Gas turbine full-state design method and device, electronic equipment and storage medium
Patent Information
- Application Number
- CN202510428804.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-07
- Publication Date
- 2025-08-15
Smart Images
Figure CN120493414A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of aviation engines, and in particular to a method, device, electronic equipment, and storage medium for full-state design of a gas turbine. Background Art
[0002] The extensive testing required during gas turbine development significantly increases R&D costs. For engine control system research, establishing a high-precision mathematical model that accurately reflects the operating conditions of each engine section is crucial, as it enhances the reliability of semi-physical testing of the control system.
[0003] Current gas turbine mathematical modeling approaches primarily rely on mechanism-based analysis and experimental identification. Identification-based modeling relies on extensive input of full-state test data under various inlet conditions to approximate the system's output response and generate a model. However, such data is costly, risky, and difficult to obtain. Analytical methods, based on the operating characteristics of gas turbine components and aero-thermodynamic principles, utilize nonlinear equations and curve interpolation tables to model and calculate aero-thermodynamic parameters. However, obtaining component characteristics at low speeds presents significant challenges. Furthermore, due to the significant deviation from the design point in analytical methods, which are significantly affected by factors such as secondary flow losses, Reynolds number, and flow continuity, the component characteristics at ultra-low speeds have a narrow range, resulting in poor convergence when solving nonlinear equations. However, all of these modeling approaches suffer from data shortages.
[0004] Therefore, how to solve the problem in the existing technology that the gas turbine model cannot adapt to multiple operating conditions due to insufficient data in the modeling method is one of the important issues that need to be urgently solved in this field. Summary of the Invention
[0005] In view of this, the embodiments of the present disclosure provide a gas turbine full-state design method, device, electronic device and storage medium to solve the problem in the prior art that the gas turbine model cannot adapt to multiple operating conditions due to insufficient data in the modeling method.
[0006] According to one aspect of the present disclosure, a gas turbine full-state design method is provided, comprising:
[0007] Obtaining dynamic parameters of the target gas turbine;
[0008] Input the dynamic parameters into the pre-built target model to obtain the speed parameters corresponding to the target gas turbine;
[0009] determining a state identifier corresponding to a target gas turbine according to a speed parameter;
[0010] And determine the target working status based on the status identifier.
[0011] In addition, according to the gas turbine full-state design method according to one aspect of the present disclosure, the target model includes a starting sub-model, and the gas turbine full-state design method further includes:
[0012] Acquiring startup test data parameters of a target gas turbine and performing noise reduction processing on the startup test data parameters;
[0013] Determine the time parameter and amplification factor of the starting test data parameters after noise reduction based on the identification method;
[0014] Constructing a mathematical model of the start-up phase of the target gas turbine based on time parameters and amplification factors;
[0015] Determining the parameter relationship between the aerodynamic parameters and the speed parameters of the target gas turbine according to the mathematical model;
[0016] Construct the starting sub-model based on the parameter relationship.
[0017] According to a gas turbine full-state design method according to one aspect of the present disclosure, the target model further includes a driving sub-model, and the gas turbine full-state design method further includes:
[0018] Obtaining aerodynamic and thermodynamic parameters of the target gas turbine;
[0019] Construct a steady-state model of the target gas turbine based on aerodynamic and thermodynamic parameters;
[0020] and determining steady-state component parameters of the driving sub-model based on the steady-state model;
[0021] Based on the steady-state component parameters, a steady-state target gas turbine nonlinear equation set is constructed under the conditions of flow continuity and power continuity;
[0022] A steady-state driving sub-model of the target gas turbine during driving is constructed based on the steady-state nonlinear equations.
[0023] According to a gas turbine full-state design method according to one aspect of the present disclosure, the target model further includes a driving sub-model, and the gas turbine full-state design method further includes:
[0024] Construct a dynamic model of the target gas turbine based on aerodynamic thermodynamic parameters;
[0025] Determining dynamic component parameters of a dynamic driving sub-model based on the dynamic model;
[0026] Under the condition of continuous flow, dynamic nonlinear and differential equations of target gas turbine are constructed based on dynamic component parameters and rotor dynamics.
[0027] A dynamic driving sub-model of the target gas turbine during driving is constructed based on the dynamic nonlinear equations and differential equations.
[0028] According to a gas turbine full-state design method according to one aspect of the present disclosure, the target model further includes a shutdown sub-model, and the gas turbine full-state design method further includes:
[0029] Acquiring shutdown test data parameters of the target gas turbine during the shutdown process;
[0030] constructing a target curve for the target gas turbine during a shutdown process based on the shutdown test data parameters, wherein the target curve is determined by a relationship between the shutdown test data parameters and a time parameter;
[0031] Construct a parking sub-model based on the target curve.
[0032] According to a gas turbine full-state design method according to one aspect of the present disclosure, a state identifier corresponding to a target gas turbine is determined according to a speed parameter, and the method further includes:
[0033] The state identifier of the target gas turbine is determined according to the turbine speed of the target gas turbine gas and the external shutdown instruction.
[0034] According to a gas turbine full-state design method according to one aspect of the present disclosure, the gas turbine full-state design method further comprises:
[0035] If the speed of the target gas turbine is less than or equal to the first threshold and there is no shutdown command signal, the state flag is the first flag;
[0036] If the speed of the target gas turbine is greater than or equal to the second threshold and there is no shutdown command signal, the state flag is the second flag;
[0037] If an external parking signal is input, the status indicator is the third indicator.
[0038] According to another aspect of the present disclosure, a gas turbine full-state design device is provided, comprising: a first acquisition module for acquiring dynamic parameters of a target gas turbine; a second acquisition module for inputting the dynamic parameters into a pre-built target model to acquire speed parameters corresponding to the target gas turbine; a first determination module for determining a state identifier corresponding to the target gas turbine based on the speed parameters; and a second determination module for determining a target operating state based on the state identifier.
[0039] According to another aspect of the present disclosure, an electronic device is provided, comprising at least one processor; and a memory for storing instructions executable by at least one processor; wherein the at least one processor is configured to execute instructions to implement the steps of the above-mentioned gas turbine full-state design method.
[0040] According to another aspect of the present disclosure, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the steps of the above-mentioned gas turbine full-state design method.
[0041] At least one of the above-mentioned technical solutions adopted in the embodiments of the present disclosure can achieve the following beneficial effects: in the above-mentioned gas turbine full-state design method, the dynamic parameters of the target gas turbine are obtained; the dynamic parameters are input into a pre-constructed target model to obtain the speed parameters corresponding to the target gas turbine; the state identifier corresponding to the target gas turbine is determined according to the speed parameters; and the target operating state is determined according to the state identifier. Based on this, by using the pre-constructed target model to obtain different target operating states of the target gas turbine, sufficient data support is provided for constructing the target model. On this basis, the speed parameters corresponding to the target gas turbine are obtained through the above-mentioned pre-constructed target model, and the target operating state of the target gas turbine is determined according to different speed parameters, which enhances the versatility of the target model, enables the target model to meet the needs of multiple operating conditions, and effectively solves the problem in the prior art that the gas turbine model cannot adapt to multiple operating conditions due to insufficient data in the modeling method. BRIEF DESCRIPTION OF THE DRAWINGS
[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0043] Figure 1 A schematic diagram illustrating a process of applying a gas turbine full-state design method according to an embodiment of the present disclosure;
[0044] Figure 2 is a schematic diagram illustrating a process of starting a sub-model according to an embodiment of the present disclosure;
[0045] Figure 3 is a schematic diagram illustrating an operation flow of a starting sub-model according to an embodiment of the present disclosure;
[0046] Figure 4 A schematic flow chart of a steady-state driving sub-model according to an embodiment of the present disclosure is further illustrated;
[0047] Figure 5 Further illustrating a flow chart of a dynamic driving sub-model according to an embodiment of the present disclosure;
[0048] Figure 6 Further illustrating a schematic diagram of the operation flow of the driving sub-model according to an embodiment of the present disclosure;
[0049] Figure 7 Further illustrating a flow chart of a parking sub-model according to an embodiment of the present disclosure;
[0050] Figure 8 A schematic diagram of a gas turbine full-state design apparatus according to an embodiment of the present disclosure is further illustrated;
[0051] Figure 9 A schematic structural diagram of an electronic device according to an embodiment of the present disclosure is further illustrated;
[0052] Figure 10 The following further illustrates a schematic structural diagram of a computer system according to an embodiment of the present disclosure. DETAILED DESCRIPTION
[0053] The following describes embodiments of the present disclosure in more detail with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.
[0054] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.
[0055] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.
[0056] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".
[0057] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.
[0058] The extensive testing required during gas turbine development significantly increases R&D costs. For engine control system research, establishing a high-precision mathematical model that accurately reflects the operating conditions of each engine section is crucial, as it enhances the reliability of semi-physical testing of the control system.
[0059] Current gas turbine mathematical modeling approaches primarily rely on mechanism-based analysis and experimental identification. Identification-based modeling relies on extensive input of full-state test data under various inlet conditions to approximate the system's output response and generate a model. However, such data is costly, risky, and difficult to obtain. Analytical methods, based on the operating characteristics of gas turbine components and aero-thermodynamic principles, utilize nonlinear equations and curve interpolation tables to model and calculate aero-thermodynamic parameters. However, obtaining component characteristics at low speeds presents significant challenges. Furthermore, due to the significant deviation from the design point in analytical methods, which are significantly affected by factors such as secondary flow losses, Reynolds number, and flow continuity, the component characteristics at ultra-low speeds have a narrow range, resulting in poor convergence when solving nonlinear equations. However, all of these modeling approaches suffer from data shortages.
[0060] In response to the above problems, the exemplary embodiments of the present disclosure provide a gas turbine full-state design method, device, electronic device and storage medium to solve the problem in the prior art that the gas turbine model cannot adapt to multiple operating conditions due to insufficient data in the modeling method.
[0061] A gas turbine full-state design method according to an embodiment of the present disclosure will be described in detail below with reference to the accompanying drawings.
[0062] Figure 1 FIG2 is a schematic diagram illustrating a process of applying the gas turbine full-state design method according to an embodiment of the present disclosure. Figure 1 As shown, the gas turbine full-state design method includes the following steps:
[0063] S101: Acquire dynamic parameters of a target gas turbine;
[0064] S102: Inputting the dynamic parameters into a pre-built target model to obtain the speed parameters corresponding to the target gas turbine;
[0065] S103: Determine a state identifier corresponding to the target gas turbine according to the speed parameter;
[0066] S104: Determine the target working state according to the state identifier.
[0067] In practical applications, the above-mentioned gas turbine full-state design method obtains the dynamic parameters of the target gas turbine; inputs the dynamic parameters into a pre-constructed target model to obtain the speed parameters corresponding to the target gas turbine; determines the state identifier corresponding to the target gas turbine based on the speed parameters; and determines the target operating state based on the state identifier. Based on this, by utilizing the pre-constructed target model to obtain different target operating states of the target gas turbine, sufficient data support is provided for constructing the target model. Furthermore, by using the pre-constructed target model to obtain the speed parameters corresponding to the target gas turbine, and determining the target operating state of the target gas turbine based on different speed parameters, the versatility of the target model is enhanced, enabling the target model to meet the requirements of multiple operating conditions, effectively resolving the problem in existing technologies where gas turbine models cannot adapt to multiple operating conditions due to insufficient data in the modeling method.
[0068] For example, Figure 2 is a flow chart illustrating a start-up sub-model according to an embodiment of the present disclosure, such as Figure 2 As shown, the target model includes a starting sub-model, and the gas turbine full-state design method also includes:
[0069] S201: Acquire startup test data parameters of a target gas turbine and perform noise reduction on the startup test data parameters. It should be understood that the startup test data parameters of the target gas turbine are obtained based on the measurement parameters of different types of sensors, such as temperature sensors and pressure sensors.
[0070] S202: Determine the time parameter and amplification factor of the noise-reduced startup test data parameters based on the identification method. It should be understood that the noise reduction processing is performed on the gas turbine startup test data through mean filtering, smoothing filtering and extreme value filtering.
[0071] S203: Construct a mathematical model of the target gas turbine during the startup phase based on the time parameter and the amplification factor. In practical applications, a first-order system without zero points can also be used to represent the mathematical model of the gas turbine as an inertia link:
[0072]
[0073] Among them, T T is the time constant of the gas turbine, K T is the amplification factor of the gas turbine, Indicates the inertia link.
[0074] S204: Determine the parameter relationship between the aerodynamic parameters and the speed parameters of the target gas turbine according to the mathematical model. It should be understood that the mathematical model is used to estimate the time constant T of the gas turbine in each data segment by using the identification method. T and amplification factor KT , the simplified starting model of the gas turbine in the time domain is obtained by performing the reverse transformation on the above formula:
[0075]
[0076] Among them, K T is the amplification factor of the gas turbine, They represent the functional relationship between the key section aerodynamic parameters and the gas turbine speed.
[0077] Based on the starting test data parameters, the functional relationship between key cross-section aerodynamic parameters and gas turbine speed is fitted, and the starting characteristics of important cross-section parameters and performance parameters such as compressor outlet pressure Pt3, exhaust temperature Tt6, and power turbine speed Np are established:
[0078] (Pt3, Tt6, Np……)=f(Ng)
[0079] Among them, Pt3 represents the total pressure at the compressor outlet, Tt6 represents the total temperature at the turbine outlet, Np represents the power turbine speed, and Ng represents the gas generator speed.
[0080] The inlet conditions of the starting mathematical model are modified so that the model can simulate the starting characteristics of cross-sectional parameters under different intake conditions:
[0081]
[0082] Wherein, T2 represents the total temperature at the gas turbine inlet, P2 represents the total pressure at the gas turbine inlet, and the subscript 1 represents other inlet conditions.
[0083] S205: Constructing a startup sub-model according to the parameter relationship.
[0084] Figure 3 is a schematic diagram illustrating the operation flow of the startup sub-model according to an embodiment of the present disclosure, such as Figure 3 As shown, step S301 is executed first, followed by the starter rotation in step S302. If the speed Ng>Ng0 in step S303, step S304 is executed to supply fuel and ignite the starter and the engine turbine to rotate together. If the speed Ng<Ng0 in step S303, step S302 is continued to be executed until Ng>Ng0, and then step S305 is executed to have Ng>Ng1. If Ng<Ng1, step S304 is continued to be executed to have the starter disengage from the gas turbine and self-accelerate. If Ng>Ng1, step S306 is continued to be executed to end the starting process of entering the slow-speed state in step S307.
[0085] For example, Figure 4Further illustrating a flow diagram of a steady-state driving sub-model according to an embodiment of the present disclosure, the target model further includes a driving sub-model, and the gas turbine full-state design method further includes:
[0086] S401: Acquire aerodynamic and thermodynamic parameters of a target gas turbine.
[0087] S402: Constructing a steady-state model of the target gas turbine according to aerodynamic thermodynamic parameters.
[0088] S403: Determine steady-state component parameters of the driving sub-model based on the steady-state model.
[0089] S404: constructing a steady-state target gas turbine nonlinear equation group based on steady-state component parameters under conditions of continuous flow and continuous power;
[0090] S405: A steady-state sub-model for the target gas turbine during operation is constructed based on the steady-state nonlinear equations. In practical applications, the steady-state sub-model for the target gas turbine is based on flow continuity and power balance between components. The nonlinear equations are solved using the Newton-Raphson iterative algorithm to obtain each quasi-steady-state operating point during the steady-state process. This solution utilizes a dual closed-loop computational structure, with an "inner loop" iterative solution. The inner loop solution method is the same as the steady-state model solution method. The outer loop is a time integrator, using the Euler method to solve the rotor dynamics differential equations.
[0091]
[0092] x k+1 =x k -[Df(x k )] -1 e k
[0093] Where: Df(x k ) is the Jacobian matrix.
[0094] in,
[0095] Figure 5 Further illustrating the flow diagram of the dynamic driving sub-model according to the embodiment of the present disclosure, as shown in FIG. Figure 5 As shown, the target model also includes a driving sub-model, and the gas turbine full-state design method also includes:
[0096] S501: Constructing a dynamic model of a target gas turbine according to aerodynamic thermodynamic parameters.
[0097] S502: Determine the dynamic component parameters of the dynamic driving sub-model based on the dynamic model. It should be understood that the target gas turbine startup process is divided into three phases. The first phase is the target gas turbine cold run: this is the acceleration process from the starter motor's power generation to the combustion chamber ignition, which begins when the starter motor drives the gas generator rotor. The second phase is the target gas turbine's phase from ignition of the fuel mixture to disengagement of the starter motor. The third phase is the phase from disengagement of the starter motor until the engine reaches idle speed. In the first phase, combined with test data parameters, the time-varying characteristics of the target gas turbine's measured parameters during the initial startup phase are identified, representing the sensor measured parameters. After ignition of the target gas turbine in the second and third phases, the target gas turbine's startup time is primarily related to the fuel supply. Through identification, a gas turbine startup mathematical model represented by a transfer function and characteristic curves of key cross-sectional parameters varying with gas turbine speed are obtained. Finally, the startup model switches to the driving sub-model to obtain component parameters.
[0098] S503: Under the condition of continuous flow, construct a dynamic target gas turbine nonlinear equation group and a differential equation group based on dynamic component parameters and rotor dynamics.
[0099] S504: Constructing a dynamic driving sub-model of the target gas turbine during driving based on the dynamic nonlinear equations and differential equations. It is understandable that solving the above dynamic driving sub-model includes solving the differential equations established by rotor dynamics.
[0100] Specifically, Euler's formula is as follows:
[0101]
[0102] Figure 6 Further illustrating the operation flow diagram of the driving sub-model according to the embodiment of the present disclosure, as shown in FIG. Figure 6As shown, starting from step S601, the parameters of the pre-built target model are initialized in step S602, until a different sub-model is selected in step S603. When the selected sub-model is a dynamic sub-model, the intake condition control parameters under the dynamic sub-model conditions are obtained in step S6041. Then, the parameters of each component are obtained in step S6042. Then, the nonlinear equations and differential equations are established in step S6043. Finally, based on whether the flow continuity is met in step S6043, the result is output to step S6044. If the flow continuity is met in step S6044, the next step S6045 is continued. If the flow is not met in step S6044, the initial parameters are updated according to the Newton-Raphson method in step S6047. The parameters are then input again to step S6042 to continue obtaining the parameters of each component. After obtaining the result in step S6044, execute the parameter acquisition in step S6045 to check whether it is completed. If the parameter acquisition in step S6045 is completed, directly execute the instruction in step S6048. If the parameter acquisition in step S6045 is not completed, execute step S6046 to calculate the speed at the next moment based on the rotor dynamics using the Euler method, and finally input the obtained speed parameters into step S602 again until the above parameter acquisition is completed.
[0103] like Figure 6 As shown, when the selected sub-model is a steady-state sub-model, the intake condition control parameters under the dynamic sub-model conditions are obtained in step S6051, and then the parameters of each component are obtained in step S6052, and then the nonlinear equation group is established in step S6053, and then whether the flow continuity is satisfied is executed in step S6054. If the flow is continuous in step S6054, step S6056 is executed to directly output the result. If the flow is discontinuous in step S6054, step S6055 is executed to update the initial parameters according to the Newton-Raphson method, and the parameters of each component are input again in step S6051, and the above steps S6051 to S6054 are repeated again until the result is output.
[0104] Figure 7 Further illustrating a flow chart of the parking sub-model according to an embodiment of the present disclosure, as shown in FIG. Figure 7 As shown, the target model also includes a shutdown sub-model, and the gas turbine full-state design method also includes:
[0105] S701: Acquire shutdown test data parameters of the target gas turbine during the shutdown process;
[0106] S702: constructing a target curve for the target gas turbine during the shutdown process based on the shutdown test data parameters, wherein the target curve is determined by a relationship between the shutdown test data parameters and a time parameter;
[0107] S703: Construct a parking sub-model based on the target curve.
[0108] Exemplarily, the method further comprises determining the state identifier corresponding to the target gas turbine according to the speed parameter: determining the state identifier of the target gas turbine according to the turbine speed of the target gas turbine gas and an external shutdown instruction.
[0109] For example, the gas turbine full-state design method further includes: if the target gas turbine speed is less than or equal to a first threshold and there is no shutdown command signal, the state flag is the first flag. It should be understood that in actual applications, the first threshold is Ng2 and the first flag is 0. If the target gas turbine speed is greater than or equal to a second threshold and there is no shutdown command signal, the state flag is the second flag. In actual applications, the second threshold is Ng3 and the second flag is 1. If an external shutdown signal is input, the state flag is the third flag and the second flag is 2.
[0110] In the case of dividing each functional module according to each function, an exemplary embodiment of the present disclosure provides a compressor aerodynamic stability prediction device, which can be a server or a chip applied to a server. Figure 8 The following is a schematic diagram of a gas turbine full-state design device according to an embodiment of the present disclosure. Figure 8 As shown, the gas turbine full-state design device 800 includes:
[0111] The first acquisition module 801 acquires the dynamic parameters of the target gas turbine.
[0112] The second acquisition module 802 inputs the dynamic parameters into a pre-built target model to obtain the speed parameters corresponding to the target gas turbine.
[0113] The first determining module 803 determines a state identifier corresponding to the target gas turbine according to the rotational speed parameter.
[0114] The second determining module 804 determines the target working state according to the state identifier.
[0115] Figure 9 The following is a schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure. Figure 9 As shown, the electronic device 900 includes at least one processor 901 and a memory 902 coupled to the processor 901. The processor 901 can execute corresponding steps in the above method disclosed in the embodiment of the present disclosure.
[0116] The processor 901 may also be referred to as a central processing unit (CPU), which may be an integrated circuit chip with signal processing capabilities. Each step in the method disclosed in the embodiment of the present disclosure may be performed by hardware integrated logic circuits in the processor 901 or by software instructions. The processor 901 may be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiment of the present disclosure may be directly embodied as being executed by a hardware decoding processor, or may be executed by a combination of hardware and software modules in the decoding processor. The software module may be located in the memory 902, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, or other mature storage media in the art. The processor 901 reads the information in the memory 902 and performs the steps of the method in combination with its hardware.
[0117] In addition, when various operations / processes according to the present disclosure are implemented by software and / or firmware, they can be transferred from a storage medium or a network to a computer system having a dedicated hardware structure, for example, Figure 10 The computer system 1000 shown is installed with the programs constituting the software. When the various programs are installed, the computer system can execute various functions, including the functions described above. Figure 10 The following further illustrates a schematic structural diagram of a computer system according to an embodiment of the present disclosure.
[0118] Computer system 1000 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are intended to be examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.
[0119] like Figure 10As shown, the computer system 1000 includes a computing unit 1001, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1002 or a computer program loaded from a storage unit 1008 into a random access memory (RAM) 1003. Various programs and data required for the operation of the computer system 1000 can also be stored in the RAM 1003. The computing unit 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.
[0120] Multiple components within computer system 1000 are connected to I / O interface 1005, including an input unit 1006, an output unit 1007, a storage unit 1008, and a communication unit 1009. Input unit 1006 can be any type of device capable of inputting information into computer system 1000. Input unit 1006 can receive input numeric or character information and generate key input signals related to user settings and / or function control of an electronic device. Output unit 1007 can be any type of device capable of presenting information and may include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. Storage unit 1008 may include, but is not limited to, a magnetic disk or an optical disk. Communication unit 1009 allows computer system 1000 to exchange information / data with other devices via a network, such as the Internet, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver and / or chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.
[0121] The computing unit 1001 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1001 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1001 performs the various methods and processes described above. For example, in some embodiments, the above-mentioned methods disclosed in the embodiments of the present disclosure may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 1008. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 900 via the ROM 1002 and / or the communication unit 1009. In some embodiments, the computing unit 1001 may be configured to perform the above-mentioned methods disclosed in the embodiments of the present disclosure by any other appropriate means (e.g., by means of firmware).
[0122] An embodiment of the present disclosure further provides a computer-readable storage medium, wherein when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the above method disclosed in the embodiment of the present disclosure.
[0123] The computer-readable storage medium in the embodiments of the present disclosure may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. The computer-readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specifically, the computer-readable storage medium may include an electrical connection based on one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0124] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.
[0125] The embodiments of the present disclosure further provide a computer program product, including a computer program, wherein when the computer program is executed by a processor, the method disclosed in the embodiments of the present disclosure is implemented.
[0126] In embodiments of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages or combinations thereof, including but not limited to object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer.
[0127] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.
[0128] The modules, components, or units described in the embodiments of the present disclosure may be implemented in software or hardware. The names of the modules, components, or units do not necessarily limit the modules, components, or units themselves.
[0129] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, and without limitation, exemplary hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.
[0130] The above descriptions are merely some embodiments of the present disclosure and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in the present disclosure.
[0131] Although some specific embodiments of the present disclosure have been described in detail by way of examples, those skilled in the art will appreciate that the above examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Those skilled in the art will appreciate that modifications may be made to the above embodiments without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.
Claims
1. A gas turbine full-state design method, characterized in that: include: Obtaining dynamic parameters of the target gas turbine; Inputting the dynamic parameters into a pre-built target model to obtain the speed parameters corresponding to the target gas turbine; Determining a state identifier corresponding to the target gas turbine according to the speed parameter; And determine the target working state according to the state identifier.
2. The gas turbine full-state design method according to claim 1, characterized in that: The target model includes a starting sub-model, and the gas turbine full-state design method further includes: Acquiring startup test data parameters of a target gas turbine and performing noise reduction processing on the startup test data parameters; Determine the time parameter and the amplification factor of the starting test data parameters after noise reduction processing based on the identification method; constructing a mathematical model of the startup phase of the target gas turbine based on the time parameter and the amplification factor; determining a parameter relationship between an aerodynamic parameter of the target gas turbine and the speed parameter according to the mathematical model; A starting sub-model is constructed according to the parameter relationship.
3. The gas turbine full-state design method according to claim 1, characterized in that: The target model further includes a driving sub-model, and the gas turbine full-state design method further includes: Obtaining aerodynamic and thermodynamic parameters of the target gas turbine; constructing a steady-state model of the target gas turbine according to the aerodynamic thermodynamic parameters; and determining steady-state component parameters of the driving sub-model based on the steady-state model; Based on the steady-state component parameters, a steady-state target gas turbine nonlinear equation set is constructed under the conditions of flow continuity and power continuity; A steady-state driving sub-model of the target gas turbine during driving is constructed based on the steady-state nonlinear equations.
4. The gas turbine full-state design method according to claim 3, characterized in that: The gas turbine full-state design method further includes: constructing a dynamic model of the target gas turbine according to the aerodynamic thermodynamic parameters; determining dynamic component parameters of the dynamic driving sub-model based on the dynamic model; Under the condition of continuous flow, dynamic nonlinear and differential equations of target gas turbine are constructed based on dynamic component parameters and rotor dynamics. A dynamic driving sub-model of the target gas turbine during driving is constructed based on the dynamic nonlinear equations and differential equations.
5. The gas turbine full-state design method according to claim 1, characterized in that: The target model further includes a parking sub-model, and the gas turbine full-state design method further includes: Acquiring shutdown test data parameters of the target gas turbine during the shutdown process; constructing a target curve for the target gas turbine during a shutdown process based on the shutdown test data parameters, wherein the target curve is determined by a relationship between the shutdown test data parameters and a time parameter; The parking sub-model is constructed based on the target curve.
6. The gas turbine full-state design method according to claim 1, characterized in that: The method of determining a state identifier corresponding to the target gas turbine according to the speed parameter further includes: A state identifier of the target gas turbine is determined according to a turbine speed of the target gas turbine and an external shutdown instruction.
7. The gas turbine full-state design method according to claim 6, characterized in that: The gas turbine full-state design method further includes: If the speed of the target gas turbine is less than or equal to the first threshold and there is no shutdown command signal, the state identifier is the first identifier; If the speed of the target gas turbine is greater than or equal to the second threshold and there is no shutdown command signal, the state flag is the second flag; If an external parking signal is input, the state identifier is the third identifier.
8. A gas turbine full-state design device, characterized in that: include: A first acquisition module acquires dynamic parameters of a target gas turbine; A second acquisition module inputs the dynamic parameters into a pre-built target model to obtain a speed parameter corresponding to the target gas turbine; A first determining module determines a state identifier corresponding to the target gas turbine according to the speed parameter; The second determining module determines a target working state according to the state identifier.
9. An electronic device, characterized in that: include: at least one processor; a memory for storing the at least one processor-executable instruction; Wherein, the at least one processor is used to execute the instructions to implement the gas turbine full-state design method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the gas turbine full-state design method according to any one of claims 1 to 7.