CN117176507A - Data analysis method, device, electronic equipment and storage medium - Google Patents

Data analysis method, device, electronic equipment and storage medium Download PDF

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Publication number
CN117176507A
CN117176507A CN202311444468.5A CN202311444468A CN117176507A CN 117176507 A CN117176507 A CN 117176507A CN 202311444468 A CN202311444468 A CN 202311444468A CN 117176507 A CN117176507 A CN 117176507A
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blf
file
dbc
message
data
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CN117176507B (en
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陈航
黄伟
刘佳信
单羿
都大龙
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Shanghai Jianzhi Qiji Technology Co ltd
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Shanghai Jianzhi Qiji Technology Co ltd
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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Abstract

The embodiment of the application provides a data analysis method, a data analysis device, electronic equipment and a storage medium. The method comprises the following steps: calling a pre-configured data analysis script to analyze a DBC file to obtain DBC message information of each frame of message in the DBC file; invoking the data analysis script to analyze the BLF file to obtain BLF message information in each frame of message in each frame of BLF file; and carrying out data analysis on the DBC message information and the BLF message information to obtain the test statistical data of the BLF file. The embodiment of the application can save test analysis time.

Description

Data analysis method, device, electronic equipment and storage medium
Technical Field
The present application relates to the field of CAN data analysis technologies, and in particular, to a data analysis method, a data analysis device, an electronic device, and a storage medium.
Background
The current intelligent driving vehicle-mounted controller is huge in data quantity of CAN (Controller Area Network) message signals transmitted by the controller area network, and often contains combined signals (such as front pavement information, front elevation information, front obstacle wavelength and the like) composed of a plurality of signals, the signals are often calculated by AI algorithm prediction, statistical data and numerical values such as numerical distribution are also important, and when CANOE (CAN open environment) is analyzed by specific Blf data, if a manual analysis method is used, the workload is increased along with the size of the collected data and the quantity of analyzed signals. And manual statistics is only suitable for single signals, combined signals composed of a plurality of signals, and logical relations among the signals cannot be intuitively displayed.
The traditional CAN data analysis method uses CANoe to collect CAN message data, and then uses CANoe software to manually analyze Blf data, and the data analysis method is suitable for strategies with definite logic functions and is used for analyzing the relation between input signals and output signals. Because the input value is fixed, the output value of the controller is fixed.
However, in the automatic driving field, many CAN signals are often estimated by an AI large model, the values of the CAN signals are not always fixed, and at the moment, statistical data such as the probability distribution of CAN signal data and the like are also concerned, and at the same time, one frame of image is often composed of many signal data, and at the moment, manual analysis by using CANoe software cannot be realized, and the requirements CAN be met by using new software tools.
Therefore, the problems that the manual analysis workload of CAN data in the current vehicle-mounted controller is large, the regression testing efficiency is low, the analysis requirement cannot be met and the like are solved.
Disclosure of Invention
The embodiment of the application provides a data analysis method, a data analysis device, electronic equipment and a storage medium, which are used for solving the problems that the manual analysis workload of the existing CAN data is large, the regression testing efficiency is low and the analysis requirement cannot be met.
In order to solve the technical problems, the embodiment of the application is realized as follows:
in a first aspect, an embodiment of the present application provides a data analysis method, where the method includes:
calling a pre-configured data analysis script to analyze a DBC file to obtain DBC message information of each frame of message in the DBC file;
invoking the data analysis script to analyze the BLF file to obtain BLF message information in each frame of message in each frame of BLF file;
and carrying out data analysis on the DBC message information and the BLF message information to obtain the test statistical data of the BLF file.
Optionally, before calling a pre-configured data analysis script to analyze the DBC file to obtain DBC message information of each frame of message in the DBC file, the method further includes:
and calling the data analysis script to read the DBC file and the BLF file in the vehicle-mounted controller.
Optionally, the calling the preconfigured data analysis script analyzes the DBC file to obtain DBC message information of each frame of message in the DBC file, including:
calling the data analysis script to analyze the DBC file to obtain message identification information, signal distribution information, signal precision offset information and signal names of each frame of message in the DBC file;
and using the message identification information, the signal distribution information, the signal precision offset information and the signal name as the DBC message information.
Optionally, the performing data analysis on the DBC message information and the BLF message information to obtain test statistical data of the BLF file includes:
adding the DBC message information and the BLF message information into a data list;
and carrying out data analysis on the information corresponding to each BLF file in the data list to obtain the test statistical data of the BLF files.
Optionally, the data analysis is performed on the information corresponding to each BLF file in the data list, to obtain test statistics of the BLF files, including:
acquiring first DBC message information and first BLF message information corresponding to the same message identification information from the data list;
determining a signal value corresponding to each frame of message based on the first DBC message information and the first BLF message information;
determining test statistical data of each BLF file based on a signal value of each frame of message in the BLF file;
the test statistics include: at least one of a maximum value, a minimum value, an average value, and a data distribution.
Optionally, the data analysis is performed on the information corresponding to each BLF file in the data list, to obtain test statistics of the BLF files, including:
acquiring a plurality of DBC message information and a plurality of BLF message information at the same time from the data list;
determining composite signal data at each moment based on the plurality of DBC message information and the plurality of BLF message information;
and determining test statistical data of each BLF file based on the composite signal data of different moments in each message period in the BLF file.
Optionally, the data analysis script is a Python script.
In a second aspect, an embodiment of the present application provides a data analysis apparatus, including:
the DBC message acquisition module is used for calling a pre-configured data analysis script to analyze the DBC file to obtain DBC message information of each frame of message in the DBC file;
the BLF message acquisition module is used for calling the data analysis script to analyze the BLF file to obtain BLF message information in each frame of message in each frame of BLF file;
and the test statistical data acquisition module is used for carrying out data analysis on the DBC message information and the BLF message information to obtain test statistical data of the BLF file.
Optionally, the apparatus further comprises:
and the file reading module is used for calling the data analysis script to read the DBC file and the BLF file in the vehicle-mounted controller.
Optionally, the DBC message obtaining module includes:
the message information acquisition unit is used for calling the data analysis script to analyze the DBC file to obtain message identification information, signal distribution information, signal precision offset information and signal names of each frame of message in the DBC file;
and the DBC message acquisition unit is used for taking the message identification information, the signal distribution information, the signal precision offset information and the signal name as the DBC message information.
Optionally, the test statistic data obtaining module includes:
a message information adding unit, configured to add the DBC message information and the BLF message information to a data list;
and the test statistical data acquisition unit is used for carrying out data analysis on the information corresponding to each BLF file in the data list to obtain the test statistical data of the BLF files.
Optionally, the test statistic data obtaining unit includes:
a first message information obtaining subunit, configured to obtain, from the data list, first DBC message information and first BLF message information corresponding to the same message identifier information;
a signal value determining subunit, configured to determine a signal value corresponding to each frame of message based on the first DBC message information and the first BLF message information;
a first statistics determining subunit, configured to determine, for each BLF file, test statistics of the BLF file based on a signal value of each frame of message in the BLF file;
the test statistics include: at least one of a maximum value, a minimum value, an average value, and a data distribution.
Optionally, the test statistic data obtaining unit includes:
a second message information obtaining subunit, configured to obtain multiple DBC message information and multiple BLF message information at the same time from the data list;
a composite signal data determining subunit, configured to determine composite signal data at each moment based on the multiple DBC message information and the multiple BLF message information;
and the second statistical data determining subunit is used for determining test statistical data of each BLF file based on the composite signal data at different moments in each message period in the BLF file.
Optionally, the data analysis script is a Python script.
In a third aspect, an embodiment of the present application provides an electronic device, including:
a memory, a processor, and a computer program stored on the memory and executable on the processor, which when executed by the processor implements the data analysis method of any of the above.
In a fourth aspect, embodiments of the present application provide a readable storage medium, which when executed by a processor of an electronic device, enables the electronic device to perform the data analysis method of any one of the above.
In the embodiment of the application, the DBC file is analyzed by calling the pre-configured data analysis script, so that DBC message information of each frame of message in the DBC file is obtained. And calling a data analysis script to analyze the BLF file to obtain BLF message information in each frame of message in each frame of BLF file. And carrying out data analysis based on the DBC message information and the BLF message information to obtain the test statistical data of the BLF file. According to the embodiment of the application, the CAN DBC file and the BLF file are analyzed through the data analysis script, the test statistical data of different signals are automatically generated, the analysis work of various signals in the BLF CAN be rapidly completed, a plurality of analysis modes are provided, the test data after iteration CAN be rapidly analyzed after the software is updated, the comparison effect is achieved, the problems that the manual analysis workload of the existing CAN data is large, the regression test efficiency is low, and the analysis requirement cannot be met are solved, and the test analysis time and the labor cost are saved.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments of the present application 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 other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of steps of a data analysis method according to an embodiment of the present application;
FIG. 2 is a flowchart illustrating steps of a method for reading a file according to an embodiment of the present application;
FIG. 3 is a flowchart illustrating steps of a method for obtaining DBC message information according to an embodiment of the present application;
FIG. 4 is a flowchart illustrating steps of a method for obtaining test statistics according to an embodiment of the present application;
FIG. 5 is a flowchart illustrating steps of a method for determining test statistics according to an embodiment of the present application;
FIG. 6 is a flowchart illustrating steps of another method for determining test statistics according to an embodiment of the present application;
fig. 7 is a schematic diagram of a CAN packet data analysis flow provided in an embodiment of the present application;
FIG. 8 is a schematic diagram of a single signal distribution in a single BLF file according to an embodiment of the present application;
FIG. 9 is a schematic diagram of an elevation curve at a certain time point according to an embodiment of the present application;
FIG. 10 is a diagram illustrating a distribution of high Cheng Fengzhi points in a single BLF file according to an embodiment of the present application;
FIG. 11 is a schematic diagram of a dynamic change video of an altitude curve in a single BLF file according to an embodiment of the present application;
fig. 12 is a schematic structural diagram of a data analysis device according to an embodiment of the present application;
fig. 13 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1, a flowchart of steps of a data analysis method according to an embodiment of the present application is shown. As shown in fig. 1, the data analysis method may include: step 101, step 102 and step 103.
Step 101: and calling a pre-configured data analysis script to analyze the DBC file to obtain DBC message information of each frame of message in the DBC file.
The embodiment of the application can be applied to a scene of analyzing DBC (Data Base Commande, database management) files and BLF files based on preconfigured data analysis scripts.
In a specific implementation, a CANoe tool is adopted for vehicle-mounted CAN bus data acquisition. The data format recorded by the CANoe tool is generally composed of two formats, ASC and BLF. The BLF (Binary Logging Format) binary data file is a binary file, and is compressed, so that the physical value cannot be directly seen, and the physical value needs to be put in a CANoe tool for viewing. In this example, the CANoe function may be carried by the data analysis script to parse the BLF file.
The pre-configured data analysis script may be a scripting tool that may implement the reading and analysis operations of the DBC file and the BLF file.
In this example, the data analysis script may be a Python script, not limited thereto, but may also be a JavaScript script, VBScript script, perl script, PHP script, ruby script, or the like. In particular, the specific script type of the data analysis script may be determined according to the service requirement, which is not limited in this embodiment.
In a specific implementation, when the CAN message data analysis is required, the DBC file and the BLF file CAN be read first. The file reading process may be specifically described in detail below in connection with fig. 2.
Referring to fig. 2, a flowchart of steps of a file reading method according to an embodiment of the present application is shown. As shown in fig. 2, the file reading method may include: step 201.
Step 201: and calling the data analysis script to read the DBC file and the BLF file in the vehicle-mounted controller.
In this embodiment, when the CAN data in the vehicle-mounted controller is analyzed, the data analysis script may be called to read the DBC file and the BLF file in the vehicle-mounted controller.
It can be understood that the data analysis script contains file reading codes which can be used for reading DBC files and BLF files in the vehicle-mounted controller, so that manual reading of the DBC files and the BLF files can be avoided, and time and cost for reading the DBC files and the BLF files can be saved.
After the DBC file in the vehicle-mounted controller is read by calling the data analysis script, the DBC file can be analyzed by calling the data analysis script so as to obtain DBC message information of each frame of message in the DBC file. The specific parsing process may be described in detail as follows in connection with fig. 3.
Referring to fig. 3, a step flowchart of a DBC message information obtaining method provided by an embodiment of the present application is shown. As shown in fig. 3, the DBC message information obtaining method may include: step 301 and step 302.
Step 301: and calling the data analysis script to analyze the DBC file to obtain message identification information, signal distribution information, signal precision offset information and signal names of each frame of message in the DBC file.
In this embodiment, after the data analysis script is called to read the DBC file in the vehicle-mounted controller, the data analysis script may be called to analyze the DBC file, so as to obtain information such as message identification information, signal distribution information, signal precision offset information, signal name, and the like of each frame of message in the DBC file.
After the data analysis script is called to parse the DBC file to obtain the message identification information, the signal distribution information, the signal precision offset information and the signal name of each frame of message in the DBC file, step 302 is executed.
Step 302: and using the message identification information, the signal distribution information, the signal precision offset information and the signal name as the DBC message information.
After the data analysis script is called to analyze the DBC file to obtain the message identification information, the signal distribution information, the signal precision offset information and the signal name of each frame of message in the DBC file, the message identification information, the signal distribution information, the signal precision offset information and the signal name of each frame of message can be used as DBC message information.
According to the embodiment of the application, the DBC file is analyzed through the data analysis script, manual analysis is not needed, the analysis efficiency of the DBC file can be improved, and the time and labor cost for analyzing the DBC file are saved.
After the pre-configured data analysis script is called to parse the DBC file to obtain DBC message information of each frame of message in the DBC file, step 103 is executed.
Step 102: and calling the data analysis script to analyze the BLF file to obtain BLF message information in each frame of message in each frame of BLF file.
After the data analysis script is called to read the BLF file in the vehicle-mounted controller, the data analysis script can be called to analyze the BLF file so as to obtain BLF message information in each frame message in each frame BLF file. Specifically, the BLF file may be parsed by using a data analysis script, and signal values in each frame of message in each frame of BLF file may be sequentially read, to extract signals to be analyzed.
After the data analysis script is invoked to parse the BLF file to obtain BLF message information in each frame of message in each frame of BLF file, step 103 is performed.
Step 103: and carrying out data analysis on the DBC message information and the BLF message information to obtain the test statistical data of the BLF file.
After the DBC file is analyzed by calling the pre-configured data analysis script to obtain DBC message information of each frame of message in the DBC file and the BLF file is analyzed by calling the data analysis script to obtain BLF message information of each frame of message in the BLF file, data analysis can be carried out on the DBC message information and the BLF message information to obtain test statistical data of the BLF file. Specifically, the DBC message information and the BLF message information may be data analyzed using different analysis modes to generate test statistics. In this example, the different analysis modes may include: the single signal analysis mode refers to analysis of signals composed of single signals, and analysis of distribution, maximum value, minimum value, average value and other data in different BLF test data. The multi-signal analysis mode is to analyze a composite signal composed of a plurality of signals, firstly provide data to generate complete composite signal data, then perform statistical analysis on characteristic values of the composite signal data, and finally generate a dynamic data video for observing the change rule of the dynamic data video.
According to the scheme provided by the embodiment of the application, the CAN DBC file and the BLF file are analyzed through the data analysis script, the test statistical data of different signals are automatically generated, the analysis work of various signals in the BLF CAN be rapidly completed, a plurality of analysis modes are provided, the iterated test data CAN be rapidly analyzed after the software is updated, the comparison effect is achieved, the problems that the manual analysis workload of the existing CAN data is large, the regression test efficiency is low, and the analysis requirement cannot be met are solved, and the test analysis time and the labor cost are saved.
In a specific implementation, after obtaining the DBC message information and the BLF message information, the DBC message information and the BLF message information may also be added to a data list, and data analysis is performed through the data list. This implementation may be described in detail below in conjunction with fig. 4.
Referring to fig. 4, a flowchart of steps of a test statistic data obtaining method according to an embodiment of the present application is shown. As shown in fig. 4, the test statistic data obtaining method may include: step 401 and step 402.
Step 401: and adding the DBC message information and the BLF message information into a data list.
In this embodiment, after a pre-configured data analysis script is called to analyze a DBC file to obtain DBC message information of each frame of message in the DBC file, and a data analysis script is called to analyze a BLF file to obtain BLF message information of each frame of message in each frame of BLF file, the DBC message information and the BLF message information may be added to a data list.
It can be appreciated that the DBC message information and the BLF message information may be stored in association with the message identification information as an index in the data list.
After adding the DBC message information and the BLF message information to the data list, step 402 is performed.
Step 402: and carrying out data analysis on the information corresponding to each BLF file in the data list to obtain the test statistical data of the BLF files.
After the DBC message information and the BLF message information are added into the data list, data analysis can be performed on the information corresponding to each BLF file in the data list, and test statistical data of the BLF files are obtained.
According to the embodiment of the application, the DBC message information and the BLF message information are added into the data list, and the test data analysis of the BLF text is carried out according to the data list, so that the DBC message information and the BLF message information corresponding to each message identifier can be accurately identified, and the analysis accuracy is improved.
In this embodiment, the signal composed of the single signal may be analyzed, and its distribution, maximum value, minimum value, average value, etc. in different blf test data may be analyzed. This implementation may be described in detail below in conjunction with fig. 5.
Referring to fig. 5, a flowchart of steps of a test statistic determining method according to an embodiment of the present application is shown. As shown in fig. 5, the test statistic determining method may include: step 501, step 502 and step 503.
Step 501: and acquiring first DBC message information and first BLF message information corresponding to the same message identification information from the data list.
In this embodiment, after adding the DBC message information and the BLF message information to the data list, the first DBC message information and the first BLF message information corresponding to the same message identification information may be obtained from the data list.
After the first DBC message information and the first BLF message information corresponding to the same message identification information are obtained from the data list, step 502 is executed.
Step 502: and determining a signal value corresponding to each frame of message based on the first DBC message information and the first BLF message information.
After the first DBC message information and the first BLF message information corresponding to the same message identification information are obtained from the data list, a signal value corresponding to each frame of message may be determined based on the first DBC message information and the first BLF message information. Specifically, analysis may be performed based on the signal distribution and the signal precision offset information in the first DBC message information, so as to obtain a signal value corresponding to each frame of message in the first BLF message information.
After determining the signal value corresponding to each frame of message based on the first DBC message information and the first BLF message information, step 503 is performed.
Step 503: for each BLF file, determining test statistical data of the BLF file based on signal values of each frame of message in the BLF file.
After determining the signal value corresponding to each frame of message based on the first DBC message information and the first BLF message information, test statistics of the BLF file may be determined for each BLF file based on the signal value of each frame of message in the BLF file. Wherein the test statistics may include: at least one of a maximum value, a minimum value, an average value, a data distribution, and the like.
In a specific implementation, signal values in the list are analyzed, the maximum value, the minimum value, the average value and the data distribution of the data are counted, the data distribution in different BLF files is summarized and compared, and the left track pavement type is taken as an example, as shown in fig. 8, and the distribution of a single signal in a single BLF file provided by the embodiment of the application is shown.
In this embodiment, a composite signal composed of a plurality of signals may be analyzed, first, data is provided to generate complete composite signal data, then, statistical analysis is performed on the characteristic values of the composite signal data, and finally, dynamic data video and the like are generated to be used for observing the change rule of the dynamic data video. This implementation may be described in detail below in conjunction with fig. 6.
Referring to fig. 6, a flowchart of steps of another test statistic determination method according to an embodiment of the application is shown. As shown in fig. 6, the test statistic determining method may include: step 601, step 602 and step 603.
Step 601: and acquiring a plurality of DBC message information and a plurality of BLF message information at the same time from the data list.
In this embodiment, the composite signal is often formed by integrating a plurality of signals, as shown in fig. 9, taking elevation data as an example, 150 elevation data points received in the same message period are acquired first, and an elevation curve is generated by integrating the data points, where the elevation curve represents an elevation value in a range of 15 meters in front of the current time.
After the DBC message information and the BLF message information are added into the data list, a plurality of DBC message information and a plurality of BLF message information at the same time can be obtained from the data list.
After the multiple DBC message information and the multiple BLF message information at the same time are obtained from the data list, step 602 is performed.
Step 602: and determining composite signal data at each moment based on the DBC message information and the BLF message information.
After the multiple pieces of DBC message information and the multiple pieces of BLF message information at the same time are obtained from the data list, composite signal data at each time can be determined based on the multiple pieces of DBC message information and the multiple pieces of BLF message information. For example, for each BLF file, composite signal data at a plurality of times may be included, and the composite signal data at each time may be analyzed by signal distribution and signal accuracy offset information in DBC message information at each time.
It will be appreciated that the above examples are only examples listed for better understanding of the technical solution of the embodiments of the present application, and are not to be construed as the only limitation of the present embodiments.
After determining the composite signal data for each time based on the plurality of DBC message information and the plurality of BLF message information, step 603 is performed.
Step 603: and determining test statistical data of each BLF file based on the composite signal data of different moments in each message period in the BLF file.
After determining the composite signal data at each time based on the plurality of DBC message information and the plurality of BLF message information, test statistics of each BLF file may be determined for the BLF file based on the composite signal data at different times within each message period in the BLF file.
In a specific implementation, in order to ensure that the peak value of the elevation data is always within the error range, the peak values at different time points are extracted through the data analysis script, and a curve of the peak value changing along with time is drawn, so that the curve of the peak value changing along with time can be used as test statistical data, as shown in fig. 10.
In addition, in order to monitor the change of the elevation curve along with time, the data of each message period are collected through scripts, so that dynamic analysis videos are generated, and the dynamic analysis videos can be used as test statistical data. The elevation curve motion profile video in a single blf file may be as shown in fig. 11.
According to the embodiment of the application, through providing a plurality of signal analysis modes and deeply mining the connection among signals, the image and video report with the performance being compared is generated, so that all test reports can be generated by one key, the time for manually counting and writing the test reports is reduced, and the labor cost is saved.
The implementation process described above may be described as follows in connection with fig. 7.
Referring to fig. 7, a schematic diagram of a CAN packet data analysis flow provided by an embodiment of the present application is shown. As shown in fig. 7, BLF data (i.e., BLF file in this example) is collected by CANOE, and the DBC file and BLF data are parsed by data analysis script to obtain test statistics of single signal, such as 1, signal value distribution; 2. signal value statistics report; 3. comparison reports in different BLF files, etc. Test statistical data of the combined signal (namely the composite signal) can be obtained, such as 1, the dynamic change rule of the combined signal; 2. and reporting the change rule of the characteristic value in the combined signal.
According to the data analysis method provided by the embodiment of the application, the DBC file is analyzed by calling the pre-configured data analysis script, so that DBC message information of each frame of message in the DBC file is obtained. And calling a data analysis script to analyze the BLF file to obtain BLF message information in each frame of message in each frame of BLF file. And carrying out data analysis based on the DBC message information and the BLF message information to obtain the test statistical data of the BLF file. According to the embodiment of the application, the CAN DBC file and the BLF file are analyzed through the data analysis script, the test statistical data of different signals are automatically generated, the analysis work of various signals in the BLF CAN be rapidly completed, a plurality of analysis modes are provided, the test data after iteration CAN be rapidly analyzed after the software is updated, the comparison effect is achieved, the problems that the manual analysis workload of the existing CAN data is large, the regression test efficiency is low, and the analysis requirement cannot be met are solved, and the test analysis time and the labor cost are saved.
Referring to fig. 12, which shows a schematic structural diagram of a data analysis device according to an embodiment of the present application, as shown in fig. 12, the data analysis device 1200 may include the following modules:
the DBC message obtaining module 1210 is configured to invoke a pre-configured data analysis script to parse a DBC file, so as to obtain DBC message information of each frame of message in the DBC file;
a BLF message obtaining module 1220, configured to invoke the data analysis script to parse the BLF file, so as to obtain BLF message information in each frame of message in each frame of the BLF file;
and the test statistical data acquisition module 1230 is used for carrying out data analysis on the DBC message information and the BLF message information to obtain the test statistical data of the BLF file.
Optionally, the apparatus further comprises:
and the file reading module is used for calling the data analysis script to read the DBC file and the BLF file in the vehicle-mounted controller.
Optionally, the DBC message obtaining module 1210 includes:
the message information acquisition unit is used for calling the data analysis script to analyze the DBC file to obtain message identification information, signal distribution information, signal precision offset information and signal names of each frame of message in the DBC file;
and the DBC message acquisition unit is used for taking the message identification information, the signal distribution information, the signal precision offset information and the signal name as the DBC message information.
Optionally, the test statistics acquisition module 1230 includes:
a message information adding unit, configured to add the DBC message information and the BLF message information to a data list;
and the test statistical data acquisition unit is used for carrying out data analysis on the information corresponding to each BLF file in the data list to obtain the test statistical data of the BLF files.
Optionally, the test statistic data obtaining unit includes:
a first message information obtaining subunit, configured to obtain, from the data list, first DBC message information and first BLF message information corresponding to the same message identifier information;
a signal value determining subunit, configured to determine a signal value corresponding to each frame of message based on the first DBC message information and the first BLF message information;
a first statistics determining subunit, configured to determine, for each BLF file, test statistics of the BLF file based on a signal value of each frame of message in the BLF file;
the test statistics include: at least one of a maximum value, a minimum value, an average value, and a data distribution.
Optionally, the test statistic data obtaining unit includes:
a second message information obtaining subunit, configured to obtain multiple DBC message information and multiple BLF message information at the same time from the data list;
a composite signal data determining subunit, configured to determine composite signal data at each moment based on the multiple DBC message information and the multiple BLF message information;
and the second statistical data determining subunit is used for determining test statistical data of each BLF file based on the composite signal data at different moments in each message period in the BLF file.
Optionally, the data analysis script is a Python script.
The data analysis device provided by the embodiment of the application analyzes the DBC file by calling the pre-configured data analysis script to obtain DBC message information of each frame of message in the DBC file. And calling a data analysis script to analyze the BLF file to obtain BLF message information in each frame of message in each frame of BLF file. And carrying out data analysis based on the DBC message information and the BLF message information to obtain the test statistical data of the BLF file. According to the embodiment of the application, the CAN DBC file and the BLF file are analyzed through the data analysis script, the test statistical data of different signals are automatically generated, the analysis work of various signals in the BLF CAN be rapidly completed, a plurality of analysis modes are provided, the test data after iteration CAN be rapidly analyzed after the software is updated, the comparison effect is achieved, the problems that the manual analysis workload of the existing CAN data is large, the regression test efficiency is low, and the analysis requirement cannot be met are solved, and the test analysis time and the labor cost are saved.
The embodiment of the application provides electronic equipment, which comprises: the system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the computer program is executed by the processor to realize the data analysis method.
Fig. 13 shows a schematic structural diagram of an electronic device 1300 according to an embodiment of the application. As shown in fig. 13, the electronic device 1300 includes a Central Processing Unit (CPU) 1301 that can perform various suitable actions and processes according to computer program instructions stored in a Read Only Memory (ROM) 1302 or computer program instructions loaded from a storage unit 1308 into a Random Access Memory (RAM) 1303. In the RAM1303, various programs and data required for the operation of the electronic device 1300 can also be stored. The CPU1301, ROM1302, and RAM1303 are connected to each other through a bus 1304. An input/output (I/O) interface 1305 is also connected to bus 1304.
Various components in electronic device 1300 are connected to I/O interface 1305, including: an input unit 1306 such as a keyboard, mouse, microphone, etc.; an output unit 1307 such as various types of displays, speakers, and the like; storage unit 1308, such as a magnetic disk, optical disk, etc.; and a communication unit 1309 such as a network card, a modem, a wireless communication transceiver, or the like. The communication unit 1309 allows the electronic device 1300 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The various processes and treatments described above may be performed by processing unit 1301. For example, the methods of any of the embodiments described above may be implemented as a computer software program tangibly embodied on a computer-readable medium, such as storage unit 1308. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 1300 via the ROM1302 and/or the communication unit 1309. When the computer program is loaded into RAM1303 and executed by CPU1301, one or more actions in the method described above may be performed.
The embodiment of the application provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the processes of the above-mentioned data analysis method embodiment, and can achieve the same technical effects, so that repetition is avoided, and no further description is given here. Wherein the computer readable storage medium is selected from Read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are to be protected by the present application.
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 solution. 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.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the units is merely a logical function division, and there may be other manners of dividing the units into actual implementations, for example, multiple units or groups may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims (10)

1. A method of data analysis, the method comprising:
calling a pre-configured data analysis script to analyze a DBC file to obtain DBC message information of each frame of message in the DBC file;
invoking the data analysis script to analyze the BLF file to obtain BLF message information in each frame of message in each frame of BLF file;
and carrying out data analysis on the DBC message information and the BLF message information to obtain the test statistical data of the BLF file.
2. The method of claim 1, further comprising, before invoking a pre-configured data analysis script to parse a DBC file to obtain DBC message information for each frame of message in the DBC file:
and calling the data analysis script to read the DBC file and the BLF file in the vehicle-mounted controller.
3. The method of claim 1, wherein the calling the pre-configured data analysis script parses the DBC file to obtain DBC message information for each frame of message in the DBC file, comprises:
calling the data analysis script to analyze the DBC file to obtain message identification information, signal distribution information, signal precision offset information and signal names of each frame of message in the DBC file;
and using the message identification information, the signal distribution information, the signal precision offset information and the signal name as the DBC message information.
4. The method of claim 1, wherein the performing data analysis on the DBC message information and the BLF message information to obtain test statistics of the BLF file includes:
adding the DBC message information and the BLF message information into a data list;
and carrying out data analysis on the information corresponding to each BLF file in the data list to obtain the test statistical data of the BLF files.
5. The method of claim 4, wherein the performing data analysis on the information corresponding to each BLF file in the data list to obtain the test statistics of the BLF file includes:
acquiring first DBC message information and first BLF message information corresponding to the same message identification information from the data list;
determining a signal value corresponding to each frame of message based on the first DBC message information and the first BLF message information;
determining test statistical data of each BLF file based on a signal value of each frame of message in the BLF file;
the test statistics include: at least one of a maximum value, a minimum value, an average value, and a data distribution.
6. The method of claim 4, wherein the performing data analysis on the information corresponding to each BLF file in the data list to obtain the test statistics of the BLF file includes:
acquiring a plurality of DBC message information and a plurality of BLF message information at the same time from the data list;
determining composite signal data at each moment based on the plurality of DBC message information and the plurality of BLF message information;
and determining test statistical data of each BLF file based on the composite signal data of different moments in each message period in the BLF file.
7. The method of any one of claims 1 to 6, wherein the data analysis script is a Python script.
8. A data analysis device, the device comprising:
the DBC message acquisition module is used for calling a pre-configured data analysis script to analyze the DBC file to obtain DBC message information of each frame of message in the DBC file;
the BLF message acquisition module is used for calling the data analysis script to analyze the BLF file to obtain BLF message information in each frame of message in each frame of BLF file;
and the test statistical data acquisition module is used for carrying out data analysis on the DBC message information and the BLF message information to obtain test statistical data of the BLF file.
9. An electronic device, comprising:
memory, a processor and a computer program stored on the memory and executable on the processor, which when executed by the processor implements the data analysis method of any one of claims 1 to 7.
10. A readable storage medium, characterized in that instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the data analysis method of any one of claims 1 to 7.
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