipment Research Institute Co Ltd
Original Assignee
Shanghai Power Equipment Research Institute Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shanghai Power Equipment Research Institute Co Ltd filed Critical Shanghai Power Equipment Research Institute Co Ltd
Priority to CN202311461754.2A priority Critical patent/CN117390811A/en
Publication of CN117390811A publication Critical patent/CN117390811A/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/14—Pipes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/08—Thermal analysis or thermal optimisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computer Hardware Design (AREA)
  • Artificial Intelligence (AREA)
  • Computational Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Mathematical Analysis (AREA)
  • Pure & Applied Mathematics (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Mathematical Optimization (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Testing Resistance To Weather, Investigating Materials By Mechanical Methods (AREA)

Abstract

The embodiment of the invention discloses a heating surface tube health degree calculation method, a heating surface tube health degree calculation device, electronic equipment and a storage medium, wherein the heating surface tube health degree calculation method comprises the following steps: acquiring operation and maintenance historical data of a power plant boiler in a high-temperature material database; determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data; determining a relationship rule of each influence factor and material accumulation damage based on the key influence position of the heating surface pipe and each influence factor; and establishing a target health degree calculation model of the key position of the heating surface management based on the relation rule. The method provided by the embodiment of the invention can pay attention to each influence factor influencing the service life of the heating surface pipe, accurately calculate the health degree of the heating surface pipe according to the relation rule of each influence factor and the accumulated damage of the materials, further improve the accuracy of estimating the residual service life of the heating surface pipe, and provide technical guarantee for the safe operation of the power plant unit.

Description

Heating surface tube health degree calculation method and device, electronic equipment and storage medium
Technical Field
The embodiment of the invention relates to the technical field of intelligent power plant management, in particular to a heating surface management health degree calculation method, a heating surface management health degree calculation device, electronic equipment and a storage medium.
Background
In a power plant, large power generation equipment is subjected to tens of thousands of hours of operation, namely long-term heat treatment or high-strength load test, material aging, oxidation corrosion and other processes, so that the equipment is accumulated to be damaged, which is a necessary result of high-temperature operation. Especially those that are out of service, most of them are still in use, except for a small amount of scrap. The boiler heating surface (mainly referred to as boiler water cooling wall, superheater, reheater and economizer) pipeline of the thermal power generating unit runs for a long time under high temperature and high pressure, steam corrosion on the inner wall and smoke corrosion on the outer wall of the boiler heating surface can lead to the reduction of the wall thickness of the pipe, meanwhile, the inside of the pipe material can be subjected to tissue aging and performance reduction, and the continuous accumulation of the damage factors can lead to the pipe bursting leakage of the heating surface pipeline, so that the safe running of the unit is seriously affected. If the performance degradation condition of the component materials can be timely and accurately found, the damage state of the heating surface pipes in the long-term service process can be judged in advance, the health degree of the heating surface pipes is given, the residual service life of the heating surface pipes is calculated, and measures such as maintenance or replacement can be adopted in advance for the severely damaged pipes so as to avoid the occurrence of non-stop accidents of the unit caused by pipe explosion of the heating surface, thereby providing technical support for the safe operation of the power plant unit.
The traditional nondestructive detection and estimation method for the health degree of the heating surface pipe is mainly used for directly calculating the health degree of the heating surface pipe according to the use time length or expert experience and the like, and estimating the residual life of the heating surface pipe according to the health degree. However, there are many factors that affect the safety of the heated surface tube of the boiler, such as overheating, abrasion, stress cracking, corrosion, welding quality, unreasonable materials and designs, and the method does not consider the above-mentioned various influencing factors, so that the calculated health of the heated surface tube and the estimated residual life of the heated surface tube are inaccurate, and cannot provide technical support for the safe operation of the power plant unit.
Disclosure of Invention
The embodiment of the invention provides a heating surface pipe health degree calculating method, a heating surface pipe health degree calculating device, electronic equipment and a storage medium, which can pay attention to each influence factor influencing the service life of the heating surface pipe, accurately calculate the health degree of the heating surface pipe according to the relation rule of each influence factor and material accumulated damage, further improve the accuracy of estimating the residual service life of the heating surface pipe and provide technical support for the safe operation of a power plant unit.
In a first aspect, an embodiment of the present invention provides a method for calculating health of a heating surface pipe, including:
Acquiring operation and maintenance historical data of a power plant boiler in a high-temperature material database;
determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data;
determining a relationship rule of each influence factor and material accumulation damage based on the key influence position of the heating surface pipe and each influence factor;
and establishing a target health degree calculation model of the key position of the heating surface management based on the relation rule.
In a second aspect, an embodiment of the present invention provides a heating surface tube health calculating device, including:
the data acquisition module is used for acquiring operation and maintenance historical data of the power plant boiler in the high-temperature material database;
the first determining module is used for determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data;
the second determining module is used for determining the relation rule of each influence factor and the material accumulation damage based on the key influence position of the heating surface pipe and each influence factor;
and the model building module is used for building a target health degree calculation model of the key position of the heating surface management based on the relation rule.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the program, the processor implements the method for controlling an electronic device according to any one of the embodiments of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where a computer program is stored, where the program when executed by a processor implements a method for calculating health of a heating surface tube according to any one of the embodiments of the present invention.
In the embodiment of the invention, the operation and maintenance historical data of the power plant boiler in the high-temperature material database is obtained; determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data; determining a relationship rule of each influence factor and material accumulation damage based on the key influence position of the heating surface pipe and each influence factor; and establishing a target health degree calculation model of the key position of the heating surface management based on the relation rule. In the embodiment of the invention, each influence factor influencing the service life of the heating surface pipe can be focused, the health degree of the heating surface pipe can be accurately calculated according to the relation rule of each influence factor and the accumulated damage of the materials, the accuracy of estimating the residual service life of the heating surface pipe is further improved, and technical guarantee is provided for the safe operation of a power plant unit.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a first flowchart of a method for calculating the health of a heating surface tube according to an embodiment of the present invention;
FIG. 2 is a second flowchart of a method for calculating the health of a heating surface tube according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a heating surface tube health calculating device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Fig. 1 is a first flowchart of a method for calculating the health of a heating surface pipe, which is provided by the embodiment of the invention, wherein the method of the embodiment of the invention can pay attention to each influencing factor influencing the service life of the heating surface pipe, accurately calculate the health of the heating surface pipe according to the relation rule of each influencing factor and the accumulated damage of materials, further improve the accuracy of estimating the residual service life of the heating surface pipe, and provide technical support for the safe operation of a power plant unit. The method can be executed by the heating surface management health degree calculating device provided by the embodiment of the invention, and the device can be realized in a software and/or hardware mode. The following embodiments will be described taking the example of the integration of the apparatus in an electronic device, and referring to fig. 1, the method may specifically include the following steps:
And 101, acquiring operation and maintenance historical data of a power plant boiler in a high-temperature material database.
Wherein the high temperature material database covers both the original state and the service state, including performance data and organization data. The high-temperature material database in the scheme comprises the life cycle data of the heating surface pipe material, historical use data, design data, detection data and the like of the power plant boiler. Historical usage data such as operating time of heated surface tubes of the boiler, load conditions, temperature, pressure, fuel consumption, environmental information at the time of operation, and the like. By analyzing the historical use data, the working condition and the use condition of the heating surface pipe of the boiler can be known. The design data comprises the design parameters, the structure, the materials and the like of the heating surface pipe of the boiler. The detection data is obtained through periodic detection and monitoring, and comprises measurement result data of various physical and chemical indexes. Such as corrosion of the inner walls of the boiler, wall thickness reduction of the pipes, and aging of the material.
Specifically, a target health degree calculation model of the heating surface pipe can be established according to the operation and maintenance historical data of the boiler in the high-temperature material database. Therefore, when the target health degree calculation model of the heating surface pipe needs to be established, the server can acquire the historical operation and maintenance data of the boiler from the high-temperature material database.
Step 102, determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data.
The key influencing position of the heating surface pipe is a position which is easy to cause the leakage of the explosion pipe of the heating surface pipe. Each influencing factor is a factor that affects the lifetime of the heated surface tube. Each influencing factor at least comprises: wall thickness, hardness, strength, tissue aging, creep, fatigue, corrosion, wear, and the like.
In an alternative embodiment, after the server obtains the operation and maintenance historical data, the server analyzes the operation and maintenance historical data to obtain key influence positions and each influence factor of the heating surface pipe. For example, by analyzing the pipe burst leakage events in the operation and maintenance history data, observing which parts frequently have problems, such as pipe bending, connecting parts, welding parts and the like, and determining the positions as key influence positions. And determining various influencing factors such as wall thickness, hardness, strength, tissue aging, creep, fatigue, corrosion, abrasion and the like which influence the service life of the heated surface pipe by analyzing pipeline damage conditions, maintenance records, material detection results and the like in the operation and maintenance historical data.
And step 103, determining the relation rule of each influence factor and the material accumulation damage based on the key influence position of the heated surface pipe and each influence factor.
Specifically, different influencing factors have different influence degrees on the damage of the material causing the heating surface pipe, and each influencing factor has a corresponding relation rule with the accumulated damage of the material. For example, long-term high temperature effects, corrosion and abrasion, etc., can lead to reduced wall thickness, which in turn reduces the strength and durability of the pipe. Too high a temperature may cause the material to soften, while too low a temperature may cause the material to become brittle. Such hardness variations may reduce the strength and fatigue resistance of the material.
In an alternative embodiment, after determining the key influence position of the heating surface pipe and each influence factor, determining a calculation mode of damage degree of each influence factor to the key influence position based on the operation and maintenance historical data; determining damage constants corresponding to the damage degrees according to the material information and the environment information of the heating surface pipe; the relation rule of each influence factor and the accumulated damage of the material is determined based on the damage constant corresponding to each damage degree, and is as follows: the strength index of the pipe is equal to the sum of products of damage constants and damage degrees of the influence factors.
And 104, establishing a target health degree calculation model of the key position of the heating surface management based on the relation rule.
The target health degree calculation model is trained and used for accurately calculating the health degree of the heating surface tube. In an alternative embodiment, after determining the relation rule between each influence factor and the material accumulation damage, determining the weight value of each influence factor according to the material information and the service environment information of the heating surface pipe; based on a relation rule, weight values of all influence factors and a predetermined neural network algorithm, an initialized health degree calculation model of a key position of a heating surface management is established; determining detection data and detection result data of each history detection from the operation and maintenance history data; determining a training sample library of the health degree calculation model based on the historical detection data; the training sample library comprises sample data and sample labels; when the initialized health degree calculation model does not meet the preset conditions, one sample is selected from the sample data to serve as a current sample, and training is conducted on the initialized health degree calculation model based on the current sample until the initialized health degree calculation model meets the preset conditions, and the target health degree calculation model is obtained.
After the target health degree calculation model is obtained, the health degree of the heating surface tube at the current moment can be calculated through the target health degree calculation model. In this scheme, optionally, calculating the health degree of the heating surface tube at the current moment according to the target health degree calculation model includes: acquiring detection data of a key influence position of a heating surface pipe at the current moment; inputting the detection data into a target health degree calculation model to obtain the health degree of the key influence position corresponding to the detection data; the remaining life of the heated surface tube is determined based on the health of the critical impact location.
Specifically, the detection data comprises relevant data obtained by detecting the heated surface pipe, including environmental data, wall thickness, hardness, strength, tissue aging, creep, fatigue, corrosion, abrasion and other relevant data of key influence positions of the heated surface pipe. After the detection data is obtained, the detection data is input into the target health degree calculation model. And the target health degree calculation model calculates the health degree of the key influence position of the heating surface tube corresponding to the input detection data according to the detection data, the relation rule of each influence factor and the material accumulation damage and the weight value of each predetermined influence factor. There is a certain relationship between the health of the heated surface tube and the remaining life of the heated surface tube, the lower the health of the heated surface tube is, the less the remaining life of the heated surface tube is, the higher the health of the heated surface tube is, and the more the remaining life of the heated surface tube is. After the health degree of the heated surface tube calculated by the target health degree calculation model is obtained, the server can determine the residual life of the heated surface tube according to the preset relationship between the health degree and the residual life.
In the above steps, the health degree of the heating surface pipe can be accurately calculated in real time through the target health degree calculation model, and the residual life of the heating surface pipe is further calculated according to the health degree, so that a user can maintain or replace a severely damaged pipeline in advance according to the residual life, and the occurrence of non-stop accidents of a unit due to pipe explosion of the heating surface is avoided.
According to the technical scheme, operation and maintenance historical data of a power plant boiler in a high-temperature material database are obtained; determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data; determining a relationship rule of each influence factor and material accumulation damage based on the key influence position of the heating surface pipe and each influence factor; and establishing a target health degree calculation model of the key position of the heating surface management based on the relation rule. According to the technical scheme, each influence factor influencing the service life of the heating surface pipe can be focused, the health degree of the heating surface pipe can be accurately calculated according to the relation rule of each influence factor and the accumulated damage of materials, the accuracy of estimating the residual service life of the heating surface pipe is further improved, and technical guarantee is provided for safe operation of a power plant unit.
Fig. 2 is a second flowchart of a heating surface tube health calculating method according to an embodiment of the present invention, where the embodiment is refined based on the foregoing embodiment. A specific method may be as shown in fig. 2, and the method may include the steps of:
step 201, acquiring operation and maintenance historical data of a power plant boiler in a high-temperature material database.
Step 202, determining key influence positions and various influence factors of heating surface pipes of the boiler based on operation and maintenance historical data.
And 203, determining a calculation mode of the damage degree of each influence factor to the key influence position based on the operation and maintenance historical data.
Wherein, each influencing factor at least comprises: wall thickness, hardness, strength, tissue aging, creep, fatigue, corrosion, wear, and the like. The damage degree of different influence factors to the key influence positions is different, and the historical data is analyzed, so that the calculation mode of the damage degree of each influence factor to the key influence positions can be obtained.
In this scheme, optionally, confirm the calculation mode of creep to the damage degree of key influence position based on operation and maintenance historical data, include: determining a main curve of creep according to a parameter method or an isotherm method based on a high-temperature material database; and determining the calculation mode of the damage degree of the creep to the key influence position based on the main curve of the creep.
The parameter method can be an L-M (Levenberg-Marquardt) parameter method, and the L-M parameter method is an optimization algorithm of a nonlinear least square method and is used for solving the nonlinear least square problem. The basic idea of the L-M parametric approach is to continuously adjust the model parameters in an iterative manner such that the residual between the predicted value and the actual observed value of the model is minimized. The method realizes gradual adjustment of parameters by combining the characteristics of a gradient descent method and a Gaussian-Newton method in each iteration step, thereby achieving the estimation of optimal parameters.
In the scheme, a main curve for fitting the lasting creep life according to an L-M parameter method is as follows:
P＝10 -3 T(K)(C+lgt r )＝C 0 +C 1 lgσ+C 2 lg 2 σ
wherein P is a main curve, and C is an L-M constant; c (C) 0 、C 1 、C 2 All are undetermined coefficients; t is the service temperature, namely the environmental temperature of the heating surface pipe, sigma is the service stress calculated in advance, T r For lifetime, K is the K temperature.
The main curve for fitting the durable creep life by using the isotherm method is: lgσ=lga-mlgt r
Wherein sigma is the service stress calculated in advance, t r For longevityBoth a and m are constants set.
Further, the degree of damage to the creep is determined as:wherein D is C To the extent of creep damage, Δt i For the run time under the parameter i, t ri For creep rupture time under the condition of parameter i, n is the number of losses at different time points.
Further, a calculation mode of damage degree of other influence factors to the key influence positions is determined based on the operation and maintenance historical data.
For example, the degree of damage to the key impact location by fatigue is determined by the following calculation:wherein D is p To the extent of fatigue damage, n i For the number of cycles under the condition of parameter i, N Pi For the total number of cycles under the condition of parameter i, n is the number of losses at different points in time.
The corrosion includes flue gas corrosion and steam corrosion, and flue gas corrosion can cause the damage to the pipe wall thickness of heating surface pipe, and the calculation mode of corrosion thickness real-time value is: delta f ＝K f t nf . Wherein K is f Is the corrosion rate coefficient; t is the corrosion time of the pipe, n f Is the corrosion kinetic index of the pipe; delta f Is an etch thickness real time value. Steam corrosion can damage the thickness of the oxide skin of the heated surface pipe, and the calculation mode of the real-time value of the thickness of the oxide skin is as follows: delta o ＝Kt n . Wherein K is an oxidation rate coefficient, t is an oxidation time, n is an oxidation factor, delta o Is the real-time value of the oxide scale thickness.
For example, the wear thickness real-time value is calculated by: delta m ＝c km v 3 t. Wherein c km Is the antiwear coefficient, v is the direct fume flow rate, t is the running time, delta m Is a wear thickness real time value.
At the time of obtaining the corrosion thickness real-time valueAfter the real-time value of the oxide skin thickness and the real-time value of the abrasion thickness, the damage degree of the smoke corrosion, the steam corrosion or the abrasion to the key influence position is calculated according to the following formula: wherein D is δ The damage degree delta of smoke corrosion, steam corrosion or abrasion i Is the thickness of smoke corrosion, steam corrosion or abrasion under the working condition of the parameter i; delta si Is the wall thickness value under the working condition of the parameter i. The coefficients in the above formula can be obtained by fitting according to the operation and maintenance history data.
Through the steps, the calculation mode of the damage degree corresponding to each influence factor can be accurately determined, and a foundation is laid for the follow-up determination of the relation rule between each influence factor and the accumulated damage of the material.
And 204, determining the relation rule of each influence factor and the accumulated damage of the material based on the calculation mode of each damage degree and the high-temperature material database.
Specifically, different influencing factors have different influence degrees on the damage of the material causing the heating surface pipe, and each influencing factor has a corresponding relation rule with the accumulated damage of the material. In this scheme, optionally, based on the calculation mode of each damage degree and the high-temperature material database, determining the relation rule of each influence factor and the accumulated damage of the material includes: determining damage constants corresponding to the damage degrees according to the material information and the environment information of the heating surface pipe; the relation rule of each influence factor and the accumulated damage of the material is determined based on the damage constant corresponding to each damage degree, and is as follows: the strength index of the heated surface pipe is equal to the sum of products of damage constants and damage degrees of various influencing factors.
The material information of the heating surface pipe comprises the material type, chemical composition, thermophysical property, mechanical property and the like of the heating surface pipe. The environmental information is the environmental conditions in which the heated surface tube is located, including temperature, pressure, gas composition, flow rate, etc. After the material information and the environment information of the heating surface pipe are obtained, determining the damage constant corresponding to each damage degree according to a summary mode of the relation rule of the material information, the environment information, each influence factor and the material accumulated damage, predetermined field big data and the like. After determining the damage constant, determining the relationship rule of each influence factor and the accumulated damage of the material based on the damage constant corresponding to each damage degree as follows: the strength index of the pipe is equal to the sum of products of damage constants and damage degrees of the influence factors.
Specifically, the relation rule of each influence factor and the accumulated damage of the material is determined by expressing the damage constant corresponding to each damage degree by the following formula:
D＝a 1 D 1 +a 2 D 2 +…+a n D n =f (σ) =f (HB) =f (δ). Wherein D is total damage amount, a 1 …a n D is a damage constant related to material characteristics and service environment 1 …D n The damage amount of different influencing factors is shown as sigma, the strength index is shown as HB, the hardness index is shown as HB, and the wall thickness index is shown as delta.
According to the steps, the relation rule between each influence factor and the accumulated damage of the material can be accurately determined, and a foundation is laid for the subsequent establishment of a target health degree calculation model according to the relation rule.
And 205, determining the weight value of each influence factor according to the material information and the environment information of the heating surface pipe.
The material information of the heating surface pipe comprises the material type, chemical composition, thermophysical property, mechanical property and the like of the heating surface pipe. The environmental information is the environmental conditions in which the heated surface tube is located, including temperature, pressure, gas composition, flow rate, etc.
After the material information and the environment information of the heating surface pipe are determined, the importance of each influence factor is quantified according to the material information and the environment information by using a quantitative evaluation method. Quantitative evaluation methods include expert scoring, fuzzy mathematical methods, and analytic hierarchy processes. The methods can weight-rank the influence factors and reflect the relative importance degree of the influence factors on the performance of the heating surface pipe. Further, according to the quantized importance evaluation result, the weight values of all the influence factors are integrated. I.e. each influencing factor is assigned a respective weight value depending on the relative magnitude of the importance of the respective influencing factor.
And 206, establishing an initialized health degree calculation model of the key position of the heating surface management based on the relation rule, the weight value of each influence factor and a predetermined neural network algorithm.
Wherein the initialized health calculation model is a model that has not been trained yet. The neural network algorithm is a calculation model for simulating the operation of the human brain neurons, and realizes learning and deducing tasks by constructing a connection network among multiple layers of neurons. Common neural network algorithms include feed forward neural networks, recurrent neural networks, self-encoders, variational self-encoders, generating countermeasure networks, reinforcement learning, and the like.
After the relation rule of each influence factor and the material accumulation damage and the weight value of each influence factor are obtained, preprocessing is carried out on the collected data, wherein the preprocessing comprises data cleaning, missing value processing, abnormal value processing and the like. And carrying out relevant feature extraction on the data in the high-temperature material database according to the influence factors and the weight values. And establishing an initialized health degree calculation model of the key position of the heating surface management according to the extracted data, the relation rule, the weight value of each influence factor and the neural network algorithm.
Step 207, obtaining a target health degree calculation model based on the initialized health degree calculation model.
The target health degree calculation model is trained and used for accurately calculating the health degree of the heating surface tube. In this embodiment, optionally, obtaining the target health degree calculation model based on the initialized health degree calculation model includes: determining detection data and detection result data of each history detection from the operation and maintenance history data; determining a training sample library of the health degree calculation model based on the historical detection data; when the initialized health degree calculation model does not meet the preset conditions, one sample is selected from the sample data to serve as a current sample, and training is conducted on the initialized health degree calculation model based on the current sample until the initialized health degree calculation model meets the preset conditions, and the target health degree calculation model is obtained.
The training sample library comprises sample data and sample labels. The detection data of the historical detection is taken as sample data, and the detection result data is taken as a sample label. The preset condition may be that the value of the predefined loss function reaches a preset value, i.e. the loss function converges. After the training sample library is determined, selecting one sample from the sample library as a current sample, and inputting the current sample into the initialized health degree calculation model to obtain output information which is output by the initialized health degree calculation model and corresponds to the current sample. And the output information and the sample label are input into a predefined loss function, and if the loss function does not reach a preset condition, the model parameters of the initialized health degree calculation model are adjusted according to the loss function. And selecting another sample from the sample library as the current sample, and repeatedly executing the operation until the loss function reaches the preset condition to obtain the target health degree calculation model.
In the embodiment of the invention, the operation and maintenance historical data of the power plant boiler in the high-temperature material database is obtained. The key influencing positions and the influencing factors of the heating surface pipes of the boiler are determined based on the operation and maintenance historical data. And determining a calculation mode of the damage degree of each influence factor to the key influence position based on the operation and maintenance historical data. Determining a main curve of creep according to a parameter method or an isotherm method based on a high-temperature material database; and determining the calculation mode of the damage degree of the creep to the key influence position based on the main curve of the creep. And determining the relation rule of each influence factor and the accumulated damage of the material based on the calculation mode of each damage degree and the high-temperature material database. Determining damage constants corresponding to the damage degrees according to the material information and the environment information of the heating surface pipe; the relation rule of each influence factor and the accumulated damage of the material is determined based on the damage constant corresponding to each damage degree, and is as follows: the strength index of the pipe is equal to the sum of products of damage constants and damage degrees of the influence factors. Determining weight values of all influence factors according to material information and service environment information of the heating surface pipe; and establishing an initialized health degree calculation model of the key position of the heating surface management based on the relation rule, the weight value of each influence factor and a predetermined neural network algorithm. And obtaining a target health degree calculation model based on the initialized health degree calculation model. Determining detection data and detection result data of each history detection from the operation and maintenance history data; determining a training sample library of the health degree calculation model based on the historical detection data; the training sample library comprises sample data and sample labels; when the initialized health degree calculation model does not meet the preset conditions, one sample is selected from the sample data to serve as a current sample, and training is conducted on the initialized health degree calculation model based on the current sample until the initialized health degree calculation model meets the preset conditions, and the target health degree calculation model is obtained. According to the technical scheme, each influence factor influencing the service life of the heating surface pipe can be focused, the health degree of the heating surface pipe can be accurately calculated according to the relation rule of each influence factor and the accumulated damage of materials, the accuracy of estimating the residual service life of the heating surface pipe is further improved, and technical guarantee is provided for safe operation of a power plant unit.
Fig. 3 is a schematic structural diagram of a heating surface tube health calculating device according to an embodiment of the present invention, where the device is adapted to execute the heating surface tube health calculating method according to the embodiment of the present invention. As shown in fig. 3, the apparatus may specifically include:
the data acquisition module 301 is configured to acquire operation and maintenance history data of a power plant boiler in the high-temperature material database;
a first determining module 302, configured to determine key influencing positions and respective influencing factors of heating surface pipes of the boiler based on the operation and maintenance history data;
a second determining module 303, configured to determine a relationship rule between each influencing factor and the material accumulation damage based on the key influencing position of the heating surface pipe and each influencing factor;
the model building module 304 is configured to build a target health degree calculation model of the heating surface management key location based on the relationship rule.
Optionally, the second determining module 303 is specifically configured to: determining a calculation mode of the damage degree of each influence factor to the key influence position based on the operation and maintenance historical data;
and determining the relation rule of each influence factor and the accumulated damage of the material based on the calculation mode of each damage degree and the high-temperature material database.
Optionally, the second determining module 303 is further configured to: determining damage constants corresponding to the damage degrees according to the material information and the environment information of the heating surface pipe;
the relation rule of each influence factor and the accumulated damage of the material is determined based on the damage constant corresponding to each damage degree, and is as follows: the strength index of the heated surface pipe is equal to the sum of products of damage constants and damage degrees of various influencing factors, wherein the hardness index of the pipeline is equal to the sum of products of damage constants and damage degrees of various influencing factors.
Optionally, the second determining module 303 is further configured to: determining a main curve of the creep according to a parameter method or an isotherm method based on the high-temperature material database;
and determining a calculation mode of the damage degree of the creep to the key influence position based on the main curve of the creep.
Optionally, the model building module 304 is specifically configured to: determining the weight value of each influence factor according to the material information and the environment information of the heating surface pipe;
based on the relation rule, the weight value of each influence factor and a predetermined neural network algorithm, establishing an initialization health degree calculation model of the key position of the heating surface management;
and obtaining the target health degree calculation model based on the initialized health degree calculation model.
Optionally, the model building module 304 is further configured to: determining detection data and detection result data of each historical detection from the operation and maintenance historical data;
determining a training sample library of the health calculation model based on the historical detection data; the training sample library comprises sample data and sample labels;
when the initialized health degree calculation model does not meet the preset condition, one sample is selected from the sample data to serve as a current sample, and training is conducted on the initialized health degree calculation model based on the current sample until the initialized health degree calculation model meets the preset condition, and the target health degree calculation model is obtained.
Optionally, the model building module 304 is further configured to: acquiring detection data of a key influence position of a heating surface pipe at the current moment;
inputting the detection data into the target health degree calculation model to obtain the health degree of the key influence position corresponding to the detection data;
the remaining life of the heated surface tube is determined based on the health of the critical impact location.
The heating surface tube health degree calculating device provided by the embodiment of the invention can execute the heating surface tube health degree calculating method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the executing method. Reference is made to the description of any method embodiment of the invention for details not described in this embodiment.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and referring to fig. 4, a schematic structural diagram of an electronic device 12 suitable for implementing the electronic device according to the embodiment of the present invention is shown. The electronic device shown in fig. 4 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments of the invention. Components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, an electronic device memory 28, a bus 18 that connects the different electronic device components, including the electronic device memory 28 and the processing unit 16.
Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
The electronic device 12 typically includes a variety of electronic device readable media. Such media can be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The electronic device memory 28 may include computer-readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile electronic device storage media. By way of example only, storage electronics 34 may be used to read from or write to a non-removable, non-volatile magnetic media (not shown in FIG. 4, commonly referred to as a "hard disk drive"). Although not shown in fig. 4, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating electronic device, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the electronic device 12, and/or any devices (e.g., network card, modem, etc.) that enable the electronic device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. In the electronic device 12 of the present embodiment, the display 24 is not provided as a separate body but is embedded in the mirror surface, and the display surface of the display 24 and the mirror surface are visually integrated when the display surface of the display 24 is not displayed. Also, the electronic device 12 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through a network adapter 20. As shown in fig. 4, the network adapter 20 communicates with other modules of the electronic device 12 over the bus 18. It should be appreciated that although not shown in fig. 4, other hardware and/or software modules may be used in connection with electronic device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID electronics, tape drives, data backup storage electronics, and the like.
The processing unit 16 executes programs stored in the electronic device memory 28 to perform various functional applications and heating surface management health calculations, for example, to implement a heating surface management health calculation method provided by an embodiment of the present invention: acquiring operation and maintenance historical data of a power plant boiler in a high-temperature material database; determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data; determining a relationship rule of each influence factor and material accumulation damage based on the key influence position of the heating surface pipe and each influence factor; and establishing a target health degree calculation model of the key position of the heating surface management based on the relation rule.
The embodiment of the invention provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements a heating surface management health degree calculating method provided by all the embodiments of the invention: acquiring operation and maintenance historical data of a power plant boiler in a high-temperature material database; determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data; determining a relationship rule of each influence factor and material accumulation damage based on the key influence position of the heating surface pipe and each influence factor; and establishing a target health degree calculation model of the key position of the heating surface management based on the relation rule. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic device, apparatus, or device of electronic, magnetic, optical, electromagnetic, infrared, or semiconductor, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution electronic device, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution electronic device, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.

Claims (10)

1. The heating surface tube health degree calculating method is characterized by comprising the following steps of:
acquiring operation and maintenance historical data of a power plant boiler in a high-temperature material database;
determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data;
determining a relationship rule of each influence factor and material accumulation damage based on the key influence position of the heating surface pipe and each influence factor;
and establishing a target health degree calculation model of the key position of the heating surface management based on the relation rule.
2. The method of claim 1, wherein determining a relationship rule for each influencing factor and material accumulation damage based on the key influencing location of the heated surface tube and each influencing factor comprises:
Determining a calculation mode of the damage degree of each influence factor to the key influence position based on the operation and maintenance historical data;
and determining the relation rule of each influence factor and the accumulated damage of the material based on the calculation mode of each damage degree and the high-temperature material database.
3. The method of claim 2, wherein determining a relationship rule between each influencing factor and the cumulative damage of the material based on the calculation mode of each damage degree and the high-temperature material database comprises:
determining damage constants corresponding to the damage degrees according to the material information and the environment information of the heating surface pipe;
the relation rule of each influence factor and the accumulated damage of the material is determined based on the damage constant corresponding to each damage degree, and is as follows: the strength index of the heated surface pipe is equal to the sum of products of damage constants and damage degrees of various influencing factors, wherein the hardness index of the pipeline is equal to the sum of products of damage constants and damage degrees of various influencing factors.
4. The method of claim 2, wherein the influencing factors include at least creep, determining a manner of calculating a degree of damage to the critical influencing location by each influencing factor based on the operation and maintenance history data, comprising:
Determining a main curve of the creep according to a parameter method or an isotherm method based on the high-temperature material database;
and determining a calculation mode of the damage degree of the creep to the key influence position based on the main curve of the creep.
5. The method of claim 1, wherein building a target health calculation model of a heating surface management key location based on the relationship law comprises:
determining the weight value of each influence factor according to the material information and the environment information of the heating surface pipe;
based on the relation rule, the weight value of each influence factor and a predetermined neural network algorithm, establishing an initialization health degree calculation model of the key position of the heating surface management;
and obtaining the target health degree calculation model based on the initialized health degree calculation model.
6. The method of claim 5, wherein deriving the target health calculation model based on the initialized health calculation model comprises:
determining detection data and detection result data of each historical detection from the operation and maintenance historical data;
determining a training sample library of the health calculation model based on the historical detection data; the training sample library comprises sample data and sample labels;
When the initialized health degree calculation model does not meet the preset condition, one sample is selected from the sample data to serve as a current sample, and training is conducted on the initialized health degree calculation model based on the current sample until the initialized health degree calculation model meets the preset condition, and the target health degree calculation model is obtained.
7. The method according to claim 1, wherein the method further comprises:
acquiring detection data of a key influence position of a heating surface pipe at the current moment;
inputting the detection data into the target health degree calculation model to obtain the health degree of the key influence position corresponding to the detection data;
the remaining life of the heated surface tube is determined based on the health of the critical impact location.
8. A heating surface tube health degree calculating device, comprising:
the data acquisition module is used for acquiring operation and maintenance historical data of the power plant boiler in the high-temperature material database;
the first determining module is used for determining key influence positions and various influence factors of heating surface pipes of the boiler based on the operation and maintenance historical data;
the second determining module is used for determining the relation rule of each influence factor and the material accumulation damage based on the key influence position of the heating surface pipe and each influence factor;
And the model building module is used for building a target health degree calculation model of the key position of the heating surface management based on the relation rule.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the heating surface management fitness computing method of any one of claims 1 to 7 when the program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when executed by a processor, implements the heating surface management fitness calculating method according to any one of claims 1 to 7.
CN202311461754.2A 2023-11-06 2023-11-06 Heating surface tube health degree calculation method and device, electronic equipment and storage medium Pending CN117390811A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311461754.2A CN117390811A (en) 2023-11-06 2023-11-06 Heating surface tube health degree calculation method and device, electronic equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311461754.2A CN117390811A (en) 2023-11-06 2023-11-06 Heating surface tube health degree calculation method and device, electronic equipment and storage medium

Publications (1)

Publication Number Publication Date
CN117390811A true CN117390811A (en) 2024-01-12

Family

ID=89471808

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202311461754.2A Pending CN117390811A (en) 2023-11-06 2023-11-06 Heating surface tube health degree calculation method and device, electronic equipment and storage medium

Country Status (1)

Country Link
CN (1) CN117390811A (en)

Similar Documents

Publication Publication Date Title
Barbosa et al. Fatigue life prediction of metallic materials considering mean stress effects by means of an artificial neural network
Hu et al. Remaining useful life model and assessment of mechanical products: a brief review and a note on the state space model method
Lu et al. Data-driven dynamic predictive maintenance for a manufacturing system with quality deterioration and online sensors
CN107291944A (en) Boiler main wants the advanced diagnostic analysis method of heating surface and system
Yeter et al. Life-extension classification of offshore wind assets using unsupervised machine learning
Garg et al. A two-phase approach for reliability and maintainability analysis of an industrial system
WO2007038533A2 (en) System to predict corrosion and scaling, program product, and related methods
Prakash et al. Toward a big data-based approach: A review on degradation models for prognosis of critical infrastructure
JP7085067B2 (en) Corrosion generation prediction model under heat insulating material and plant maintenance support device
CN115600739A (en) Boiler superheater and reheater oxide skin prediction method and system
CN103729534A (en) Particulate fouling experimental device, prediction method and prediction system for arc-tube heat exchanger
Li et al. A method of probabilistic analysis for steel pipeline with correlated corrosion defects
CN117390811A (en) Heating surface tube health degree calculation method and device, electronic equipment and storage medium
Hazra et al. Estimation of flow-accelerated corrosion rate in nuclear piping system
WO2013169241A1 (en) Predictive corrosion coupons from data mining
Wang et al. Neural network-assisted probabilistic creep-fatigue assessment of hydrogenation reactor with physics-based surrogate model
RU2692438C1 (en) Method of evaluation of strength and determination of service life of drums and header of boiler
Al Rashdan et al. Development of a Technology Roadmap for Online Monitoring of Nuclear Power Plants
KR102545240B1 (en) Apparatus and method for predicting of the tube wall thinning
Zhou et al. Quantification of value of information associated with optimal observation actions within partially observable Markov decision processes
Rouse et al. A neural network approach for determining spatial and geometry dependent Green's functions for thermal stress approximation in power plant header components
Kim et al. Uncertainty analysis of data-based models for estimating collapse moments of wall-thinned pipe bends and elbows
JP2002108412A (en) Method and system for constructing model
Mishra et al. Evaluation of Implicit Reliability Level Associated with Fatigue Design Criteria of Nuclear Class-1 Piping
Riswanto et al. Maintenance cost optimization on reliability centered maintenance based on failure rate on flash gas compression system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination