Flight data decoding configuration method and device, computer device and storage medium

Abstract

The application relates to a flight data decoding configuration method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: determining matching target sensor configuration parameters based on the aircraft type and flight time information of an aircraft from various sensor configuration parameters; the sensor configuration parameters are configuration information in a storage process; converting the target sensor configuration parameters into decoding configuration parameters according to the metadata of the target sensor configuration parameters; and performing parameter configuration on the decoding process of the flight data according to the decoding configuration parameters. The method can determine the decoding configuration parameters of various sensor data through metadata, can convert the target sensor configuration parameters into decoding configuration parameters, can improve the accuracy of the decoding process of configuration data, and can reuse the decoding configuration, thereby improving the efficiency and accuracy of the parameter configuration of the decoding process.

Description

Technical Field

[0001] This application relates to the field of aviation technology, and in particular to a flight data decoding and configuration method, apparatus, computer equipment, storage medium, and computer program product. Background Technology

[0002] Quick Access Recorder (QAR) data was initially used for the investigation and analysis of flight accidents / incidents. Currently, QAR data is widely used in all phases of flight.

[0003] In traditional techniques, the data decoding process for fast access recorders requires manual configuration and updates of parameters. This involves exporting all the record parameter XML files from the AIRFASE FAP file to obtain all record parameter XML files for each aircraft type, and then importing the parameter configurations. This process cannot achieve fully automated updates of data acquisition parameter configurations for aircraft, requires an excessive number of files, and is inefficient. Summary of the Invention

[0004] Therefore, it is necessary to provide a flight data decoding configuration method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can improve the decoding efficiency of fast access recorders in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a flight data decoding configuration method. The method includes:

[0006] From the configuration parameters of each sensor, the matching target sensor configuration parameters are determined based on the aircraft type and flight time information; the sensor configuration parameters are configuration information stored in the process.

[0007] Based on the metadata of the target sensor configuration parameters, the target sensor configuration parameters are converted into decoded configuration parameters;

[0008] The decoding process of the flight data is configured according to the decoding configuration parameters.

[0009] In one embodiment, determining the matching target sensor configuration parameters from the various sensor configuration parameters based on the aircraft type and flight time information includes:

[0010] Determine the aircraft's departure batch and the date the aircraft was in flight;

[0011] In the sensor configuration parameters of each fast access recorder, a matching target sensor configuration parameter is found based on the takeoff batch and the date.

[0012] In one embodiment, before converting the sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters, the process includes:

[0013] It was determined that all strings contained in the target sensor configuration parameters were parsable characters;

[0014] The completeness of the target sensor configuration parameters is determined according to the preset parameter format;

[0015] If the target sensor configuration parameters are complete, the target sensor configuration parameters are parsed to obtain the metadata of the target sensor configuration parameters.

[0016] In one embodiment, the sensor configuration parameters include configuration parameters for each subframe and data content types for each sensor parameter; the metadata includes parameter structure metadata of the sensor configuration parameters; the step of converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes:

[0017] When the data content type belongs to a preset type and the configuration parameters of each subframe are consistent, it is determined that the target sensor configuration parameters pass the verification, and the verified sensor configuration parameters are converted into decoded configuration parameters.

[0018] When the data content type does not belong to the preset type and the configuration parameters of each subframe are consistent, it is determined whether the number of parameter structures of the sensor parameters matches the preset number indicated by the parameter structure metadata. If they match, it is determined that the target sensor configuration parameters have passed the verification, and the verified sensor configuration parameters are converted into decoded configuration parameters.

[0019] In one embodiment, the decoding configuration parameters include the parameter sampling frequency corresponding to the subframe parameter configuration value; the step of converting the target sensor configuration parameters into decoding configuration parameters according to the metadata of the target sensor configuration parameters includes:

[0020] Based on the metadata, the target sensor configuration parameters are converted into numerical types to obtain the format-converted sensor configuration parameters.

[0021] During the process of converting sensor configuration parameters into the numerical type, the parameter sampling frequency corresponding to the subframe parameter configuration value is determined based on the subframe parameter configuration value of the target sensor configuration parameters.

[0022] In one embodiment, determining the parameter sampling frequency corresponding to the subframe parameter configuration value based on the subframe parameter configuration value includes:

[0023] If the subframe parameter configuration value represents all subframes, then the parameter sampling frequency corresponding to the subframe parameter configuration value is determined according to the maximum value in the metadata of each parameter structure.

[0024] If the subframe parameter configuration value has a preset symbol, then the preset parameter value corresponding to the preset symbol is determined as the parameter sampling frequency corresponding to the subframe parameter configuration value;

[0025] If the subframe parameter configuration value represents not all subframes and the preset symbol does not exist, then the preset parameter value corresponding to the not all subframes is determined as the parameter sampling frequency corresponding to the subframe parameter configuration value.

[0026] In one embodiment, converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes:

[0027] If the sensor parameters configured by the target sensor configuration parameters include a parameter structure and there are multiple parameter structure metadata, then the sensor parameters are configured according to the number of parameter structure metadata through the sensor configuration parameters to obtain the decoded configuration parameters;

[0028] If the target sensor configuration parameters include multiple parameter structures, then in each parameter structure, the sensor parameters are configured using the sensor configuration parameters to obtain the decoding configuration parameters.

[0029] In one embodiment, converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes:

[0030] The decoding configuration parameter table is compared with the target sensor configuration parameters in sequence according to one or more metadata of parameter identifier, parameter data content type, parameter custom configuration information, storage unit location, and parameter bit, to obtain the newly added decoding configuration parameters in the target sensor configuration parameters;

[0031] Add the new decoding configuration parameters to the decoding configuration parameter table.

[0032] In one embodiment, determining the matching sensor configuration parameters based on the aircraft type and flight time information includes:

[0033] In the batch of aircraft taking off, the server periodically polls the matching relationship between the target aircraft and the sensor configuration parameters, and determines the target sensor configuration parameters that the target aircraft matches based on the matching relationship.

[0034] The server determines the status parameters indicated by the flight detail task based on the association between the target aircraft and the flight detail task;

[0035] The server determines the conversion time of the decoding configuration parameters based on the status parameters;

[0036] The step of converting the sensor configuration parameters into decoded configuration parameters according to the metadata of the sensor configuration parameters includes:

[0037] During the decoding configuration parameter conversion time of the target aircraft, the server converts the sensor configuration parameters of the target aircraft into the decoding configuration parameters of the target aircraft according to the metadata of the sensor configuration parameters of the target aircraft.

[0038] Secondly, this application also provides an apparatus for flight data decoding and configuration. The apparatus includes:

[0039] The configuration parameter matching module is used to determine the target sensor configuration parameters to match from the configuration parameters of each sensor, based on the aircraft type and flight time information; the sensor configuration parameters are configuration information stored in the process.

[0040] The parameter conversion module is used to convert the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters;

[0041] The decoding configuration module is used to configure the decoding process of the flight data according to the decoding configuration parameters.

[0042] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the flight data decoding configuration steps in any of the above embodiments.

[0043] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the flight data decoding configuration steps in any of the above embodiments.

[0044] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the flight data decoding configuration steps in any of the above embodiments.

[0045] The aforementioned flight data decoding and configuration method, apparatus, computer equipment, storage medium, and computer program product determine matching target sensor configuration parameters from various sensor configuration parameters based on the aircraft's takeoff batch and flight time information. These target sensor configuration parameters are configuration information stored in the process. The target sensor configuration parameters are converted into decoding configuration parameters according to their metadata. The decoding process of the flight data is then configured according to these decoding configuration parameters. Since the metadata of the target sensor configuration parameters is universal for both types of configuration parameters, decoding configuration parameters for various types of sensor data can be determined through the metadata. This allows the target sensor configuration parameters to be converted into decoding configuration parameters, improving the accuracy of the data decoding process. Furthermore, the decoding configuration can be reused, enhancing the efficiency and accuracy of parameter configuration in the decoding process. Attached Figure Description

[0046] Figure 1 This is an application environment diagram of the flight data decoding configuration method in one embodiment;

[0047] Figure 2 This is a flowchart illustrating a flight data decoding configuration method in one embodiment;

[0048] Figure 3 A structural block diagram of a device configured for flight data decoding in one embodiment;

[0049] Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0051] The nodes that can be used for fast access recorder data include, but are not limited to: flight quality monitoring, aircraft and engine status and performance monitoring, fuel consumption, flight route and other aspects of flight operation monitoring, improvement and optimization of aircraft design, test flight troubleshooting, pilot training and training, and various flight-related special studies, which can be studies on turbulence, hard landing, etc.

[0052] The flight data decoding configuration method provided in this application embodiment can be applied to, for example, Figure 1 The application environment shown.

[0053] The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart airborne equipment. Portable wearable devices can include head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster composed of multiple servers. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated onto the server 104 or placed on a cloud or other network server. Unless otherwise specified, the solutions in this case can all be executed on a server or on a terminal.

[0054] In one embodiment, such as Figure 2 As shown, a flight data decoding configuration method is provided, which can be applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0055] Step 202: Determine the matching target sensor configuration parameters from the various sensor configuration parameters based on the aircraft type and flight time information; the sensor configuration parameters are configuration information stored in the process.

[0056] Sensor configuration parameters are used to configure sensor parameters during the storage process, ensuring that at least some sensor parameter values ​​are stored in their respective storage locations. Since the sensor configuration parameters are set specifically for each storage location, the data storage location for each sensor parameter can be quickly determined through these parameters, thereby enabling the retrieval of the corresponding sensor parameter data.

[0057] Taking ARINC717 and ARINC767 as examples, the sensor configuration parameters are the parameters in the recording map file. The decoding processing methods corresponding to each specification can be the same or different. For example, under the ARINC717 specification, QAR data in txt format is processed; while under the ARINC767 specification, QAR data in xml format is processed.

[0058] Aircraft type and flight time information are two dimensions for setting sensor profiles. The aircraft type is calculated based on a specific flight batch and is used to identify a particular batch of aircraft. Flight time information is used to determine the date or other time period during the flight. Sensor profiles can be created, generated, or modified using the aircraft's takeoff batch and takeoff date. Correspondingly, target sensor profiles can be determined using the takeoff batch and takeoff date.

[0059] In one embodiment, determining matching target sensor configuration parameters based on aircraft type and flight time information includes: determining the aircraft's takeoff batch and the date of the aircraft's flight; and searching for matching target sensor configuration parameters in the sensor configuration parameters of each fast access recorder based on the takeoff batch and date.

[0060] The takeoff batch refers to the flight batch of an aircraft at its departure airport, which determines the number of flights taking off within a unit of time. The flight process date refers to the date on which the aircraft performs its flight process, used to determine the overall time range. By using the takeoff batch and the flight process date, a target aircraft requiring flight data decoding configuration can be identified from among the various aircraft. The sensor configuration file of the fast storage recorder installed on the target aircraft is the target sensor configuration file.

[0061] In one implementation, in the sensor profiles of each fast access recorder, a matching target sensor profile is searched based on the takeoff batch and date, including: determining the fast access recorder for each aircraft; polling the matching relationship between the aircraft in the takeoff batch and the sensor profiles according to the date of the aircraft's flight, and determining the target sensor profile matched by the target aircraft based on the matching relationship.

[0062] By determining the target sensor profile based on the takeoff batch and the date of the aircraft during flight, the target sensor profile of the target aircraft can be directly inferred from the data of the takeoff airport, with moderate accuracy, which can meet the decoding process of flight data.

[0063] Step 204: Convert the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters.

[0064] Metadata is structured data of the target sensor configuration parameters, used to describe the target sensor parameters so that the target sensor configuration parameters can be accurately converted into target sensor configuration parameters. For example, parameter name, parameter description, parameter type, subframe configuration, parameter symbol identifier, and parameter sampling frequency are metadata, while the configuration data corresponding to each of these parameters are the target sensor configuration parameters. Correspondingly, the parameter values ​​corresponding to each of these parameters are the parameter values ​​of the sensor parameters configured by the target sensor configuration parameters.

[0065] Decoding is used to convert raw data in binary format recorded in DFDR, QAR, or DAR recorders into engineering data values ​​with units. Decoding is the reverse process of recording, and its key point is to clarify the mapping relationship between various specifications such as ARINC717 and ARINC767.

[0066] Decoding is used to faithfully reconstruct the parameter values ​​of flight parameters recorded by the data recorder (DFDR, QAR, or DAR). Traditional manual decoding involves first identifying the parameter's recording location (Subframe, Word, Bits, Superframe Cycle) based on the data recording map to calculate the raw value. It derives the raw data of the parameter based on the parameter types (BNR, BCD, Discrete, etc.) defined in the aircraft parameter specification manual, and then calculates the engineered value of the parameter based on the parameters defined in the aircraft parameter specification manual. This process requires manual configuration by the user throughout, resulting in low efficiency.

[0067] In one embodiment, before converting the sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters, the process includes: determining that all strings contained in the target sensor configuration parameters are parsable characters; determining the completeness of the target sensor configuration parameters according to a preset parameter format; and if the target sensor configuration parameters are complete parameters, parsing the target sensor configuration parameters to obtain the metadata of the target sensor configuration parameters.

[0068] Resolvable characters are those that can be parsed during the decoding process. They are used to determine whether the characters in the target sensor configuration file conform to the decoding standard. For example, if the decoding process detects that special characters such as @, !, and ~ cannot be parsed, these special characters can be deleted, which can also indicate that the target sensor configuration file is abnormal.

[0069] The preset parameter format includes the sensor's parameter name, parameter word position, configuration parameters used to define subframes, least significant bit, most significant bit, coefficient 0, coefficient 1, and whether there is a sign bit. Optionally, if any parameter in the target sensor configuration parameters does not conform to its preset parameter format, and no corresponding parameter format adjustment interface is detected, the target sensor configuration file is determined to be abnormal.

[0070] In the event of abnormal configuration of target sensor parameters, it is not necessary to obtain the corresponding metadata, so as to avoid excessive data processing during the data conversion process and thus speed up the decoding and configuration.

[0071] In one embodiment, converting the target sensor configuration parameters into decoding configuration parameters according to the target sensor configuration parameter metadata includes: configuring parameters, frame configuration parameters, and subframe configuration parameters according to the target sensor configuration file format, and sequentially converting the target sensor configuration file format, frame structure, and subframe structure into a decoding configuration file. The decoding configuration file is used to configure the flight data decoding process in the flight recorder memory to define the parameters for decoding flight data for each flight phase within a flight segment.

[0072] In an exemplary embodiment, the sensor configuration parameters are parameters in the sensor configuration file, i.e., the MAP configuration file; step 202 converts the MAP configuration file into a MAP_TO_PARAMETER table. The MAP configuration file is named eo_2022_01_01_map.txt. After parsing the contents of the file, the contents corresponding to each sensor configuration parameter are obtained; each sensor configuration parameter includes, but is not limited to, WRD, SF, LSB, LEN, SGN, MNEMONIC, AGE, POLY0, POLY1, PARAMETER, DESCRIPT, CRS FORMAT, CNVRSN, PARAM TYPE, ZERO TEXT, NON ZERO, and COMMENT.

[0073] WRD corresponds to the parameter word position; SF indicates the subframe configuration parameter used to define the subframe, with numbers 1 to 4 indicating the subframe in which it is used, and ALL indicating that all 4 subframes are used to fill this parameter; LSB indicates the least significant bit of the word; LEN indicates the number of bits in the parameter data, and the most significant bit can be calculated by combining the least significant bit; SGN indicates whether it is unsigned, N indicates unsigned, and Y indicates signed; MNEMONIC indicates the parameter abbreviation; AGE is the parameter structure metadata, indicating how many parts the parameter consists of, composed of numbers, with 1 for empty, and the larger the number, the earlier the parameter is recorded, indicating that the parameter is stored in the first place; POLY0 and POLY1 represent coefficient 0 and coefficient 1, the final engineered value of the decoded parameter, which will be used for parameter description and parameter variants, namely, PARAMETER DESCRIPTION and AIRCRAFT_PARAMETER_VERSION. CRS represents the CRS checksum; FORMAT represents the parameter content type, which includes encoding types such as BNR, BCD, DIS, ASCII, and INT, each corresponding to a different parsing method; CNVRSN represents the CNV checksum; PARAM TYPE represents the parameter type, and DITS are all numeric types; ZERO TEXT and NON ZERO represent content with 0 and non-zero values, used to display discrete type content; COMMENT is the parameter configuration comment.

[0074] Among them, AGE is the parameter structure metadata, which indicates how many parts the parameter consists of. It is composed of numbers, with 1 being empty. The larger the number, the earlier the parameter is recorded, indicating that the parameter is ultimately stored first.

[0075] In one optional implementation, the sensor configuration parameters include configuration parameters for each subframe and data content types for each sensor parameter; the metadata includes parameter structure metadata for the sensor configuration parameters. The subframe configuration parameters are used to configure parameter storage at the data granularity of the subframe; the data content types for each sensor parameter include BNR, BCD, DIS, ASCII, or INT, etc.; the parameter structure metadata is used to define the preset number of sensor parameters that should be configured by each sensor configuration parameter.

[0076] Optionally, before converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters, the process includes: verifying parameters other than special non-verification parameters such as positioning or formatting in the target sensor configuration parameters according to the metadata, to obtain verified parameters; and converting the target sensor configuration parameters into decoded configuration parameters. The non-verification parameters include the synchronization word, and the verified parameters include the synchronization word and the verified target sensor configuration parameters.

[0077] In an optional embodiment, converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes: when the data content type belongs to a preset type and the configuration parameters of each subframe are consistent, determining that the target sensor configuration parameters pass the verification, and converting the verified sensor configuration parameters into decoded configuration parameters; when the data content type does not belong to a preset type and the configuration parameters of each subframe are consistent, determining whether the number of parameter structures of the sensor parameters matches the preset number indicated by the parameter structure metadata, and if they match, determining that the target sensor configuration parameters pass the verification, and converting the verified sensor configuration parameters into decoded configuration parameters.

[0078] In one embodiment, determining whether the number of parameter structures of the sensor parameters matches the preset number indicated by the parameter structure metadata includes: determining the cumulative value of the number of parameter structures indicated by the sensor parameters, and the cumulative value of the preset number indicated by the metadata of each parameter structure; determining whether the cumulative value of the number of parameter structures is the same as the cumulative value of the preset number; if they are the same, they match; if they are not the same, they do not match.

[0079] When the data content type is a preset type and the configuration parameters of each subframe are consistent, the parameter structure verification process of the sensor parameters by the parameter structure metadata can be omitted, and this identification process can be directly achieved through the configuration parameters of each subframe. When the data content type is not a preset type and the configuration parameters of each subframe are consistent, the number of parameter structures of the sensor parameters is counted, and it is determined whether the number of parameter structures of the sensor parameters matches the preset number indicated by the parameter structure metadata, so as to accurately realize the parameter structure verification.

[0080] In an exemplary embodiment, all sensor parameters in the MAP_TO_PARAMETER table are retrieved and categorized. Each sensor parameter is validated. If validation fails, a configuration error is indicated to the user, and the import process is terminated. First, it is determined whether the sensor parameter is a special parameter, such as a synchronization word; if so, this sensor parameter is ignored. Next, the subframe configuration of the sensor parameter is checked for consistency. If the sensor parameter consists of multiple parts, the subframe configuration of each part is checked for consistency. If they are different, the parameter validation fails, and the user is prompted that the parameter subframe configuration is incorrect. If the sensor parameter is not encoded using BCD encoding, the parameter structure metadata (AGE) is checked for correctness. The total number of parameter structures in the standard sensor parameter is compared with the total number indicated by the parameter structure metadata. If they are different, the check fails, and the user is prompted that the sensor parameter structure configuration is incorrect. It is understood that the target sensor configuration parameters involved in step 204 are the validated sensor configuration parameters.

[0081] In one embodiment, converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes: converting the target sensor configuration parameters into numerical types according to each metadata to obtain the format-converted sensor configuration parameters; and determining the parameter sampling frequency corresponding to the subframe parameter configuration value based on the subframe parameter configuration value of the target sensor configuration parameters during the conversion of the sensor configuration parameters into numerical types.

[0082] The subframe parameter configuration value is used to determine the number of subframes configured for each sensor parameter. The larger the data volume of a sensor parameter, the more subframes it corresponds to. For example, if the data volume of a certain sensor parameter needs to fill 4 subframes, then the data granularity of that sensor parameter is a concept of frame granularity; if the data volume of a certain sensor parameter needs to fill 16 subframes, then the data granularity of that sensor parameter is a concept of superframe granularity.

[0083] In one implementation, the target sensor configuration parameters are converted into numerical types according to each metadata to obtain format-converted sensor configuration parameters. This includes: sequentially converting the target sensor parameters of each metadata into a preset numerical type to obtain format-converted sensor configuration parameters. For example, the parameter word position, least significant bit, most significant bit, coefficient 0, and coefficient 1 from the MAP_TO_PARAMETER configuration table are added to the WORD_DEFINITION table.

[0084] In one embodiment, determining the parameter sampling frequency corresponding to the subframe parameter configuration value based on the subframe parameter configuration value of the target sensor configuration parameters includes: mapping the subframe parameter configuration value of the target sensor configuration parameters to obtain a mapping result; and determining the parameter sampling frequency corresponding to the subframe parameter configuration value based on the meaning represented by the mapping result.

[0085] The configuration parameters are converted step by step according to the metadata, thereby efficiently and accurately converting the sensor configuration parameters into decoding configuration parameters. The appropriate parameter sampling frequency is determined by the subframe parameter configuration values ​​to facilitate the extraction of flight data from the fast storage recorder, thus enabling efficient decoding. Optionally, the target sensor configuration parameters involved in this embodiment are the verified sensor configuration parameters.

[0086] In one specific implementation, determining the parameter sampling frequency corresponding to the subframe parameter configuration value based on the subframe parameter configuration value includes: if the subframe parameter configuration value represents all subframes, then determining the parameter sampling frequency corresponding to the subframe parameter configuration value based on the maximum value in the metadata of each parameter structure; if the subframe parameter configuration value has a preset symbol, then determining the preset parameter value corresponding to the preset symbol as the parameter sampling frequency corresponding to the subframe parameter configuration value; if the subframe parameter configuration value represents not all subframes and does not have a preset symbol, then determining the preset parameter value corresponding to not all subframes as the parameter sampling frequency corresponding to the subframe parameter configuration value.

[0087] Optionally, if a subframe parameter configuration value of 0 or other preset parameters used to characterize all subframes are detected, then the subframe parameter configuration value characterizes all subframes. In this case, the parameter sampling frequency of the sensor parameter is determined based on the maximum value of the parameter structure metadata. The fast storage recorder extracts the data of the sensor parameter according to this parameter sampling frequency and stores the sensor parameter data in all subframes of that sensor parameter for decoding. For example, if the subframe parameter configuration value is 0, the result of adding 1 to the maximum value of the parameter structure metadata is used as the parameter sampling frequency of the sensor parameter.

[0088] Optionally, if the subframe parameter configuration value contains a comma or other preset symbol, the preset parameter values ​​corresponding to the decimal point or other preset symbol are mapped to obtain a mapping result; the parameter sampling frequency corresponding to the subframe parameter configuration value is determined based on this mapping result. For example, if the subframe parameter configuration value is non-zero and contains a comma, the parameter frequency is 0.5. Wherein, if the subframe parameter configuration value contains a decimal point or other preset symbol, the subframe parameter configuration value represents not all subframes.

[0089] Optionally, if the subframe parameter configuration value represents not all subframes and there is no preset symbol, then the preset parameter value corresponding to the not all subframes is determined as the parameter sampling frequency corresponding to the subframe parameter configuration value. For example, if the subframe parameter configuration value is a number greater than 0 and the number does not contain a comma, the parameter frequency is 0.25.

[0090] In an exemplary embodiment, metadata such as parameter name, parameter description, parameter type, subframe configuration, parameter symbol identifier, and parameter frequency from the MAP_TO_PARAMETER configuration table is imported into the PARAMETER_DEFINITION table. If the subframe configuration parameter value is used to represent a parameter present in every frame, the configuration value is set to ALL. The parameter type is converted to a number, with the conversion rules being 1 for BNR, 2 for BCD, 3 for DIS, 4 for String and ASCII, and 5 for INT. The symbol configuration value is converted to a numeric type, with N being 0 and Y being 1. The parameter frequency is calculated: if the parameter subframe configuration is 0, the parameter frequency is the maximum value of AGE plus 1; if the subframe configuration value is non-zero, and contains a comma, the parameter frequency is 0.5; if the subframe configuration value is a number greater than 0, the parameter frequency is 0.25.

[0091] Therefore, based on the sign or the parameter represented by the subframe parameter configuration value, the appropriate parameter sampling frequency can be determined more precisely, so as to extract flight data from the fast storage recorder and thus perform efficient decoding.

[0092] In one embodiment, the above-mentioned conversion of the verified sensor configuration parameters into decoded configuration parameters includes: if the sensor parameters configured by the target sensor configuration parameters include a parameter structure and there are multiple parameter structure metadata, then the sensor parameters are configured according to the number of parameter structure metadata through the sensor configuration parameters to obtain decoded configuration parameters; if the sensor parameters configured by the target sensor configuration parameters include multiple parameter structures, then the sensor parameters are configured according to the sensor configuration parameters in each parameter structure to obtain decoded configuration parameters.

[0093] The number of parameter structure metadata and the number of parameter structures are somewhat interchangeable. Sensor parameters can be configured separately through each parameter structure metadata, or sensor parameters can be configured through each parameter structure. Optionally, the target sensor configuration parameters involved in this embodiment are the verified sensor configuration parameters.

[0094] In an exemplary embodiment, the parameter word position, least significant bit, most significant bit, coefficient 0, and coefficient 1 from the MAP_TO_PARAMETER configuration table are written to the WORD_DEFINITION table. If a parameter has only a single part, multiple configuration entries are written according to the number of AGEs; if a parameter consists of multiple parameter structures, sensor configuration parameters for defining sensor parameter words are written sequentially in each parameter structure.

[0095] Based on the amount of metadata in the parameter structure, the sensor parameters are configured separately through the sensor configuration parameters. This allows the solution to convert the data according to different methods compatible with the sensor configuration data, resulting in high compatibility of the decoding configuration parameters.

[0096] In one embodiment, the above-mentioned conversion of the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes: comparing the decoded configuration parameter table with the target sensor configuration parameters according to one or more metadata of parameter identifier, parameter data content type, parameter custom configuration information, storage unit location, and parameter bits in sequence to obtain the newly added decoded configuration parameters in the target sensor configuration parameters; and adding the newly added decoded configuration parameters to the decoded configuration parameter table.

[0097] In an exemplary embodiment, newly imported parameters are obtained from `PARAMETER_DEFINITION` and compared with existing parameters of the same name. If no parameter of the same name exists, it indicates that this parameter is new, and the parameter is marked as `NEW_DATA`. The parameter definitions are compared; if the parameter type has changed, the parameter is marked as new. After comparing the parameter definitions, the custom configurations of the parameters are compared. First, the word positions are compared for consistency; if they are inconsistent, the parameter is marked as having a different word definition, and the status is set to `WORD_DIFFERENT`. Then, the least significant bit, most significant bit, coefficient 0, and coefficient 1 of the parameter are compared; if any of these are inconsistent, the status is marked as `WORD_DIFFERENT`. After comparing all parameters...

[0098]

[0099] Depending on the parameter definition (PARAMETER_DIFFERENT), word definition (WORD_DIFFERENT), and existing data (STOCK_DATA), this step ignores all existing data and writes parameters for other states to the PARAMETER_TO_AIRCRAFT_BY_EO table.

[0100] Therefore, by comparing various metadata sources, the newly added decoding configuration parameters for each metadata dimension are determined. These new parameters are then added to the decoding configuration parameter table for real-time updates, improving update efficiency. It's important to understand that because this process uses metadata comparison, sensor configuration parameters and decoding configuration parameters can be modified synchronously, resulting in high real-time update efficiency.

[0101] Optionally, obtain the configuration files for each aircraft using this batch from the interface, write the EO information for each aircraft and the EO used in this batch into the flight detail task table (EO_TASK_DETAIL table), identify the correspondence between each aircraft and the EO, and mark the relationship. The corresponding relationships are: OPEN - not completed, CLOSE - completed, C / W - partially completed, CANCE - cancelled, APPING - under approval, UNDER - under monitoring.

[0102] In one embodiment, determining matching sensor configuration parameters based on aircraft type and flight time information includes: in a batch of aircraft taking off, the server periodically polls the matching relationship between the target aircraft and the sensor configuration parameters, and determines the target sensor configuration parameters matching the target aircraft based on the matching relationship; the server determines the status parameters indicated by the flight detail task based on the association between the target aircraft and the flight detail task; and the server determines the decoding configuration parameter conversion time based on the status parameters.

[0103] Correspondingly, according to the metadata of the sensor configuration parameters, the sensor configuration parameters are converted into decoded configuration parameters, including: during the decoding configuration parameter conversion time of the target aircraft, the server converts the sensor configuration parameters of the target aircraft into decoded configuration parameters of the target aircraft according to the metadata of the sensor configuration parameters of the target aircraft.

[0104] In one optional implementation, among the aircraft in the takeoff batch, the server periodically polls the matching relationship between the target aircraft and the sensor configuration parameters, including: among each aircraft in the takeoff batch, the server polls the matching relationship between the target aircraft and the sensor configuration parameters according to a preset time interval; or, among each aircraft in the takeoff batch, the server sequentially polls the matching relationship between the target aircraft and the sensor configuration parameters at multiple preset time points.

[0105] In an optional implementation, the server determines the status parameters of the flight detail task indication based on the association between the target aircraft and the flight detail task, including: determining the status parameters of the target aircraft from the flight detail task based on the target aircraft identifier; wherein the status parameters of the target aircraft include: OPEN - not completed, CLOSE - completed, C / W - partially completed, CANCE - cancelled, APPING - under approval, UNDER - under monitoring.

[0106] In one exemplary embodiment, the association between EO_TASK_DETAIL and

[0107] The parameters in PARAMETER_TO_AIRCRAFT_BY_EO are written to

[0108] The AIRCRAFT_PARAMETER_VERSION table contains information about the mapping between aircraft and MAPs. Specifically, the system periodically polls the mapping between aircraft and MAPs in the background. If an aircraft is in a CLOSE state, the system writes all the parameter configuration information for this upgrade (i.e., the parameters in the PARAMETER_TO_AIRCRAFT_BY_EO table) to the AIRCRAFT_PARAMETER_VERSION table and marks the effective date as the CLOSE state date. After this, the aircraft will use all the upgraded and existing parameter configurations to decode QAR data.

[0109] In one embodiment, after configuring the parameters for the flight data decoding process according to the decoding configuration file, the process further includes clearing the decoding configuration file. For example, if the target aircraft associated with this EO has already completed the sensor configuration parameter upgrade, the background process will clear configuration information such as the decoding configuration file associated with this EO and mark this EO upgrade as complete. For example, if all aircraft associated with this EO have completed the upgrade, the background process will clear all configuration information associated with this EO and mark this EO upgrade as complete.

[0110] Step 206: Configure the parameters for the decoding process of the flight data according to the decoding configuration parameters.

[0111] In one embodiment, the decoding process of flight data is parameter-configured according to decoding configuration parameters, including: performing parameter format detection on the aircraft's sensor configuration parameters to determine that the sensor configuration parameters conform to the format conditions for flight data decoding; if the preset positions and intervals of each synchronization word in the sensor configuration parameters that conform to the format conditions conform to the synchronization word conditions of the sensor configuration parameters, then it is determined that the sensor configuration parameters conform to the frame length conditions; obtaining a decoding configuration template according to the storage path of the sensor configuration parameters, and obtaining flight data from the storage location of the sensor data; and performing decoding process processing on the data obtained according to the parameters corresponding to the decoding configuration template.

[0112] In one embodiment, the decoding process of data obtained according to the parameters corresponding to the decoding configuration template includes: dividing the flight data into data intervals of each superframe number according to the superframe number in the decoding configuration template; in the data interval of the superframe number, correcting the subframe number in the decoding configuration template by the superframe number to obtain the corrected subframe number corresponding to the superframe number; and decoding the flight data of the corrected subframe number corresponding to the superframe number in each flight segment.

[0113] The data obtained according to the parameters corresponding to the decoding configuration template can be data recorded via DFDR, QAR, or DAR. This process can follow the ARINC717 standard or other specifications. Optionally, the data is recorded cyclically per superframe or frame, with each frame lasting 4 seconds. Each second of data is a subframe or subframe. The storage space for each subframe can be 64, 128, 256, 512, or 1024 words, with each word having 12 data bits. Specific flight parameter values ​​are filled into the words and data bits. The first word of each second subframe is a synchronization word, which includes, but is not limited to, Teledyne format synchronization words or Hamilton format synchronization words.

[0114] Therefore, at the granularity of the superframe number and subframe number, the subframe number in the decoding configuration template is corrected by the superframe number to obtain the corrected subframe number corresponding to the superframe number. The error repair accuracy rate is over 95%, the flight matching result is over 95%, and the parameter decoding result accuracy is over 99%.

[0115] In one specific embodiment, the parameter sampling frequency is used to collect flight data according to the corresponding parameter sampling frequency of the converted subframe configuration parameter value, and to decode the collected flight data.

[0116] In the aforementioned flight data decoding and configuration method, matching target sensor configuration parameters are determined from the configuration parameters of each sensor based on the aircraft's takeoff batch and flight time information. These target sensor configuration parameters are configuration information stored in the process. The target sensor configuration parameters are converted into decoding configuration parameters according to their metadata. The decoding process of the flight data is then configured according to these decoding configuration parameters. Since the metadata of the target sensor configuration parameters is common to both types of configuration parameters, the decoding configuration parameters for various types of sensor data can be determined through the metadata. This allows the target sensor configuration parameters to be converted into decoding configuration parameters, improving the accuracy of the data decoding process. Furthermore, the decoding configuration can be reused, enhancing the efficiency and accuracy of parameter configuration in the decoding process.

[0117] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0118] Based on the same inventive concept, this application also provides an apparatus for implementing the flight data decoding and configuration method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations of one or more flight data decoding and configuration apparatus embodiments provided below can be found in the limitations of the flight data decoding and configuration method described above, and will not be repeated here.

[0119] In one embodiment, such as Figure 3 As shown, a device for configuring flight data decoding is provided, comprising:

[0120] The configuration parameter matching module 302 is used to determine the target sensor configuration parameters to be matched from the configuration parameters of each sensor, based on the aircraft type and flight time information; the sensor configuration parameters are configuration information stored in the process.

[0121] The parameter conversion module 304 is used to convert the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters;

[0122] The decoding configuration module 306 is used to configure the decoding process of the flight data according to the decoding configuration parameters.

[0123] In one embodiment, the configuration parameter matching module 302 is used to:

[0124] Determine the aircraft's departure batch and the date the aircraft was in flight;

[0125] In the sensor configuration parameters of each fast access recorder, a matching target sensor configuration parameter is found based on the takeoff batch and the date.

[0126] In one embodiment, the parameter conversion module 304 is used for:

[0127] It was determined that all strings contained in the target sensor configuration parameters were parsable characters;

[0128] The completeness of the target sensor configuration parameters is determined according to the preset parameter format;

[0129] If the target sensor configuration parameters are complete, the target sensor configuration parameters are parsed to obtain the metadata of the target sensor configuration parameters.

[0130] In one embodiment, the sensor configuration parameters include configuration parameters for each subframe and data content types for each sensor parameter; the metadata includes parameter structure metadata for the sensor configuration parameters; the parameter conversion module 304 is used for:

[0131] When the data content type belongs to a preset type and the configuration parameters of each subframe are consistent, it is determined that the target sensor configuration parameters pass the verification, and the verified sensor configuration parameters are converted into decoded configuration parameters.

[0132] When the data content type does not belong to the preset type and the configuration parameters of each subframe are consistent, it is determined whether the number of parameter structures of the sensor parameters matches the preset number indicated by the parameter structure metadata. If they match, it is determined that the target sensor configuration parameters have passed the verification, and the verified sensor configuration parameters are converted into decoded configuration parameters.

[0133] In one embodiment, the decoding configuration parameters include the parameter sampling frequency corresponding to the subframe parameter configuration value; the parameter conversion module 304 is used for:

[0134] Based on the metadata, the target sensor configuration parameters are converted into numerical types to obtain the format-converted sensor configuration parameters.

[0135] During the process of converting sensor configuration parameters into the numerical type, the parameter sampling frequency corresponding to the subframe parameter configuration value is determined based on the subframe parameter configuration value of the target sensor configuration parameters.

[0136] In one embodiment, the parameter conversion module 304 is used for:

[0137] If the subframe parameter configuration value represents all subframes, then the parameter sampling frequency corresponding to the subframe parameter configuration value is determined according to the maximum value in the metadata of each parameter structure.

[0138] If the subframe parameter configuration value has a preset symbol, then the preset parameter value corresponding to the preset symbol is determined as the parameter sampling frequency corresponding to the subframe parameter configuration value;

[0139] If the subframe parameter configuration value represents not all subframes and the preset symbol does not exist, then the preset parameter value corresponding to the not all subframes is determined as the parameter sampling frequency corresponding to the subframe parameter configuration value.

[0140] In one embodiment, the parameter conversion module 304 is used for:

[0141] If the sensor parameters configured by the target sensor configuration parameters include a parameter structure and there are multiple parameter structure metadata, then the sensor parameters are configured according to the number of parameter structure metadata through the sensor configuration parameters to obtain the decoded configuration parameters;

[0142] If the target sensor configuration parameters include multiple parameter structures, then in each parameter structure, the sensor parameters are configured using the sensor configuration parameters to obtain the decoding configuration parameters.

[0143] In one embodiment, the parameter conversion module 304 is used for:

[0144] The decoding configuration parameter table is compared with the target sensor configuration parameters in sequence according to one or more metadata of parameter identifier, parameter data content type, parameter custom configuration information, storage unit location, and parameter bit, to obtain the newly added decoding configuration parameters in the target sensor configuration parameters;

[0145] Add the new decoding configuration parameters to the decoding configuration parameter table.

[0146] In one embodiment, the configuration parameter matching module 302 is used to:

[0147] In the batch of aircraft taking off, the server periodically polls the matching relationship between the target aircraft and the sensor configuration parameters, and determines the target sensor configuration parameters that the target aircraft matches based on the matching relationship.

[0148] The server determines the status parameters indicated by the flight detail task based on the association between the target aircraft and the flight detail task;

[0149] The server determines the conversion time of the decoding configuration parameters based on the status parameters;

[0150] Correspondingly, the decoding configuration module 306 is used for:

[0151] During the decoding configuration parameter conversion time of the target aircraft, the server converts the sensor configuration parameters of the target aircraft into the decoding configuration parameters of the target aircraft according to the metadata of the sensor configuration parameters of the target aircraft.

[0152] Each module in the aforementioned flight data decoding configuration device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0153] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores configuration parameters and corresponding data for various sensors. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a flight data decoding and configuration method.

[0154] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0155] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0156] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0157] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0158] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0159] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0160] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0161] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A flight data decoding and configuration method, characterized in that, The method includes: From the configuration parameters of each sensor, the matching target sensor configuration parameters are determined based on the aircraft type and flight time information; the sensor configuration parameters are configuration information stored in the process. Based on the metadata of the target sensor configuration parameters, the target sensor configuration parameters are converted into decoded configuration parameters; The decoding process of the flight data is configured according to the decoding configuration parameters. Specifically, converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes: converting the target sensor configuration parameters into numerical types according to the metadata to obtain the format-converted sensor configuration parameters; during the process of converting the sensor configuration parameters into the numerical types, determining the parameter sampling frequency corresponding to the subframe parameter configuration value based on the subframe parameter configuration value of the target sensor configuration parameters.

2. The method according to claim 1, characterized in that, The step of determining the matching target sensor configuration parameters from the various sensor configuration parameters based on the aircraft type and flight time information includes: Determine the aircraft's departure batch and the date the aircraft was in flight; In the sensor configuration parameters of each fast access recorder, a matching target sensor configuration parameter is found based on the takeoff batch and the date.

3. The method according to claim 1, characterized in that, Before converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters, the process includes: It was determined that all strings contained in the target sensor configuration parameters were parsable characters; The completeness of the target sensor configuration parameters is determined according to the preset parameter format; If the target sensor configuration parameters are complete, the target sensor configuration parameters are parsed to obtain the metadata of the target sensor configuration parameters.

4. The method according to claim 1, characterized in that, The sensor configuration parameters include configuration parameters for each subframe and data content types for each sensor parameter; the metadata includes parameter structure metadata of the sensor configuration parameters; the conversion of the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes: When the data content type belongs to a preset type and the configuration parameters of each subframe are consistent, it is determined that the target sensor configuration parameters pass the verification, and the verified sensor configuration parameters are converted into decoded configuration parameters. When the data content type does not belong to the preset type and the configuration parameters of each subframe are consistent, it is determined whether the number of parameter structures of the sensor parameters matches the preset number indicated by the parameter structure metadata. If they match, it is determined that the target sensor configuration parameters have passed the verification, and the verified sensor configuration parameters are converted into decoded configuration parameters.

5. The method according to claim 1, characterized in that, The step of determining the parameter sampling frequency corresponding to the subframe parameter configuration value based on the subframe parameter configuration value includes: If the subframe parameter configuration value represents all subframes, then the parameter sampling frequency corresponding to the subframe parameter configuration value is determined according to the maximum value in the metadata of each parameter structure. If the subframe parameter configuration value has a preset symbol, then the preset parameter value corresponding to the preset symbol is determined as the parameter sampling frequency corresponding to the subframe parameter configuration value; If the subframe parameter configuration value represents not all subframes and the preset symbol does not exist, then the preset parameter value corresponding to the not all subframes is determined as the parameter sampling frequency corresponding to the subframe parameter configuration value.

6. The method according to claim 1, characterized in that, The step of converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes: If the sensor parameters configured by the target sensor configuration parameters include a parameter structure and there are multiple parameter structure metadata, then the sensor parameters are configured according to the number of parameter structure metadata through the sensor configuration parameters to obtain the decoded configuration parameters; If the target sensor configuration parameters include multiple parameter structures, then in each parameter structure, the sensor parameters are configured using the sensor configuration parameters to obtain the decoding configuration parameters.

7. The method according to claim 1, characterized in that, The step of converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes: The decoding configuration parameter table is compared with the target sensor configuration parameters in sequence according to one or more metadata of parameter identifier, parameter data content type, parameter custom configuration information, storage unit location, and parameter bit, to obtain the newly added decoding configuration parameters in the target sensor configuration parameters; Add the new decoding configuration parameters to the decoding configuration parameter table.

8. The method according to claim 1, characterized in that, The process of determining matching sensor configuration parameters based on aircraft type and flight time information includes: In the batch of aircraft taking off, the server periodically polls the matching relationship between the target aircraft and the sensor configuration parameters, and determines the target sensor configuration parameters that the target aircraft matches based on the matching relationship. The server determines the status parameters indicated by the flight detail task based on the association between the target aircraft and the flight detail task; The server determines the conversion time of the decoding configuration parameters based on the status parameters; The step of converting the sensor configuration parameters into decoded configuration parameters according to the metadata of the sensor configuration parameters includes: During the decoding configuration parameter conversion time of the target aircraft, the server converts the sensor configuration parameters of the target aircraft into the decoding configuration parameters of the target aircraft according to the metadata of the sensor configuration parameters of the target aircraft.

9. A device for configuring flight data decoding, characterized in that, The device includes: The configuration parameter matching module is used to determine the target sensor configuration parameters to match from the configuration parameters of each sensor, based on the aircraft type and flight time information; the sensor configuration parameters are configuration information stored in the process. The parameter conversion module is used to convert the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters; The decoding configuration module is used to configure the decoding process of the flight data according to the decoding configuration parameters. The step of converting the target sensor configuration parameters into decoded configuration parameters according to the metadata of the target sensor configuration parameters includes: converting the target sensor configuration parameters into numerical types according to the metadata to obtain the format-converted sensor configuration parameters; and determining the parameter sampling frequency corresponding to the subframe parameter configuration value based on the subframe parameter configuration value of the target sensor configuration parameters during the conversion of the sensor configuration parameters into the numerical type.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

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