Method and device for predicting service life of gas turbine blade and electronic equipment

Abstract

The invention provides a gas turbine blade life prediction method and device and electronic equipment. The method comprises the following steps: transmitting an ultrasonic signal to a blade of the gas turbine, and receiving a reflection signal of the blade; extracting feature information of the blade from the reflected signal, wherein the feature information at least comprises internal features and surface features of the blade; and inputting the feature information into a pre-trained target life prediction model, and predicting the residual life of the blade by the target life prediction model so as to output the residual life of the blade. Therefore, according to the scheme, the state and the health condition of the blade can be monitored in real time, and important technical support is provided for safe operation of the gas turbine by predicting the service life of the blade, so that the reliability of the gas turbine is improved.

Description

Technical Field

[0001] The present application relates to the technical field of gas turbines, and in particular to a method, device and electronic equipment for predicting the life of gas turbine blades. Background Art

[0002] Gas turbines are one of the important equipments currently used in power generation, aviation, aerospace and other fields. As the core components, the durability of the blades directly affects the service life and operating efficiency of the entire equipment. However, due to the long-term exposure of the blades to high temperature and high pressure working environment, they are susceptible to corrosion, thermal stress and other factors, which lead to damage and breakage, thereby reducing the working efficiency and service life of the entire equipment.

[0003] Traditional blade life assessment methods are mainly based on empirical formulas and test data, and have disadvantages such as inaccurate results, high time cost, and reliance on manual experience. Summary of the invention

[0004] The purpose of this application is to solve one of the technical problems in the related art at least to some extent.

[0005] To this end, the first purpose of this application is to propose a life prediction method for gas turbine blades to achieve real-time monitoring of the status and health of the blades, and to provide important technical support for the safe operation of the gas turbine by predicting the blade life.

[0006] The second objective of the present application is to provide a life prediction device for gas turbine blades.

[0007] The third objective of the present application is to provide an electronic device.

[0008] A fourth objective of the present application is to provide a computer-readable storage medium.

[0009] A fifth object of the present application is to provide a computer program product.

[0010] To achieve the above-mentioned purpose, the first aspect of the present application proposes a method for predicting the life of a gas turbine blade, comprising: transmitting an ultrasonic signal to the blade of the gas turbine and receiving a reflected signal from the blade; extracting characteristic information of the blade from the reflected signal, wherein the characteristic information includes at least internal characteristics and surface characteristics of the blade; inputting the characteristic information into a pre-trained target life prediction model, and predicting the remaining life of the blade by the target life prediction model to output the remaining life of the blade.

[0011] To achieve the above-mentioned purpose, the second aspect of the present application proposes a life prediction device for gas turbine blades, comprising: an ultrasonic transceiver module and a signal processing module, wherein the ultrasonic transceiver module is connected to the signal processing module; the ultrasonic transceiver module is used to transmit ultrasonic signals to the blades of the gas turbine and receive the reflected signals of the blades; the signal processing module is used to extract characteristic information of the blades based on the reflected signals, wherein the characteristic information includes at least internal characteristics and surface characteristics of the blades; the characteristic information is input into a pre-trained target life prediction model, and the target life prediction model predicts the remaining life of the blades to output the remaining life of the blades.

[0012] To achieve the above-mentioned purpose, the third aspect embodiment of the present application proposes an electronic device, comprising: a processor; and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, so that the processor can execute the life prediction method of the gas turbine blade described in the first aspect embodiment above.

[0013] To achieve the above-mentioned purpose, the fourth aspect of the present application proposes a computer-readable storage medium having a computer program stored thereon, wherein the computer instructions are used to enable the computer to execute the method for predicting the life of a gas turbine blade as described in the first aspect of the above-mentioned embodiment.

[0014] To achieve the above-mentioned purpose, a fifth embodiment of the present application proposes a computer program product, including a computer program, which, when executed by a processor, implements the life prediction method of the gas turbine blade described in the first embodiment above.

[0015] The life prediction method, device and electronic device of the gas turbine blade provided in the present application extract the characteristic information of the blade from the reflection signal by transmitting an ultrasonic signal to the blade of the gas turbine and receiving the reflection signal reflected by the blade. Furthermore, the characteristic information is input into the pre-trained target life prediction model to obtain the remaining life of the blade. Based on the method provided in the present application, by introducing the ultrasonic guided wave signal into the inside of the blade for measurement, non-destructive detection of the damage inside the blade can be achieved, thereby monitoring the status and health of the blade in real time, and by predicting the life of the blade, important technical support is provided for the safe operation of the gas turbine, thereby improving the reliability of the gas turbine.

[0016] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0018] Figure 1 A schematic flow chart of a method for predicting the life of a gas turbine blade provided in an embodiment of the present application;

[0019] Figure 2 A schematic flow chart of another method for predicting the life of a gas turbine blade provided in an embodiment of the present application;

[0020] Figure 3 A schematic flow chart of a training process of a target life prediction model in a life prediction method for a gas turbine blade provided in an embodiment of the present application;

[0021] Figure 4 A schematic diagram of the structure of a life prediction device for a gas turbine blade provided in an embodiment of the present application;

[0022] Figure 5 A schematic diagram of a life prediction device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0024] The method provided in the embodiments of the present application can be applied to technical fields such as aerospace, petrochemicals, and electricity.

[0025] The following describes the life prediction method and device for gas turbine blades according to an embodiment of the present application with reference to the accompanying drawings.

[0026] Figure 1 is a flow chart of a method for predicting the life of a gas turbine blade according to an embodiment of the present application, such as Figure 1 As shown, the life prediction method of the gas turbine blade of the embodiment of the present application includes but is not limited to the following steps:

[0027] S101, transmitting an ultrasonic signal to a blade of a gas turbine, and receiving a reflected signal from the blade.

[0028] It should be noted that the execution subject of the life prediction method of the gas turbine blade provided in the embodiment of the present application is an electronic device, and the electronic device can be a terminal device. Optionally, the terminal device can be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and the non-mobile electronic device can be a personal computer (personal computer, PC), a television, etc. The embodiment of the present application is not specifically limited.

[0029] In some implementations, an ultrasonic measuring device may be installed on the surface of a gas turbine blade to generate an ultrasonic signal and transmit the ultrasonic signal to the blade to measure the blade and receive a reflected signal reflected by the blade.

[0030] Alternatively, the ultrasonic signal may be a spiral ultrasonic signal.

[0031] Among them, spiral ultrasonic waves can form multipath propagation inside the blade, realizing comprehensive monitoring of the internal state of the blade.

[0032] In some implementations, the ultrasonic measuring device may include an ultrasonic transmitter and a receiver, wherein the ultrasonic transmitter may generate an ultrasonic signal and transmit the ultrasonic signal to the blade, and the receiver may receive a reflected signal from the blade.

[0033] In some implementations, in order to prevent the ultrasonic signal from attenuating during the transmission process, the signal strength of the ultrasonic signal may be enhanced first, and the enhanced ultrasonic signal may be transmitted to the blade.

[0034] In some implementations, after receiving the reflection signal, a database may be established based on the reflection signal to analyze the life of the blade according to a variety of different reflection signals, thereby improving the diversity of the data.

[0035] S102, extracting characteristic information of the blade from the reflection signal, where the characteristic information at least includes internal characteristics and surface characteristics of the blade.

[0036] It can be understood that the internal characteristics of the blade may include: internal defects, such as cracks, inclusions, pores, etc., and material structure; the surface characteristics of the blade may include: surface roughness, surface coating or attachments, surface defects, such as scratches, corrosion pits, etc.

[0037] In some implementations, the internal defects in the internal features of the blade will produce reflection, scattering and other phenomena during the propagation of the ultrasonic signal, thereby changing the waveform, amplitude and phase characteristics of the reflected signal. In other words, the type, location and size of the internal defects of the blade can be identified by comparing and analyzing the waveform changes of the reflected signal.

[0038] In some implementations, the material structure of the internal features of the blade affects the propagation characteristics of the ultrasonic signal. For example, parameters such as the density and elastic modulus of the material will affect the propagation speed and attenuation characteristics of the ultrasonic signal. By measuring the propagation speed and attenuation coefficient of the ultrasonic signal in the blade, the material structure and performance parameters of the blade can be indirectly inferred.

[0039] In some implementations, the surface roughness of the blade surface features affects the reflection intensity of the ultrasonic wave. The rougher the surface, the stronger the reflection signal; conversely, the smoother the surface, the weaker the reflection signal. The roughness of the blade surface can be evaluated by analyzing the amplitude change of the reflection signal.

[0040] In some implementations, surface coatings or deposits on the surface features of the blade may affect the reflection characteristics of the ultrasonic wave. The presence and thickness of the coatings or deposits on the blade surface may be identified by measuring the frequency and phase changes of the reflected signal.

[0041] In some implementations, surface defects such as scratches, corrosion pits, etc. in the surface features of the blade will also generate reflected signals during the propagation of the ultrasonic signal. High-resolution ultrasonic detection technology can be used to identify tiny defects on the blade surface.

[0042] That is to say, by extracting parameters such as the amplitude and phase of the reflected signal, the internal features and surface features of the blade corresponding to the reflected signal can be determined as feature information.

[0043] S103, inputting the characteristic information into a pre-trained target life prediction model, and using the target life prediction model to predict the remaining life of the blade to output the remaining life of the blade.

[0044] In some implementations, a life prediction model can be pre-trained based on historical feature information and the remaining life of the blade corresponding to the historical feature information to obtain a target life prediction model, and then the target life prediction model can be used to predict the remaining life of the blade based on the feature information.

[0045] In some implementations, the characteristic information is input into a target life prediction model, which predicts the remaining life of the blade, obtains the remaining life of the blade and outputs it.

[0046] In the life prediction method of the gas turbine blade provided in the embodiment of the present application, ultrasonic signals are transmitted to the blades of the gas turbine, and reflected signals reflected by the blades are received, thereby extracting characteristic information of the blades from the reflected signals. Furthermore, the characteristic information is input into the pre-trained target life prediction model to obtain the remaining life of the blades. Based on the method provided in the present application, by introducing ultrasonic guided wave signals into the interior of the blades for measurement, non-destructive detection of the damage inside the blades can be achieved, thereby monitoring the status and health of the blades in real time, and by predicting the life of the blades, important technical support is provided for the safe operation of the gas turbine, thereby improving the reliability of the gas turbine.

[0047] Figure 2 is a flow chart of a method for predicting the life of a gas turbine blade according to an embodiment of the present application, such as Figure 2 As shown, the life prediction method of the gas turbine blade of the embodiment of the present application includes but is not limited to the following steps:

[0048] S201, obtaining a correspondence between a plurality of first identifications of candidate gas turbines and ultrasonic parameters.

[0049] In some implementations, for different types of gas turbines, different ultrasonic signals may be used to predict the life of the blades of the gas turbine. The type of the gas turbine may be used as a first identifier, and ultrasonic parameters of different ultrasonic signals may be obtained.

[0050] Furthermore, a correspondence between a plurality of first identifications of candidate gas turbines and ultrasonic parameters is established, so as to determine the ultrasonic parameters for transmitting ultrasonic signals to blades of the gas turbine according to the correspondence.

[0051] S202, obtaining a second identifier of the gas turbine, and determining a target ultrasonic parameter of an ultrasonic signal transmitted to the gas turbine based on the second identifier and the corresponding relationship.

[0052] In some implementations, the type of the gas turbine for which life prediction is to be performed is obtained and used as a second identifier, so that a query is performed in a pre-established correspondence relationship according to the second identifier, and the ultrasonic parameter corresponding to the second identifier is used as the target ultrasonic parameter of the ultrasonic signal transmitted to the gas turbine.

[0053] S203, transmitting ultrasonic signals to the blades of the gas turbine based on the target ultrasonic parameters.

[0054] In some implementations, an ultrasonic signal may be generated based on a target ultrasonic parameter and transmitted to a blade of a gas turbine.

[0055] In some implementations, in order to enhance the ultrasonic signal and avoid significant attenuation of the ultrasonic signal during transmission, the attenuation signal in the ultrasonic signal can be obtained, and the signal strength of the attenuation signal can be enhanced to obtain an enhanced ultrasonic signal, and the enhanced ultrasonic signal can be transmitted to the blade.

[0056] S204, receiving the reflected signal of the blade.

[0057] In the embodiment of the present application, the implementation method of step S204 can be implemented by any method in the embodiments of the present application, which is not limited here and will not be repeated.

[0058] S205, extracting characteristic information of the blade from the reflection signal, where the characteristic information at least includes internal characteristics and surface characteristics of the blade.

[0059] In the embodiment of the present application, the implementation method of step S205 can be implemented by any method in the embodiments of the present application, which is not limited here and will not be repeated.

[0060] S206, inputting the characteristic information into a pre-trained target life prediction model, and using the target life prediction model to predict the remaining life of the blade to output the remaining life of the blade.

[0061] In the embodiment of the present application, the implementation method of step S206 can be implemented by any method in the embodiments of the present application, which is not limited here and will not be repeated.

[0062] In some implementations, after the remaining life of the blade is obtained, it can be determined whether the blade of the gas turbine has a safety hazard based on the remaining life of the blade, and if there is a safety hazard, the blade is maintained. Alternatively, a remaining life threshold at which the blade of the gas turbine is in a safe state can be determined, and based on the remaining life threshold, it can be determined whether the blade has a safety hazard.

[0063] That is to say, if the remaining life of the blade is greater than or equal to the remaining life threshold, it is determined that the blade is in a safe state and there is no safety hazard; if the remaining life of the blade is less than the remaining life threshold, it is determined that the blade is in an unsafe state and there is a safety hazard.

[0064] That is, in response to the remaining life being less than the remaining life threshold, maintenance processing is performed on the blade.

[0065] In the life prediction method of the gas turbine blade provided in the embodiment of the present application, an ultrasonic signal can be generated based on ultrasonic parameters, and the ultrasonic signal can be transmitted to the blade of the gas turbine, and the reflected signal reflected by the blade can be received, so as to extract the characteristic information of the blade from the reflected signal. Further, the characteristic information is input into the pre-trained target life prediction model to obtain the remaining life of the blade. Based on the method provided in the present application, by introducing the ultrasonic guided wave signal into the interior of the blade for measurement, non-destructive detection of the damage inside the blade can be achieved, so as to monitor the status and health of the blade in real time, and by predicting the life of the blade, important technical support is provided for the safe operation of the gas turbine, thereby improving the reliability of the gas turbine.

[0066] Based on the above embodiments, the present application embodiment can explain the training process of the target life prediction model, such as Figure 3 As shown, the training process of the target life prediction model in the embodiment of the present application includes but is not limited to the following steps:

[0067] S301, obtaining a historical reflection signal of a blade, and determining historical characteristic information of the historical reflection signal.

[0068] In some implementations, a database may be generated based on the reflection signal of the blade, and the reflection signal may be obtained from the database as the historical reflection signal.

[0069] Furthermore, feature extraction is performed on the historical reflection signal to determine historical feature information corresponding to the historical reflection signal.

[0070] Optionally, by extracting parameters such as the amplitude and phase of the historical reflection signal, the internal characteristics and surface characteristics of the blade corresponding to the historical reflection signal can be determined as the historical characteristic information.

[0071] S302, determining a reference remaining life corresponding to the historical characteristic information.

[0072] S303, inputting the historical feature information into the life prediction model to be trained, and the life prediction model outputs the predicted remaining life.

[0073] In some implementations, the remaining life corresponding to the historical feature information may be manually annotated to determine a reference remaining life corresponding to the historical feature information.

[0074] In some implementations, a life prediction model to be trained can be constructed based on techniques such as machine learning or deep learning, and historical feature information can be input into the life prediction model. The life prediction model predicts the remaining life of the blade based on the historical feature information and outputs the predicted remaining life.

[0075] S304, adjusting the life prediction model based on the predicted remaining life and the reference remaining life to obtain a target life prediction model.

[0076] In some implementations, the implementation function of the model can be determined based on the predicted remaining life and the reference remaining life, and the life prediction model can be adjusted based on the loss function, and training can be continued based on the adjusted model using historical feature information until the training is completed to obtain the target life prediction model.

[0077] Optionally, the training may be terminated when the accuracy of the remaining life predicted by the life prediction model output reaches a set threshold, or the training may be terminated when the number of training times of the life prediction model reaches a threshold.

[0078] In the life prediction method for gas turbine blades provided in an embodiment of the present application, the historical reflection signals of the blades are obtained, and the constructed life prediction model is trained based on the historical feature information corresponding to the historical reflection signals to obtain a target life prediction model, so that the model can learn the laws and patterns of blade performance degradation, thereby more accurately predicting the remaining life, and enabling the model to extract key features related to the blade life, thereby enhancing the targeted nature of the prediction.

[0079] Figure 4 FIG. 1 is a schematic diagram of a life prediction device for a gas turbine blade according to an exemplary embodiment. Figure 4 As shown, the life prediction device 100 for a gas turbine blade includes:

[0080] Ultrasonic transceiver module 101 and signal processing module 102 . The ultrasonic transceiver module 101 is connected to the signal processing module 102 .

[0081] The ultrasonic transceiver module 101 is used to transmit ultrasonic signals to the blades of the gas turbine and receive reflected signals from the blades.

[0082] The signal processing module 102 is used to extract characteristic information of the blade from the reflection signal, where the characteristic information at least includes internal characteristics and surface characteristics of the blade.

[0083] Furthermore, by inputting the feature information into a pre-trained target life prediction model, the target life prediction model predicts the remaining life of the blade to output the remaining life of the blade.

[0084] In some implementations, the signal processing module 102 may perform pre-processing operations such as filtering and denoising on the received reflection signal before extracting features.

[0085] In some implementations, the ultrasonic transceiver module 101 includes: an ultrasonic transmitter 111 and an ultrasonic receiver 112 , and both the ultrasonic transmitter 111 and the ultrasonic receiver 112 are linked to the blades of the gas turbine via ultrasonic signals.

[0086] In some implementations, the ultrasonic transmitter 111 is used to generate an ultrasonic signal and transmit the ultrasonic signal to the blade.

[0087] In some implementations, the ultrasonic receiver 112 is configured to receive a reflected signal reflected by the blade.

[0088] In some implementations, the ultrasonic transmitter 111 may generate an ultrasonic signal to be transmitted according to the ultrasonic parameters. By obtaining the correspondence between the first identifiers of multiple candidate gas turbines and the ultrasonic parameters, and obtaining the second identifier of the gas turbine, and based on the second identifier and the correspondence, the target ultrasonic parameters of the ultrasonic signal transmitted to the gas turbine are determined, and then the ultrasonic signal may be transmitted to the blades of the gas turbine based on the target ultrasonic parameters.

[0089] Optionally, the type of gas turbine can be used as a first identifier, and ultrasonic parameters of different ultrasonic signals can be obtained to establish a correspondence between multiple candidate gas turbine first identifiers and ultrasonic parameters, so as to determine the ultrasonic parameters of the ultrasonic signal emitted to the blades of the gas turbine based on the correspondence.

[0090] Furthermore, the type of the gas turbine for which life prediction is to be performed is obtained, and the type is used as a second identifier to query in a pre-established correspondence according to the second identifier, and the ultrasonic parameter corresponding to the second identifier is used as the target ultrasonic parameter of the ultrasonic signal emitted to the gas turbine.

[0091] That is, the ultrasonic transmitter 111 may generate an ultrasonic signal based on the target ultrasonic parameter and transmit the ultrasonic signal to the blade.

[0092] In some implementations, the life prediction device 100 for a gas turbine blade further includes a signal amplifier 103 , and the ultrasonic transmitter 111 is connected to the ultrasonic receiver 112 based on the signal amplifier 103 .

[0093] In some implementations, the signal amplifier 103 is used to enhance the ultrasonic signal generated by the ultrasonic transmitter and transmit the enhanced ultrasonic signal to the blade.

[0094] Optionally, an enhanced ultrasonic signal may be obtained by acquiring an attenuated signal in the ultrasonic signal and enhancing the signal strength of the attenuated signal.

[0095] In some implementations, the life prediction apparatus 100 for a gas turbine blade further includes a data collector 104 , which is connected to an ultrasonic receiver 112 .

[0096] In some implementations, the data collector 104 is used to store the reflection signals and establish a database based on the stored reflection signals.

[0097] In some implementations, the signal processing module 102 is further configured to obtain a reflection signal from a database and determine characteristic information based on the reflection signal.

[0098] In the life prediction device for gas turbine blades provided in the embodiment of the present application, an ultrasonic signal is generated by an ultrasonic transceiver module, and the ultrasonic signal is transmitted to the blades of the gas turbine, and a reflected signal reflected by the blades is received, so that the characteristic information of the blades is extracted from the reflected signal by the signal processing module. Further, the characteristic information is input into the pre-trained target life prediction model to obtain the remaining life of the blades. Based on the method provided in the present application, by introducing the ultrasonic guided wave signal into the interior of the blade for measurement, non-destructive detection of the damage inside the blade can be achieved, thereby monitoring the status and health of the blades in real time, and by predicting the life of the blades, important technical support is provided for the safe operation of the gas turbine, thereby improving the reliability of the gas turbine.

[0099] Figure 5 Shown is a schematic diagram of a life prediction device corresponding to the method proposed in an embodiment of the present application. Figure 5 It includes: blades, ultrasonic transmitters, ultrasonic receivers, signal conditioners, data acquisition instruments, database storage modules, and life assessment software.

[0100] Among them, the signal conditioner corresponds to the signal processing module in the embodiment of the present application, the data acquisition instrument and the database storage module correspond to the data acquisition device in the embodiment of the present application, the database storage module is used to store the received reflection signal, and the life assessment software is equipped with a target life prediction model.

[0101] The ultrasonic transmitter transmits an ultrasonic signal to the blade, and the ultrasonic receiver receives the reflected signal reflected by the blade. The signal conditioner extracts the characteristics of the reflected signal and transmits the reflected signal to the data acquisition instrument, which stores the reflected signal in the database storage module. After the signal conditioner extracts the characteristic information, the characteristic information is transmitted to the life assessment software, and the target life prediction model in the life assessment software predicts the remaining life of the blade based on the characteristic information, thereby outputting the remaining life of the blade.

[0102] In order to implement the above embodiments, the present application also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0103] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0104] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0105] The collection, storage, use, processing, transmission, provision and application of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0106] It should be noted that personal information from users should be collected for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign the agreement / authorization including authorization of relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others who have access to personal information data comply with its privacy policy and procedures.

[0107] This application is expected to provide an implementation scheme for users to selectively block the use or access of personal information data. That is, this application is expected to provide hardware and / or software to prevent or block access to such personal information data. Once the personal information data is no longer needed, risks can be minimized by limiting data collection and deleting data. In addition, when applicable, personal identifiers are removed from such personal information to protect the privacy of users.

[0108] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction 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 may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0109] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0110] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0111] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0112] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0113] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0114] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0115] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for predicting the life of a gas turbine blade, characterized in that: The method comprises: transmitting an ultrasonic signal to a blade of a gas turbine and receiving a reflected signal from the blade; Extracting characteristic information of the blade from the reflection signal, wherein the characteristic information at least includes internal characteristics and surface characteristics of the blade; The characteristic information is input into a pre-trained target life prediction model, and the target life prediction model predicts the remaining life of the blade to output the remaining life of the blade.

2. The method according to claim 1, characterized in that The transmitting of ultrasonic signals to the blades of the gas turbine comprises: Acquire the correspondence between the first identifications of a plurality of candidate gas turbines and the ultrasonic parameters; Acquiring a second identifier of the gas turbine, and determining a target ultrasonic parameter of an ultrasonic signal transmitted to the gas turbine based on the second identifier and the corresponding relationship; Based on the target ultrasonic parameter, an ultrasonic signal is transmitted to a blade of the gas turbine.

3. The method according to claim 2, characterized in that The method further comprises: An attenuated signal in the ultrasonic signal is acquired, and the signal strength of the attenuated signal is enhanced to obtain an enhanced ultrasonic signal, and the enhanced ultrasonic signal is transmitted to the blade.

4. The method according to claim 1, characterized in that After outputting the remaining life of the blade, the method further includes: determining a remaining life threshold at which blades of the gas turbine are in a safe state; In response to the remaining life being less than the remaining life threshold, performing maintenance processing on the blade.

5. The method according to claim 1, characterized in that The training process of the target life prediction model includes: Acquire a historical reflection signal of the blade, and determine historical characteristic information of the historical reflection signal; Determine a reference remaining life corresponding to the historical characteristic information; Inputting the historical feature information into a life prediction model to be trained, and outputting a predicted remaining life by the life prediction model; Based on the predicted remaining life and the reference remaining life, the life prediction model is adjusted to obtain the target life prediction model.

6. A life prediction device for a gas turbine blade, characterized in that: The device comprises: An ultrasonic transceiver module and a signal processing module, wherein the ultrasonic transceiver module is connected to the signal processing module; The ultrasonic transceiver module transmits ultrasonic signals to the blades of the gas turbine and receives reflected signals from the blades; The signal processing module is used to extract characteristic information of the blade based on the reflection signal, wherein the characteristic information at least includes internal characteristics and surface characteristics of the blade; The characteristic information is input into a pre-trained target life prediction model, and the target life prediction model predicts the remaining life of the blade to output the remaining life of the blade.

7. The device according to claim 5, characterized in that The ultrasonic transceiver module comprises: an ultrasonic transmitter and an ultrasonic receiver, wherein both the ultrasonic transmitter and the ultrasonic receiver are linked to the blades of the gas turbine through ultrasonic signals; The ultrasonic transmitter is used to generate the ultrasonic signal and transmit the ultrasonic signal to the blade; The ultrasonic receiver is used to receive the reflected signal reflected by the blade.

8. The device according to claim 7, characterized in that The ultrasonic transmitter is also used for: Acquire the correspondence between the first identifications of a plurality of candidate gas turbines and the ultrasonic parameters; Acquiring a second identifier of the gas turbine, and determining a target ultrasonic parameter of an ultrasonic signal transmitted to the gas turbine based on the second identifier and the corresponding relationship; Based on the target ultrasonic parameter, an ultrasonic signal is transmitted to a blade of the gas turbine.

9. The device according to claim 7, characterized in that The device further comprises: a signal amplifier, the ultrasonic transmitter being connected to the ultrasonic receiver based on the signal amplifier; The signal amplifier is used to enhance the ultrasonic signal generated by the ultrasonic transmitter and transmit the enhanced ultrasonic signal to the blade.

10. The device according to claim 9, characterized in that The signal amplifier is also used for: An attenuated signal in the ultrasonic signal is acquired, and the signal strength of the attenuated signal is enhanced to obtain the enhanced ultrasonic signal.

11. The device according to claim 7, characterized in that The device further comprises: a data collector, the data collector being connected to the ultrasonic receiver; The data collector is used to store the reflection signal and establish a database based on the stored reflection signal; The signal processing module is further used to obtain the reflection signal from the database and determine the characteristic information based on the reflection signal.

12. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 5.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 5 when executed by a processor.

14. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 5 when being executed by a processor.

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