Telemetering general analysis real-time compiling method and system and computer readable storage medium

Abstract

The invention provides a telemetering general analysis real-time compiling method and system and a computer readable storage medium, if a real-time telemetering parameter is a native parameter, the real-time telemetering parameter is extracted according to an extraction algorithm, and if the real-time telemetering parameter is a derivative parameter, the real-time telemetering parameter is extracted according to an extraction algorithm. If yes, a preset compiler is called to compile the dynamic compilation source code of the derivative parameter in real time to obtain target telemetry data corresponding to the derivative parameter, and in this way, the dynamic compilation source code capable of solving the derivative parameter directly runs in a memory, so that real-time code compilation of the derivative parameter can be carried out, and the accuracy of the result is improved. A real-time extraction algorithm of derivative parameters is dynamically expanded, so that the applicability and expansibility of real-time parameter analysis are improved, the remote measurement analysis development threshold is reduced, the development period is shortened, the analysis logic takes effect immediately after being modified, the system does not need to be deployed again, and the requirement for rapid adjustment of analysis rules in remote measurement data processing is met.

Description

Technical Field

[0001] The present invention relates to the field of telemetry communication technology, and more particularly to a method for extracting telemetry data in aerospace, and more particularly to a method, system, and computer-readable storage medium for universal telemetry parsing and real-time compilation. Background Art

[0002] In the field of telemetry data analysis, traditional development methods often require developers to write a large amount of code to implement data analysis logic. This not only requires developers to have advanced programming skills and a deep understanding of telemetry protocols, but also has a long development cycle and is difficult to quickly respond to changing requirements. When faced with different types of telemetry data or parameter adjustments, it's necessary to re-investigate specific telemetry protocols, modify code, compile, and deploy, resulting in low efficiency. While some low-code platforms can simplify the development process, they often lack deep integration with the C language and real-time compilation capabilities in telemetry parsing scenarios. They can't dynamically compile code down to the instruction set, and can't meet the demand for immediate effect after dynamic adjustments to parsing logic.

[0003] Therefore, there is an urgent need for a real-time compilation solution for telemetry general parsing that lowers the threshold for telemetry parsing development, allows non-professional developers to quickly configure parameters and specific parsing algorithms, shortens the development cycle, and enables immediate effect of parsing logic modifications without redeploying the system, thus meeting the need for rapid adjustment of parsing rules in telemetry data processing. Summary of the Invention

[0004] In view of the above problems, the purpose of the present invention is to provide a real-time compilation method, system and computer-readable storage medium for universal telemetry analysis, so as to solve the technical problem in the prior art that each time there are new derivative parameters, the code needs to be modified according to the parameter calculation method, and the running program needs to be recompiled and generated, resulting in a long development cycle and low deployment efficiency.

[0005] The present invention provides a telemetry universal parsing and real-time compilation method, which includes: The telemetry data parameter parsing logic is configured through a preset visual low-code parameter configuration model; wherein the telemetry data parameter parsing logic includes: dividing the telemetry parameter types of the telemetry data into native parameters and derived parameters, storing the extraction algorithm of the native parameters, storing the dependent native parameters corresponding to the derived parameters, and dynamically compiling source code that can solve the derived parameters based on the dependent native parameters; receiving real-time telemetry data, and determining whether a real-time telemetry parameter is the native parameter or the derived parameter; the real-time telemetry parameter is a telemetry parameter obtained by performing real-time data extraction on the real-time telemetry data; wherein, If the real-time telemetry parameter is the native parameter, extracting the real-time telemetry parameter according to the extraction algorithm; If the real-time telemetry parameter is the derived parameter, a preset compiler is called to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter.

[0006] Preferably, the preset visual low-code parameter configuration model includes: Generate a visual low-code parameter configuration interface with graphical components through the development framework, so that the user can input the telemetry parameters to be extracted through the visual low-code parameter configuration interface; Establish a storage module, and connect the storage module to the visual low-code parameter configuration interface to form a visual low-code parameter configuration model.

[0007] Preferably, the storage module stores the native parameter extraction algorithm, the dependent native parameters corresponding to the derived parameters, and the dynamically compiled source code that can solve the derived parameters based on the dependent native parameters; wherein, it includes: Treating common parameters and asynchronous parameters in the telemetry parameters as native parameters, extracting common attributes of the native parameters as extraction categories, and storing the parameter names of the native parameters and the extraction categories as subsets of JSON in JSON format; The telemetry parameters that need to be extracted and calculated based on the native parameters are used as derived parameters, the native parameters on which the derived parameters are dependent are stored as dependent native parameters, and the dynamically compiled source code is converted into JSON format for storage; wherein the dynamically compiled source code includes the dependency operation logic between the derived parameters and the dependent native parameters.

[0008] Preferably, determining whether the real-time telemetry parameter is the native parameter or the derived parameter includes: If the user actively inputs real-time telemetry parameters for the real-time telemetry data, the real-time telemetry parameters are matched one-to-one with the telemetry parameters in the storage module; If the user preselects the automatic mode, the telemetry parameters in the storage module are automatically assigned to the real-time telemetry data based on the data format, protocol type, or header keyword of the real-time telemetry data as the real-time telemetry parameters corresponding to the telemetry data; In which, a parameter type identifier is preset on the telemetry parameter; if the parameter type identifier of the telemetry parameter is a native parameter, the real-time telemetry parameter is the native parameter; if the parameter type identifier of the telemetry parameter is a derived parameter, the real-time telemetry parameter is a derived parameter.

[0009] Preferably, calling a preset compiler to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter includes: Parsing the dynamically compiled source code according to the name, keyword or operator of the derived parameter to obtain a source code instruction set; Invoking the compiler to compile the source code instruction set in real time to generate an executable parsing module; The target telemetry data corresponding to the derived parameters is obtained through the analysis module.

[0010] Preferably, in the process of calling the compiler to compile the source code instruction set in real time to generate an executable parsing module, if error information is captured, the compiler will feedback the error information to the user in the form of a log, and the user can modify the C language source code instruction set online through the visual low-code parameter configuration interface.

[0011] Preferably, after the user modifies the source code instruction set online to form a new version of the dynamically compiled source code, the visual low-code parameter configuration model uses hot loading technology to replace the existing parsing module online with a new version of the parsing module compiled based on the new version of the dynamically compiled source code.

[0012] The present invention also provides a telemetry universal parsing and real-time compilation system, which implements the telemetry universal parsing and real-time compilation method described above, comprising: A visual low-code parameter configuration model for configuring telemetry data parameter parsing logic; wherein the telemetry data parameter parsing logic includes: classifying telemetry parameter types of telemetry data into native parameters and derived parameters, storing an extraction algorithm for the native parameters, storing dependent native parameters corresponding to the derived parameters, and dynamically compiled source code that can solve the derived parameters based on the dependent native parameters; A telemetry data parameter parsing model is used to determine whether a real-time telemetry parameter is the native parameter or the derived parameter; the real-time telemetry parameter is a telemetry parameter obtained by performing real-time data extraction on the real-time telemetry data; wherein, If the real-time telemetry parameter is the native parameter, extracting the real-time telemetry parameter according to the extraction algorithm; If the real-time telemetry parameter is the derived parameter, a preset compiler is called to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter.

[0013] Preferably, the visual low-code parameter configuration model includes: a visual low-code parameter configuration interface with graphical components and a storage module generated by a development framework; wherein, The visual low-code parameter configuration interface is used to enable the user to input the telemetry parameters to be extracted through the visual low-code parameter configuration interface; The storage module is used to classify and store all telemetry parameters; which includes: treating common parameters and asynchronous parameters in the telemetry parameters as native parameters, extracting common attributes of the native parameters as extraction categories, and treating the parameter names of the native parameters and the extraction categories as subsets of JSON, and storing them in JSON format; treating telemetry parameters that need to be attached to the native parameters for extraction and calculation as derived parameters, storing the native parameters to which the derived parameters are attached as dependent native parameters, and converting the dynamically compiled source code into JSON format for storage; wherein, the dynamically compiled source code contains the dependency operation logic between the derived parameters and the dependent native parameters.

[0014] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the telemetry universal parsing and real-time compilation method as described above.

[0015] From the above technical solution, it can be seen that the telemetry general parsing real-time compilation method, system and computer-readable storage medium provided by the present invention configure the telemetry data parameter parsing logic through a preset visual low-code parameter configuration model, wherein the telemetry parameter types of the telemetry data are divided into native parameters and derived parameters, the extraction algorithm of the native parameters is stored, the dependent native parameters corresponding to the derived parameters are stored, and the dynamic compilation source code that can solve the derived parameters according to the dependent native parameters is stored. Then, after receiving the real-time telemetry data, it is directly determined whether the real-time telemetry parameter for data extraction of the real-time telemetry data is the native parameter or the derived parameter. If the real-time telemetry parameter is the native parameter, the real-time telemetry parameter is extracted according to the extraction algorithm. If the real-time telemetry parameter is the derived parameter, the preset compilation is called. The compiler compiles the dynamic compilation source code of the derived parameters in real time to obtain the target telemetry data corresponding to the derived parameters. In this way, when designing the telemetry parameter input, in addition to the conventional information, a C language script can be added as input. The parsing source code instruction set is dynamically compiled during the real-time parsing process, so that the dynamic compilation source code that can solve the derived parameters can be directly run in the memory, so that the real-time compilation code of the derived parameters can be performed, and the real-time extraction algorithm of the derived parameters can be dynamically expanded, thereby improving the applicability and scalability of real-time parameter parsing. In this way, the threshold for telemetry parsing development is lowered, and non-professional developers can also quickly configure parameters and specific parsing algorithms, shortening the development cycle, and realizing immediate effect after the parsing logic is modified without redeploying the system, meeting the needs of rapid adjustment of parsing rules in telemetry data processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] By referring to the following description in conjunction with the accompanying drawings, and with a more complete understanding of the present invention, other objects and results of the present invention will become more apparent and easier to understand. In the accompanying drawings: Figure 1 Flowchart of a telemetry universal parsing and real-time compilation method according to an embodiment of the present invention; Figure 2 4 is a system block diagram of a telemetry universal parsing and real-time compilation system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] Telemetry real-time parameters are the process of extracting parameters from telemetry data and quantifying them in engineering. There are many types of telemetry parameters. Generally speaking, conventional parameters are called native parameters. We can select common information for standardization, such as the number of parameter bits, parameter type, parameter calibration, etc. Based on this information, parameter classes and interfaces are designed. In real-time extraction, the corresponding telemetry parameters can be extracted through various operations. However, the extraction of certain complex parameters cannot be obtained only through conventional calculation formulas. It requires the values ​​of other parameters, such as the value of barometric pressure altitude, which depends on the value of barometric pressure. After extracting the barometric pressure value, a series of operations are performed to extract the barometric pressure altitude. We define such parameters as derived parameters. The extraction of derived parameters can be coded according to different parameter calculation methods. This will result in each new derived parameter requiring code modification based on the parameter calculation method, recompilation, and generation of a running program.

[0018] To address the above-mentioned issues, the present invention provides a real-time compilation method, system, and computer-readable storage medium for universal telemetry parsing. Based on the aforementioned technical issues, in this embodiment, in addition to conventional information, a C language script is added as input when designing telemetry parameter input. The C language source code is dynamically compiled and parsed during the real-time parsing process. This allows the real-time compilation code for derived parameters to be designed in advance, and the real-time extraction algorithm for derived parameters to be dynamically expanded, thus providing great applicability and scalability for real-time parameter parsing. The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0019] In order to illustrate the telemetry universal parsing real-time compilation method and system provided by the present invention, Figure 1 、 Figure 2 The embodiments of the present invention are exemplarily indicated.

[0020] The following description of exemplary embodiments is merely illustrative in nature and is in no way intended to limit the present invention, its application, or uses. Techniques and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques and devices should be considered part of the specification.

[0021] like Figure 1As shown, the present invention provides a telemetry universal parsing and real-time compilation method, comprising: S1: Configuring telemetry data parameter parsing logic through a preset visual low-code parameter configuration model; wherein the telemetry data parameter parsing logic includes: classifying telemetry parameter types of telemetry data into native parameters and derived parameters, storing an extraction algorithm for the native parameters, storing dependent native parameters corresponding to the derived parameters, and dynamically compiling source code that can solve the derived parameters based on the dependent native parameters; S2: Receive real-time telemetry data, and determine whether the real-time telemetry parameter is the native parameter or the derived parameter; the real-time telemetry parameter is the telemetry parameter obtained by performing real-time data extraction on the real-time telemetry data; wherein, If the real-time telemetry parameter is the native parameter, extracting the real-time telemetry parameter according to the extraction algorithm; If the real-time telemetry parameter is the derived parameter, a preset compiler is called to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter.

[0022] It should be noted that real-time telemetry data is a data set with various categories and certain commonalities, and the telemetry parameter is the category itself, or the commonality itself, that is, the real-time telemetry data can be extracted through the telemetry parameter (real-time telemetry parameter), so as to obtain telemetry data of a specific category or specific commonality. The telemetry data of the specific category or specific commonality is the target telemetry data corresponding to the telemetry parameter (real-time telemetry parameter).

[0023] Step S1 is a process of configuring telemetry data parameter parsing logic through a preset visual low-code parameter configuration model; wherein the telemetry data parameter parsing logic includes: dividing the telemetry parameter types of the telemetry data into native parameters and derived parameters, storing the extraction algorithm of the native parameters, storing the dependent native parameters corresponding to the derived parameters, and dynamically compiling source code that can solve the derived parameters based on the dependent native parameters; In this embodiment, the process of presetting a visual low-code parameter configuration model includes: S11: Generate a visual low-code parameter configuration interface with a graphical component through a development framework, so that a user can input telemetry parameters to be extracted through the visual low-code parameter configuration interface; S12: Establish a storage module, and connect the storage module to the visual low-code parameter configuration interface to form a visual low-code parameter configuration model.

[0024] All telemetry parameters are classified and stored by the storage module, that is, the storage module stores the extraction algorithm of the native parameters, the dependent native parameters corresponding to the derived parameters, and the dynamic compilation source code that can solve the derived parameters according to the dependent native parameters; wherein, it includes: S121: treating common parameters and asynchronous parameters in the telemetry parameters as native parameters, extracting common attributes of the native parameters as extraction categories, and storing the parameter names of the native parameters and the extraction categories as subsets of JSON in JSON format; S122: The telemetry parameters that need to be extracted and calculated based on the native parameters are used as derived parameters, the native parameters on which the derived parameters are dependent are stored as dependent native parameters, and the dynamically compiled source code is converted into JSON format for storage; wherein the dynamically compiled source code includes the dependency operation logic between the derived parameters and the dependent native parameters.

[0025] In one specific embodiment, the development framework is QT, a cross-platform C++ graphical user interface application development framework. Regarding the construction of a low-code parameter configuration interface, a visual low-code parameter configuration interface is designed based on the QT framework, providing graphical components (such as text boxes, drop-down boxes, and buttons) for users to enter telemetry parsing parameters (such as data format, protocol type, and parsing rules). QT's signals and slots mechanism is used to implement the interaction logic between components, allowing users to intuitively configure parsing parameters.

[0026] Regarding parameter classification and storage, once the user completes parameter input and triggers a generation instruction, the system parses the input parameters. Based on the telemetry parameter template rules, parameters are defined as native and derived parameters. Native parameters are further divided into standard and asynchronous parameters. First, common attributes of the parameters are extracted. Parameter names, parameter types, and other information are designed as subsets of JSON according to the JSON format. This standardizes parameter storage to the JSON format.

[0027] Step S2 is a process of receiving real-time telemetry data and determining whether the real-time telemetry parameter extracted from the real-time telemetry data is the native parameter or the derived parameter. If the real-time telemetry parameter is the native parameter, the real-time telemetry parameter is extracted according to the extraction algorithm; if the real-time telemetry parameter is the derived parameter, a preset compiler is called to perform real-time compilation of the dynamic compilation source code of the derived parameter to obtain the target telemetry data corresponding to the derived parameter.

[0028] In this embodiment, determining whether the real-time telemetry parameter is the native parameter or the derived parameter includes: S211: If the user actively inputs real-time telemetry parameters for the real-time telemetry data, the real-time telemetry parameters are matched one-to-one with the telemetry parameters in the storage module; S212: If the user preselects the automatic mode, the telemetry parameters in the storage module are automatically assigned to the real-time telemetry data based on the data format, protocol type, or header keyword of the real-time telemetry data as the real-time telemetry parameters corresponding to the telemetry data; In which, a parameter type identifier is preset on the telemetry parameter; if the parameter type identifier of the telemetry parameter is a native parameter, the real-time telemetry parameter is the native parameter; if the parameter type identifier of the telemetry parameter is a derived parameter, the real-time telemetry parameter is a derived parameter.

[0029] Invoking a preset compiler to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter, including: S221: Parsing the dynamically compiled source code according to the name, keyword, or operator of the derived parameter to obtain a source code instruction set; S222: calling the compiler to perform real-time compilation on the source code instruction set to generate an executable parsing module; S223: Obtain target telemetry data corresponding to the derived parameters through the analysis module.

[0030] Among them, in this embodiment, in the process of calling the compiler to compile the source code instruction set in real time to generate an executable parsing module, if error information is captured, the compiler will feedback the error information to the user in the form of a log, and the user can modify the source code instruction set online through the visual low-code parameter configuration interface.

[0031] After the user modifies the source code instruction set online to form a new version of the dynamically compiled source code, the visual low-code parameter configuration model uses hot loading technology to replace the existing parsing module online with a new version of the parsing module compiled based on the new version of the dynamically compiled source code.

[0032] In a specific embodiment, for most native parameters, the telemetry data received in real time is input into the preset first parsing module. The first parsing module processes the data according to the parsing logic of the native parameters, outputs the parsing results, and displays them through the QT interface or transmits them to other system modules. If the relevant compilation details of the native parameters need to be modified later, the parsing logic of the native parameters can be directly modified based on the visual low-code parameter configuration model, thereby forming a new first parsing module and completing the update of the first parsing module.

[0033] For derived parameters, the dynamically compiled source code for the derived parameters is input. Based on the parameter name, formal parameters, keywords, operators, and other information, the derived parameter source code instruction set (C language source code instruction set) is parsed in real time. The compiler (in this specific embodiment, the TCC compiler) is then dynamically invoked to compile the generated C language source file (C language source code instruction set) in real time. During the compilation process, error messages output by the TCC compiler (such as syntax errors and type mismatches) are captured and fed back to the user in the form of a log, prompting them to correct the parameter configuration. If the compilation is successful, an executable parsing module is generated to obtain telemetry data for the derived parameters in real time, thus realizing a scalable execution environment in real time.

[0034] Furthermore, in this embodiment, when the user modifies the native or derived parameters again and triggers a regeneration instruction, a new first parsing module corresponding to the native parameters or a new parsing module corresponding to the derived parameters is regenerated. In this embodiment, hot reloading technology is employed to replace the old parsing module (the first parsing module) without interrupting the reception and processing of telemetry data, thereby achieving dynamic updates of the parsing logic.

[0035] In a more specific overall embodiment, it is necessary to install QT and visual studio 2015 development environment on the host, configure the compilation tool chain (such as GCC), and associate and arrange the TCC compiler source code, compile and integrate it into the development project to ensure that the TCC compiler can be called through the code for compilation operations. More specifically, regarding the construction of the low-code parameter configuration interface, QT classes such as QWidget, QLineEdit, and QComboBox are used to build parameter input components, and layout managers such as QVBoxLayout and QHBoxLayout are used to design the interface layout. Custom signal and slot functions are defined to implement parameter input validation (such as data format checking) and inter-component linkage logic.

[0036] Regarding parameter classification and storage, a parameter management class is established, and different parameter objects are constructed according to different parameter classifications. The common attributes of parameters are represented by different interfaces, and the common parsing algorithm for native parameters is distinguished by keywords; the dynamic compilation code of derived parameters is represented in string form, and the final parameters are stored in JSON format.

[0037] Subsequently, a data receiving thread is created, using a native socket-encapsulated class to receive telemetry data. This data is passed to the compiled parsing module, which formats the parsing results and displays them in various user interfaces (e.g., curve charts, tables, and full-frame images). The dynamic parsing string for the compiled derived function is written using the TCC compiler APIs (such as tcc_new and tcc_compile_string). First, the dynamic parsing string for the derived parameter is obtained. This string contains the parameter name of the native parameter, which is then associated with the native parameter as a formal parameter. Then, using a syntax parsing tool, the user input parameters are accurately filled into the corresponding positions in the template, recognized as formal parameter information, and a C script is generated. Finally, the generated C script is passed to the TCC compiler for real-time compilation and the compiled results are obtained. This allows the real-time parsing module to obtain the values ​​of the derived parameters through dynamic compilation and parsing.

[0038] In addition, hot loading is achieved by using dynamic library mechanism and shared library loading technology. When updating the parsing module (the first parsing module), the old parsing module occupying resources is first unloaded, and then the new parsing module is loaded and the data parsing process is reinitialized.

[0039] Based on the above embodiments, the real-time compilation method for general telemetry parsing provided by the present invention lowers the threshold for telemetry parsing development through visual low-code parameter configuration. Non-professional developers can also quickly configure parameters and specific parsing algorithms, shortening the development cycle. It supports "runtime algorithm injection" and uses compiler real-time compilation and hot loading technology to achieve immediate effect after modification of the parsing logic without redeploying the system, thereby meeting the demand for rapid adjustment of parsing rules in telemetry data processing.

[0040] like Figure 2 As shown, the present invention also provides a telemetry universal parsing and real-time compilation system 100, which implements the telemetry universal parsing and real-time compilation method as described above, including: A visual low-code parameter configuration model 110 is used to configure telemetry data parameter parsing logic; wherein the telemetry data parameter parsing logic includes: classifying telemetry parameter types of telemetry data into native parameters and derived parameters, storing an extraction algorithm for the native parameters, storing dependent native parameters corresponding to the derived parameters, and dynamically compiling source code that can solve the derived parameters based on the dependent native parameters; The telemetry data parameter parsing model 120 is used to determine whether the real-time telemetry parameter is the native parameter or the derived parameter; the real-time telemetry parameter is the telemetry parameter extracted from the real-time telemetry data; wherein, If the real-time telemetry parameter is the native parameter, extracting the real-time telemetry parameter according to the extraction algorithm; If the real-time telemetry parameter is the derived parameter, a preset compiler is called to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter.

[0041] The visual low-code parameter configuration model includes: a visual low-code parameter configuration interface with graphical components and a storage module generated by the QT framework (development framework); wherein, The visual low-code parameter configuration interface is used to enable the user to input the telemetry parameters to be extracted through the visual low-code parameter configuration interface; The storage module is used to classify and store all telemetry parameters; which includes: treating common parameters and asynchronous parameters in the telemetry parameters as native parameters, extracting common attributes of the native parameters as extraction categories, and treating the parameter names of the native parameters and the extraction categories as subsets of JSON, and storing them in JSON format; treating telemetry parameters that need to be attached to the native parameters for extraction and calculation as derived parameters, storing the native parameters to which the derived parameters are attached as dependent native parameters, and converting the dynamically compiled source code into JSON format for storage; wherein, the dynamically compiled source code contains the dependency operation logic between the derived parameters and the dependent native parameters.

[0042] Similarly, a visual interface is built based on the QT framework (development framework), providing a parameter input component to receive user-entered telemetry parsing parameters. The component manages component interactions through a signal and slot mechanism. User-entered parameters are parsed and managed according to parameter type. Real-time telemetry data is received, and for derived parameters, the TCC compiler is used to compile the generated C language source file. Compilation errors are captured and fed back to the user, and the compiled parsing module is output. The compiled parsing module is then used to perform data parsing and output the parsing results. Hot reloading technology is used to dynamically replace parsing modules and support real-time updates of the parsing logic.

[0043] The specific implementation method is described in the embodiment of the above-mentioned telemetry general parsing and real-time compilation method, which will not be described in detail here.

[0044] As described above, the telemetry general parsing real-time compilation system provided by the present invention can lower the threshold for telemetry parsing development. Non-professional developers can also quickly configure parameters and specific parsing algorithms, shorten the development cycle, and realize immediate effect after the parsing logic is modified without redeploying the system, thereby meeting the demand for rapid adjustment of parsing rules in telemetry data processing.

[0045] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the aforementioned telemetry general parsing and real-time compilation method is implemented. The readable storage medium may be non-volatile or volatile. The readable storage medium stores a device setting self-adjustment program. When the device setting self-adjustment program is executed by the processor, the following is implemented: The telemetry data parameter parsing logic is configured through a preset visual low-code parameter configuration model; wherein the telemetry data parameter parsing logic includes: dividing the telemetry parameter types of the telemetry data into native parameters and derived parameters, storing the extraction algorithm of the native parameters, storing the dependent native parameters corresponding to the derived parameters, and dynamically compiling source code that can solve the derived parameters based on the dependent native parameters; receiving real-time telemetry data, and determining whether a real-time telemetry parameter extracted from the real-time telemetry data is the native parameter or the derived parameter; wherein, If the real-time telemetry parameter is the native parameter, extracting the real-time telemetry parameter according to the extraction algorithm; If the real-time telemetry parameter is the derived parameter, a preset compiler is called to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter.

[0046] Specifically, the specific implementation method when the computer program is executed by the processor can refer to the description of the relevant steps of the embodiment of the telemetry general parsing and real-time compilation method, which will not be repeated here.

[0047] In the several embodiments provided by the present invention, it should be understood that the disclosed methods, systems, and readable storage media can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and actual implementation may employ other division methods.

[0048] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0049] The above description uses the accompanying drawings to illustrate the method, system, and computer-readable storage medium for real-time compilation of universal telemetry parsing according to the present invention. However, those skilled in the art will appreciate that various improvements can be made to the method, system, and computer-readable storage medium for real-time compilation of universal telemetry parsing according to the present invention without departing from the scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A telemetry general parsing and real-time compilation method, characterized in that: include: The telemetry data parameter parsing logic is configured through a preset visual low-code parameter configuration model; wherein the telemetry data parameter parsing logic includes: dividing the telemetry parameter types of the telemetry data into native parameters and derived parameters, storing the extraction algorithm of the native parameters, storing the dependent native parameters corresponding to the derived parameters, and dynamically compiling source code that can solve the derived parameters based on the dependent native parameters; receiving real-time telemetry data, and determining whether a real-time telemetry parameter is the native parameter or the derived parameter; the real-time telemetry parameter is a telemetry parameter obtained by performing real-time data extraction on the real-time telemetry data; wherein, If the real-time telemetry parameter is the native parameter, extracting the real-time telemetry parameter according to the extraction algorithm; If the real-time telemetry parameter is the derived parameter, a preset compiler is called to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter.

2. The telemetry universal parsing and real-time compilation method according to claim 1, characterized in that: Preset visual low-code parameter configuration model, including: Generate a visual low-code parameter configuration interface with graphical components through the development framework, so that the user can input the telemetry parameters to be extracted through the visual low-code parameter configuration interface; Establish a storage module, and connect the storage module to the visual low-code parameter configuration interface to form a visual low-code parameter configuration model.

3. The telemetry universal parsing and real-time compilation method according to claim 2, characterized in that: The storage module stores the extraction algorithm of the native parameters, the dependent native parameters corresponding to the derived parameters, and the dynamic compilation source code that can solve the derived parameters according to the dependent native parameters; wherein, the method includes: Treating common parameters and asynchronous parameters in the telemetry parameters as native parameters, extracting common attributes of the native parameters as extraction categories, and storing the parameter names of the native parameters and the extraction categories as subsets of JSON in JSON format; The telemetry parameters that need to be extracted and calculated based on the native parameters are used as derived parameters, the native parameters on which the derived parameters are dependent are stored as dependent native parameters, and the dynamically compiled source code is converted into JSON format for storage; wherein the dynamically compiled source code includes the dependency operation logic between the derived parameters and the dependent native parameters.

4. The telemetry universal parsing and real-time compilation method according to claim 3, characterized in that: Determining whether the real-time telemetry parameter is the native parameter or the derived parameter includes: If the user actively inputs real-time telemetry parameters for the real-time telemetry data, the real-time telemetry parameters are matched one-to-one with the telemetry parameters in the storage module; If the user preselects the automatic mode, the telemetry parameters in the storage module are automatically assigned to the real-time telemetry data based on the data format, protocol type, or header keyword of the real-time telemetry data as the real-time telemetry parameters corresponding to the telemetry data; In which, a parameter type identifier is preset on the telemetry parameter; if the parameter type identifier of the telemetry parameter is a native parameter, the real-time telemetry parameter is the native parameter; if the parameter type identifier of the telemetry parameter is a derived parameter, the real-time telemetry parameter is a derived parameter.

5. The telemetry universal parsing and real-time compilation method according to claim 4, characterized in that: Invoking a preset compiler to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter, including: Parsing the dynamically compiled source code according to the name, keyword or operator of the derived parameter to obtain a source code instruction set; Invoking the compiler to compile the source code instruction set in real time to generate an executable parsing module; The target telemetry data corresponding to the derived parameters is obtained through the analysis module.

6. The telemetry universal parsing and real-time compilation method according to claim 5, characterized in that: In the process of calling the compiler to compile the source code instruction set in real time to generate an executable parsing module, if error information is captured, the compiler will feedback the error information to the user in the form of a log, and the user can modify the source code instruction set online through the visual low-code parameter configuration interface.

7. The telemetry universal parsing and real-time compilation method according to claim 6, characterized in that: After the user modifies the source code instruction set online to form a new version of the dynamically compiled source code, the visual low-code parameter configuration model uses hot loading technology to replace the existing parsing module online with a new version of the parsing module compiled based on the new version of the dynamically compiled source code.

8. A telemetry universal parsing and real-time compilation system, characterized by Implementing the telemetry universal parsing and real-time compilation method according to any one of claims 1 to 7, comprising: A visual low-code parameter configuration model for configuring telemetry data parameter parsing logic; wherein the telemetry data parameter parsing logic includes: classifying telemetry parameter types of telemetry data into native parameters and derived parameters, storing an extraction algorithm for the native parameters, storing dependent native parameters corresponding to the derived parameters, and dynamically compiled source code that can solve the derived parameters based on the dependent native parameters; A telemetry data parameter parsing model is used to receive real-time telemetry data and determine whether the real-time telemetry parameter is the native parameter or the derived parameter; the real-time telemetry parameter is the telemetry parameter extracted from the real-time telemetry data; wherein, If the real-time telemetry parameter is the native parameter, extracting the real-time telemetry parameter according to the extraction algorithm; If the real-time telemetry parameter is the derived parameter, a preset compiler is called to compile the dynamic compilation source code of the derived parameter in real time to obtain target telemetry data corresponding to the derived parameter.

9. The telemetry universal parsing and real-time compilation system according to claim 8, characterized in that: The visual low-code parameter configuration model includes: a visual low-code parameter configuration interface with graphical components and a storage module generated by a development framework; wherein, The visual low-code parameter configuration interface is used to enable the user to input the telemetry parameters to be extracted through the visual low-code parameter configuration interface; The storage module is used to classify and store all telemetry parameters; which includes: treating common parameters and asynchronous parameters in the telemetry parameters as native parameters, extracting common attributes of the native parameters as extraction categories, and treating the parameter names of the native parameters and the extraction categories as subsets of JSON, and storing them in JSON format; treating telemetry parameters that need to be attached to the native parameters for extraction and calculation as derived parameters, storing the native parameters to which the derived parameters are attached as dependent native parameters, and converting the dynamically compiled source code into JSON format for storage; wherein, the dynamically compiled source code contains the dependency operation logic between the derived parameters and the dependent native parameters.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the telemetry general parsing and real-time compilation method according to any one of claims 1 to 7 is implemented.

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