Verification method and device of gas turbine

Abstract

The invention provides a gas turbine verification method and device, and relates to the technical field of gas turbines. The method comprises the following steps: acquiring a plurality of to-be-analyzed candidate performance indexes corresponding to the gas turbine; for any candidate performance index, determining the severity, occurrence degree and detection degree corresponding to the candidate performance index based on an FMEA analysis method, and determining an index risk level and an index risk score corresponding to the candidate performance index according to the severity, the occurrence degree and the detection degree; according to the index risk level and the index risk score, determining a target performance index of a verification driver to be formulated from the candidate performance indexes; and according to the target performance index, sequentially making a verification drive, a verification task and a verification plan corresponding to the gas turbine, and verifying the gas turbine according to the verification plan. According to the method, the potential risk is pre-judged and pertinent verification is carried out, so that the potential fault hidden danger can be eliminated before the gas turbine is actually put into use, and the overall reliability and the operation stability of the gas turbine are improved.

Description

Technical Field

[0001] This application relates to the technical field of gas turbines, and in particular, to a verification method and device for a gas turbine. Background Art

[0002] As the "crown jewel" of the manufacturing industry, gas turbines are widely used in the fields of aviation, energy, and other high-end equipment. Due to its technical complexity, the independent development of gas turbines has always been an important topic in China's manufacturing industry. As a technology-intensive product, gas turbines cover multiple disciplinary fields such as aerodynamics, heat transfer, combustion, mechanical engineering, materials science, process design, structural integrity, control technology, and testing methods. At the same time, the design and manufacture of gas turbines highly depend on engineering experience, which requires R & D personnel to carry out a large amount of verification and iteration work in the actual production process. Summary of the Invention

[0003] This application aims to solve at least one of the technical problems in the related art to some extent.

[0004] To this end, one object of this application is to propose a verification method for a gas turbine, including: obtaining a plurality of candidate performance indicators to be analyzed corresponding to the gas turbine; for any candidate performance indicator, determining the severity, occurrence degree, and detection degree corresponding to the candidate performance indicator based on the FMEA analysis method, and determining the index risk level and index risk score corresponding to the candidate performance indicator according to the severity, occurrence degree, and detection degree; determining the target performance indicator to be verified-driven from the candidate performance indicators according to the index risk level and index risk score; sequentially formulating a verification drive, verification task, and verification plan corresponding to the gas turbine according to the target performance indicator, and verifying the gas turbine according to the verification plan.

[0005] The second object of this application is to propose a verification device for a gas turbine.

[0006] The third object of this application is to propose an electronic device.

[0007] The fourth object of this application is to propose a non-transitory computer-readable storage medium.

[0008] The fifth object of this application is to propose a computer program product.

[0009] To achieve the above object, an embodiment of the first aspect of the present application proposes a verification method for a gas turbine, including: obtaining a plurality of candidate performance indicators to be analyzed corresponding to the gas turbine; for any candidate performance indicator, determining the severity, occurrence degree, and detection degree corresponding to the candidate performance indicator based on the FMEA analysis method, and determining the indicator risk level and indicator risk score corresponding to the candidate performance indicator according to the severity, occurrence degree, and detection degree; determining the target performance indicator to be verified-driven from the candidate performance indicators according to the indicator risk level and indicator risk score; sequentially formulating the verification drive, verification task, and verification plan corresponding to the gas turbine according to the target performance indicator, and verifying the gas turbine according to the verification plan.

[0010] According to an embodiment of the present application, determining the indicator risk level corresponding to the candidate performance indicator according to the severity, occurrence degree, and detection degree includes: obtaining a pre-set risk level mapping table, where the risk level mapping table is used to represent the mapping relationship between the candidate severity, candidate occurrence degree, candidate detection degree, and candidate risk level; querying the risk level mapping table according to the severity, occurrence degree, and detection degree to obtain the indicator risk level corresponding to the candidate performance indicator.

[0011] According to an embodiment of the present application, determining the indicator risk level corresponding to the candidate performance indicator according to the severity, occurrence degree, and detection degree includes: jointly inputting the severity, occurrence degree, and detection degree corresponding to the candidate performance indicator into a pre-trained risk level prediction model to obtain the indicator risk level output by the risk level prediction model.

[0012] According to an embodiment of the present application, the method for determining the indicator risk score includes: taking the product of the severity, occurrence degree, and detection degree as the indicator risk score corresponding to the candidate performance indicator.

[0013] According to an embodiment of the present application, determining the target performance indicator to be verified-driven from the candidate performance indicators according to the indicator risk level and indicator risk score includes: in response to the indicator risk level corresponding to any candidate performance indicator belonging to the high risk level, determining the candidate performance indicator as the target performance indicator; in response to the indicator risk level corresponding to any candidate performance indicator belonging to the medium risk level and the indicator risk score corresponding to the candidate performance indicator being greater than a preset score threshold, determining the candidate performance indicator as the target performance indicator.

[0014] According to an embodiment of the present application, a verification drive, verification tasks, and a verification plan corresponding to a gas turbine are formulated in sequence according to target performance indicators, including: classifying the target performance indicators, and formulating a verification drive according to the classification result, where the verification drive is used to represent the verification requirements of the gas turbine; formulating specific verification tasks corresponding to each verification drive, where each verification drive corresponds to one or more verification tasks, and the verification tasks include clear verification passing criteria; for any verification task, respectively obtain the measurement point priority corresponding to the verification task, the task risk level corresponding to the verification task, and the verification requirement priority corresponding to the verification task; formulate a verification plan corresponding to the gas turbine according to the measurement point priority, task risk level, and verification requirement priority respectively corresponding to each verification task.

[0015] According to an embodiment of the present application, a method for determining the verification requirement priority corresponding to a verification task includes: obtaining the verification necessity level and verification urgency level corresponding to the verification task; determining the verification requirement priority corresponding to the verification task according to the verification necessity level and verification urgency level; obtaining associated verification tasks associated with the verification task, and obtaining the associated verification requirement priorities corresponding to the associated verification tasks; updating the verification requirement priority corresponding to the verification task according to the associated verification requirement priorities.

[0016] To achieve the above object, an embodiment of the second aspect of the present application proposes a verification device for a gas turbine, including: an acquisition module, configured to acquire a plurality of candidate performance indicators to be analyzed corresponding to the gas turbine; an analysis module, configured to, for any candidate performance indicator, determine the severity, occurrence degree, and detection degree corresponding to the candidate performance indicator based on the FMEA analysis method, and determine the indicator risk level and indicator risk score corresponding to the candidate performance indicator according to the severity, occurrence degree, and detection degree; a determination module, configured to determine the target performance indicator for which a verification drive is to be formulated from the candidate performance indicators according to the indicator risk level and indicator risk score; a verification module, configured to formulate a verification drive, verification tasks, and a verification plan corresponding to the gas turbine in sequence according to the target performance indicator, and verify the gas turbine according to the verification plan.

[0017] According to an embodiment of the present application, the analysis module is further configured to: obtain a pre-set risk level mapping table, where the risk level mapping table is used to represent the mapping relationship between candidate severity, candidate occurrence degree, candidate detection degree, and candidate risk level; query the risk level mapping table according to the severity, occurrence degree, and detection degree to obtain the indicator risk level corresponding to the candidate performance indicator.

[0018] According to an embodiment of the present application, the analysis module is further configured to: jointly input the severity, occurrence degree, and detection degree corresponding to the candidate performance indicator into a pre-trained risk level prediction model to obtain the indicator risk level output by the risk level prediction model.

[0019] According to an embodiment of the present application, the analysis module is further configured to: use the product of severity, occurrence degree, and detection degree as the index risk score corresponding to the candidate performance index.

[0020] According to an embodiment of the present application, the determination module is further configured to: in response to the index risk level corresponding to any candidate performance index belonging to the high risk level, determine the candidate performance index as the target performance index; in response to the index risk level corresponding to any candidate performance index belonging to the medium risk level and the index risk score corresponding to the candidate performance index being greater than a preset score threshold, determine the candidate performance index as the target performance index.

[0021] According to an embodiment of the present application, the verification module is further configured to: classify the target performance index, and formulate a verification drive according to the classification result, where the verification drive is used to represent the verification requirements of the gas turbine; formulate specific verification tasks corresponding to each verification drive, where each verification drive corresponds to one or more verification tasks, and the verification tasks include clear verification pass criteria; for any verification task, respectively obtain the measurement point priority corresponding to the verification task, the task risk level corresponding to the verification task, and the verification requirement priority corresponding to the verification task; formulate a verification plan corresponding to the gas turbine according to the measurement point priority, task risk level, and verification requirement priority respectively corresponding to each verification task.

[0022] According to an embodiment of the present application, the verification module is further configured to: obtain the verification necessity level and verification urgency level corresponding to the verification task; determine the verification requirement priority corresponding to the verification task according to the verification necessity level and verification urgency level; obtain the associated verification task associated with the verification task, and obtain the associated verification requirement priority corresponding to the associated verification task; update the verification requirement priority corresponding to the verification task according to the associated verification requirement priority.

[0023] To achieve the above object, an embodiment of the third aspect of the present application provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to implement the verification method of the gas turbine as described in the embodiment of the first aspect of the present application.

[0024] To achieve the above object, an embodiment of the fourth aspect of the present application provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the verification method of the gas turbine as described in the embodiment of the first aspect of the present application.

[0025] To achieve the above object, an embodiment of the fifth aspect of the present application provides a computer program product, including a computer program which, when executed by a processor, implements the verification method of a gas turbine as described in the embodiment of the first aspect of the present application.

[0026] The present application at least achieves the following beneficial effects: Through the FMEA analysis method, the present application can comprehensively and systematically evaluate the risk of each performance index of the gas turbine, ensuring that high-risk indicators receive priority attention and verification; by predicting potential risks and conducting targeted verification, potential fault hazards can be eliminated before the gas turbine is actually put into use, thereby improving the overall reliability and operating stability of the gas turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0028] Figure 1 is a schematic diagram of an exemplary implementation of a verification method for a gas turbine shown in an embodiment of the present application.

[0029] Figure 2 is a schematic diagram of an exemplary implementation of a verification method for a gas turbine shown in an embodiment of the present application.

[0030] Figure 3 is a schematic diagram of a verification device for a gas turbine shown in an embodiment of the present application.

[0031] Figure 4 is a schematic diagram of an electronic device shown in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present application, and should not be construed as a limitation of the present application.

[0033] Figure 1 is a schematic diagram of an exemplary implementation of a verification method for a gas turbine shown in the present application. As Figure 1 shown, the verification method of the gas turbine includes the following steps:

[0034] S101, obtain a plurality of candidate performance indicators to be analyzed corresponding to the gas turbine.

[0035] Among them, the candidate performance indicators to be analyzed can cover various levels such as the overall machine performance, component / system performance, and component / sub-system performance. Each candidate performance indicator may have an impact on the overall operation of the gas turbine.

[0036] S102. For any candidate performance indicator, determine the severity, occurrence, and detectability corresponding to the candidate performance indicator based on the FMEA analysis method, and determine the indicator risk level and indicator risk score corresponding to the candidate performance indicator according to the severity, occurrence, and detectability.

[0037] Among them, Failure Mode and Effect Analysis (FMEA) is an analysis method used to determine potential failure modes and their causes. According to the work requirements, the selectable FMEA methods include functional FMEA, hardware FMEA, process FMEA, etc. Functional FMEA analyzes the causes and their impacts that may lead to each functional failure mode of the product; hardware FMEA analyzes the causes and their impacts that may lead to each hardware failure mode of the product; process FMEA can be applied to the product production process, use and operation process, maintenance process, management process, etc.

[0038] In this application, for any candidate performance indicator, determine the severity, occurrence, and detectability corresponding to the candidate performance indicator based on the FMEA analysis method. Exemplarily, if there are 100 candidate performance indicators, then determine the severity, occurrence, and detectability corresponding to each of these 100 candidate performance indicators respectively based on the FMEA analysis method.

[0039] Among them, the severity, denoted as S, can be designed to have a value range of 1 to 10, indicating the degree of serious impact that may be caused to the gas turbine if this performance indicator is abnormal. The larger the value, the higher the severity. For example, if the severity is 8, it means that the abnormality of this performance indicator will cause the gas turbine to be scrapped, out of control or lose its main function, or cause the gas turbine to be scrapped, resulting in the termination of the overall machine test work, or cause all test results to be missing.

[0040] Among them, the occurrence, denoted as O, can be designed to have a value range of 1 to 10, indicating the occurrence probability of the abnormality of this performance indicator. The larger the value, the greater the occurrence probability.

[0041] Among them, the detectability, denoted as D, can be designed to have a value range of 1 to 10, indicating the difficulty of detecting this abnormality by existing means. The larger the value, the more difficult it is to detect.

[0042] As an optional method, the method of expert analysis and evaluation can be selected to determine the severity S, occurrence O, and detectability D corresponding to the candidate performance indicator.

[0043] After determining the severity, occurrence, and detectability corresponding to the candidate performance indicators as described above, it is necessary to further determine the indicator risk level corresponding to the candidate performance indicators based on the severity, occurrence, and detectability. For example, a risk level mapping table for representing the mapping relationship between the candidate severity, candidate occurrence, candidate detectability, and candidate risk level can be preset in advance, and by querying this table, the indicator risk level corresponding to each candidate performance indicator can be determined.

[0044] After determining the severity, occurrence, and detectability corresponding to the candidate performance indicators as described above, it is also necessary to determine the indicator risk score corresponding to the candidate performance indicators based on the severity, occurrence, and detectability. Among them, the calculation formula for the indicator risk score is:

[0045] RPN = S × O × D

[0046] In the above formula, RPN represents the indicator risk score corresponding to the candidate performance indicator, S represents the severity, O represents the occurrence, and D represents the detectability.

[0047] That is, if there are 100 candidate performance indicators, then through the above process, the indicator risk levels and indicator risk scores corresponding to these 100 candidate performance indicators are obtained.

[0048] S103. Determine the target performance indicators to be verified and driven based on the indicator risk level and indicator risk score from the candidate performance indicators.

[0049] In this application, based on the indicator risk level and indicator risk score, the target performance indicators with higher risks that need to be verified are selected from the candidate performance indicators.

[0050] S104. Formulate the verification drive, verification tasks, and verification plan corresponding to the gas turbine in sequence according to the target performance indicators, and verify the gas turbine according to the verification plan.

[0051] Among them, the verification drive clarifies the direction and key points of the verification work.

[0052] Among them, the verification task is the actual operation link corresponding to the verification drive. Through the execution of specific tasks, it verifies the consistency between the actual performance of the gas turbine and the design standards.

[0053] Among them, the verification plan is the systematic arrangement of all verification tasks. It ensures that the verification work is completed on time and with quality, and provides a clear execution path for each verification task.

[0054] Exemplarily, if it is found that multiple target performance indicators are all related to a certain temperature control system of a gas turbine, the verification drive designed based on this temperature control system can be: verifying whether this temperature control system meets the design requirements and preventing system failures caused by temperature control failures.

[0055] Further, the verification tasks designed based on this verification drive may include the following three items:

[0056] 1. Calibrate the temperature sensor to ensure accurate readings.

[0057] 2. Test the response of the gas turbine under different load conditions to verify whether the temperature control system can maintain a predetermined temperature range.

[0058] 3. Confirm whether the temperature control system can trigger the alarm function and take corresponding cooling measures when the temperature is too high.

[0059] After obtaining the verification tasks corresponding to all verification drives respectively, a verification plan for the gas turbine is generated according to each verification task. The verification plan will involve targeted verification of each component, system or the whole machine of the gas turbine. According to the formulated plan, the verification is gradually implemented to ensure that the gas turbine can meet its performance requirements.

[0060] The embodiment of the present application proposes a verification method for a gas turbine, including: obtaining multiple candidate performance indicators to be analyzed corresponding to the gas turbine; for any candidate performance indicator, determining the severity, occurrence degree and detection degree corresponding to the candidate performance indicator based on the FMEA analysis method, and determining the indicator risk level and indicator risk score corresponding to the candidate performance indicator according to the severity, occurrence degree and detection degree; determining the target performance indicators to be formulated with verification drives from the candidate performance indicators according to the indicator risk level and indicator risk score; successively formulating the verification drives, verification tasks and verification plans corresponding to the gas turbine according to the target performance indicators, and verifying the gas turbine according to the verification plan. Through the FMEA analysis method, the present application can comprehensively and systematically evaluate the risks of each performance indicator of the gas turbine to ensure that high-risk indicators receive priority attention and verification; by predicting potential risks and conducting targeted verification, potential fault hazards can be eliminated before the gas turbine is actually put into use, thereby improving the overall reliability and operation stability of the gas turbine.

[0061] Figure 2 It is a schematic diagram of an exemplary implementation manner of a verification method for a gas turbine shown in the present application, as Figure 2 shown, this verification method for a gas turbine includes the following steps:

[0062] S201, obtaining multiple candidate performance indicators to be analyzed corresponding to the gas turbine.

[0063] S202. For any candidate performance metric, determine the severity, occurrence, and detectability corresponding to the candidate performance metric based on the FMEA analysis method, and determine the metric risk level and metric risk score corresponding to the candidate performance metric according to the severity, occurrence, and detectability.

[0064] When obtaining the metric risk level, as an achievable way, obtain a pre-set risk level mapping table. Exemplarily, Table 1 is a risk level mapping table shown in this application.

[0065] Table 1 Risk Level Mapping Table

[0066] Severity S Occurrence O Detection D Index Risk Level 9～10 8～10 7～10 Level 1 Risk …… …… …… …… 4～6 6～7 5～6 Level 2 Risk …… …… …… …… 2～3 6～7 2～3 Level 3 Risk …… …… …… ……

[0067] As shown in Table 1, the risk level mapping table is used to represent the mapping relationship between the candidate severity, candidate occurrence, candidate detectability, and candidate risk level; query the risk level mapping table according to the severity, occurrence, and detectability to obtain the metric risk level corresponding to the candidate performance metric. Among them, it should be understood that Table 1 is only an example and does not exhaust all examples.

[0068] When obtaining the metric risk level, as another achievable way, jointly input the severity, occurrence, and detectability corresponding to the candidate performance metric into a pre-trained risk level prediction model to obtain the metric risk level output by the risk level prediction model.

[0069] Among them, the risk level prediction model can be trained based on pre-set sample data, and the sample data includes sample severity, sample occurrence, sample detectability, and the risk level label corresponding to this piece of sample data.

[0070] When obtaining the metric risk score, take the product of the severity, occurrence, and detectability as the metric risk score corresponding to the candidate performance metric. Among them, the calculation formula for the metric risk score is:

[0071] RPN = S × O × D

[0072] In the above formula, RPN represents the metric risk score corresponding to the candidate performance metric, S represents severity, O represents occurrence, and D represents detectability.

[0073] S203. In response to the metric risk level corresponding to any candidate performance metric belonging to the high risk level, determine the candidate performance metric as the target performance metric.

[0074] Suppose the metric risk level includes a total of 4 risk levels: level 1 risk, level 2 risk, level 3 risk, and level 4 risk. The level 1 risk and level 2 risk can be classified as high risk levels, the level 3 risk can be classified as medium risk levels, and the level 4 risk can be classified as low risk levels.

[0075] In this application, it is considered that the candidate performance indicators belonging to the high-risk level have potential hazards, so the candidate performance indicators belonging to the high-risk level are determined as the target performance indicators.

[0076] S204. In response to the index risk level corresponding to any candidate performance indicator belonging to the medium-risk level and the index risk score corresponding to the candidate performance indicator being greater than the preset score threshold, the candidate performance indicator is determined as the target performance indicator.

[0077] In this application, it is considered that the candidate performance indicators belonging to the medium-risk level can be selectively determined as the target performance indicators. For example, the candidate performance indicators that simultaneously have the characteristics of belonging to the medium-risk level and the index risk score being greater than the preset score threshold can be determined as the target performance indicators.

[0078] S205. In response to the index risk level corresponding to any candidate performance indicator belonging to the low-risk level, or in response to any candidate performance indicator belonging to the medium-risk level and the index risk score corresponding to the candidate performance indicator being less than or equal to the preset score threshold, it indicates that this candidate performance indicator does not require the formulation of a verification drive, and then the subsequent analysis of this candidate performance indicator is ended.

[0079] S206. Classify the target performance indicators, and formulate a verification drive according to the classification result. The verification drive is used to represent the verification requirements of the gas turbine.

[0080] For example, indicators such as temperature and pressure can be classified as safety indicators, and then a verification drive related to safety is formulated.

[0081] Indicators such as the concentration of emissions such as nitrogen oxides and carbon dioxide can be classified as environmental indicators, and then a verification drive related to the environment is formulated.

[0082] S207. Formulate specific verification tasks corresponding to each verification drive. Among them, each verification drive corresponds to one or more verification tasks, and the verification tasks include clear verification passing criteria.

[0083] Exemplarily, if it is found that multiple target performance indicators are all related to a certain temperature control system of the gas turbine, the verification drive designed based on this temperature control system can be: verify whether this temperature control system meets the design requirements and prevent system failures caused by temperature control failures.

[0084] Furthermore, the verification tasks designed based on this verification drive can include the following 3 items:

[0085] 1. Calibrate the temperature sensor to ensure its reading is accurate.

[0086] 2. Test the response of the gas turbine under different load conditions to verify whether the temperature control system can maintain the predetermined temperature range.

[0087] 3. Confirm whether the temperature control system can trigger the alarm function when the temperature is too high and take corresponding cooling measures.

[0088] S208. For any verification task, obtain the measurement point priority corresponding to the verification task, the task risk level corresponding to the verification task, and the verification requirement priority corresponding to the verification task respectively.

[0089] Among them, the measurement point priority refers to the importance of different measurement points (such as temperature, pressure, vibration and other monitoring points) and the order of their priority processing during the verification process. The measurement point priority can be divided into three levels: high, medium and low.

[0090] Among them, the task risk level refers to the assessment of the verification task based on the possible risks or potential hazards brought by the verification task itself during the verification task. The task risk level can be divided into three levels: high, medium and low. For example, a high risk level indicates that the verification task may cause damage to the gas turbine and requires shutdown for maintenance or replacement; a medium risk level indicates that the verification task may cause damage to the gas turbine, but the loss caused is acceptable or does not affect the continuation of the test after simple inspection and repair; a low risk level indicates that the verification task basically will not cause damage to the gas turbine.

[0091] Among them, the verification requirement priority corresponding to the verification task refers to the requirements of the verification task for system stability, compliance and reliability. Verification tasks with higher priorities usually need to be executed earlier and more deeply. The verification requirement priority can be divided into levels 1 to 4: level 1 must be carried out and is given priority; level 2 must be carried out, but the test sequence can be optimized according to the situation; level 3 needs to be carried out, but the test sequence can be arranged appropriately later; level 4 is hoped to be carried out, but can be trimmed according to the situation.

[0092] Specifically, the method for determining the verification requirement priority corresponding to the verification task includes: obtaining the verification necessity level and the verification urgency level corresponding to the verification task; determining the verification requirement priority corresponding to the verification task according to the verification necessity level and the verification urgency level. Among them, the verification necessity level is used to reflect the necessity of carrying out the verification task (for example, a higher verification necessity level indicates that if this test cannot be carried out, the risk related to the safety of the gas turbine cannot be eliminated); the verification urgency level is used to reflect the urgency of carrying out the verification task (for example, a higher urgency level indicates that if this verification task cannot be carried out, it will affect the normal progress of other verification tasks).

[0093] Specifically, the mapping relationship between the verification necessity level, the verification urgency level and the verification requirement priority can be preset in advance, and the mapping relationship can be queried according to the verification necessity level and the verification urgency level corresponding to the verification task to determine the verification requirement priority corresponding to the verification task.

[0094] Furthermore, considering that some verification tasks are related to other verification tasks, and if a certain verification task is not carried out, it will also affect the normal progress of other verification tasks. In this application, for each verification task, associated verification tasks associated with this verification task are obtained, and the priority of the associated verification requirements corresponding to the associated verification tasks is obtained; the priority of the verification requirements corresponding to the verification task is updated according to the priority of the associated verification requirements. For example, the highest verification requirement priority is taken from the verification requirement priorities corresponding to the verification task and its corresponding associated verification task as the final verification requirement priority of the verification task and its corresponding associated verification task.

[0095] S209. Develop a verification plan for the gas turbine according to the measuring point priority, task risk level, and verification requirement priority corresponding to each verification task.

[0096] Among them, the verification plan can be understood as planning parameters such as the execution order and execution time of each verification task.

[0097] Exemplarily, a mapping relationship between the measuring point priority, task risk level, verification requirement priority, and plan level can be preset in advance, and this mapping relationship is queried according to the measuring point priority, task risk level, and verification requirement priority corresponding to each verification task to determine the plan level corresponding to each verification task. Optionally, the plan level can be divided into 5 levels, and verification tasks with a higher plan level are executed first.

[0098] S210. Verify the gas turbine according to the verification plan.

[0099] Through the FMEA analysis method, this application can comprehensively and systematically evaluate the risk of each performance index of the gas turbine, ensuring that high-risk indicators receive priority attention and verification; by predicting potential risks and conducting targeted verification, potential fault hazards can be eliminated before the gas turbine is actually put into use, thereby improving the overall reliability and operation stability of the gas turbine.

[0100] Figure 3 is a schematic diagram of a verification device for a gas turbine shown in this application. As Figure 3 shown, the verification device 300 of the gas turbine includes an acquisition module 301, an analysis module 302, a determination module 303, and a verification module 304, where:

[0101] The acquisition module 301 is used to acquire a plurality of candidate performance indicators to be analyzed corresponding to the gas turbine.

[0102] An analysis module 302 is configured to determine, for any candidate performance metric, the severity, occurrence, and detectability corresponding to the candidate performance metric based on the FMEA analysis method, and determine the metric risk level and metric risk score corresponding to the candidate performance metric according to the severity, occurrence, and detectability.

[0103] A determination module 303 is configured to determine, from the candidate performance metrics, the target performance metric to be verified-driven according to the metric risk level and metric risk score.

[0104] A verification module 304 is configured to sequentially formulate a verification drive, verification tasks, and a verification plan corresponding to the gas turbine according to the target performance metric, and verify the gas turbine according to the verification plan.

[0105] Through the FMEA analysis method, this device can comprehensively and systematically evaluate the risk of each performance metric of the gas turbine, ensuring that high-risk metrics receive priority attention and verification; by predicting potential risks and conducting targeted verification, potential fault hazards can be eliminated before the gas turbine is actually put into use, thereby improving the overall reliability and operating stability of the gas turbine.

[0106] Furthermore, the analysis module 302 is further configured to: obtain a pre-set risk level mapping table, which is used to represent the mapping relationship between candidate severity, candidate occurrence, candidate detectability, and candidate risk level; query the risk level mapping table according to the severity, occurrence, and detectability to obtain the metric risk level corresponding to the candidate performance metric.

[0107] Furthermore, the analysis module 302 is further configured to: jointly input the severity, occurrence, and detectability corresponding to the candidate performance metric into a pre-trained risk level prediction model to obtain the metric risk level output by the risk level prediction model.

[0108] Furthermore, the analysis module 302 is further configured to: use the product of the severity, occurrence, and detectability as the metric risk score corresponding to the candidate performance metric.

[0109] Furthermore, the determination module 303 is further configured to: in response to the metric risk level corresponding to any candidate performance metric belonging to the high-risk level, determine the candidate performance metric as the target performance metric; in response to the metric risk level corresponding to any candidate performance metric belonging to the medium-risk level and the metric risk score corresponding to the candidate performance metric being greater than a preset score threshold, determine the candidate performance metric as the target performance metric.

[0110] Further, the verification module 304 is further configured to: classify the target performance indicators, and formulate a verification driver according to the classification result, where the verification driver is used to represent the verification requirements of the gas turbine; formulate specific verification tasks corresponding to each verification driver, where each verification driver corresponds to one or more verification tasks, and the verification tasks include clear verification passing criteria; for any verification task, respectively obtain the measuring point priority corresponding to the verification task, the task risk level corresponding to the verification task, and the verification requirement priority corresponding to the verification task; formulate a verification plan corresponding to the gas turbine according to the measuring point priority, task risk level, and verification requirement priority respectively corresponding to each verification task.

[0111] Further, the verification module 304 is further configured to: obtain the verification necessity level and verification urgency level corresponding to the verification task; determine the verification requirement priority corresponding to the verification task according to the verification necessity level and verification urgency level; obtain the associated verification tasks associated with the verification task, and obtain the associated verification requirement priorities corresponding to the associated verification tasks; update the verification requirement priority corresponding to the verification task according to the associated verification requirement priorities.

[0112] To implement the above embodiments, an embodiment of the present application further provides an electronic device 400, as Figure 4 shown. The electronic device 400 includes: a processor 401 and a memory 402 communicatively connected to the processor. The memory 402 stores instructions executable by at least one processor. The instructions are executed by at least one processor 401 to implement the verification method of the gas turbine as shown in the above embodiments.

[0113] To implement the above embodiments, an embodiment of the present application further provides a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to cause a computer to implement the verification method of the gas turbine as shown in the above embodiments.

[0114] To implement the above embodiments, an embodiment of the present application further provides a computer program product, including a computer program that implements the verification method of the gas turbine as shown in the above embodiments when executed by a processor.

[0115] In the description of the present application, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present application.

[0116] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, "a plurality of" means two or more unless otherwise specifically defined.

[0117] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0118] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as a limitation to the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A gas turbine verification method, characterized in that: include: Acquire multiple candidate performance indicators to be analyzed corresponding to the gas turbine; For any of the candidate performance indicators, determine the severity, occurrence and detection corresponding to the candidate performance indicator based on the FMEA analysis method, and determine the indicator risk level and indicator risk score corresponding to the candidate performance indicator according to the severity, occurrence and detection; Determining a target performance indicator to be driven by verification from the candidate performance indicators according to the indicator risk level and the indicator risk score; The verification drive, verification task and verification plan corresponding to the gas turbine are formulated in sequence according to the target performance index, and the gas turbine is verified according to the verification plan.

2. The method according to claim 1, characterized in that The determining, according to the severity, the occurrence and the detection, the indicator risk level corresponding to the candidate performance indicator comprises: Obtaining a preset risk level mapping table, wherein the risk level mapping table is used to represent a mapping relationship between candidate severity, candidate occurrence, candidate detection and candidate risk level; The risk level mapping table is queried according to the severity, the occurrence and the detection to obtain the indicator risk level corresponding to the candidate performance indicator.

3. The method according to claim 1, characterized in that: The determining, according to the severity, the occurrence and the detection, the indicator risk level corresponding to the candidate performance indicator comprises: The severity, the occurrence and the detection corresponding to the candidate performance indicator are input into a pre-trained risk level prediction model to obtain the indicator risk level output by the risk level prediction model.

4. The method according to claim 2 or 3, characterized in that: The method for determining the indicator risk score includes: The product of the severity, the occurrence and the detection is used as the indicator risk score corresponding to the candidate performance indicator.

5. The method according to claim 4, characterized in that The step of determining the target performance indicator to be driven by the verification from the candidate performance indicators according to the indicator risk level and the indicator risk score includes: In response to the indicator risk level corresponding to any of the candidate performance indicators belonging to a high risk level, determining the candidate performance indicator as a target performance indicator; In response to the indicator risk level corresponding to any of the candidate performance indicators belonging to the medium risk level, and the indicator risk score corresponding to the candidate performance indicator is greater than a preset score threshold, the candidate performance indicator is determined as the target performance indicator.

6. The method according to claim 5, characterized in that The step of formulating verification drive, verification task and verification plan corresponding to the gas turbine in sequence according to the target performance index includes: Classifying the target performance indicators and formulating a verification driver according to the classification results, wherein the verification driver is used to represent the verification requirements of the gas turbine; Formulate a specific verification task corresponding to each verification driver, wherein each verification driver corresponds to one or more verification tasks, and the verification task includes a clear verification pass standard; For any of the verification tasks, respectively obtain the measurement point priority corresponding to the verification task, the task risk level corresponding to the verification task, and the verification requirement priority corresponding to the verification task; A verification plan corresponding to the gas turbine is formulated according to the measurement point priority, the task risk level and the verification requirement priority respectively corresponding to each verification task.

7. The method according to claim 6, characterized in that The method for determining the priority of the verification requirement corresponding to the verification task includes: Obtaining a verification necessity level and a verification urgency level corresponding to the verification task; Determining the verification requirement priority corresponding to the verification task according to the verification necessity level and the verification urgency level; Acquire an associated verification task associated with the verification task, and acquire an associated verification requirement priority corresponding to the associated verification task; The verification requirement priority corresponding to the verification task is updated according to the associated verification requirement priority.

8. A gas turbine verification device, characterized in that: include: An acquisition module, used for acquiring a plurality of candidate performance indicators to be analyzed corresponding to the gas turbine; An analysis module, for determining, for any of the candidate performance indicators, the severity, occurrence and detection corresponding to the candidate performance indicator based on the FMEA analysis method, and determining the indicator risk level and indicator risk score corresponding to the candidate performance indicator according to the severity, occurrence and detection; A determination module, configured to determine a target performance indicator to be developed for verification driving from the candidate performance indicators according to the indicator risk level and the indicator risk score; The verification module is used to formulate verification drive, verification task and verification plan corresponding to the gas turbine in sequence according to the target performance index, and verify the gas turbine according to the verification plan.

9. An electronic device, comprising: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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