A heavy-duty gas turbine control logic verification method and verification platform

Abstract

The application discloses a heavy-duty gas turbine control logic verification method and a verification platform, and comprises the following steps: obtaining a first SAMA graph of heavy-duty gas turbine control logic; generating combined working condition parameters under multiple different working conditions; checking a first gas turbine simulation model to obtain a second gas turbine simulation model after checking; determining a parameter operation boundary corresponding to the second gas turbine simulation model; verifying the control logic in the first SAMA graph based on the parameter operation boundary, the combined working condition parameters and the second gas turbine simulation model to obtain a control logic verification result. The application realizes the automatic verification of the control logic under multiple levels and wide range working conditions in the design stage, determines and modifies the control logic design defects in advance, improves the verification coverage and verification efficiency, makes the verification result more accurate, and improves the development efficiency and reliability of the gas turbine control logic.

Description

Technical Field

[0001] This invention relates to the field of gas turbine verification technology, and in particular to a method and platform for verifying the control logic of a heavy-duty gas turbine. Background Technology

[0002] As a core piece of equipment in the energy and power sector, the reliability and completeness of the control logic of gas turbines directly affect the safety and reliability of unit operation. With the increasing complexity of gas turbine systems and the diversification of operating conditions, the control logic needs to achieve precise coordination of the dynamic characteristics of various key equipment, components, and the overall system, and ensure stable control performance and rapid response capabilities under complex conditions such as extreme environments and component performance degradation, thereby ensuring the stable operation of the gas turbine.

[0003] Related technologies utilize graphical programming tools such as SAMA diagrams to functionally modularize the logic design of gas turbine control, and then manually write and debug the control strategy. However, existing verification mainly relies on hardware-in-the-loop (HIL) simulation platforms combined with simplified mathematical models for limited operating condition testing, which is insufficient to comprehensively cover the multi-dimensional parameter coupling scenarios that may occur throughout the entire life cycle of a gas turbine, resulting in inadequate verification coverage. Furthermore, the accuracy of simulation models under complex operating conditions is difficult to guarantee, and test case generation depends on manual methods, resulting in limited coverage and low automation, leading to low verification efficiency and difficulty in fully demonstrating the effectiveness of the control logic under a wide range of complex operating conditions, resulting in inaccurate verification results. Summary of the Invention

[0004] This invention provides a method and platform for verifying the control logic of heavy-duty gas turbines, in order to solve the technical problems of insufficient verification coverage, low verification efficiency and inaccurate verification results in the prior art.

[0005] To address this, the present invention proposes a method for verifying the control logic of a heavy-duty gas turbine. This method utilizes combined operating parameters under various operating conditions, parameter operating boundaries, and a verified second gas turbine simulation model to verify the control logic in the first SAMA diagram, obtaining the control logic verification results. 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 modification of control logic design defects. This improves the verification coverage and efficiency, resulting in more accurate verification results and enhancing the development efficiency and reliability of the gas turbine control logic.

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

[0007] To achieve the above objectives, the present invention provides a method for verifying the control logic of a heavy-duty gas turbine, comprising:

[0008] Obtain the first SAMA diagram of the control logic for a heavy-duty gas turbine;

[0009] Generate combined operating parameters under various working conditions;

[0010] The first gas turbine simulation model was verified to obtain the verified second gas turbine simulation model.

[0011] Determine the parameter operating boundaries corresponding to the second gas turbine simulation model;

[0012] Based on the parameter operating boundary, the combined operating condition parameters, and the second gas turbine simulation model, the control logic in the first SAMA diagram is verified to obtain the control logic verification result.

[0013] The heavy-duty gas turbine control logic verification method of this invention may also have the following additional technical features:

[0014] In this embodiment of the invention, generating combined operating parameters under various different operating conditions includes:

[0015] Generate environmental parameters and adjustment coefficients for various operating conditions;

[0016] Based on the environmental parameters and the adjustment coefficients, combined operating parameters for various different operating conditions are generated using the LHS method.

[0017] In this embodiment of the invention, the step of verifying the first gas turbine simulation model to obtain the verified second gas turbine simulation model includes:

[0018] Determine the parameters to be corrected in the first gas turbine simulation model;

[0019] Determine the gradient calculation result of the parameter to be corrected;

[0020] 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.

[0021] The target parameters are input into the first gas turbine simulation model to obtain the verified second gas turbine simulation model.

[0022] In this embodiment of the invention, determining the parameters to be corrected in the first gas turbine simulation model includes:

[0023] Calculate the sensitivity index of each parameter in the first gas turbine simulation model, wherein the sensitivity index is used to indicate the degree of influence of the parameter on the objective function, and the objective function is the loss function corresponding to the first gas turbine simulation model;

[0024] If the sensitivity index of the parameter is greater than a preset threshold, then the parameter is determined to be a parameter to be corrected.

[0025] In this embodiment of the invention, determining the parameter operating boundary corresponding to the second gas turbine simulation model includes:

[0026] The target parameters are input into the parameter boundary model to obtain the parameter operating boundary corresponding to the second gas turbine simulation model.

[0027] In this embodiment of the invention, the step of verifying the control logic in the first SAMA diagram based on the parameter operating boundary, the combined operating condition parameters, and the second gas turbine simulation model to obtain the control logic verification result includes:

[0028] Integrate the control logic from the first SAMA diagram into the second gas turbine simulation model;

[0029] The combined operating condition parameters are sequentially injected into the second gas turbine simulation model to obtain the operating parameters of the second gas turbine simulation model during operation;

[0030] Determine whether the operating parameters exceed the operating boundaries of the parameters;

[0031] If the operating parameters do not exceed the operating boundaries of the parameters, then the control logic in the first SAMA diagram is determined to have passed verification.

[0032] In this embodiment of the invention, when the control logic verification result is successful, the method further includes:

[0033] Determine the IO signal requirement set and IO signal verification set corresponding to the first SAMA diagram;

[0034] 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 and the second SAMA diagram are merged to obtain the third SAMA diagram, wherein the second SAMA diagram is the SAMA diagram of the previous version.

[0035] In this embodiment of the 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 verification of the IO signal verification set based on preset rules and the IO signal requirement set includes:

[0036] Based on the set of IO signal requirements, the set of control logic IO signals is bidirectionally matched to obtain the first verification result;

[0037] Based on the set of IO signal requirements, a bidirectional matching is performed on the set of IO signals in the simulation model to obtain a second verification result;

[0038] Based on the IO signal demand set, a bidirectional matching is performed on the boundary model IO signal set to obtain a third verification result;

[0039] Based on the IO signal demand set, a one-way matching is performed on the working condition generated IO signal set to obtain the fourth verification result;

[0040] If no abnormal I / O points are found 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.

[0041] In this embodiment of the invention, the step of merging the first SAMA diagram and the second SAMA diagram to obtain the third SAMA diagram includes:

[0042] Determine the first branch version of the first SAMA diagram and the second branch version of the second SAMA diagram;

[0043] Conflict detection is performed between the first branch version and the second branch version to obtain the conflict detection results;

[0044] If the conflict detection result indicates that there is no conflict, then the first branch version and the second branch version are merged to obtain the third SAMA graph.

[0045] In this embodiment of the invention, the method further includes:

[0046] Get the target index position;

[0047] The cached SAMA graph of the baseline version is used to apply the stored incremental codes sequentially according to the version iteration order until the target index position is reached, thereby obtaining the fourth SAMA graph at the target index position, wherein the incremental codes are used to indicate the difference operators between adjacent versions.

[0048] To achieve the above objectives, another aspect of the present invention proposes a heavy-duty gas turbine control logic verification platform, the verification platform comprising:

[0049] A control logic design system is used to obtain the first SAMA diagram of the control logic for heavy-duty gas turbines.

[0050] A control logic testing and verification system is used to generate combined operating parameters under various different working conditions.

[0051] A multi-level simulation system for gas turbines is used to verify the first gas turbine simulation model and obtain the verified second gas turbine simulation model.

[0052] The control logic test and verification system is also used to determine the parameter operating boundaries corresponding to the second gas turbine simulation model;

[0053] The control logic test and verification system is also used to verify the control logic in the first SAMA diagram based on the parameter operating boundary, the combined operating condition parameters, and the second gas turbine simulation model, and to obtain the control logic verification result.

[0054] In this embodiment of the invention, the control logic test and verification system includes a complex operating condition generation module; the complex operating condition generation module is specifically used for:

[0055] Generate environmental parameters and adjustment coefficients for various operating conditions;

[0056] Based on the environmental parameters and the adjustment coefficients, combined operating parameters for various different operating conditions are generated using the LHS method.

[0057] In this embodiment of the invention, the gas turbine multi-level simulation system includes a model verification tool; the model verification tool is specifically used for:

[0058] Determine the parameters to be corrected in the first gas turbine simulation model;

[0059] Determine the gradient calculation result of the parameter to be corrected;

[0060] 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.

[0061] The target parameters are input into the first gas turbine simulation model to obtain the verified second gas turbine simulation model.

[0062] In this embodiment of the invention, the model verification tool is further used for:

[0063] Calculate the sensitivity index of each parameter in the first gas turbine simulation model, wherein the sensitivity index is used to indicate the degree of influence of the parameter on the objective function, and the objective function is the loss function corresponding to the first gas turbine simulation model;

[0064] If the sensitivity index of the parameter is greater than a preset threshold, then the parameter is determined to be a parameter to be corrected.

[0065] In this embodiment of the invention, the control logic test and verification system further includes a boundary model library; the boundary model library is specifically used for:

[0066] The target parameters are input into the parameter boundary model to obtain the parameter operating boundary corresponding to the second gas turbine simulation model.

[0067] In this embodiment of the invention, the control logic test and verification system is further used for:

[0068] Integrate the control logic from the first SAMA diagram into the second gas turbine simulation model;

[0069] The combined operating condition parameters are sequentially injected into the second gas turbine simulation model to obtain the operating parameters of the second gas turbine simulation model during operation;

[0070] Determine whether the operating parameters exceed the operating boundaries of the parameters;

[0071] If the operating parameters do not exceed the operating boundaries of the parameters, then the control logic in the first SAMA diagram is determined to have passed verification.

[0072] In this embodiment of the invention, the verification platform further includes a collaborative development system, which includes an IO point verification tool and a version control tool;

[0073] The IO point verification tool is used to determine the IO signal demand set and IO signal verification set corresponding to the first SAMA diagram;

[0074] The IO point verification tool is also used to verify the IO signal verification set based on preset rules and the IO signal requirement set;

[0075] If the verification is successful, the version control tool is further used to merge the first SAMA diagram and the second SAMA diagram to obtain a third SAMA diagram, wherein the second SAMA diagram is the SAMA diagram of the previous version.

[0076] In this embodiment of the 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; the IO point verification tool is specifically used for:

[0077] Based on the set of IO signal requirements, the set of control logic IO signals is bidirectionally matched to obtain the first verification result;

[0078] Based on the set of IO signal requirements, a bidirectional matching is performed on the set of IO signals in the simulation model to obtain a second verification result;

[0079] Based on the IO signal demand set, a bidirectional matching is performed on the boundary model IO signal set to obtain a third verification result;

[0080] Based on the IO signal demand set, a one-way matching is performed on the working condition generated IO signal set to obtain the fourth verification result;

[0081] If no abnormal I / O points are found 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.

[0082] In this embodiment of the invention, the version control tool is specifically used for:

[0083] Determine the first branch version of the first SAMA diagram and the second branch version of the second SAMA diagram;

[0084] Conflict detection is performed between the first branch version and the second branch version to obtain the conflict detection results;

[0085] If the conflict detection result indicates that there is no conflict, then the first branch version and the second branch version are merged to obtain the third SAMA graph.

[0086] In this embodiment of the invention, the version control tool is further used for:

[0087] Get the target index position;

[0088] The cached SAMA graph of the baseline version is used to apply the stored incremental codes sequentially according to the version iteration order until the target index position is reached, thereby obtaining the fourth SAMA graph at the target index position, wherein the incremental codes are used to indicate the difference operators between adjacent versions.

[0089] The present invention discloses a method and platform for verifying the control logic of a heavy-duty gas turbine, comprising: acquiring a first SAMA diagram of the control logic of the heavy-duty gas turbine; generating combined operating parameters under various operating conditions; verifying a first gas turbine simulation model to obtain a verified second gas turbine simulation model; determining the 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, combined operating parameters, and the verified second gas turbine simulation model to obtain the control logic verification result. Therefore, the present invention utilizes combined operating parameters under various operating conditions, parameter operating boundaries, and the verified second gas turbine simulation model to verify the control logic in the first SAMA diagram, obtaining the control logic verification result. This allows for automated verification of the control logic under multiple levels and a wide range of operating conditions during the design phase, enabling early identification and modification of control logic design defects, improving verification coverage and efficiency, resulting in more accurate verification results, and enhancing the development efficiency and reliability of the gas turbine control logic.

[0090] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0091] 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 taken in conjunction with the accompanying drawings, wherein:

[0092] Figure 1 This is a flowchart illustrating the control logic verification method for heavy-duty gas turbines according to an embodiment of the present invention.

[0093] Figure 2 This is a flowchart illustrating the control logic verification method for heavy-duty gas turbines according to an embodiment of the present invention.

[0094] Figure 3 This is a flowchart illustrating the control logic verification method for heavy-duty gas turbines according to an embodiment of the present invention.

[0095] Figure 4 This is a flowchart illustrating the control logic verification method for heavy-duty gas turbines according to an embodiment of the present invention.

[0096] Figure 5 This is a schematic diagram of the structure of a heavy-duty gas turbine control logic verification platform according to an embodiment of the present invention. Detailed Implementation

[0097] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0098] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0099] The following description, with reference to the accompanying drawings, illustrates a method and platform for verifying the control logic of a heavy-duty gas turbine according to an embodiment of the present invention.

[0100] Figure 1 This is a flowchart illustrating the heavy-duty gas turbine control logic verification method according to an embodiment of the present invention.

[0101] like Figure 1 As shown, the method may include the following steps:

[0102] Step 101: Obtain the first SAMA diagram of the heavy-duty gas turbine control logic.

[0103] In this embodiment of the invention, the requirements analysis and conceptual design of the control logic of a heavy-duty gas turbine can be obtained, and the first SAMA diagram corresponding to the control logic can be generated using the various functional components contained in the logic function library.

[0104] In this embodiment of the invention, the logic function library contains the functional components required for the design of gas turbine control logic, which are used to implement the required logic function description.

[0105] In this embodiment of the invention, the logic function library includes at least an analog quantity arithmetic library, a digital quantity arithmetic library, an advanced algorithm library, and a signal library.

[0106] In this embodiment of the invention, the analog quantity arithmetic library includes at least the functional modules for various elementary mathematical operations, size selection, quality judgment, saturation, dead zone, differentiation, and integration.

[0107] In this embodiment of the invention, the digital quantity arithmetic library includes at least functional modules such as AND, OR, NOT operations and high / low level counting.

[0108] In this embodiment of the invention, the advanced algorithm library contains custom algorithm blocks, which can implement complex functions and algorithms (such as matrix operations and complex timing sequences) by writing code in different languages, and supports encapsulation. The different languages ​​can include C, C++, and Fortran.

[0109] In this embodiment of the invention, the signal library includes at least IO signal blocks, intermediate point signal blocks, and alarm signal blocks, wherein the IO signal blocks should contain information such as signal name, extension name, signal description, signal type, range, and dimensions.

[0110] Step 102: Generate combined operating parameters for various different operating conditions.

[0111] In this embodiment of the invention, when verifying the control logic, it is necessary to generate a combination of operating condition parameters under various different operating conditions, so as to improve the verification coverage by using the combination of operating condition parameters under various different operating conditions.

[0112] In this embodiment of the invention, the method for generating combined operating parameters under various different operating conditions may include the following steps:

[0113] Step 1021: Generate environmental parameters and adjustment coefficients for various operating conditions.

[0114] In this embodiment of the invention, the aforementioned combined operating condition parameters may include complex combinations of operating conditions under different atmospheric environments and different performance degradation scenarios. The environmental parameters may include atmospheric temperature, humidity, and pressure. Furthermore, environmental parameters can be injected as input parameters into the first gas turbine simulation model. Also, different performance degradation scenarios can be addressed by adjusting the coefficients... ( The corresponding parameters of the first gas turbine simulation model are injected to regulate performance degradation in the form of a product of environmental parameters and adjustment coefficients. Furthermore, the different performance degradation conditions mentioned above can include reduced compressor flow, decreased compressor efficiency, decreased combustion efficiency, and decreased turbine efficiency.

[0115] In this embodiment of the invention, environmental parameters and adjustment coefficients for various operating conditions can be generated through a database.

[0116] Step 1022: Based on environmental parameters and adjustment coefficients, generate combined operating parameters for various different operating conditions using the LHS method.

[0117] In this embodiment of the invention, due to environmental parameters With adjustment coefficient Constitutes a dimension Using a full space traversal approach for the test space would make the testing process take a very long time.

[0118] In this embodiment of the invention, combined operating condition parameters under various working conditions can be generated using the LHS method based on environmental parameters and adjustment coefficients. This achieves a complex operating condition that is uniformly distributed across all dimensions of the overall test space, thereby improving the verification coverage and reducing the time required to generate combined operating condition parameters.

[0119] For example, when 100 test conditions are generated by selecting combinations of atmospheric temperature, compressor efficiency decrease, combustion efficiency decrease, and turbine efficiency decrease, the atmospheric temperature... Set the value range to ℃, efficiency reduction of the three major components Set the value range to Furthermore, the four operating condition parameter dimensions are independently and randomly sorted within their effective intervals to obtain random sequences of the four parameters, each containing 100 elements. This process must ensure that the parameters are uncorrelated. Further, the random sequences of the four parameters are aligned sequentially to obtain... Within the test space, 100 sets of test conditions are generated to ensure a uniform distribution of each parameter dimension. Table 1 shows the complex combination of test conditions parameters and adjustment coefficients corresponding to various environmental parameters under different conditions in this embodiment of the invention.

[0120] Table 1

[0121]

[0122] In this embodiment of the invention, the aforementioned 100 sets of combined operating condition parameters can uniformly cover more than 99% of the parameter space (95% confidence level), while compared to a full-range scan (assuming 10 levels per parameter, which would require 10...). 4 The testing conditions greatly improve the efficiency of testing and verification.

[0123] Step 103: Verify the first gas turbine simulation model to obtain the verified second gas turbine simulation model.

[0124] In this embodiment of the invention, before verifying the control logic in the first SAMA diagram, it is necessary to verify 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 do not become invalid due to the distortion of the model.

[0125] In this embodiment of the invention, the aforementioned first gas turbine simulation model may include an equipment-level model, a component-level model, and a system-level model. The equipment-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 derived directly from technical manuals and bench test calibration data. The component-level model is constructed based on aerodynamic thermodynamic characteristic lines, including various characteristic lines from the three main components (such as the pressure ratio-flow characteristic surface of the compressor and the curve of turbine efficiency versus expansion ratio). These characteristic lines can be obtained in advance through finite element simulation or prototype testing during the gas turbine design phase and encapsulated as pluggable function modules. The system-level model couples the characteristic lines of each component using the lumped parameter method to construct a real-time simulation environment at the whole-machine level, capable of simulating the full-condition thermodynamic cycle process of the gas turbine from start-up, load variation to shutdown.

[0126] In this embodiment of the invention, the method for verifying a first gas turbine simulation model to obtain a verified second gas turbine simulation model may include: determining the parameters to be corrected in the first gas turbine simulation model, determining the gradient calculation results of the parameters to be corrected, iteratively updating the parameters to be corrected using the gradient descent method based on the gradient calculation results until the 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 part will be described in detail in subsequent embodiments.

[0127] Step 104: Determine the parameter operating boundaries corresponding to the second gas turbine simulation model.

[0128] In this embodiment of the invention, after obtaining the verified second gas turbine simulation model through the above steps, the parameter operating 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 operating boundary.

[0129] In this embodiment of the invention, the method for determining the parameter operating boundary corresponding to the second gas turbine simulation model may include: inputting the target parameters into the parameter boundary model to obtain the parameter operating boundary corresponding to the second gas turbine simulation model.

[0130] In this embodiment of the invention, the above-mentioned parameter boundary model includes at least the minimum IGV boundary model, the maximum IGV boundary model, the minimum T4 boundary model, the maximum T4 boundary model, the maximum T3 boundary model, the combustion chamber quenching equivalence ratio boundary model, and the combustion chamber backfire equivalence ratio boundary model.

[0131] In this embodiment of the invention, each of the above-mentioned parameter boundary models embeds a verified independent gas turbine main unit system model, whose model parameters are updated synchronously with the target parameters in the second gas turbine simulation model. The embedded gas turbine main unit system models in each of the above-mentioned parameter boundary models operate stably under their respective defined boundary conditions and output the parameter operating boundaries corresponding to key gas turbine parameters (such as power, exhaust temperature, combustion chamber outlet temperature, etc.). In this embodiment of the invention, the above-mentioned parameter operating boundaries can be parameter operating ranges.

[0132] Step 105: Based on the parameter operating boundary, combined operating condition parameters, and the second gas turbine simulation model, verify the control logic in the first SAMA diagram to obtain the control logic verification results.

[0133] In this embodiment of the invention, after obtaining the parameter operating boundary, combined operating condition 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 boundary, combined operating condition parameters and the second gas turbine simulation model to obtain the control logic verification result.

[0134] In this embodiment of the invention, the method for verifying the control logic in the first SAMA diagram based on the parameter operating boundary, combined operating condition parameters, and the second gas turbine simulation model, and obtaining the control logic verification result, may include the following steps:

[0135] Step 1051: Connect the control logic in the first SAMA diagram to the second gas turbine simulation model.

[0136] Step 1052: The combined operating condition parameters are sequentially injected into the second gas turbine simulation model to obtain the operating parameters of the second gas turbine simulation model during operation.

[0137] In this embodiment of the invention, combined operating condition parameters are sequentially injected into the second gas turbine simulation model. The control logic in the first SAMA diagram controls the operation of the second gas turbine simulation model based on these combined operating condition parameters, thereby controlling the operating parameters of the second gas turbine simulation model during operation. In this embodiment of the invention, the operating parameters can be one or more of the aforementioned key parameters.

[0138] Step 1053: Determine whether the running parameters exceed the parameter running boundaries.

[0139] In this embodiment of the 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 boundary, so as to determine whether the control logic in the first SAMA diagram passes the verification.

[0140] In this embodiment of the invention, if none of the operating parameters exceed 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.

[0141] Step 1054: If the operating parameters do not exceed the parameter operating boundaries, then the control logic in the first SAMA diagram is verified.

[0142] In this embodiment of the 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 the control logic in the first SAMA diagram is determined to have passed the verification.

[0143] The heavy-duty gas turbine control logic verification method of this invention includes: acquiring a first SAMA diagram of the heavy-duty gas turbine control logic; generating combined operating parameters under various operating conditions; verifying the first gas turbine simulation model to obtain a verified second gas turbine simulation model; determining the 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, combined operating parameters, and the second gas turbine simulation model to obtain control logic verification results. Therefore, this invention utilizes combined operating parameters under various operating conditions, parameter operating boundaries, and the verified second gas turbine simulation model to verify the control logic in the first SAMA diagram, obtaining control logic verification results. This allows for automated verification of the control logic under multiple levels and a wide range of operating conditions during the design phase, enabling early identification and modification of control logic design defects, improving verification coverage and efficiency, resulting in more accurate verification results, and enhancing the development efficiency and reliability of gas turbine control logic.

[0144] In this embodiment of the invention, as a detailed explanation of step 103, such as Figure 2 As shown, it may also include:

[0145] Step 1031: Determine the parameters to be corrected in the first gas turbine simulation model.

[0146] In this embodiment of the invention, the method for determining the parameters to be corrected in the first gas turbine simulation model may include the following steps:

[0147] Step 10311: Calculate the sensitivity index of each parameter in the first gas turbine simulation model.

[0148] In this embodiment of the invention, the sensitivity index is used to indicate the degree of influence of the parameters on the objective function, which is the loss function corresponding to the first gas turbine simulation model.

[0149] In this embodiment of the 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:

[0150]

[0151] in, To remove parameters The subsequent set of other candidate parameters, For fixed parameters J is the conditional expectation of the objective function, where J is the objective function and Var is the variance.

[0152] The simulation model of the first gas turbine was established using the lumped parameter method, and the corresponding model state and output can be abstracted into state equations represented by nonlinear functions. With output equation When actual measurement data or design data After input, the objective function J is defined as the mean square error of both:

[0153]

[0154] Where x(t) is the state vector, the state variable changes with time, u(t) is the control input vector at time t, and t0 and t... f It is the time range, and f and g are state equations represented by nonlinear functions.

[0155] Step 10312: If the sensitivity index of the parameter is greater than the preset threshold, then the parameter is determined to be a parameter to be corrected.

[0156] In this embodiment of the invention, after obtaining the sensitivity index of each parameter through the above steps, it can be determined whether the parameter needs to be corrected based on the sensitivity index of the parameter.

[0157] In this embodiment of the invention, if the sensitivity index of a parameter is greater than a preset threshold, then the parameter is determined to be a parameter to be corrected. The preset threshold can be set as needed, such as 0.01.

[0158] For example, assuming a preset threshold of 0.01, determine the set of all parameters to be corrected. Table 2 shows examples of sensitivity index judgment criteria. Based on these examples, the parameters to be corrected can be determined.

[0159] Table 2

[0160]

[0161] Step 1032: Determine the gradient calculation results of the parameters to be corrected.

[0162] In this embodiment of the 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. Parameters to be corrected Variational analysis is performed to obtain the gradient calculation results of the parameters to be corrected.

[0163] In this embodiment of the 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:

[0164] ,

[0165] Here, g is a nonlinear function y(t)=g[x(t), u(t)], which is differentiated by the function g with respect to the state vector x.

[0166] In this embodiment of the invention, the above-mentioned adjoint equation describes the backpropagation of the error gradient along time.

[0167] In this embodiment of the invention, a small perturbation is introduced into the adjoint equation. Parameters to be corrected Variational analysis was performed to obtain the gradient calculation results of the parameters to be corrected:

[0168]

[0169] The gradient calculation results mentioned above can directly reflect the contribution of the parameters to the output error.

[0170] Step 1033: 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.

[0171] In this embodiment of the invention, the gradient calculation results of each parameter 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 parameter is obtained.

[0172] In this embodiment of the invention, the parameters to be corrected are iteratively updated using the gradient descent method, and the updated parameters are:

[0173] ,

[0174] in, To set the learning rate.

[0175] In this embodiment of the invention, the target parameter is obtained when the output result corresponding to the updated parameter tends to a steady state and converges.

[0176] Step 1034: Input the target parameters into the first gas turbine simulation model to obtain the verified second gas turbine simulation model.

[0177] In this embodiment of the 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 the verified second gas turbine simulation model.

[0178] In this embodiment of the invention, the first gas turbine simulation model is verified through the above steps to obtain the 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, so as to ensure that the test verification results after the combined operating condition parameters are injected do not become invalid due to the distortion of the model.

[0179] In another embodiment of the present invention, the above-described heavy-duty gas turbine control logic verification method, such as Figure 3 As shown, the above method may further include:

[0180] Step 301: Obtain the first SAMA diagram of the heavy-duty gas turbine control logic.

[0181] Step 302: Generate combined operating parameters for various different operating conditions.

[0182] Step 303: Verify the first gas turbine simulation model to obtain the verified second gas turbine simulation model.

[0183] Step 304: Determine the parameter operating boundaries corresponding to the second gas turbine simulation model.

[0184] Step 305: Based on the parameter operating boundary, combined operating condition parameters, and the second gas turbine simulation model, verify the control logic in the first SAMA diagram to obtain the control logic verification results.

[0185] For a detailed description of steps 301 to 305, please refer to the above embodiments. The embodiments of the present invention will not be repeated here.

[0186] Step 306: When the control logic verification result is that the verification is passed, determine the IO signal requirement set and IO signal verification set corresponding to the first SAMA diagram.

[0187] In this embodiment of the invention, the above-mentioned IO signal demand set can be the actual IO signal demand set.

[0188] In this embodiment of the invention, the above-mentioned 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.

[0189] In this embodiment of the 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 invention, the corresponding control logic IO signal set, simulation model IO signal set, boundary model IO signal set, and operating condition generated IO signal set can be obtained through the various control logic design results, gas turbine simulation models at each level, boundary models, and complex operating condition generation modules.

[0190] In this embodiment of the invention, the set of IO signal requirements can be determined by the list of IO point requirements involved in the gas turbine control system.

[0191] Step 307: Verify the IO signal verification set based on preset rules and the IO signal requirement set. If the verification passes, merge the first SAMA diagram and the second SAMA diagram to obtain the third SAMA diagram.

[0192] In this embodiment of the invention, the method for verifying the IO signal verification set based on preset rules and the IO signal requirement set may include the following steps:

[0193] Step 3071: Perform bidirectional matching of the control logic IO signal set based on the IO signal demand set to obtain the first verification result;

[0194] Step 3072: Perform bidirectional matching of the simulation model's IO signal set based on the IO signal demand set to obtain the second verification result;

[0195] Step 3073: Perform bidirectional matching of the boundary model IO signal set based on the IO signal demand set to obtain the third verification result;

[0196] Step 3074: Perform one-way matching of the IO signal set generated by the working condition based on the IO signal demand set to obtain the fourth verification result;

[0197] Step 3075: If no abnormal I / O points are found in the first, second, third, and fourth verification results, the verification passes; otherwise, the verification fails.

[0198] In this embodiment of the invention, the structured data elements of the IO quantity in the control logic IO signal set can be converted into string format and then bidirectionally matched with the character content information in the IO signal demand set.

[0199] In this embodiment of the invention, a bidirectional matching is performed between the structured data elements and the information of the IO point signal name, extension, signal type, range, and dimension 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 and error-free, the first verification result is considered verified.

[0200] In this embodiment of the invention, the bidirectional matching can include forward matching and reverse matching. Forward matching can be used to filter out actual I / O points that were incorrectly designed or overlooked during the logic design process, while reverse matching can be used to filter out I / O points that no longer need to enter the subsequent logic design or testing process due to version iteration or other reasons.

[0201] In this embodiment of the invention, the method for matching the simulation model IO signal set and the boundary model IO signal is the same as the method steps described above, and will not be repeated here.

[0202] In this embodiment of the invention, the above-mentioned one-way matching of the operating condition generated IO signal set based on the IO signal demand set is required to satisfy that the operating condition generated IO signal set is a subset of the IO signal demand set. That is, the IO signal demand set needs to completely include all IOs of the operating condition generated IO signal set, but the operating condition generated IO signal set does not necessarily include all IOs of the IO signal demand set.

[0203] In this embodiment of the invention, if the verification is confirmed 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. The second SAMA diagram is the previous version of the SAMA diagram; that is, the second SAMA diagram corresponds to the version that was previously stored.

[0204] In this embodiment of the invention, the method for merging the first SAMA graph and the second SAMA graph to obtain the third SAMA graph may include: determining a first branch version of the first SAMA graph and a second branch version of the second SAMA graph, and performing conflict detection on the first branch version and the second branch version to obtain a conflict detection result; if the conflict detection result indicates that there is no conflict, then merging the first SAMA graph and the second SAMA graph to obtain the third SAMA graph. This part will be described in detail in subsequent embodiments.

[0205] In this embodiment of the invention, the above method may include the following steps:

[0206] Step 308: Obtain the target index location.

[0207] Step 309, using the cached SAMA graph of the baseline version The stored incremental codes are applied sequentially according to version iteration order until the target index position is reached, resulting in the fourth SAMA graph at the target index position. .

[0208] In this embodiment of the invention, the above-described incremental encoding is used to indicate the difference operator between adjacent versions.

[0209] In an embodiment of the present invention, ,in, The sum of incremental codes to reach the target index position, where N is the number of incremental codes to be merged, and the baseline version is G0.

[0210] In this embodiment of the invention, the version backtracking function can be realized through the above steps 308 to 309 to determine the fourth SAMA diagram that needs to be backtracked.

[0211] In this embodiment of the invention, the above steps can be used to manage multiple branch versions generated during collaborative development, realize the automatic merging of control logic design changes and the tracing of historical versions, improve logic design efficiency, and reduce the time cost of manual verification.

[0212] In this embodiment of the invention, as a detailed explanation of step 307, such as Figure 4 As shown, it may also include:

[0213] Step 401: Determine the first branch version of the first SAMA diagram and the second branch version of the second SAMA diagram.

[0214] In this embodiment of the invention, the first branch version of the first SAMA diagram can be determined by the parameters in the control logic, simulation model, and boundary model of the first SAMA diagram.

[0215] In this embodiment of the invention, the second branch version of the second SAMA diagram can be determined by the parameters in the control logic, simulation model, and boundary model of the second SAMA diagram.

[0216] Step 402: Perform conflict detection on the first branch version and the second branch version to obtain the conflict detection results.

[0217] In this embodiment of the 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.

[0218] In this embodiment of the invention, the method for performing conflict detection between the first branch version and the second branch version to obtain conflict detection results may include:

[0219] Step 4021: Upload the SAMA graph branch of the first branch version to the version snapshot database, and store the SAMA graph branch logical chain state of the snapshot in the format of the first directed graph. ;

[0220] In this embodiment of the invention, the first directed graph is as follows: ,in, For component function nodes The set, The set of all nodes where signal flow exists ( express arrive (existence of signal flow) Node attribute mapping function .

[0221] Step 4022: Obtain the second directed graph of the second branch version from the version snapshot database. ;

[0222] Step 4023: Determine whether the same node in the first directed graph and the second directed graph satisfies the conflict detection criteria. If the conflict detection criteria are met, a conflict is determined to exist; otherwise, no conflict is determined to exist. The conflict detection criteria can be:

[0223] ,

[0224] Step 403: If the conflict detection result is that there is no conflict, then merge the first branch version and the second branch version to obtain the third SAMA graph.

[0225] In this embodiment of the invention, the method for merging the first branch version and the second branch version to obtain the third SAMA graph may include: determining the incremental code 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 code to obtain the third SAMA graph.

[0226] In this embodiment of the invention, the method for determining the incremental encoding of the first branch version and the second branch version may include the following steps:

[0227] Step 1: Determine the first representation of the multiple modification actions in the first directed graph corresponding to the first branch version, and the second representation of the second directed graph corresponding to the second branch version;

[0228] Step 2: Calculate the difference operator between adjacent versions based on the first representation and the second representation to obtain the incremental code.

[0229] In this embodiment of the invention, the aforementioned modification actions include adding actions, deleting actions, and modifying actions.

[0230] In an embodiment of the present invention, when a functional component node is added to the first directed graph... and assign it initial properties. When (e.g., signal name, range, etc.), add the first representation corresponding to the action. for:

[0231] ,

[0232] In an embodiment of the present invention, when a functional component node is deleted from the first directed graph... When deleting all associated signal streams, the first representation corresponding to the deletion action is... for:

[0233] ,

[0234] In an embodiment of the present invention, when a node is modified in the first directed graph... A certain attribute When the value is changed, update from the old value to the new value. The first representation corresponding to the modification action for:

[0235]

[0236] In this embodiment of the invention, the difference operator between adjacent versions is calculated using the first representation of the addition action, the first representation of the deletion action, the first representation of the modification action, and the second representation of the addition action, the second representation of the deletion action, and the second representation of the modification action in the second directed graph, for incremental encoding. Formal storage,

[0237]

[0238] Among them, the smallest unit of change operation between versions Described from version arrive The specific actions to modify the graph structure and attributes include adding or deleting component functional nodes and modifying their attributes.

[0239] In this embodiment of the invention, after obtaining the incremental codes of the first branch version and the second branch version through the above steps, the incremental codes of the first branch version can be used as a basis for further processing. Incremental coding with the second branch version Automatic merging of multiple branches yields a third SAMA graph.

[0240] In this embodiment of the invention, the process of merging the incremental codes of different branch versions can be represented as follows:

[0241]

[0242] Among them, graph difference application operators It can represent the transition from an old version to a new version.

[0243] In this embodiment of the invention, if the conflict detection result indicates that a conflict exists, manual intervention should be performed to determine the conflicting part, re-upload the version snapshot database, and re-perform the conflict detection. Based on this, the conflict detection also has the function of locating the conflicting functional component nodes and attribute values ​​in the SAMA diagram.

[0244] In this embodiment of the invention, the above steps can be used to manage multiple branch versions generated during collaborative development, realize the automatic merging of control logic design changes and the tracing of historical versions, improve logic design efficiency, and reduce the time cost of manual verification.

[0245] To achieve the above embodiments, such as Figure 5 As shown, this embodiment also provides a heavy-duty gas turbine control logic verification platform, which may include:

[0246] Control logic design system 501 is used to obtain the first SAMA diagram of the control logic of heavy-duty gas turbine;

[0247] The control logic test and verification system 502 is used to generate combined operating parameters under various different operating conditions.

[0248] The gas turbine multi-level simulation system 503 is used to verify the first gas turbine simulation model and obtain the verified second gas turbine simulation model.

[0249] The control logic test and verification system 502 is also used to determine the parameter operating boundaries corresponding to the second gas turbine simulation model;

[0250] The control logic test and verification system 502 is also used to verify the control logic in the first SAMA diagram based on the parameter operating boundary, combined operating condition parameters, and the second gas turbine simulation model, and to obtain the control logic verification results.

[0251] In this embodiment of the invention, the control logic design system 501 mainly consists of modules such as a logic function library, which supports logic design.

[0252] In this embodiment of the invention, the logic function library contains the functional components required for the design of gas turbine control logic, which are used to implement the required logic function description.

[0253] In this embodiment of the invention, the logic function library includes at least an analog quantity arithmetic library, a digital quantity arithmetic library, an advanced algorithm library, and a signal library.

[0254] In this embodiment of the invention, the analog quantity calculation library includes at least various elementary mathematical operations, size selection, quality judgment, saturation, dead zone, differentiation, integration and other functional modules.

[0255] In this embodiment of the invention, the digital quantity arithmetic library includes at least functional modules such as AND, OR, NOT operations, and high / low level counting.

[0256] In this embodiment of the invention, the advanced algorithm library contains custom algorithm blocks, which can be used to implement complex functions and algorithms, such as matrix operations and complex timing sequences, by writing C, C++, Fortran and other code, and supports encapsulation.

[0257] In this embodiment of the 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, and dimensions.

[0258] In this embodiment of the 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 used for:

[0259] Generate environmental parameters and adjustment coefficients for various operating conditions;

[0260] Based on environmental parameters and adjustment coefficients, combined operating parameters for various operating conditions are generated using the LHS method.

[0261] In this embodiment of the 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 pressure) and different component performance degradation conditions (including reduced compressor flow, decreased compressor efficiency, decreased combustion efficiency, and decreased turbine efficiency). The module uses a combined coverage algorithm (such as the LHS method) to generate complex operating conditions with uniformly distributed parameter dimensions and injects them into the gas turbine multi-level simulation system to achieve a combination of complex operating conditions covering the entire operating condition range.

[0262] In this embodiment of the invention, the above-mentioned gas turbine multi-level simulation system 503 includes a model verification tool 5031; the above-mentioned model verification tool 5031 is specifically used for:

[0263] Determine the parameters to be corrected in the first gas turbine simulation model;

[0264] Determine the gradient calculation results for the parameters to be corrected;

[0265] 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.

[0266] The target parameters are input into the first gas turbine simulation model to obtain the verified second gas turbine simulation model.

[0267] In this embodiment of the invention, the gas turbine multi-level simulation system 503 constructs a full-dimensional model system covering equipment level, component level, and whole machine level. It interfaces with the control logic designed in the control logic design system 501 through a data interface and interacts with the control logic testing 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 in upstream information such as experimental data and design data, providing a high-fidelity dynamic environment for the hierarchical verification of the designed control logic.

[0268] In this embodiment of the invention, the gas turbine multi-level simulation system 503 also includes a multi-level model library.

[0269] In this embodiment of the invention, a multi-level model library calls models of different precision levels according to logical verification requirements to achieve a dynamic balance between simulation accuracy and verification efficiency. Among them, the equipment-level model can accurately reproduce the dynamic characteristics of actuators and sensors, such as the flow-opening hysteresis curve of the fuel valve and the step response time of the 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 pressure ratio-flow characteristic surface of the compressor and the curve of turbine efficiency changing with expansion ratio). The above characteristic lines are obtained in advance through finite element simulation or prototype test during the gas turbine design stage and encapsulated 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 at the whole machine level, which can simulate the full-condition thermodynamic cycle process of the gas turbine from start-up, load change to shutdown.

[0270] In this embodiment of the invention, the model verification tool 5031 can adopt a hierarchical verification strategy to perform differentiated calibration on the characteristics and data observability of models at different levels, so as to converge the difference between the simulation output and the upstream input design or experimental data, and make the simulation models at different levels closer to the actual performance.

[0271] In this embodiment of the invention, the above-mentioned device-level model can be constructed based on physical mechanism equations, and its parameters can be directly fixed by factory calibration data. Furthermore, the dynamic response error can be automatically compensated by a closed-loop control algorithm, thus eliminating the need for frequent verification.

[0272] In this embodiment of the invention, for the above-mentioned component-level model, after the initial characteristic line is imported, when design iteration updates or operational state drift occur (such as blade fouling causing pressure ratio-flow characteristic shift), a proxy model-assisted local fitting method is used for verification, and interpolation correction is performed on key sections of the characteristic line to ensure the fidelity of the component model in typical operating conditions.

[0273] In this embodiment of the invention, for the above-mentioned system-level model, the model verification tool 5031 can also be used for:

[0274] Calculate the sensitivity index of each parameter in the simulation model of the first gas turbine, where the sensitivity index is used to indicate the degree of influence of the parameter on the objective function, and the objective function is the loss function corresponding to the simulation model of the first gas turbine.

[0275] If the sensitivity index of a parameter is greater than a preset threshold, then the parameter is determined to be a parameter to be corrected.

[0276] In this embodiment of the invention, the control logic test and 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 operating boundary corresponding to the second gas turbine simulation model.

[0277] In this embodiment of the invention, the boundary model library 5022 is based on the gas turbine operation control concept and protection requirements, providing various control boundaries for the control logic test and verification system 502. Specifically, the boundary model library 5022 includes at least the minimum IGV boundary model, the maximum IGV boundary model, the minimum T4 boundary model, the maximum T4 boundary model, the maximum T3 boundary model, the combustion chamber flameout equivalence ratio boundary model, and the combustion chamber flashback equivalence ratio boundary model.

[0278] In this embodiment of the invention, each boundary model embeds an independent gas turbine main unit system model that has undergone verification. The verification parameters are the target parameters transmitted by the model verification tool in the gas turbine multi-level simulation system and are updated synchronously with it. In this embodiment of the invention, the embedded gas turbine models in each boundary model operate stably on their respective defined boundary conditions and output the operating boundary lines formed by the key parameters of the gas turbine (such as power, exhaust temperature, combustion chamber outlet temperature, etc.).

[0279] In this embodiment of the invention, the control logic test and verification system is further used for:

[0280] Integrate the control logic from the first SAMA diagram into the second gas turbine simulation model;

[0281] The combined operating condition parameters are sequentially injected into the second gas turbine simulation model to obtain the operating parameters of the second gas turbine simulation model during operation;

[0282] Determine whether the operating parameters exceed the parameter operating boundaries;

[0283] If the operating parameters do not exceed the parameter operating boundaries, then the control logic in the first SAMA diagram is verified.

[0284] In this embodiment of the invention, the complex operating condition generation module sequentially injects combined operating condition parameters into the gas turbine multi-level simulation system and makes it run under the control logic in the first SAMA diagram accessed by the control logic design system. It judges whether the operating parameters of the second gas turbine simulation model 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 the control logic validity judgment result.

[0285] In this embodiment of the invention, the verification platform further includes a collaborative development system 504, which includes an IO point verification tool 5041 and a version control tool 5042.

[0286] IO point verification tool 5041 is used to determine the IO signal requirement set and IO signal verification set corresponding to the first SAMA diagram;

[0287] The IO point verification tool 5041 is also used to verify the IO signal verification set based on preset rules and the IO signal requirement set;

[0288] If the verification passes, version control tool 5042 is also used to merge the first SAMA diagram and the second SAMA diagram to obtain the third SAMA diagram, where the second SAMA diagram is the SAMA diagram of the previous version.

[0289] In this embodiment of the 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.

[0290] In this embodiment of the invention, the IO point verification tool 5041 is specifically used for:

[0291] Based on the set of IO signal requirements, a bidirectional matching of the set of control logic IO signals is performed to obtain the first verification result;

[0292] A second verification result is obtained by bidirectionally matching the IO signal set of the simulation model based on the IO signal demand set.

[0293] A third verification result is obtained by bidirectional matching of the boundary model IO signal set based on the IO signal demand set.

[0294] Based on the IO signal demand set, the IO signal set generated by the working condition is unidirectionally matched to obtain the fourth verification result;

[0295] If no abnormal I / O points are found in the first, second, third, and fourth verification results, the verification passes; otherwise, the verification fails.

[0296] In this embodiment of the invention, the IO point verification tool 5041 can perform bidirectional verification and validation of the IO signal blocks of various control logic design results, gas turbine multi-level simulation models, boundary models, and complex operating condition generation modules, as well as the IO point requirement list involved in the actual gas turbine control system.

[0297] In this embodiment of the 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 result can be extracted through a specific API interface, converted into string format, and then bidirectionally matched with the character content information in the actual IO requirement set.

[0298] In this embodiment of the invention, the verification process involves bidirectionally matching the structured data elements with the information such as the signal name, extension, signal type, range, and dimension of the IO points in the actual IO requirement set according to set rules. Forward matching can filter out actual IO points that were designed incorrectly or overlooked during the logic design process, while reverse matching can filter out IO points that no longer need to enter the subsequent logic design or testing process due to version iteration or other reasons. This is beneficial for releasing and optimizing the allocation of hardware resources.

[0299] In this embodiment of the invention, the version control tool 5042 is specifically used for:

[0300] Determine the first branch version of the first SAMA diagram and the second branch version of the second SAMA diagram;

[0301] Perform conflict detection between the first branch version and the second branch version, and obtain the conflict detection results;

[0302] If the conflict detection result indicates that there is no conflict, then the first branch version and the second branch version are merged to obtain the third SAMA graph.

[0303] In this embodiment of the invention, the version control tool 5042 is further used for:

[0304] Get the target index position;

[0305] The cached SAMA graph of the baseline version is used to apply the stored incremental codes sequentially according to the version iteration order until the target index position is reached, resulting in the fourth SAMA graph at the target index position. The incremental codes are used to indicate the difference operators between adjacent versions.

[0306] In this embodiment of the invention, the version control tool 5042 can perform multi-branch version management on the SAMA diagram architecture modifications generated during collaborative development, realize the automatic merging of design changes and the tracing of historical versions, which is conducive to the efficient collaborative implementation of a large amount of logical design work.

[0307] In this embodiment of the invention, the version control tool 5042, based on the internal data model of the logic design platform, stores metadata such as the topology, functional component attributes and parameter configurations of the SAMA graph logic chain in the version snapshot database, converts them into incremental encoding sequences with semantic identifiers, and compares the differences with the baseline data in the version repository.

[0308] In this embodiment of the invention, during the version merging process, a conflict detection algorithm is used to perform compatibility analysis on 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.

[0309] In this embodiment of the invention, when a logically contradictory modification is detected by the conflict detection algorithm (such as the same intermediate point signal calculation method differing simultaneously in different version branches), a manual intervention prompt is triggered.

[0310] In this embodiment of the invention, the version control tool also has a version rollback function, which supports the accurate restoration of historical versions of logical design by timestamp, modifier, or functional module.

[0311] The heavy-duty gas turbine control logic verification platform proposed in this invention obtains a first SAMA diagram of the heavy-duty gas turbine control logic; generates combined operating parameters under various operating conditions; verifies the first gas turbine simulation model to obtain a verified second gas turbine simulation model; determines the parameter operating boundaries corresponding to the second gas turbine simulation model; and verifies the control logic in the first SAMA diagram based on the parameter operating boundaries, combined operating parameters, and the verified second gas turbine simulation model to obtain the control logic verification results. Therefore, this invention utilizes combined operating parameters under various operating conditions, parameter operating boundaries, and the verified second gas turbine simulation model to verify the control logic in the first SAMA diagram, obtaining control logic verification results. This allows for automated verification of the control logic across multiple levels and a wide range of operating conditions during the design phase, enabling early identification and modification of control logic design defects, improving verification coverage and efficiency, resulting in more accurate verification results, and enhancing the development efficiency and reliability of gas turbine control logic.

[0312] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0313] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method of heavy-duty gas turbine control logic verification, characterized by, The method comprises: acquiring a first SAMA graph of heavy gas turbine control logic; generating combined working condition parameters under multiple different working conditions; verifying a first gas turbine simulation model to obtain a second gas turbine simulation model after verification; determining a parameter operating boundary corresponding to the second gas turbine simulation model; based on the parameter operating boundary, the combined working condition parameters and the second gas turbine simulation model, verifying the control logic in the first SAMA graph to obtain a control logic verification result; if the control logic verification result is verified, determining an IO signal requirement set and an IO signal verification set corresponding to the first SAMA graph, and verifying the IO signal verification set based on a preset rule and the IO signal requirement set; if the verification is passed, merging the first SAMA graph and a second SAMA graph to obtain a third SAMA graph, wherein the second SAMA graph is a previous version of the SAMA graph.

2. The method of claim 1, wherein, The generation of combined working condition parameters under multiple different working conditions comprises: generating environmental parameters and adjustment coefficients under multiple different working conditions; based on the environmental parameters and the adjustment coefficients, generating combined working condition parameters under multiple different working conditions by the LHS method.

3. The method of claim 1, wherein, The verification of the first gas turbine simulation model to obtain the second gas turbine simulation model after verification comprises: determining a parameter 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, iteratively updating the parameter to be corrected by the gradient descent method until a target parameter is obtained; inputting the target parameter into the first gas turbine simulation model to obtain the second gas turbine simulation model after verification.

4. The method of claim 3, wherein, The determination of the parameter to be corrected in the first gas turbine simulation model comprises: calculating a sensitivity index of each parameter in the first gas turbine simulation model, wherein the sensitivity index is used to indicate the influence degree of the parameter on a target function, and the target 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 as the parameter to be corrected.

5. The method of claim 3, wherein, The determination of the parameter operating boundary corresponding to the second gas turbine simulation model comprises: inputting the target parameter into a parameter boundary model to obtain the parameter operating boundary corresponding to the second gas turbine simulation model.

6. The method of claim 1, wherein, The verification of the control logic in the first SAMA graph based on the parameter operating boundary, the combined working condition parameters and the second gas turbine simulation model to obtain a control logic verification result comprises: connecting the control logic in the first SAMA graph to the second gas turbine simulation model; injecting the combined working condition parameters into the second gas turbine simulation model in sequence to obtain operating parameters of the second gas turbine simulation model in the running process; determining whether the operating parameters exceed the parameter operating boundary; if the operating parameters do not exceed the parameter operating boundary, it is determined that the control logic in the first SAMA graph is verified.

7. The method of claim 1, wherein, 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; and the verification of the IO signal verification set based on the preset rule and the IO signal requirement set includes: bidirectional matching of the control logic IO signal set based on the IO signal requirement set to obtain a first verification result; bidirectional matching of the simulation model IO signal set based on the IO signal requirement set to obtain a second verification result; bidirectional matching of the boundary model IO signal set based on the IO signal requirement set to obtain a third verification result; unidirectional matching of the working condition generation IO signal set based on the IO signal requirement set to obtain a fourth verification result; if there is no abnormal IO point 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 is failed.

8. The method of claim 1, wherein, The merging based on 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, merging based on the first branch version and the second branch version to obtain a third SAMA graph.

9. The method of claim 1, wherein, The method further includes: obtaining a target index position; applying, in a version iteration order, the stored incremental encoding of a baseline version of a cache SAMA graph one by one until the target index position is reached to obtain a fourth SAMA graph of the target index position, wherein the incremental encoding is used to indicate the difference operator between adjacent versions.

10. A heavy-duty gas turbine control logic verification platform, characterized by, The verification platform includes: a control logic design system configured to obtain a first SAMA graph of control logic of a heavy-duty gas turbine; a control logic test and verification system configured to generate combined working condition parameters under multiple different working conditions; a gas turbine multi-level simulation system configured to verify a first gas turbine simulation model to obtain a second gas turbine simulation model after verification; the control logic test and verification system is further configured to determine parameter operation boundaries corresponding to the second gas turbine simulation model; the control logic test and verification system is further configured to verify control logic in the first SAMA graph based on the parameter operation boundaries, the combined working condition parameters, and the second gas turbine simulation model to obtain a control logic verification result; a collaborative development system including an IO point verification tool and a version control tool; the IO point verification tool is configured to, if the control logic verification result is verification passed, determine an IO signal requirement set and an IO signal verification set corresponding to the first SAMA graph, and verify the IO signal verification set based on a preset rule and the IO signal requirement set. The version control tool is configured to, if the verification passes, merge the first SAMA graph and a second SAMA graph to obtain a third SAMA graph, wherein the second SAMA graph is a SAMA graph of a previous version.

11. The verification platform of claim 10, wherein, The control logic test verification system comprises a complex working condition generation module, and the complex working condition generation module is specifically configured to: generate environmental parameters and adjustment coefficients in multiple different working conditions; generate combined working condition parameters in multiple different working conditions based on the environmental parameters and the adjustment coefficients.

12. The verification platform of claim 10, wherein, The gas turbine multi-level simulation system comprises a model verification tool, and the model verification tool is specifically configured to: determine a to-be-corrected parameter in the first gas turbine simulation model; determine a gradient calculation result of the to-be-corrected parameter; update the to-be-corrected parameter by using a gradient descent method based on the gradient calculation result until a target parameter is obtained; input the target parameter into the first gas turbine simulation model to obtain a second gas turbine simulation model after verification.

13. The verification platform of claim 12, wherein, The model verification tool is further configured to: calculate a sensitivity index of each parameter in the first gas turbine simulation model, wherein the sensitivity index is used to indicate an influence degree of the parameter on a target function, and the target 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, determine that the parameter is a to-be-corrected parameter.

14. The verification platform of claim 12, wherein, The control logic test verification system further comprises a boundary model library, and the boundary model library is specifically configured to: input the target parameter into a parameter boundary model to obtain a parameter operation boundary corresponding to the second gas turbine simulation model.

15. The verification platform of claim 10, wherein, The control logic test verification system is further configured to: input control logic in the first SAMA graph into the second gas turbine simulation model; inject the combined working condition parameters into the second gas turbine simulation model in sequence to obtain an operation parameter of the second gas turbine simulation model in a running process; determine whether the operation parameter exceeds the parameter operation boundary; if the operation parameter does not exceed the parameter operation boundary, determine that the control logic in the first SAMA graph passes the verification.

16. The verification platform of claim 10, wherein, The IO signal verification set comprises 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, and the IO point verification tool is specifically configured to: perform bidirectional matching on the control logic IO signal set based on the IO signal requirement set to obtain a first verification result; perform 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; perform unidirectional matching on the working condition generation IO signal set based on the IO signal requirement set to obtain a fourth verification result; if there is no abnormal IO point 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.

17. The verification platform of claim 10, wherein, 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, performing merging based on the first branch version and the second branch version to obtain a third SAMA graph.

18. The verification platform of claim 10, wherein, The version control tool is further used for: obtaining a target index position; applying stored incremental encodings in a version iteration order one by one through a cache SAMA graph of a baseline version until the target index position is reached to obtain a fourth SAMA graph of the target index position, wherein the incremental encodings are used to indicate difference operators between adjacent versions.

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