Unmanned aerial vehicle flight anomaly analysis method, system and device and storage medium

Abstract

The invention relates to an unmanned aerial vehicle flight anomaly analysis method, system and device and a storage medium, and the method comprises the steps: obtaining a computer hardware code and user information, and carrying out the login analysis of a user based on the computer hardware code and the user information; constructing identification information of the log file, recording flight data of the unmanned aerial vehicle based on the identification information and preset data structure body information, and storing the flight data in 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. According to the method, the workload of manual analysis can be reduced, the abnormal result can be visually checked, and the unmanned aerial vehicle abnormal analysis efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of UAV technology, and in particular to a method, system, device and storage medium for analyzing UAV flight anomalies. Background Art

[0002] With the country's opening up of low-altitude economic policies, drone light shows are becoming more and more popular, and the scale of cluster performances is also expanding, from the initial hundreds of drones to today's thousands of clusters. Along with this comes the 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] The existing drone log analysis is done manually, and the missionplanner_old software is required, which can only parse the bin file to view detailed data. The biggest pain point of the existing drone log analysis is that it is difficult to get started, and professional personnel are required to perform log analysis. In addition, only the user who uses the log knows the specific function of the log, and other users cannot obtain it, which leads to low efficiency of drone abnormality 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 unmanned aerial vehicle flight anomalies, so as to improve the efficiency of unmanned aerial vehicle anomaly analysis.

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

[0006] Acquire a computer hardware code and user information, and perform 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 application provides a drone flight anomaly analysis system, including:

[0011] A login module, used 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, used to 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;

[0013] An analysis module, used 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 one or more processors can implement any one 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, any one of the above-mentioned drone flight anomaly analysis methods is implemented.

[0017] The embodiment of the present invention provides a method, system, device and storage medium for analyzing the abnormality of unmanned aerial vehicle flight. The method includes: 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 the identification information of the log file, and recording the flight data of the unmanned aerial vehicle based on the identification information and the 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 result into a display diagram, and displaying the display diagram. The embodiment of the present invention constructs the identification information of the log file, and records the flight data of the unmanned aerial vehicle based on the identification information and the preset data structure information. When abnormality analysis is required, the recorded flight data is extracted for abnormality analysis, and the analysis results are displayed, which can reduce the workload of manual analysis, and can intuitively view the abnormal results, which is conducive to improving the efficiency of abnormality analysis of unmanned aerial vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0020] Figure 2 It 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 It 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 It 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 It 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 It is a flowchart for implementing the fifth sub-process in the method for analyzing the abnormal flight of a drone provided in an embodiment of the present application;

[0025] Figure 7 is a schematic diagram of a drone flight anomaly analysis system provided in 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 meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0028] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood 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 is 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 unmanned aerial vehicle flight anomalies is shown.

[0033] It should be noted that if there are substantially the same results, the method of the present invention is not limited to 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 the user, so that the user can view the abnormal 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. When the login verification passes, the user is logged in.

[0036] The computer hardware code is a combination 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 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: Acquire the computer hardware code, and acquire the user information through a user login interface.

[0040] S13: Determine whether the preset activation coefficient is exceeded based on the computer hardware code, and 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 user login interface configuration file; then a computer hardware code is obtained, and user information is obtained through the user login interface. Based on the computer hardware code, it is determined whether the preset activation coefficient is exceeded. If so, an alarm message 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 an error is 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, and after a user logs into the software, the user can choose whether to update the abnormality analysis tool. 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.

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

[0049] Among them, flight data refers to the data of the drone during flight control. SD card, full name Secure Digital Card, is a new generation of 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 drone 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 time of the drone, the single-chip time and the number of the drone are obtained, and the current time, the single-chip time and the number of the drone are combined and converted into characters to generate a string, and the string is used as the identification information of the log file. Then the preset data structure and structure identifier are obtained, and the data structure and structure identifier are set by the user according to actual needs. Before recording the data, it is necessary to record the identification header of each data, and use the currently recorded data as the new data. When recording the data, a two-way linked list is used to implement it. On one side, the MsgHead (message header) is recorded, and the message header connects the data structure and the structure identifier, and identifies the name of the major log and its subclass log of the log file after export, and identifies the data type of the subclass log record. On the other side, the data of multiple tasks is received through a unified interface, and the corresponding data is identified according to the structure, and the data is first recorded in the message queue, and then the corresponding log file is matched, and the flight data is stored in the log file. Finally, the flight data is stored in the 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 the data to be received.

[0059] S242: Enumerate the structure identifier based on the identifier 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, record the identification header of each piece of data to be received, which can be 0XA3 and 0X95, and represent the current recorded data as new data through the identification header. Then, based on the identification header, enumerate the structure identification by enumeration to bind the structure identification with the data to be received to obtain binding information. Through the binding information, the structure identification is bound to the data structure to be recorded.

[0063] Because enumeration is unique, the structure identifier is also unique. As long as a parameter that can be considered to be changed is given, each binary bit of this parameter corresponds to each structure identifier, that is, to record the data with the structure identifier of 1, you only need to set the first position of the parameter to 1, and do not need to set this data to 0; this parameter and the structure label are operated, and the data is recorded if it is true (that is, A&B=1), and skipped if it is false (that is, A&B=0), so as to identify the data that needs to be recorded. Therefore, the target log file is identified by matching the structure with the identification information. The target log file is used to record the flight data corresponding to the structure. Finally, each task records the flight data of the drone 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 of the tasks 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 at 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; then the target record data is obtained from the initial data according to the structure identifier in the binding information. Then the target record data is stored in the message queue at a preset time interval, and the target record data in the message queue is written into the target log file byte by byte to record the flight data of the drone.

[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 have recorded different flight data according to different log files, so when a flight control error occurs and an abnormality analysis is required, the corresponding flight data is extracted and decoded from the SD card, and an abnormality analysis result is generated based on the flight data. Among them, the abnormality analysis method adopts the existing flight control abnormality analysis method for analysis.

[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, extract the flight data from the SD card.

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

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

[0076] Specifically, when the drone sends an error, a data anomaly analysis instruction is generated. When the server receives the data anomaly analysis instruction, it extracts the flight data from the SD card, reads the flight data in single bytes, decodes the flight data in 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 quantity in the flight data is converted into a display diagram of Roll, Pitch, Yaw and throttle. The start time of the EKF (Extended Kalman Filter) will be marked with a red dotted vertical axis in the display diagram. When an EKF occurs in the drone, the pilot will use the remote control to save the aircraft. If the rescue fails or other uncontrollable factors cause other problems, the pilot's stick operation can be seen intuitively through the graph, and it can also be seen whether the drone has completed the response according to the operation; in this way, it can be determined whether it is a pilot's misoperation 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 diagram and display the display diagram.

[0079] In the embodiment of the present application, the computer hardware code and user information are obtained, and the user login is performed based on the computer hardware code and the user information login analysis; 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; the flight data is extracted and decoded from the SD card, and an abnormal analysis result is generated based on the flight data; the flight data and the abnormal analysis result are converted into a display diagram, and the display diagram is displayed. The embodiment of the present invention constructs the identification information of the log file, and records the flight data of the drone based on the identification information and the preset data structure information. When abnormal analysis is required, the recorded flight data is extracted for abnormal analysis, and the analysis results are displayed, which can reduce the workload of manual analysis, and can intuitively view the abnormal results, which is conducive to improving the efficiency of abnormal analysis of drones.

[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 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] A login module 51, used 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;

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

[0084] An analysis module 53, used 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 acquire the current time, the single chip computer time and the number of the drone;

[0088] An identification information generating unit, used for converting 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, used 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 drone based on the identification header, the structure identification 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 comprises:

[0093] An identification header recording unit, used for recording the identification header of each piece of the data to be received;

[0094] A binding unit, configured to enumerate the structure identifier based on the identifier header to bind the structure identifier to the data to be received to obtain binding information;

[0095] A log file identification unit, used 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, used for receiving 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 a structure identifier in the binding information;

[0100] A data storage unit, used to store the target record data in a message queue according to 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, used 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, used 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 the preset activation coefficient is exceeded based on the computer hardware code, and if not, to perform a 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 used to obtain target version information if an update instruction from the user is received, and to 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 abnormality analysis instruction;

[0111] A flight data decoding unit, used for reading the flight data in single byte and decoding the flight data in a preset data format;

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

[0113] In the embodiment of the present application, the computer hardware code and user information are obtained, and the user login is performed based on the computer hardware code and the user information login analysis; 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; the flight data is extracted and decoded from the SD card, and an abnormal analysis result is generated based on the flight data; the flight data and the abnormal analysis result are converted into a display diagram, and the display diagram is displayed. The embodiment of the present invention constructs the identification information of the log file, and records the flight data of the drone based on the identification information and the preset data structure information. When abnormal analysis is required, the recorded flight data is extracted for abnormal analysis, and the analysis results are displayed, which can reduce the workload of manual analysis, and can intuitively view the abnormal results, which is conducive to improving the efficiency of abnormal analysis of drones.

[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 which are interconnected and communicated with each other 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, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead. Among them, those skilled in the art can understand that the computer device here 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 microprocessors, application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), digital signal processors (DSP), embedded devices, etc.

[0116] Computer devices can be computing devices such as desktop computers, notebooks, PDAs, and cloud servers. Computer devices can interact with users through keyboards, mice, remote controls, touch pads, or voice control devices.

[0117] The memory 71 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), 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 memory, disk, optical disk, etc. In some embodiments, the memory 71 can be an internal storage unit of the computer device 7, such as a hard disk or memory of the computer device 7. In other embodiments, the memory 71 can also be an external storage device of the computer device 7, such as a plug-in hard disk equipped on the computer device 7, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Of course, the memory 71 can also include both the internal storage unit of the computer device 7 and its external storage device. In this embodiment, the memory 71 is generally used to store the operating system and various application software installed on the computer device 7, such as the program code of the drone flight anomaly analysis method, etc. In addition, the memory 71 can also be used to temporarily store various types of data that have been output or are to be output.

[0118] The processor 72 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 72 is generally used to control the overall operation of the computer device 7. In this embodiment, the processor 72 is used to run the program code stored in the memory 71 or process data, such as running the program code of the above-mentioned 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, and 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 a drone flight anomaly analysis method as described above.

[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 a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an 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, a disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods of each embodiment of the present application.

[0122] Obviously, the embodiments described above are only some embodiments of the present application, rather than all 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 is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to replace some of the technical features therein with equivalents. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A method for analyzing unmanned aerial vehicle flight anomalies, characterized in that: include: Acquire a computer hardware code and user information, and perform 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; The flight data and the abnormality analysis results are converted into display graphs, and the display graphs are displayed.

2. The method for analyzing unmanned aerial vehicle flight anomaly according to claim 1, characterized in that: 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 drone based on the identification header, the structure identifier and the identification information; The flight data is stored in the SD card.

3. The method for analyzing unmanned aerial vehicle flight anomaly according to claim 2, characterized in that: The recording of the identification header of each piece of data to be received, and recording the flight data of the drone based on the identification header, the structure identification and the identification information, includes: Recording the identification header of each piece of the data to be received; Based on the identification header, the structure identification is enumerated to bind the structure identification with 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.

4. The method for analyzing unmanned aerial vehicle flight anomaly according to claim 3, characterized in that: The step of recording the flight data of the UAV through a unified interface based on the target log file and the binding information for each task includes: Receive data corresponding to each of the tasks through the unified interface to obtain initial data; Acquire 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 at 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.

5. The method for analyzing unmanned aerial vehicle flight anomaly according to claim 1, characterized in that: The obtaining of the computer hardware code and the 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 the 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.

6. The method for analyzing unmanned aerial vehicle flight anomaly according to claim 1, characterized in that: 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.

7. The method for analyzing unmanned aerial vehicle flight anomaly according to any one of claims 1 to 6, 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 a preset data format; The abnormality analysis result is generated based on the flight data.

8. A UAV flight anomaly analysis system, characterized in that: include: A login module, used 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, used to 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; An analysis module, used to extract and decode the flight data from the SD card, and generate an abnormality analysis result based on the flight data; The graphic display module is used to convert the flight data and the abnormality analysis results into display graphs and display the display graphs.

9. A computer device, characterized in that: It includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method for analyzing unmanned aerial vehicle flight anomaly according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for analyzing unmanned aerial vehicle flight anomalies according to any one of claims 1 to 7 is implemented.

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