CN113886202A - Vehicle log analysis method, system, device, medium and vehicle - Google Patents

Vehicle log analysis method, system, device, medium and vehicle Download PDF

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CN113886202A
CN113886202A CN202111150601.7A CN202111150601A CN113886202A CN 113886202 A CN113886202 A CN 113886202A CN 202111150601 A CN202111150601 A CN 202111150601A CN 113886202 A CN113886202 A CN 113886202A
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vehicle
log
state
condition
expected
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陈崇峰
闵祥伟
程志强
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Weilai Automobile Technology Anhui Co Ltd
NIO Technology Anhui Co Ltd
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Weilai Automobile Technology Anhui Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3466—Performance evaluation by tracing or monitoring
    • G06F11/3476—Data logging
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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    • G06F16/17—Details of further file system functions
    • G06F16/1734—Details of monitoring file system events, e.g. by the use of hooks, filter drivers, logs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
    • G06F16/367—Ontology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/448—Execution paradigms, e.g. implementations of programming paradigms
    • G06F9/4498—Finite state machines

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Abstract

The invention relates to the technical field of vehicle control, in particular to a vehicle log analysis method, a system, a device, a medium and a vehicle, and aims to solve the problems of high requirement on professional knowledge and low efficiency in the existing vehicle log analysis process. For this purpose, the invention creates a corresponding finite-state machine model according to different vehicle state analysis services so as to analyze the vehicle log, judge whether the vehicle is in the vehicle state corresponding to the vehicle state analysis services, and output a log line indicating that the vehicle is in the vehicle state, thereby avoiding the process of manually confirming the vehicle log when the vehicle is in fault or the vehicle state needs to be confirmed, simultaneously reducing the requirement on professional knowledge in the process of analyzing the vehicle log, and enabling the analysis process of the vehicle log to be more accurate and efficient.

Description

Vehicle log analysis method, system, device, medium and vehicle
Technical Field
The invention relates to the technical field of vehicle control, and particularly provides a method, a system, a device, a medium and a vehicle for analyzing a vehicle log.
Background
The log is data generated by a vehicle-mounted software system, mainly records the running state of the vehicle and detailed information of the work of each module of the vehicle, and is an important basis in the processes of maintaining, troubleshooting and monitoring the running safety of the vehicle. For an intelligent automobile, the real situation of the automobile needs to be concerned in time through analysis of a vehicle-mounted log. In practical applications, in the processes of vehicle maintenance, troubleshooting and safety monitoring, multiple types of logs of multiple modules are often required to be comprehensively analyzed, and then a conclusion can be obtained. In the process of comprehensive analysis, the logs are often manually reviewed to determine faults or vehicle states, which requires a technician to have a good understanding of the condition of the vehicle logs of the various modules of the vehicle. Meanwhile, the manual log checking process cannot be automated, and the overall efficiency is low. In addition, the analysis of the vehicle log has high requirements on technicians, so that many problems cannot be solved effectively in the prior period, and the problems need to be fed back to manufacturers for solving, thereby further reducing the efficiency of the vehicle log analysis.
Accordingly, there is a need in the art for a new analysis scheme for vehicle logs to address the above-mentioned problems.
Disclosure of Invention
The invention aims to solve the technical problems, namely, the problems of high requirement on professional knowledge and low efficiency in the conventional vehicle log analysis process are solved.
In a first aspect, the present invention provides a method of analyzing a vehicle log, the method comprising:
for each vehicle state analysis service, determining a log keyword of a vehicle log related to the vehicle state analysis service and a transition condition between different log keywords, and creating a finite state machine model of the vehicle state analysis service by taking the log keyword as a state and the transition condition as a state transition event;
collecting an actual vehicle log related to a vehicle state analysis service, and analyzing the actual vehicle log by using a finite state machine model of the vehicle state analysis service;
judging whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to an analysis result; and if so, outputting a log row which indicates that the vehicle is in the vehicle state in the actual vehicle log.
In one aspect of the above method for analyzing a vehicle log, the step of analyzing the actual vehicle log using a finite state machine model of the vehicle state analysis service includes:
according to the log keywords of the vehicle log related to the vehicle state analysis service, extracting keywords from the actual vehicle log to obtain a log row containing the log keywords in the actual vehicle log;
analyzing the log line by using the finite state machine model.
In one aspect of the above method for analyzing a vehicle log, the step of "analyzing the log using the finite state machine model" includes:
analyzing the finite-state machine model to obtain a directed cyclic graph with the state as a node and the state transition event as a directed edge;
acquiring an expected condition set and an unexpected condition set of the directed cyclic graph;
analyzing the log line according to the expected condition set and the unexpected condition set;
wherein the set of expected conditions includes at least one expected condition, the expected condition being a condition determined from a state transition event that enables a state transition between adjacent states; the set of unexpected conditions includes at least one unexpected condition that is a condition determined from a state transition event that a state transition between adjacent states cannot be achieved.
In an embodiment of the method for analyzing the vehicle log, the method further includes sequentially analyzing each log line according to the sequence of the log line time from first to last and according to the expected condition set and the unexpected condition set by the following steps:
step S1: acquiring a first state of the directed cyclic graph, and taking the first state as a current state;
step S2: carrying out condition matching on the current log line and expected conditions and unexpected conditions corresponding to the current state in the expected condition set and the unexpected condition set respectively; if the current log line is successfully matched with the expected condition, go to step S3; if the current log line is successfully matched with the unexpected condition, recording matching error information according to the current log line and then transferring to the step S4;
step S3: performing state transition query on the directed cyclic graph according to the expected conditions; if the next state transferred from the current state is inquired, taking the next state as a new current state and transferring to the step S4; if the next state transferred from the current state is not inquired, matching error information according to the current log line record and then transferring to the step S4;
step S4: and re-acquiring the expected condition set and the unexpected condition set, reading in the next log line, and turning to the step S2 after the next log line is taken as a new current log line.
In one technical solution of the above method for analyzing a vehicle log, "judging whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to an analysis result; if yes, the step of outputting a log line indicating that the vehicle is in the vehicle state in the actual vehicle log "includes:
and judging whether each expected condition has a log line which is successfully matched or not according to the analysis result, if so, judging that the vehicle is in a vehicle state corresponding to the vehicle state analysis service, and outputting the log line.
In a second aspect, the present invention provides an analysis system for vehicle logs, the analysis system comprising:
a finite state machine creating module configured to determine, for each vehicle state analysis service, a log keyword of a vehicle log related to the vehicle state analysis service and a transition condition between different log keywords, and create a finite state machine model of the vehicle state analysis service with the log keyword as a state and the transition condition as a state transition event;
a vehicle log analysis module configured to collect an actual vehicle log related to a vehicle state analysis service, the actual vehicle log being analyzed using a finite state machine model of the vehicle state analysis service;
a vehicle state judging module configured to judge whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to an analysis result; and if so, outputting a log row which indicates that the vehicle is in the vehicle state in the actual vehicle log.
In an aspect of the above system for analyzing a vehicle log, the vehicle log analyzing module includes:
a vehicle log extraction unit configured to perform keyword extraction on the actual vehicle log according to a log keyword of the vehicle log related to the vehicle state analysis service, and acquire a log row including the log keyword in the actual vehicle log;
a vehicle log analysis unit configured to analyze the log line using the finite state machine model.
In one aspect of the above vehicle log analysis system, the vehicle log analysis unit includes:
a directed cyclic graph obtaining subunit configured to analyze the finite state machine model, and obtain a directed cyclic graph with the state as a node and the state transition event as a directed edge;
an expected and unexpected condition set acquisition subunit configured to acquire an expected condition set and an unexpected condition set of the directed cyclic graph;
a log line analysis subunit configured to analyze the log line according to the expected and unexpected condition sets;
wherein the set of expected conditions includes at least one expected condition, the expected condition being a condition determined from a state transition event that enables a state transition between adjacent states; the set of unexpected conditions includes at least one unexpected condition that is a condition determined from a state transition event that a state transition between adjacent states cannot be achieved.
In an embodiment of the above system for analyzing vehicle logs, the system is further configured to sequentially analyze each log line according to the expected condition set and the unexpected condition set in the order from the first to the last of the log line time by the following steps:
step S1: acquiring a first state of the directed cyclic graph, and taking the first state as a current state;
step S2: carrying out condition matching on the current log line and expected conditions and unexpected conditions corresponding to the current state in the expected condition set and the unexpected condition set respectively; if the current log line is successfully matched with the expected condition, go to step S3; if the current log line is successfully matched with the unexpected condition, recording matching error information according to the current log line and then transferring to the step S4;
step S3: performing state transition query on the directed cyclic graph according to the expected conditions; if the next state transferred from the current state is inquired, taking the next state as a new current state and transferring to the step S4; if the next state transferred from the current state is not inquired, matching error information according to the current log line record and then transferring to the step S4;
step S4: and re-acquiring the expected condition set and the unexpected condition set, reading in the next log line, and turning to the step S2 after the next log line is taken as a new current log line.
In an aspect of the above system for analyzing a vehicle log, the vehicle state determination module is further configured to determine whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to the following steps:
and judging whether each expected condition has a log line which is successfully matched or not according to the analysis result, if so, judging that the vehicle is in a vehicle state corresponding to the vehicle state analysis service, and outputting the log line.
In a third aspect, there is provided a control device comprising a processor and a storage device adapted to store a plurality of program codes adapted to be loaded and run by the processor to perform the method of analyzing a vehicle log according to any one of the above-described methods of analyzing a vehicle log.
In a fourth aspect, there is provided a computer readable storage medium having stored therein a plurality of program codes adapted to be loaded and executed by a processor to perform the method of analyzing a vehicle log according to any one of the above-described methods of analyzing a vehicle log.
In a fifth aspect, a vehicle is provided, which includes the vehicle log analysis system according to any one of the above-described vehicle log analysis systems.
Under the condition of adopting the technical scheme, the invention can create a finite state machine model for vehicle state analysis according to the log keywords of the vehicle log related to the vehicle state analysis service and the transfer conditions among different log keywords, analyze the actual vehicle log by applying the finite state machine model, judge whether the vehicle is in the vehicle state corresponding to the vehicle state analysis service according to the analysis result, and output the log indicating that the vehicle is in the vehicle state if the log is in the vehicle state. Through the configuration mode, the corresponding finite-state machine model can be created according to different vehicle state analysis services, so that the vehicle log can be analyzed, whether the vehicle is in the vehicle state corresponding to the vehicle state analysis services or not is judged, the log line indicating that the vehicle is in the vehicle state is output, the process of manually confirming the vehicle log when the vehicle breaks down or the vehicle state needs to be confirmed is avoided, meanwhile, the requirement on professional knowledge in the process of analyzing the vehicle log is reduced, and the analysis process of the vehicle log is more accurate and efficient.
The method for analyzing the vehicle log is characterized by comprising the following steps:
for each vehicle state analysis service, determining a log keyword of a vehicle log related to the vehicle state analysis service and a transition condition between different log keywords, and creating a finite state machine model of the vehicle state analysis service by taking the log keyword as a state and the transition condition as a state transition event;
collecting an actual vehicle log related to a vehicle state analysis service, and analyzing the actual vehicle log by using a finite state machine model of the vehicle state analysis service;
judging whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to an analysis result; and if so, outputting a log row which indicates that the vehicle is in the vehicle state in the actual vehicle log.
The analysis method according to claim 1, wherein the step of analyzing the actual vehicle log using a finite state machine model of the vehicle state analysis service includes:
according to the log keywords of the vehicle log related to the vehicle state analysis service, extracting keywords from the actual vehicle log to obtain a log row containing the log keywords in the actual vehicle log;
analyzing the log line by using the finite state machine model.
The analysis method according to claim 2, wherein the step of analyzing the log line using the finite state machine model includes:
analyzing the finite-state machine model to obtain a directed cyclic graph with the state as a node and the state transition event as a directed edge;
acquiring an expected condition set and an unexpected condition set of the directed cyclic graph;
analyzing the log line according to the expected condition set and the unexpected condition set;
wherein the set of expected conditions includes at least one expected condition, the expected condition being a condition determined from a state transition event that enables a state transition between adjacent states; the set of unexpected conditions includes at least one unexpected condition that is a condition determined from a state transition event that a state transition between adjacent states cannot be achieved.
Scheme 4. the analysis method according to scheme 3, wherein the method further comprises analyzing each log line sequentially according to the expected condition set and the unexpected condition set in the order of log line time from first to last by:
step S1: acquiring a first state of the directed cyclic graph, and taking the first state as a current state;
step S2: carrying out condition matching on the current log line and expected conditions and unexpected conditions corresponding to the current state in the expected condition set and the unexpected condition set respectively; if the current log line is successfully matched with the expected condition, go to step S3; if the current log line is successfully matched with the unexpected condition, recording matching error information according to the current log line and then transferring to the step S4;
step S3: performing state transition query on the directed cyclic graph according to the expected conditions; if the next state transferred from the current state is inquired, taking the next state as a new current state and transferring to the step S4; if the next state transferred from the current state is not inquired, matching error information according to the current log line record and then transferring to the step S4;
step S4: and re-acquiring the expected condition set and the unexpected condition set, reading in the next log line, and turning to the step S2 after the next log line is taken as a new current log line.
Scheme 5. the analysis method according to scheme 4, characterized by that, judge whether the said vehicle is in the vehicle state that the said vehicle state analyzes the business corresponds to according to the result of analysis; if yes, the step of outputting a log line indicating that the vehicle is in the vehicle state in the actual vehicle log "includes:
and judging whether each expected condition has a log line which is successfully matched or not according to the analysis result, if so, judging that the vehicle is in a vehicle state corresponding to the vehicle state analysis service, and outputting the log line.
Scheme 6. an analysis system of vehicle logs, characterized in that the analysis system comprises:
a finite state machine creating module configured to determine, for each vehicle state analysis service, a log keyword of a vehicle log related to the vehicle state analysis service and a transition condition between different log keywords, and create a finite state machine model of the vehicle state analysis service with the log keyword as a state and the transition condition as a state transition event;
a vehicle log analysis module configured to collect an actual vehicle log related to a vehicle state analysis service, the actual vehicle log being analyzed using a finite state machine model of the vehicle state analysis service;
a vehicle state judging module configured to judge whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to an analysis result; and if so, outputting a log row which indicates that the vehicle is in the vehicle state in the actual vehicle log.
The analysis system of claim 6, wherein the vehicle log analysis module comprises:
a vehicle log extraction unit configured to perform keyword extraction on the actual vehicle log according to a log keyword of the vehicle log related to the vehicle state analysis service, and acquire a log row including the log keyword in the actual vehicle log;
a vehicle log analysis unit configured to analyze the log line using the finite state machine model.
The analysis system according to claim 7, characterized in that the vehicle log analysis unit includes:
a directed cyclic graph obtaining subunit configured to analyze the finite state machine model, and obtain a directed cyclic graph with the state as a node and the state transition event as a directed edge;
an expected and unexpected condition set acquisition subunit configured to acquire an expected condition set and an unexpected condition set of the directed cyclic graph;
a log line analysis subunit configured to analyze the log line according to the expected and unexpected condition sets;
wherein the set of expected conditions includes at least one expected condition, the expected condition being a condition determined from a state transition event that enables a state transition between adjacent states; the set of unexpected conditions includes at least one unexpected condition that is a condition determined from a state transition event that a state transition between adjacent states cannot be achieved.
Scheme 9. the analysis system of claim 8, wherein the system is further configured to analyze each log line in turn, in order of log line time from first to last, according to the expected and unexpected condition sets and by:
step S1: acquiring a first state of the directed cyclic graph, and taking the first state as a current state;
step S2: carrying out condition matching on the current log line and expected conditions and unexpected conditions corresponding to the current state in the expected condition set and the unexpected condition set respectively; if the current log line is successfully matched with the expected condition, go to step S3; if the current log line is successfully matched with the unexpected condition, recording matching error information according to the current log line and then transferring to the step S4;
step S3: performing state transition query on the directed cyclic graph according to the expected conditions; if the next state transferred from the current state is inquired, taking the next state as a new current state and transferring to the step S4; if the next state transferred from the current state is not inquired, matching error information according to the current log line record and then transferring to the step S4;
step S4: and re-acquiring the expected condition set and the unexpected condition set, reading in the next log line, and turning to the step S2 after the next log line is taken as a new current log line.
The analysis system of claim 10, wherein the vehicle state determination module is further configured to determine whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to the following steps:
and judging whether each expected condition has a log line which is successfully matched or not according to the analysis result, if so, judging that the vehicle is in a vehicle state corresponding to the vehicle state analysis service, and outputting the log line.
Scheme 11 a control device comprising a processor and a storage means adapted to store a plurality of program codes, characterized in that said program codes are adapted to be loaded and run by said processor to perform the method of analysis of a vehicle log according to any of the schemes 1 to 5.
An aspect 12, a computer-readable storage medium having a plurality of program codes stored therein, wherein the program codes are adapted to be loaded and executed by a processor to perform the method of analyzing a vehicle log according to any one of aspects 1 to 5.
Solution 13, a vehicle characterized in that it comprises the system for analyzing a vehicle log according to any one of solutions 6 to 10.
Drawings
The disclosure of the present invention will become more readily understood with reference to the accompanying drawings. As is readily understood by those skilled in the art: these drawings are for illustrative purposes only and are not intended to constitute a limitation on the scope of the present invention. Wherein:
FIG. 1 is a flow chart illustrating the main steps of a method for analyzing a vehicle log according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of the main steps of sequentially analyzing the log rows of each vehicle log according to the expected condition set and the unexpected condition set according to one implementation of an embodiment of the invention;
FIG. 3 is a block diagram of the main structure of a vehicle log analysis system according to an embodiment of the present invention;
fig. 4 is a schematic flow chart illustrating the process of pushing and popping the status when the log line of each vehicle log is analyzed in turn according to the expected condition set and the unexpected condition set according to one implementation manner of the embodiment of the invention.
Detailed Description
Some embodiments of the invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and are not intended to limit the scope of the present invention.
In the description of the present invention, a "module" or "processor" may include hardware, software, or a combination of both. A module may comprise hardware circuitry, various suitable sensors, communication ports, memory, may comprise software components such as program code, or may be a combination of software and hardware. The processor may be a central processing unit, a microprocessor, a digital signal processor, or any other suitable processor. The processor has data and/or signal processing functionality. The processor may be implemented in software, hardware, or a combination thereof. Non-transitory computer readable storage media include any suitable medium that can store program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random-access memory, and the like. The term "a and/or B" denotes all possible combinations of a and B, such as a alone, B alone or a and B. The term "at least one A or B" or "at least one of A and B" means similar to "A and/or B" and may include only A, only B, or both A and B. The singular forms "a", "an" and "the" may include the plural forms as well.
In the processes of vehicle maintenance, troubleshooting and safety monitoring, it is often necessary to comprehensively analyze multiple types of vehicle logs of multiple modules to obtain a conclusion. In the prior art, the fault or the vehicle state is often determined by manually checking the vehicle log, which requires a technician to know the condition of the vehicle log of each module of the vehicle. Meanwhile, the process of manually checking the vehicle log cannot be automated, and the overall efficiency is low. In addition, the analysis of the vehicle log has high requirements on technicians, so that many problems cannot be solved effectively in the prior period, and the problems need to be fed back to manufacturers for solving, thereby further reducing the efficiency of the vehicle log analysis.
The invention provides a method, a system, a device, a medium and a vehicle for analyzing a vehicle log, which solve the problems.
Referring to fig. 1, fig. 1 is a flow chart illustrating main steps of a method for analyzing a vehicle log according to an embodiment of the present invention. As shown in fig. 1, the method for analyzing the vehicle log in the embodiment of the present invention mainly includes the following steps S101 to S103.
Step S101: and for each vehicle state analysis service, determining a log keyword of a vehicle log related to the vehicle state analysis service and a transition condition between different log keywords, and creating a finite-state machine model of the vehicle state analysis service by taking the log keyword as a state and taking the transition condition as a state transition event. A finite state machine model is a tool used for modeling the behavior of an object, and can describe the state sequence of the object in the life cycle and how to respond to various events from the outside, and generally comprises states and state transition events. The vehicle state analysis service may include daily maintenance of the vehicle as a whole, daily maintenance of functional modules of the vehicle, vehicle troubleshooting, vehicle operation safety monitoring, vehicle function analysis, and the like.
In the present embodiment, a log key of a vehicle log related to the vehicle state analysis service and a transition condition between different keys may be determined according to each vehicle state analysis service, and the log key may be set to a state of a finite state machine model, and the transition condition may be set to a state transition event of the finite state machine model to construct a finite state machine model of the different vehicle state analysis services. In addition, in this embodiment, the log key may further include a component name, a module name, and the like. The module refers to a set of components which can independently execute certain functions after multiplexing the components. The name of a module is the name of a certain module in an Electronic Control Unit (ECU), and the name of a component is the name of a certain component in the ECU. The software function in the ECU can be realized by a plurality of modules, the log line of the software includes the component name and the module name to which the log belongs, the component name or the module name can be used as the log keyword to extract the actual vehicle log, and the actual vehicle log extracted by using the component name or the module name as the log keyword is the vehicle log related to a certain function of the vehicle corresponding to the component name or the module name. When a certain function of the vehicle corresponding to the component name or the module name needs to be analyzed, the component name or the module name can be used as a log keyword of a vehicle log related to the vehicle state analysis service. The transfer condition between different log keywords refers to a determination condition for transferring from one log keyword to a next log keyword associated with the log keyword, for example, one log keyword is an error code, the next log keyword is a module name, and the determination condition may be whether the error code matches the module name.
Step S102: and collecting the actual vehicle log related to the vehicle state analysis service, and analyzing the actual vehicle log by using a finite state machine model of the vehicle state analysis service.
In this embodiment, an actual vehicle log related to the vehicle state analysis service may be collected, and a finite state machine model of the vehicle state analysis service created in step S101 may be acquired, and the actual vehicle log may be analyzed by using the finite state machine model.
Step S103: judging whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to the analysis result; if yes, outputting a log line in the actual vehicle log, wherein the log line indicates that the vehicle is in the vehicle state.
In this embodiment, whether the vehicle is in the vehicle state corresponding to the vehicle state analysis service may be determined according to an analysis result obtained by analyzing the actual vehicle log in step S102; if yes, outputting a log line of a vehicle log indicating that the vehicle is in the vehicle state in the actual vehicle log.
Based on the above steps S101 to S103, the present invention can create a finite state machine model for vehicle state analysis according to the log keywords of the vehicle log related to the vehicle state analysis service and the transition conditions between different log keywords, analyze the actual vehicle log by using the finite state machine model, determine whether the vehicle is in the vehicle state corresponding to the vehicle state analysis service according to the analysis result, and if so, output the log indicating that the vehicle is in the vehicle state. Through the configuration mode, the corresponding finite-state machine model can be created according to different vehicle state analysis services, so that the vehicle log can be analyzed, whether the vehicle is in the vehicle state corresponding to the vehicle state analysis services or not is judged, the log line indicating that the vehicle is in the vehicle state is output, the process of manually confirming the vehicle log when the vehicle breaks down or the vehicle state needs to be confirmed is avoided, meanwhile, the requirement on professional knowledge in the process of analyzing the vehicle log is reduced, and the analysis process of the vehicle log is more accurate and efficient.
Step S102 and step S103 will be further described below.
In one implementation manner of the embodiment of the present invention, step S102 further includes:
step S1021: and extracting keywords from the actual vehicle log according to the log keywords of the vehicle log related to the vehicle state analysis service, and acquiring a log row containing the log keywords in the actual vehicle log.
In this embodiment, the key extraction may be performed on the actual vehicle log according to the log key of the vehicle log related to the vehicle state analysis service, so as to obtain the log line including the log key in the actual vehicle log.
In one embodiment, the actual vehicle log may be a system log of on-board software, a vehicle ECU (Electronic Control Unit) log, a log of a vehicle application, a vehicle alarm log, and the like. The actual vehicle logs from different sources can be classified, the larger actual vehicle logs can be segmented, and the actual vehicle logs can be processed, so that the actual vehicle logs have a uniform format. Furthermore, after the log lines of the actual vehicle logs containing the log keywords are obtained, the log lines can be labeled so as to improve the analysis speed of the subsequent vehicle logs.
Step S1022: the log line was analyzed using a finite state machine model.
In the present embodiment, the log line including the log keyword acquired in step S1021 may be analyzed using a finite state machine model.
In one embodiment, the finite state machine model may analyze one vehicle log of a system log of on-board software, a vehicle ECU log, a log of a vehicle application program, and a vehicle alarm log, or may simultaneously analyze a plurality of vehicle logs. That is, the vehicle logs in a single file may be analyzed, or the vehicle logs of the same component in different modules in the same ECU, the same component or module of different ECUs, the same component in different modules in different ECUs, and the like may be analyzed. That is, vehicle logs of the same component in different modules in the same ECU, the same component or module in different ECUs, the same component in different modules in different ECUs, and the like may be extracted according to the log keyword, and the extracted log may be further analyzed using a finite state machine model.
In one implementation manner of the embodiment of the present invention, step S1022 further includes:
step S10221: analyzing the finite-state machine model to obtain a directed cyclic graph with states as nodes and state transition events as directed edges;
step S10222: acquiring an expected condition set and an unexpected condition set of the directed cyclic graph;
step S10223: analyzing the log line according to the expected condition set and the unexpected condition set;
wherein the set of expected conditions includes at least one expected condition, the expected condition being a condition determined from the state transition event that enables a state transition between adjacent states; the set of unexpected conditions includes at least one unexpected condition that is a condition determined from the state transition event that a state transition between adjacent states cannot be achieved. For example: if the state transition event is whether the error code and the module code match successfully, the expected condition may be that the error code and the module code match successfully, and the unexpected condition may be that the error code and the module code do not match successfully.
In this embodiment, the finite-state machine model created in step S101 may be analyzed to obtain a directed cyclic graph with the state of the finite-state machine model as a node and the state transition event of the finite-state machine as a directed edge, where the directed cyclic graph is composed of a group of nodes and a group of directed edges, and each directed edge connects an ordered pair of nodes. A set of expected conditions and a set of unexpected conditions can be obtained from the directed cyclic graph, wherein the set of expected conditions can include at least one expected condition that is a condition determined from a state transition event that enables a state transition between adjacent states; the set of unexpected conditions can include at least one unexpected condition that is a condition determined from a state transition event that fails to effect a state transition between adjacent states. The log lines extracted in step S1021 may be further analyzed according to the expected condition set and the unexpected condition set.
Referring to FIG. 2, FIG. 2 is a flow chart illustrating the main steps of sequentially analyzing the log lines of each vehicle log according to the expected condition set and the unexpected condition set according to one implementation of an embodiment of the present invention. As shown in fig. 2, in one embodiment, each log line may be analyzed in turn according to the expected condition set and the unexpected condition set in the order of the log line time from first to last through the following steps S201 to S208:
step S201: and acquiring a first state of the directed cyclic graph, and taking the first state as the current state.
Step S202: and carrying out condition matching on the current log line and the expected conditions and the unexpected conditions corresponding to the current state in the expected condition set and the unexpected condition set respectively.
In this embodiment, the current log line may be matched with the expected conditions and the unexpected conditions corresponding to the current state in the expected condition set and the unexpected condition set, respectively.
Step S203: and judging whether the current log line is successfully matched with the expected condition or is successfully matched with the unexpected condition. If the current log line is successfully matched with the expected conditions, jumping to the step S204; if the current log line is successfully matched with the unexpected condition, the process goes to step S208.
In this embodiment, it can be determined whether the current log line is successfully matched with the expected condition or successfully matched with the unexpected condition in step S202, and if the current log line is successfully matched with the expected condition, the process jumps to step S204; if the current log line is successfully matched with the unexpected condition, the process goes to step S208.
Step S204: and performing state transition query on the directed cyclic graph according to expected conditions.
In this embodiment, the state transition query may be performed on the directed cyclic graph according to expected conditions.
Step S205: whether the next state of transition from the current state is inquired is judged. If yes, go to step S206; if not, go to step S208.
In this embodiment, it may be determined whether a state query is performed on the directed cyclic graph in step S204 and whether a state next to a transition of the state of the directed cyclic graph from the current state is queried. If yes, namely, the current state is not the last state of the directed cyclic graph, the step S206 is skipped; if not, it indicates that the current state is the last state of the directed cyclic graph, then go to step S208.
Step S206: the next state is taken as the new current state, and then the process goes to step S207.
In this embodiment, the next state queried in step S204 may be set as the new current state.
Step S207: and (4) acquiring the expected condition set and the unexpected condition set again, reading in the next log line, and jumping to the step S202 after taking the next log line as a new current log line.
In this embodiment, the expected condition set and the unexpected condition set may be obtained again, and after the next log line is read in, the process jumps to step S202 to continue the matching of the next log line. That is to say, when the current log line is successfully matched with the expected condition and the directed cyclic graph has the next state, the next log line is continuously read, and whether the next log line is successfully matched with the expected condition or successfully matched with the unexpected condition is judged.
Step S208: and skipping to step S207 after recording the matching error information according to the current log line. That is, in the case that the current log line is successfully matched with the unexpected condition, it indicates that the current log line may be the log line in which the matching error occurs, so that the matching error information may be recorded according to the current log line, and then the next log line may be read continuously, and the expected condition and the unexpected condition corresponding to the current state (the first state of the directed cyclic graph) determined according to step S201 are matched with the next log line (step S202 is performed). Meanwhile, when the current log line is successfully matched with the expected conditions and the directed cyclic graph does not have the next state, it also indicates that the current log line may be the log line with the matching error, so that the matching error information may be recorded according to the current log line, and then the next log line is continuously read, and the expected conditions and the unexpected conditions corresponding to the current state (the first state of the directed cyclic graph) determined according to step S201 are matched with the next log line (step S202 is executed).
In one embodiment, referring to fig. 4, fig. 4 is a schematic flow chart illustrating the process of pushing and popping the log lines of each vehicle log when the log lines are sequentially analyzed according to the expected condition set and the unexpected condition set according to one embodiment of the present invention. As shown in FIG. 4, CpIs a set of expected conditions, CuFor an unexpected set of conditions, ViIs in a state, LiFor a log row, the normal form P (directed graph) is a directed cyclic graph, the directed cyclic graph includes a state set V and a condition set C, and the state set V (vertex set) is a state ViThat is, a set of nodes in a directed cyclic graph; the condition set C (directed edge conversion set) is a set of conditions for determining whether or not the state matches a log line when the vehicle log is analyzed, that is, a set of conditions for performing conversion with directed edges in the directed cyclic graph. The vehicle log can be analyzed according to the method shown in fig. 2, and if the expected condition set of the current state is successfully matched with the current log line, the current state is pushed and the next state transferred from the current state is queried; if the current state is found, the found state is used as the current state, the expected condition set of the current state is obtained again, and if the expected condition set of the current state is successfully matched with the current log line, the current state is continuously pushed; and by analogy, when the current state is the last state, all the push states are popped, and matching error information is recorded according to the current log line. And when the unexpected condition set of the current state is successfully matched with the current log line, popping the stack of the pushed state. Whether the matching with the expected condition set is successful or the matching with the unexpected condition set is successful, after the state is popped, the next log line is read in.
In one implementation of the embodiment of the present invention, the step S103 further includes the following steps:
and judging whether each expected condition has a log line successfully matched or not according to the analysis result, if so, judging that the vehicle is in a vehicle state corresponding to the vehicle state analysis service, and outputting the log line.
In this embodiment, whether each expected condition of the vehicle has a successfully matched log line may be determined according to the analysis result of sequentially analyzing each log line in steps S201 to S208, and if yes, it is determined that the successfully matched log lines are the log lines indicating that the vehicle is in the vehicle state corresponding to the vehicle state analysis service, and the successfully matched log lines may be output to facilitate subsequent analysis processing work.
In one implementation manner of the embodiment of the present invention, log keywords of a vehicle log related to a vehicle state analysis service and/or log keywords including a component name and a module name may be stored in a preset keyword library, and technicians and users in the field may add, delete, update, and the like the log keywords according to actual needs; the expected condition set and the log row indicating that the vehicle is in the vehicle state can be stored in a preset analysis result library, and the expected condition set and the log row indicating that the vehicle is in the vehicle state can be displayed through a preset display interface; those skilled in the art can edit, add or delete the finite-state machine models created for different vehicle state analysis services according to actual application needs.
It should be noted that, although the foregoing embodiments describe each step in a specific sequence, those skilled in the art will understand that, in order to achieve the effect of the present invention, different steps do not necessarily need to be executed in such a sequence, and they may be executed simultaneously (in parallel) or in other sequences, and these changes are all within the protection scope of the present invention.
Further, the invention also provides an analysis system of the vehicle log.
Referring to fig. 3, fig. 3 is a main structural block diagram of an analysis system of a vehicle log according to an embodiment of the present invention. As shown in fig. 3, the analysis system of the vehicle log in the embodiment of the present invention may include a finite state machine creation module, a vehicle log analysis module, and a vehicle state judgment module. In this embodiment, the finite state machine creation module may be configured to determine, for each vehicle state analysis service, a log keyword of a vehicle log related to the vehicle state analysis service and a transition condition between different log keywords, and create a finite state machine model of the vehicle state analysis service with the log keyword as a state and the transition condition as a state transition event. The vehicle log analysis module may be configured to collect actual vehicle logs related to the vehicle status analysis service, the actual vehicle logs being analyzed using a finite state machine model of the vehicle status analysis service. The vehicle state judging module can be configured to judge whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to the analysis result; if yes, outputting a log line in the actual vehicle log, wherein the log line indicates that the vehicle is in the vehicle state.
In one embodiment, the vehicle log analysis module may include a vehicle log extraction unit and a vehicle log analysis unit. In this embodiment, the vehicle log extraction unit may be configured to perform keyword extraction on the actual vehicle log based on a log keyword of the vehicle log related to the vehicle state analysis service, and acquire a log line including the log keyword in the actual vehicle log. The vehicle log analysis unit may be configured to analyze the log line using a finite state machine model.
In one embodiment, the vehicle log analysis unit may include a directed cyclic graph acquisition sub-unit, an expected and unexpected condition set acquisition sub-unit, and a log line analysis sub-unit. In this embodiment, the directed cyclic graph acquiring subunit may be configured to analyze the finite state machine model, and acquire a directed cyclic graph having states as nodes and state transition events as directed edges. The expected and unexpected condition set acquisition sub-unit may be configured to acquire an expected condition set and an unexpected condition set of the directed cyclic graph. The log line analysis subunit may be configured to analyze the log line according to the expected condition set and the unexpected condition set. Wherein the set of expected conditions may include at least one expected condition, and the expected condition may be a condition determined from the state transition event that enables a state transition between adjacent states; the set of unexpected conditions can include at least one unexpected condition, which can be a condition determined from a state transition event that a state transition between adjacent states cannot be achieved.
In one embodiment, the analysis system for vehicle logs may be further configured to sequentially analyze each log line according to the expected condition set and the unexpected condition set in the order of the log line time from first to last by:
step S1: acquiring a first state of the directed cyclic graph, and taking the first state as a current state;
step S2: carrying out condition matching on the current log line with an expected condition set and an unexpected condition set, wherein the expected condition set and the unexpected condition set correspond to the current state; if the current log line is successfully matched with the expected condition, go to step S3; if the current log line is successfully matched with the unexpected condition, recording matching error information according to the current log line and then transferring to the step S4;
step S3: performing state transition query on the directed cyclic graph according to expected conditions; if the next state to be transferred from the current state is inquired, taking the next state as a new current state and transferring to the step S4; if the next state transferred from the current state is not inquired, the step is switched to the step S4 after the error information is matched according to the current log line record;
step S4: the expected condition set and the unexpected condition set are obtained again, the next log line is read in, and the next log line is taken as a new current log line and then the process goes to step S2.
In one embodiment, the vehicle state determination module may be further configured to determine whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to the following steps:
and judging whether each expected condition has a log line which is successfully matched or not according to the analysis result, if so, judging that the vehicle is in a vehicle state corresponding to the vehicle state analysis service, and outputting the log line.
The above-mentioned vehicle log analysis system is used for executing the vehicle log analysis method embodiments shown in fig. 1 and fig. 2, and the technical principles, the solved technical problems and the generated technical effects of the two are similar, and it can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working process and related description of the vehicle log analysis system may refer to the content described in the vehicle log analysis method embodiment, and no further description is given here.
It will be understood by those skilled in the art that all or part of the flow of the method according to the above-described embodiment may be implemented by a computer program, which may be stored in a computer-readable storage medium and used to implement the steps of the above-described embodiments of the method when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device capable of carrying said computer program code, media, usb disk, removable hard disk, magnetic diskette, optical disk, computer memory, read-only memory, random access memory, electrical carrier wave signals, telecommunication signals, software distribution media, etc. It should be noted that the computer readable storage medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable storage media that does not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
Furthermore, the invention also provides a control device. In an embodiment of the control device according to the invention, the control device comprises a processor and a storage device, the storage device may be configured to store a program for performing the method for analyzing the vehicle log of the above-described method embodiment, and the processor may be configured to execute a program in the storage device, the program including, but not limited to, a program for performing the method for analyzing the vehicle log of the above-described method embodiment. For convenience of explanation, only the parts related to the embodiments of the present invention are shown, and details of the specific techniques are not disclosed. The control device may be a control device apparatus formed including various electronic apparatuses.
Further, the invention also provides a computer readable storage medium. In one computer-readable storage medium embodiment according to the present invention, a computer-readable storage medium may be configured to store a program for executing the analysis method of the vehicle log of the above-described method embodiment, and the program may be loaded and executed by a processor to implement the analysis method of the vehicle log. For convenience of explanation, only the parts related to the embodiments of the present invention are shown, and details of the specific techniques are not disclosed. The computer readable storage medium may be a storage device formed by including various electronic devices, and optionally, the computer readable storage medium is a non-transitory computer readable storage medium in the embodiment of the present invention.
Further, the invention also provides a vehicle. In an embodiment of a vehicle according to the invention, the vehicle comprises an analysis system for vehicle logs as described in any of the above embodiments of analysis system for vehicle logs. The vehicles in this embodiment include, but are not limited to: smart cars, etc.
Further, it should be understood that, since the configuration of each module is only for explaining the functional units of the apparatus of the present invention, the corresponding physical devices of the modules may be the processor itself, or a part of software, a part of hardware, or a part of a combination of software and hardware in the processor. Thus, the number of individual modules in the figures is merely illustrative.
Those skilled in the art will appreciate that the various modules in the apparatus may be adaptively split or combined. Such splitting or combining of specific modules does not cause the technical solutions to deviate from the principle of the present invention, and therefore, the technical solutions after splitting or combining will fall within the protection scope of the present invention.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.

Claims (10)

1. A method of analyzing a vehicle log, the method comprising:
for each vehicle state analysis service, determining a log keyword of a vehicle log related to the vehicle state analysis service and a transition condition between different log keywords, and creating a finite state machine model of the vehicle state analysis service by taking the log keyword as a state and the transition condition as a state transition event;
collecting an actual vehicle log related to a vehicle state analysis service, and analyzing the actual vehicle log by using a finite state machine model of the vehicle state analysis service;
judging whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to an analysis result; and if so, outputting a log row which indicates that the vehicle is in the vehicle state in the actual vehicle log.
2. The analysis method according to claim 1, wherein the step of analyzing the actual vehicle log using a finite state machine model of the vehicle condition analysis service comprises:
according to the log keywords of the vehicle log related to the vehicle state analysis service, extracting keywords from the actual vehicle log to obtain a log row containing the log keywords in the actual vehicle log;
analyzing the log line by using the finite state machine model.
3. The analysis method according to claim 2, wherein the step of analyzing the log line using the finite state machine model comprises:
analyzing the finite-state machine model to obtain a directed cyclic graph with the state as a node and the state transition event as a directed edge;
acquiring an expected condition set and an unexpected condition set of the directed cyclic graph;
analyzing the log line according to the expected condition set and the unexpected condition set;
wherein the set of expected conditions includes at least one expected condition, the expected condition being a condition determined from a state transition event that enables a state transition between adjacent states; the set of unexpected conditions includes at least one unexpected condition that is a condition determined from a state transition event that a state transition between adjacent states cannot be achieved.
4. The analysis method according to claim 3, further comprising analyzing each log line in turn, in order of log line time from first to last, according to the expected condition set and the unexpected condition set and by:
step S1: acquiring a first state of the directed cyclic graph, and taking the first state as a current state;
step S2: carrying out condition matching on the current log line and expected conditions and unexpected conditions corresponding to the current state in the expected condition set and the unexpected condition set respectively; if the current log line is successfully matched with the expected condition, go to step S3; if the current log line is successfully matched with the unexpected condition, recording matching error information according to the current log line and then transferring to the step S4;
step S3: performing state transition query on the directed cyclic graph according to the expected conditions; if the next state transferred from the current state is inquired, taking the next state as a new current state and transferring to the step S4; if the next state transferred from the current state is not inquired, matching error information according to the current log line record and then transferring to the step S4;
step S4: and re-acquiring the expected condition set and the unexpected condition set, reading in the next log line, and turning to the step S2 after the next log line is taken as a new current log line.
5. The analysis method according to claim 4, wherein "determining whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to the analysis result; if yes, the step of outputting a log line indicating that the vehicle is in the vehicle state in the actual vehicle log "includes:
and judging whether each expected condition has a log line which is successfully matched or not according to the analysis result, if so, judging that the vehicle is in a vehicle state corresponding to the vehicle state analysis service, and outputting the log line.
6. An analysis system for vehicle logs, the analysis system comprising:
a finite state machine creating module configured to determine, for each vehicle state analysis service, a log keyword of a vehicle log related to the vehicle state analysis service and a transition condition between different log keywords, and create a finite state machine model of the vehicle state analysis service with the log keyword as a state and the transition condition as a state transition event;
a vehicle log analysis module configured to collect an actual vehicle log related to a vehicle state analysis service, the actual vehicle log being analyzed using a finite state machine model of the vehicle state analysis service;
a vehicle state judging module configured to judge whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to an analysis result; and if so, outputting a log row which indicates that the vehicle is in the vehicle state in the actual vehicle log.
7. The analytics system of claim 6, wherein the vehicle log analysis module comprises:
a vehicle log extraction unit configured to perform keyword extraction on the actual vehicle log according to a log keyword of the vehicle log related to the vehicle state analysis service, and acquire a log row including the log keyword in the actual vehicle log;
a vehicle log analysis unit configured to analyze the log line using the finite state machine model.
8. The analysis system according to claim 7, wherein the vehicle log analysis unit includes:
a directed cyclic graph obtaining subunit configured to analyze the finite state machine model, and obtain a directed cyclic graph with the state as a node and the state transition event as a directed edge;
an expected and unexpected condition set acquisition subunit configured to acquire an expected condition set and an unexpected condition set of the directed cyclic graph;
a log line analysis subunit configured to analyze the log line according to the expected and unexpected condition sets;
wherein the set of expected conditions includes at least one expected condition, the expected condition being a condition determined from a state transition event that enables a state transition between adjacent states; the set of unexpected conditions includes at least one unexpected condition that is a condition determined from a state transition event that a state transition between adjacent states cannot be achieved.
9. The analysis system of claim 8, wherein the system is further configured to analyze each log line in turn, in order of log line time from first to last, according to the expected and unexpected condition sets by:
step S1: acquiring a first state of the directed cyclic graph, and taking the first state as a current state;
step S2: carrying out condition matching on the current log line and expected conditions and unexpected conditions corresponding to the current state in the expected condition set and the unexpected condition set respectively; if the current log line is successfully matched with the expected condition, go to step S3; if the current log line is successfully matched with the unexpected condition, recording matching error information according to the current log line and then transferring to the step S4;
step S3: performing state transition query on the directed cyclic graph according to the expected conditions; if the next state transferred from the current state is inquired, taking the next state as a new current state and transferring to the step S4; if the next state transferred from the current state is not inquired, matching error information according to the current log line record and then transferring to the step S4;
step S4: and re-acquiring the expected condition set and the unexpected condition set, reading in the next log line, and turning to the step S2 after the next log line is taken as a new current log line.
10. The analysis system of claim 9, wherein the vehicle state determination module is further configured to determine whether the vehicle is in a vehicle state corresponding to the vehicle state analysis service according to the following steps:
and judging whether each expected condition has a log line which is successfully matched or not according to the analysis result, if so, judging that the vehicle is in a vehicle state corresponding to the vehicle state analysis service, and outputting the log line.
CN202111150601.7A 2021-09-29 2021-09-29 Vehicle log analysis method, system, device, medium and vehicle Pending CN113886202A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116541442A (en) * 2023-07-05 2023-08-04 无锡车联天下信息技术有限公司 New energy automobile log analysis method and device

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116541442A (en) * 2023-07-05 2023-08-04 无锡车联天下信息技术有限公司 New energy automobile log analysis method and device
CN116541442B (en) * 2023-07-05 2023-09-08 无锡车联天下信息技术有限公司 New energy automobile log analysis method and device

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