Flameout control method, device and equipment for full-model gas turbine and storage medium

Abstract

The invention relates to the technical field of gas turbines, in particular to a flameout control method, a flameout control device and flameout control equipment of a full-model gas turbine and a storage medium. Therefore, whether the gas turbine has the flameout risk or not can be predicted from two dimensions, the risk supervision efficiency of the gas turbine is improved, and when it is predicted that the gas turbine has the flameout risk, the running state of the gas turbine is adjusted, the flameout risk of the gas turbine is reduced, and the working efficiency of the gas turbine is improved. The technical problem that in the prior art, whether the gas turbine flames out or not cannot be supervised, and the working efficiency of the gas turbine is affected is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of gas turbines, and in particular to a flameout control method, device, equipment and storage medium for a full-type gas turbine. Background Art

[0002] During the operation of the gas turbine, the combustion performance of the gas turbine may be reduced due to external environment, changes in fuel composition or structural blockage, resulting in lean combustion of the gas turbine or even flameout. The flameout and restart of the gas turbine will produce a large amount of pollutant gas emissions, violating local environmental protection standards. More seriously, it will cause gas turbine failure and reduce the working efficiency of the gas turbine. Currently, there is no supervision and control plan for the risk of flameout of gas turbines in the gas turbine field.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide a flameout control method, device, equipment and storage medium for a full range of gas turbines, aiming to solve the technical problem in the prior art that it is impossible to monitor whether a gas turbine will flameout, thereby affecting the working efficiency of the gas turbine.

[0005] To achieve the above object, the present invention provides a flameout control method for a full-type gas turbine, the method comprising the following steps:

[0006] Obtain the current operating parameters of the gas turbine and the combustion chamber combustion signal;

[0007] Predicting whether there is a flameout risk based on the current operating parameters and the combustion chamber combustion signal using a trained fault analysis model;

[0008] When it is predicted that the gas turbine has a flameout risk, the operating state of the gas turbine is adjusted so that each operating parameter of the gas turbine meets preset conditions.

[0009] Optionally, the adjusting the operating state of the gas turbine includes:

[0010] Determining a target opening of each valve of the gas turbine based on a preset flameout limit curve corresponding to the model of the gas turbine;

[0011] The opening of at least one valve in the gas turbine is adjusted according to the target opening.

[0012] Optionally, after determining the target opening of each valve of the gas turbine based on the preset flameout limit curve corresponding to the model of the gas turbine, the method further includes:

[0013] Determining a valve to be adjusted in the gas turbine according to a preset flameout limit curve;

[0014] Obtaining the current opening of the valve to be adjusted;

[0015] Determining a single adjustment step length according to the current opening and the target opening;

[0016] The opening of the valve to be adjusted is adjusted at least once according to the single adjustment step.

[0017] Optionally, the adjusting the operating state of the gas turbine further includes:

[0018] Determining a target speed of a compressor of the gas turbine based on a preset flameout limit curve corresponding to the model of the gas turbine;

[0019] The speed of the compressor in the gas turbine is adjusted to a target speed.

[0020] Optionally, after obtaining the current operating parameters of the gas turbine and the combustion signal of the combustion chamber, the method further includes:

[0021] Performing low-pass filtering on the combustion chamber combustion signal to obtain a low-pass filtered signal of the combustion chamber combustion signal;

[0022] Determine the total signal amount and signal mean value of the combustion chamber combustion signal per unit time;

[0023] Generate a low-pass filtered signal root mean square according to the signal mean and the low-pass filtered signal;

[0024] Generate a normalized root mean square of the combustion chamber combustion signal according to the signal root mean square and the signal total amount;

[0025] Accordingly, the predicting whether there is a flameout risk by using a trained fault analysis model according to the current operating parameters and the combustion signal of the combustion chamber includes:

[0026] Predict whether there is a flameout risk based on the current operating parameters and the normalized root mean square of the combustion chamber combustion signal through a trained fault analysis model.

[0027] Optionally, predicting whether there is a flameout risk according to the current operating parameters and the combustion chamber combustion signal by using a trained fault analysis model includes:

[0028] Performing spectral characteristic analysis on the combustion signal of the combustion chamber to determine the distribution ratio of the target luminous signal of the specific signal spectral radiation wavelength;

[0029] Extracting temperature fluctuation data of each area in the combustion chamber in the current working parameters;

[0030] Calculating a flameout probability parameter according to the distribution ratio of the target luminous signal, the temperature fluctuation data, the normalized root mean square of the combustion chamber combustion signal, and a preset coefficient corresponding to the gas turbine model;

[0031] It is predicted whether there is a flameout risk for the gas turbine in the next cycle according to the flameout probability parameter.

[0032] Optionally, predicting whether there is a flameout risk for the gas turbine in the next cycle according to the flameout probability parameter includes:

[0033] When the flameout probability parameter is greater than or equal to a preset threshold, determining that the gas turbine has a flameout risk in the next cycle;

[0034] When the flameout probability parameter is less than a preset threshold, it is determined that there is no flameout risk for the gas turbine in the next cycle.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also provides a flameout control device for a full-type gas turbine, the flameout control device for a full-type gas turbine comprising:

[0036] An acquisition module, used for acquiring current operating parameters of the gas turbine and combustion signals of the combustion chamber;

[0037] A prediction module, used to predict whether there is a flameout risk according to the current working parameters and the combustion signal of the combustion chamber through a trained fault analysis model;

[0038] The adjustment module is used to adjust the operating state of the gas turbine when it is predicted that the gas turbine has a risk of flameout, so that various operating parameters of the gas turbine meet preset conditions.

[0039] In addition, to achieve the above-mentioned purpose, the present invention also proposes a flameout control device for a full-type gas turbine, the flameout control device for the full-type gas turbine comprising: a memory, a processor, and a flameout control program for the full-type gas turbine stored in the memory and executable on the processor, the flameout control program for the full-type gas turbine being configured to implement the steps of the flameout control method for the full-type gas turbine as described above.

[0040] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a flameout control program for a full-type gas turbine is stored. When the flameout control program for the full-type gas turbine is executed by a processor, the steps of the flameout control method for the full-type gas turbine as described above are implemented.

[0041] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the flameout control method of the full-type gas turbine as described above.

[0042] One or more technical solutions proposed in the present invention have at least the following technical effects: the present invention obtains the current operating parameters and combustion signals of the combustion chamber of the gas turbine; predicts whether there is a risk of flameout through a trained fault analysis model based on the current operating parameters and the combustion signals of the combustion chamber; when it is predicted that there is a risk of flameout of the gas turbine, the operating state of the gas turbine is adjusted so that the various operating parameters of the gas turbine meet the preset conditions. The present invention evaluates the combustion condition of the combustion chamber in the current state by combining the current operating parameters of the gas turbine and the combustion signals in the combustion chamber, so as to predict whether there is a risk of flameout of the gas turbine from two dimensions, thereby improving the risk supervision efficiency of the gas turbine, and when it is predicted that there is a risk of flameout of the gas turbine, the operating state of the gas turbine is adjusted to reduce the risk of flameout of the gas turbine and improve the working efficiency of the gas turbine, thereby avoiding the technical problem in the prior art that it is impossible to supervise whether the gas turbine will flameout, thereby affecting the working efficiency of the gas turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0045] Figure 1 It is a flow chart of a first embodiment of a flameout control method for a full-type gas turbine of the present invention;

[0046] Figure 2 It is a flow chart of a second embodiment of a flameout control method for a full-type gas turbine according to the present invention;

[0047] Figure 3 It is a flow chart of a third embodiment of a flameout control method for a full-type gas turbine of the present invention;

[0048] Figure 4 It is a structural block diagram of a first embodiment of a flameout control device for a full-type gas turbine of the present invention;

[0049] Figure 5It is a structural schematic diagram of a flameout control device for a full-type gas turbine in a hardware operating environment involved in an embodiment of the present invention.

[0050] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0052] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0053] Based on this, the embodiment of the present invention provides a flameout control method for a full-type gas turbine, referring to Figure 1 , Figure 1 The figure is a flow chart of a first embodiment of a flameout control method for a full-type gas turbine according to the present invention.

[0054] In this embodiment, the flameout control method of the full-type gas turbine includes:

[0055] Step S10: Acquire the current operating parameters of the gas turbine and the combustion signal of the combustion chamber.

[0056] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a control computer electrically connected to a gas turbine, etc. The following takes a control computer electrically connected to a gas turbine as an example to illustrate this embodiment and the following embodiments.

[0057] In this embodiment, the current operating parameters of the gas turbine include but are not limited to the gas emissions of the gas turbine during operation, the combustion chamber pressure pulsation, the speed of the compressor, the temperature of each area in the combustion chamber, etc., wherein the gas emissions include but are not limited to various NOx gases and CO, etc. A large amount of polluting gases will be emitted during the operation of the gas turbine. Excessive polluting gases will cause environmental pollution, and incomplete combustion will occur. The combustion residue will subsequently affect the service life of the equipment, and the combustion chamber pressure pulsation data will affect the normal operation of the gas turbine. Too low combustion chamber pressure may cause the gas turbine to stall, and frequent shutdown and restart will seriously damage the service life of the equipment.

[0058] Furthermore, after the real-time acquisition of the gas turbine operating parameter set, the method further includes:

[0059] The working parameter set is preprocessed, and the preprocessing at least includes: moving arithmetic average, exponentially weighted moving average and extreme value processing.

[0060] Since it is difficult to collect the working parameters of the gas turbine during operation, especially the emission of pollutant gases, it is difficult to directly use it for subsequent combustion adjustment judgment and single adjustment step calculation. For example, when obtaining the pressure pulsation data of the combustion chamber, a combustion chamber pressure probe or a high-speed pressure sensor and other devices can be used for collection. In order to improve the accuracy of the combustion chamber pressure pulsation data, the arithmetic average of multiple collected pressure pulsation data can be performed to improve the accuracy of the pressure pulsation data within a time period. When collecting the emission of pollutant gases, a continuous emission monitoring system (CEMS) can be used to monitor and record the concentration and emission of industrial pollutants in real time, or a risk evaluation and mitigation strategy system (REMS). Other devices or equipment that can realize gas emission collection can also be used. This embodiment does not impose specific restrictions on this.

[0061] The combustion signal of the combustion chamber refers to the luminous signal of the combustion flame in the combustion chamber collected by the optical probe installed on the side wall of the combustion chamber. There are different processing methods depending on the type of reacting fuel in the combustion chamber. The luminous signal of the flame refers to the signal that some molecules generate light radiation due to electron transition during the fuel combustion reaction.

[0062] Step S20: predicting whether there is a flameout risk based on the current operating parameters and the combustion chamber combustion signal using a trained fault analysis model.

[0063] The trained fault analysis model may be an algorithm model for feature recognition of flame luminescence signals based on statistics, or may be a neural network model for identifying and predicting the combustion conditions of gas turbines after classification training, etc. This embodiment does not impose any specific restrictions on this.

[0064] Step S30: When it is predicted that the gas turbine has a flameout risk, the operating state of the gas turbine is adjusted so that each operating parameter of the gas turbine meets preset conditions.

[0065] It can be understood that the operating state of the gas turbine can be adjusted by controlling the opening of the valves of each fuel inlet participating in the combustion reaction in the combustion chamber, the speed of the compressor that delivers air to the combustion chamber, or the pressure pulsation parameters in the combustion chamber, etc. This embodiment does not impose specific restrictions on this.

[0066] The preset condition refers to the normal working parameter range corresponding to each working parameter of the gas turbine when the gas turbine is working normally. By adjusting the operating state of the gas turbine so that each working parameter of the gas turbine returns to the theoretical normal working parameter range, the possibility of gas turbine flameout is reduced and the risk of flameout is reduced.

[0067] This embodiment evaluates the combustion condition of the combustion chamber in the current state by combining the current operating parameters of the gas turbine and the combustion signal in the combustion chamber, so as to predict whether the gas turbine has the risk of flameout from two dimensions, thereby improving the risk supervision efficiency of the gas turbine, and when it is predicted that the gas turbine has the risk of flameout, adjusting the operating state of the gas turbine, reducing the risk of flameout of the gas turbine, and improving the working efficiency of the gas turbine, thereby avoiding the technical problem in the prior art that it is impossible to supervise whether the gas turbine will flameout, thereby affecting the working efficiency of the gas turbine.

[0068] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , step S30, comprising:

[0069] Step S301: determining the target opening of each valve of the gas turbine based on a preset flameout limit curve corresponding to the model of the gas turbine.

[0070] Step S302: adjusting the opening of at least one valve in the gas turbine according to the target opening.

[0071] It should be noted that there are differences in the operating parameters corresponding to different gas turbine types. When adjusting the operating state of the gas turbine, in order to adapt to the differences in the normal operating parameter ranges of different gas turbine models, this embodiment will pre-perform combustion analysis on various types of gas turbines, so as to determine the lower limit values ​​of various parameters of various types of gas turbines, and then use the lower limit values ​​of various parameters as the preset flameout limit curves of the corresponding types of gas turbines, for example: the theoretical opening of the valve corresponding to each fuel, and the theoretical opening is used to ensure that the gas turbine can have a normal combustion reaction and meet the minimum combustion performance requirements for the operation of the gas turbine.

[0072] Furthermore, after determining the target opening of each valve of the gas turbine based on the preset flameout limit curve corresponding to the model of the gas turbine, the method further includes:

[0073] Determining a valve to be adjusted in the gas turbine according to a preset flameout limit curve;

[0074] Obtaining the current opening of the valve to be adjusted;

[0075] Determining a single adjustment step length according to the current opening and the target opening;

[0076] The opening of the valve to be adjusted is adjusted at least once according to the single adjustment step.

[0077] In a specific implementation, when adjusting the opening of each valve, the valve corresponding to the fuel that has the greatest impact on the combustion reaction in the combustion chamber can be determined as the valve to be adjusted based on the opening of each valve, so that the combustion condition of the combustion chamber can be adjusted as quickly as possible.

[0078] At the same time, in order to avoid excessive changes in the valve opening in a short period of time, which may cause lean combustion or deflagration in the combustion chamber, which may lead to direct flameout, in this embodiment, the above situation is reduced by adjusting it in multiple times. For example, if the current opening of the valve to be adjusted is 10% and the target opening is 70%, the opening of the valve to be adjusted can be increased by 20% each time, and adjusted in three times with an interval set between each adjustment, so as to reduce the occurrence of abnormal situations such as sudden flameout or deflagration in the combustion chamber.

[0079] Furthermore, the adjusting the operating state of the gas turbine further includes:

[0080] Determining a target speed of a compressor of the gas turbine based on a preset flameout limit curve corresponding to the model of the gas turbine;

[0081] The speed of the compressor in the gas turbine is adjusted to a target speed.

[0082] Specifically, in addition to the opening of each valve, the speed of the compressor directly affects the flow rate of air and part of the gas fuel, and can also affect the strength of the combustion performance. In this embodiment, the speed of the compressor can be adjusted synchronously while adjusting the opening of the valve, that is, as the valve increases, the compressor speed also increases, thereby accelerating the combustion state adjustment process of the gas turbine.

[0083] This embodiment determines the target opening of each valve of the gas turbine based on a preset flameout limit curve corresponding to the model of the gas turbine; adjusts the opening of at least one valve in the gas turbine according to the target opening, thereby affecting the direct operation of the combustion reaction, fundamentally solving the flameout risk caused by poor combustion performance, and also improving the combustion performance of the gas turbine.

[0084] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , after step S10, further comprising:

[0085] Step S210: performing low-pass filtering on the combustion chamber combustion signal to obtain a low-pass filtered signal of the combustion chamber combustion signal.

[0086] Step S220: Determine the total signal amount and signal mean value of the combustion chamber combustion signal per unit time.

[0087] Step S230: Generate a root mean square of the signal after low-pass filtering according to the signal mean and the low-pass filtered signal.

[0088] Step S240: generating a normalized root mean square of the combustion chamber combustion signal according to the signal root mean square and the signal total amount.

[0089] It should be noted that by monitoring the changing trend of the statistical value of the combustion signal in the combustion chamber as the equivalence ratio decreases, selecting several values ​​with obvious changing trends as control parameters, and setting appropriate thresholds, it is possible to monitor and control the combustion stability of the flame. Specifically, the formula for generating the standardized root mean square of the combustion signal in the combustion chamber is:

[0090]

[0091] Where N is the total amount of the combustion chamber combustion signal collected per unit time; q` is the low-pass filter signal of the combustion chamber combustion signal; q is the signal mean; RMS b It represents the RMS value after low-pass filtering, and NRMS is the standardized RMS value of the combustion signal in the combustion chamber.

[0092] Further, the predicting whether there is a flameout risk by using a trained fault analysis model according to the current operating parameters and the combustion signal of the combustion chamber includes:

[0093] Performing spectral characteristic analysis on the combustion signal of the combustion chamber to determine the distribution ratio of the target luminous signal of the specific signal spectral radiation wavelength;

[0094] Extracting temperature fluctuation data of each area in the combustion chamber in the current working parameters;

[0095] Calculating a flameout probability parameter according to the distribution ratio of the target luminous signal, the temperature fluctuation data, the normalized root mean square of the combustion chamber combustion signal, and a preset coefficient corresponding to the gas turbine model;

[0096] It is predicted whether there is a flameout risk for the gas turbine in the next cycle according to the flameout probability parameter.

[0097] In a specific implementation, when different types of fuels undergo combustion reactions, there are differences in the transition electrons generated. By performing spectral feature analysis on the combustion chamber combustion signal, the target luminescent signal with the largest difference in electron distribution ratio between the lean combustion state and the oxygen-rich combustion state can be screened out, thereby determining the distribution ratio of the target luminescent signal of a specific signal spectral radiation wavelength, wherein the target luminescent signal is related to the type of fuel in the combustion chamber.

[0098] For example, in the flame formed by the combustion of hydrocarbon fuels, the order of the luminous intensity of various luminous signals is: when lean, OH>CH>C 2 , rich combustion C 2 >CH>OH, so when predicting the lean burnout limit, the OH chemiluminescence signal can be used as the target luminescence signal, and the distribution ratio can be determined by extracting the distribution of the signal spectrum radiation wavelength of the OH chemiluminescence signal in the combustion chamber.

[0099] Specifically, the specific formula for calculating the flameout probability parameter according to the distribution ratio of the target luminous signal, the temperature fluctuation data, the normalized root mean square of the combustion chamber combustion signal, and the preset coefficient corresponding to the gas turbine model is:

[0100] P=a1*p+a2*T 变化 +a3*NRMS+a4

[0101] Where P is the flameout probability parameter, a1-a4 are preset coefficients corresponding to the gas turbine model, p is the distribution ratio of the target luminous signal of the specific signal spectrum radiation wavelength, T 变化 is the temperature fluctuation data, and NRMS is the normalized root mean square of the combustion signal in the combustion chamber.

[0102] Further, the predicting whether there is a flameout risk for the gas turbine in the next cycle according to the flameout probability parameter includes:

[0103] When the flameout probability parameter is greater than or equal to a preset threshold, determining that the gas turbine has a flameout risk in the next cycle;

[0104] When the flameout probability parameter is less than a preset threshold, it is determined that there is no flameout risk for the gas turbine in the next cycle.

[0105] In a specific implementation, the preset threshold can be set to 0.9, that is, when the flameout probability parameter is greater than or equal to 0.9, it is determined that the gas turbine has a flameout risk in the next cycle; when the flameout probability parameter is less than 0.9, it is determined that the gas turbine has a flameout risk in the next cycle.

[0106] This embodiment obtains a low-pass filtered signal of the combustion chamber combustion signal by performing low-pass filtering on the combustion chamber combustion signal; determines the total signal amount and signal mean of the combustion chamber combustion signal in unit time; generates a root mean square of the signal after low-pass filtering according to the signal mean and the low-pass filtered signal; generates a standardized root mean square of the combustion chamber combustion signal according to the signal root mean square and the total signal amount, thereby predicting whether there is a flameout risk based on the current working parameters and the standardized root mean square of the combustion chamber combustion signal through a trained fault analysis model, thereby improving the accuracy of determining the flameout risk.

[0107] This application also provides a flameout control device for a full-type gas turbine, please refer to Figure 4 , the flameout control device of the full-type gas turbine comprises:

[0108] The acquisition module 10 is used to acquire the current operating parameters of the gas turbine and the combustion signal of the combustion chamber.

[0109] The prediction module 20 is used to predict whether there is a flameout risk according to the current operating parameters and the combustion signal of the combustion chamber through a trained fault analysis model.

[0110] The adjustment module 30 is used to adjust the operating state of the gas turbine when it is predicted that the gas turbine has a flameout risk, so that various operating parameters of the gas turbine meet preset conditions.

[0111] This embodiment evaluates the combustion condition of the combustion chamber in the current state by combining the current operating parameters of the gas turbine and the combustion signal in the combustion chamber, so as to predict whether the gas turbine has the risk of flameout from two dimensions, thereby improving the risk supervision efficiency of the gas turbine, and when it is predicted that the gas turbine has the risk of flameout, adjusting the operating state of the gas turbine, reducing the risk of flameout of the gas turbine, and improving the working efficiency of the gas turbine, thereby avoiding the technical problem in the prior art that it is impossible to supervise whether the gas turbine will flameout, thereby affecting the working efficiency of the gas turbine.

[0112] In one embodiment, the adjustment module 30 is further used to determine the target opening of each valve of the gas turbine based on a preset flameout limit curve corresponding to the model of the gas turbine; and adjust the opening of at least one valve in the gas turbine according to the target opening.

[0113] In one embodiment, the adjustment module 30 is further used to determine the valve to be adjusted in the gas turbine according to a preset flameout limit curve; obtain the current opening of the valve to be adjusted; determine a single adjustment step according to the current opening and the target opening; and adjust the opening of the valve to be adjusted at least once according to the single adjustment step.

[0114] In one embodiment, the adjustment module 30 is further used to determine the target speed of the compressor of the gas turbine based on a preset flameout limit curve corresponding to the model of the gas turbine; and adjust the speed of the compressor in the gas turbine to the target speed.

[0115] In one embodiment, the acquisition module 10 is further used to perform low-pass filtering on the combustion chamber combustion signal to obtain a low-pass filtered signal of the combustion chamber combustion signal; determine the total signal amount and signal mean of the combustion chamber combustion signal per unit time; generate a root mean square of the signal after low-pass filtering according to the signal mean and the low-pass filtered signal; generate a standardized root mean square of the combustion chamber combustion signal according to the signal root mean square and the total signal; accordingly, predicting whether there is a flameout risk based on the current operating parameters and the combustion chamber combustion signal through a trained fault analysis model includes: predicting whether there is a flameout risk based on the current operating parameters and the standardized root mean square of the combustion chamber combustion signal through a trained fault analysis model.

[0116] In one embodiment, the prediction module 20 is further used to perform spectral feature analysis on the combustion chamber combustion signal to determine the distribution ratio of the target luminous signal of the specific signal spectral radiation wavelength; extract the temperature fluctuation data of each area in the combustion chamber in the current working parameters; calculate the flameout probability parameter according to the distribution ratio of the target luminous signal, the temperature fluctuation data and the preset coefficient corresponding to the gas turbine model; and predict whether there is a flameout risk for the gas turbine in the next cycle according to the flameout probability parameter.

[0117] In one embodiment, the prediction module 20 is further used to determine that the gas turbine has a risk of flameout in the next cycle when the flameout probability parameter is greater than or equal to a preset threshold value; and to determine that the gas turbine does not have a risk of flameout in the next cycle when the flameout probability parameter is less than a preset threshold value.

[0118] The present application provides a flameout control device for a full-type gas turbine, and the flameout control device for a full-type gas turbine includes: 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 so that the at least one processor can execute the flameout control method for the full-type gas turbine in the above-mentioned embodiment one.

[0119] Reference below Figure 5, which shows a schematic diagram of the structure of a flameout control device for a full-type gas turbine suitable for implementing the embodiment of the present application. The flameout control device for a full-type gas turbine in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The flameout control device for the full-type gas turbine shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0120] like Figure 5 As shown, the flameout control device of the full-type gas turbine may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the flameout control device of the full-type gas turbine are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems may be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 may allow the flameout control device of the full-type gas turbine to communicate wirelessly or wired with other devices to exchange data. Although the flameout control device of the full-type gas turbine with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0121] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0122] The flameout control device for a full-type gas turbine provided in the present application adopts the flameout control method for a full-type gas turbine in the above-mentioned embodiment, and can solve the technical problem of flameout control for a full-type gas turbine. Compared with the prior art, the beneficial effects of the flameout control device for a full-type gas turbine provided in the present application are the same as the beneficial effects of the flameout control method for a full-type gas turbine provided in the above-mentioned embodiment, and other technical features in the flameout control device for a full-type gas turbine are the same as the features disclosed in the method of the previous embodiment, and are not described in detail here.

[0123] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0124] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0125] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, the computer-readable program instructions being used to execute the flameout control method for the full-type gas turbine in the above-mentioned embodiment.

[0126] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0127] The computer-readable storage medium may be included in the flameout control device of the full-type gas turbine; or may exist independently without being assembled into the flameout control device of the full-type gas turbine.

[0128] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the flameout control device of the full-type gas turbine, the flameout control device of the full-type gas turbine enables: flameout control of the full-type gas turbine.

[0129] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0130] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0131] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0132] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned flameout control method for a full-type gas turbine, and can solve the technical problem of flameout control for a full-type gas turbine. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the flameout control method for a full-type gas turbine provided in the above-mentioned embodiment, and will not be described in detail here.

[0133] The present application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the flameout control method for a full-type gas turbine as described above.

[0134] The computer program product provided by the present application can solve the technical problem of flameout control of all types of gas turbines. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the flameout control method of all types of gas turbines provided by the above embodiment, which will not be repeated here.

[0135] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A flameout control method for a full-type gas turbine, characterized in that: The flameout control method of the full-type gas turbine comprises: Obtain the current operating parameters of the gas turbine and the combustion chamber combustion signal; Predicting whether there is a flameout risk based on the current operating parameters and the combustion chamber combustion signal using a trained fault analysis model; When it is predicted that the gas turbine has a flameout risk, the operating state of the gas turbine is adjusted so that each operating parameter of the gas turbine meets preset conditions.

2. The method according to claim 1, characterized in that The step of adjusting the operating state of the gas turbine includes: Determining a target opening of each valve of the gas turbine based on a preset flameout limit curve corresponding to the model of the gas turbine; The opening of at least one valve in the gas turbine is adjusted according to the target opening.

3. The method according to claim 2, characterized in that After determining the target opening of each valve of the gas turbine based on the preset flameout limit curve corresponding to the model of the gas turbine, the method further includes: Determining a valve to be adjusted in the gas turbine according to a preset flameout limit curve; Obtaining the current opening of the valve to be adjusted; Determining a single adjustment step length according to the current opening and the target opening; The opening of the valve to be adjusted is adjusted at least once according to the single adjustment step.

4. The method according to claim 2, characterized in that The step of adjusting the operating state of the gas turbine further includes: Determining a target speed of a compressor of the gas turbine based on a preset flameout limit curve corresponding to the model of the gas turbine; The speed of the compressor in the gas turbine is adjusted to a target speed.

5. The method according to any one of claims 1 to 4, characterized in that After obtaining the current operating parameters of the gas turbine and the combustion signal of the combustion chamber, the method further includes: Performing low-pass filtering on the combustion chamber combustion signal to obtain a low-pass filtered signal of the combustion chamber combustion signal; Determine the total signal amount and signal mean value of the combustion chamber combustion signal per unit time; Generate a low-pass filtered signal root mean square according to the signal mean and the low-pass filtered signal; Generate a normalized root mean square of the combustion chamber combustion signal according to the signal root mean square and the signal total amount; Accordingly, the predicting whether there is a flameout risk by using a trained fault analysis model according to the current operating parameters and the combustion signal of the combustion chamber includes: Predict whether there is a flameout risk by using a trained fault analysis model according to the current operating parameters, the combustion chamber combustion signal and the normalized root mean square of the combustion chamber combustion signal.

6. The method according to any one of claims 1 to 4, characterized in that The predicting whether there is a flameout risk according to the current working parameters and the combustion chamber combustion signal by using a trained fault analysis model includes: Performing spectral characteristic analysis on the combustion signal of the combustion chamber to determine the distribution ratio of the target luminous signal of the specific signal spectral radiation wavelength; Extracting temperature fluctuation data of each area in the combustion chamber in the current working parameters; Calculating a flameout probability parameter according to the distribution ratio of the target luminous signal, the temperature fluctuation data, the normalized root mean square of the combustion chamber combustion signal, and a preset coefficient corresponding to the gas turbine model; It is predicted whether there is a flameout risk for the gas turbine in the next cycle according to the flameout probability parameter.

7. The method according to claim 6, characterized in that The predicting whether there is a flameout risk of the gas turbine in the next cycle according to the flameout probability parameter includes: When the flameout probability parameter is greater than or equal to a preset threshold, determining that the gas turbine has a flameout risk in the next cycle; When the flameout probability parameter is less than a preset threshold, it is determined that there is no flameout risk for the gas turbine in the next cycle.

8. A flameout control device for a full-type gas turbine, characterized in that: The flameout control device of the full-type gas turbine comprises: An acquisition module, used for acquiring current operating parameters of the gas turbine and combustion signals of the combustion chamber; A prediction module, used to predict whether there is a flameout risk according to the current working parameters and the combustion signal of the combustion chamber through a trained fault analysis model; The adjustment module is used to adjust the operating state of the gas turbine when it is predicted that the gas turbine has a risk of flameout, so that various operating parameters of the gas turbine meet preset conditions.

9. A flameout control device for a full-type gas turbine, characterized in that: The flameout control device of the full-type gas turbine includes: a memory, a processor, and a flameout control program of the full-type gas turbine stored in the memory and executable on the processor, and the flameout control program of the full-type gas turbine is configured to implement the steps of the flameout control method of the full-type gas turbine as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a flameout control program for a full-type gas turbine, and when the flameout control program for a full-type gas turbine is executed by a processor, the steps of the flameout control method for a full-type gas turbine according to any one of claims 1 to 7 are implemented.

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