Heavy duty gas turbine control logic verification method and verification platform

Abstract

The invention discloses a heavy duty gas turbine control logic verification method and verification platform. The method comprises the steps of obtaining a first SAMA graph of heavy duty gas turbine control logic; generating combined working condition parameters under various different working conditions; verifying the first gas turbine simulation model to obtain a verified second gas turbine simulation model; determining a parameter operation boundary corresponding to the second gas turbine simulation model; and on the basis of the parameter operation boundary, the combined working condition parameter and the second gas turbine simulation model, verifying the control logic in the first SAMA graph to obtain a control logic verification result. According to the method, multi-level wide-range working condition automatic verification is carried out on the control logic in the design stage, the design defects of the control logic are determined and modified in advance, the verification coverage range and the verification efficiency are improved, the verification result is more accurate, and the development efficiency and the credibility of the gas turbine control logic are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of combustion engine verification, and in particular to a heavy-duty gas turbine control logic verification method and verification platform. Background Art

[0002] As core equipment in the energy and power sector, the reliability and verification completeness of gas turbine control logic are directly related to the safety and reliability of unit operation. With the increasing complexity of gas turbine systems and the diversification of operating conditions, control logic must precisely coordinate the dynamic characteristics of key equipment, components, and the overall system. This requires ensuring stable control performance and rapid response capabilities under complex operating conditions, such as extreme environments and component degradation, to ensure stable gas turbine operation.

[0003] Related technologies utilize graphical programming tools such as SAMA diagrams to describe the functional modularity of gas turbine control logic design, and then manually program and debug the control strategy. However, existing verification primarily relies on hardware-in-the-loop (HIL) simulation platforms combined with simplified mathematical models for limited operating condition testing. This makes it difficult to fully cover the multi-dimensional parameter coupling scenarios that may occur throughout the gas turbine's lifecycle, resulting in insufficient verification coverage. Furthermore, the accuracy of the simulation model under complex operating conditions is difficult to guarantee, and test case generation relies on manual labor, with limited coverage and a low degree of automation. This results in low verification efficiency, making it difficult to fully demonstrate the effectiveness of the control logic under a wide range of complex operating conditions, and inaccurate verification results. Summary of the Invention

[0004] The present invention provides a heavy-duty gas turbine control logic verification method and verification platform to solve the technical problems of insufficient verification coverage, low verification efficiency and inaccurate verification results in the above-mentioned prior art.

[0005] To this end, the present invention proposes a heavy-duty gas turbine control logic verification method, which can use the combined operating parameters, parameter operation boundaries and the verified second gas turbine simulation model under a variety of different operating conditions to verify the control logic in the first SAMA diagram and obtain the control logic verification result. Therefore, the control logic can be automatically verified under multi-level and wide-range operating conditions in the design stage, and the control logic design defects can be determined and modified in advance, thereby improving the verification coverage and verification efficiency, making the verification results more accurate, and improving the development efficiency and credibility of the gas turbine control logic.

[0006] Another object of the present invention is to provide a heavy-duty gas turbine control logic verification platform.

[0007] To achieve the above objectives, the present invention provides a heavy-duty gas turbine control logic verification method, comprising: Obtain the first SAMA diagram of the heavy-duty gas turbine control logic; Generate combined working condition parameters under various working conditions; Verifying the first gas turbine simulation model to obtain a verified second gas turbine simulation model; determining a parameter operating boundary corresponding to the second gas turbine simulation model; Based on the parameter operation boundary, the combined operating condition parameter and the second gas turbine simulation model, the control logic in the first SAMA diagram is verified to obtain a control logic verification result.

[0008] The heavy-duty gas turbine control logic verification method according to the embodiment of the present invention may also have the following additional technical features: In an embodiment of the present invention, generating combined operating condition parameters under a plurality of different operating conditions includes: Generate environmental parameters and adjustment coefficients under various working conditions; Based on the environmental parameters and the adjustment coefficients, combined operating condition parameters under a variety of different operating conditions are generated through the LHS method.

[0009] In an embodiment of the present invention, verifying the first gas turbine simulation model to obtain a verified second gas turbine simulation model includes: determining parameters to be corrected in the first gas turbine simulation model; Determining a gradient calculation result of the parameter to be corrected; Based on the gradient calculation result, the parameter to be corrected is iteratively updated using the gradient descent method until the target parameter is obtained; The target parameters are input into the first gas turbine simulation model to obtain a verified second gas turbine simulation model.

[0010] In an embodiment of the present invention, determining the parameters to be corrected in the first gas turbine simulation model includes: calculating a sensitivity index of each parameter in the first gas turbine simulation model, wherein the sensitivity index is used to indicate an influence of the parameter on an objective function, and the objective function is a loss function corresponding to the first gas turbine simulation model; If the sensitivity index of the parameter is greater than a preset threshold, the parameter is determined to be a parameter to be corrected.

[0011] In an embodiment of the present invention, determining the parameter operating boundary corresponding to the second gas turbine simulation model includes: The target parameters are input into a parameter boundary model to obtain a parameter operation boundary corresponding to the second gas turbine simulation model.

[0012] In an embodiment of the present invention, verifying the control logic in the first SAMA diagram based on the parameter operation boundary, the combined operating condition parameter, and the second gas turbine simulation model to obtain a control logic verification result includes: Connecting the control logic in the first SAMA diagram to the second gas turbine simulation model; injecting the combined operating condition parameters into the second gas turbine simulation model in sequence to obtain operating parameters of the second gas turbine simulation model during operation; determining whether the operating parameter exceeds the parameter operating boundary; If the operating parameter does not exceed the parameter operating boundary, it is determined that the control logic in the first SAMA diagram passes the verification.

[0013] In an embodiment of the present invention, when the control logic verification result is verification passed, the method further includes: Determine an IO signal requirement set and an IO signal verification set corresponding to the first SAMA diagram; The IO signal verification set is verified based on preset rules and the IO signal requirement set. If the verification passes, the first SAMA diagram is merged with the second SAMA diagram to obtain a third SAMA diagram, wherein the second SAMA diagram is the previous version of the SAMA diagram.

[0014] In an embodiment of the present invention, the IO signal verification set includes a control logic IO signal set, a simulation model IO signal set, a boundary model IO signal set, and a working condition generated IO signal set; and verifying the IO signal verification set based on preset rules and the IO signal requirement set includes: Performing bidirectional matching on the control logic IO signal set based on the IO signal requirement set to obtain a first verification result; Performing bidirectional matching on the simulation model IO signal set based on the IO signal requirement set to obtain a second verification result; Performing bidirectional matching on the boundary model IO signal set based on the IO signal requirement set to obtain a third verification result; Performing a one-way match on the working condition generated IO signal set based on the IO signal requirement set to obtain a fourth verification result; If there are no abnormal IO points in the first verification result, the second verification result, the third verification result and the fourth verification result, the verification passes; otherwise, the verification fails.

[0015] In an embodiment of the present invention, the merging of the first SAMA graph and the second SAMA graph to obtain a third SAMA graph includes: determining a first branch version of the first SAMA graph and a second branch version of the second SAMA graph; Performing conflict detection on the first branch version and the second branch version to obtain a conflict detection result; If the conflict detection result is that there is no conflict, the first branch version and the second branch version are merged to obtain a third SAMA graph.

[0016] In an embodiment of the present invention, the method further includes: Get the target index position; The cached SAMA graph of the baseline version is applied sequentially in the version iteration order using the stored incremental codes until the target index position is reached, thereby obtaining the fourth SAMA graph of the target index position, wherein the incremental codes are used to indicate the difference operator between adjacent versions.

[0017] To achieve the above objectives, the present invention further provides a heavy-duty gas turbine control logic verification platform, the verification platform comprising: Control logic design system for obtaining the first SAMA diagram of heavy-duty gas turbine control logic; Control logic test and verification system, used to generate combined operating parameters under various working conditions; A gas turbine multi-level simulation system is used to verify the first gas turbine simulation model to obtain a verified second gas turbine simulation model; The control logic test and verification system is further configured to determine parameter operating boundaries corresponding to the second gas turbine simulation model; The control logic test and verification system is also used to verify the control logic in the first SAMA diagram based on the parameter operation boundary, the combined operating parameters and the second gas turbine simulation model to obtain a control logic verification result.

[0018] In an embodiment of the present invention, the control logic test and verification system includes a complex operating condition generation module; the complex operating condition generation module is specifically configured to: Generate environmental parameters and adjustment coefficients under various working conditions; Based on the environmental parameters and the adjustment coefficients, combined operating condition parameters under a variety of different operating conditions are generated through the LHS method.

[0019] In an embodiment of the present invention, the gas turbine multi-level simulation system includes a model verification tool; the model verification tool is specifically used to: determining parameters to be corrected in the first gas turbine simulation model; Determining a gradient calculation result of the parameter to be corrected; Based on the gradient calculation result, the parameter to be corrected is iteratively updated using the gradient descent method until the target parameter is obtained; The target parameters are input into the first gas turbine simulation model to obtain a verified second gas turbine simulation model.

[0020] In an embodiment of the present invention, the model verification tool is further used to: calculating a sensitivity index of each parameter in the first gas turbine simulation model, wherein the sensitivity index is used to indicate an influence of the parameter on an objective function, and the objective function is a loss function corresponding to the first gas turbine simulation model; If the sensitivity index of the parameter is greater than a preset threshold, the parameter is determined to be a parameter to be corrected.

[0021] In an embodiment of the present invention, the control logic test and verification system further includes a boundary model library; the boundary model library is specifically used to: The target parameters are input into a parameter boundary model to obtain a parameter operation boundary corresponding to the second gas turbine simulation model.

[0022] In an embodiment of the present invention, the control logic test and verification system is further used to: Connecting the control logic in the first SAMA diagram to the second gas turbine simulation model; injecting the combined operating condition parameters into the second gas turbine simulation model in sequence to obtain operating parameters of the second gas turbine simulation model during operation; determining whether the operating parameter exceeds the parameter operating boundary; If the operating parameter does not exceed the parameter operating boundary, it is determined that the control logic in the first SAMA diagram passes the verification.

[0023] In an embodiment of the present invention, the verification platform further includes a collaborative development system, and the collaborative development system includes an IO point verification tool and a version control tool; The IO point verification tool is used to determine the IO signal requirement set and IO signal verification set corresponding to the first SAMA diagram; The IO point verification tool is further used to verify the IO signal verification set based on preset rules and the IO signal requirement set; If the verification is passed, the version control tool is further used to merge the first SAMA diagram with the second SAMA diagram to obtain a third SAMA diagram, wherein the second SAMA diagram is the SAMA diagram of the previous version.

[0024] In an embodiment of the present invention, the IO signal verification set includes a control logic IO signal set, a simulation model IO signal set, a boundary model IO signal set, and a working condition generated IO signal set; the IO point verification tool is specifically used to: Performing bidirectional matching on the control logic IO signal set based on the IO signal requirement set to obtain a first verification result; Performing bidirectional matching on the simulation model IO signal set based on the IO signal requirement set to obtain a second verification result; Performing bidirectional matching on the boundary model IO signal set based on the IO signal requirement set to obtain a third verification result; Performing a one-way match on the working condition generated IO signal set based on the IO signal requirement set to obtain a fourth verification result; If there are no abnormal IO points in the first verification result, the second verification result, the third verification result and the fourth verification result, the verification passes; otherwise, the verification fails.

[0025] In an embodiment of the present invention, the version control tool is specifically used to: determining a first branch version of the first SAMA graph and a second branch version of the second SAMA graph; Performing conflict detection on the first branch version and the second branch version to obtain a conflict detection result; If the conflict detection result is that there is no conflict, the first branch version and the second branch version are merged to obtain a third SAMA graph.

[0026] In an embodiment of the present invention, the version control tool is further used to: Get the target index position; The cached SAMA graph of the baseline version is applied sequentially in the version iteration order using the stored incremental codes until the target index position is reached, thereby obtaining the fourth SAMA graph of the target index position, wherein the incremental codes are used to indicate the difference operator between adjacent versions.

[0027] A heavy-duty gas turbine control logic verification method and verification platform according to an embodiment of the present invention includes obtaining a first SAMA diagram of the heavy-duty gas turbine control logic; generating combined operating condition parameters under a plurality of different operating conditions; verifying the first gas turbine simulation model to obtain a verified second gas turbine simulation model; determining parameter operating boundaries corresponding to the second gas turbine simulation model; and verifying the control logic in the first SAMA diagram based on the parameter operating boundaries, the combined operating condition parameters, and the second gas turbine simulation model to obtain a control logic verification result. Thus, the present invention utilizes the combined operating condition parameters under a plurality of different operating conditions, the parameter operating boundaries, and the verified second gas turbine simulation model to verify the control logic in the first SAMA diagram to obtain a control logic verification result. This allows for automated verification of the control logic across multiple levels and a wide range of operating conditions during the design phase, enabling the early identification and correction of control logic design defects, thereby improving verification coverage and efficiency, resulting in more accurate verification results and enhancing the development efficiency and credibility of the gas turbine control logic.

[0028] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which: Figure 1 is a flow chart of a heavy-duty gas turbine control logic verification method according to an embodiment of the present invention; Figure 2 is a flow chart of a heavy-duty gas turbine control logic verification method according to an embodiment of the present invention; Figure 3 is a flow chart of a heavy-duty gas turbine control logic verification method according to an embodiment of the present invention; Figure 4 is a flow chart of a heavy-duty gas turbine control logic verification method according to an embodiment of the present invention; Figure 5 2 is a schematic structural diagram of a heavy-duty gas turbine control logic verification platform according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0031] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0032] The following describes a heavy-duty gas turbine control logic verification method and verification platform proposed according to an embodiment of the present invention with reference to the accompanying drawings.

[0033] Figure 1 It is a flow chart of a heavy-duty gas turbine control logic verification method according to an embodiment of the present invention.

[0034] like Figure 1 As shown, the method may include the following steps: Step 101: Obtain a first SAMA diagram of the heavy-duty gas turbine control logic.

[0035] In an embodiment of the present invention, a demand analysis and conceptual design of a heavy-duty gas turbine control logic may be obtained, and a first SAMA diagram corresponding to the control logic may be generated using various functional components included in a logic function library.

[0036] In the embodiment of the present invention, the logic function library includes the functional components required for the gas turbine control logic design, and is used to implement the required logic function description.

[0037] In the embodiment of the present invention, the logic function library includes at least an analog quantity operation library, a digital quantity operation library, an advanced algorithm library and a signal library.

[0038] In the embodiment of the present invention, the analog quantity operation library at least includes functional modules of various elementary mathematical operations, size selection, quality judgment, saturation, dead zone, differentiation and integration.

[0039] In the embodiment of the present invention, the digital quantity operation library at least includes functional modules such as AND / OR operation and high and low level counting.

[0040] In an embodiment of the present invention, the advanced algorithm library includes custom algorithm blocks that can be used to implement complex functions and algorithms (such as matrix operations and complex time series) by writing code in different languages, including C, C++, and Fortran, and supports encapsulation.

[0041] In an embodiment of the present invention, the signal library includes at least IO signal blocks, intermediate point signal blocks and alarm signal blocks, among which the IO signal blocks should contain information such as signal name, extension name, signal description, signal type, range, dimension, etc.

[0042] Step 102: Generate combined operating condition parameters under multiple different operating conditions.

[0043] In an embodiment of the present invention, when verifying the control logic, it is necessary to generate combined operating condition parameters under multiple different operating conditions, so as to verify the control logic through the combined operating condition parameters under multiple different operating conditions, thereby improving the verification coverage.

[0044] In an embodiment of the present invention, the method for generating combined operating condition parameters under multiple different operating conditions may include the following steps: Step 1021: Generate environmental parameters and adjustment coefficients under various working conditions.

[0045] In an embodiment of the present invention, the above-mentioned combined operating condition parameters may include complex operating condition combinations under different atmospheric environments and different performance degradation conditions. Among them, the environmental parameters may include atmospheric temperature, humidity and pressure. , and the environmental parameters can be injected into the first gas turbine simulation model as input parameters. And different performance degradation conditions can be adjusted by adjusting the coefficients ( ) by injecting corresponding parameters into the first gas turbine simulation model, thereby regulating performance degradation in the form of the product of the environmental parameters and the adjustment coefficient. Furthermore, the aforementioned different performance degradation conditions may include reduced compressor flow, decreased compressor efficiency, decreased combustion efficiency, and decreased turbine efficiency.

[0046] In the embodiment of the present invention, environmental parameters and adjustment coefficients under various working conditions may be generated through a database.

[0047] Step 1022: Based on the environmental parameters and the adjustment coefficients, a LHS method is used to generate combined operating parameters under various operating conditions.

[0048] In the embodiment of the present invention, due to the environmental parameters and adjustment factor Constitute a dimension If the test space is large, the test process will take a long time if the whole space is traversed.

[0049] In an embodiment of the present invention, based on environmental parameters and adjustment coefficients, the LHS method can be used to generate combined operating condition parameters under various different operating conditions, thereby achieving complex operating conditions that are evenly distributed in all dimensions within the overall test space, improving the verification coverage, and reducing the time for generating combined operating condition parameters.

[0050] For example, when atmospheric temperature, compressor efficiency reduction, combustion efficiency reduction, and turbine efficiency reduction are selected to generate 100 test conditions, atmospheric temperature The value range is set to ℃, efficiency drop of the three major components The value range is set to And, independently random sort the valid intervals of the four working condition parameter dimensions to obtain random sequences of the four parameters, each sequence contains 100 elements. The above process needs to ensure that there is no correlation between the parameters. Further, the random sequences of the four parameters are aligned in order, and In the test space, 100 test conditions are generated to satisfy the uniform distribution of each parameter dimension. Table 1 is a table of complex working condition combination parameters corresponding to environmental parameters and adjustment coefficients under various working conditions in an embodiment of the present invention.

[0051] Table 1

[0052] Among them, in the embodiment of the present invention, the above 100 sets of combined operating parameters can evenly cover more than 99% of the parameter space (confidence level 95%), and compared with the full range scan (assuming that each parameter has 10 levels, 10 4 test conditions), greatly improving the test verification efficiency.

[0053] Step 103: Verify the first gas turbine simulation model to obtain a verified second gas turbine simulation model.

[0054] In an embodiment of the present invention, before verifying the control logic in the first SAMA diagram, it is necessary to calibrate the first gas turbine simulation model so that its steady-state and dynamic performance are close to the latest test data or design data, so as to ensure that the test verification results after the combined operating condition parameters are injected are not invalidated due to model distortion.

[0055] In an embodiment of the present invention, the first gas turbine simulation model may include a device-level model, a component-level model, and a system-level model. The device-level model accurately reproduces the dynamic characteristics of actuators and sensors, such as the flow-opening hysteresis curve of a fuel valve and the step response time of a thermocouple sensor. Its parameters are generally directly derived from technical manuals and bench test calibration data. The component-level model is constructed based on aerodynamic thermodynamic characteristic lines and includes various characteristic lines for the three major components (such as the compressor's pressure ratio-flow characteristic curve and the turbine efficiency versus expansion ratio curve). These characteristic lines can be pre-obtained through finite element simulation or prototype testing during the turbine design phase and packaged as pluggable function modules. The system-level model couples the characteristic lines of each component using a lumped parameter method to construct a complete-machine-level real-time simulation environment, capable of simulating the full-operation thermodynamic cycle of the turbine, from startup, load variation, to shutdown.

[0056] In an embodiment of the present invention, a method for calibrating a first gas turbine simulation model to obtain a verified second gas turbine simulation model may include: determining parameters to be corrected in the first gas turbine simulation model, calculating gradients of the parameters to be corrected, iteratively updating the parameters to be corrected using a gradient descent method based on the gradient calculation results until target parameters are obtained, and inputting the target parameters into the first gas turbine simulation model to obtain the verified second gas turbine simulation model. This will be described in detail in subsequent embodiments.

[0057] Step 104: Determine the parameter operating boundaries corresponding to the second gas turbine simulation model.

[0058] In an embodiment of the present invention, after obtaining the verified second gas turbine simulation model through the above steps, the parameter operation boundary corresponding to the second gas turbine simulation model can be determined, so as to verify the control logic in the first SAMA diagram through the parameter operation boundary.

[0059] In an embodiment of the present invention, the method for determining the parameter operating boundary corresponding to the second gas turbine simulation model may include: inputting the target parameter into the parameter boundary model to obtain the parameter operating boundary corresponding to the second gas turbine simulation model.

[0060] In an embodiment of the present invention, the above-mentioned parameter boundary model at least includes a minimum IGV boundary model, a maximum IGV boundary model, a minimum T4 boundary model, a maximum T4 boundary model, a maximum T3 boundary model, a combustion chamber flameout equivalence ratio boundary model and a combustion chamber backfire equivalence ratio boundary model.

[0061] In an embodiment of the present invention, each of the aforementioned parameter boundary models embeds a verified independent gas turbine main engine system model, whose model parameters are synchronized and updated with the target parameters in the second gas turbine simulation model. The embedded gas turbine main engine system model in each of the aforementioned parameter boundary models operates stably within its defined boundary conditions and outputs parameter operating boundaries corresponding to key gas turbine parameters (e.g., power, exhaust temperature, combustion chamber outlet temperature, etc.). In this embodiment of the present invention, these parameter operating boundaries may be parameter operating ranges.

[0062] Step 105 : Verify the control logic in the first SAMA diagram based on the parameter operation boundary, the combined operating condition parameters, and the second gas turbine simulation model to obtain a control logic verification result.

[0063] In an embodiment of the present invention, after obtaining the parameter operating boundaries, combined operating parameters and the second gas turbine simulation model through the above steps, the control logic in the first SAMA diagram can be verified based on the parameter operating boundaries, combined operating parameters and the second gas turbine simulation model to obtain a control logic verification result.

[0064] In an embodiment of the present invention, the method for verifying the control logic in the first SAMA diagram based on the parameter operating boundary, the combined operating condition parameter, and the second gas turbine simulation model to obtain the control logic verification result may include the following steps: Step 1051: Connect the control logic in the first SAMA diagram to the second gas turbine simulation model.

[0065] Step 1052: inject the combined operating condition parameters into the second gas turbine simulation model in sequence to obtain the operating parameters of the second gas turbine simulation model during operation.

[0066] In this embodiment of the present invention, the combined operating condition parameters are sequentially injected into the second gas turbine simulation model. The operation of the second gas turbine simulation model is controlled based on the combined operating condition parameters by the control logic in the first SAMA diagram, thereby determining the operating parameters of the second gas turbine simulation model during operation. In this embodiment of the present invention, the operating parameters may be one or more of the aforementioned key parameters.

[0067] Step 1053: Determine whether the operating parameters exceed the parameter operating boundary.

[0068] In an embodiment of the present invention, after obtaining the operating parameters of the second gas turbine simulation model during operation through the above steps, it can be determined whether the operating parameters exceed the parameter operating boundaries to determine whether the control logic in the first SAMA diagram passes verification.

[0069] In an embodiment of the present invention, if none of the operating parameters exceeds the corresponding parameter operating boundary, it is determined that the operating parameters do not exceed the parameter operating boundary; otherwise, it is determined that the operating parameters exceed the parameter operating boundary.

[0070] Step 1054: If the operating parameters do not exceed the parameter operating boundaries, it is determined that the control logic in the first SAMA diagram has passed the verification.

[0071] In an embodiment of the present invention, if the operating parameters do not exceed the parameter operating boundary, it means that the result obtained based on the control logic in the first SAMA diagram is within the parameter operating boundary, and then it is determined that the control logic in the first SAMA diagram has passed the verification.

[0072] A heavy-duty gas turbine control logic verification method according to an embodiment of the present invention includes obtaining a first SAMA diagram of the heavy-duty gas turbine control logic; generating combined operating condition parameters under a plurality of different operating conditions; verifying the first gas turbine simulation model to obtain a verified second gas turbine simulation model; determining parameter operating boundaries corresponding to the second gas turbine simulation model; and verifying the control logic in the first SAMA diagram based on the parameter operating boundaries, the combined operating condition parameters, and the second gas turbine simulation model to obtain a control logic verification result. Thus, the present invention utilizes the combined operating condition parameters under a plurality of different operating conditions, the parameter operating boundaries, and the verified second gas turbine simulation model to verify the control logic in the first SAMA diagram to obtain a control logic verification result. This allows for automated verification of the control logic under a wide range of operating conditions at multiple levels during the design phase, enabling the early identification and correction of control logic design defects, thereby improving verification coverage and efficiency, resulting in more accurate verification results and enhancing the development efficiency and credibility of the gas turbine control logic.

[0073] In the embodiment of the present invention, as a detailed description of step 103, as shown in FIG. Figure 2 As shown, it may also include: Step 1031: Determine parameters to be corrected in the first gas turbine simulation model.

[0074] In an embodiment of the present invention, the method for determining the parameters to be corrected in the first gas turbine simulation model may include the following steps: Step 10311: Calculate the sensitivity index of each parameter in the first gas turbine simulation model.

[0075] In an embodiment of the present invention, the sensitivity index is used to indicate the influence of the parameter on the objective function, and the objective function is a loss function corresponding to the first gas turbine simulation model.

[0076] In an embodiment of the present invention, the method for calculating the sensitivity index of each parameter in the first gas turbine simulation model may include: calculating the sensitivity index of each parameter in the first gas turbine simulation model using a sensitivity index formula, wherein the sensitivity index formula is:

[0077] in, To remove parameters The following set of other parameters to be selected, is a fixed parameter is the conditional expectation of the objective function, J is the objective function, and Var is the calculated variance.

[0078] Among them, the first gas turbine simulation model is established by the lumped parameter method, and the corresponding model state and output can be abstracted as a state equation represented by a nonlinear function and output equation , when actual measurement data or design data After input, define the objective function J as the mean square error between the two:

[0079] Among them, x(t) is the change of state vector state variables over time, u(t) is the control input vector at time t, t0 and t f is the time range, f and g are the state equations represented by nonlinear functions.

[0080] Step 10312: If the sensitivity index of the parameter is greater than a preset threshold, the parameter is determined to be a parameter to be corrected.

[0081] In the embodiment of the present invention, after the sensitivity index of each parameter is obtained through the above steps, it can be determined whether the parameter is a parameter to be corrected according to the sensitivity index of the parameter.

[0082] In an embodiment of the present invention, if the sensitivity index of a parameter is greater than a preset threshold, the parameter is determined to be a parameter to be corrected, wherein the preset threshold can be set as needed, such as 0.01.

[0083] For example, assuming the preset threshold is 0.01, determine the set of all parameters to be corrected Table 2 is an example table of sensitivity index judgment basis, based on which the parameters to be corrected can be determined through the sensitivity index judgment basis example table.

[0084] Table 2

[0085] Step 1032: Determine the gradient calculation result of the parameter to be corrected.

[0086] In an embodiment of the present invention, the method for determining the gradient calculation result of the parameter to be corrected may include: constructing an adjoint equation, and introducing a small perturbation into the adjoint equation , treat the correction parameters Perform variational analysis to obtain the gradient calculation results of the parameters to be corrected.

[0087] In the embodiment of the present invention, the evolution trajectory of the state equation is solved by forward simulation , and introduce accompanying variables , construct the adjoint equation and its boundary conditions, where the adjoint equation is: ,

[0088] Where g is a nonlinear function y(t)=g[x(t),u(t)], which is used to derive the state x vector through the function g.

[0089] In the embodiment of the present invention, the adjoint equation describes the back propagation of the error gradient along time.

[0090] In the embodiment of the present invention, by introducing a small perturbation into the adjoint equation , treat the correction parameters Perform variational analysis to obtain the gradient calculation results of the parameters to be corrected:

[0091] Among them, the above gradient calculation results can directly reflect the contribution of parameters to the output error.

[0092] Step 1033: Based on the gradient calculation result, the parameters to be corrected are iteratively updated using the gradient descent method until the target parameters are obtained.

[0093] In an embodiment of the present invention, the gradient calculation results of the parameters to be corrected are obtained through the above steps. Based on the gradient calculation results, the parameters to be corrected can be iteratively updated using the gradient descent method until the target parameters are obtained.

[0094] In the embodiment of the present invention, the parameters to be corrected are iteratively updated using the gradient descent method, and the updated parameters are: ,

[0095] in, To set the learning rate.

[0096] In the embodiment of the present invention, when the output results corresponding to the updated parameters tend to a steady state and converge, the target parameters are obtained.

[0097] Step 1034: Input the target parameters into the first gas turbine simulation model to obtain a verified second gas turbine simulation model.

[0098] In an embodiment of the present invention, after obtaining the target parameters through the above steps, the target parameters can be input into the first gas turbine simulation model to obtain a verified second gas turbine simulation model.

[0099] In an embodiment of the present invention, the first gas turbine simulation model is verified through the above steps to obtain a verified second gas turbine simulation model, so that the steady-state and dynamic performance of the second gas turbine simulation model are close to the latest test data or design data, thereby ensuring that the test verification results after the combined operating condition parameters are injected are not invalidated due to model distortion.

[0100] In another embodiment of the present invention, the above-mentioned heavy-duty gas turbine control logic verification method is as follows: Figure 3 As shown, the above method may further include: Step 301: Obtain a first SAMA diagram of the heavy-duty gas turbine control logic.

[0101] Step 302: Generate combined operating condition parameters under multiple different operating conditions.

[0102] Step 303: Verify the first gas turbine simulation model to obtain a verified second gas turbine simulation model.

[0103] Step 304: Determine the parameter operating boundaries corresponding to the second gas turbine simulation model.

[0104] Step 305 : Verify the control logic in the first SAMA diagram based on the parameter operation boundary, the combined operating condition parameters, and the second gas turbine simulation model to obtain a control logic verification result.

[0105] For the introduction of steps 301 to 305 , reference may be made to the detailed introduction in the above embodiment, which will not be elaborated herein.

[0106] Step 306 : When the control logic verification result is verification passed, the IO signal requirement set and IO signal verification set corresponding to the first SAMA diagram are determined.

[0107] In the embodiment of the present invention, the above-mentioned IO signal requirement set may be an IO signal requirement set actually required.

[0108] In an embodiment of the present invention, the IO signal verification set includes a control logic IO signal set, a simulation model IO signal set, a boundary model IO signal set, and a working condition generation IO signal set.

[0109] In this embodiment of the present invention, the IO signal requirement set and IO signal verification set corresponding to the first SAMA diagram can be determined using an IO point verification tool. In this embodiment of the present invention, the corresponding control logic IO signal set, simulation model IO signal set, boundary model IO signal set, and operating condition generation IO signal set can be obtained using various control logic design results, gas turbine simulation models at all levels, boundary models, and complex operating condition generation modules.

[0110] In an embodiment of the present invention, the IO signal requirement set may be determined through an IO point requirement list involved in the gas turbine control system.

[0111] Step 307 : Verify the IO signal verification set based on the preset rules and the IO signal requirement set. If the verification passes, merge the first SAMA diagram with the second SAMA diagram to obtain a third SAMA diagram.

[0112] In an embodiment of the present invention, the method for verifying the IO signal verification set based on the preset rules and the IO signal requirement set may include the following steps: Step 3071: Perform bidirectional matching on the control logic IO signal set based on the IO signal requirement set to obtain a first verification result; Step 3072: performing bidirectional matching on the simulation model IO signal set based on the IO signal requirement set to obtain a second verification result; Step 3073: perform bidirectional matching on the boundary model IO signal set based on the IO signal requirement set to obtain a third verification result; Step 3074: Perform a one-way match on the working condition generated IO signal set based on the IO signal requirement set to obtain a fourth verification result; Step 3075: If there are no abnormal IO points in the first verification result, the second verification result, the third verification result, and the fourth verification result, the verification passes; otherwise, the verification fails.

[0113] In an embodiment of the present invention, the structured data element of the IO quantity in the control logic IO signal set can be converted into a character string format and then bidirectionally matched with the character content information in the IO signal requirement set.

[0114] In this embodiment of the present invention, a bidirectional match is performed between the structured data element and the IO point signal name, extension, signal type, range, and dimension information in the IO signal requirement set to obtain a first verification result. If an abnormal IO point is matched, the first verification result includes the abnormal IO point. If both bidirectional matching results are normal, the first verification result indicates that the verification has passed.

[0115] In an embodiment of the present invention, the bidirectional matching can include forward matching and reverse matching. Forward matching can be used to filter out actual IO points that were incorrectly designed or omitted during the logic design process, while reverse matching can be used to filter out IO points that are no longer required for subsequent logic design or testing due to version iteration or other reasons.

[0116] In the embodiment of the present invention, the method for matching the simulation model IO signal set and the boundary model IO signal is the same as the above method steps, which will not be described in detail in the embodiment of the present invention.

[0117] In the embodiment of the present invention, the above-mentioned one-way matching of the working condition generated IO signal set is performed based on the IO signal requirement set, wherein the one-way matching needs to satisfy that the working condition generated IO signal set is a subset of the IO signal requirement set, that is, the IO signal requirement set needs to completely include all IOs in the working condition generated IO signal set, but the working condition generated IO signal set does not necessarily include all IOs in the IO signal requirement set.

[0118] In an embodiment of the present invention, if the verification is determined to be successful through the above steps, the first SAMA diagram and the second SAMA diagram can be merged to obtain a third SAMA diagram, wherein the second SAMA diagram is a SAMA diagram of the previous version, that is, the second SAMA diagram corresponds to the version stored last time.

[0119] In an embodiment of the present invention, the method for obtaining a third SAMA diagram by merging the first SAMA diagram with the second SAMA diagram may include: determining a first branch version of the first SAMA diagram and a second branch version of the second SAMA diagram, performing a conflict detection on the first branch version and the second branch version to obtain a conflict detection result; and if the conflict detection result indicates that no conflict exists, merging the first SAMA diagram with the second SAMA diagram to obtain a third SAMA diagram. This content will be described in detail in subsequent embodiments.

[0120] In an embodiment of the present invention, the above method may include the following steps: Step 308: Obtain the target index position.

[0121] Step 309: cache SAMA graph of baseline version , using the stored incremental code in the version iteration order, until the target index position is reached, and the fourth SAMA diagram of the target index position is obtained .

[0122] In the embodiment of the present invention, the above-mentioned incremental encoding is used to indicate the difference operator between adjacent versions.

[0123] In an embodiment of the present invention, ,in, is the sum of the incremental codes to reach the target index position, N is the number of incremental codes that need to be merged, and the baseline version is G0.

[0124] In the embodiment of the present invention, the version backtracking function can be implemented through the above steps 308 to 309 to determine the fourth SAMA diagram that needs to be backtracked.

[0125] In an embodiment of the present invention, the above steps can be used to manage the multi-branch versions generated during the collaborative development process, realize automatic merging of control logic design changes and historical version tracing, improve logic design efficiency, and reduce the time cost of manual verification.

[0126] In the embodiment of the present invention, as a detailed description of step 307, as shown in FIG. Figure 4 As shown, it may also include: Step 401 : Determine a first branch version of a first SAMA graph and a second branch version of a second SAMA graph.

[0127] In the embodiment of the present invention, the first branch version of the first SAMA diagram may be determined by using parameters in the control logic, the simulation model, and the boundary model in the first SAMA diagram.

[0128] In the embodiment of the present invention, the second branch version of the second SAMA diagram may be determined by using parameters in the control logic, the simulation model, and the boundary model in the second SAMA diagram.

[0129] Step 402: Conflict detection is performed on the first branch version and the second branch version to obtain a conflict detection result.

[0130] In an embodiment of the present invention, after obtaining the first branch version and the second branch version through the above steps, conflict detection can be performed on the first branch version and the second branch version, so as to perform version management based on the obtained conflict detection results.

[0131] In an embodiment of the present invention, the method for performing conflict detection on the first branch version and the second branch version to obtain a conflict detection result may include: Step 4021: Upload the SAMA graph branch of the first branch version to the version snapshot database, and store the SAMA graph branch logic chain state of the snapshot in the format of the first directed graph. ; In an embodiment of the present invention, the first directed graph is ,in, Component function node A collection of is the set of all nodes with signal flow ( express arrive There is a signal flow), Mapping function for node attributes .

[0132] Step 4022: Obtain the second directed graph of the second branch version in the version snapshot database ; Step 4023: Determine whether the same node in the first directed graph and the second directed graph satisfies a conflict detection condition. If the conflict detection condition is satisfied, it is determined that a conflict exists; if the conflict detection condition is not satisfied, it is determined that no conflict exists. The conflict detection condition may be: ,

[0133] Step 403: If the conflict detection result is that there is no conflict, the first branch version and the second branch version are merged to obtain a third SAMA graph.

[0134] In an embodiment of the present invention, the above-mentioned method of obtaining a third SAMA graph based on merging the first branch version and the second branch version may include: determining the incremental encoding of the first branch version and the second branch version, and merging the first branch version and the second branch version based on the incremental encoding to obtain the third SAMA graph.

[0135] In an embodiment of the present invention, the method for determining the incremental encoding between the first branch version and the second branch version may include the following steps: Step 1: Determine a first representation of multiple modification actions in a first directed graph corresponding to a first branch version and a second representation of multiple modification actions in a second directed graph corresponding to a second branch version; Step 2: Calculate the difference operator of adjacent versions based on the first representation and the second representation to obtain the incremental code.

[0136] In the embodiment of the present invention, the aforementioned multiple modification actions include adding actions, deleting actions, and modifying actions.

[0137] In the embodiment of the present invention, when a functional component node is added to the first directed graph , and give it initial attributes (such as signal name, range, etc.), add the first indication of the action for: ,

[0138] In the embodiment of the present invention, when a functional component node is deleted in the first directed graph , and delete all its associated signal flows, delete the first representation corresponding to the action for: ,

[0139] In the embodiment of the present invention, when a node is modified in the first directed graph An attribute of When the value of The first representation corresponding to the modification action for:

[0140] In the embodiment of the present invention, the difference operator of adjacent versions is calculated by using the first representation of the adding action, the first representation of the deleting action and the first representation of the modifying action in the second directed graph, the second representation of the adding action, the second representation of the deleting action and the second representation of the modifying action to incrementally encode the difference operator of adjacent versions. Form storage,

[0141] Among them, the minimum change operation unit between versions Describes the version arrive The specific modification actions of the graph structure and properties include adding and deleting component function nodes and modifying properties.

[0142] In the embodiment of the present invention, after obtaining the incremental code of the first branch version and the incremental code of the second branch version through the above steps, the incremental code of the first branch version can be used to generate the incremental code of the second branch version. Delta encoding with the second branch version Automatically merge multiple branches to obtain the third SAMA diagram.

[0143] In the embodiment of the present invention, the process of merging the incremental encodings of the different branch versions can be expressed as follows:

[0144] where the graph difference applies the operator It can indicate the change from the old version to the new version.

[0145] In an embodiment of the present invention, if the conflict detection result shows that a conflict exists, manual intervention should be made to judge, adjust the conflicting part, re-upload the version snapshot database and re-perform conflict detection. Based on this, the conflict detection also has the function of locating the positions of the conflicting functional component nodes and attribute values ​​in the SAMA diagram.

[0146] In an embodiment of the present invention, the above steps can be used to manage the multi-branch versions generated during the collaborative development process, realize automatic merging of control logic design changes and historical version tracing, improve logic design efficiency, and reduce the time cost of manual verification.

[0147] In order to implement the above embodiment, Figure 5 As shown, this embodiment also provides a heavy-duty gas turbine control logic verification platform, which may include: A control logic design system 501 is used to obtain a first SAMA diagram of a heavy-duty gas turbine control logic; The control logic test and verification system 502 is used to generate combined operating parameters under various operating conditions; The gas turbine multi-level simulation system 503 is configured to verify the first gas turbine simulation model to obtain a verified second gas turbine simulation model; The control logic test and verification system 502 is further configured to determine parameter operating boundaries corresponding to the second gas turbine simulation model; The control logic test and verification system 502 is further used to verify the control logic in the first SAMA diagram based on the parameter operation boundary, the combined operating condition parameters and the second gas turbine simulation model to obtain a control logic verification result.

[0148] In the embodiment of the present invention, the control logic design system 501 is mainly composed of modules such as a logic function library and supports logic design.

[0149] In the embodiment of the present invention, the logic function library includes the functional components required for the gas turbine control logic design, and is used to implement the required logic function description.

[0150] In the embodiment of the present invention, the logic function library includes at least an analog quantity operation library, a digital quantity operation library, an advanced algorithm library, a signal library, and the like.

[0151] In the embodiment of the present invention, the analog operation library at least includes various functional modules such as elementary mathematical operations, size selection, quality judgment, saturation, dead zone, differentiation, and integration.

[0152] In the embodiment of the present invention, the digital quantity operation library at least includes functional modules such as AND / OR operation, high and low level counting, etc.

[0153] In an embodiment of the present invention, the advanced algorithm library includes custom algorithm blocks, which can implement complex functions and algorithms such as matrix operations, complex timing, etc. by writing C, C++, Fortran and other codes, and supports encapsulation.

[0154] In an embodiment of the present invention, the signal library includes at least IO signal blocks, intermediate point signal blocks, alarm signal blocks, etc., wherein the IO signal blocks should contain information such as signal name, extension name, signal description, signal type, range, dimension, etc.

[0155] In an embodiment of the present invention, the control logic test and verification system 502 includes a complex operating condition generation module 5021. The complex operating condition generation module is specifically configured to: Generate environmental parameters and adjustment coefficients under various working conditions; Based on environmental parameters and adjustment coefficients, the LHS method is used to generate combined operating parameters under various working conditions.

[0156] In an embodiment of the present invention, the complex operating condition generation module 5021 is used to generate combined operating condition parameters that include various complex atmospheric environments (including parameters such as different temperatures, humidity, and atmospheric pressures) and different component performance degradation conditions (including reduced compressor flow, decreased compressor efficiency, decreased combustion efficiency, decreased turbine efficiency, etc.), and use a combined covering algorithm (such as the LHS method) to generate complex operating conditions with uniform distribution of various parameter dimensions, and inject them into the gas turbine multi-level simulation system to achieve a complex operating condition combination covering the entire operating condition range.

[0157] In an embodiment of the present invention, the gas turbine multi-level simulation system 503 includes a model verification tool 5031. The model verification tool 5031 is specifically used to: determining parameters to be corrected in the first gas turbine simulation model; Determine the gradient calculation result of the parameter to be corrected; Based on the gradient calculation results, the parameters to be corrected are iteratively updated using the gradient descent method until the target parameters are obtained; The target parameters are input into the first gas turbine simulation model to obtain a verified second gas turbine simulation model.

[0158] In this embodiment of the present invention, the multi-level gas turbine simulation system 503 constructs a full-dimensional model system covering the equipment, component, and complete machine levels. It interfaces with the control logic designed in the control logic design system 501 via a data interface and interacts with the control logic test and verification system 502 to inject complex operating conditions into the simulation model. Furthermore, it has the ability to automatically verify the model based on changes to upstream information such as test data and design data, providing a high-fidelity dynamic environment for hierarchical verification of the designed control logic.

[0159] In the embodiment of the present invention, the gas turbine multi-level simulation system 503 further includes a multi-level model library.

[0160] In an embodiment of the present invention, a multi-level model library calls models of different accuracy levels according to logical verification requirements to achieve a dynamic balance between simulation accuracy and verification efficiency. Specifically, the device-level model can accurately reproduce the dynamic characteristics of actuators and sensors, such as the flow-opening hysteresis curve of a fuel valve and the step response time of a thermocouple sensor. Its parameters are generally directly derived from the manufacturer's technical manual and bench test calibration data. The component-level model is constructed based on aerodynamic thermodynamic characteristic lines, including various characteristic lines of the three major components (such as the compressor's pressure ratio-flow characteristic surface and the turbine efficiency versus expansion ratio curve). These characteristic lines are pre-obtained through finite element simulation or prototype testing during the gas turbine design phase and packaged as pluggable function modules. The system-level model couples the characteristic lines of each component through the lumped parameter method to construct a real-time simulation environment for the entire engine, capable of simulating the full-operation thermodynamic cycle of the gas turbine, from startup, load change, to shutdown.

[0161] In an embodiment of the present invention, the model verification tool 5031 can adopt a hierarchical verification strategy to implement differentiated calibration of the characteristics and data observability of models at different levels to achieve the difference between the converged simulation output and the upstream input design or test data, so that simulation models at different levels are closer to actual performance.

[0162] In an embodiment of the present invention, the above-mentioned device-level model can be constructed based on physical mechanism equations, its parameters are directly solidified through factory calibration data, and the dynamic response error can be automatically compensated through a closed-loop control algorithm. Based on this, there is no need for frequent calibration.

[0163] In an embodiment of the present invention, for the above-mentioned component-level model, after the initial characteristic line is imported, when design iteration updates or operating state drift occur (such as blade fouling causing a shift in the pressure ratio-flow characteristic), a surrogate model-assisted local fitting method is used for verification, and interpolation correction is performed on the key sections of the characteristic line to ensure the fidelity of the component model in the typical operating condition area.

[0164] In an embodiment of the present invention, for the system-level model, the model verification tool 5031 may also be used to: Calculating a sensitivity index of each parameter in the first gas turbine simulation model, wherein the sensitivity index is used to indicate an influence of the parameter on an objective function, where the objective function is a loss function corresponding to the first gas turbine simulation model; If the sensitivity index of the parameter is greater than a preset threshold, the parameter is determined to be a parameter to be corrected.

[0165] In an embodiment of the present invention, the control logic test verification system 502 further includes a boundary model library 5022 ; the boundary model library 5022 is specifically used to input the target parameters into the parameter boundary model to obtain the parameter operation boundary corresponding to the second gas turbine simulation model.

[0166] In this embodiment of the present invention, the boundary model library 5022 provides various control boundaries for the control logic test and verification system 502, based on the concepts of gas turbine operation control and protection requirements. Specifically, the boundary model library 5022 includes at least a minimum IGV boundary model, a maximum IGV boundary model, a minimum T4 boundary model, a maximum T4 boundary model, a maximum T3 boundary model, a combustion chamber flameout equivalence ratio boundary model, and a combustion chamber flashback equivalence ratio boundary model.

[0167] In this embodiment of the present invention, each boundary model embeds a calibrated, independent gas turbine main engine system model. Its calibration parameters are synchronized and updated with the target parameters transmitted by the model calibration tool within the gas turbine multi-level simulation system. In this embodiment of the present invention, the embedded gas turbine model within each boundary model operates stably within its defined boundary conditions and outputs operating boundaries defined by key gas turbine parameters (e.g., power, exhaust temperature, combustion chamber outlet temperature, etc.).

[0168] In an embodiment of the present invention, the control logic test and verification system is further used to: Connecting the control logic in the first SAMA diagram to the second gas turbine simulation model; injecting the combined operating condition parameters into the second gas turbine simulation model in sequence to obtain operating parameters of the second gas turbine simulation model during operation; Determine whether the operating parameters exceed the parameter operating boundaries; If the operating parameters do not exceed the parameter operating boundaries, it is determined that the control logic in the first SAMA diagram passes the verification.

[0169] In an embodiment of the present invention, the complex operating condition generation module sequentially injects the combined operating condition parameters into the gas turbine multi-level simulation system and causes it to operate under the control logic in the first SAMA diagram connected to the control logic design system. It determines whether the operating parameters of the second gas turbine simulation model operation process exceed the operating boundaries of various parameters output by the boundary model library and records the verification status, forming an automated closed-loop verification process from test case generation and injection to the output of control logic validity judgment results.

[0170] In the embodiment of the present invention, the verification platform further includes a collaborative development system 504 , and the collaborative development system 504 includes an IO point verification tool 5041 and a version control tool 5042 .

[0171] IO point verification tool 5041, used to determine the IO signal requirement set and IO signal verification set corresponding to the first SAMA diagram; The IO point verification tool 5041 is further used to verify the IO signal verification set based on preset rules and the IO signal requirement set; If the verification is passed, the version control tool 5042 is further used to merge the first SAMA diagram with the second SAMA diagram to obtain a third SAMA diagram, wherein the second SAMA diagram is the SAMA diagram of the previous version.

[0172] In an embodiment of the present invention, the IO signal verification set includes a control logic IO signal set, a simulation model IO signal set, a boundary model IO signal set, and a working condition generation IO signal set.

[0173] In an embodiment of the present invention, the IO point verification tool 5041 is specifically used to: Perform bidirectional matching on the control logic IO signal set based on the IO signal requirement set to obtain a first verification result; Performing bidirectional matching on the simulation model IO signal set based on the IO signal requirement set to obtain a second verification result; Perform bidirectional matching on the boundary model IO signal set based on the IO signal requirement set to obtain a third verification result; Performing a one-way match on the working condition generated IO signal set based on the IO signal requirement set to obtain a fourth verification result; If there are no abnormal IO points in the first verification result, the second verification result, the third verification result and the fourth verification result, the verification passes; otherwise, the verification fails.

[0174] In an embodiment of the present invention, the IO point verification tool 5041 can perform bidirectional verification and validation on the IO signal blocks of various control logic design results, multi-level simulation models of gas turbines, boundary models, complex operating condition generation modules, and the IO point requirement list involved in the actual control system of the gas turbine.

[0175] In an embodiment of the present invention, based on the internal data standard of the software platform where the SAMA diagram is located, the structured data elements of the IO quantity in the logic design results can be extracted through a specific API interface, converted into a string format, and then bidirectionally matched with the character content information in the actual IO requirement set.

[0176] In an embodiment of the present invention, the verification process is to perform bidirectional matching on the signal name, extension name, signal type, range, dimension and other information of the structured data element and the actual IO requirement set according to the set rules. The forward matching can be used to screen out the actual IO points that are incorrectly designed or omitted in the logic design process, and the reverse matching can be used to screen out the IO points that no longer need to enter the subsequent logic design or testing process due to version iteration and other reasons, which is conducive to releasing and optimizing hardware resource allocation.

[0177] In an embodiment of the present invention, the version control tool 5042 is specifically used to: determining a first branch version of the first SAMA graph and a second branch version of the second SAMA graph; Perform conflict detection on the first branch version and the second branch version to obtain a conflict detection result; If the conflict detection result is that there is no conflict, the first branch version and the second branch version are merged to obtain a third SAMA graph.

[0178] In an embodiment of the present invention, the version control tool 5042 is further used to: Get the target index position; The cached SAMA graph of the baseline version is applied sequentially in the version iteration order using the stored incremental codes until the target index position is reached, thereby obtaining the fourth SAMA graph of the target index position, wherein the incremental codes are used to indicate the difference operator between adjacent versions.

[0179] In an embodiment of the present invention, the version control tool 5042 can perform multi-branch version management on the SAMA diagram architecture modification content generated during the collaborative development process, realize automatic merging of design changes and historical version tracing, which is conducive to efficient and collaborative development of a large amount of logic design work.

[0180] In an embodiment of the present invention, the version control tool 5042 is based on the internal data model of the logic design platform, and stores metadata such as the topological structure, functional component attributes and parameter configuration of the SAMA diagram logical chain through the version snapshot database, converts it into an incremental coding sequence with semantic identification, and compares the differences with the baseline data in the version library.

[0181] In an embodiment of the present invention, during the version merging process, a conflict detection algorithm is used to perform compatibility analysis on the parallel modification behaviors of the same logical chain, automatically mark non-conflicting changes (such as parameter optimization of different independent functional components) and generate a merged SAMA diagram.

[0182] In an embodiment of the present invention, when a conflict detection algorithm finds logically contradictory modifications (for example, the calculation method of the same intermediate point signal differs simultaneously in different version branches), a manual intervention prompt is triggered.

[0183] In an embodiment of the present invention, the version control tool also has a version backtracking function, which supports accurate restoration of historical versions of logic design by timestamp, modifier or functional module dimension.

[0184] In the heavy-duty gas turbine control logic verification platform proposed by the present invention, a first SAMA diagram of the heavy-duty gas turbine control logic is obtained; combined operating condition parameters under multiple different operating conditions are generated; the first gas turbine simulation model is verified to obtain a verified second gas turbine simulation model; parameter operating boundaries corresponding to the second gas turbine simulation model are determined; and based on the parameter operating boundaries, the combined operating condition parameters, and the second gas turbine simulation model, the control logic in the first SAMA diagram is verified to obtain a control logic verification result. Thus, the present invention utilizes the combined operating condition parameters under multiple different operating conditions, the parameter operating boundaries, and the verified second gas turbine simulation model to verify the control logic in the first SAMA diagram and obtain a control logic verification result. This allows for automated verification of the control logic under a wide range of operating conditions at multiple levels during the design phase, enabling the early identification and correction of control logic design defects, thereby improving verification coverage and efficiency, resulting in more accurate verification results and enhancing the development efficiency and credibility of gas turbine control logic.

[0185] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions of this disclosure can be achieved. This is not a limitation herein.

[0186] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A heavy-duty gas turbine control logic verification method, characterized in that: The method comprises: Obtain the first SAMA diagram of the heavy-duty gas turbine control logic; Generate combined working condition parameters under various working conditions; Verifying the first gas turbine simulation model to obtain a verified second gas turbine simulation model; determining a parameter operating boundary corresponding to the second gas turbine simulation model; Based on the parameter operation boundary, the combined operating condition parameter and the second gas turbine simulation model, the control logic in the first SAMA diagram is verified to obtain a control logic verification result.

2. The method according to claim 1, characterized in that The generating of combined operating condition parameters under a plurality of different operating conditions includes: Generate environmental parameters and adjustment coefficients under various working conditions; Based on the environmental parameters and the adjustment coefficients, combined operating condition parameters under a variety of different operating conditions are generated through the LHS method.

3. The method according to claim 1, characterized in that The verifying the first gas turbine simulation model to obtain a verified second gas turbine simulation model includes: determining parameters to be corrected in the first gas turbine simulation model; Determining a gradient calculation result of the parameter to be corrected; Based on the gradient calculation result, the parameter to be corrected is iteratively updated using the gradient descent method until the target parameter is obtained; The target parameters are input into the first gas turbine simulation model to obtain a verified second gas turbine simulation model.

4. The method according to claim 3, characterized in that The determining of the parameters to be corrected in the first gas turbine simulation model includes: calculating a sensitivity index of each parameter in the first gas turbine simulation model, wherein the sensitivity index is used to indicate an influence of the parameter on an objective function, and the objective function is a loss function corresponding to the first gas turbine simulation model; If the sensitivity index of the parameter is greater than a preset threshold, the parameter is determined to be a parameter to be corrected.

5. The method according to claim 3, characterized in that Determining the parameter operating boundary corresponding to the second gas turbine simulation model includes: The target parameters are input into a parameter boundary model to obtain a parameter operation boundary corresponding to the second gas turbine simulation model.

6. The method according to claim 1, characterized in that The verifying the control logic in the first SAMA diagram based on the parameter operation boundary, the combined operating condition parameter, and the second gas turbine simulation model to obtain a control logic verification result includes: Connecting the control logic in the first SAMA diagram to the second gas turbine simulation model; injecting the combined operating condition parameters into the second gas turbine simulation model in sequence to obtain operating parameters of the second gas turbine simulation model during operation; determining whether the operating parameter exceeds the parameter operating boundary; If the operating parameter does not exceed the parameter operating boundary, it is determined that the control logic in the first SAMA diagram passes the verification.

7. The method according to claim 1, characterized in that When the control logic verification result is verification passed, the method further includes: Determine an IO signal requirement set and an IO signal verification set corresponding to the first SAMA diagram; The IO signal verification set is verified based on preset rules and the IO signal requirement set. If the verification passes, the first SAMA diagram is merged with the second SAMA diagram to obtain a third SAMA diagram, wherein the second SAMA diagram is the previous version of the SAMA diagram.

8. The method according to claim 7, characterized in that The IO signal verification set includes a control logic IO signal set, a simulation model IO signal set, a boundary model IO signal set, and a working condition generated IO signal set; and verifying the IO signal verification set based on preset rules and the IO signal requirement set includes: Performing bidirectional matching on the control logic IO signal set based on the IO signal requirement set to obtain a first verification result; Performing bidirectional matching on the simulation model IO signal set based on the IO signal requirement set to obtain a second verification result; Performing bidirectional matching on the boundary model IO signal set based on the IO signal requirement set to obtain a third verification result; Performing a one-way match on the working condition generated IO signal set based on the IO signal requirement set to obtain a fourth verification result; If there are no abnormal IO points in the first verification result, the second verification result, the third verification result and the fourth verification result, the verification passes; otherwise, the verification fails.

9. The method according to claim 7, characterized in that The step of merging the first SAMA diagram with the second SAMA diagram to obtain a third SAMA diagram includes: determining a first branch version of the first SAMA graph and a second branch version of the second SAMA graph; Performing conflict detection on the first branch version and the second branch version to obtain a conflict detection result; If the conflict detection result is that there is no conflict, the first branch version and the second branch version are merged to obtain a third SAMA graph.

10. The method according to claim 7, characterized in that The method further comprises: Get the target index position; The cached SAMA graph of the baseline version is applied sequentially in the version iteration order using the stored incremental codes until the target index position is reached, thereby obtaining the fourth SAMA graph of the target index position, wherein the incremental codes are used to indicate the difference operator between adjacent versions.

11. A heavy-duty gas turbine control logic verification platform, characterized in that: The verification platform includes: Control logic design system for obtaining the first SAMA diagram of heavy-duty gas turbine control logic; Control logic test and verification system, used to generate combined operating parameters under various working conditions; A gas turbine multi-level simulation system is used to verify the first gas turbine simulation model to obtain a verified second gas turbine simulation model; The control logic test and verification system is further configured to determine parameter operating boundaries corresponding to the second gas turbine simulation model; The control logic test and verification system is also used to verify the control logic in the first SAMA diagram based on the parameter operation boundary, the combined operating parameters and the second gas turbine simulation model to obtain a control logic verification result.

12. The verification platform according to claim 11, characterized in that: The control logic test and verification system includes a complex working condition generation module; the complex working condition generation module is specifically used to: Generate environmental parameters and adjustment coefficients under various working conditions; Based on the environmental parameters and the adjustment coefficients, combined operating condition parameters under a variety of different operating conditions are generated through the LHS method.

13. The verification platform according to claim 11, characterized in that: The gas turbine multi-level simulation system includes a model verification tool; the model verification tool is specifically used to: determining parameters to be corrected in the first gas turbine simulation model; Determining a gradient calculation result of the parameter to be corrected; Based on the gradient calculation result, the parameter to be corrected is iteratively updated using the gradient descent method until the target parameter is obtained; The target parameters are input into the first gas turbine simulation model to obtain a verified second gas turbine simulation model.

14. The verification platform according to claim 13, characterized in that: The model verification tool is also used to: calculating a sensitivity index of each parameter in the first gas turbine simulation model, wherein the sensitivity index is used to indicate an influence of the parameter on an objective function, and the objective function is a loss function corresponding to the first gas turbine simulation model; If the sensitivity index of the parameter is greater than a preset threshold, the parameter is determined to be a parameter to be corrected.

15. The verification platform according to claim 13, characterized in that: The control logic test and verification system further includes a boundary model library; the boundary model library is specifically used to: The target parameters are input into a parameter boundary model to obtain a parameter operation boundary corresponding to the second gas turbine simulation model.

16. The verification platform according to claim 11, characterized in that: The control logic test and verification system is also used to: Connecting the control logic in the first SAMA diagram to the second gas turbine simulation model; injecting the combined operating condition parameters into the second gas turbine simulation model in sequence to obtain operating parameters of the second gas turbine simulation model during operation; determining whether the operating parameter exceeds the parameter operating boundary; If the operating parameter does not exceed the parameter operating boundary, it is determined that the control logic in the first SAMA diagram passes the verification.

17. The verification platform according to claim 11, characterized in that: The verification platform also includes a collaborative development system, which includes an IO point verification tool and a version control tool; The IO point verification tool is used to determine the IO signal requirement set and IO signal verification set corresponding to the first SAMA diagram; The IO point verification tool is further used to verify the IO signal verification set based on preset rules and the IO signal requirement set; If the verification is passed, the version control tool is further used to merge the first SAMA diagram with the second SAMA diagram to obtain a third SAMA diagram, wherein the second SAMA diagram is the SAMA diagram of the previous version.

18. The verification platform according to claim 17, characterized in that: The IO signal verification set includes a control logic IO signal set, a simulation model IO signal set, a boundary model IO signal set, and a working condition generated IO signal set; the IO point verification tool is specifically used to: Performing bidirectional matching on the control logic IO signal set based on the IO signal requirement set to obtain a first verification result; Performing bidirectional matching on the simulation model IO signal set based on the IO signal requirement set to obtain a second verification result; Performing bidirectional matching on the boundary model IO signal set based on the IO signal requirement set to obtain a third verification result; Performing a one-way match on the working condition generated IO signal set based on the IO signal requirement set to obtain a fourth verification result; If there are no abnormal IO points in the first verification result, the second verification result, the third verification result, and the fourth verification result, the verification is passed; Otherwise, the verification fails.

19. The verification platform according to claim 17, characterized in that: The version control tool is specifically used for: determining a first branch version of the first SAMA graph and a second branch version of the second SAMA graph; Performing conflict detection on the first branch version and the second branch version to obtain a conflict detection result; If the conflict detection result is that there is no conflict, the first branch version and the second branch version are merged to obtain a third SAMA graph.

20. The verification platform according to claim 17, characterized in that: The version control tool is also used to: Get the target index position; The cached SAMA graph of the baseline version is applied sequentially in the version iteration order using the stored incremental codes until the target index position is reached, thereby obtaining the fourth SAMA graph of the target index position, wherein the incremental codes are used to indicate the difference operator between adjacent versions.

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