UAV flight anomaly analysis method, system, device and storage medium

Abstract

The present application relates to a method, system, device, and storage medium for analyzing unmanned aerial vehicle (UAV) flight anomaly. The method includes: obtaining a computer hardware code and user information, and performing user login based on the computer hardware code and user information login analysis; constructing identification information for a log file, and recording the UAV's flight data based on the identification information and preset data structure information, and storing the flight data on an SD card; extracting and decoding the flight data from the SD card, and generating anomaly analysis results based on the flight data; converting the flight data and anomaly analysis results into a display graph, and displaying the display graph. The present application can reduce the workload of manual analysis and enable intuitive viewing of anomaly results, which is conducive to improving the efficiency of UAV anomaly analysis.

Description

Technical Field

[0001] The present application relates to the field of drone technology, and in particular to a drone flight anomaly analysis method, system, device, and storage medium. Background Art

[0002] With the country's opening up of low-altitude economic policies, drone light shows are becoming increasingly popular, and the scale of cluster performances is also expanding. From the initial hundreds of drones to the current thousands of clusters, what comes with it is heavy after-sales maintenance and how to more conveniently discover what problems exist with abnormal drones. Therefore, a drone log recording and analysis system is needed to solve this problem.

[0003] Existing drone log analysis is performed manually using the missionplanner_old software, which can only parse bin files to view detailed data. The biggest drawback of existing drone log analysis is that it is difficult to use and requires professional personnel to perform log analysis. Furthermore, only users who use the logs know the specific purpose of the logs, while others do not have access to them. This results in low efficiency in drone anomaly analysis. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to propose a method, system, device and storage medium for analyzing drone flight anomalies to improve the efficiency of drone anomaly analysis.

[0005] In order to solve the above technical problems, the present invention provides a method for analyzing drone flight anomalies, including:

[0006] Obtaining a computer hardware code and user information, and performing user login based on the computer hardware code and the user information login analysis;

[0007] Constructing identification information of a log file, and recording flight data of the drone based on the identification information and preset data structure information, and storing the flight data in an SD card;

[0008] Extracting and decoding the flight data from the SD card, and generating an abnormality analysis result based on the flight data;

[0009] The flight data and the abnormality analysis results are converted into display graphs, and the display graphs are displayed.

[0010] In order to solve the above technical problems, the present invention provides a drone flight anomaly analysis system, comprising:

[0011] A login module, configured to obtain a computer hardware code and user information, and perform user login based on the computer hardware code and the user information login analysis;

[0012] A recording module is used to construct identification information of a log file, record the flight data of the drone based on the identification information and preset data structure information, and store the flight data in an SD card;

[0013] an analysis module, configured to extract and decode the flight data from the SD card, and generate an abnormality analysis result based on the flight data;

[0014] The graphic display module is used to convert the flight data and the abnormality analysis results into display graphs and display the display graphs.

[0015] In order to solve the above technical problems, a technical solution adopted by the present invention is: to provide a computer device, including one or more processors; a memory for storing one or more programs, so that the one or more processors can implement any of the above-mentioned drone flight anomaly analysis methods.

[0016] In order to solve the above technical problems, a technical solution adopted by the present invention is: a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements any one of the above-mentioned drone flight anomaly analysis methods.

[0017] Embodiments of the present invention provide a method, system, device, and storage medium for analyzing unmanned aerial vehicle (UAV) flight anomaly. The method includes: obtaining a computer hardware code and user information, and performing a login analysis based on the computer hardware code and user information to log in the user; constructing identification information for a log file, and recording the UAV's flight data based on the identification information and preset data structure information, and storing the flight data on an SD card; extracting and decoding the flight data from the SD card, and generating an anomaly analysis result based on the flight data; and converting the flight data and the anomaly analysis result into a display image, and displaying the display image. By constructing identification information for a log file and recording the UAV's flight data based on the identification information and preset data structure information, the embodiment of the present invention extracts the recorded flight data for anomaly analysis when anomaly analysis is required, and displays the analysis results. This reduces the workload of manual analysis and allows for intuitive viewing of anomaly results, thereby improving the efficiency of UAV anomaly analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the solutions in this application, a brief introduction will be given below to the drawings required for use in the description of the embodiments of this application. Obviously, the drawings described below are some embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 This is a flowchart of an implementation of the UAV flight anomaly analysis method provided in an embodiment of the present application;

[0020] Figure 2 This is a flowchart for implementing the first sub-process in the drone flight anomaly analysis method provided in an embodiment of the present application;

[0021] Figure 3 This is a flowchart for implementing the second sub-process in the drone flight anomaly analysis method provided in an embodiment of the present application;

[0022] Figure 4 This is a flowchart for implementing the third sub-process in the drone flight anomaly analysis method provided in an embodiment of the present application;

[0023] Figure 5 This is a flowchart for implementing the fourth sub-process in the drone flight anomaly analysis method provided in an embodiment of the present application;

[0024] Figure 6 This is a flowchart for implementing the fifth sub-process in the drone flight anomaly analysis method provided in an embodiment of the present application;

[0025] Figure 7 This is a schematic diagram of a drone flight anomaly analysis system provided by an embodiment of the present application;

[0026] Figure 8 It is a schematic diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this application belongs. The terms used in the specification of the application are for the purpose of describing specific embodiments only and are not intended to limit this application. The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0028] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0029] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0030] The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0031] It should be noted that the drone flight anomaly analysis method provided in the embodiment of the present application is generally executed by a server, and accordingly, the drone flight anomaly analysis system is generally configured in the server.

[0032] See also Figure 1 , Figure 1 A specific implementation of the method for analyzing drone flight anomalies is shown.

[0033] It should be noted that the method of the present invention is not limited to the method of Figure 1 The process sequence shown is limited to the following steps:

[0034] S1: Obtain a computer hardware code and user information, and perform user login based on the computer hardware code and the user information login analysis.

[0035] Specifically, the embodiment of the present application provides a user login interface for logging in and facilitating the user to view the abnormality analysis results of the drone. In the embodiment of the present application, it is necessary to obtain the computer hardware code and user information, and perform a login verification based on the computer hardware code and user information. If the login verification passes, the user is logged in.

[0036] The computer hardware code is a string of numbers and letters used to uniquely identify computer hardware, which usually contains identification information of key hardware devices in the computer. In the embodiment of the present application, the computer hardware code is used to limit the number of times a user can use it on different computers.

[0037] See also Figure 2 , Figure 2 A specific implementation of step S1 is shown, which is described in detail as follows:

[0038] S11: Obtain a user login interface configuration file, and load a user login interface based on the user login interface configuration file.

[0039] S12: Obtain the computer hardware code, and obtain the user information through a user login interface.

[0040] S13: Determine whether the computer hardware code exceeds a preset activation coefficient based on the computer hardware code; if not, perform a login check based on the user information.

[0041] S14: If the login verification is successful, the user information is saved and the user is logged in.

[0042] Specifically, a user login interface configuration file is obtained and a user login interface is loaded based on the configuration file. A computer hardware code is then obtained and user information is obtained through the user login interface. Based on the computer hardware code, a determination is made as to whether a preset activation coefficient has been exceeded. If so, an alarm is generated and user login is restricted. If not, a login verification is performed based on the user information. If the login verification fails, an error message is generated and reported based on the error message. If the login verification passes, the user information is saved and the user is logged in.

[0043] Furthermore, after the user logs in, the user name, password and expiration date are written locally using AES encryption for the next offline login, user memory and automatic login.

[0044] Furthermore, after step S1, the present application also provides a specific embodiment: if an update instruction from the user is received, the target version information is obtained, and the update is performed based on the target version information.

[0045] Specifically, the embodiment of the present application provides software corresponding to an analysis system. After a user logs in to the software, the user can choose whether to update the anomaly analysis tool. If an update instruction is received from the user, the target version information is obtained and updated based on the target version information.

[0046] In a specific embodiment, the code of the target version information is pushed to the CI (Continuous Integration) branch. After the CI branch is triggered, the server Jenkins receives the code of the target version information, switches the virtual environment to execute the shell script, pulls the code of the target version information, and executes the compilation command. After the compilation is completed, it is compressed and packaged, and the compressed package is sent to the server, thereby realizing the update of the exception analysis tool.

[0047] S2: Construct identification information of a log file, and record the flight data of the drone based on the identification information and preset data structure information, and store the flight data in an SD card.

[0048] Specifically, in the embodiment of this application, it is necessary to construct the identification information of the log file and define the structure of the recorded data. The user needs to define the structure according to actual needs. The corresponding log file is determined by the corresponding data structure identifier, and the flight data of the drone is recorded in the target log file and stored in the SD card.

[0049] Flight data refers to data stored during the drone's flight control process. An SD card, or Secure Digital Card, is a new-generation memory device based on semiconductor flash memory. The preset data structure information includes a preset data structure and a structure identifier.

[0050] See also Figure 3 , Figure 3 A specific implementation of step S2 is shown, which is described in detail as follows:

[0051] S21: Obtain the current time, the MCU time and the number of the UAV.

[0052] S22: Convert the current time, the single-chip computer time, and the serial number into characters to generate identification information of the log file.

[0053] S23: Obtain the preset data structure and the structure identifier.

[0054] S24: Record the identification header of each piece of data to be received, and record the flight data of the UAV based on the identification header, the structure identifier, and the identification information.

[0055] S25: Storing the flight data in the SD card.

[0056] Specifically, the current drone time, MCU time, and drone number are obtained. These are then combined and converted to characters to generate a string. This string is used as the log file identifier. A preset data structure and structure identifier are then obtained. These data structures and structure identifiers are user-configurable. Before data recording, the identifier header for each data item is recorded, and the currently recorded data is treated as the new data item. Data recording is implemented using a bidirectional linked list. One side records the MsgHead (message header), which links the data structure and structure identifier. The header identifies the main log category and its sub-category names for the exported log file, as well as the data type of the sub-category record. The other side receives data from multiple tasks through a unified interface, identifies the corresponding data based on the structure, and first records the data in a message queue. The data is then matched to the corresponding log file, and the flight data is stored in the log file. Finally, the flight data is stored on an SD card.

[0057] See also Figure 4 , Figure 4 A specific implementation of step S24 is shown, which is described in detail as follows:

[0058] S241: Record the identification header of each piece of data to be received.

[0059] S242: Enumerate the structure identifier based on the identification header to bind the structure identifier to the data to be received to obtain binding information.

[0060] S243: Match the structure with the identification information to identify the target log file.

[0061] S244: Record the flight data of the UAV for each task through a unified interface based on the target log file and binding information.

[0062] Specifically, before recording data, an identification header of each piece of data to be received is recorded. The identification header can be 0XA3 or 0X95. The identification header is used to represent the currently recorded data as new data. Then, a structure identifier is enumerated based on the identification header to bind the structure identifier to the data to be received, thereby obtaining binding information. Using this binding information, the structure identifier is bound to the data structure to be recorded.

[0063] Because enumerations are unique, structure identifiers are also unique. Given a parameter that can be modified, each binary bit of this parameter corresponds to each structure identifier. That is, to record data with a structure identifier of 1, simply set the first bit of the parameter to 1, and if this data is not needed, set it to 0. This parameter is ANDed with the structure tag. If true, the data is recorded (i.e., A&B = 1), and if false, it is skipped (i.e., A&B = 0), thereby identifying the data to be recorded. Therefore, the target log file is identified by matching the structure with the identifier information. This target log file is used to record the flight data corresponding to the structure. Finally, each task records the drone's flight data based on the target log file and binding information through a unified interface.

[0064] See also Figure 5 , Figure 5 A specific implementation of step S244 is shown, which is described in detail as follows:

[0065] S2441: Receive data corresponding to each task through the unified interface to obtain initial data.

[0066] S2442: Obtain target record data from the initial data according to the structure identifier in the binding information.

[0067] S2443: Storing the target record data in a message queue according to a preset time interval.

[0068] S2444: Write the target record data in the message queue into the target log file byte by byte to record the flight data of the UAV.

[0069] Specifically, the data corresponding to each task is received through a unified interface to obtain the initial data. The target record data is then retrieved from the initial data based on the structure identifier in the binding information. The target record data is then stored in a message queue at preset intervals and written byte by byte to the target log file to record the drone's flight data.

[0070] S3: Extracting and decoding the flight data from the SD card, and generating an abnormality analysis result based on the flight data.

[0071] Specifically, the above steps record different flight data in different log files. Therefore, when a flight control error occurs and anomaly analysis is required, the corresponding flight data is extracted and decoded from the SD card, and anomaly analysis results are generated based on the flight data. The anomaly analysis method uses existing flight control anomaly analysis methods.

[0072] See also Figure 6 , Figure 6 A specific implementation of step S3 is shown, which is described in detail as follows:

[0073] S31: If a data abnormality analysis instruction is received, the flight data is extracted from the SD card.

[0074] S32: Read the flight data in single byte format and decode the flight data in accordance with a preset data format.

[0075] S33: Generate the abnormality analysis result based on the flight data.

[0076] Specifically, when a drone sends an error, it generates a data anomaly analysis command. Upon receiving the command, the server extracts the flight data from the SD card, reads the flight data byte by byte, decodes it according to a preset data format, and generates an anomaly analysis result based on the flight data.

[0077] S4: Convert the flight data and the abnormality analysis result into a display graph, and display the display graph.

[0078] Specifically, the remote control stick values in the flight data are converted into display graphs of Roll, Pitch, Yaw, and throttle. The start time of the EKF (Extended Kalman Filter) is marked with a red dotted vertical axis in the display graph. When an EKF occurs in the drone, the pilot will use the remote control to rescue the aircraft. If the rescue fails or other uncontrollable factors cause other problems, the pilot's stick operation can be intuitively seen in the form of a graph, and it can also be seen whether the drone has responded according to the operation; in this way, it can be determined whether it is a pilot's mistake or a problem with the drone itself. At the same time, the embodiment of the present application can also convert the abnormal analysis results into a display graph and display the display graph.

[0079] In an embodiment of the present application, a computer hardware code and user information are obtained, and user login is performed based on the computer hardware code and the user information login analysis; identification information of a log file is constructed, and based on the identification information and preset data structure information, the flight data of the drone is recorded, and the flight data is stored in an SD card; the flight data is extracted and decoded from the SD card, and an abnormality analysis result is generated based on the flight data; the flight data and the abnormality analysis result are converted into a display graph, and the display graph is displayed. By constructing the identification information of a log file and recording the flight data of the drone based on the identification information and the preset data structure information, the embodiment of the present invention extracts the recorded flight data for abnormality analysis when abnormality analysis is required, and displays the analysis results. This can reduce the workload of manual analysis, and can intuitively view abnormality results, which is conducive to improving the efficiency of drone abnormality analysis.

[0080] Please refer to Figure 7 , as a response to the above Figure 1 The present application provides an embodiment of a UAV flight anomaly analysis system, which is similar to the embodiment of the present invention. Figure 1 Corresponding to the method embodiment shown, the system can be specifically applied to various electronic devices.

[0081] like Figure 7 As shown, the drone flight anomaly analysis system of this embodiment includes: a login module 51, a recording module 52, an analysis module 53 and a graphic display module 54, wherein:

[0082] Login module 51, used to obtain computer hardware code and user information, and perform user login based on the computer hardware code and user information login analysis;

[0083] The recording module 52 is used to construct identification information of the log file, record the flight data of the drone based on the identification information and preset data structure information, and store the flight data in the SD card;

[0084] an analysis module 53, configured to extract and decode the flight data from the SD card, and generate an abnormality analysis result based on the flight data;

[0085] The graphic display module 54 is used to convert the flight data and the abnormality analysis results into display graphs and display the display graphs.

[0086] Furthermore, the preset data structure information includes a preset data structure and a structure identifier, and the recording module 52 includes:

[0087] A time acquisition unit, used to obtain the current time, the MCU time and the number of the drone;

[0088] An identification information generating unit, configured to convert the current time, the single chip computer time and the serial number into characters to generate identification information of the log file;

[0089] A structure acquisition unit, configured to acquire the preset data structure and the structure identifier;

[0090] a flight data recording unit, configured to record an identification header of each piece of data to be received, and record the flight data of the UAV based on the identification header, the structure identifier, and the identification information;

[0091] The flight data storage unit is used to store the flight data in the SD card.

[0092] Furthermore, the flight data recording unit includes:

[0093] an identification header recording unit, configured to record the identification header of each piece of the to-be-received data;

[0094] a binding unit, configured to enumerate the structure identifier based on the identification header, so as to bind the structure identifier to the data to be received, and obtain binding information;

[0095] a log file identification unit, configured to identify a target log file by matching the structure with the identification information;

[0096] The data acquisition unit is used to record the flight data of the UAV for each task through a unified interface based on the target log file and binding information.

[0097] Furthermore, the data acquisition unit includes:

[0098] an initial data receiving unit, configured to receive data corresponding to each of the tasks through the unified interface to obtain initial data;

[0099] a target record data acquisition unit, configured to acquire target record data from the initial data according to the structure identifier in the binding information;

[0100] A data storage unit, configured to store the target record data in a message queue at a preset time interval;

[0101] A data writing unit is used to write the target record data in the message queue into the target log file byte by byte to record the flight data of the UAV.

[0102] Furthermore, the login module 51 includes:

[0103] A user login interface loading unit, configured to obtain a user login interface configuration file and load the user login interface based on the user login interface configuration file;

[0104] A user information acquisition unit, configured to acquire the computer hardware code and acquire the user information through a user login interface;

[0105] a login verification unit, configured to determine whether a preset activation coefficient is exceeded based on the computer hardware code, and if not, perform login verification based on the user information;

[0106] The user login unit is used to save the user information and perform user login if the login verification is successful.

[0107] Furthermore, the login module 51 further includes:

[0108] The update module is configured to obtain target version information upon receiving an update instruction from the user, and perform an update based on the target version information.

[0109] Furthermore, the analysis module 53 includes:

[0110] A flight data extraction unit, configured to extract the flight data from the SD card upon receiving a data anomaly analysis instruction;

[0111] a flight data decoding unit, configured to read the flight data in single-byte format and decode the flight data in accordance with a preset data format;

[0112] An abnormality analysis result generating unit is used to generate the abnormality analysis result based on the flight data.

[0113] In an embodiment of the present application, a computer hardware code and user information are obtained, and user login is performed based on the computer hardware code and the user information login analysis; identification information of a log file is constructed, and based on the identification information and preset data structure information, the flight data of the drone is recorded, and the flight data is stored in an SD card; the flight data is extracted and decoded from the SD card, and an abnormality analysis result is generated based on the flight data; the flight data and the abnormality analysis result are converted into a display graph, and the display graph is displayed. By constructing the identification information of a log file and recording the flight data of the drone based on the identification information and the preset data structure information, the embodiment of the present invention extracts the recorded flight data for abnormality analysis when abnormality analysis is required, and displays the analysis results. This can reduce the workload of manual analysis, and can intuitively view abnormality results, which is conducive to improving the efficiency of drone abnormality analysis.

[0114] To solve the above technical problems, the present application also provides a computer device. Figure 8 , Figure 8 This is a basic structural block diagram of the computer device in this embodiment.

[0115] The computer device 7 includes a memory 71, a processor 72, and a network interface 73 that are interconnected through a system bus. It should be noted that Figure 8 Only a computer device 7 having three components, memory 71, processor 72, and network interface 73, is shown. However, it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead. It should be understood by those skilled in the art that a computer device herein is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc.

[0116] Computer devices can be desktop computers, laptops, PDAs, cloud servers, etc. Computer devices can interact with users through keyboards, mice, remote controls, touchpads, or voice-activated devices.

[0117] Memory 71 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, magnetic disk, optical disk, etc. In some embodiments, memory 71 may be an internal storage unit of computer device 7, such as the hard disk or memory of computer device 7. In other embodiments, memory 71 may also be an external storage device of computer device 7, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash memory card, etc. Of course, memory 71 may also include both internal storage units and external storage devices of computer device 7. In this embodiment, memory 71 is typically used to store the operating system and various application software installed on computer device 7, such as the program code of the drone flight anomaly analysis method. In addition, memory 71 may also be used to temporarily store various types of data that have been output or are about to be output.

[0118] In some embodiments, processor 72 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. Processor 72 is typically used to control the overall operation of computer device 7. In this embodiment, processor 72 is used to execute program code stored in memory 71 or process data, such as executing the program code of the aforementioned drone flight anomaly analysis method to implement various embodiments of the drone flight anomaly analysis method.

[0119] The network interface 73 may include a wireless network interface or a wired network interface. The network interface 73 is generally used to establish a communication connection between the computer device 7 and other electronic devices.

[0120] The present application also provides another embodiment, namely, providing a computer-readable storage medium, which stores a computer program, and the computer program can be executed by at least one processor to enable the at least one processor to perform the steps of the above-mentioned drone flight anomaly analysis method.

[0121] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of each embodiment of the present application.

[0122] Obviously, the embodiments described above are only some of the embodiments of the present application, rather than all of the embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned specific embodiments, or to make equivalent replacements for some of the technical features therein. Any equivalent structure made using the contents of the present application specification and the accompanying drawings, directly or indirectly used in other related technical fields, is also within the scope of patent protection of the present application.

Claims

1. A method for analyzing unmanned aerial vehicle flight anomalies, characterized in that: include: Obtaining a computer hardware code and user information, and performing user login based on the computer hardware code and the user information login analysis; Constructing identification information of a log file, and recording flight data of the drone based on the identification information and preset data structure information, and storing the flight data in an SD card; Extracting and decoding the flight data from the SD card, and generating an abnormality analysis result based on the flight data; Converting the flight data and the abnormality analysis results into a display graph, and displaying the display graph; The preset data structure information includes a preset data structure and a structure identifier, the identification information of the log file is constructed, and the flight data of the drone is recorded based on the identification information and the preset data structure information, and the flight data is stored in the SD card, including: Get the current time, MCU time and the number of the drone; Convert the current time, the single chip computer time and the serial number into characters to generate identification information of the log file; Obtaining the preset data structure and the structure identifier; Recording the identification header of each piece of data to be received, and recording the flight data of the UAV based on the identification header, the structure identifier, and the identification information; The flight data is stored in the SD card.

2. The method for analyzing unmanned aerial vehicle flight anomaly according to claim 1, characterized in that: The recording of the identification header of each piece of data to be received, and recording the flight data of the UAV based on the identification header, the structure identifier, and the identification information, includes: Recording the identification header of each piece of the data to be received; Enumerating the structure identifier based on the identification header to bind the structure identifier to the data to be received to obtain binding information; Matching the structure with the identification information to identify the target log file; Each task records the flight data of the UAV through a unified interface based on the target log file and binding information.

3. The method for analyzing unmanned aerial vehicle flight anomaly according to claim 2, wherein: The step of recording the flight data of the UAV based on the target log file and the binding information for each task through a unified interface includes: Receive data corresponding to each task through the unified interface to obtain initial data; Obtaining target record data from the initial data according to the structure identifier in the binding information; Storing the target record data in a message queue according to a preset time interval; The target record data in the message queue is written byte by byte into the target log file to record the flight data of the UAV.

4. The method for analyzing unmanned aerial vehicle flight anomaly according to claim 1, wherein: The obtaining of the computer hardware code and user information, and performing user login based on the computer hardware code and the user information login analysis, includes: Obtaining a user login interface configuration file, and loading a user login interface based on the user login interface configuration file; Obtaining the computer hardware code and obtaining the user information through a user login interface; Determining whether a preset activation coefficient is exceeded based on the computer hardware code, and if not, performing a login check based on the user information; If the login verification is successful, the user information is saved and the user is logged in.

5. The method for analyzing unmanned aerial vehicle flight anomaly according to claim 1, wherein: After obtaining the computer hardware code and user information and performing user login based on the computer hardware code and the user information login analysis, the method further includes: If an update instruction from the user is received, the target version information is obtained and the update is performed based on the target version information.

6. The method for analyzing unmanned aerial vehicle flight anomaly according to any one of claims 1 to 5, characterized in that: The extracting and decoding the flight data from the SD card, and generating an abnormality analysis result based on the flight data, includes: If a data abnormality analysis instruction is received, extract the flight data from the SD card; Reading the flight data in single byte format and decoding the flight data in accordance with a preset data format; The abnormality analysis result is generated based on the flight data.

7. A UAV flight anomaly analysis system, characterized in that: include: A login module, configured to obtain a computer hardware code and user information, and perform user login based on the computer hardware code and the user information login analysis; A recording module is used to construct identification information of a log file, record the flight data of the drone based on the identification information and preset data structure information, and store the flight data in an SD card; an analysis module, configured to extract and decode the flight data from the SD card, and generate an abnormality analysis result based on the flight data; A graphic display module, configured to convert the flight data and the abnormality analysis results into a display graph, and present the display graph; The preset data structure information includes a preset data structure and a structure identifier, and the recording module includes: A time acquisition unit, used to obtain the current time, the MCU time and the number of the drone; An identification information generating unit, configured to convert the current time, the single chip computer time and the serial number into characters to generate identification information of the log file; A structure acquisition unit, configured to acquire the preset data structure and the structure identifier; a flight data recording unit, configured to record an identification header of each piece of data to be received, and record the flight data of the UAV based on the identification header, the structure identifier, and the identification information; The flight data storage unit is used to store the flight data in the SD card.

8. A computer device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the method for analyzing the flight anomaly of a UAV according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for analyzing unmanned aerial vehicle flight anomalies according to any one of claims 1 to 6.

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