Log data display method and device, equipment and medium

Abstract

The invention discloses a log data display method and device, equipment and a medium, and relates to the technical field of vehicle-mounted interconnection, and the method comprises the steps: obtaining whole vehicle log data, obtaining a sampling frequency according to the whole vehicle log data, obtaining an analysis result according to the sampling frequency, and outputting the analysis result to a drawing window for image drawing according to the analysis result, so as to display the log data. By analyzing the sampling frequency of the log data of the whole vehicle, drawing the image to display the analysis result and optimizing data processing and display, the data analysis efficiency is improved, and the user interaction is enhanced by visually displaying the data.

Description

Technical Field

[0001] The present invention relates to the field of vehicle-mounted interconnection technology, and in particular to a log data display method, device, equipment and medium. Background Art

[0002] With the rapid development of autonomous driving technology, advanced driver assistance systems (ADAS) are increasingly being used in vehicles. To ensure the safety and reliability of these systems, rigorous algorithm testing and validation are required. Observational calibration is a key step in this process. It involves acquiring vehicle status information via in-vehicle networks (such as CAN or Ethernet) and adjusting and optimizing algorithm parameters based on this information. Because the testing process generates a large amount of data, effective tools are needed to manage and analyze this data so that developers can quickly identify issues and make appropriate adjustments.

[0003] Currently, there are a variety of tools on the market that offer presentation methods for data analysis and visualization. For example: CANalyzer: Developed by Vector Informatik GmbH, it supports analysis, monitoring, and simulation of various network protocols, including CAN, LIN, and FlexRay. It can record and replay data and perform data plotting and analysis through its graphics module. PlotJuggler: An open-source, real-time data visualization and recording tool widely used in fields such as robotics and autonomous driving. It can quickly display and analyze real-time data from various sensors and controllers. These tools meet the needs of data analysis to a certain extent, but they have limitations in certain areas and cannot fully meet the demands of rapidly developing autonomous driving technology.

[0004] While existing data analysis and presentation methods offer some functionality, they suffer from practical limitations: limited data processing capabilities, difficulty handling large amounts of custom-formatted log data, insufficient support for non-standard data formats, and a lack of in-depth analysis of signal quality, such as signal continuity and sampling frequency stability. Existing tools also lack intuitive user interfaces, making it difficult for users to quickly configure and adjust analysis parameters, and implementing complex data manipulation and view customization. Therefore, a more accurate and high-capacity data presentation method is urgently needed to meet the growing demands of testing and verification. Summary of the Invention

[0005] The main purpose of this application is to provide a log data display method, device, equipment and medium, aiming to solve the technical problem of how to improve user experience.

[0006] To achieve the above objectives, this application proposes a log data display method, which includes:

[0007] Get vehicle log data;

[0008] Obtaining a sampling frequency according to the vehicle log data;

[0009] Obtaining analysis results according to the sampling frequency;

[0010] The analysis results are output to a drawing window for image drawing to display the log data.

[0011] In one embodiment, the step of obtaining the sampling frequency based on the vehicle log data includes:

[0012] By traversing the entire vehicle log data, a plurality of log information is obtained;

[0013] Obtaining, based on the plurality of log information, differences between a plurality of current row timestamp information and a previous row timestamp information;

[0014] The weighted average of the differences is calculated to obtain the sampling frequency.

[0015] In one embodiment, the step of obtaining the difference between the timestamp information of the current row and the timestamp information of the previous row according to the multiple log information includes:

[0016] Obtaining corresponding current row timestamp information according to the multiple log information;

[0017] Get the timestamp information of the first row of initialization;

[0018] Obtaining a first row difference value according to the first current row timestamp information and the initialized first row timestamp information;

[0019] The first row of current timestamp information is used as the initialized first row of timestamp information for traversal until the last row of difference is obtained, so as to obtain the difference between multiple current row timestamp information and the previous row timestamp information.

[0020] In one embodiment, the step of obtaining the analysis result according to the sampling frequency includes:

[0021] Obtaining a comparison result by comparing the sampling frequency with a preset frequency threshold;

[0022] Perform analysis based on the comparison result to obtain an analysis result;

[0023] The analysis results include:

[0024] When the comparison result shows that the sampling frequency exceeds the first preset frequency threshold, it is determined that data loss occurs;

[0025] When the comparison result shows that the sampling frequency does not exceed the second preset frequency threshold, it is determined that data is missing.

[0026] In one embodiment, the step of outputting the analysis result to a drawing window for image drawing to display the log data includes:

[0027] Create local coordinate axes and global coordinate axes in the drawing window;

[0028] The local coordinate axis or the global coordinate axis is selected according to the analysis result to obtain a log data list, and the log data can be displayed in a graphical form by checking the log data.

[0029] In one embodiment, after the step of selecting the local coordinate axis or the global coordinate axis according to the analysis result to obtain a log data list, the following steps are included:

[0030] Performing a selection operation through the drawing window to switch between different coordinate axis types;

[0031] When switching to a different axis type, the graphic display in the plot window is updated to reflect the new axis settings and log data bindings.

[0032] In one embodiment, the step of obtaining vehicle log data includes:

[0033] Get initial log data;

[0034] Obtaining a timestamp and data information according to the initial log data;

[0035] The plurality of data information are converted into data of the same format according to the timestamp to obtain the vehicle log data.

[0036] In addition, to achieve the above-mentioned purpose, the present application also proposes a log data display device, which includes:

[0037] Acquisition module, used to obtain vehicle log data;

[0038] A calculation module, configured to obtain a sampling frequency based on the vehicle log data;

[0039] An analysis module, configured to obtain analysis results according to the sampling frequency;

[0040] The drawing module is used to output the analysis results to a drawing window for image drawing to display the log data.

[0041] In addition, to achieve the above-mentioned purpose, the present application also proposes a medium, which is a computer-readable medium and stores a computer program. When the computer program is executed by a processor, the steps of the log data display method described above are implemented.

[0042] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the steps of the log data display method described above.

[0043] This application obtains vehicle log data, determines the sampling frequency based on the data, generates analysis results based on the sampling frequency, and outputs the analysis results to a drawing window for image rendering to display the log data. By analyzing the sampling frequency of vehicle log data and rendering the analysis results, data processing and display are optimized, improving data analysis efficiency. The intuitive display of data enhances user interaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0045] Figure 1 This is a flow chart of the first embodiment of the log data display method of this application;

[0046] Figure 2 This is a flow chart of the second embodiment of the log data display method of this application;

[0047] Figure 3 This is a schematic diagram of the module structure of the log data display device according to an embodiment of the present application;

[0048] Figure 4 Schematic diagram of the device structure of the hardware operating environment involved in the log data display method in the embodiment of the present application;

[0049] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0050] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0051] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0052] The main solution of the embodiment of the present application is: obtaining coordinate information of multiple sensors, obtaining multiple time frame information based on the multiple coordinate information, performing calculations based on the multiple time frame information to obtain multiple Hausdorff distances, performing outlier judgment based on the multiple Hausdorff distances, and obtaining a target fusion result.

[0053] Based on this, the present invention provides a log data display method. Figure 1 , Figure 1 This is a flow chart of the first embodiment of the log data display method of this application.

[0054] In this embodiment, the log data display method includes steps S10 to S40:

[0055] Step S10: Obtain vehicle log data.

[0056] It's important to note that vehicle log data typically includes sensor readings, controller status, actuator feedback, and environmental information, transmitted in real time via onboard communication networks such as CAN or Ethernet. Log data collection involves not only real-time recording but also data preprocessing, storage, and subsequent analysis. To ensure data integrity and accuracy, data verification and synchronization are often required to ensure time consistency across different data sources.

[0057] As the amount of data increases, traditional data processing methods cannot meet the needs of efficient analysis. This embodiment can receive and process large-scale vehicle log data based on the log analysis and drawing tool of this embodiment. The tool first preprocesses the log data, including data cleaning, format unification and outlier detection.

[0058] Furthermore, initial log data is obtained, and timestamps and data information are obtained from the initial log data. Based on the timestamps, the multiple data information is converted into data of the same format to obtain the complete vehicle log data. The raw log data obtained from the vehicle contains information from various sources, such as vehicle status data collected via the CAN bus or text logs stored in CSV or TXT formats. This raw data typically has its own timestamps and specific data formats. To enable unified analysis and processing of this diverse data, the initial log data must first be extracted and preprocessed to separate the timestamps and specific data information. Next, a specialized regularization tool is used to convert this data to a unified data format, such as [timestamp: name=value]. This ensures that information from different data sources can be correctly parsed and displayed on the same platform, thereby forming a complete complete vehicle log data set.

[0059] Next, advanced algorithms calculate the sampling frequency of each signal, a key indicator for assessing data quality. This analysis helps identify potential issues during data acquisition, such as dropped frames or oversampling. The results are then used to generate detailed reports that include not only sampling frequency statistics but also analysis of the signal's time and frequency domain characteristics.

[0060] Step S20: obtaining a sampling frequency according to the vehicle log data.

[0061] It's important to note that sampling frequency refers to the number of times data is collected per unit time. For autonomous driving systems, a high sampling frequency provides more detailed data, helping to capture subtle changes in vehicle operation. However, a too low sampling frequency may result in data loss and fail to accurately reflect the vehicle's actual state. To determine an accurate sampling frequency, the timestamps in the vehicle log data must first be analyzed. The data collection frequency can be determined by calculating the time interval between two consecutive data points. This process requires precise parsing and calculation of timestamps, often requiring the use of efficient algorithms to process large numbers of data points to ensure accuracy and efficiency. After determining the sampling interval for each data point, statistical analysis methods, such as calculating the average sampling interval and standard deviation, can be used to assess the sampling frequency of the entire dataset. Furthermore, visualization tools, such as plotting a histogram of the sampling intervals, can be used to visually display the distribution of the sampling frequencies. This helps identify anomalies in the data collection process, such as sudden changes in the sampling interval, which may be caused by sensor failure or data recording errors.

[0062] Furthermore, by traversing the entire vehicle log data, multiple log information is obtained, and based on the multiple log information, the difference between the timestamp information of the current row and the timestamp information of the previous row is obtained. When processing the entire vehicle log data, the system traverses the data line by line to extract the timestamp information from each record. For each record containing a timestamp, the system updates the current timestamp variable, current_ts, and compares it with the previous timestamp, last_ts. By calculating the difference between the current timestamp and the timestamp of the previous row, the difference between the two is obtained.

[0063] Specifically, the system obtains the corresponding current row timestamp information from multiple log messages. When processing vehicle log data, in order to accurately calculate the signal sampling frequency, it first needs to traverse every record in the log file. The system reads each record one by one and extracts the current row timestamp information from it.

[0064] It's important to understand that to begin the process of obtaining the timestamp information for the first row of the initialization, the system must first determine the timestamp information for the first row of the log file as the initialization time reference. This is accomplished by reading the first record in the log file, setting the timestamp information in this record as the timestamp information for the first row of the initialization. The first row difference is calculated based on the timestamp information for the current row and the timestamp information for the first row of the initialization. Next, the system compares the timestamp information for the current row with the timestamp information for the first row of the initialization to obtain the time difference for the first row. Using the current timestamp information for the first row of the initialization as the timestamp information for the first row of the initialization, the system iterates through the log file until the last row of the initialization is obtained, thereby obtaining multiple differences between the timestamp information for the current row and the timestamp information for the previous row. The system then updates the timestamp information for the current row to the timestamp information for the first row of the initialization, and then iterates through the next row of records, repeating the above steps to calculate the time difference for each subsequent row. This process continues until the last row of the log file is reached. In each iteration, the timestamp information for the current row is subtracted from the timestamp information for the previous row (which is now the updated initialization timestamp information) to obtain the new time difference value. In this way, the system can calculate the time differences between all records, row by row. These differences reflect the actual time intervals between different sampling points of the signal. This method not only helps identify the stability of signal sampling but also can be used to detect packet loss or other anomalies in signal transmission. Finally, by statistically analyzing these time differences, the signal sampling frequency can be further analyzed.

[0065] Furthermore, a weighted average is calculated on the differences to obtain the sampling frequency. When processing vehicle log data, the sampling frequency can be obtained by traversing each record and calculating the difference between adjacent timestamps. In order to more accurately reflect the true sampling frequency of the signal, these differences need to be statistically analyzed. Specifically, the sampling frequency of the signal can be estimated by calculating the weighted average of these differences. The weighted average can take into account the importance of different sampling intervals. For example, if certain sampling intervals appear more frequently, they will have a greater weight in the final calculation result. By taking a weighted average of these sampling intervals, a more stable and accurate sampling frequency estimate is obtained, which can maintain a high degree of accuracy even in the presence of occasional outliers or data packet loss.

[0066] Step S30: obtaining analysis results according to the sampling frequency.

[0067] It's important to understand that the calculated sampling frequency can be used to assess signal continuity and stability. Large fluctuations in the sampling frequency indicate possible signal transmission instability, such as network latency or hardware failure. Developers can use this information to further investigate the cause of the signal instability and take steps to address it. Furthermore, the analysis results can reveal any signal data loss. If the signal sampling interval significantly exceeds the normal range over a certain period of time—for example, if the sampling interval is greater than or less than 20% of the normal interval—this may indicate signal data loss during this period. In such cases, the system will generate a warning in the analysis report, alerting developers to these periods of signal loss and recommending further investigation.

[0068] During the analysis process, the calculated sampling frequency is first compared with preset performance indicators. These indicators include minimum and maximum sampling frequency thresholds, as well as the expected sampling frequency range. If the actual sampling frequency is lower than the minimum threshold, it may mean that data collection is not frequent enough to capture rapidly changing events. If the sampling frequency is higher than the maximum threshold, it may cause data overload, increase the processing burden, and potentially affect the system's real-time performance. Furthermore, the analysis results can reveal inconsistencies in the data collection process, such as abnormal fluctuations in the sampling frequency during certain time periods. These fluctuations may be caused by sensor failures, communication interruptions, or problems with the data processing algorithm. By identifying these inconsistencies, timely adjustments can be made to ensure data continuity and integrity.

[0069] Furthermore, sampling frequency analysis can help optimize data collection strategies. For example, the sampling frequency can be dynamically adjusted based on the vehicle's actual operating conditions and environmental changes to ensure data quality while reducing unnecessary data redundancy. This dynamic adjustment strategy improves data processing efficiency, reduces storage and transmission costs, and ensures rapid system response to critical events. Ultimately, the results of sampling frequency analysis can be used to generate detailed performance reports, providing data support for system design optimization and fault diagnosis. These reports can include statistical analysis of sampling frequency, trend charts, and abnormal event markers, providing developers with an intuitive and comprehensive data analysis perspective.

[0070] Step S40: Output the analysis result to a drawing window for image drawing to display the log data.

[0071] It's important to note that plotting the analysis results in a graph window is a key step in transforming complex log data into intuitive visual information. After cleaning and analyzing the log data and calculating the sampling frequency, the next step is to display this data in the form of a chart. The graphing tool is designed to help developers understand and diagnose problems more quickly through a graphical interface.

[0072] Specifically, local and global axes are created in the drawing window. Based on the analysis results, either local or global axes can be selected to display a list of log data. Log data can be displayed graphically by selecting the selected log data. The main interface of the drawing analysis tool offers two display modes: local and global axes, to suit different analysis needs. When local axis mode is selected, each signal has its own independent axis, clearly displaying the changing trends and details of each signal. This is particularly useful when signals vary widely or when detailed observation of individual signals is required. Global axis mode, on the other hand, plots all signals within the same coordinate system, making it easy to compare relative changes between different signals and helping to understand overall system behavior. Users can select the log data they want to display in the signal list bar on the drawing tool interface. Signal display can be easily controlled by simply checking the box next to the signal name on the left. This design allows developers to dynamically adjust the content of the drawing window based on their current analysis focus, avoiding unnecessary information and allowing them to focus on analyzing important signals.

[0073] Furthermore, the drawing window allows users to switch between different axis types by selecting them. When switching to a different axis type, the graphical display in the drawing window updates to reflect the new axis settings and log data binding. To better suit data visualization needs in different scenarios, different axis types are available for users to choose from. Users can select the desired axis type using specific controls in the drawing window, such as clicking a button or selecting from a drop-down menu. When the user selects local axis mode, the drawing window immediately responds by assigning a separate axis to each signal and adjusting the view to display the unique trends of those signals. Conversely, if the user selects global axis mode, the drawing window clears the existing plot content, sets a new shared axis, and then replots the data for all selected signals according to this common coordinate system. Whenever the axis type is changed, the drawing tool updates the graphical display to ensure that the signal curves accurately reflect the new axis settings. Furthermore, users can select specific log data to be displayed using the signal list bar, controlling the display of the signals with a simple checkbox. Once the signal selection changes, the drawing window will also be updated to only display the selected signal and rearranged according to the current coordinate axis type, so that the data presentation is more in line with the user's analysis needs.

[0074] This embodiment provides a log data display method that obtains vehicle log data, determines a sampling frequency based on the data, generates analysis results based on the sampling frequency, and outputs the analysis results to a drawing window for image rendering to display the log data. By analyzing the sampling frequency of the vehicle log data and rendering the analysis results, data processing and display are optimized, improving data analysis efficiency and enhancing user interaction through intuitive data display.

[0075] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 2 The log data display method step S30 further includes steps S301 to S302:

[0076] Step S301 : obtaining a comparison result by comparing the sampling frequency with a preset frequency threshold.

[0077] It's important to note that by iterating through each line of log data, the system first identifies and updates the timestamp information, thereby calculating the actual interval between signal sampling. Next, the system attempts to match signal names and assigns the corresponding value to the signal's structure instance. If no timestamp changes are detected between signal names, the system assumes that the data was sampled at a fixed 20 millisecond interval.

[0078] Once the new timestamp update is confirmed, the system checks all saved signal data to see if any signal failed to upload data at that time. At this time, it can be determined whether a signal has been missed by comparing it with the preset 20% sampling interval deviation threshold.

[0079] Step S302: perform analysis based on the comparison result to obtain an analysis result.

[0080] It's important to understand that when the system encounters the same signal name again without a timestamp update, it assumes the signal lacks timestamp information and records data at a fixed 20-millisecond interval. This ensures that signals are recorded at the expected frequency even in the absence of timestamps. Once a timestamp update is detected, the system enters the next sampling point. The system then checks whether any signals have not received updates during this period. If a signal is missing, it is flagged in the analysis report. This mechanism ensures that developers are promptly aware of any interruptions or loss in signal transmission. Data loss is considered if the sampling frequency exceeds the first preset frequency threshold; data loss is considered if the sampling frequency does not exceed the second preset frequency threshold. The system uses a 20% threshold to determine if a signal is missing. Specifically, if the updated timestamp (current_ts) exceeds the sampling frequency of the last valid timestamp (last_ts) by more than 1.2 times or less than 0.8 times, the system considers all signals at the current sampling point to be missing. This approach can effectively identify data loss due to device failure or other reasons and help developers quickly locate the moment the problem occurs.

[0081] This embodiment compares the sampling frequency with a preset frequency threshold to obtain a comparison result, and performs analysis based on the comparison result to obtain an analysis result. By comparing the sampling frequency with the preset threshold, signal anomalies can be accurately identified, improving data reliability and analysis efficiency.

[0082] This application also provides a log data display device, please refer to Figure 3 , the device comprises:

[0083] The acquisition module 10 is used to obtain vehicle log data.

[0084] The calculation module 20 is used to obtain the sampling frequency according to the vehicle log data.

[0085] The analysis module 30 is used to obtain analysis results according to the sampling frequency.

[0086] The drawing module 40 is used to draw an image according to the analysis result output to the drawing window to display the log data.

[0087] The log data display device provided in this application, employing the log data display method of the aforementioned embodiment, can address the technical problem of improving user experience. Compared to the prior art, the log data display device provided in this application has the same beneficial effects as the log data display method provided in the aforementioned embodiment. Other technical features of the log data display device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0088] In one embodiment, the calculation module 20 is further used to obtain multiple log information by traversing the entire vehicle log data; obtain the difference between multiple current row timestamp information and previous row timestamp information based on the multiple log information; and calculate the weighted average of the differences to obtain the sampling frequency.

[0089] In one embodiment, the calculation module 20 is further used to obtain corresponding current row timestamp information based on multiple log information; obtain the initialized first row timestamp information; obtain the first row difference based on the first current row timestamp information and the initialized first row timestamp information; traverse the first row current timestamp information as the initialized first row timestamp information until the last row difference is obtained, so as to obtain the difference between multiple current row timestamp information and the previous row timestamp information.

[0090] In one embodiment, the analysis module 30 is further configured to obtain a comparison result by comparing the sampling frequency with a preset frequency threshold; and perform analysis based on the comparison result to obtain an analysis result.

[0091] In one embodiment, the drawing module 40 is further used to create a local coordinate axis and a global coordinate axis in the drawing window; select the local coordinate axis or the global coordinate axis according to the analysis result, obtain a log data list, and allow the log data to be displayed in a graphical form by checking the log data.

[0092] In one embodiment, the drawing module 40 is further used to perform a selection operation through the drawing window to switch between different coordinate axis types; when switching to a different coordinate axis type, the graphic display in the drawing window is updated to reflect the new coordinate axis setting and log data binding.

[0093] In one embodiment, the acquisition module 10 is further configured to acquire initial log data; obtain a timestamp and data information based on the initial log data; and convert multiple data information into data of the same format based on the timestamp to obtain vehicle log data.

[0094] The present application provides a log data display device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the log data display method in the above-mentioned embodiment one.

[0095] Reference below Figure 4 , which shows a schematic diagram of the structure of a log data display device suitable for implementing the embodiments of the present application. The log data display device in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The log data display device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0096] like Figure 4As shown, the log data display device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 1002 or programs loaded from a storage device 1003 into a random access memory (RAM) 1004. RAM 1004 also stores various programs and data required for the operation of the log data display device. Processing device 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage device 1003 including, for example, a magnetic tape, hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the log data display device to communicate with other devices wirelessly or wired to exchange data. Although the figure shows a log data display device with various systems, it should be understood that it is not required to implement or have all of the systems shown. More or fewer systems can be implemented or provided instead.

[0097] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0098] The log data display device provided in this application, employing the log data display method described in the aforementioned embodiment, can address the technical problem of improving user experience. Compared to the prior art, the log data display device provided in this application achieves the same beneficial effects as the log data display method described in the aforementioned embodiment. Other technical features of this log data display device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0099] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0100] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0101] The present application provides a computer-readable medium having computer-readable program instructions (ie, a computer program) stored thereon, and the computer-readable program instructions are used to execute the log data display method in the above embodiment.

[0102] The computer-readable medium provided in this application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination thereof. More specific examples of computer-readable media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0103] The computer-readable medium may be included in the log data display device, or may exist independently without being incorporated into the log data display device.

[0104] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the log data display device, the log data display device can write computer program codes for performing the operations of the present application in one or more programming languages ​​or a combination thereof. The above-mentioned programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, C++, and also conventional procedural programming languages ​​such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0105] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0106] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0107] The readable medium provided in this application is a computer-readable medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described log data display method, which can solve the technical problem of how to improve the user experience. Compared with the prior art, the beneficial effects of the computer-readable medium provided in this application are the same as those of the log data display method provided in the above-described embodiment, and will not be elaborated here.

[0108] The present application also provides a computer program product, including a computer program, which implements the steps of the log data display method as described above when executed by a processor.

[0109] The computer program product provided in this application can solve the technical problem of how to improve user experience. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the log data display method provided in the above embodiment, and will not be repeated here.

[0110] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A log data display method, characterized in that: The method comprises: Get vehicle log data; Obtaining a sampling frequency according to the vehicle log data; Obtaining analysis results according to the sampling frequency; The analysis result is output to a drawing window for image drawing to display the log data.

2. The method according to claim 1, characterized in that The step of obtaining the sampling frequency according to the vehicle log data comprises: By traversing the vehicle log data, a plurality of log information is obtained; Obtaining differences between multiple current row timestamp information and previous row timestamp information according to the multiple log information; The difference is weighted averaged to obtain the sampling frequency.

3. The method according to claim 2, characterized in that The step of obtaining the difference between multiple current row timestamp information and previous row timestamp information according to the multiple log information includes: According to the multiple log information, obtain the corresponding current row timestamp information; Get the first row of initialized timestamp information; Obtaining a first row difference value according to the first current row timestamp information and the initialized first row timestamp information; The first row of current timestamp information is used as the first row of initialized timestamp information for traversal until the last row of difference is obtained, so as to obtain the difference between multiple current row timestamp information and the previous row timestamp information.

4. The method according to claim 1, characterized in that The step of obtaining the analysis result according to the sampling frequency comprises: Obtaining a comparison result by comparing the sampling frequency with a preset frequency threshold; Perform analysis according to the comparison result to obtain an analysis result; The analysis results include: When the comparison result is that the sampling frequency exceeds the first preset frequency threshold, it is determined that data loss exists; When the comparison result is that the sampling frequency does not exceed the second preset frequency threshold, it is determined that data is missing.

5. The method according to claim 1, characterized in that The step of outputting the analysis result to a drawing window for image drawing to display the log data includes: Create local and global axes in the drawing window; The local coordinate axis or the global coordinate axis is selected according to the analysis result to obtain a log data list, and the log data can be displayed in a graphical manner by checking the log data.

6. The method according to claim 5, characterized in that After the step of selecting the local coordinate axis or the global coordinate axis according to the analysis result to obtain a log data list, the method further comprises: Performing a selection operation through the drawing window to switch between different coordinate axis types; When switching to a different axis type, the graphic display in the plot window is updated to reflect the new axis settings and log data bindings.

7. The method according to claim 1, characterized in that The step of obtaining vehicle log data includes: Get initial log data; According to the initial log data, obtaining a timestamp and data information; The plurality of data information are converted into data of the same format according to the timestamp to obtain the vehicle log data.

8. A log data display device, characterized in that: The device comprises: Acquisition module, used to obtain vehicle log data; A calculation module, used for obtaining a sampling frequency according to the vehicle log data; An analysis module, used to obtain analysis results according to the sampling frequency; The drawing module is used to output the analysis result to a drawing window for image drawing to display the log data.

9. A log data display device, characterized in that: The device comprises: a memory, a processor, and a log data display program stored in the memory and executable on the processor, wherein the log data display program is configured to implement the steps of the log data display method according to any one of claims 1 to 7.

10. A medium, characterized in that The medium stores a log data display program, and when the log data display program is executed by a processor, the steps of the log data display method according to any one of claims 1 to 7 are implemented.

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