Aero-engine state monitoring method and device and electronic equipment

Abstract

The invention relates to the technical field of aero-engine health state monitoring, in particular to an aero-engine state monitoring method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the state data of an aero-engine; based on the state data, multiple pieces of leg data of normal operation of the aero-engine assembly are selected, the data acquisition length is preset, and the normal operation data of the assembly are converted to obtain function type data; converting the function type data by using a B-spline basis function, and obtaining a registration curve based on an elastic registration method; acquiring a registration curve average value to obtain a standard reference baseline; and performing curve processing on the data acquisition length, the B-spline primary function conversion and the elastic registration, and performing error accumulation operation with a standard reference curve to obtain an engine state health score. Real-time and accurate monitoring of the health state of the aero-engine assembly is achieved, safe and stable operation of the aero-engine is guaranteed, the service life is prolonged, and the maintenance efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of aircraft engine health status monitoring, and in particular to an aircraft engine status monitoring method, device, electronic equipment and storage medium. Background Art

[0002] Aircraft engines are highly complex and precise thermal machines and an important part of the high-end manufacturing equipment manufacturing industry. The safety and reliability of their operation have attracted much attention, so real-time and accurate monitoring of the health status of aircraft engines is particularly critical. During the operation of aircraft engines, the performance degradation and failure of key components such as fuel pumps, oil supply pipes, blades, bearings, and oil coolers will directly affect the performance and life of aircraft engines. However, the performance degradation and failure of these components are often difficult to observe directly. During the service life of aircraft engines, if traditional offline detection methods are used to evaluate the health status of internal components, the operation of aircraft engines needs to be frequently suspended, which is time-consuming and labor-intensive. Summary of the invention

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

[0004] To this end, the first purpose of this application is to propose an aircraft engine condition monitoring method to solve the problems of existing technical means such as large limitations, long detection time and high cost.

[0005] The second object of the present application is to provide a device.

[0006] The third objective of the present application is to provide an electronic device.

[0007] A fourth objective of the present application is to provide a computer-readable storage medium.

[0008] To achieve the above-mentioned purpose, the first embodiment of the present application proposes a method for monitoring the state of an aircraft engine, comprising:

[0009] Obtain status data of aircraft engines;

[0010] Based on the state data, multiple flight segment data of normal operation of the aircraft engine component are selected, the data collection length is preset, and the normal operation data of the component is converted to obtain function-type data;

[0011] The functional data is transformed using a B-spline basis function, and a registration curve is obtained based on an elastic registration method;

[0012] Obtaining an average value of the registration curve to obtain a standard reference baseline;

[0013] The data acquisition length, the B-spline basis function conversion and the elastic registration are subjected to curve processing, and an error accumulation operation is performed with the standard reference curve to obtain an engine state health score.

[0014] Preferably, the obtaining of the aircraft engine status data comprises:

[0015] The input variables of the health status monitoring model of the aircraft engine parts are selected and initialized, and the length interval range of the data collection of the input variables in a single flight segment is determined.

[0016] Preferably, based on the status data, multiple flight segment data of normal operation of the aircraft engine component are selected, the data collection length is preset, and the normal operation data of the component is converted to obtain the function type data including:

[0017] Preset the data collection length according to multiple flight segments of normal operation of aircraft engine components;

[0018] The monitoring signal of the component is converted into functional data by using a set of curves discretely expressed in a point grid;

[0019] The functional data is processed based on the data collection length to obtain functional data of a preset collection length.

[0020] Preferably, the step of converting the functional data using a B-spline basis function and obtaining a registration curve based on an elastic registration method comprises:

[0021] Preset the number of functions and spline order of B-spline basis functions;

[0022] The functional data is transformed using the B-spline basis function, and the properties of the Fisher-Rao metric are used to achieve curve alignment based on the SRSF framework.

[0023] Preferably, the B-spline basis function expression is:

[0024]

[0025] Among them, k represents the index value of the B-spline basis function, k = 1, 2, ..., K, and d represents the spline order, d = 1, 2, ..., D.

[0026] Preferably, obtaining the average value of the registration curve to obtain a standard reference baseline comprises:

[0027] The average of the aligned curves is taken to obtain the standard reference baseline of the real-time sensor monitoring signal within a single flight segment when the component is operating normally.

[0028] Preferably, the data acquisition length, the B-spline basis function conversion and the elastic registration are subjected to curve processing, and an error accumulation operation is performed with the standard reference curve to obtain the engine status health score, which includes:

[0029] Performing curve processing on the data acquisition length, the B-spline basis function conversion and the elastic registration, and calculating the cumulative error between the processed curve and the standard reference baseline;

[0030] The accumulated error is determined based on a preset health score threshold, the health score of the flight segment is calculated using a linear mapping transformation and compared with the health score lower limit threshold to obtain the engine status health score.

[0031] To achieve the above-mentioned purpose, the second embodiment of the present application proposes an aircraft engine state monitoring device, comprising:

[0032] A data acquisition module, which acquires the status data of the aircraft engine;

[0033] A function conversion module, based on the state data, selects a plurality of flight segment data of normal operation of the aircraft engine component, presets a data collection length, and converts the normal operation data of the component to obtain function type data;

[0034] A curve conversion module, which converts the functional data using a B-spline basis function and obtains a registration curve based on an elastic registration method;

[0035] A reference baseline acquisition module is used to obtain the average value of the registration curve to obtain a standard reference baseline;

[0036] The state evaluation module performs curve processing on the data acquisition length, the B-spline basis function conversion and the elastic registration, and performs error accumulation operation with the standard reference curve to obtain the engine state health score.

[0037] To achieve the above-mentioned purpose, the third aspect of the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0038] The memory stores computer-executable instructions;

[0039] The processor executes the computer-executable instructions stored in the memory to implement any of the above methods.

[0040] To achieve the above objectives, the fourth aspect of the present application proposes a computer-readable storage medium, including computer-executable instructions stored in the computer-readable storage medium, and the computer-executable instructions are used to implement any of the methods described above when executed by a processor.

[0041] The present application provides an aircraft engine status monitoring method, which utilizes the online monitoring data of various aircraft engine components during the flight of the aircraft to analyze and process the multi-source status sensor information collected in real time. Different from designing a supervised learning algorithm for prediction, the health status of aircraft engine components is indirectly predicted through unsupervised design of health index values. This process can accurately monitor the health status of internal components of aircraft engines without affecting the normal operation of aircraft engines, thereby providing technical support for the management and maintenance of aircraft engines.

[0042] 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

[0043] 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:

[0044] Figure 1 A flowchart of a first specific embodiment of an aircraft engine condition monitoring method provided by the present invention;

[0045] Figure 2 is a flow chart of an aircraft engine status detection method;

[0046] Figure 3 The original data of the oil pressure signal OIL_PRS1_R of the left engine of aircraft A during the 12 flight segments when the oil supply pipe of the left engine of aircraft A is operating normally;

[0047] Figure 4 The curve of the oil pressure signal OIL_PRS1_R of the left engine of aircraft A in normal operation of the oil supply pipe in a total of 12 flight segments after data acquisition length standardization, B-spline basis function conversion and elastic registration;

[0048] Figure 5 It is the standard reference baseline of the oil pressure signal of the oil supply pipe of the left engine of aircraft A;

[0049] Figure 6 The comparison between the processed lubricating oil pressure signal and the standard reference baseline of the lubricating oil supply pipe of the left engine of aircraft A in a normal operation segment and a failure segment;

[0050] Figure 7 The health score of the oil supply pipe of the left engine of aircraft A for a total of 150 flight segments before and after the failure;

[0051] Figure 8 The original data of the oil temperature signal OIT_APU of the APU oil cooler of aircraft B during the 23 flight segments when the APU oil cooler was operating normally;

[0052] Fig. 9 The curve of the oil temperature signal OIT_APU of the APU oil cooler of aircraft B during the 23 normal flight segments after data acquisition length standardization, B-spline basis function conversion and elastic registration;

[0053] Fig.10 It is the standard reference baseline of the oil temperature signal of the APU oil cooler of aircraft B;

[0054] Fig.11 The comparison of the processed oil temperature signal of the APU oil cooler of aircraft B in one normal operation segment and one failure segment with the standard reference baseline;

[0055] Fig.12 The health score of the APU oil cooler of aircraft B for a total of 150 flight segments;

[0056] Fig.13 A structural block diagram of an aircraft engine status monitoring device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The core of the present invention is to provide an aircraft engine status monitoring method, device, electronic equipment and storage medium, which indirectly predicts the health status of aircraft engine components through unsupervised design health index values, thereby realizing real-time and accurate monitoring of the health status of aircraft engine components.

[0058] In order to enable those skilled in the art to better understand the scheme of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Please refer to Figure 1 , Figure 1 This is a flow chart of a first specific embodiment of an aircraft engine status monitoring method provided by the present invention; the specific operation steps are as follows:

[0060] Step S101: Acquire status data of the aircraft engine;

[0061] The input variables of the health status monitoring model of the aircraft engine parts are selected and initialized, and the length interval range of the data collection of the input variables in a single flight segment is determined.

[0062] Step S102: Based on the state data, multiple flight segment data of normal operation of the aircraft engine component are selected, the data collection length is preset, and the normal operation data of the component is converted to obtain function data;

[0063] Preset the data collection length according to multiple flight segments of normal operation of aircraft engine components;

[0064] The monitoring signal of the component is converted into functional data by using a set of curves discretely expressed in a point grid;

[0065] The functional data is processed based on the data collection length to obtain functional data of a preset collection length.

[0066] Step S103: transforming the functional data using a B-spline basis function, and obtaining a registration curve based on an elastic registration method;

[0067] Preset the number of functions and spline order of B-spline basis functions;

[0068] The functional data is transformed using the B-spline basis function, and the properties of the Fisher-Rao metric are used to achieve curve alignment based on the SRSF framework.

[0069] The B-spline basis function expression is:

[0070]

[0071] Among them, k represents the index value of the B-spline basis function, k = 1, 2, ..., K, and d represents the spline order, d = 1, 2, ..., D.

[0072] Step S104: obtaining the average value of the registration curve to obtain a standard reference baseline;

[0073] The average of the aligned curves is taken to obtain the standard reference baseline of the real-time sensor monitoring signal within a single flight segment when the component is operating normally.

[0074] Step S105: performing curve processing on the data acquisition length, the B-spline basis function conversion and the elastic registration, and performing error accumulation operation with the standard reference curve to obtain an engine status health score.

[0075] Performing curve processing on the data acquisition length, the B-spline basis function conversion and the elastic registration, and calculating the cumulative error between the processed curve and the standard reference baseline;

[0076] The accumulated error is determined based on a preset health score threshold, the health score of the flight segment is calculated using a linear mapping transformation and compared with the health score lower limit threshold to obtain the engine status health score.

[0077] This embodiment provides an aircraft engine status monitoring method, which uses online monitoring data of various aircraft engine components during the flight of the aircraft to analyze and process multi-source status sensor information collected in real time. Different from designing a supervised learning algorithm for prediction, the health status of aircraft engine components is indirectly predicted through unsupervised design of health index values. This process can accurately monitor the health status of internal components of the aircraft engine without affecting the normal operation of the aircraft engine, providing technical support for the management and maintenance of the aircraft engine.

[0078] Based on the above embodiment, this embodiment describes the method for monitoring the state of an aircraft engine. Figure 2 As shown, the details are as follows:

[0079] Input data selection and data preprocessing;

[0080] Selection of input variables for health status monitoring models of aircraft engine components;

[0081] According to the degradation mechanism analysis and variable correlation analysis of each component inside the aircraft engine, combined with the type of sensors installed in the aircraft engine, it is necessary to select appropriate sensor monitoring data for each component as the input variable of the model. For example, for the lubricating oil supply pipe, you can consider monitoring variables such as lubricating oil pressure signal and lubricating oil volume; for the lubricating oil cooler, you can consider monitoring variables such as lubricating oil temperature; for the fuel pump, you can consider monitoring variables such as fuel flow; for the blades, you can consider monitoring signals such as speed.

[0082] Variable initialization;

[0083] Take the monitoring data of m sensors in n segments as the input data of the model to form a data matrix X = (x ijt ) n×m×p , where x ijt represents the tth data of the jth sensor in the ith flight segment, i = 1, 2, ..., n, j = 1, 2, ..., m, t = 1, 2, ..., p ij ,p=max i＝1,2,…,n,j＝1,2,..,n {p ij}.

[0084] Determine the length interval range of data collection for variables within a single flight segment;

[0085] According to the difference in the length of data collection of the selected variable in a single flight segment, the length interval range of data collection can be obtained [p l ,p], where p l =min i＝1,2,…,n,j＝1,2,..,n {p ij}.

[0086] Perform functional data transformation and standardization on a set of flight segment data when aircraft engine components are operating normally;

[0087] According to the normal operation of the selected aircraft engine components h segment data, set an appropriate standardized data collection length p std , where p std ∈[p l ,p], it is recommended to use the set {p ij} i＝1,2,…,n,j＝1,2,..,n The mode of p std ;

[0088] The component is expressed in this n h The real-time sensor monitoring signals in each flight segment are converted into functional data, recorded as

[0089] Based on the standardized data acquisition length p std , standardize the point grid, eliminate the difference in data collection length of different segments, and obtain a set of functional data of standardized collection length when the component is operating normally, recorded as

[0090] This set of functional data is transformed using B-spline basis functions, and the elastic registration method is used to achieve curve alignment using the properties of the Fisher-Rao metric:

[0091] Set the number of functions K and the spline order D of the B-spline basis function;

[0092] The B-spline basis function expression is as follows:

[0093] B k,1 (x)=1,if t k ≤x <t k+1 ,0otherwise

[0094]

[0095] Wherein, k represents the index value of the B-spline basis function, k=1,2,…,K, and d represents the spline order, d=1,2,…,D.

[0096] Use B-spline basis functions to transform this set of functional data;

[0097] After determining the number and order of B-spline basis functions, this set of functional data Each function curve in is transformed as follows:

[0098]

[0099] in, represents the converted function, c k represents the weight of the kth basis function. The function data converted by the B-spline basis function is recorded as

[0100] The elastic registration method is used to achieve curve alignment based on the SRSF (square-root slope function) framework by taking advantage of the properties of the Fisher-Rao metric.

[0101] by Represents a single function after transformation, recorded as the registration template function g. Calculate the function after registration The warping amount with the minimum Fisher-Rao distance to the registration function g is:

[0102]

[0103] where d λ represents the extended Fisher-Rao distance with a penalty term, which is used to control the amount of warping and is calculated as follows:

[0104]

[0105] The penalty term limits the amount of flexibility used in curve alignment. The functional data after registration is recorded as

[0106] The average of the aligned curves is taken to obtain the standard reference baseline of the real-time sensor monitoring signal of the component in a single flight segment when it is operating normally. The baseline of the jth monitoring signal is recorded as The baseline set of all real-time sensor monitoring signals is recorded as

[0107] For any single flight segment, the accumulated error between the curve of the real-time sensor monitoring signal after data acquisition length normalization, B-spline basis function conversion and elastic registration and the standard reference baseline is used as the basis for evaluating the health status of the component. The lower limit threshold of the health score corresponding to the "normal" state is set, and then the health score of the flight segment is given by linear mapping transformation:

[0108] For any single flight segment that needs to be evaluated, the real-time sensor monitoring signal is subjected to data acquisition length normalization, B-spline basis function conversion and elastic registration to obtain

[0109] The calculated curve With standard reference baseline collection The cumulative error between i ;

[0110] According to the set health score lower limit threshold S corresponding to the "normal" state thr , calculate the health score of the flight segment through linear mapping transformation, denoted as S i and the lower threshold S thr By comparing the health scores, it can be determined whether to repair or replace the components.

[0111] This embodiment provides an aircraft engine status monitoring method, which uses online monitoring data of various aircraft engine components during the flight of the aircraft to analyze and process multi-source status sensor information collected in real time. Different from designing a supervised learning algorithm for prediction, the health status of aircraft engine components is indirectly predicted through unsupervised design of health index values. This process can accurately monitor the health status of internal components of the aircraft engine without affecting the normal operation of the aircraft engine, providing technical support for the management and maintenance of the aircraft engine.

[0112] Based on the above embodiment, this embodiment uses specific data to illustrate the method, which is as follows:

[0113] Health status monitoring of the oil supply pipe of the left engine of aircraft A;

[0114] For the oil supply pipe of the left engine of aircraft A, the oil pressure signal OIL_PRS1_R is selected as the monitoring variable, and a mapping relationship between the variable and the health status of the oil supply pipe is constructed. A total of 1626 flight segments of aircraft A are collected, and the number of sensor oil pressure signals collected in a single segment is approximately 1500 to 2000. The standardized data collection length p_std is set to 2000. A set of 12 flight segment data when the oil supply pipe is operating normally is selected, Figure 3 The original data curve of this group of data is shown. Using the functional data analysis method, the data acquisition length standardization, B-spline basis function conversion and elastic registration are performed on this group of data to obtain 12 registered curves, as shown in Figure 4 Then, the average of this group of curves is taken to obtain the standard reference baseline of the lubricating oil pressure signal OIL_PRS1_R in a single flight segment when the lubricating oil supply pipe is operating normally, as shown in Figure 5 As shown. Based on the cumulative error between the processed monitoring data of a single segment and the standard reference baseline, the health score of the lubricating oil supply pipe is calculated. The lower limit threshold of the health score corresponding to the "normal" state is set to S_thr = 0.9, Figure 6The comparison of the processed oil pressure signal of the oil supply pipe in a normal operation segment and a fault segment with the standard reference baseline is shown. Finally, the health score of the oil supply pipe in a total of 150 segments before and after the fault (segment index 926 to 1075) is calculated and shown in Figure 7 middle.

[0115] Health status monitoring of the oil cooler of the auxiliary power system of aircraft B;

[0116] The main purpose of the auxiliary power system (APU) is to allow the main engine to be stopped without relying on ground equipment to supply electricity. The core part is a small turbine engine. For the oil cooler of the APU of aircraft B, the oil temperature signal OIT_APU is selected as the monitoring variable, and a mapping relationship between this variable and the health status of the oil cooler is constructed. A total of 51 flight segments of aircraft B were collected. The APU is only used at the beginning and end of a single segment. The length of the effective oil temperature signal in a single segment is about 150, so the standardized data collection length p_std=150 is set. A set of 23 flight segment data when the oil cooler is operating normally is selected, Figure 8 The original data curve of this group of data is shown. Using the functional data analysis method, the data acquisition length standardization, B-spline basis function conversion and elastic registration are performed on this group of data to obtain 23 curves after registration, as shown in Fig. 9 Then, the average of this group of curves is taken to obtain the standard reference baseline of the oil temperature signal OIT_APU in a single flight segment when the oil cooler is operating normally, as shown in Fig.10 As shown. Based on the cumulative error between the processed monitoring data of a single flight segment and the standard reference baseline, the health score of the lubricating oil cooler is calculated. The lower limit threshold of the health score corresponding to the "normal" state is set to S_thr = 0.9, Fig.11 The comparison of the processed oil temperature signal of the oil cooler in a normal operation segment and a fault segment with the standard reference baseline is shown. Finally, the health score of the oil cooler in a total of 41 segments was calculated (the 10 segments after the fault were excluded due to abnormal data collection) and is shown in Fig.12 middle.

[0117] Please refer to Fig.13 , Fig.13 A structural block diagram of an aircraft engine status monitoring device provided by an embodiment of the present invention; the specific device may include:

[0118] A data acquisition module 100 is used to acquire the state data of the aircraft engine;

[0119] The function conversion module 200 selects a plurality of flight segment data of normal operation of the aircraft engine component based on the state data, presets the data collection length, and converts the normal operation data of the component to obtain function type data;

[0120] A curve conversion module 300 converts the functional data using a B-spline basis function and obtains a registration curve based on an elastic registration method;

[0121] A reference baseline acquisition module 400 is used to acquire the average value of the registration curve to obtain a standard reference baseline;

[0122] The state evaluation module 500 performs curve processing on the data acquisition length, the B-spline basis function conversion and the elastic registration, and performs error accumulation operation with the standard reference curve to obtain the engine state health score.

[0123] An aircraft engine state monitoring device of the present embodiment is used to implement the aforementioned aircraft engine state monitoring method. Therefore, the specific implementation method of an aircraft engine state monitoring device can be seen in the embodiment part of an aircraft engine state monitoring method in the previous text. For example, the data acquisition module 100, the function conversion module 200, the curve conversion module 300, the reference baseline acquisition module 400, and the state evaluation module 500 are respectively used to implement steps S101, S102, S103, S104, and S105 in the aforementioned aircraft engine state monitoring method. Therefore, its specific implementation method can refer to the description of the corresponding embodiments of each part, which will not be repeated here.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] The collection, storage, use, processing, transmission, provision and disclosure 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.

[0128] 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.

[0129] The present application is expected to provide an implementation scheme for users to selectively block the use or access of personal information data. That is, the present disclosure 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, the risk can be minimized by limiting data collection and deleting the data. In addition, when applicable, such personal information is de-identified to protect the privacy of the user.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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 their combination: 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.

[0135] 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.

[0136] 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.

[0137] 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 monitoring the state of an aircraft engine, characterized in that: include: Obtain status data of aircraft engines; Based on the status data, multiple flight segment data of normal operation of the aircraft engine component are selected, the data collection length is preset, and the normal operation data of the component is converted to obtain function-type data; The functional data is transformed using a B-spline basis function, and a registration curve is obtained based on an elastic registration method; Obtaining an average value of the registration curve to obtain a standard reference baseline; The data acquisition length, the B-spline basis function conversion and the elastic registration are subjected to curve processing, and an error accumulation operation is performed with the standard reference curve to obtain an engine state health score.

2. The method for monitoring the state of an aircraft engine according to claim 1, characterized in that: The obtaining of the state data of the aircraft engine comprises: The input variables of the health status monitoring model of the aircraft engine parts are selected and initialized, and the length interval range of the data collection of the input variables in a single flight segment is determined.

3. The method for monitoring the state of an aircraft engine according to claim 1, characterized in that: Based on the state data, multiple flight segment data of normal operation of the aircraft engine component are selected, the data collection length is preset, and the normal operation data of the component is converted to obtain the function type data including: Preset the data collection length according to multiple flight segments of normal operation of aircraft engine components; The monitoring signal of the component is converted into functional data by using a set of curves discretely expressed in a point grid; The functional data is processed based on the data collection length to obtain functional data of a preset collection length.

4. The method for monitoring the state of an aircraft engine according to claim 1, characterized in that: The method of converting the functional data using a B-spline basis function and obtaining a registration curve based on an elastic registration method comprises: Preset the number of functions and spline order of B-spline basis functions; The functional data is transformed using the B-spline basis function, and the properties of the Fisher-Rao metric are used to achieve curve alignment based on the SRSF framework.

5. The method for monitoring the state of an aircraft engine according to claim 1, characterized in that: The B-spline basis function expression is: Among them, k represents the index value of the B-spline basis function, k = 1, 2, ..., K, and d represents the spline order, d = 1, 2, ..., D.

6. The method for monitoring the state of an aircraft engine according to claim 1, characterized in that: The obtaining of the average value of the registration curve to obtain the standard reference baseline comprises: The average of the aligned curves is taken to obtain the standard reference baseline of the real-time sensor monitoring signal within a single flight segment when the component is operating normally.

7. The method for monitoring the state of an aircraft engine according to claim 1, characterized in that: The data acquisition length, the B-spline basis function conversion and the elastic registration are processed by curve processing, and the error accumulation operation is performed with the standard reference curve to obtain the engine status health score, which includes: Performing curve processing on the data acquisition length, the B-spline basis function conversion and the elastic registration, and calculating the cumulative error between the processed curve and the standard reference baseline; The accumulated error is determined based on a preset health score threshold, the health score of the flight segment is calculated using a linear mapping transformation and compared with the health score lower limit threshold to obtain the engine status health score.

8. An aircraft engine status monitoring device, characterized in that: include: A data acquisition module, which acquires the status data of the aircraft engine; A function conversion module, based on the state data, selects a plurality of flight segment data of normal operation of the aircraft engine component, presets a data collection length, and converts the normal operation data of the component to obtain function type data; A curve conversion module, which converts the functional data using a B-spline basis function and obtains a registration curve based on an elastic registration method; A reference baseline acquisition module is used to obtain the average value of the registration curve to obtain a standard reference baseline; The state evaluation module performs curve processing on the data acquisition length, the B-spline basis function conversion and the elastic registration, and performs error accumulation operation with the standard reference curve to obtain the engine state health score.

9. 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 7.

10. 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 7 when executed by a processor.

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