CN120178844A - Embedded log analysis method and device - Google Patents
Embedded log analysis method and device Download PDFInfo
- Publication number
- CN120178844A CN120178844A CN202510354871.1A CN202510354871A CN120178844A CN 120178844 A CN120178844 A CN 120178844A CN 202510354871 A CN202510354871 A CN 202510354871A CN 120178844 A CN120178844 A CN 120178844A
- Authority
- CN
- China
- Prior art keywords
- fault
- data
- telemetry
- tracking
- code
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0208—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the configuration of the monitoring system
- G05B23/0213—Modular or universal configuration of the monitoring system, e.g. monitoring system having modules that may be combined to build monitoring program; monitoring system that can be applied to legacy systems; adaptable monitoring system; using different communication protocols
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24065—Real time diagnostics
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Debugging And Monitoring (AREA)
Abstract
本说明书实施例提供嵌入式日志分析方法及装置，其中嵌入式日志分析方法包括：获取遥测数据源码，基于遥测数据源码进行解析确定遥测解析数据；基于遥测解析数据确定故障识别数据；其中，故障识别数据包括故障数据和/或追踪数据，故障数据用于标识故障点，追踪数据用于进行场景复现；基于故障识别数据和逻辑关联库进行故障分析，得到故障原因。通过上述方案中的故障数据和追踪数据可以实现在火箭与地面通信中降低日志的内存和带宽消耗，并实现基于故障数据和追踪数据进行自动化分析，从而提高故障定位的准确度以及速度。
The embodiments of this specification provide an embedded log analysis method and device, wherein the embedded log analysis method includes: obtaining a telemetry data source code, performing analysis based on the telemetry data source code to determine telemetry analysis data; determining fault identification data based on the telemetry analysis data; wherein the fault identification data includes fault data and/or tracking data, the fault data is used to identify the fault point, and the tracking data is used to reproduce the scene; performing fault analysis based on the fault identification data and the logical association library to obtain the cause of the fault. The fault data and tracking data in the above scheme can reduce the memory and bandwidth consumption of the log in the communication between the rocket and the ground, and realize automatic analysis based on the fault data and tracking data, thereby improving the accuracy and speed of fault location.
Description
Technical Field
The embodiment of the specification relates to the technical field of aerospace, in particular to an embedded log analysis method.
Background
In the aerospace field, a flight control system is used as a core component, and effective recording and analysis of historical test log data of the flight control system are critical to key technology verification, accumulation and iteration. The existing log system usually records log data in a nonvolatile memory or transmits the log data to ground test and control equipment through a wireless link, and the log system has the defects that a log data structure needs to occupy larger hardware memory resources or wireless link bandwidth resources, a log output to a target medium needs to consume partial time resources which possibly affect the running performance of the system, a large amount of log data is usually needed to be manually analyzed in an offline mode, a plurality of data sources are difficult to quickly select and comprehensively analyze, the system fault cause is difficult to quickly locate and solve, and specific scenes and logic branches of software execution cannot be efficiently reproduced.
The flight control system supporting software usually runs in an embedded hardware platform with limited memory resources, and the hardware platform can not be recycled after certain flight tests are finished, so that the wireless link equipped in the actual task is usually limited in bandwidth. These all present significant challenges for efficient expansion and further application optimization of conventional log systems.
Thus, a better solution is needed.
Disclosure of Invention
In view of this, the present description embodiments provide an embedded log analysis method. One or more embodiments of the present specification relate to an embedded journal analysis apparatus, a computing device, a computer-readable storage medium, and a computer program that solve the technical drawbacks of the related art.
According to a first aspect of embodiments of the present disclosure, there is provided an embedded log analysis method, including:
acquiring telemetry data source codes, and analyzing and determining telemetry analysis data based on the telemetry data source codes;
Determining fault identification data based on the telemetry analytic data, wherein the fault identification data comprises fault data and/or tracking data, the fault data is used for identifying fault points, and the tracking data is used for scene reproduction;
and carrying out fault analysis based on the fault identification data and the logic association library to obtain a fault reason.
In one possible implementation, parsing the determined telemetry parse data based on telemetry source code includes:
Determining bit source code data based on the telemetry data source code;
and converting the bit source code data into telemetry analysis data according to a preset conversion rule.
In one possible implementation, determining fault identification data based on telemetry resolution data includes:
extracting a target fault code from telemetry analysis data, wherein the target fault code is a fault code of the current telemetry period;
comparing the target fault code with a fault logic association library to determine a fault comparison result, wherein the fault logic association library comprises at least two fault codes and logic association relations between the at least two fault codes and the telemetering physical quantity;
And under the condition that the fault comparison result is the target fault code in the fault logic association inventory, taking the target fault code as fault data.
In one possible implementation, determining fault identification data based on telemetry resolution data includes:
extracting a target tracking code from telemetry analysis data, wherein the target tracking code is the tracking code of the current telemetry period;
Comparing the target tracking code with a tracking logic association library to determine a tracking comparison result, wherein the tracking logic association library comprises at least two tracking codes and a logic association relationship between the at least two tracking codes and the telemetering physical quantity;
And under the condition that the tracking comparison result is that the target tracking code exists in the tracking logic association library, taking the target tracking code as tracking data.
In one possible implementation, performing fault analysis based on the fault identification data and the logical association library includes:
extracting fault details from the telemetry resolution data in the event that the fault identification data includes fault data;
Acquiring corresponding first telemetering physical quantities from a fault logic association library based on fault data and fault details;
and carrying out fault analysis based on the first telemetering physical quantity, and determining the fault reason.
In one possible implementation, performing fault analysis based on the fault identification data and the logical association library includes:
In the case that the fault identification data comprises trace data, or in the case that the fault identification data comprises trace data and the fault analysis is performed based on the first telemetering physical quantity, and the cause of the fault is not determined, extracting trace details from the telemetering analysis data;
generating history tracking details based on the second telemetry physical quantity;
the cause of the fault is determined based on the historical tracking details and the expected tracking details.
In one possible implementation, the method further includes:
After determining the fault cause, obtaining a solution measure from the logic association library based on the fault cause, and displaying the solution measure;
in the case that the cause of the fault is not determined, the trace data and the fault data are displayed to perform fault analysis based on the trace data and the fault data.
According to a second aspect of embodiments of the present specification, there is provided an embedded log analysis device, comprising:
The data acquisition module is configured to acquire telemetry data source codes, and analyze and determine telemetry analysis data based on the telemetry data source codes;
The system comprises a data analysis module, a scene reproduction module and a scene reproduction module, wherein the data analysis module is configured to determine fault identification data based on telemetry analysis data, the fault identification data comprises fault data and/or tracking data, the fault data is used for identifying a fault point, and the tracking data is used for performing scene reproduction;
The fault judging module is configured to perform fault analysis based on the fault identification data and the logic association library to obtain a fault reason.
According to a third aspect of embodiments of the present specification, there is provided a computing device comprising:
A memory and a processor;
The memory is configured to store computer-executable instructions that, when executed by the processor, perform the steps of the embedded log analysis method described above.
According to a fourth aspect of embodiments of the present specification, there is provided a computer readable storage medium storing computer executable instructions which, when executed by a processor, implement the steps of the above-described embedded log analysis method.
According to a fifth aspect of embodiments of the present specification, there is provided a computer program, wherein the computer program, when executed in a computer, causes the computer to perform the steps of the above-described embedded log analysis method.
The embodiment of the specification provides an embedded log analysis method and device, wherein the embedded log analysis method comprises the steps of obtaining telemetry data source codes, analyzing and determining telemetry analysis data based on the telemetry data source codes, determining fault identification data based on the telemetry analysis data, wherein the fault identification data comprises fault data and/or tracking data, the fault data is used for identifying fault points, the tracking data is used for scene reproduction, and performing fault analysis based on the fault identification data and a logic association library to obtain fault reasons. According to the fault data and the tracking data in the scheme, the memory and bandwidth consumption of the log can be reduced in the communication between the rocket and the ground, and the automatic analysis based on the fault data and the tracking data is realized, so that the accuracy and the speed of fault positioning are improved.
Drawings
FIG. 1 is a flow chart of an embedded log analysis method provided in one embodiment of the present disclosure;
FIG. 2 is a fault code schematic diagram of an embedded log analysis method according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a trace code of an embedded log analysis method according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a trace flag code of an embedded log analysis method according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of interface codes of an embedded log analysis method according to an embodiment of the present disclosure;
FIG. 6 is a schematic diagram of an architecture of an embedded log analysis method according to an embodiment of the present disclosure;
FIG. 7 is a schematic diagram of an embedded log analyzer according to an embodiment of the present disclosure;
FIG. 8 is a block diagram of a computing device provided in one embodiment of the present description.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present description. This description may be embodied in many other forms than described herein and similarly generalized by those skilled in the art to whom this disclosure pertains without departing from the spirit of the disclosure and, therefore, this disclosure is not limited by the specific implementations disclosed below.
The terminology used in the one or more embodiments of the specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of the specification. As used in this specification, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present specification refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that, although the terms first, second, etc. may be used in one or more embodiments of this specification to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first may also be referred to as a second, and similarly, a second may also be referred to as a first, without departing from the scope of one or more embodiments of the present description. The term "if" as used herein may be interpreted as "at..once" or "when..once" or "in response to a determination", depending on the context.
In the present specification, an embedded log analysis method is provided, and the present specification relates to an embedded log analysis apparatus, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.
Referring to fig. 1, fig. 1 shows a flowchart of an embedded log analysis method according to an embodiment of the present disclosure, which specifically includes the following steps.
Step 101, acquiring telemetry data source codes, and analyzing and determining telemetry analysis data based on the telemetry data source codes;
the telemetry data source codes are data source codes which are transmitted to the ground by rocket according to the period, such as binary bit streams. The telemetry analysis data is data obtained by analyzing telemetry data source codes through set rules, for example, binary data is converted into decimal data.
In one possible implementation, parsing the telemetry parse data based on telemetry data source codes includes determining bit source code data based on the telemetry data source codes and converting the bit source code data to telemetry parse data according to a preset conversion rule.
The bit source code data may be binary bit stream data.
In practical applications, the rocket periodically transmits telemetry data source codes to the ground, and the transmission period is usually 10ms.
For example, the flight control software of the rocket sends ground telemetry data source codes to a ground measurement and control system in a period of 100ms, wherein the ground telemetry data source codes are 00000011, and the telemetry data source codes are converted into decimal numbers of 3, so that telemetry analysis data are obtained.
According to the embodiment of the specification, the telemetry data source codes are converted into telemetry analysis data, so that the subsequent identification analysis is facilitated, and the staff can conveniently analyze the telemetry analysis data.
And 102, determining fault identification data based on the telemetry analysis data, wherein the fault identification data comprises fault data and/or tracking data, the fault data is used for identifying fault points, and the tracking data is used for scene reproduction.
The fault identification data is data for performing fault identification. The fault data may be data of the rocket inserted into the telemetry data source code in one telemetry period, and the trace data may be data of the rocket inserted into the telemetry data source code in one telemetry period. The fault data and trace data may be in two parts of the telemetry data source code.
In practical application, an on-arrow log recording module can be arranged, the log recording module efficiently records fault codes (EC: error codes) and tracking codes (TC: track codes) of the system in a bit mode, so that the problem of quick locking in data analysis is facilitated, and detailed Error statistics and state tracking capability are provided through fault details (ErrorInfo _t) and tracking details (TrackInfo _t).
Furthermore, the on-arrow log recording module specifically needs to comprise the following functions of modularized classification, namely classifying fault codes and tracking codes according to the functional modules, so that maintenance and expansion are facilitated. Bit field compression storage, which uses Bit field (Bit-field) and Union (Union) to compact storage state, and saves memory space. And (3) state statistics, namely recording the triggering times of each code through a counting array, and assisting in problem positioning and performance analysis. In the design of fault/trace codes, ec_set macros are used to define various fault codes (EC: error codes), such as specific fault codes contained in the modules of the underlying driver, the application protocol, the test trigger flow, etc. given in fig. 2. Various types of tracking codes (TC: track Code) are defined using the tc_set macro, such as specific tracking codes contained in the initial alignment, compound navigation, etc. modules given in the example of fig. 3.
Specifically, the ec_set and the tc_set are expanded into enumeration members through an X (X) macro, a fault enumeration type (error code_t) and a trace enumeration type (TrackCode _t) are automatically generated, and the total number of fault codes and the total number of trace codes are counted through the ec_num and the tc_num respectively. By defining a fault bit field (ErrorBits _t) and a TRACE bit field (TrackBits _t) by a complex_track_type_bits, combining the bit fields with a buffer, two access modes are realized:
a) Bit operation, wherein each fault or tracking code corresponds to one bit, and a position 1 represents triggering and supports quick state marking;
b) Buffer storage, which is convenient for storing or transmitting bit field data in a whole memory mode.
Specific fault codes (TransInfo _t.code), fault code description information (TransInfo _t.desc), fault bit fields (bits), fault count arrays (bitCnt) and other information are recorded through fault details (ErrorInfo _t). Specific tracking code (TransInfo _t.code), tracking code description information (TransInfo _t.desc), tracking bit field (bits), tracking count array (bitCnt) and other information are recorded through tracking details (TrackInfo _t).
Referring to fig. 4, taking trace details as an example (fault details are the same) analysis, on occupation of storage resources (hardware memory or communication bandwidth), 1bit is used to represent 1 logic branch marking point, the maximum logic branch number that a single control cycle trace detail can mark is N x 8/P, where N represents the number of bytes occupied by the single output cycle trace detail, and P represents the number of control cycles contained in the single output cycle.
For example, in rocket flight control systems, the control period is typically 10ms, and assuming that the flight control software sends 20 bytes of tracking details to the ground survey launch system in 100ms periods, the maximum logical branch number that a single control period tracking detail can mark is 16. If the communication bandwidth allows, the flight control software outputs tracking details in a control period, and the maximum number of markable logic branches is increased to 160, so that each software operation branch can be covered. The communication bandwidth and the control logic complexity of the flight control software are comprehensively considered, wherein under the condition of the shortage of the communication bandwidth, the tracking details can record the execution condition of the logic branches of the key software module preferentially, and under the condition of the permission of the communication bandwidth, the tracking details can record and cover all the logic branches of the software as much as possible.
Further, in the interface, referring to fig. 5, taking trace log RECORD as an example (fault log RECORD is the same), in practical use, firstly, the trace log initialization interface (track_begin) is called to set a starting state, then, the trace log RECORD interface (track_record) is called to mark a target logic branch, and when the target logic branch is marked, a target trace code is used to directly assign a corresponding bit of a trace bit field, so that consumed system time resources are negligible.
When the data size of the fault code, the trace detail and the fault detail needs to be set according to the actual situation, for example, in one period, if the free communication resources are higher, the data of the fault code, the trace detail and the fault detail can be more, and if the free communication resources are less, the data of the fault code, the trace detail and the fault detail need to be reduced, so that normal tasks are not affected.
In one possible implementation, determining fault identification data based on telemetry analysis data comprises extracting a target fault code from the telemetry analysis data, wherein the target fault code is a fault code of a current telemetry period, comparing the target fault code with a fault logic association library to determine a fault comparison result, wherein the fault logic association library comprises at least two fault codes and logic association relations between the at least two fault codes and telemetry physical quantities, and taking the target fault code as the fault data under the condition that the fault comparison result is the target fault code in a fault logic association inventory.
The target fault code is data for identifying faults in the current period, and the fault logic association library is a database of fault codes and telemetering physical quantities, telemetering physical quantities and fault reasons set on the ground according to manual experience knowledge.
In practical application, when the fault code exists in the telemetry analysis data, the data corresponding to the fault code can be extracted, so that the fault identification data can be determined.
For example, four logical branches A, B, C, D are included in the rocket, and the corresponding decimal fault codes are 1, 2, 3 and 4 respectively. The fault code in the telemetry data source code received in a certain period is 00000011, and can be resolved into decimal number 3, if the fault code 3 can be found in the fault logic association library, the fault data is 3.
According to the embodiment of the specification, the fault codes in the telemetry data source codes are acquired, and the acquired fault codes are matched with faults in the fault logic association library, so that the faults of the current period are determined, and the fault positioning speed is improved.
In one possible implementation, determining fault identification data based on telemetry analysis data comprises extracting a target tracking code from the telemetry analysis data, wherein the target tracking code is the tracking code of the current telemetry period, comparing the target tracking code with a tracking logic association library to determine a tracking comparison result, wherein the tracking logic association library comprises at least two tracking codes and a logic association relationship between the at least two tracking codes and telemetry physical quantities, and taking the target tracking code as tracking data when the tracking comparison result is that the target tracking code exists in the tracking logic association library.
The target tracking code is data for identifying the execution action of the current period, and the tracking logic association library is a database of the set tracking code, the telemetering physical quantity and the fault reason.
In practical application, when the tracking code exists in the telemetry analysis data, the data corresponding to the tracking code can be extracted, so that the data can be determined as fault identification data.
For example, four logical branches A, B, C, D are included in the rocket, and the corresponding decimal tracking codes are 1, 2, 3 and 4 respectively. The tracking code in the telemetry data source code received in a certain period is 00000011, and can be resolved into decimal number 3, if the fault code 3 can be found in the tracking logic association library, the tracking data is 3.
According to the embodiment of the specification, the tracking code in the telemetry data source code is acquired, and the acquired tracking code is matched with the tracking logic association library, so that the executing action of the current period is determined, and the scene reproduction speed is improved.
And 103, carrying out fault analysis based on the fault identification data and the logic association library to obtain a fault reason.
In practical application, referring to fig. 6, log analysis software can be deployed on the ground, where the log analysis software takes telemetry analysis data and a logical association library as input, automatically processes the log data (in an online or offline manner) through a fault automatic analysis module and a scene recurrence analysis module, and displays the analysis result on a man-machine interaction interface or stores the analysis result in an analysis document.
It should be noted that, the corresponding logic association library may be customized according to the telemetry data protocol convention and in combination with the requirement of the professional data analysis, and the embodiment of the present disclosure does not limit the specific implementation of the logic association library.
In one possible implementation, fault analysis is performed based on the fault identification data and the logic association library, and the fault analysis comprises the steps of extracting fault details from telemetry analysis data when the fault identification data comprises the fault data, acquiring corresponding first telemetry physical quantities from the fault logic association library based on the fault data and the fault details, and performing fault analysis based on the first telemetry physical quantities to determine a cause of the fault.
Wherein the fault details are all fault codes recorded in the current telemetry period. The first telemetering physical quantity is a telemetering physical quantity corresponding to the fault details.
In practical application, logic association relations between each fault code and other remote measurement physical quantities possibly causing the fault are set in a fault logic association library, when a certain fault code in fault details corresponds to bit setting, log analysis software automatically acquires and processes the associated physical quantity according to the fault association relation set in the association library, and gives out specific reasons and possible solving measures for causing the fault, wherein the reasons and the solving measures can be selectively added into the association library, and are given out by different professional designers according to priori conclusions and experiences.
Along the above example, the rocket includes A, B, C, D logic branches, and the corresponding decimal fault codes are 1, 2, 3 and 4 respectively. 00000011, the fault code in the telemetry data source code received in a certain period can be resolved into decimal number 3, if the fault code 3 can be found in the fault logic association library, the fault data is 3, the corresponding C logic branch is formed, the corresponding physical quantity of C is the relevant physical quantity of power supply conversion, and the power supply conversion fault of the fault cause is determined.
Further, the electric system designer correlates the power supply conversion fault with three telemetering physical quantities of flight control time, a test initiation control flow execution mark and the arrow thermal battery bus voltage, wherein fault correlation logic is that 1) the power supply conversion flow starting mark is valid and then the thermal battery activation flow completion mark is invalid, 2) the time from the power supply conversion flow starting mark to the thermal battery bus voltage is valid is larger than a given time index, and then possible solving measures are given, namely 1) the power supply conversion is ensured to be executed after the thermal battery is activated, 2) whether a power supply conversion circuit is faulty is checked, 3) the thermal battery bus voltage valid judgment threshold is changed, and 4) the time index required for completing the power conversion is changed.
The analysis process of the fault details is the same as that of the fault code, for example, the fault details are 00000101, and the first position 1 from right to left indicates that the fault occurs in the a, and the third position 1 indicates that the fault occurs in the C.
According to the embodiment of the specification, the fault is rapidly positioned through the fault code and the fault details, so that fault analysis is realized, a fault solution is provided, and the fault solution speed is improved.
In one possible implementation, fault analysis is performed based on the fault identification data and the logic association library, including extracting tracking details from the telemetry resolution data in the event that the fault identification data includes trace data or in the event that the fault identification data includes trace data and the fault analysis is performed based on the first telemetry physical quantity fails to determine a cause of the fault, obtaining corresponding second telemetry physical quantity and expected tracking details based on the trace code and the logic association library, generating historical tracking details based on the second telemetry physical quantity, and determining a cause of the fault based on the historical tracking details and the expected tracking details.
Wherein the tracking details are all tracking codes recorded in the current telemetry period, i.e. all performed actions. The second telemetric physical quantity is a telemetric physical quantity corresponding to the tracking details. The expected trace details are logical branches that should normally be executed.
In practical application, the execution condition of the logical branch of the flight control software of each control period is recorded in detail in the tracking details, and in the process of analyzing practical data, a designer can select one or a plurality of local control periods to perform scene reproduction. And setting a certain or some telemetering physical measurement value (data value or state value, which can be calculated for a second time) and the logic association relation (recorded as an association rule) of tracking details in the tracking logic association library, wherein a designer can set a plurality of similar association rules according to actual analysis requirements to form the professional association rule library. When traversing the telemetry data, the log analysis software judges whether the selected physical measurement values meet the triggering conditions given in the association rules in real time, if so, the log analysis software compares whether expected tracking details (expected software logic branch execution conditions) given in the association rules are consistent with actual tracking details (actual software logic branch execution conditions) recorded in the telemetry data of the current control period, and if not, further comprehensive analysis is needed for specific reasons.
It should be noted that, the present scheme may perform scene reproduction directly through the tracking code, or may perform scene reproduction when the fault cause cannot be determined through the fault code.
Along the above example, the rocket includes A, B, C, D logic branches, and the corresponding decimal tracking codes are 1,2, 3 and 4 respectively. 00000101, the trace code in the telemetry data source code received in a certain period can be resolved into decimal number 3, then the fault code 3 can be found in the trace logic association library, the trace data is 3, the current executed logic branch can be determined to be C, in the trace logic association library, the guidance control designer associates the flight time sequence state quantity (1 bit corresponds to a flight time sequence point, such as bit0 corresponds to the start control moment, bit1 corresponds to the engine exhaustion moment and the like) with trace details, the C corresponds to the flight time sequence state quantity is determined from the trace logic association library, a plurality of association rules are formed according to the mathematical simulation result of the flight control model, and after the software is expressed to run to a certain flight stage, the given logic branch can be covered, namely the expected trace details can be obtained.
Further, the tracking detail is 00000111, the first position 1 from right to left indicates that the execution of the A is performed, the second position 1 indicates that the execution of the B is performed, and the third position 1 indicates that the execution of the C is performed. And finally judging whether the tracking details are consistent with the expected tracking details.
According to the embodiment of the specification, the executed logic branches of the rocket are determined by setting the tracking codes and the tracking details, so that the execution condition of the rocket can be reappeared on the ground, fault analysis is performed, the accuracy of the fault analysis is improved, and the data base of the fault analysis is increased.
In one possible implementation, the method further comprises the steps of acquiring a solution from the logic association library based on the fault reason after the fault reason is determined, displaying the solution, and displaying the tracking data and the fault data when the fault reason is not determined so as to enable staff to conduct fault analysis based on the tracking data and the fault data.
In practical application, the logic association relation between each fault code and the tracking details possibly causing the fault is set in the fault logic association library, and when a certain fault code in the fault details is set corresponding to a bit, log analysis software automatically acquires and processes the associated physical quantity according to the fault association relation set in the association library, and gives out specific reasons and possible solving measures for causing the fault.
It should be noted that under the condition of the telemetry communication bandwidth permission, the fault code can be thinned as much as possible, that is, the flight control software needs to add fault detail setting operation to all corresponding fault logic branches as much as possible, and the log analysis software can give out specific reasons and possible solving measures for causing the fault without configuring a correlation library.
The following example comprises that the fault associated logic is 1) the power supply conversion process starting mark is valid and then the thermal battery activation process completion mark is invalid, and 2) the time from the power supply conversion process starting mark to the thermal battery bus voltage is valid is longer than a given time index, and corresponding fault detail setting operations are respectively added in the effective branches of the 2 fault associated logic, so that the same analysis effect can be realized.
The embodiment of the specification provides an embedded log analysis method and device, wherein the embedded log analysis method comprises the steps of obtaining telemetry data source codes, analyzing and determining telemetry analysis data based on the telemetry data source codes, determining fault identification data based on the telemetry analysis data, wherein the fault identification data comprises fault data and/or tracking data, the fault data is used for identifying fault points, the tracking data is used for scene reproduction, and performing fault analysis based on the fault identification data and a logic association library to obtain fault reasons.
According to the fault data and the tracking data in the scheme, the memory and bandwidth consumption of the log can be reduced in the communication between the rocket and the ground, and the automatic analysis based on the fault data and the tracking data is realized, so that the accuracy and the speed of fault positioning are improved.
In an integral embodiment, flight control software of the rocket transmits ground telemetry data source codes to a ground testing and launching system in a period of 100ms, wherein the rocket comprises A, B, C, D logic branches, and decimal fault codes corresponding to the logic branches are 1,2, 3 and 4 respectively. The fault code in the telemetry data source code received in a certain period is 00000011, and can be resolved into decimal number 3, if the fault code 3 can be found in the fault logic association library, the fault data is 3. The detail of the fault is 00000101, and when the first position 1 from right to left, the fault appears in the A, and when the third position 1 shows that the fault appears in the C. The trace code in the telemetry data source code is 00000011, and can be resolved into decimal number 3, if the fault code 3 can be found in the trace logic association library, the trace data is 3. The tracking detail is 00000111, the first position 1 from right to left indicates that A is executed, the second position 1 indicates that B is executed, and the third position 1 indicates that C is executed.
After the fault data and the tracking data are acquired, fault analysis can be performed, and if the physical quantity corresponding to the C is the relevant physical quantity of power supply conversion, the power supply conversion fault caused by the fault is determined. From the fault details it can also be determined that a has failed. And obtaining the fault reasons and the solving measures corresponding to the A and the C from the fault logic association library.
Further, the trace data is 3, it may be determined that the current logic branch of execution is C, the trace detail is 00000111, the first position 1 from right to left indicates that a has been executed, the second position 1 indicates that B has been executed, and the third position 1 indicates that C has been executed. And judging whether the fault logic association library is consistent with the expected tracking details, if not, acquiring corresponding fault reasons and solving measures from the fault logic association library.
In the above step, if the fault logic association library does not find the corresponding fault code, fault cause or solution, the scene can be reproduced directly through the tracking code and the tracking details, so that the staff can perform fault analysis. Scene reproduction may also be performed directly after the tracking code and tracking details are obtained.
Corresponding to the method embodiment, the present disclosure further provides an embodiment of an embedded log analysis device, and fig. 7 shows a schematic structural diagram of an embedded log analysis device according to one embodiment of the present disclosure. As shown in fig. 7, the apparatus includes:
A data acquisition module 701 configured to acquire telemetry data source codes, parse based on the telemetry data source codes, and determine telemetry parse data;
a data parsing module 702 configured to determine fault identification data based on telemetry parsing data, wherein the fault identification data includes fault data for identifying a fault point and/or trace data for performing scene reproduction;
The fault judging module 703 is configured to perform fault analysis based on the fault identification data and the logic association library to obtain a fault cause.
In one possible implementation, parsing the determined telemetry parse data based on telemetry source code includes:
Determining bit source code data based on the telemetry data source code;
and converting the bit source code data into telemetry analysis data according to a preset conversion rule.
In one possible implementation, determining fault identification data based on telemetry resolution data includes:
extracting a target fault code from telemetry analysis data, wherein the target fault code is a fault code of the current telemetry period;
comparing the target fault code with a fault logic association library to determine a fault comparison result, wherein the fault logic association library comprises at least two fault codes and logic association relations between the at least two fault codes and the telemetering physical quantity;
And under the condition that the fault comparison result is the target fault code in the fault logic association inventory, taking the target fault code as fault data.
In one possible implementation, determining fault identification data based on telemetry resolution data includes:
extracting a target tracking code from telemetry analysis data, wherein the target tracking code is the tracking code of the current telemetry period;
Comparing the target tracking code with a tracking logic association library to determine a tracking comparison result, wherein the tracking logic association library comprises at least two tracking codes and a logic association relationship between the at least two tracking codes and the telemetering physical quantity;
And under the condition that the tracking comparison result is that the target tracking code exists in the tracking logic association library, taking the target tracking code as tracking data.
In one possible implementation, performing fault analysis based on the fault identification data and the logical association library includes:
extracting fault details from the telemetry resolution data in the event that the fault identification data includes fault data;
Acquiring corresponding first telemetering physical quantities from a fault logic association library based on fault data and fault details;
and carrying out fault analysis based on the first telemetering physical quantity, and determining the fault reason.
In one possible implementation, performing fault analysis based on the fault identification data and the logical association library includes:
In the case that the fault identification data comprises trace data, or in the case that the fault identification data comprises trace data and the fault analysis is performed based on the first telemetering physical quantity, and the cause of the fault is not determined, extracting trace details from the telemetering analysis data;
generating history tracking details based on the second telemetry physical quantity;
the cause of the fault is determined based on the historical tracking details and the expected tracking details.
In one possible implementation, the method further includes:
After determining the fault cause, obtaining a solution measure from the logic association library based on the fault cause, and displaying the solution measure;
And under the condition that the fault cause is not determined, the tracking data and the fault data are displayed so that the staff can conduct fault analysis based on the tracking data and the fault data.
The embodiment of the specification provides an embedded log analysis method and device, wherein the embedded log analysis device comprises the steps of obtaining telemetry data source codes, analyzing and determining telemetry analysis data based on the telemetry data source codes, determining fault identification data based on the telemetry analysis data, wherein the fault identification data comprises fault data and/or tracking data, the fault data is used for identifying fault points, the tracking data is used for scene reproduction, and performing fault analysis based on the fault identification data and a logic association library to obtain fault reasons. According to the fault data and the tracking data in the scheme, the memory and bandwidth consumption of the log can be reduced in the communication between the rocket and the ground, and the automatic analysis based on the fault data and the tracking data is realized, so that the accuracy and the speed of fault positioning are improved.
The above is a schematic scheme of an embedded log analysis device of the present embodiment. It should be noted that, the technical solution of the embedded log analysis device and the technical solution of the embedded log analysis method belong to the same concept, and details of the technical solution of the embedded log analysis device, which are not described in detail, can be referred to the description of the technical solution of the embedded log analysis method.
Fig. 8 illustrates a block diagram of a computing device 800 provided in accordance with one embodiment of the present description. The components of computing device 800 include, but are not limited to, memory 810 and processor 820. Processor 820 is coupled to memory 810 through bus 830 and database 850 is used to hold data.
Computing device 800 also includes access device 840, access device 840 enabling computing device 800 to communicate via one or more networks 860. Examples of such networks include public switched telephone networks (PSTN, public Switched Telephone Network), local area networks (LAN, local Area Network), wide area networks (WAN, wide Area Network), personal area networks (PAN, personal Area Network), or combinations of communication networks such as the internet. The access device 840 may include one or more of any type of network interface, wired or wireless, such as a network interface card (NIC, network interface controller), such as an IEEE802.11 wireless local area network (WLAN, wireless Local Area Network) wireless interface, a worldwide interoperability for microwave access (Wi-MAX, worldwide Interoperability for Microwave Access) interface, an ethernet interface, a universal serial bus (USB, universal Serial Bus) interface, a cellular network interface, a bluetooth interface, near Field Communication (NFC).
In one embodiment of the present description, the above-described components of computing device 800, as well as other components not shown in FIG. 8, may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device illustrated in FIG. 8 is for exemplary purposes only and is not intended to limit the scope of the present description. Those skilled in the art may add or replace other components as desired.
Computing device 800 may be any type of stationary or mobile computing device including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smart phone), wearable computing device (e.g., smart watch, smart glasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or personal computer (PC, personal Computer). Computing device 800 may also be a mobile or stationary server.
Wherein the processor 820 is configured to execute computer-executable instructions that, when executed by the processor, perform the steps of the embedded log analysis method described above. The foregoing is a schematic illustration of a computing device of this embodiment. It should be noted that, the technical solution of the computing device and the technical solution of the above-mentioned embedded log analysis method belong to the same concept, and details of the technical solution of the computing device, which are not described in detail, can be referred to the description of the technical solution of the above-mentioned embedded log analysis method.
An embodiment of the present disclosure also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described embedded log analysis method.
The above is an exemplary version of a computer-readable storage medium of the present embodiment. It should be noted that, the technical solution of the storage medium and the technical solution of the above-mentioned embedded log analysis method belong to the same concept, and details of the technical solution of the storage medium which are not described in detail can be referred to the description of the technical solution of the above-mentioned embedded log analysis method.
An embodiment of the present disclosure further provides a computer program, where the computer program, when executed in a computer, causes the computer to perform the steps of the above-described embedded log analysis method.
The above is an exemplary version of a computer program of the present embodiment. It should be noted that, the technical solution of the computer program and the technical solution of the embedded log analysis method belong to the same concept, and details of the technical solution of the computer program, which are not described in detail, can be referred to the description of the technical solution of the embedded log analysis method.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The computer instructions include computer program code that may be in source code form, object code form, executable file or some intermediate form, etc. The computer readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of combinations of actions, but it should be understood by those skilled in the art that the embodiments are not limited by the order of actions described, as some steps may be performed in other order or simultaneously according to the embodiments of the present disclosure. Further, those skilled in the art will appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily all required for the embodiments described in the specification.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments.
The preferred embodiments of the present specification disclosed above are merely used to help clarify the present specification. Alternative embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the teaching of the embodiments. The embodiments were chosen and described in order to best explain the principles of the embodiments and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. This specification is to be limited only by the claims and the full scope and equivalents thereof.
Claims (10)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202510354871.1A CN120178844A (en) | 2025-03-24 | 2025-03-24 | Embedded log analysis method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202510354871.1A CN120178844A (en) | 2025-03-24 | 2025-03-24 | Embedded log analysis method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN120178844A true CN120178844A (en) | 2025-06-20 |
Family
ID=96033267
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202510354871.1A Pending CN120178844A (en) | 2025-03-24 | 2025-03-24 | Embedded log analysis method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN120178844A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070129009A1 (en) * | 2005-12-01 | 2007-06-07 | Electronics And Telecommunications Research Institute | Fault management system using satellite telemetering technology and method thereof |
| CN104360939A (en) * | 2014-10-29 | 2015-02-18 | 中国建设银行股份有限公司 | Method, equipment and system for positioning fault |
| US20170147472A1 (en) * | 2015-11-19 | 2017-05-25 | Honeywell International Inc. | Systems and methods for a real time embedded trace |
| CN110789568A (en) * | 2019-10-09 | 2020-02-14 | 北京全路通信信号研究设计院集团有限公司 | Fault diagnosis method and system based on train operation scene |
| CN118796699A (en) * | 2024-07-24 | 2024-10-18 | 卡斯柯信号(成都)有限公司 | A scene reproduction method, device and storage medium based on fault log |
-
2025
- 2025-03-24 CN CN202510354871.1A patent/CN120178844A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070129009A1 (en) * | 2005-12-01 | 2007-06-07 | Electronics And Telecommunications Research Institute | Fault management system using satellite telemetering technology and method thereof |
| CN104360939A (en) * | 2014-10-29 | 2015-02-18 | 中国建设银行股份有限公司 | Method, equipment and system for positioning fault |
| US20170147472A1 (en) * | 2015-11-19 | 2017-05-25 | Honeywell International Inc. | Systems and methods for a real time embedded trace |
| CN110789568A (en) * | 2019-10-09 | 2020-02-14 | 北京全路通信信号研究设计院集团有限公司 | Fault diagnosis method and system based on train operation scene |
| CN118796699A (en) * | 2024-07-24 | 2024-10-18 | 卡斯柯信号(成都)有限公司 | A scene reproduction method, device and storage medium based on fault log |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113778864B (en) | A test case generation method and device, electronic device and storage medium | |
| CN111475324B (en) | Log information analysis method, device, computer equipment and storage medium | |
| CN111259212B (en) | Telemetering data interpretation method, device, equipment and storage medium | |
| CN109324789A (en) | A software development method | |
| CN119336609B (en) | Automatic generation method of software configuration item test cases based on large language model | |
| CN114036074A (en) | Test method and test device for terminal equipment | |
| CN113704099A (en) | Test script generation method and equipment for spacecraft power system evaluation | |
| CN118362862A (en) | Fault detection and positioning method, medium and system based on chip system test | |
| CN112783513A (en) | Code risk checking method, device and equipment | |
| CN118885162B (en) | Front-end and back-end code generation and deployment system based on text AI model | |
| CN118660312B (en) | Automatic test method and device suitable for wireless test of data link system | |
| US12367429B2 (en) | Method and device for optimizing deep learning model conversion, and storage medium | |
| CN115184674A (en) | Insulation test method and device, electronic terminal and storage medium | |
| CN119271545A (en) | Code evaluation and conversion method, system and medium applied to heterogeneous multi-core chips | |
| CN119089354A (en) | Beidou positioning information processing method and system based on artificial intelligence | |
| CN120178844A (en) | Embedded log analysis method and device | |
| CN119052109A (en) | Network quality difference analysis method and device, storage medium and electronic equipment | |
| CN119166511A (en) | Test case generation method and device | |
| CN117009223A (en) | Software testing method, system, storage medium and terminal based on abstract grammar | |
| CN114510818B (en) | Method and device for simulating and verifying test cases for spacecraft test identification | |
| CN117009218A (en) | Multi-interface system testing method, device, system and storage medium | |
| CN113342632A (en) | Simulation data automatic processing method and device, electronic equipment and storage medium | |
| CN119473253B (en) | Method and device for generating testability design script, electronic equipment and storage medium | |
| CN120407024B (en) | Verification method and device for instruction sequence, electronic equipment and storage medium | |
| CN117970070B (en) | Boolean satisfaction-based compression method and device for automatic circuit test vector |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |