CN111930097A - Vehicle diagnostic data analysis method, device, equipment and storage medium - Google Patents

Vehicle diagnostic data analysis method, device, equipment and storage medium Download PDF

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Publication number
CN111930097A
CN111930097A CN202010736759.1A CN202010736759A CN111930097A CN 111930097 A CN111930097 A CN 111930097A CN 202010736759 A CN202010736759 A CN 202010736759A CN 111930097 A CN111930097 A CN 111930097A
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class object
data
segment
class
identification information
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CN111930097B (en
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刘均
邓蒙召
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Shenzhen Launch Technology Co Ltd
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Shenzhen Launch Technology Co Ltd
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    • 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
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0221—Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods

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Abstract

The application provides a vehicle diagnosis data analysis method, a device, equipment and a storage medium, relates to the technical field of vehicle diagnosis, and can effectively avoid the problem of vehicle diagnosis data reference error in the vehicle diagnosis data analysis process. The method comprises the following steps: analyzing a source file of vehicle diagnostic data to obtain at least one section of data object included in the source file; respectively traversing each segment of the data object, and determining the attribute information of each class object in each segment of the data object; for any segment of the data objects in each segment of the data objects, if the attribute information of a class object does not include the identification information of the class object in the segment of the data object, traversing a class object list of the segment of the data object to acquire the diagnostic information of the class object; if the attribute information of the class object in the segment of data object comprises the identification information of the class object, acquiring the diagnosis information of the class object based on the identification information of the class object.

Description

Vehicle diagnostic data analysis method, device, equipment and storage medium
Technical Field
The present application relates to the field of vehicle diagnosis technologies, and in particular, to a method, an apparatus, a device, and a storage medium for analyzing vehicle diagnosis data.
Background
Currently, vehicle diagnostic data based on the ODX standard is packaged in XML tags. However, when referring to the vehicle diagnostic data encapsulated based on the XML tag, since not every type of vehicle diagnostic data corresponds to unique identification Information (ID), if the vehicle diagnostic data is referred to based on the identification information of the vehicle diagnostic data, there is a risk that part of the vehicle diagnostic data is lost. In order to solve the above problem, a referencing method of vehicle diagnostic data using value referencing, also called short name (shortname) referencing, is proposed. However, since the values of the vehicle diagnostic data encapsulated based on the XML tags are not unique, there may be a case where different vehicle diagnostic data have the same value in the same diagnostic file, resulting in a problem of a reference error when referring to the vehicle diagnostic data by the value.
Disclosure of Invention
The embodiment of the application provides a vehicle diagnosis data analysis method, a vehicle diagnosis data analysis device and a storage medium, and can effectively avoid the problem of vehicle diagnosis data reference error in the vehicle diagnosis data analysis process.
In a first aspect, the present application provides a vehicle diagnostic data parsing method, including:
analyzing a source file of vehicle diagnostic data to obtain at least one section of data object included in the source file;
respectively traversing each segment of the data object, and determining the attribute information of each class object in each segment of the data object;
for any segment of the data objects in each segment of the data objects, if the attribute information of a class object does not include the identification information of the class object in the segment of the data object, traversing a class object list of the segment of the data object to acquire the diagnostic information of the class object;
if the attribute information of the class object in the segment of data object comprises the identification information of the class object, acquiring the diagnosis information of the class object based on the identification information of the class object.
In an optional implementation manner, if the attribute information of the class object includes the identification information of the class object in the segment of data object, the diagnostic information of the class object is obtained based on the identification information of the class object, and may be replaced with:
if the attribute information of the class object in the segment of data object includes the identification information of the class object, traversing the class object list of the data object corresponding to the class object to acquire the diagnostic information of the class object.
In an optional implementation manner, the traversing the class object list of the segment of data object to respectively obtain the diagnostic information corresponding to each class object in the segment of data object includes:
and traversing the class object list of the data object, and acquiring the diagnosis information of the class object based on a value reference method.
In an optional implementation manner, the traversing the class object list of the segment of data object, and obtaining the diagnostic information of the class object based on a value reference method includes:
and traversing the class object list of the data object of the class object based on the short name of the class object, and acquiring the diagnosis information matched with the short name of the class object.
In an optional implementation manner, after traversing each segment of the data object and determining attribute information of each class object in each segment of the data object, the method further includes:
for any segment of the data object in each segment of the data object, if the attribute information of all class objects in the segment of the data object comprises the identification information corresponding to each class object, establishing a mapping relation between each class object and the identification information corresponding to each class object;
and respectively acquiring the diagnosis information of each class object in the data object based on the mapping relation.
In an optional implementation manner, the establishing a mapping relationship between each class object and the identification information corresponding to each class object includes:
and respectively establishing key value pairs between each class object and the identification information corresponding to each class object, and storing each key value pair into the global container object.
In an optional implementation manner, the obtaining, based on the mapping relationship, the diagnostic information of each class object in the segment of the data object respectively includes:
traversing each key-value pair in the container object, and respectively determining identification information corresponding to each class object;
and respectively acquiring the diagnostic information corresponding to the identification information of each class object according to the identification information of each class object.
In a second aspect, the present application provides a vehicle diagnostic data analysis device, comprising:
the obtaining module is used for analyzing a source file of vehicle diagnostic data to obtain at least one section of data object included in the source file;
the determining module is used for respectively traversing each segment of the data object and determining the attribute information of each class object in each segment of the data object;
a first obtaining module, configured to, for any segment of the data objects in each segment of the data objects, if attribute information of a class object does not include identification information of the class object in the segment of the data object, traverse a class object list of the segment of the data object, and obtain diagnostic information of the class object;
and the second obtaining module is used for obtaining the diagnosis information of the class object based on the identification information of the class object if the attribute information of the class object in the segment of data object comprises the identification information of the class object.
In an optional implementation manner, the second obtaining module is configured to traverse a class object list of the data object corresponding to the class object to obtain the diagnostic information of the class object if the attribute information of the class object includes the identification information of the class object in the segment of data object.
In an optional implementation manner, the first obtaining module is specifically configured to:
for any segment of the data objects, if the attribute information of a class object does not include the identification information of the class object in the segment of the data object, traversing the class object list of the segment of the data object, and acquiring the diagnostic information of the class object based on a value reference method.
In an optional implementation manner, the first obtaining module is specifically configured to:
for any segment of the data objects, if the attribute information of a class object does not include the identification information of the class object in the segment of the data object, traversing the class object list of the data object of the class object based on the short name of the class object, and acquiring the diagnosis information matched with the short name of the class object.
In an optional implementation manner, the method further includes:
the establishing module is used for establishing a mapping relation between each class object and the identification information corresponding to each class object if the attribute information of all the class objects in the data object comprises the identification information corresponding to each class object aiming at any segment of the data object in each segment of the data object;
and the third acquisition module is used for respectively acquiring the diagnostic information of each class object in the data object based on the mapping relation.
In an optional implementation manner, the establishing module is specifically configured to:
for any segment of the data object in each segment of the data object, if the attribute information of all the class objects in the segment of the data object includes the identification information corresponding to each class object, respectively establishing a key value pair between each class object and the identification information corresponding to each class object, and storing each key value pair into a global container object.
In an optional implementation manner, the third obtaining module includes:
the determining unit is used for traversing each key value pair in the container object and respectively determining the identification information corresponding to each class object;
and the acquisition unit is used for respectively acquiring the diagnostic information corresponding to the identification information of each class object according to the identification information of each class object.
In a third aspect, the present application provides a vehicle diagnostic data interpretation apparatus comprising:
a memory for storing a vehicle diagnostic data analysis program;
a processor configured to implement the vehicle diagnostic data analysis method according to the first aspect or any of the alternatives of the first aspect when executing the vehicle diagnostic data analysis program.
A fourth unit, the present application provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the vehicle diagnostic data parsing method according to the first aspect or any alternative of the first aspect.
In a fifth aspect, the present application provides a computer program product, which when run on a vehicle diagnostic data analysis device, causes the vehicle diagnostic data analysis device to execute the steps of the vehicle diagnostic data analysis method according to the first aspect or any optional manner of the first aspect.
By adopting the vehicle diagnosis data analysis method provided by the application, whether the attribute information of each class object in each segment of data object in the vehicle diagnosis data source file corresponds to the identification information of the class object is determined, and when the attribute information of the class object does not comprise the identification information of the class object, the diagnosis information of the class object is obtained by traversing the class object list of the segment of data object, so that the problem of reference error of the vehicle diagnosis data in the vehicle diagnosis data analysis process can be effectively avoided.
It is understood that the beneficial effects of the second aspect to the fifth aspect can be referred to the related description of the first aspect, and are not described herein again.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a schematic diagram illustrating a vehicle diagnostic data parsing scheme provided by an embodiment of the present application;
FIG. 2 is a schematic diagram of a class object within an XML tag provided by an embodiment of the present application;
FIG. 3 is a schematic diagram of a class object structure provided in an embodiment of the present application;
FIG. 4 is a schematic flow chart diagram of a vehicle diagnostic data parsing method provided by an embodiment of the present application;
FIG. 5 is a schematic diagram of a vehicle diagnostic data parser provided in an embodiment of the present application;
fig. 6 is a schematic diagram of a vehicle diagnostic data analysis device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items. Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
It should also be understood that the appearances of the phrases "in one embodiment," "in some embodiments," and the like in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise.
Before explaining the vehicle diagnostic data analysis method provided by the present application, first, the vehicle diagnostic data analysis principle employed by the present application and the related concepts in the vehicle diagnostic data analysis will be exemplarily explained with reference to fig. 1.
As shown in fig. 1, fig. 1 is a schematic diagram illustrating a vehicle diagnostic data analysis principle provided in an embodiment of the present application. In some embodiments of the present application, the vehicle Diagnostic Data parsing device 101 is communicatively connected to the vehicle 102 to be diagnosed, the vehicle Diagnostic Data parsing device 101 obtains a source file 1021 of vehicle Diagnostic Data stored in the vehicle 102 to be diagnosed, and needs to parse the obtained source file 1021 of the vehicle Diagnostic Data, for example, in some embodiments, the vehicle Diagnostic Data parsing device 101 may be a hardware device in various vehicle Diagnostic application scenarios, such as a vehicle Diagnostic device, the source file 1021 of the vehicle Diagnostic Data is an eXtensible Markup Language (XML) format file based on an ODX (Open Diagnostic Data Exchange) standard, different types of Diagnostic Data are packaged by XML tags, each XML node usually contains a piece of Data object, such as a DOP (Data object properties) Data object, each DOP data object takes two corresponding XML tags as two interval boundary tags, multiple types of vehicle diagnosis data are contained in each DOP data object, each type of vehicle diagnosis data usually has an ID field as the unique identification information thereof, and a short name shortname field is contained, wherein the shortname is equivalent to the name of the corresponding type of vehicle diagnosis data. When the vehicle diagnostic data parsing device 101 acquires the vehicle diagnostic data in the ODX source file, a corresponding class object is designed for each type of vehicle diagnostic data, and is used for storing the specific type of vehicle diagnostic data in each segment of DOP data.
For example, as shown in fig. 2, fig. 2 is a schematic diagram of a class object in an XML tag provided by an embodiment of the present application. In fig. 2, class objects of one class, such as ECU-VARIANT, DIAG-DATA-DICTIONARY-SPEC, DTC-DOPS, DTC-DOP, DTCs and DTC, are defined to store vehicle diagnostic DATA within two interval boundary tags (within a corresponding segment of DOP DATA object) of the corresponding XML, respectively. As can be seen from FIG. 2, the class object of DTC-DOP includes a string variable for storing identification information ID of the class object, and other string variables are defined for storing the identifier OID, SHORT NAME SHORT-NAME, LONG NAME LONG-NAME and TYPE DIAG-CODED-TYPE of the diagnostic information of the class object, respectively. As can be seen from fig. 2, in this embodiment, the attribute information of the class object DTC-DOP includes the identification information ID of the class object. For example, as shown in fig. 3, fig. 3 is a schematic diagram of a class object structure provided in an embodiment of the present application, attribute information of a class object PARAM does not include the identification information of the class object, at this time, diagnostic information corresponding to the class object PARAM cannot be obtained using an identification information ID, and since a shortname of the class object PARAM may be the same as shortnames of other class objects, diagnostic information corresponding to the class object cannot be accurately obtained by simple value application. As can be seen from the characteristics of the XML format file, the higher-level tag corresponding to each class object, that is, the XML tag of the data object to which each class object belongs, has uniqueness, and therefore, in some embodiments of the present application, in a case where the attribute information of a class object does not include the identification information of the class object, the diagnostic information of the class object may be accurately obtained by traversing the class object list of the data object to which the class object belongs.
The following describes an exemplary vehicle diagnostic data analysis method provided by the present application with reference to specific embodiments.
Referring to fig. 4, fig. 4 is a schematic flow chart of a vehicle diagnostic data parsing method according to an embodiment of the present application. The main execution body of the vehicle diagnostic data analysis method in the embodiment is a vehicle diagnostic data analysis device, including but not limited to hardware devices in various vehicle diagnostic application scenarios, such as a vehicle diagnostic device. The vehicle diagnostic data parsing method as shown in fig. 4 may include:
s401, analyzing a source file of vehicle diagnostic data to obtain at least one section of data object included in the source file.
In some embodiments of the present application, the at least one segment of data object is a data object attribute DOP (data object properties) data object, which is used in vehicle diagnostic data of the ODX standard to interpret and describe a data stream of the diagnostic data, such as data of a diagnostic request and a reply, and also to provide diagnostic information, such as a data conversion relationship between a code value and a physical value of a diagnostic device. Each section of the data object takes two corresponding XML tags as two interval boundary tags, each section of the data object contains various types of diagnostic data, and the corresponding class object stores various types of diagnostic data in an XML tag file.
S402, traversing each segment of the data object respectively, and determining the attribute information of each class object in each segment of the data object.
In some embodiments of the present application, the attribute information of each class object is stored in a string variable under an XML tag corresponding to the class object, where the attribute information of a part of the class object includes identification information of the class object, the attribute information of a part of the class object does not include the identification information of the class object, but the attribute information of all the class objects includes names (including short names shortname and longname) of corresponding class objects and diagnostic information corresponding to the class objects.
S403, for any segment of the data objects, if the attribute information of a class object does not include the identification information of the class object in the segment of the data object, traversing the class object list of the segment of the data object, and acquiring the diagnostic information of the class object.
For example, when the attribute information of the class object PARAM shown in fig. 3 does not include the identification information of the class object, at this time, the upper level data object </PARAM > corresponding to the class object PARAM is traversed, as can be seen from fig. 3, the two boundary tags (XML tags) of the class object list of the data object </PARAM > are </PARAM >, the class object in the boundary tag </PARAM > constitutes the class object list of the data object </PARAM >, and the XML tag of the data object has uniqueness, and the diagnostic information of the class object can be accurately obtained by traversing the class object list of the data object corresponding to the class object.
Illustratively, in some embodiments of the present application, the diagnostic information of the class object may be obtained based on a value reference method by traversing the class object list of the segment of data object.
Since the boundary labels of the data objects have uniqueness, the names of the corresponding class objects in the same segment of data objects generally have uniqueness, and after the data object to which the class object belongs is determined, diagnostic information of the class object can be acquired based on a value reference (name reference or short name reference) method by traversing the class object list of the segment of data object.
For example, based on the short name of the class object, the class object list of the data object of the class object is traversed to obtain the diagnosis information matched with the short name of the class object.
It can be understood that, in a segment of data object, if the class object of the data object corresponds to the identification information, the identification information may uniquely refer to the class object, or the diagnostic information corresponding to the class object may be referred to by the value reference method described above.
In an optional implementation manner, for any segment of the data object in each segment of the data object, if the attribute information of all class objects in the segment of the data object includes identification information corresponding to each class object, a mapping relationship between each class object and the identification information corresponding to each class object is established; and respectively acquiring the diagnosis information of each class object in the data object based on the mapping relation.
Specifically, the establishing of the mapping relationship between each class object and the identification information corresponding to each class object includes: and respectively establishing key value pairs between each class object and the identification information corresponding to each class object, and storing each key value pair into the global container object.
Correspondingly, based on the mapping relationship, obtaining the diagnostic information of each class object in the segment of the data object respectively includes: traversing each key-value pair in the container object, and respectively determining identification information corresponding to each class object; and respectively acquiring the diagnostic information corresponding to the identification information of each class object according to the identification information of each class object.
S404, if the attribute information of the class object includes the identification information of the class object in the segment of data object, acquiring the diagnostic information of the class object based on the identification information of the class object.
In this embodiment, the process of acquiring the diagnostic information of the class object based on the identification information of the class object includes: the process of obtaining the diagnostic information of the class object by referring to the identification information of the corresponding class object by the global container object can be seen in detail in the knowledge of the existing global container variable reference, which is not detailed herein,
it can be understood that, if the attribute information of a class object in the segment of data object includes the identification information of the class object, the diagnostic information of the class object may also be obtained in a value reference manner, that is, the diagnostic information of the class object may be obtained by traversing the class object list of the data object corresponding to the class object.
Based on the above embodiment, it can be known that, with the vehicle diagnostic data analysis method provided by the present application, by determining whether the attribute information of each class object in each segment of data object in the vehicle diagnostic data source file corresponds to the identification information of the class object, and when the attribute information of a class object does not include the identification information of the class object, the diagnostic information of the class object is obtained by traversing the class object list of the segment of data object. The problem of vehicle diagnostic data reference error in the vehicle diagnostic data analysis process can be effectively avoided
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Based on the vehicle diagnostic data analysis method provided by the embodiment, the embodiment of the invention further provides an embodiment of a device for realizing the embodiment of the method.
Referring to fig. 5, fig. 5 is a schematic view of a vehicle diagnostic data analysis device according to an embodiment of the present disclosure. The units included are used to perform the steps in the corresponding embodiment of fig. 4. Please refer to fig. 4 for a related description of the embodiment. For convenience of explanation, only the portions related to the present embodiment are shown. Referring to fig. 5, the vehicle diagnostic data analysis device 5 includes:
an obtaining module 501, configured to parse a source file of vehicle diagnostic data to obtain at least one segment of data object included in the source file;
a determining module 502, configured to traverse each segment of the data object, and determine attribute information of each class object in each segment of the data object;
a first obtaining module 503, configured to, for any segment of the data objects in each segment of the data objects, if attribute information of a class object in the segment of the data object does not include identification information of the class object, traverse a class object list of the segment of the data object, and obtain diagnostic information of the class object;
a second obtaining module 504, configured to, if the attribute information of a class object in the segment of data object includes identification information of the class object, obtain diagnosis information of the class object based on the identification information of the class object.
In an optional implementation manner, the second obtaining module 504 is configured to traverse a class object list of the data object corresponding to the class object to obtain the diagnostic information of the class object if the attribute information of the class object includes the identification information of the class object in the segment of data object.
In an optional implementation manner, the first obtaining module 503 is specifically configured to:
for any segment of the data objects, if the attribute information of a class object does not include the identification information of the class object in the segment of the data object, traversing the class object list of the segment of the data object, and acquiring the diagnostic information of the class object based on a value reference method.
In an optional implementation manner, the first obtaining module 503 is specifically configured to:
for any segment of the data objects, if the attribute information of a class object does not include the identification information of the class object in the segment of the data object, traversing the class object list of the data object of the class object based on the short name of the class object, and acquiring the diagnosis information matched with the short name of the class object.
In an optional implementation manner, the method further includes:
the establishing module is used for establishing a mapping relation between each class object and the identification information corresponding to each class object if the attribute information of all the class objects in the data object comprises the identification information corresponding to each class object aiming at any segment of the data object in each segment of the data object;
and the third acquisition module is used for respectively acquiring the diagnostic information of each class object in the data object based on the mapping relation.
In an optional implementation manner, the establishing module is specifically configured to:
for any segment of the data object in each segment of the data object, if the attribute information of all the class objects in the segment of the data object includes the identification information corresponding to each class object, respectively establishing a key value pair between each class object and the identification information corresponding to each class object, and storing each key value pair into a global container object.
In an optional implementation manner, the third obtaining module includes:
the determining unit is used for traversing each key value pair in the container object and respectively determining the identification information corresponding to each class object;
and the acquisition unit is used for respectively acquiring the diagnostic information corresponding to the identification information of each class object according to the identification information of each class object.
It should be noted that, because the contents of information interaction, execution process, and the like between the modules are based on the same concept as that of the embodiment of the method of the present application, specific functions and technical effects thereof may be specifically referred to a part of the embodiment of the method, and details are not described here.
Fig. 6 is a schematic diagram of a vehicle diagnostic data analysis device according to an embodiment of the present application. As shown in fig. 6, the vehicle diagnostic data analysis apparatus 101 of this embodiment includes: a processor 600, a memory 60, and a computer program 602, such as a vehicle diagnostic data parser, stored in the memory 601 and operable on the processor 600. The processor 600, when executing the computer program 602, implements the steps in the various vehicle diagnostic data analysis method embodiments described above, such as the steps 401 to 404 shown in fig. 4. Alternatively, the processor 600 executes the computer program 602 to implement the functions of the modules/units in the above device embodiments, such as the functions of the modules 501 to 504 shown in fig. 5.
Illustratively, the computer program 502 may be partitioned into one or more modules/units that are stored in the memory 501 and executed by the processor 50 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution process of the computer program 502 in the vehicle diagnostic data analysis device 101. For example, the computer program 502 may be divided into an obtaining module, a determining module, a first obtaining module, and a second obtaining module, and specific functions of each module please refer to the related descriptions in the embodiment corresponding to fig. 4, which is not described herein again.
The vehicle diagnostic data parsing device may include, but is not limited to, a processor 500, a memory 501. Those skilled in the art will appreciate that fig. 5 is merely an example of the vehicle diagnostic data parsing device 101 and does not constitute a limitation of the vehicle diagnostic data parsing device 101, and may include more or less components than those shown, or combine some components, or different components, for example, the video processing device may also include an input-output device, a network access device, a bus, etc.
The Processor 500 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 501 may be an internal storage unit of the vehicle diagnostic data analysis device 5, such as a hard disk or a memory of the vehicle diagnostic data analysis device 5. The memory 501 may also be an external storage device of the vehicle diagnostic data analysis device 5, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the vehicle diagnostic data analysis device 101. Further, the memory 501 may also include both an internal storage unit and an external storage device of the vehicle diagnostic data analysis device 101. The memory 501 is used to store the computer program 502 and other programs and data required by the vehicle diagnostic data analysis apparatus. The memory 501 may also be used to temporarily store data that has been output or is to be output.
The embodiment of the application also provides a computer readable storage medium, which stores a computer program, and the computer program can realize the vehicle diagnosis data analysis method when being executed by a processor.
The embodiment of the application provides a computer program product, and when the computer program product runs on a vehicle diagnosis data analysis device, the vehicle diagnosis data analysis device can realize the vehicle diagnosis data analysis method when executed.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.

Claims (10)

1. A vehicle diagnostic data parsing method, comprising:
analyzing a source file of vehicle diagnostic data to obtain at least one section of data object included in the source file;
respectively traversing each segment of the data object, and determining the attribute information of each class object in each segment of the data object;
for any segment of the data objects in each segment of the data objects, if the attribute information of a class object does not include the identification information of the class object in the segment of the data object, traversing a class object list of the segment of the data object to acquire the diagnostic information of the class object;
if the attribute information of the class object in the segment of data object comprises the identification information of the class object, acquiring the diagnosis information of the class object based on the identification information of the class object.
2. The method according to claim 1, wherein if the attribute information of a class object in the segment of data object includes identification information of the class object, the diagnostic information of the class object is obtained based on the identification information of the class object, and the method is replaced by:
if the attribute information of the class object in the segment of data object includes the identification information of the class object, traversing the class object list of the data object corresponding to the class object to acquire the diagnostic information of the class object.
3. The method according to claim 1 or 2, wherein traversing the class object list of the segment of data objects to obtain the diagnostic information of the class object comprises:
and traversing the class object list of the data object, and acquiring the diagnosis information of the class object based on a value reference method.
4. The method of claim 3, wherein traversing the class object list of the segment of data objects, and obtaining diagnostic information for the class object based on a value reference method comprises:
and traversing the class object list of the data object of the class object based on the short name of the class object, and acquiring the diagnosis information matched with the short name of the class object.
5. The method of claim 4, after traversing each segment of the data object and determining attribute information of each class object in each segment of the data object, further comprising:
for any segment of the data object in each segment of the data object, if the attribute information of all class objects in the segment of the data object comprises the identification information corresponding to each class object, establishing a mapping relation between each class object and the identification information corresponding to each class object;
and respectively acquiring the diagnosis information of each class object in the data object based on the mapping relation.
6. The method according to claim 5, wherein the establishing a mapping relationship between each class object and the identification information corresponding to each class object comprises:
and respectively establishing key value pairs between each class object and the identification information corresponding to each class object, and storing each key value pair into the global container object.
7. The method according to claim 6, wherein the obtaining the diagnosis information of each class object in the segment of the data object based on the mapping relationship comprises:
traversing each key-value pair in the container object, and respectively determining identification information corresponding to each class object;
and respectively acquiring the diagnostic information corresponding to the identification information of each class object according to the identification information of each class object.
8. A vehicle diagnostic data analysis device, comprising:
the obtaining module is used for analyzing a source file of vehicle diagnostic data to obtain at least one section of data object included in the source file;
the determining module is used for respectively traversing each segment of the data object and determining the attribute information of each class object in each segment of the data object;
a first obtaining module, configured to, for any segment of the data objects in each segment of the data objects, if attribute information of a class object does not include identification information of the class object in the segment of the data object, traverse a class object list of the segment of the data object, and obtain diagnostic information of the class object;
and the second obtaining module is used for obtaining the diagnosis information of the class object based on the identification information of the class object if the attribute information of the class object in the segment of data object comprises the identification information of the class object.
9. A vehicle diagnostic data interpretation apparatus, comprising:
a memory for storing a vehicle diagnostic data analysis program;
a processor for implementing the vehicle diagnostic data analysis method according to any one of claims 1 to 7 when executing the vehicle diagnostic data analysis program.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, implements a vehicle diagnostic data interpretation method according to any one of claims 1 to 7.
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