A method and device for monitoring a steam turbine component, an electronic device and a storage medium

Abstract

The application discloses a kind of monitoring method, device, electronic equipment and storage medium of steam turbine component.It is determined that the planned stress level of target component of target steam turbine under current planning working condition based on the planned variable load characteristic parameter of target steam turbine under current planning working condition, through pre-constructed mapping relationship;Safety condition is determined that target steam turbine executes current planning working condition according to planned stress level;Actual stress level of target component of target steam turbine is determined based on actual variable load characteristic parameter and actual main steam temperature parameter after target steam turbine executes current planning working condition, through pre-constructed mapping relationship;According to actual stress level, the cumulative life consumption of target component is determined, and life consumption monitoring is realized for target component based on cumulative life consumption.The technical scheme of the present application realizes the fine control of high-temperature component stress and life, and improves the safety monitoring capability of high-temperature component.

Description

Technical Field

[0001] This invention relates to the field of steam turbine technology, and in particular to a method, device, electronic equipment, and storage medium for monitoring steam turbine components. Background Technology

[0002] With the increasing proportion of new energy grid connection and the growing demand for grid peak shaving, steam turbine generator sets need to frequently and rapidly change loads within a wide load range. For units operating under sliding pressure, the main steam pressure and the heat transfer coefficient of high-temperature components change to varying degrees under rapid load change conditions. The main steam temperature also fluctuates due to lags in boiler combustion, feedwater, and steam temperature control. At the same time, the steam temperature between different stages of the turbine changes significantly, and there is a lag between the steam temperature changes between different stages and the metal temperature response of high-temperature components. This results in unsteady temperature gradients within high-temperature components and between different components, subjecting high-temperature components to frequent alternating thermal stresses. This causes low-cycle fatigue life damage to high-temperature components and threatens the safe operation of multiple components such as the turbine rotor, cylinder, and blades.

[0003] In existing technologies, various methods and systems have been proposed to address the structural strength and lifespan of high-temperature components in steam turbines, encompassing analysis, calculation, design optimization, and operational monitoring. However, these methods primarily focus on the stress and lifespan reliability of high-temperature components under transient start-up and shutdown conditions such as cold start, warm start, hot start, extremely hot start, and shutdown. Under current power grid requirements, the stress and lifespan control of high-temperature components is rudimentary, resulting in insufficient safety monitoring of these components. Summary of the Invention

[0004] This invention provides a method, device, electronic equipment, and storage medium for monitoring turbine components, so as to achieve refined control over the stress and lifespan of high-temperature components and improve the safety monitoring capability of high-temperature components.

[0005] According to one aspect of the present invention, a method for monitoring steam turbine components is provided, the method comprising:

[0006] Based on the planned variable load characteristic parameters of the target steam turbine under the current planned operating conditions, the planned stress level of the target component of the target steam turbine under the current planned operating conditions is determined by pre-constructing a mapping relationship;

[0007] Determine the safety status of the target steam turbine performing the current planned operating condition based on the planned stress level;

[0008] Based on the actual variable load characteristic parameters and actual main steam temperature parameters of the target steam turbine after executing the current planned operating condition, the actual stress level of the target component of the target steam turbine is determined through the pre-constructed mapping relationship.

[0009] The cumulative life loss of the target component is determined based on the actual stress level, and life loss monitoring is implemented for the target component based on the cumulative life loss.

[0010] According to another aspect of the present invention, a monitoring device for a steam turbine component is provided, the device comprising:

[0011] The planned stress level determination module is used to determine the planned stress level of the target component of the target steam turbine under the current planned operating conditions based on the planned variable load characteristic parameters of the target steam turbine under the current planned operating conditions, through a pre-built mapping relationship;

[0012] The safety monitoring module is used to determine the safety status of the target steam turbine performing the current planned operating condition based on the planned stress level.

[0013] The actual stress level determination module is used to determine the actual stress level of the target component of the target steam turbine based on the actual variable load characteristic parameters and actual main steam temperature parameters after the target steam turbine performs the current planned operating condition, through the pre-built mapping relationship.

[0014] The life monitoring module is used to determine the cumulative life loss of the target component based on the actual stress level, and to monitor the life loss of the target component based on the cumulative life loss.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the monitoring method for turbine components according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the monitoring method for turbine components according to any embodiment of the present invention.

[0020] The technical solution of this invention determines the planned stress level of the target component of the target steam turbine under the current planned operating conditions by using the planned variable load characteristic parameters of the target steam turbine under the current planned operating conditions and by pre-constructing a mapping relationship; determines the safety status of the target steam turbine in executing the current planned operating conditions based on the planned stress level; determines the actual stress level of the target component of the target steam turbine based on the actual variable load characteristic parameters and the actual main steam temperature parameters after the target steam turbine executes the current planned operating conditions, by pre-constructing a mapping relationship; determines the cumulative life loss of the target component based on the actual stress level, and monitors the life loss of the target component based on the cumulative life loss. This invention employs a closed-loop monitoring method based on precise variable load characteristic parameters to estimate stress, achieving planned load safety prediction, actual operating data feedback, and cumulative life loss monitoring. This solves the problem of insufficient safety monitoring of high-temperature components due to the coarse stress and life control of existing technologies under current power grid requirements, thereby achieving refined control of the stress and life of high-temperature components and improving the safety monitoring capability of high-temperature components.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart illustrating a monitoring method for a steam turbine component provided in Embodiment 1 of the present invention;

[0024] Figure 2 This is a schematic diagram of the structure of a monitoring device for a steam turbine component provided in Embodiment 2 of the present invention;

[0025] Figure 3 This is a schematic diagram of the structure of an electronic device for implementing the monitoring method for turbine components according to an embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such processes, methods, products or devices.

[0028] Example 1

[0029] Figure 1 This is a flowchart of a monitoring method for steam turbine components provided in Embodiment 1 of the present invention. This embodiment is applicable to the safety monitoring of high-temperature components of a steam turbine unit. The method can be executed by a monitoring device for the steam turbine components, which can be implemented in hardware and / or software and can be configured in a server. Figure 1 As shown, the method includes:

[0030] S110. Based on the planned variable load characteristic parameters of the target turbine under the current planned operating conditions, the planned stress level of the target component of the target turbine under the current planned operating conditions is determined by pre-constructing a mapping relationship.

[0031] In this context, "target turbine" refers to a steam turbine generator set requiring component safety monitoring. "Current planned operating condition" refers to the planned operating condition for the target turbine at the current moment. "Planned variable load characteristic parameters" refer to parameters corresponding to the planned operating condition that represent load changes; in this embodiment, these parameters may include the load change range and the load change rate. "Pre-built mapping relationship" can be a mapping relationship between the load change range, the load change rate, the main steam temperature, and the stress level. "Target component" refers to high-temperature components on the target turbine. "Planned stress level" refers to the stress condition of the target component under the current planned operating condition.

[0032] This embodiment can determine the planned stress of the target component under the planned variable load characteristic parameters and the specified main steam temperature by pre-constructing the mapping relationship.

[0033] In one optional implementation, the planned load change characteristic parameters are obtained by: obtaining the current planned load curve of the target turbine; identifying each load change event from the current planned load curve, and extracting the planned load change characteristic parameters corresponding to each load change event; wherein, a load change event is defined as a monotonic change process from one steady-state load platform to another steady-state load platform, and the planned load change characteristic parameters include the planned load change range and the planned load change rate.

[0034] The current planned load curve can be obtained from the unit dispatching system or DCS (Distributed Control System), and it reflects the planned load data of the target turbine. The planned load change range can include characteristics such as the starting load, ending load, and load change amplitude within a single load change event. The planned load change rate can include characteristics such as the average load change rate and the maximum load change rate.

[0035] Accordingly, determining the planned stress level of the target component of the target turbine under the current planned operating conditions by pre-constructing mapping relationships may include: determining the planned stress level of the target component under each load change event by pre-constructing mapping relationships.

[0036] In this embodiment, the planned load change range, planned load change rate, and specified main steam temperature for each load change event can be used as inputs to pre-construct a mapping relationship to obtain the planned stress level of the target component under each load change event.

[0037] Optionally, the pre-built mapping relationship in this embodiment can be constructed in the following ways: by performing interpolation processing based on the pre-built thermo-coupling response database to establish the pre-built mapping relationship; or by using the response surface methodology to establish a regression model based on the pre-built thermo-coupling response database to obtain the pre-built mapping relationship; or by using a Kriging model, radial basis function model, or neural network model to establish a surrogate mapping based on the pre-built thermo-coupling response database to obtain the pre-built mapping relationship; or by using a simplified physical model based on the pre-built thermo-coupling response database to estimate the thermal stress level based on the temperature gradient characteristics caused by load changes to establish the pre-built mapping relationship.

[0038] This embodiment can utilize the thermo-mechanical coupling response database of the target component to establish a mapping relationship between load change range, load change rate, main steam temperature and stress level of weak parts.

[0039] Optionally, the pre-built thermo-mechanical coupling response database in this embodiment is constructed in the following way: obtaining the combination relationship between a specified load change range, a specified load change rate, and a specified main steam temperature; using finite element analysis to analyze the temperature distribution and stress distribution of the target components of the target turbine in each set of specified load change ranges, specified load change rates, and specified main steam temperatures; and associating and storing the specified load change ranges, specified load change rates, specified main steam temperatures, temperature distributions, and stress distributions to obtain the pre-built thermo-mechanical coupling response database.

[0040] The specified load variation range can include, for example, 5%-20%THA, 20%-40%THA, 40%-70%THA, 70%-100%THA, etc. The specified load variation rate can include, for example, 2%Pe / min, 3%Pe / min, 4%Pe / min, 5%Pe / min, or even increasing to 10%Pe / min, etc. The specified main steam temperature can be obtained based on the rated main steam temperature, and the specified main steam temperature can include, for example, rated main steam temperature minus 20℃, rated main steam temperature minus 10℃, rated main steam temperature, rated main steam temperature plus 10℃, and rated main steam temperature plus 20℃, etc.

[0041] This embodiment combines specified load change ranges, specified load change rates, and specified main steam temperatures sequentially and performs finite element analysis to calculate transient finite element temperature and stress fields. It determines the overall temperature and stress distribution of high-temperature components (such as turbine rotors and inner cylinders) under each combination of specified load change ranges, specified load change rates, and specified main steam temperatures, identifies the weak points in stress and lifespan of high-temperature components, and stores the characteristics of specified load change ranges, specified load change rates, temperature distributions, and stress distributions in a correlated manner to form a thermal-mechanical coupling response database for high-temperature components.

[0042] S120. Determine the safety status of the target steam turbine under the current planned operating conditions based on the planned stress level.

[0043] In one alternative implementation, determining the safety status of the target turbine under the current planned operating condition based on the planned stress level may include: comparing the planned stress level of the target component with a safety threshold under each load change event; wherein the safety threshold is constructed based on the yield strength of the target component material; determining that the target turbine can operate safely under the current planned operating condition if all planned stress levels are less than or equal to the safety threshold; and determining that the target turbine is in danger under the current planned operating condition if there is a planned stress level greater than the safety threshold.

[0044] In this embodiment, the planned stress level of each weak point of the target component under each load change event is used as... The safety threshold is expressed as... ,in, This represents the yield strength of the material at the operating temperature, where K is an empirical constant. If... If the safety criterion is met, it is determined that the target turbine can operate safely under the current planned operating conditions; if If the safety criteria are not met, it is determined that the weak point may pose a danger to the target turbine under the current planned operating conditions, and the system alarm indicates that the load change rate is too fast.

[0045] Furthermore, if all All meet If so, it can be determined that the target steam turbine can operate safely under the current planned operating conditions; if any one of them exists... satisfy If so, it can be determined that the target steam turbine is in danger under the current planned operating conditions.

[0046] S130. Based on the actual variable load characteristic parameters and actual main steam temperature parameters of the target turbine after the target turbine performs the current planned operating conditions, the actual stress level of the target components of the target turbine is determined by pre-constructing a mapping relationship.

[0047] In this embodiment, after the target steam turbine operates according to the current planned load curve, the actual operating data of the target steam turbine can be obtained through the unit's DCS system to obtain the actual load change range, actual load change rate, and actual main steam temperature. Furthermore, using pre-built mapping relationships, the actual stress level of the weak points of the target components is recalculated based on the actual load change range, actual load change rate, and actual main steam temperature.

[0048] S140. Determine the cumulative life loss of the target component based on the actual stress level, and monitor the life loss of the target component based on the cumulative life loss.

[0049] In one optional implementation, determining the cumulative life loss of the target component based on the actual stress level may include: querying the low-cycle fatigue crack initiation life curve corresponding to the target component material based on the actual stress level corresponding to each load change event, to obtain the low-cycle fatigue crack initiation life of the target component under each load change event; calculating the reciprocal of the low-cycle fatigue crack initiation life to obtain the low-cycle fatigue crack initiation life loss of the target component under each load change event; counting the number of cycles for each type of load change event; and accumulating the low-cycle fatigue crack initiation life loss of the target component under each load change event using the linear superposition rule of life loss based on the number of cycles for each type of load change event, to obtain the cumulative life loss of the target component.

[0050] In this embodiment, the low-cycle fatigue crack initiation life N of the target component during a single load change event can be determined based on the calculated actual stress level and the low-cycle fatigue crack initiation life curve of the target component material. The low-cycle fatigue crack initiation life loss d under variable load conditions can then be calculated: d = 1 / N.

[0051] Furthermore, different load change events under the current operating conditions can be classified, and the number of cycles for each type can be counted. The cumulative lifespan loss of high-temperature components can be accumulated using the Palmgren-Miner linear superposition rule to obtain the cumulative lifespan loss of the target component.

[0052] In one alternative implementation, monitoring the life loss of a target component based on cumulative life loss may include: generating a life loss warning for the target component when the cumulative life loss reaches a preset life loss threshold, so as to prompt maintenance or limit subsequent load changes.

[0053] This embodiment can estimate the number of load cycles within the lifespan based on cumulative lifespan loss, thereby enabling lifespan prediction of high-temperature components in steam turbines. This optimizes the service life of high-temperature components and greatly improves the economy and safety of the unit during frequent and rapid load changes.

[0054] The technical solution of this embodiment determines the planned stress level of the target component of the target turbine under the current planned operating conditions by using the planned variable load characteristic parameters of the target turbine under the current planned operating conditions through a pre-built mapping relationship; determines the safety status of the target turbine in executing the current planned operating conditions based on the planned stress level; determines the actual stress level of the target component of the target turbine based on the actual variable load characteristic parameters and the actual main steam temperature parameters after the target turbine executes the current planned operating conditions through a pre-built mapping relationship; determines the cumulative life loss of the target component based on the actual stress level, and monitors the life loss of the target component based on the cumulative life loss. This solution uses a closed-loop monitoring method based on precise variable load characteristic parameters to estimate stress, achieving planned load safety prediction, actual operation data feedback, and cumulative life loss monitoring. This solves the problem of insufficient safety monitoring of high-temperature components due to the coarse stress and life control of existing technologies under current power grid requirements, thus achieving refined control of the stress and life of high-temperature components and improving the safety monitoring capability of high-temperature components.

[0055] Example 2

[0056] Figure 2 This is a schematic diagram of a monitoring device for a steam turbine component provided in Embodiment 2 of the present invention. Figure 2As shown, the device includes: a planned stress level determination module 210, a safety condition monitoring module 220, an actual stress level determination module 230, and a life monitoring module 240. Wherein:

[0057] The planned stress level determination module 210 is used to determine the planned stress level of the target component of the target steam turbine under the current planned operating conditions based on the planned variable load characteristic parameters of the target steam turbine under the current planned operating conditions, by pre-constructing a mapping relationship;

[0058] Safety monitoring module 220 is used to determine the safety status of the target steam turbine performing the current planned operating condition based on the planned stress level;

[0059] The actual stress level determination module 230 is used to determine the actual stress level of the target component of the target steam turbine based on the actual variable load characteristic parameters and the actual main steam temperature parameters after the target steam turbine performs the current planned operating condition, through the pre-built mapping relationship.

[0060] The life monitoring module 240 is used to determine the cumulative life loss of the target component based on the actual stress level, and to monitor the life loss of the target component based on the cumulative life loss.

[0061] The technical solution of this embodiment determines the planned stress level of the target component of the target turbine under the current planned operating conditions by using the planned variable load characteristic parameters of the target turbine under the current planned operating conditions through a pre-built mapping relationship; determines the safety status of the target turbine in executing the current planned operating conditions based on the planned stress level; determines the actual stress level of the target component of the target turbine based on the actual variable load characteristic parameters and the actual main steam temperature parameters after the target turbine executes the current planned operating conditions through a pre-built mapping relationship; determines the cumulative life loss of the target component based on the actual stress level, and monitors the life loss of the target component based on the cumulative life loss. This solution uses a closed-loop monitoring method based on precise variable load characteristic parameters to estimate stress, achieving planned load safety prediction, actual operation data feedback, and cumulative life loss monitoring. This solves the problem of insufficient safety monitoring of high-temperature components due to the coarse stress and life control of existing technologies under current power grid requirements, thus achieving refined control of the stress and life of high-temperature components and improving the safety monitoring capability of high-temperature components.

[0062] Optionally, the planned variable load characteristic parameters are obtained in the following ways:

[0063] Obtain the current planned load curve of the target steam turbine;

[0064] Identify each load change event from the current planned load curve and extract the planned load change characteristic parameters corresponding to each load change event;

[0065] The load change event is defined as a monotonic change process from one steady-state load platform to another, and the planned load change characteristic parameters include the planned load change range and the planned load change rate.

[0066] Correspondingly, the planned stress level determination module 210 can be specifically used for:

[0067] The planned stress level of the target component under each load change event is determined by pre-constructing mapping relationships.

[0068] Optionally, the pre-built mapping relationship is a mapping relationship between load change range, load change rate, main steam temperature and stress level;

[0069] The pre-built mapping relationship is constructed in the following way:

[0070] Interpolation is performed based on a pre-built thermo-coupling response database to establish the pre-built mapping relationship; or

[0071] Based on a pre-built thermo-coupled response database, a regression model is established using the response surface methodology to obtain the pre-built mapping relationship; or

[0072] Based on a pre-built thermo-coupling response database, a surrogate mapping is established using a Kriging model, radial basis function model, or neural network model to obtain the pre-built mapping relationship; or

[0073] Based on a pre-built thermo-mechanical coupling response database, a simplified physical model is used to estimate the thermal stress level according to the temperature gradient characteristics caused by load changes, so as to establish the pre-built mapping relationship.

[0074] Optionally, the pre-built thermo-coupling response database is constructed in the following manner:

[0075] Obtain the combined relationship between a specified load change range, a specified load change rate, and a specified main steam temperature;

[0076] Finite element analysis was used to analyze the temperature and stress distribution of the target components of the target steam turbine under each specified load variation range, specified load rate, and specified main steam temperature.

[0077] The pre-built thermo-mechanical coupling response database is obtained by associating and storing the specified load change range, specified load change rate, specified main steam temperature, temperature distribution, and stress distribution.

[0078] Optional, the security monitoring module 220 can be used for:

[0079] The planned stress level of the target component under each load change event is compared with a safety threshold; wherein the safety threshold is constructed based on the yield strength of the target component material.

[0080] If all planned stress levels are less than or equal to the safety threshold, it is determined that the target steam turbine can operate safely under the current planned operating conditions;

[0081] If the planned stress level is greater than the safety threshold, the target turbine is determined to be in danger under the current planned operating condition.

[0082] Optional, the life monitoring module 240 can be used for:

[0083] Based on the actual stress level corresponding to each load change event, the low-cycle fatigue crack initiation life curve corresponding to the target component material is queried to obtain the low-cycle fatigue crack initiation life of the target component under each load change event.

[0084] The reciprocal of the low-cycle fatigue crack initiation life is used to obtain the low-cycle fatigue crack initiation life loss of the target component under each load change event.

[0085] Count the number of cycles for each type of load change event;

[0086] Based on the number of cycles for each type of load change event, the cumulative life loss of the target component under each load change event is accumulated using the linear superposition law of life loss, thus obtaining the cumulative life loss of the target component.

[0087] Optional, the life monitoring module 240 can also be used for:

[0088] When the cumulative lifespan loss reaches a preset lifespan threshold, a lifespan loss warning message is generated for the target component to prompt maintenance or limit subsequent load changes.

[0089] The turbine component monitoring device provided in this embodiment of the invention can execute the turbine component monitoring method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0090] Example 3

[0091] Figure 3 A schematic diagram of an electronic device 300 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers or various forms of mobile devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0092] like Figure 3 As shown, the electronic device 300 includes at least one processor 301 and a memory, such as a read-only memory (ROM) 302 or a random access memory (RAM) 303, communicatively connected to the at least one processor 301. The memory stores computer programs executable by the at least one processor. The processor 301 can perform various appropriate actions and processes based on the computer program stored in the ROM 302 or loaded into the RAM 303 from storage unit 308. The RAM 303 can also store various programs and data required for the operation of the electronic device 300. The processor 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0093] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0094] Processor 301 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 301 performs the various methods and processes described above, such as methods for monitoring turbine components.

[0095] In some embodiments, the method for monitoring turbine components may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by processor 301, one or more steps of the method for monitoring turbine components described above may be performed. Alternatively, in other embodiments, processor 301 may be configured to perform the method for monitoring turbine components by any other suitable means (e.g., by means of firmware).

[0096] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0097] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0098] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0099] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0100] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0101] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0102] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0103] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for monitoring steam turbine components, characterized in that, include: Based on the planned variable load characteristic parameters of the target steam turbine under the current planned operating conditions, the planned stress level of the target component of the target steam turbine under the current planned operating conditions is determined by pre-constructing a mapping relationship; Determine the safety status of the target steam turbine performing the current planned operating condition based on the planned stress level; Based on the actual variable load characteristic parameters and actual main steam temperature parameters of the target steam turbine after executing the current planned operating condition, the actual stress level of the target component of the target steam turbine is determined through the pre-constructed mapping relationship. The cumulative life loss of the target component is determined based on the actual stress level, and life loss monitoring is implemented for the target component based on the cumulative life loss.

2. The method according to claim 1, characterized in that, The planned variable load characteristic parameters are obtained through the following methods: Obtain the current planned load curve of the target steam turbine; Identify each load change event from the current planned load curve and extract the planned load change characteristic parameters corresponding to each load change event; The load change event is defined as a monotonic change process from one steady-state load platform to another, and the planned load change characteristic parameters include the planned load change range and the planned load change rate. Accordingly, the planned stress level of the target component of the target steam turbine under the current planned operating condition is determined by pre-constructing mapping relationships, including: The planned stress level of the target component under each load change event is determined by pre-constructing mapping relationships.

3. The method according to claim 2, characterized in that, The pre-constructed mapping relationship is a mapping relationship between load change range, load change rate, main steam temperature and stress level; The pre-built mapping relationship is constructed in the following way: Interpolation is performed based on a pre-built thermo-coupling response database to establish the pre-built mapping relationship; or Based on a pre-built thermo-coupled response database, a regression model is established using the response surface methodology to obtain the pre-built mapping relationship. or Based on a pre-built thermo-coupling response database, a surrogate mapping is established using a Kriging model, radial basis function model, or neural network model to obtain the pre-built mapping relationship; or Based on a pre-built thermo-mechanical coupling response database, a simplified physical model is used to estimate the thermal stress level according to the temperature gradient characteristics caused by load changes, so as to establish the pre-built mapping relationship.

4. The method according to claim 3, characterized in that, The pre-built thermo-coupling response database is constructed in the following manner: Obtain the combined relationship between a specified load change range, a specified load change rate, and a specified main steam temperature; Finite element analysis was used to analyze the temperature and stress distribution of the target components of the target steam turbine under each specified load variation range, specified load rate, and specified main steam temperature. The pre-built thermo-mechanical coupling response database is obtained by associating and storing the specified load change range, specified load change rate, specified main steam temperature, temperature distribution, and stress distribution.

5. The method according to claim 2, characterized in that, Determining the safety of the target steam turbine performing the current planned operating condition based on the planned stress level includes: The planned stress level of the target component under each load change event is compared with a safety threshold; wherein the safety threshold is constructed based on the yield strength of the target component material. If all planned stress levels are less than or equal to the safety threshold, it is determined that the target steam turbine can operate safely under the current planned operating conditions; If the planned stress level is greater than the safety threshold, the target turbine is determined to be in danger under the current planned operating condition.

6. The method according to claim 2, characterized in that, Determining the cumulative lifespan loss of the target component based on the actual stress level includes: Based on the actual stress level corresponding to each load change event, the low-cycle fatigue crack initiation life curve corresponding to the target component material is queried to obtain the low-cycle fatigue crack initiation life of the target component under each load change event. The reciprocal of the low-cycle fatigue crack initiation life is used to obtain the low-cycle fatigue crack initiation life loss of the target component under each load change event. Count the number of cycles for each type of load change event; Based on the number of cycles for each type of load change event, the cumulative life loss of the target component under each load change event is accumulated using the linear superposition law of life loss, thus obtaining the cumulative life loss of the target component.

7. The method according to claim 1, characterized in that, Based on the cumulative lifespan loss, lifespan loss monitoring is implemented for the target component, including: When the cumulative lifespan loss reaches a preset lifespan threshold, a lifespan loss warning message is generated for the target component to prompt maintenance or limit subsequent load changes.

8. A monitoring device for a steam turbine component, characterized in that, include: The planned stress level determination module is used to determine the planned stress level of the target component of the target steam turbine under the current planned operating conditions based on the planned variable load characteristic parameters of the target steam turbine under the current planned operating conditions, through a pre-built mapping relationship; The safety monitoring module is used to determine the safety status of the target steam turbine performing the current planned operating condition based on the planned stress level. The actual stress level determination module is used to determine the actual stress level of the target component of the target steam turbine based on the actual variable load characteristic parameters and actual main steam temperature parameters after the target steam turbine performs the current planned operating condition, through the pre-built mapping relationship. The life monitoring module is used to determine the cumulative life loss of the target component based on the actual stress level, and to monitor the life loss of the target component based on the cumulative life loss.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform a monitoring method for a steam turbine component according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement a monitoring method for a steam turbine component according to any one of claims 1-7.

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