Method, apparatus and device for testing aircraft fuel equipment based on lvdt

Abstract

The application relates to an LVDT-based aircraft fuel equipment testing method, device and equipment, which is applied to the technical field of aircraft fuel equipment testing and comprises the following steps: acquiring test data and simulation data, the test data being actual test data obtained by an LVDT, the simulation data being simulation test data obtained by simulating a flight process, the test data corresponding to the simulation data one by one; performing curve fitting on the simulation data to obtain at least one fitting curve; determining a correction strategy based on the fitting curve, the simulation data, the test data and an error threshold, wherein the correction strategy comprises a correction type; and correcting the test data based on the correction strategy. The application has the effect of reducing the error of test data.

Description

Technical Field

[0001] The present application relates to the technical field of aircraft fuel equipment testing, and in particular to an LVDT-based aircraft fuel equipment testing method, apparatus, and equipment. Background Art

[0002] Fuel equipment is an essential component of aircraft. Its functions and characteristics play a very important role in the flight safety and mission completion of the aircraft. LVDT linear position sensors are characterized by high temperature and ruggedness. They can withstand high temperature spikes and the harsh environments commonly found in military aircraft. They are often widely used in aircraft fuel equipment to monitor fuel levels, for example.

[0003] However, since the aircraft will be affected by various environmental factors during flight, the flight environment is relatively complex, which will cause errors in the test data obtained by the LVDT linear position sensor. If the error is too large, it will cause serious consequences. Summary of the Invention

[0004] In order to reduce the error of test data, the present application provides an LVDT-based aircraft fuel equipment testing method, device and equipment.

[0005] In a first aspect, the present application provides an LVDT-based aircraft fuel equipment testing method, which adopts the following technical solutions:

[0006] An LVDT-based aircraft fuel equipment testing method, comprising:

[0007] Acquire test data and simulation data, wherein the test data is data obtained from actual LVDT testing, and the simulation data is simulated test data obtained by simulating a flight process, and the test data and the simulation data have a one-to-one correspondence; perform curve fitting on the simulation data to obtain at least one fitting curve;

[0008] determining a correction strategy based on the fitting curve, the simulation data, the test data, and an error threshold, the correction strategy including a correction type;

[0009] The test data is modified based on the modification strategy.

[0010] By adopting the above technical solution, the flight process is simulated to obtain simulation data, and the simulation data is curve fitted to obtain at least one fitting curve. The correction type is determined based on the fitting curve, simulation data, test data and error threshold, thereby determining the correction strategy. The test data is corrected according to the correction strategy, making the test data more accurate and reducing the error of the test data.

[0011] Optionally, performing curve fitting on the simulation data to obtain at least one fitting curve includes:

[0012] grouping the simulation data based on the environmental information to obtain at least one first data combination, wherein the simulation data in each of the first data combinations corresponds to the same environmental information, and the environmental information is used to characterize the flight environment in which the simulation data is tested;

[0013] Perform curve fitting on the simulation data in each of the first data combinations to obtain at least one fitting curve.

[0014] By adopting the above technical solution, the simulation data is grouped according to the corresponding environmental information, so that the simulation data in each first data combination is more stable, and the simulation data of each first data combination is curve fitted separately, so that the error of the fitting curve is smaller, so that the correction strategy determined according to the fitting curve is more accurate, and then the test data corrected using the correction strategy is more accurate, thereby reducing the error of the test data.

[0015] Optionally, the correction type includes test parameter correction and test value correction, and determining the correction strategy based on the fitting curve, the simulation data, the test data, and the error threshold includes:

[0016] If the simulation data is not on the fitting curve, determining the simulation data as the first simulation data;

[0017] Counting the number of the first simulation data corresponding to each of the fitting curves;

[0018] If the number of the first simulation data is greater than a preset number, the correction type is test parameter correction.

[0019] By adopting the above technical solution, when performing curve fitting, if the number of simulation data that does not fall on the fitting curve is greater than a preset number, that is, the stability of the simulation data is poor, the test parameters need to be corrected, that is, the correction type is test parameter correction. Using the corrected test parameters for testing can make the obtained test data more accurate and reduce the error of the test data.

[0020] Optionally, if the correction type is the test parameter correction, the method further includes:

[0021] Acquiring historical test data, wherein the historical test data includes historical parameter data and historical test results;

[0022] Dividing the historical parameter data based on the types of the historical parameter data to obtain at least one parameter set;

[0023] Determine a correlation based on the parameter set and the historical test results, the correlation being a correlation between a parameter corresponding to each type of the historical parameter data and the historical test results;

[0024] Determining the parameter whose correlation is greater than the preset correlation as a correction parameter;

[0025] The correction parameters corresponding to the test data are corrected based on the historical parameter data.

[0026] By adopting the above technical solution, the correlation between each parameter and the historical test results is determined based on the historical parameter data in the historical test data and the corresponding historical test results, the parameter with a correlation greater than the preset correlation is determined as the correction parameter, and the correction parameter corresponding to the test data is corrected according to the historical parameter data, so that the corrected parameter is more effective. Using the corrected test parameters for testing can make the obtained test data more accurate and reduce the error of the test data.

[0027] Optionally, after counting the number of first simulation data corresponding to each fitting curve, the method further includes:

[0028] If the number of the first simulation data is less than or equal to the preset number, calculating the difference between the test data and the corresponding fitting value, where the fitting value is the value corresponding to the test data on the fitting curve;

[0029] If the differences are all smaller than the error threshold, the correction type is the test value correction;

[0030] A correction value is calculated based on the difference.

[0031] By adopting the above technical solution, if the number of the first simulation data is less than or equal to the preset number, that is, the simulation data is relatively stable, then the difference between the test data and the corresponding fitting value is calculated. If the difference is less than the error threshold, it is only necessary to correct the test data to obtain accurate test data. The calculation is performed based on the difference to obtain the correction value. The test data is corrected by the correction value, so that the corrected test data is more accurate and the error of the test data is reduced.

[0032] Optionally, before the correction type is the test value correction if the differences are all smaller than the error threshold, the method further includes:

[0033] Get the fuel equipment model;

[0034] Dividing the test data based on the fuel equipment model to obtain at least one second data combination, each of the second data combinations contains the test data corresponding to the same fuel equipment model;

[0035] An error threshold is determined based on the fuel equipment model corresponding to the second data combination.

[0036] By adopting the above technical solution, since different models of fuel equipment have different accuracy and application scenarios, the error threshold is determined according to the fuel equipment model, so that the error threshold is more in line with actual needs, and the correction strategy determined according to the error threshold is more reasonable, and the test data corrected using the correction strategy is more accurate, thereby reducing the error of the test data.

[0037] Optionally, after calculating the correction value based on the difference, the method further includes:

[0038] If the correction value is greater than the preset correction value, determining fault information;

[0039] A fault warning is performed based on the fault information.

[0040] By adopting the above technical solution, if the correction value is greater than the preset correction value, the LVDT is faulty. Fault information is determined based on the fault situation, and a fault warning is issued based on the fault information, so that relevant maintenance personnel can determine the fault situation in a timely manner and thus repair the LVDT in a timely manner, reducing losses caused by inaccurate testing.

[0041] In a second aspect, the present application provides an LVDT-based aircraft fuel equipment testing device, which adopts the following technical solutions:

[0042] An aircraft fuel equipment testing device based on LVDT, comprising:

[0043] A data acquisition module is used to acquire test data and simulation data. The test data is data obtained from actual LVDT testing, and the simulation data is simulated test data obtained by simulating the flight process. The test data and the simulation data have a one-to-one correspondence.

[0044] A curve fitting module, configured to perform curve fitting on the simulation data to obtain at least one fitting curve;

[0045] a strategy determination module, configured to determine a correction strategy based on the fitting curve, the simulation data, the test data, and an error threshold, wherein the correction strategy includes a correction type;

[0046] A data correction module is used to correct the test data based on the correction strategy.

[0047] By adopting the above technical solution, the flight process is simulated to obtain simulation data, and the simulation data is curve fitted to obtain at least one fitting curve. The correction type is determined based on the fitting curve, simulation data, test data and error threshold, thereby determining the correction strategy. The test data is corrected according to the correction strategy, making the test data more accurate and reducing the error of the test data.

[0048] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0049] An electronic device comprising a processor coupled to a memory;

[0050] The memory stores a computer program that can be loaded by the processor and executes the LVDT-based aircraft fuel equipment testing method according to any one of the first aspects.

[0051] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0052] A computer-readable storage medium stores a computer program capable of being loaded by a processor and executing the LVDT-based aircraft fuel equipment testing method according to any one of the first aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 1 is a flow chart of an LVDT-based aircraft fuel equipment testing method provided in an embodiment of the present application.

[0054] Figure 2 1 is a structural block diagram of an LVDT-based aircraft fuel equipment testing device 200 provided in an embodiment of the present application.

[0055] Figure 3 It is a structural block diagram of the electronic device 300 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The present application is further described in detail below with reference to the accompanying drawings.

[0057] The present invention provides an LVDT-based aircraft fuel equipment testing method. This LVDT-based aircraft fuel equipment testing method can be performed by an electronic device, which can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be, but is not limited to, a smartphone, tablet computer, or desktop computer.

[0058] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0059] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0060] like Figure 1 As shown, a method for testing aircraft fuel equipment based on LVDT is described. The main process of the method is described as follows (steps S101 to S104):

[0061] Step S101: Acquire test data and simulation data.

[0062] The test data is the data obtained from the actual LVDT test, that is, the test results, and the simulation data is the simulated test data obtained by simulating the flight process, that is, the simulated test results. The test data and the simulation data correspond one to one.

[0063] An aircraft simulator is used to simulate the flight process under various flight environments within a first preset time to obtain simulated test data, i.e., simulation data, so that the simulation data can be obtained from the aircraft simulator, and the data obtained by actual testing of the LVDT under various flight environments within the first preset time, i.e., test data, can be obtained from the LVDT of the aircraft. The various flight environments simulated by the aircraft simulator are the same as the various flight environments in which the LVDT of the aircraft obtains test data, and the various parameters used for testing under the same flight environment are the same, i.e., the test data and the simulation data are obtained under the same flight environment and with the same parameters, so the test data and the simulation data are in a one-to-one correspondence, and the first preset time can be half a month, one month, or two months.

[0064] Step S102: Perform curve fitting on the simulation data to obtain at least one fitting curve.

[0065] Specifically, curve fitting is performed on the simulation data to obtain at least one fitting curve, including: grouping the simulation data based on environmental information to obtain at least one first data combination, wherein the simulation data in each first data combination corresponds to the same environmental information, and the environmental information is used to characterize the flight environment in which the simulation data is tested; and curve fitting is performed on the simulation data in each first data combination to obtain at least one fitting curve.

[0066] In this embodiment, in order to more clearly determine the impact of different flight environments on the test, the simulation data is grouped according to the corresponding environmental information to obtain at least one first data combination, so that the simulation data in each first data combination corresponds to the same environmental information, that is, the simulation data in each first data combination are all tested under the same flight environment, and the number of first data combinations is the number of types of environmental information.

[0067] In order to more clearly display the situation of the simulation data, the simulation data in each first data combination is curve fitted separately. The curve fitting process is implemented by a curve fitting tool. The curve fitting tool can be curve software, MATLAB software, or EXCEL software. After curve fitting, the same number of fitting curves as the number of first data combinations will be obtained.

[0068] Step S103: determining a correction strategy based on the fitting curve, simulation data, test data, and error threshold.

[0069] The correction strategy includes correction types, and the correction types include test parameter correction and test value correction.

[0070] Specifically, a correction strategy is determined based on the fitting curve, simulation data, test data and error threshold, including: if the simulation data is not on the fitting curve, the simulation data is determined as the first simulation data; the number of first simulation data corresponding to each fitting curve is counted separately; if the number of first simulation data is greater than the preset number, the correction type is test parameter correction.

[0071] In this embodiment, after curve fitting is performed on the simulation data to obtain a fitting curve, it is determined whether there is simulation data that does not fall on the fitting curve, and the simulation data is determined as the first simulation data, that is, the first simulation data is the simulation data that does not fall on the fitting curve, and the number of first simulation data in the simulation data corresponding to each fitting curve is counted. If the number of first simulation data is greater than the preset number, it means that the simulation data is highly unstable and the error is large. It is necessary to correct the test parameters in the test process, so as to re-test and obtain more stable and accurate simulation data. Therefore, the correction type is test parameter correction, wherein the preset number is obtained by calculation, and the calculation method is: preset number = proportional coefficient * the number of simulation data in the first data combination corresponding to the fitting curve. The proportional coefficient is determined according to the flight requirements. More specifically, the proportional coefficient is inversely correlated with the flight requirements, that is, the higher the flight requirements, the smaller the proportional coefficient. The proportional coefficient can be 5% or 10%.

[0072] More specifically, if the correction type is test parameter correction, the method also includes: obtaining historical test data, the historical test data including historical parameter data and historical test results; dividing the historical parameter data based on the type of historical parameter data to obtain at least one parameter set; determining the correlation based on the parameter set and the historical test results, the correlation being the correlation between the parameter corresponding to each historical parameter data and the historical test results; determining the parameter having a correlation greater than a preset correlation as a correction parameter; and correcting the correction parameter corresponding to the test data based on the historical parameter data.

[0073] In this embodiment, historical test data within a second preset time is obtained from the database, and the historical parameter data is divided according to the type of the historical parameter data to obtain at least one parameter set. The historical parameter data in each parameter set corresponds to the same parameter type, and the number of parameter sets is the number of parameter types corresponding to the historical parameter data. The second preset time can be one month or two months.

[0074] The correlation between each parameter and the historical test results is calculated using the correlation calculation formula. The specific calculation formula can be:

[0075]

[0076] Among them, ρ is used to characterize the correlation between each parameter and historical test results, x i is the i-th historical parameter data corresponding to each parameter, y i is the historical test result corresponding to the i-th historical parameter data, and n is the number of historical parameter data corresponding to each parameter.

[0077] A high correlation means that this type of parameter has a greater impact on the historical test results, that is, this type of parameter is more closely associated with the test results. If the error of the test result is large, it indicates that the possibility of unreasonable setting of this type of parameter is also greater. The parameter with a correlation greater than the preset correlation is determined as the correction parameter, where the preset correlation can be 0.5 or 0.6. If the correction type is test parameter correction, the correction strategy is to modify the correction parameter corresponding to the test data according to the historical parameter data under the same flight environment, thereby improving the accuracy of the test data.

[0078] Specifically, after counting the number of first simulation data corresponding to each fitting curve respectively, the method also includes: if the number of first simulation data is less than or equal to a preset number, calculating the difference between the test data and the corresponding fitting value, and the fitting value is the value corresponding to the test data on the fitting curve; if the difference is less than the error threshold, the correction type is test value correction; and calculating the correction value based on the difference.

[0079] In this embodiment, if the number of the first simulation data is less than or equal to the preset number, it means that the stability of the simulation data is high, the setting of the test parameters is relatively reasonable, and there is no need to correct the test parameters. Since there is a one-to-one correspondence between the test data and the simulation data, there is also a one-to-one correspondence between the simulation data and the fitting value. When the simulation data is on the fitting curve, the simulation data and the fitting value are the same. When the simulation data is not on the fitting curve, that is, when the simulation data is the first simulation data, the simulation data and the fitting value are different. Therefore, the test data and the fitting value are also in a one-to-one correspondence. The difference between the test data and the corresponding fitting value is calculated. If the difference between the test data and the corresponding fitting value is less than the corresponding error threshold, it is only necessary to correct the test data to obtain accurate test data without retesting, saving manpower and material resources. Among them, the error threshold is the maximum value of the error determined by the technician based on the flight situation, that is, the threshold for accurate test data can be obtained by correcting the test data.

[0080] The average value of all the differences obtained from the fitting values ​​in the same fitting curve is calculated, and the average value is used as the correction value of the corresponding test data. The correction strategy is to correct the test data according to the correction value.

[0081] Specifically, if the differences are all less than the error threshold, the correction type is before the test value correction, and the method also includes: obtaining the fuel equipment model; dividing the test data based on the fuel equipment model to obtain at least one second data combination, each second data combination containing test data corresponding to the same fuel equipment model; and determining the error threshold based on the fuel equipment model corresponding to the second data combination.

[0082] In this embodiment, the fuel equipment model corresponding to each test data is obtained from the database. The fuel equipment model is the type of fuel equipment. The test data is divided according to the fuel equipment model to obtain at least one second data combination. The number of second data combinations is equal to the number of types of fuel equipment. The error threshold is determined by the staff according to the precision of the fuel equipment. Each fuel equipment has the same precision. The correspondence between the fuel equipment model and the error threshold is pre-stored in the database. Therefore, the error threshold can be searched from the database according to the fuel equipment model. More specifically, the precision of the fuel equipment is inversely correlated with the error threshold, that is, the higher the precision of the fuel equipment, the smaller the error threshold, and the lower the precision of the fuel equipment, the larger the error threshold.

[0083] Specifically, after calculating the correction value based on the difference, the method further includes: if the correction value is greater than a preset correction value, determining fault information; and performing a fault warning based on the fault information.

[0084] In this embodiment, if the correction value is greater than the preset correction value, it means that the test data needs to be corrected by a large value, that is, the gap between the test data and the accurate data is large. At this time, it can be determined that the LVDT is faulty, and the fault information is "The gap between the test data and the accurate data is large, and the LVDT is faulty." A fault warning is issued based on the fault information, so that relevant maintenance personnel can determine the fault situation in time, and thus repair the LVDT in time, reducing losses caused by inaccurate testing. Among them, the preset correction value is the maximum error value determined by the maintenance personnel to indicate that the LVDT is not faulty.

[0085] Step S104: Correct the test data based on the correction strategy.

[0086] If the correction type is test value correction, the test data is corrected according to the correction value. If the correction type is test parameter correction, the correction parameters corresponding to the test data are modified according to the historical parameter data under the same flight environment, so that the test is re-performed according to the modified correction parameters to obtain accurate test data.

[0087] Figure 2 This is a structural block diagram of an LVDT-based aircraft fuel equipment testing device 200 provided in an embodiment of the present application.

[0088] like Figure 2 As shown, the LVDT-based aircraft fuel equipment testing device 200 mainly includes:

[0089] The data acquisition module 201 is used to acquire test data and simulation data. The test data is the data obtained by the actual LVDT test, and the simulation data is the simulated test data obtained by simulating the flight process. The test data and the simulation data have a one-to-one correspondence.

[0090] The curve fitting module 202 is used to perform curve fitting on the simulation data to obtain at least one fitting curve;

[0091] A strategy determination module 203 is configured to determine a correction strategy based on the fitting curve, simulation data, test data, and an error threshold, wherein the correction strategy includes a correction type;

[0092] The data correction module 204 is configured to correct the test data based on the correction strategy.

[0093] As an optional implementation of this embodiment, the curve fitting module 202 is further specifically used to perform curve fitting on the simulation data to obtain at least one fitting curve, including: grouping the simulation data based on environmental information to obtain at least one first data combination, wherein the simulation data in each first data combination corresponds to the same environmental information, and the environmental information is used to characterize the flight environment in which the simulation data is tested; and performing curve fitting on the simulation data in each first data combination to obtain at least one fitting curve.

[0094] As an optional implementation of this embodiment, the correction type includes test parameter correction and test value correction. The strategy determination module 203 is also specifically used to determine the correction strategy based on the fitting curve, simulation data, test data and error threshold, including: if the simulation data is not on the fitting curve, then the simulation data is determined as the first simulation data; counting the number of first simulation data corresponding to each fitting curve respectively; if the number of first simulation data is greater than the preset number, then the correction type is test parameter correction.

[0095] As an optional implementation of this embodiment, the strategy determination module 203 is also specifically used to, if the correction type is test parameter correction, include: obtaining historical test data, the historical test data including historical parameter data and historical test results; dividing the historical parameter data based on the type of historical parameter data to obtain at least one parameter set; determining the correlation based on the parameter set and the historical test results, the correlation being the correlation between the parameter corresponding to each historical parameter data and the historical test results; determining the parameter having a correlation greater than a preset correlation as a correction parameter; and correcting the correction parameter corresponding to the test data based on the historical parameter data.

[0096] As an optional implementation of this embodiment, the strategy determination module 203 is also specifically used to, after counting the number of first simulation data corresponding to each fitting curve, include: if the number of first simulation data is less than or equal to a preset number, then calculating the difference between the test data and the corresponding fitting value, the fitting value is the value corresponding to the test data on the fitting curve; if the difference is less than the error threshold, the correction type is test value correction; and calculating the correction value based on the difference.

[0097] As an optional implementation of this embodiment, the strategy determination module 203 is also specifically used to, before the correction type is test value correction if the difference values ​​are all less than the error threshold, include: obtaining the fuel equipment model; dividing the test data based on the fuel equipment model to obtain at least one second data combination, each second data combination contains test data corresponding to the same fuel equipment model; and determining the error threshold based on the fuel equipment model corresponding to the second data combination.

[0098] As an optional implementation of this embodiment, the strategy determination module 203 is further specifically configured to, after calculating the correction value based on the difference, include: determining fault information if the correction value is greater than a preset correction value; and performing a fault warning based on the fault information.

[0099] In one example, the module in any of the above devices can be one or more integrated circuits configured to implement the above methods, such as: one or more application specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0100] For another example, when the modules in the device can be implemented in the form of a processing element scheduling program, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor capable of calling programs. For another example, these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0101] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0102] Figure 3 This is a structural block diagram of an electronic device 300 provided in an embodiment of the present application.

[0103] like Figure 3 As shown, the electronic device 300 includes a processor 301 and a memory 302 , and may further include an information input / information output (I / O) interface 303 , one or more communication components 304 , and a communication bus 305 .

[0104] The processor 301 is used to control the overall operation of the electronic device 300 to complete all or part of the steps of the aforementioned LVDT-based aircraft fuel equipment testing method. The memory 302 is used to store various types of data to support the operation of the electronic device 300. Such data may include, for example, instructions for any application or method operating on the electronic device 300, as well as application-related data. The memory 302 may be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0105] The I / O interface 303 provides an interface between the processor 301 and other interface modules, which may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 304 is used for wired or wireless communication between the electronic device 300 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more thereof, therefore, the corresponding communication component 304 may include: Wi-Fi components, Bluetooth components, NFC components.

[0106] The electronic device 300 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components, and is used to execute the LVDT-based aircraft fuel equipment testing method provided in the above embodiment.

[0107] Communication bus 305 may include a path for transmitting information between the aforementioned components. Communication bus 305 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, for example. Communication bus 305 may be divided into an address bus, a data bus, a control bus, and the like.

[0108] The electronic device 300 may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., as well as fixed terminals such as digital TVs, desktop computers, etc., and may also be servers, etc.

[0109] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the above-mentioned LVDT-based aircraft fuel equipment testing method are implemented.

[0110] The computer-readable storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc., which can store program codes.

[0111] The terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0112] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of application involved in this application is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the aforementioned application concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions applied for in this application.

Claims

1. A method for testing aircraft fuel equipment based on LVDT, characterized in that: include: Acquire test data and simulation data, wherein the test data is data obtained from actual LVDT testing, and the simulation data is simulated test data obtained by simulating a flight process, and the test data and the simulation data correspond one-to-one; Performing curve fitting on the simulation data to obtain at least one fitting curve; Determining a correction strategy based on the fitting curve, the simulation data, the test data, and an error threshold, the correction strategy including a correction type, and the correction type including a test parameter correction and a test value correction; The determining of a correction strategy based on the fitting curve, the simulation data, the test data, and the error threshold comprises: If the simulation data is not on the fitting curve, determining the simulation data as the first simulation data; Counting the number of the first simulation data corresponding to each of the fitting curves; If the number of the first simulation data is greater than a preset number, the correction type is test parameter correction; After counting the number of first simulation data corresponding to each fitting curve, the method further includes: If the number of the first simulation data is less than or equal to the preset number, calculating the difference between the test data and the corresponding fitting value, where the fitting value is the value corresponding to the test data on the fitting curve; If the differences are all smaller than the error threshold, the correction type is the test value correction; calculating a correction value based on the difference; The test parameters or test values ​​are modified based on the modification strategy.

2. The method according to claim 1, characterized in that The performing curve fitting on the simulation data to obtain at least one fitting curve comprises: grouping the simulation data based on the environmental information to obtain at least one first data combination, wherein the simulation data in each of the first data combinations corresponds to the same environmental information, and the environmental information is used to characterize the flight environment in which the simulation data is tested; Perform curve fitting on the simulation data in each of the first data combinations to obtain at least one fitting curve.

3. The method according to claim 1, characterized in that If the correction type is the test parameter correction, the method further includes: Acquiring historical test data, wherein the historical test data includes historical parameter data and historical test results; Dividing the historical parameter data based on the types of the historical parameter data to obtain at least one parameter set; Determine a correlation based on the parameter set and the historical test results, the correlation being a correlation between a parameter corresponding to each type of the historical parameter data and the historical test results; Determining the parameter whose correlation is greater than the preset correlation as a correction parameter; The correction parameters corresponding to the test data are corrected based on the historical parameter data.

4. The method according to claim 1, wherein Before the step of setting the correction type to test value correction if the differences are all smaller than the error threshold, the method further includes: Get the fuel equipment model; Dividing the test data based on the fuel equipment model to obtain at least one second data combination, each of the second data combinations contains the test data corresponding to the same fuel equipment model; An error threshold is determined based on the fuel equipment model corresponding to the second data combination.

5. The method according to claim 1, wherein After calculating the correction value based on the difference, the method further includes: If the correction value is greater than the preset correction value, determining fault information; A fault warning is performed based on the fault information.

6. An aircraft fuel equipment testing device based on LVDT, characterized in that: include: A data acquisition module is used to acquire test data and simulation data. The test data is data obtained from actual LVDT testing, and the simulation data is simulated test data obtained by simulating the flight process. The test data and the simulation data have a one-to-one correspondence. A curve fitting module, configured to perform curve fitting on the simulation data to obtain at least one fitting curve; a strategy determination module, configured to determine a correction strategy based on the fitting curve, the simulation data, the test data, and an error threshold, wherein the correction strategy includes a correction type, and the correction type includes a test parameter correction and a test value correction; The determining of a correction strategy based on the fitting curve, the simulation data, the test data, and the error threshold comprises: If the simulation data is not on the fitting curve, determining the simulation data as the first simulation data; Counting the number of the first simulation data corresponding to each of the fitting curves; If the number of the first simulation data is greater than a preset number, the correction type is test parameter correction; After counting the number of first simulation data corresponding to each fitting curve, the method further includes: If the number of the first simulation data is less than or equal to the preset number, calculating the difference between the test data and the corresponding fitting value, where the fitting value is the value corresponding to the test data on the fitting curve; If the differences are all smaller than the error threshold, the correction type is the test value correction; calculating a correction value based on the difference; A data correction module is used to correct the test parameters or test values ​​based on the correction strategy.

7. An electronic device, characterized in that: comprising a processor coupled to a memory; The processor is configured to execute the computer program stored in the memory, so that the electronic device performs the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The method comprises a computer program or instructions, which, when executed on a computer, causes the computer to execute the method according to any one of claims 1 to 5.

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