WO2024103685A1

WO2024103685A1 - Multi-dimensional and multi-field inversion method for steam turbine rotor, and electronic device and storage medium

Info

Publication number: WO2024103685A1
Application number: PCT/CN2023/097024
Authority: WO
Inventors: 张亦宁; 初世明; 张春秀; 王鑫雨; 卢洪涛; 郑宏伟; 尉坤; 程学亮; 李洪亮; 邵崇晖
Original assignee: 哈电发电设备国家工程研究中心有限公司; 哈尔滨汽轮机厂有限责任公司
Priority date: 2022-11-17
Filing date: 2023-05-30
Publication date: 2024-05-23
Also published as: CN115758726A

Abstract

The present invention belongs to the technical field of inversion of steam turbine rotors. Provided are a multi-dimensional and multi-field inversion method for a steam turbine rotor, and an electronic device and a storage medium. The method comprises: S1, calculating a transient temperature field change and a transient stress field change of a rotor within one simulation start and stop period; S2, splitting a transient temperature field change result and a transient stress field change result into data files of several time layers; S3, selecting, as labels, parameters in the data file of each time layer that meet specific features; S4, acquiring parameter values of different labels; S5, calculating a similarity measure value between the current running state of the rotor and a transient feature of the data file of each time layer; and S6, selecting the data file of the time layer with the highest similarity, and for each point in the entire domain of the rotor, performing weighted summation using the similarity measure value as a weight, so as to obtain a parameter value on each node in a temperature field and a stress field. By means of the present invention, the technical problem in the prior art of it being impossible to monitor internal details of a running steam turbine rotor is solved.

Description

A steam turbine rotor multi-dimensional multi-field inversion method, electronic equipment and storage medium

Technical Field

The present application relates to a steam turbine rotor monitoring method, and more particularly to a steam turbine rotor multi-dimensional multi-field inversion method, electronic equipment and storage medium, belonging to the technical field of steam turbine rotor inversion.

Background technique

The turbine rotor is a rotating body supported by bearings in the turbine. It is a typical rotating component. Monitoring and converting its internal temperature and stress during operation is of great significance for evaluating its operating status. It is difficult to directly arrange temperature and stress sensors on the rotor body. For real-time monitoring of the operating status of the turbine rotor, the turbine rotor is currently mainly taken as a whole to analyze its average volume temperature and stress. There is still a lack of real-time monitoring and inversion analysis of the temperature field and stress field of the turbine rotor.

technical problem

A brief overview of the present invention is provided below in order to provide a basic understanding of certain aspects of the present invention. It should be understood that this overview is not an exhaustive overview of the present invention. It is not intended to identify key or important parts of the present invention, nor is it intended to limit the scope of the present invention. Its purpose is merely to present certain concepts in a simplified form as a prelude to a more detailed description discussed later.

Technical Solutions

In view of this, in order to solve the technical problem that the internal details of the running steam turbine rotor cannot be monitored in the prior art, the present invention provides a steam turbine rotor multi-dimensional multi-field inversion method, electronic equipment and storage medium.

Solution 1: A multi-dimensional and multi-field inversion method for a steam turbine rotor, comprising the following steps:

S1. Calculate the transient temperature field and stress field changes of the rotor during a simulated start-stop cycle;

S2. Split the transient temperature field and stress field change results of the rotor in a simulated start-stop cycle into data files of several time layers;

S3. Select parameters that meet specific characteristics in the data file of each time layer as labels, and calibrate the labels with the parameters;

S4. Get parameter values of different tags;

S5. Calculate the similarity measure between the current operating state of the rotor and the transient characteristics of each time layer data file;

S6. Select the time layer data file with the highest similarity, and perform weighted summation for each point in the entire rotor domain using the similarity measurement value as the weight to obtain the parameter value at each node in the temperature field and stress field.

Preferably, S1 is specifically:

S11. Mesh the rotor in the R-Z coordinate system;

S12. The parameters in the startup curve are used as boundary conditions for transient calculation. The startup curve includes transient changes in the temperature, pressure and flow of main steam and reheat steam;

S13. Perform steady-state calculation under rated conditions, and use the steady-state temperature field and stress field calculation results under rated conditions as initial conditions to calculate the temperature field and stress field after the rotor is cooled for H hours as initial conditions for transient calculation of the startup process;

S14. Use the finite element method to carry out transient calculation of the temperature field and stress field inside the rotor during the startup process;

S15. Output the transient process results of temperature field and stress field.

Preferably, the parameters meeting the specific characteristics include: thermal parameters introduced by the DCS, the initial state of the transient process, and the time TD from the initial state to the current moment.

Preferably, S4 is specifically:

The parameter values of the thermal parameter tag introduced by DCS include:

The temperature of steam inlet area R6 is T1 and the pressure is P1;

The connecting regions R4 and R4' have a temperature T2 and a pressure T2;

The exhaust area R2 has a temperature T3 and a pressure T3;

The parameter values of the initial state tag of the transient process include:

When the speed N0 at the initial moment is below 100r/min, the unit is in a cold state and FI=1;

When the speed N0 at the initial moment is 3000r/min, the unit is in hot state FI=2;

When the speed N0 at the initial moment is between 100r/min-3000r/min, the speed change within the DertT time period is collected. If the speed increases within the DertT time period, the unit is judged to be in a cold state FI=1, otherwise it is judged to be in a hot state FI=2;

The parameter value of the TD label of the time elapsed from the initial state to the current moment includes: the difference between the total simulation time of the current time layer and the time of the start/stop moment.

Preferably, S5 is specifically:

S51. The introduced measurement point signal and the tag signal obtained through preliminary analysis are combined to obtain a combination of all tag parameters at the current moment;

S52. For each tag parameter, set a weight according to the proportion of the temperature field parameter that affects it;

S53. Calculate similarity measure value

;

In the formula is the similarity measure between the current rotor state and the states marked by the time layer (n); is the value of the i-th measured label parameter; is the value of the i-th label parameter in the time layer (n); is the weight of the i-th label parameter.

Preferably, S6 specifically includes:

;

In the formula is the temperature value of the jth node in the entire rotor domain; N is the number of time layers involved in the temperature field inversion; is the temperature value of the jth node on the time layer (n); is the stress value of the jth node in the entire rotor domain; is the stress value of the jth node on the time layer (n).

Solution 2: An electronic device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of a multi-dimensional and multi-field inversion method for a steam turbine rotor described in Solution 1 are implemented.

Solution three: A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements a multi-dimensional and multi-field inversion method for a steam turbine rotor as described in Solution one.

Beneficial Effects

The beneficial effects of the present invention are as follows: In the existing rotor monitoring technology, the real-time monitoring of one-dimensional radial temperature and stress on different segmented sections of the rotor is mainly focused, and there is a lack of real-time monitoring technology for the two-dimensional global temperature field and stress field of the rotor; the inversion solution of the two-dimensional global temperature field and stress field is limited by computer computing efficiency and mainly relies on non-real-time calculation.

The present invention can be installed on-site at a power plant to invert the temperature field and stress field of the entire two-dimensional rotor in real time. The monitoring inversion is real-time, and the inversion and display area covers the entire area, so that users can observe the rotor operation status conveniently and intuitively. It is beneficial for power plant operators to establish the concept of the changing laws of the temperature field and stress field of the entire rotor during the start-up, operation, shutdown, and load change of the steam turbine. It can guide operation and maintenance personnel to fully understand the temperature and stress levels of various parts of the rotor under different working conditions, deepen their understanding of the temperature and stress state of the rotor during operation, and promptly discover abnormal states of the temperature field and stress field of the rotor during operation. It solves the technical problem in the prior art that the internal details of the steam turbine rotor in operation cannot be monitored.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

FIG1 is a schematic flow chart of a multi-dimensional and multi-field inversion method for a steam turbine rotor;

FIG2 is a schematic diagram of the structure of a multi-dimensional and multi-field monitoring system for a steam turbine rotor;

FIG3 is a schematic diagram of an example rotor structure and boundary conditions;

FIG4 is a schematic diagram of an example rotor temperature field inversion result;

FIG. 5 is a schematic diagram showing the display effect of an example rotor cloud diagram on a UI device.

Embodiments of the present invention

In order to make the technical solutions and advantages in the embodiments of the present application more clearly understood, the exemplary embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than an exhaustive list of all the embodiments. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

Embodiment 1, referring to FIG. 1-FIG. 5, this embodiment is described. A multi-dimensional and multi-field inversion method for a steam turbine rotor comprises a signal collector for collecting real-time DCS signals of a power plant DCS system, a server for multi-dimensional and multi-field monitoring of a rotor, and a UI interactive device for displaying a monitored two-dimensional temperature field and stress field cloud map of the rotor. The signal collector, the server, and the UI interactive device are connected in sequence. The real-time DCS signal mainly comprises steam pressure and temperature signals before and after the steam bypass rotor, and a rotor speed signal. A multi-dimensional and multi-field inversion method for a steam turbine rotor comprises the following steps:

S11. Mesh the rotor in the R-Z coordinate system;

Specifically, the startup curve is given by the turbine design unit;

S13. Perform steady-state calculation under rated conditions, and use the calculation results of the steady-state temperature field and stress field under rated conditions as initial conditions, calculate the temperature field and stress field after the rotor has cooled for H hours, as the initial conditions for transient calculation during the startup process, calculate the temperature field and stress field after the rotor has cooled for H hours, as the initial conditions for transient calculation during the startup process;

For example, H=72 hours means cold start; H=10 hours means warm start; H=6 hours means hot start; H=2 hours means extremely hot start;

S14. Based on the initial conditions and boundary conditions determined in the above steps, the finite element method is used to carry out transient process calculations of the temperature field and stress field inside the rotor during the startup process;

The starting modes that need to be calculated include cold start, warm start, hot start, and extremely hot start. At least one of the above four starting modes is required.

For example, the finite element calculation result output file of the transient temperature field is temperature.fem, which is split into 1000 time layer data files t_timestep1.data-t_timestep1000.data at different times.

S3. Select parameters that meet specific characteristics in the data file of each time layer as labels, and calibrate the labels with parameters; the parameters that meet specific characteristics include: thermal parameters introduced by DCS, the initial state of the transient process, and the time TD from the initial state to the current moment.

S4. Obtain parameter values of different tags; the obtained parameter values are transient characteristics of the data file of this time layer;

The parameter values of the thermal parameter tag introduced by DCS include:

The temperature of steam inlet area R6 is T1 and the pressure is P1;

The connecting regions R4 and R4' have a temperature T2 and a pressure T2;

The exhaust area R2 has a temperature T3 and a pressure T3;

The positions of each area on the rotor are shown in Figure 3. For a conventional rotor without connected areas, the thermal parameters of the steam inlet and exhaust areas are mainly considered, and the parameters of the connected area do not need to be considered.

As the boundary conditions of transient finite element calculations, the thermal parameters on the boundary are constantly changing with time. Examples of boundary conditions that change with time are shown in Table 1 Boundary Condition Data Table, which is stored in the boundary condition file.

Table 1 Boundary condition data table

The output results of the finite element calculation are also arranged in time series, the time elapsed from the initial moment to each moment in the time series, as shown in Table 2 Time Series Data Table, and stored in the time series file.

Table 2 Time series data table

Usually, the time intervals between parameter changes in the boundary condition file are relatively large, so it is sufficient to clearly describe the changes in the external input parameters. For example, the number of boundary condition changes in the example is 34.

The time interval of parameter changes in the time series file is the time step of the finite element calculation. Usually, in order to balance the calculation efficiency and calculation accuracy, the finite element calculation is performed by variable time step. In order to ensure the calculation efficiency, the time step needs to be set as large as possible while meeting the convergence conditions. At the same time, in order to ensure the convergence of transient finite element calculation in the time dimension, the time step cannot be set too large, and the time step needs to be set smaller when the external parameters change drastically. This leads to the number of time layers in the time series file being far more than the descriptive settings in the boundary condition file. In the example, the number of time layers for transient finite element calculation is 1000. In order to match the two, it is necessary to use interpolation methods, such as linear difference methods, to complete the boundary conditions on each time layer label.

The parameter values of the initial state tag of the transient process include:

The tag parameter FI is calibrated according to whether the current time layer is the startup process or the shutdown process. During the startup process, the initial state of the unit is cold FI=1; during the shutdown process, the initial state of the unit is hot FI=2. TD is calculated by taking the difference between the total simulation time of the current time layer and the time of the start (stop) moment, and calibrated in the tag.

The initial state of the transient process is determined by the speed N0 at the initial moment:

S5. Calculate the similarity measure between the current operating state of the rotor and the transient characteristics of each time layer data file in the actual operation of the system;

S51. The introduced T1, P1, T2, P2, T3 and P3 measurement point signals are combined with the FI and TD tag signals obtained through preliminary analysis to obtain a combination of all tag parameters at the current moment;

Each tag parameter needs to have a weight set to characterize the impact of a single parameter on the overall situation. An example of a set of tag parameters is listed in Table 3. The weight of the FI parameter needs to be set larger to distinguish whether the current unit action is startup or shutdown.

The label weight is used to characterize the impact of a single parameter on the overall situation. The weight is based on 1.0 and can be adjusted by the user according to the actual situation. For example, it is analyzed that the current unit action, whether it is startup or shutdown, has a greater impact on the transient characteristics of the current time layer, so the weight of the FI parameter needs to be set larger, and the weight is adjusted to 100.0; the analysis shows that the current experience time TD and the temperature and pressure of each section of the rotor inlet and exhaust steam T1, P1, T2, P2, T3, P3 have the same impact on the transient state of the rotor's temperature field and stress field, so the weights of the above parameters are all set to 1.0.

Table 3 Label parameter weight table

S53. Calculate similarity measure value

;

S6. According to the analysis results of the similarity measure, different time layers are sorted in descending order of similarity measure. The time layer data file with the highest similarity is selected, and for each point in the entire rotor domain, the similarity measure value is used as the weight, and a weighted sum is performed to obtain the parameter value at each node in the temperature field and stress field.

;

In the formula is the temperature value of the jth node in the entire rotor domain; N is the number of time layers involved in the temperature field inversion; is the temperature value of the jth node on the time layer (n); is the stress value of the jth node in the entire rotor domain; is the stress value of the jth node on the time layer (n). The temperature field calculation results of an example are shown in Figure 4.

Specifically, the parameter value at each node in the temperature field and the stress field is plotted as a cloud map, and the cloud map can be displayed on a UI interactive device, as shown in FIG5 .

Embodiment 2: The computer device of the present invention may be a device including a processor and a memory, such as a single chip microcomputer including a central processing unit. Furthermore, the processor is used to implement the steps of the above-mentioned recommendation method based on CREO software that can modify the recommendation data driven by the relationship when executing the computer program stored in the memory.

The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

Embodiment 3, Computer-readable storage medium embodiment

The computer-readable storage medium of the present invention can be any form of storage medium that can be read by a processor of a computer device, including but not limited to non-volatile memory, volatile memory, ferroelectric memory, etc. A computer program is stored on the computer-readable storage medium. When the processor of the computer device reads and executes the computer program stored in the memory, the steps of the above-mentioned modeling method of modifiable relationship-driven modeling data based on CREO software can be implemented.

The computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer readable media do not include electric carrier signals and telecommunication signals.

Although the present invention has been described according to a limited number of embodiments, it will be apparent to those skilled in the art, with the benefit of the above description, that other embodiments may be envisioned within the scope of the invention thus described. In addition, it should be noted that the language used in this specification is selected primarily for readability and didactic purposes, rather than for explaining or defining the subject matter of the present invention. Therefore, many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the appended claims. The disclosure of the present invention is illustrative, not restrictive, with respect to the scope of the present invention, which is defined by the appended claims.

Claims

A steam turbine rotor multi-dimensional multi-field inversion method, characterized by comprising the following steps:

S1. Calculate the transient temperature field and stress field changes of the rotor during a simulated start-stop cycle;

S2. Split the transient temperature field and stress field change results of the rotor in a simulated start-stop cycle into data files of several time layers;

S3. Select parameters that meet specific characteristics in the data file of each time layer as labels, and calibrate the labels with the parameters;

S4. Get parameter values of different tags;

S5. Calculate the similarity measure between the current operating state of the rotor and the transient characteristics of each time layer data file;

S6. Select the time layer data file with the highest similarity, and perform weighted summation for each point in the entire rotor domain using the similarity measurement value as the weight to obtain the parameter value at each node in the temperature field and stress field.
The multi-dimensional and multi-field inversion method for a steam turbine rotor according to claim 1 is characterized in that S1 is specifically:

S11. Mesh the rotor in the R-Z coordinate system;

S12. The parameters in the startup curve are used as boundary conditions for transient calculation. The startup curve includes transient changes in the temperature, pressure and flow of main steam and reheat steam;

S13. Perform steady-state calculation under rated conditions, and use the steady-state temperature field and stress field calculation results under rated conditions as initial conditions to calculate the temperature field and stress field after the rotor is cooled for H hours as initial conditions for transient calculation of the startup process;

S14. Use the finite element method to carry out transient calculation of the temperature field and stress field inside the rotor during the startup process;

S15. Output the transient process results of temperature field and stress field.
According to claim 2, a multi-dimensional and multi-field inversion method for a steam turbine rotor is characterized in that the parameters meeting specific characteristics include: thermal parameters introduced by DCS, the initial state of the transient process, and the time TD from the initial state to the current moment.
The multi-dimensional and multi-field inversion method for a steam turbine rotor according to claim 3 is characterized in that S4 specifically comprises:

The parameter values of the thermal parameter tag introduced by DCS include:

The temperature of steam inlet area R6 is T1 and the pressure is P1;

The connecting regions R4 and R4' have a temperature T2 and a pressure T2;

The exhaust area R2 has a temperature T3 and a pressure T3;

The parameter values of the initial state tag of the transient process include:

When the speed N0 at the initial moment is below 100r/min, the unit is in a cold state and FI=1;

When the speed N0 at the initial moment is 3000r/min, the unit is in hot state FI=2;

When the speed N0 at the initial moment is between 100r/min-3000r/min, the speed change within the DertT time period is collected. If the speed increases within the DertT time period, the unit is judged to be in a cold state FI=1, otherwise it is judged to be in a hot state FI=2;

The parameter value of the TD label of the time elapsed from the initial state to the current moment includes: the difference between the total simulation time of the current time layer and the time of the start/stop moment.
The multi-dimensional and multi-field inversion method for a steam turbine rotor according to claim 4 is characterized in that S5 specifically comprises:

S51. The introduced measurement point signal and the tag signal obtained through preliminary analysis are combined to obtain a combination of all tag parameters at the current moment;

S52. For each tag parameter, set a weight according to the proportion of the temperature field parameter that affects it;

S53. Calculate similarity measure value

;

In the formula is the similarity measure between the current rotor state and the states marked by the time layer (n); is the value of the i-th measured label parameter; is the value of the i-th label parameter in the time layer (n); is the weight of the i-th label parameter.
The multi-dimensional and multi-field inversion method for a steam turbine rotor according to claim 5 is characterized in that S6 specifically comprises:

;

In the formula is the temperature value of the jth node in the entire rotor domain; N is the number of time layers involved in the temperature field inversion; is the temperature value of the jth node on the time layer (n); is the stress value of the jth node in the entire rotor domain; is the stress value of the jth node on the time layer (n).
An electronic device, characterized in that it includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of a multi-dimensional and multi-field inversion method for a steam turbine rotor as described in any one of claims 1-6 when executing the computer program.
A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, a multi-dimensional and multi-field inversion method for a steam turbine rotor as described in any one of claims 1 to 6 is implemented.