Processing Method and Statistical Method for Vehicle Fault Diagnosis Data in the Internet-Connected Environment

Abstract

The present invention provides a method for processing and a method for counting vehicle fault diagnosis data in a networked environment, including: when the first category of diagnosis data is not received at the current moment and the second category of diagnosis data and the monitoring and statistical data are not received at the current moment, it is determined that the first category of diagnosis data at the current moment is in a data packet loss state, and the first category of diagnosis data at the current moment is filled and formed according to the first category of diagnosis data at the previous moment; when the second category of diagnosis data or the monitoring and statistical data are received at the current moment, it is determined that the first category of diagnosis data at the current moment is in an automatic recovery state, and the first category of diagnosis data at the current moment is filled and formed according to the basic data in the first category of diagnosis data at the previous moment and the diagnosis conclusion data at the current moment. The present invention can make the diagnosis data more complete and accurate on the premise of ensuring real-time performance, and is convenient for statistical analysis of the fault diagnosis data.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a method for processing and a method for statistically analyzing vehicle fault diagnosis data in a networked environment. Background Art

[0002] With the gradual popularization of automotive intelligent networking technology, especially the iterative upgrade of autonomous driving technology, the requirement for data transmission ability is getting higher and higher. Through powerful data transmission, closed-loop data analysis can be realized, and then OTA iterative upgrade of vehicle-end software can be completed. Among them, the real-time performance of data transmission is also an embodiment of data transmission ability.

[0003] Currently, the higher the real-time performance of data transmission, the higher the probability of data packet loss. As a result, when the cloud server receives the diagnostic data transmitted from the vehicle end, it is difficult to distinguish whether the un-received diagnostic data fails to meet the trigger condition or there is a data packet loss situation. Based on incomplete diagnostic data, accurate analysis and statistics of faults cannot be carried out. Summary of the Invention

[0004] The present invention provides a method for processing and a method for statistically analyzing vehicle fault diagnosis data in a networked environment to solve the above problems.

[0005] The present invention provides a method for processing vehicle fault diagnosis data in a networked environment, including:

[0006] Obtaining real-time monitoring data transmitted from the vehicle end, where the real-time monitoring data includes fault diagnosis data and monitoring and statistical data; among them, the fault diagnosis data includes diagnosis data of multiple fault categories;

[0007] When the first-category diagnosis data is not received at the current moment, determining whether the second-category diagnosis data or the monitoring and statistical data is received at the current moment; where the first-category diagnosis data is the diagnosis data of one fault category determined from multiple fault categories, and the second-category diagnosis data is the diagnosis data of multiple fault categories excluding the first-category diagnosis data;

[0008] When the second-category diagnosis data and the monitoring and statistical data are not received at the current moment, determining that the first-category diagnosis data at the current moment is in a data packet loss state, and filling the first-category diagnosis data at the current moment according to the first-category diagnosis data at the previous moment;

[0009] When the second - category diagnostic data or monitoring and statistical data is received at the current moment, it is determined that the first - category diagnostic data at the current moment is in the automatic recovery state, and the first - category diagnostic data at the current moment is filled and formed based on the basic data in the first - category diagnostic data at the previous moment and the diagnostic conclusion data at the current moment; wherein, the value of the diagnostic conclusion data at the current moment is empty; the filled first - category diagnostic data at the current moment is used to form the diagnostic data table.

[0010] According to a method for processing vehicle fault diagnostic data in a connected environment provided by the present invention, after obtaining the real - time monitoring data transmitted back from the vehicle end, the method further includes:

[0011] When the first - category diagnostic data is received at the current moment, it is determined that the first - category diagnostic data at the current moment is in the normal state.

[0012] According to a method for processing vehicle fault diagnostic data in a connected environment provided by the present invention, after obtaining the real - time monitoring data transmitted back from the vehicle end, the method further includes:

[0013] Within the ignition cycle of the vehicle, if the first - category diagnostic data is not received, it is determined that the vehicle has not triggered the first fault category, and the state of the first - category diagnostic data being empty is maintained in the diagnostic data table composed of the fault diagnostic data.

[0014] The present invention also provides a method for statistically analyzing vehicle fault diagnostic data in a connected environment, including:

[0015] Based on the above - mentioned method for processing vehicle fault diagnostic data in a connected environment, the fault diagnostic data obtained from the vehicle end is processed to obtain a diagnostic data table;

[0016] Based on the diagnostic data table, statistical analysis is performed on different fault categories to obtain statistical results.

[0017] According to a method for statistically analyzing vehicle fault diagnostic data in a connected environment provided by the present invention, the statistical analysis of different fault categories based on the diagnostic data table includes:

[0018] When the first - category diagnostic data at the current moment is in the data packet loss state and the first - category diagnostic data at the previous moment is in the normal state, it is determined that the vehicle end continuously triggers the first fault category at the current moment, and the number of occurrences of the first fault category is counted as one.

[0019] According to a method for statistically analyzing vehicle fault diagnostic data in a connected environment provided by the present invention, the statistical analysis of different fault categories based on the diagnostic data table includes:

[0020] When the first category of diagnostic data at the current moment is in the automatic recovery state and the first category of diagnostic data at the next moment is in the normal state, it is determined that the vehicle end triggers the first fault category again at the next moment, and the number of occurrences of the first fault category is counted as two.

[0021] The present invention also provides a processing device for vehicle fault diagnostic data in a networked environment, including:

[0022] A monitoring data acquisition module, configured to acquire real-time monitoring data transmitted back by the vehicle end, where the real-time monitoring data includes fault diagnostic data and monitoring and statistical data; among them, the fault diagnostic data includes diagnostic data of multiple fault categories;

[0023] A data judgment module, configured to judge whether the second category of diagnostic data or monitoring and statistical data is received at the current moment when the first category of diagnostic data is not received at the current moment; among them, the first category of diagnostic data is diagnostic data of a fault category determined from multiple fault categories, and the second category of diagnostic data is diagnostic data of multiple fault categories excluding the first category of diagnostic data;

[0024] A data packet loss determination module, configured to determine that the first category of diagnostic data at the current moment is in the data packet loss state when the second category of diagnostic data and monitoring and statistical data are not received at the current moment, and fill and form the first category of diagnostic data at the current moment according to the first category of diagnostic data at the previous moment;

[0025] A recovery determination module, configured to determine that the first category of diagnostic data at the current moment is in the automatic recovery state when the second category of diagnostic data or monitoring and statistical data is received at the current moment, and fill and form the first category of diagnostic data at the current moment according to the basic data in the first category of diagnostic data at the previous moment and the diagnostic conclusion data at the current moment; among them, the diagnostic conclusion data at the current moment takes a null value; the filled first category of diagnostic data at the current moment is used to form a diagnostic data table.

[0026] The present invention also provides a statistical device for vehicle fault diagnostic data in a networked environment, including:

[0027] A diagnostic data table acquisition module, configured to process the fault diagnostic data acquired from the vehicle end based on the processing device for vehicle fault diagnostic data in the networked environment as described above to obtain a diagnostic data table;

[0028] A statistics module, configured to perform statistical analysis on different fault categories based on the diagnostic data table to obtain a statistical result.

[0029] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the processing method of vehicle fault diagnosis data or the statistical method of vehicle fault diagnosis data in the above-mentioned networked environment is implemented.

[0030] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the processing method of vehicle fault diagnosis data or the statistical method of vehicle fault diagnosis data in the above-mentioned networked environment is implemented.

[0031] The processing method and statistical method of vehicle fault diagnosis data in the networked environment provided by the present invention first determine whether the reason for the missing diagnosis data is data packet loss or automatic recovery, and then adopt corresponding data filling methods according to different reasons. Specifically, the data filling method corresponding to data packet loss is to directly fill the diagnosis data at the previous moment to form the diagnosis at the current moment; while the data filling method corresponding to automatic recovery is to fill the basic data in the first category of diagnosis data at the previous moment and the diagnosis conclusion data at the current moment to form the first category of diagnosis data at the current moment. Through the above data processing, the integrity of the diagnosis data can be ensured, and the reason for the missing data can also be clarified, making the subsequent fault statistical analysis more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 is a schematic flowchart of the processing method of vehicle fault diagnosis data in the networked environment provided by the present invention;

[0034] Figure 2 is a schematic flowchart of the statistical method of vehicle fault diagnosis data in the networked environment provided by the present invention;

[0035] Figure 3 is a structural block diagram of the processing device of vehicle fault diagnosis data in the networked environment provided by the present invention;

[0036] Figure 4 is a structural block diagram of the statistical device of vehicle fault diagnosis data in the networked environment provided by the present invention;

[0037] Figure 5 illustrates a schematic diagram of the physical structure of an electronic device. Detailed implementation manners

[0038] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some, rather than all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without making creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0039] Currently, the mainstream backhaul data includes the following categories: 1) Moment data based on specific events; 2) real-time monitoring data.

[0040] Among them, the real-time monitoring data further includes: a) heartbeat monitoring data, which is usually uploaded periodically at a fixed interval (such as 1 s - 5 s); b) fault diagnosis data, which is triggered for backhaul and is a kind of diagnostic data that is sent to the background together with the heartbeat monitoring data after being triggered; c) Metric statistical data, which is triggered for backhaul and is a kind of statistical data that is sent to the background together with the heartbeat monitoring data after being triggered.

[0041] Data backhaul has high requirements for real-time performance in vehicle operation, especially for commercial operation vehicles such as autonomous driving fleets Robotaxi, autonomous driving trucks Robotruck, autonomous driving buses Robobus, and logistics carts. In the above commercial operation vehicles, the real-time monitoring data needs to be uploaded to the background monitoring platform in real time to achieve the purpose of real-time monitoring and quick response.

[0042] Currently, in automotive autonomous driving systems with a complexity level of L2+ or above, fault diagnosis usually adopts triggered backhaul due to a large number of faults, that is, when no fault occurs, no fault diagnosis data is uploaded; when a fault is triggered, the corresponding fault diagnosis data is uploaded.

[0043] On the other hand, there is usually a conflicting relationship between the real-time requirement and the packet loss rate requirement in the signal transmission of the network connection. That is, given certain hardware, communication status, and 4G services, the higher the real-time requirement, the higher the corresponding packet loss rate will be; the lower the requirement for the packet loss rate, the lower the real-time performance will be. In automotive autonomous driving, there is a high real-time requirement for status monitoring, so a certain packet loss rate has to be tolerated. Under such conditions, it is easy to cause problems with the diagnostic data transmitted back from the vehicle terminal. Specifically, since the diagnostic data is uploaded in a triggered manner, that is, when there is no diagnostic report, the diagnostic data is not uploaded; and if data packet loss occurs, it will also result in no diagnostic data being uploaded. At this time, when analyzing the diagnostic data later, if a certain type of diagnosis is not triggered, it is impossible to distinguish whether this untriggered state is due to the disappearance of the diagnosis caused by the recovery of the fault or the disappearance caused by data packet loss.

[0044] If the disappearance of the diagnosis due to fault recovery and data packet loss cannot be distinguished, it will cause a very large statistical deviation. Specifically, when a certain type of fault diagnosis continuously occurs and reports the diagnosis category in each previous cycle, but only one frame is lost in the middle, and then continues to occur and report the diagnosis category in each subsequent cycle, then the lost frame will cause one original fault to be counted as two, and the original maintenance time of this fault will be counted as an average of half of the maintenance time. If the number of lost frames increases, and so on. For example, if the heartbeat frequency is 1Hz, a certain type of fault diagnosis persists for 1 hour without recovery, and 35 frames are lost out of 3600 frames during this period, with a packet loss rate of less than 1%, but the number of fault occurrences increases from 1 to 36, and the duration of the fault decreases from 3600s to 100s. This statistical deviation is huge and unacceptable, and it will directly lead to inaccurate final statistical results.

[0045] In addition, data packet loss is usually caused by external communication environment factors and protocol priority sequence factors. Packet loss generally causes the entire packet of the communication protocol to be lost at that moment, that is, the heartbeat monitoring data, diagnostic data, and Metric data are all lost simultaneously. And the probability that only the diagnostic data is lost while the heartbeat monitoring data and Metric data still remain normal is extremely low. The DDS communication commonly used by the domain controller of the autonomous driving system usually has an extremely low probability of such problems. The present invention makes use of this characteristic. When the fault diagnosis data is received in the cloud and before generating the diagnostic data table and entering the data lake, the diagnostic data table to be entered into the lake is improved through data processing, thereby effectively solving the above-mentioned statistical deviation problem.

[0046] The following specifically describes the method for processing and the method for statistics of vehicle fault diagnosis data in a network connection environment proposed by the present invention with reference to the accompanying drawings.

[0047] Figure 1It is a schematic flowchart of a method for processing vehicle fault diagnosis data in a networked environment provided by the present invention; as Figure 1 shown, a method for processing vehicle fault diagnosis data in a networked environment includes the following steps:

[0048] S101, obtain real-time monitoring data transmitted back from the vehicle end.

[0049] Among them, the real-time monitoring data includes fault diagnosis data and monitoring and statistical data. The fault diagnosis data includes diagnosis data of multiple fault categories. In this embodiment, the monitoring and statistical data refers to heartbeat monitoring data and Metric statistical data. The diagnosis data of multiple fault categories means that there may sometimes be multiple faults triggered by the vehicle end, and the diagnosis data corresponding to different categories of faults are each independent as a piece of data, and the data of different fault categories constitute the original fault diagnosis data.

[0050] In this step, the real-time monitoring data transmitted back from the vehicle end is the original data. Due to the requirement for real-time performance, data packet loss is bound to occur in the original data. Specifically for the fault diagnosis data, it is necessary to further determine whether the missing part of the diagnosis data is caused by data packet loss or because the corresponding fault has automatically recovered and the corresponding diagnosis data has not been triggered for upload, and then complete the filling of the original fault diagnosis data according to the two different reasons to form complete fault diagnosis data.

[0051] It should be noted that the heartbeat monitoring data, fault diagnosis data, and Metric statistical data are all at the same fixed time period (such as every whole second moment in UTC time), and the three will be uploaded to the cloud synchronously in the same packet of real-time data packets of the same communication protocol. The difference is that the heartbeat is in each cycle's data packet, while the fault diagnosis data and Metric statistical data only appear in the transmitted data packets when the trigger conditions are met.

[0052] S102, when the first category of diagnosis data is not received at the current moment, determine whether the second category of diagnosis data or monitoring and statistical data is received at the current moment.

[0053] Among them, the first-category diagnostic data is the diagnostic data of a fault category determined from multiple fault categories, and the second-category diagnostic data is the diagnostic data of multiple fault categories excluding the first-category diagnostic data. Specifically, since multiple different faults may be triggered at the vehicle end at the same time, and each category of fault corresponds to a piece of diagnostic data, it is necessary to judge and process the diagnostic data of each category. Therefore, the diagnostic data of a certain fault category in the diagnostic data is used as the first-category diagnostic data, and specific processing is carried out around this first-category diagnostic data. After the processing is completed, another fault category's diagnostic data is reselected as the first-category diagnostic data for further processing until all the diagnostic data corresponding to the fault categories is processed. The second-category diagnostic data is relative to the first-category diagnostic data. When it is determined to process the diagnostic data of a certain category first among multiple fault categories, the remaining diagnostic data of other fault categories is classified as the second-category diagnostic data.

[0054] Table 1 Schematic Table of Original Fault Diagnosis Data

[0055] Vehicle Number Date and Time Diagnosis ID Diagnosis Version Diagnosis Value ...... UUID 000001 10:50:00 00000001 001 1 ...... xxxxx 000001 10:50:00 00000002 001 1 ...... xxxxx 000001 10:50:00 00000003 001 1 ...... xxxxx 000001 10:50:00 00000004 001 1 ...... xxxxx

[0056] As shown in Table 1, the vehicle number is the identification number of the vehicle end, used to distinguish the fault diagnosis data transmitted back from different vehicle ends to the cloud server. The date and time (the year, month, and day information is omitted in Table 1 and also includes the year, month, and day time information in actual applications) is the time when the fault diagnosis data is received. The diagnostic ID is the identification number of different fault categories. At the moment of 10:50:00, 4 different categories of faults are triggered at the vehicle end, and each fault category is distinguished by a different diagnostic ID. The diagnostic version indicates that for each individual diagnostic ID, a version can be provided to manage the updated version status. Specifically, for autonomous driving, many diagnoses are related to the driving state, such as the yaw rate and lane departure. Usually, diagnoses are defined for values exceeding the critical value to ensure driving safety, and the size of this diagnostic critical value, the triggered anti-shake time, the corresponding Fallback level, whether to inhibit the activation of the AD mode, etc. can all be changed in different versions, and the best state can be repeatedly debugged. Each individual diagnostic ID has a corresponding version to help identify the corresponding values. The diagnostic value is the corresponding fault status value after the diagnosis is triggered (there may be multiple fault states corresponding to multiple values). If only 1 is used to represent a fault and 0 is used to represent no fault, the message will be sent to the cloud when the value = 1, and the message will not be sent to the cloud when the value = 0. It should be noted that in this embodiment, only 1 is used to represent a fault. In other embodiments of the present invention, different non-zero values can also be used to represent different fault states, and the present invention does not limit this.

[0057] Exemplarily, take the diagnostic data with a diagnostic ID of 00000001 in Table 1 as the first category of diagnostic data, then the three pieces of diagnostic data with diagnostic IDs of 00000002, 00000003, and 00000004 are regarded as the second category of diagnostic data. At the moment of 10:50:00, when the cloud server receives the diagnostic data with a diagnostic ID of 00000001, there is no need to determine whether the second category of diagnostic data or monitoring and statistical data is received at the moment of 10:50:00, that is, there is no need to process the diagnostic data with a diagnostic ID of 00000001. Further, take the diagnostic data with a diagnostic ID of 00000002 as the new first category of diagnostic data, and the three pieces of diagnostic data with diagnostic IDs of 00000001, 00000003, and 00000004 are regarded as the second category of diagnostic data, and then process the diagnostic data based on the above classification, and so on, to complete the processing of all fault diagnostic data.

[0058] In this step, if the diagnostic data corresponding to a certain diagnostic ID (i.e., the first category of diagnostic data) is not received at the current moment, it is necessary to further determine the reason for the missing diagnostic data corresponding to this diagnostic ID, specifically by using the diagnostic data corresponding to other diagnostic IDs (i.e., the second category of diagnostic data), heartbeat monitoring data, and Metric statistical data that are transmitted back to the cloud server together with the diagnostic data corresponding to this diagnostic ID.

[0059] S103, in the case where the second category of diagnostic data and monitoring and statistical data are not received at the current moment, determine that the first category of diagnostic data at the current moment is in a data packet loss state, and fill the first category of diagnostic data at the current moment based on the first category of diagnostic data at the previous moment; the filled first category of diagnostic data at the current moment is used to form a diagnostic data table.

[0060] In this step, if the cloud server not only does not receive the diagnostic data of a certain diagnostic ID at a certain moment, but also does not receive any data among the diagnostic data corresponding to other diagnostic IDs, heartbeat monitoring data, and Metric statistical data, that is, a whole packet is lost, it indicates that data packet loss occurs between the vehicle end and the cloud due to external communication environment factors or protocol priority sequence factors. At this time, determine that the reason for the missing diagnostic data of a certain diagnostic ID at this moment is data packet loss, and label the diagnostic data of a certain diagnostic ID at this moment as being in a data packet loss state. In specific practice, distinguish the reporting status of diagnostic data by adding a filled diagnostic status to the diagnostic data table to display the above-mentioned label.

[0061] After determining that the reason for the missing diagnostic data of a certain diagnostic ID at a certain moment is data packet loss, it is necessary to fill in the missing diagnostic data. Specifically, since the reason for its loss is packet loss caused by external communication environment factors and protocol priority sequence factors, the diagnostic data of the previous moment is directly filled into the current moment to form the diagnostic data of the current moment, ensuring the integrity of the diagnostic data table.

[0062] Table 2 Schematic Table 1 of Diagnostic Data before Filling for a Certain Diagnostic ID

[0063] Vehicle Number Date and Time Diagnosis ID Diagnosis Version Diagnosis Value ...... UUID 000001 10:50:00 00000001 001 1 ...... xxxxx 000001 10:50:01 00000001 001 1 ...... xxxxx 000001 10:50:03 00000001 001 1 ...... xxxxx

[0064] As shown in Table 2, taking the diagnostic data corresponding to diagnostic ID 00000001 as an example, if the set time interval for diagnostic data transmission is 1 s, then at 10:50:02, the diagnostic data corresponding to diagnostic ID 00000001 is missing. At the same time, the cloud server has not received the diagnostic data of other diagnostic IDs such as 00000002, 00000003, and 00000004. It should also be that the heartbeat monitoring data and Metric statistical data of the fault diagnosis data transmitted back to the cloud server have not been received. Therefore, the missing diagnostic data at 10:50:02 is caused by data packet loss. Therefore, it is directly filled according to the diagnostic data at 10:50:01, and the corresponding data status is marked in the newly added filled diagnostic status column. See Table 3 for details.

[0065] Table 3 Schematic Table 1 of Diagnostic Data after Filling for a Certain Diagnostic ID

[0066]

[0067] Among them, when the value of the filled diagnostic status is 2, it means that the reason for the missing diagnostic data at 10:50:02 is packet loss; when the value of the filled diagnostic status is 1, it means that the cloud server has normally received the diagnostic data transmitted back from the vehicle end. The date and time are automatically adjusted according to the data transmission frequency, and other contents are the same as those at 10:50:01.

[0068] It should be noted that if the first category of diagnostic data has not been received at the beginning, it means that a certain fault has not been triggered and there is no need to fill in the data.

[0069] S104, in the case of receiving the second category of diagnostic data or monitoring and statistical data at the current moment, determine that the first category of diagnostic data at the current moment is in the automatic recovery state, and fill and form the first category of diagnostic data at the current moment according to the basic data in the first category of diagnostic data at the previous moment and the diagnostic conclusion data at the current moment; among them, the value of the diagnostic conclusion data at the current moment is empty; the filled first category of diagnostic data at the current moment is used to form the diagnostic data table.

[0070] In this step, if there is diagnostic data of other diagnostic IDs, or heartbeat monitoring data, or Metric statistical data in the real-time monitoring data transmitted back from the vehicle end at the current moment, that is, the communication between the vehicle end and the cloud is in a normal state. At this time, it is determined that the reason for the lack of diagnostic data of a certain diagnostic ID at the current moment is that the fault of this ID has been automatically resolved, that is, the vehicle end has automatically resumed normal operation. Without triggering a fault, the diagnostic data will naturally not be transmitted back to the cloud server anymore. Under this condition, the data filling at the current moment is completed according to the diagnostic data of the previous moment. Specifically, the basic information of the diagnostic data of the previous moment is retained until the current moment, and the diagnostic result data at the current moment are all taken as empty values.

[0071] Still taking Table 2 mentioned above as an example, it is determined that the reason for the lack of data at 10:50:02 is that the fault has been automatically resolved. At this time, the basic data filling at 10:50:02 is completed according to the basic data (i.e., vehicle number, diagnostic ID, and date and time) in 10:50:01. It should be noted that the current moment is automatically updated according to the data transmission time interval and the previous moment. And the diagnostic conclusion data (i.e., diagnostic version, diagnostic value, UUID, etc.) are all empty (i.e., NULL), and the corresponding filled diagnostic status is represented by 0. The filled diagnostic data can be seen in Table 4.

[0072] Table 4 Schematic Table of Diagnostic Data after Filling for a Certain Diagnostic ID II

[0073]

[0074] The method for processing vehicle fault diagnostic data in a networked environment provided by the embodiments of the present invention first determines whether the reason for the lack of diagnostic data is data packet loss or automatic recovery, and then adopts corresponding data filling methods according to different reasons. Specifically, the data filling method corresponding to data packet loss is to directly fill the diagnostic data of the current moment according to the diagnostic data of the previous moment; while the data filling method corresponding to automatic recovery is to fill the basic data in the first category of diagnostic data of the previous moment and the diagnostic conclusion data of the current moment to form the first category of diagnostic data of the current moment. Through the above data processing, the integrity of the diagnostic data can be ensured, and the reason for the data loss can be clarified, making the subsequent fault statistical analysis more accurate.

[0075] Further, after obtaining the real-time monitoring data transmitted back from the vehicle end, the method further includes:

[0076] When the first category of diagnostic data is received at the current moment, it is determined that the first category of diagnostic data at the current moment is in a normal state.

[0077] Specifically, if the cloud server normally receives the diagnostic data transmitted back by the vehicle end due to a fault trigger, a normal label is attached to the diagnostic data, and in Tables 3 and 4, it is specifically distinguished by filling the diagnostic status value with 1.

[0078] The method for processing vehicle fault diagnostic data in the connected environment provided by the embodiment of the present invention determines that the received first-category diagnostic data is in a normal state, thereby facilitating subsequent statistical analysis such as fault duration and frequency.

[0079] Further, after obtaining the real-time monitoring data transmitted back by the vehicle end, the method further includes:

[0080] Within the ignition cycle of the vehicle, if the first-category diagnostic data is not received, it is determined that the vehicle has not triggered the first fault category, and the first-category diagnostic data is maintained as empty in the diagnostic data table composed of fault diagnostic data.

[0081] Specifically, the diagnostic data covered by the diagnostic data table is the data within one vehicle ignition cycle. If the diagnostic data corresponding to a certain diagnostic ID has not been received even once throughout the vehicle ignition cycle, it means that a certain fault has not occurred within the vehicle ignition cycle, and the above data filling process is not performed in the diagnostic data table, that is, the state where the diagnostic ID has not received any data is maintained.

[0082] It should be noted that the above data filling process is performed when the diagnostic data of a certain diagnostic ID appears within the vehicle ignition cycle, that is, when a certain fault is triggered within the vehicle ignition cycle, the subsequent missing diagnostic data is filled.

[0083] The method for processing vehicle fault diagnostic data in the connected environment provided by the embodiment of the present invention maintains the first-category diagnostic data as empty and does not perform data filling when the first fault category is not triggered within the vehicle ignition cycle, thereby preventing a significant increase in the data volume due to excessive data filling. This significantly increased data volume will affect the computing resources required for subsequent search and statistics, and improves the efficiency of subsequent statistical analysis.

[0084] Figure 2 It is a schematic flowchart of the statistical method for vehicle fault diagnostic data in the connected environment provided by the present invention; as Figure 2 shown, a statistical method for vehicle fault diagnostic data in the connected environment includes the following steps:

[0085] S201, process the fault diagnostic data obtained from the vehicle end based on the above method for processing vehicle fault diagnostic data in the connected environment to obtain a diagnostic data table.

[0086] In this step, the original fault diagnosis data obtained at the vehicle end is processed by the above-mentioned method for processing vehicle fault diagnosis data in the networked environment, so as to obtain complete fault diagnosis data, and then a corresponding diagnosis data table is formed according to the complete fault diagnosis data. Among them, the original fault diagnosis data is the data within one ignition cycle.

[0087] S202. Perform statistical analysis on different fault categories based on the diagnosis data table to obtain statistical results.

[0088] In this step, fault statistics and analysis are performed according to the complete diagnosis data table. Specifically, the time duration for which a fault category corresponding to a certain diagnosis ID persists can be determined according to the status of the diagnosis data and the date and time of the diagnosis data. Through various data statistical analysis methods such as counting the number of occurrences of a fault category corresponding to a certain diagnosis ID in the entire ignition cycle, the corresponding statistical results are obtained.

[0089] The statistical method for vehicle fault diagnosis data in the networked environment provided by the embodiments of the present invention processes the complete fault diagnosis data by using the above-mentioned method for processing vehicle fault diagnosis data in the networked environment, and then forms a corresponding diagnosis data table according to the complete fault diagnosis data. Based on this diagnosis data table, fault statistics and analysis are completed, so as to obtain more accurate statistical results.

[0090] Further, the performing statistical analysis on different fault categories based on the diagnosis data table includes:

[0091] When the first-category diagnosis data at the current moment is in a data packet loss state and the first-category diagnosis data at the previous moment is in a normal state, it is determined that the vehicle end continuously triggers the first fault category at the current moment, and the number of occurrences of the first fault category is counted as one time.

[0092] When the first-category diagnosis data at the current moment is in a data packet loss state and the first-category diagnosis data at the previous moment is in an automatic recovery state, it is determined that the vehicle end is still in the automatic recovery state at the current moment.

[0093] In this step, if the filled diagnosis status value of a certain diagnosis data in the diagnosis data table is 2 and the filled diagnosis status value at the previous moment is 1, no secondary statistics are performed during the fault count. Taking Table 3 as an example, since the reason for the data loss at 10:50:02 is packet loss and the statuses at 10:50:01 and 10:50:03 are both normal reporting statuses, it can be regarded that the intermediate 10:50:02 is also a fault occurrence moment, that is, the fault persists from 10:50:00 to 10:50:03, which is a continuous fault once.

[0094] Table 5 Schematic Table III of Diagnostic Data after Filling a Certain Diagnostic ID

[0095]

[0096] Taking Table 5 as an example again, the filled diagnostic status values at 10:53:02, 10:53:03, and 10:53:04 are all 2, indicating packet loss. The filled diagnostic statuses corresponding to the diagnostic data before (i.e., 10:53:01) and after (10:53:05) packet loss are both 1, that is, the diagnostic ID 00000001 is in a continuously reported state. Regarding 10:53:00 - 10:53:05 as the maintenance of the fault, it is still regarded as one fault during fault statistics.

[0097] In the method for statistically analyzing vehicle fault diagnosis data in a connected environment provided by the embodiments of the present invention, when the data is in a packet loss state and there is normal reporting before and after it, the statistics of the maintenance duration and number of faults are both processed with the lost frame data as the state where the fault is still triggered, ensuring the accuracy of the statistical results.

[0098] Further, the statistical analysis of different fault categories based on the diagnostic data table includes:

[0099] When the first - category diagnostic data at the current moment is in an automatic recovery state and the first - category diagnostic data at the next moment is in a normal state, it is determined that the vehicle end triggers the first fault category again at the next moment, and the number of occurrences of the first fault category is statistically counted as two.

[0100] In this step, if the filled diagnostic status value of a certain diagnostic data in the diagnostic data table is 0, and the filled diagnostic status value at the next moment is 1, then secondary statistics are required during the statistics of the number of faults. Taking Table 4 as an example, since the reason for the data loss at 10:50:02 is automatic recovery, that is, it indicates that the fault has disappeared. If the diagnostic data is in a normal reporting state at a subsequent time (i.e., at 10:50:03), in this situation, it is regarded as the recurrence of the fault, and the statistics of the fault maintenance time and number are different from the packet loss state. In Table 4, a total of 2 faults occurred. Among them, the first fault lasted from 10:50:00 to 10:50:01, and the second started from 10:50:03.

[0101] Table 6 Schematic Table IV of Diagnostic Data after Filling a Certain Diagnostic ID

[0102]

[0103] For another example, if the filled diagnostic data table is as shown in Table 6, since the filled diagnostic status value at 10:55:04 is 0 and the filled diagnostic status value at 10:55:05 is 2, that is, the previous moment was in the automatic recovery state, then in the case of packet loss at the next moment, the continuous fault at 10:55:05 and 10:55:06 has been resolved. And because normal reported diagnostic data appears at 10:55:07, a total of 2 faults occurred in Table 6. The duration of the first fault is from 10:55:00 to 10:55:01, and the duration of the second fault needs to be calculated starting from 10:55:07.

[0104] Table 7 Schematic Table V of Diagnostic Data after Filling for a Certain Diagnostic ID

[0105]

[0106] For another example, if the filled diagnostic data table is as shown in Table 7, since the filled diagnostic status value at 10:55:04 is 2 and the filled diagnostic status value at 10:55:05 is 0, that is, the previous moment was in the packet loss state, then in the case of automatic recovery at the next moment, the packet loss state is the continuous state where the fault is occurring at 10:57:01. A total of 2 faults occurred in Table 7. The duration of the first fault is from 10:55:00 to 10:55:04, and the duration of the second fault needs to be calculated starting from 10:55:07.

[0107] For the statistical method of vehicle fault diagnosis data in the networked environment provided by the embodiments of the present invention, when the data is in the automatic recovery state and there is still normal diagnostic data reported thereafter, the duration and number of faults are both statistically counted based on the recurrence of the fault, ensuring the accuracy of the statistical results.

[0108] Next, the processing device for vehicle fault diagnosis data in the networked environment provided by the present invention will be described. The processing device for vehicle fault diagnosis data in the networked environment described below can be correspondingly referred to the processing method for vehicle fault diagnosis data in the networked environment described above.

[0109] Figure 3 is the structural block diagram of the processing device for vehicle fault diagnosis data in the networked environment provided by the present invention; as Figure 3 shown, a processing device for vehicle fault diagnosis data in the networked environment includes

[0110] A monitoring data acquisition module 301, configured to acquire real-time monitoring data transmitted back from the vehicle terminal.

[0111] Among them, the real-time monitoring data includes fault diagnosis data and monitoring and statistical data. The fault diagnosis data includes diagnosis data of multiple fault categories. In this embodiment, the monitoring and statistical data refers to heartbeat monitoring data and Metric statistical data. The diagnosis data of multiple fault categories means that there may sometimes be multiple faults triggered at the vehicle end, and the diagnosis data corresponding to different fault categories are each independent as a piece of data. The data of different fault categories constitutes the original fault diagnosis data.

[0112] In this module, the real-time monitoring data transmitted back from the vehicle end is the original data. Due to the requirement for real-time performance, data packet loss is bound to occur in the middle of the original data. Specifically for the fault diagnosis data, it is necessary to further determine whether the missing part of the diagnosis data in the middle is caused by data packet loss or because the corresponding fault has automatically recovered and the corresponding diagnosis data has not been triggered for upload, and then complete the filling of the original fault diagnosis data according to two different reasons to form complete fault diagnosis data.

[0113] The data judgment module 302 is used to judge whether the second category of diagnosis data or the monitoring and statistical data is received at the current moment when the first category of diagnosis data is not received at the current moment.

[0114] Among them, the first category of diagnosis data is the diagnosis data of one fault category determined from multiple fault categories, and the second category of diagnosis data is the diagnosis data of multiple fault categories excluding the first category of diagnosis data. Specifically, since multiple different faults may be triggered at the vehicle end at the same time, and each category of fault corresponds to a piece of diagnosis data, it is necessary to judge and process the diagnosis data of each category. Therefore, the diagnosis data of a certain fault category in the diagnosis data is used as the first category of diagnosis data, and specific processing is carried out around this first category of diagnosis data. After the processing is completed, another fault category's diagnosis data is reselected as the first category of diagnosis data for processing until the diagnosis data corresponding to all fault categories is completed. The second category of diagnosis data is relative to the first category of diagnosis data. When it is determined to process the diagnosis data of a certain category first among multiple fault categories, the remaining diagnosis data of other fault categories is classified as the second category of diagnosis data.

[0115] As shown in Table 1, the car number is the identification number of the car end, which is used to distinguish the fault diagnosis data transmitted back to the cloud server from different car ends. The date and time (the year, month, and day information is omitted in Table 1, and the year, month, and day time information is also included in actual applications) is the time when the fault diagnosis data is received. The diagnosis ID is the identification number of different fault categories. At the moment of 10:50:00, the car end triggered 4 different categories of faults, and each fault category is distinguished by a different diagnosis ID. The diagnosis version means that for each individual diagnosis ID, a version can be provided to manage the updated version status. Specifically, for autonomous driving, many diagnoses are related to the driving state, such as the yaw rate and lane departure. Usually, diagnoses are defined for values exceeding the critical value to ensure driving safety. The size of the critical value of this diagnosis, the triggered anti-shake time, the corresponding Fallback level, whether to inhibit the activation of the AD mode, etc. can all be changed in different versions, and the best state can be repeatedly debugged. Each individual diagnosis ID has a corresponding version that can help identify the corresponding values. The diagnosis value is the corresponding fault status value after the diagnosis is triggered (there may be multiple fault states, corresponding to multiple values). If only 1 is used to indicate a fault and 0 is used to indicate no fault, then when the value = 1, the message will be sent to the cloud, and when the value = 0, the message will not be sent to the cloud. It should be noted that in this embodiment, only 1 is used to indicate a fault. In other embodiments of the present invention, different non-zero values can also be used to represent different fault states, and the present invention does not limit this.

[0116] Exemplarily, taking the diagnostic data with the diagnosis ID of 00000001 in Table 1 as the first category of diagnostic data, then the three pieces of diagnostic data with the diagnosis IDs of 00000002, 00000003, and 00000004 are all regarded as the second category of diagnostic data. At the moment of 10:50:00, when the cloud server receives the diagnostic data with the diagnosis ID of 00000001, it is not necessary to determine whether the second category of diagnostic data or monitoring and statistical data is received at the moment of 10:50:00, that is, there is no need to process the diagnostic data with the diagnosis ID of 00000001. Further, taking the diagnostic data with the diagnosis ID of 00000002 as the new first category of diagnostic data, the three pieces of diagnostic data with the diagnosis IDs of 00000001, 00000003, and 00000004 are all regarded as the second category of diagnostic data, and then the diagnostic data is processed based on the above classification, and so on, to complete the processing of all fault diagnosis data.

[0117] In this module, when the diagnostic data corresponding to a certain diagnostic ID (i.e., the first category of diagnostic data) is not received at the current moment, it is necessary to further determine the reason for the lack of the diagnostic data corresponding to this diagnostic ID. Specifically, it is determined by the diagnostic data corresponding to other diagnostic IDs (i.e., the second category of diagnostic data), the heartbeat monitoring data, and the Metric statistical data that are transmitted back to the cloud server together with the diagnostic data corresponding to this diagnostic ID.

[0118] The data packet loss determination module 303 is used to determine that the first category of diagnostic data at the current moment is in a data packet loss state when the second category of diagnostic data, the monitoring, and the statistical data are not received at the current moment, and fill in the first category of diagnostic data at the current moment based on the first category of diagnostic data at the previous moment; the filled first category of diagnostic data at the current moment is used to form the diagnostic data table.

[0119] In this module, if the cloud server not only does not receive the diagnostic data of a certain diagnostic ID at a certain moment, but also does not receive any data among the diagnostic data corresponding to other diagnostic IDs, the heartbeat monitoring data, and the Metric statistical data, it is determined that the reason for the lack of the diagnostic data of a certain diagnostic ID at that moment is data packet loss, and a label indicating that the data of a certain diagnostic ID at that moment is in a data packet loss state is added to the diagnostic data of that moment. In specific practice, the reporting status of the diagnostic data is distinguished by adding a filled diagnostic status to the diagnostic data table to display the above-mentioned label.

[0120] After determining that the reason for the lack of the diagnostic data of a certain diagnostic ID at a certain moment is data packet loss, it is necessary to fill in the missing diagnostic data. Specifically, since the reason for its lack is data packet loss caused by external communication environment factors and protocol priority sequence factors, the diagnostic data at the previous moment is directly filled into the current moment to form the diagnostic data at the current moment, ensuring the integrity of the diagnostic data table.

[0121] As shown in Table 2, taking the diagnostic data corresponding to the diagnostic ID 00000001 as an example, if the set time interval for transmitting the diagnostic data back is 1 s, then at 10:50:02, the diagnostic data corresponding to the diagnostic ID 00000001 is missing. At the same time, the cloud server also does not receive the diagnostic data of other diagnostic IDs such as 00000002, 00000003, and 00000004, and the heartbeat monitoring data and the Metric statistical data that should be transmitted back to the cloud server together with the fault diagnostic data are not received either. Then, the missing diagnostic data at 10:50:02 is caused by data packet loss. Therefore, it is directly filled according to the diagnostic data at 10:50:01, and the corresponding data status is marked in the newly added filled diagnostic status column. See Table 3 for details.

[0122] When the value of the fill diagnostic status is 2, it means that the reason for the missing diagnostic data at 10:50:02 is packet loss; when the value of the fill diagnostic status is 1, it means that the cloud server has received the diagnostic data sent back by the vehicle normally. The date and time are automatically adjusted according to the frequency of data return, and other contents use the data at 10:50:01.

[0123] It should be noted that if the first category of diagnostic data has not been received at the beginning, it means that a certain fault has not been triggered and there is no need to fill in the data.

[0124] The recovery determination module 304 is used to determine that the first category diagnostic data at the current moment is in an automatic recovery state when the second category diagnostic data or monitoring and statistical data is received at the current moment, and to fill in the first category diagnostic data at the current moment according to the basic data in the first category diagnostic data at the previous moment and the diagnostic conclusion data at the current moment; wherein the diagnostic conclusion data at the current moment takes a value of empty; the filled first category diagnostic data at the current moment is used to form a diagnostic data table.

[0125] In this module, if the real-time monitoring data sent back by the vehicle at the current moment contains diagnostic data of other diagnostic IDs, heartbeat monitoring data, or metric statistics, it is determined that the reason for the lack of diagnostic data of a certain diagnostic ID at the current moment is that the fault of the ID has been automatically resolved, that is, the vehicle has automatically resumed normal operation, and if no fault is triggered, the diagnostic data will naturally not be sent back to the cloud server. Under this condition, the data at the current moment is filled based on the diagnostic data at the previous moment. Specifically, the basic information of the diagnostic data at the previous moment is retained until the current moment, and the diagnostic result data at the current moment is set to null.

[0126] Still taking the above Table 2 as an example, it is determined that the reason for the missing data at 10:50:02 is that the fault is automatically resolved. At this time, the basic data at 10:50:02 is filled according to the basic data in 10:50:01 (i.e., vehicle number, diagnosis ID, and date and time). It should be noted that the current time is automatically updated according to the time interval of data return and the previous time. The diagnostic conclusion data (i.e., diagnostic version, diagnostic value, UUID, etc.) are all empty (i.e., NULL), and the corresponding filled diagnostic status is represented by 0. The filled diagnostic data is shown in Table 4.

[0127] The processing device for vehicle fault diagnosis data in a connected environment provided by an embodiment of the present invention first determines whether the reason for the missing diagnosis data is data packet loss or automatic recovery, and then adopts corresponding data filling methods according to different reasons. Specifically, the data filling method corresponding to data packet loss is to directly fill the diagnosis data at the previous moment to form the diagnosis at the current moment; while the data filling method corresponding to automatic recovery is to fill the basic data in the first category of diagnosis data at the previous moment and the diagnosis conclusion data at the current moment to form the first category of diagnosis data at the current moment. Through the above data processing, the integrity of the diagnosis data can be ensured, and the reason for the missing data can also be clarified, making the subsequent fault statistical analysis more accurate.

[0128] The statistical device for vehicle fault diagnosis data in a connected environment provided by the present invention will be described below. The statistical device for vehicle fault diagnosis data in a connected environment described below can be correspondingly referred to the statistical method for vehicle fault diagnosis data in a connected environment described above.

[0129] Figure 4 is the structural block diagram of the statistical device for vehicle fault diagnosis data in a connected environment provided by the present invention; as Figure 4 shown, a statistical device for vehicle fault diagnosis data in a connected environment includes:

[0130] A diagnostic data table acquisition module 401, configured to process the fault diagnosis data obtained from the vehicle end based on the above-mentioned processing device for vehicle fault diagnosis data in a connected environment, and obtain a diagnostic data table.

[0131] In this module, the original fault diagnosis data obtained from the vehicle end is processed through the above-mentioned processing method for vehicle fault diagnosis data in a connected environment, so as to obtain complete fault diagnosis data, and then a corresponding diagnostic data table is formed according to the complete fault diagnosis data. Among them, the original fault diagnosis data is the data within one ignition cycle.

[0132] A statistics module 402, configured to perform statistical analysis on different fault categories based on the diagnostic data table, and obtain a statistical result.

[0133] In this module, fault statistics and analysis are performed according to the complete diagnostic data table. Specifically, the duration maintained by the fault category corresponding to a certain diagnosis ID can be determined according to the status of the diagnostic data and the date and time of the diagnostic data. A lot of data statistical analysis methods such as counting the number of times the fault category corresponding to a certain diagnosis ID occurs by integrating the diagnostic data within the entire ignition cycle are used to obtain the corresponding statistical result.

[0134] The statistical device for vehicle fault diagnosis data in the networked environment provided by the embodiments of the present invention processes the complete fault diagnosis data by using the above-mentioned processing method for vehicle fault diagnosis data in the networked environment, and then forms a corresponding diagnosis data table based on the complete fault diagnosis data, and completes the statistics and analysis of faults on the basis of the diagnosis data table, so as to obtain a more accurate statistical result.

[0135] Figure 5 An entity structure diagram of an electronic device is exemplified, as Figure 5 shown. The electronic device may include: a processor 510, a communication interface 520, a memory 530, and a communication bus 540. Among them, the processor 510, the communication interface 520, and the memory 530 complete communication with each other through the communication bus 540. The processor 510 can call the logical instructions in the memory 530 to execute the processing method for vehicle fault diagnosis data in the networked environment. The method includes: obtaining real-time monitoring data transmitted back from the vehicle end, where the real-time monitoring data includes fault diagnosis data and monitoring and statistical data; among them, the fault diagnosis data includes diagnosis data of multiple fault categories; in the case that the diagnosis data of the first category is not received at the current moment, determining whether the diagnosis data of the second category or the monitoring and statistical data is received at the current moment; where the diagnosis data of the first category is the diagnosis data of one fault category determined from multiple fault categories, and the diagnosis data of the second category is the diagnosis data of multiple fault categories excluding the diagnosis data of the first category; in the case that the diagnosis data of the second category and the monitoring and statistical data are not received at the current moment, determining that the diagnosis data of the first category at the current moment is in a data packet loss state, and filling and forming the diagnosis data of the first category at the current moment according to the diagnosis data of the first category at the previous moment; in the case that the diagnosis data of the second category or the monitoring and statistical data is received at the current moment, determining that the diagnosis data of the first category at the current moment is in an automatic recovery state, and filling and forming the diagnosis data of the first category at the current moment according to the basic data in the diagnosis data of the first category at the previous moment and the diagnosis conclusion data at the current moment; where the diagnosis conclusion data at the current moment takes a null value; the filled diagnosis data of the first category at the current moment is used to form a diagnosis data table.

[0136] Or used to execute the statistical method for vehicle fault diagnosis data in the networked environment. The method includes: processing the fault diagnosis data obtained from the vehicle end based on the above-mentioned processing method for vehicle fault diagnosis data in the networked environment to obtain a diagnosis data table; performing statistical analysis on different fault categories based on the diagnosis data table to obtain a statistical result.

[0137] In addition, when the logical instructions in the above-mentioned memory 530 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0138] In another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is configured to execute the method for processing vehicle fault diagnosis data in a networked environment provided by the above-mentioned various methods. The method includes: obtaining real-time monitoring data transmitted back from the vehicle end, where the real-time monitoring data includes fault diagnosis data and monitoring and statistical data; wherein, the fault diagnosis data includes diagnosis data of multiple fault categories; in the case where the diagnosis data of the first category is not received at the current moment, determining whether the diagnosis data of the second category or the monitoring and statistical data is received at the current moment; wherein, the diagnosis data of the first category is the diagnosis data of a fault category determined from multiple fault categories, and the diagnosis data of the second category is the diagnosis data of multiple fault categories excluding the diagnosis data of the first category; in the case where the diagnosis data of the second category and the monitoring and statistical data are not received at the current moment, determining that the diagnosis data of the first category at the current moment is in a data packet loss state, and filling the diagnosis data of the first category at the current moment with the diagnosis data of the first category at the previous moment; in the case where the diagnosis data of the second category or the monitoring and statistical data is received at the current moment, determining that the diagnosis data of the first category at the current moment is in an automatic recovery state, and filling the diagnosis data of the first category at the current moment with the basic data in the diagnosis data of the first category at the previous moment and the diagnosis conclusion data at the current moment; wherein, the diagnosis conclusion data at the current moment takes a null value; the filled diagnosis data of the first category at the current moment is used to form a diagnosis data table.

[0139] Or it is configured to execute the method for statistically analyzing vehicle fault diagnosis data in a networked environment. The method includes: processing the fault diagnosis data obtained from the vehicle end based on the method for processing vehicle fault diagnosis data in the networked environment described above to obtain a diagnosis data table; statistically analyzing different fault categories based on the diagnosis data table to obtain a statistical result.

[0140] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative effort.

[0141] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0142] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. And these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A method for processing vehicle fault diagnosis data in a connected environment, characterized in that Including: Obtain the real-time monitoring data transmitted back from the vehicle end, where the real-time monitoring data includes fault diagnosis data and monitoring and statistical data; among them, the fault diagnosis data includes diagnosis data of multiple fault categories; In the case that the first category of diagnosis data is not received at the current moment, determine whether the second category of diagnosis data or monitoring and statistical data is received at the current moment; where the first category of diagnosis data is the diagnosis data of one fault category determined from multiple fault categories, and the second category of diagnosis data is the diagnosis data excluding the first category of diagnosis data among the diagnosis data of multiple fault categories; In the case that the second category of diagnosis data and monitoring and statistical data are not received at the current moment, determine that the first category of diagnosis data at the current moment is in a data packet loss state, and fill and form the first category of diagnosis data at the current moment according to the first category of diagnosis data at the previous moment; In the case that the second category of diagnosis data or monitoring and statistical data is received at the current moment, determine that the first category of diagnosis data at the current moment is in an automatic recovery state, and fill and form the first category of diagnosis data at the current moment according to the basic data in the first category of diagnosis data at the previous moment and the diagnosis conclusion data at the current moment; where the diagnosis conclusion data at the current moment takes a null value; the filled first category of diagnosis data at the current moment is used to form a diagnosis data table.

2. The method for processing vehicle fault diagnosis data in a networked environment according to claim 1, wherein After the step of obtaining the real-time monitoring data transmitted back from the vehicle end, the method further includes: In the case that the first category of diagnosis data is received at the current moment, determine that the first category of diagnosis data at the current moment is in a normal state.

3. The method for processing vehicle fault diagnosis data in a networked environment according to claim 1, wherein After the step of obtaining the real-time monitoring data transmitted back from the vehicle end, the method further includes: Within the ignition cycle of the vehicle, if the first category of diagnosis data is not received, determine that the vehicle has not triggered the first fault category, and maintain the state that the first category of diagnosis data is empty in the diagnosis data table composed of fault diagnosis data.

4. A statistical method for vehicle fault diagnosis data in a connected environment, characterized in that, Including: Process the fault diagnosis data obtained from the vehicle end based on the method for processing vehicle fault diagnosis data in the networked environment as described in any one of claims 1-3 to obtain a diagnosis data table; Perform statistical analysis on different fault categories based on the diagnosis data table to obtain statistical results.

5. The statistical method for vehicle fault diagnosis data in a connected environment according to claim 4, characterized in that The performing statistical analysis on different fault categories based on the diagnosis data table includes: In the case that the first category of diagnosis data at the current moment is in a data packet loss state and the first category of diagnosis data at the previous moment is in a normal state, determine that the vehicle end continuously triggers the first fault category at the current moment, and count the number of occurrences of the first fault category as one time.

6. The statistical method for vehicle fault diagnosis data in a networked environment according to claim 4, wherein, The performing statistical analysis on different fault categories based on the diagnosis data table includes: In the case that the first category of diagnosis data at the current moment is in an automatic recovery state and the first category of diagnosis data at the next moment is in a normal state, determine that the vehicle end triggers the first fault category again at the next moment, and count the number of occurrences of the first fault category as two times.

7. A processing device for vehicle fault diagnosis data in a networked environment, characterized in that Including: A monitoring data acquisition module, configured to obtain the real-time monitoring data transmitted back from the vehicle end, where the real-time monitoring data includes fault diagnosis data and monitoring and statistical data; among them, the fault diagnosis data includes diagnosis data of multiple fault categories; A data judgment module, configured to determine whether the second category of diagnostic data or the monitoring and statistical data is received at the current moment when the first category of diagnostic data is not received at the current moment; wherein, the first category of diagnostic data is the diagnostic data of a fault category determined from multiple fault categories, and the second category of diagnostic data is the diagnostic data of multiple fault categories excluding the first category of diagnostic data; A data packet loss determination module, configured to determine that the first category of diagnostic data at the current moment is in a data packet loss state when the second category of diagnostic data and the monitoring and statistical data are not received at the current moment, and fill the first category of diagnostic data at the current moment based on the first category of diagnostic data at the previous moment; A recovery determination module, configured to determine that the first category of diagnostic data at the current moment is in an automatic recovery state when the second category of diagnostic data or the monitoring and statistical data is received at the current moment, and fill the first category of diagnostic data at the current moment based on the basic data in the first category of diagnostic data at the previous moment and the diagnostic conclusion data at the current moment; wherein, the diagnostic conclusion data at the current moment takes a null value; the filled first category of diagnostic data at the current moment is used to form a diagnostic data table.

8. A statistical device for vehicle fault diagnosis data in a connected environment, characterized in that, Including: A diagnostic data table acquisition module, configured to process the fault diagnostic data obtained from the vehicle end by using the vehicle fault diagnostic data processing device according to claim 7 to obtain a diagnostic data table; A statistics module, configured to perform statistical analysis on different fault categories based on the diagnostic data table to obtain a statistical result.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the vehicle fault diagnostic data processing method according to any one of claims 1-3 or the vehicle fault diagnostic data statistics method according to any one of claims 4-6 in the networked environment.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the vehicle fault diagnostic data processing method according to any one of claims 1-3 or the vehicle fault diagnostic data statistics method according to any one of claims 4-6 in the networked environment.

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