CN113902233A - Vehicle safety early warning method, big data platform device, vehicle-mounted terminal and vehicle - Google Patents
Vehicle safety early warning method, big data platform device, vehicle-mounted terminal and vehicle Download PDFInfo
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Abstract
The invention provides a vehicle safety early warning method, a big data platform analysis device, a vehicle-mounted terminal, a computer storage medium and a vehicle, wherein the method comprises the following steps: acquiring fault alarm operation data; determining the fault type according to the fault alarm operation data and a vehicle early warning model; generating fault early warning information according to the fault type; and sending the fault early warning information to an early warning management end corresponding to the fault type. The vehicle safety early warning method provided by the embodiment of the invention analyzes the operation big data, pre-judges and early warns the fault in advance, guides the user to carry out rescue and fault analysis, and helps the maintenance personnel to accurately position the fault and the maintenance strategy when the fault occurs, thereby reducing the contradiction between the vehicle owner and the maintenance manufacturer and improving the user experience.
Description
Technical Field
The invention relates to the technical field of vehicles, in particular to a vehicle safety early warning method, a big data platform analysis device, a vehicle-mounted terminal, a computer storage medium and a vehicle.
Background
With the continuous improvement of the living standard of people, the possession quantity of family cars in China is improved year by year, and great convenience is brought to our lives.
The big data and artificial intelligence industry rises rapidly in recent years, brand new vitality is injected for the development of new energy automobiles, and a large number of micro-processing sensors and electronic devices are commonly adopted on new-generation new energy automobiles, and the number of the micro-processing sensors and the electronic devices can reach hundreds of thousands. Although manufacturing processes, other communication and processing technologies are continuously developed, the use of a large number of electronic control units and sensors necessarily leads to the increase of wiring harnesses and connectors of the whole electronic control system, thereby increasing the failure rate of each module, and the modern automobile industry has relatively perfect failure detection and maintenance systems.
However, since the vehicle fault detection system requires that a vehicle owner transfers a faulty vehicle to a nearby maintenance shop to use after finding a fault, when the maintenance shop performs maintenance, a worker of a maintenance manufacturer needs to use a professional fault analyzer to troubleshoot the vehicle fault, however, a fault code of the fault analyzer may not accurately indicate the fault problem, so that the vehicle owner and the maintenance shop contradict each other, and the fault analysis system is adopted to analyze the data of the vehicle after the fault occurs, so that the fault that the vehicle is about to occur cannot be prejudged and early warned in advance, so that a user does not have time to rescue in advance, and rescue and maintenance are passive at a high speed or in a remote place. Meanwhile, the vehicle-mounted computer of the vehicle is mainly used for comprehensive functions such as navigation positioning, network function, information prompt, entertainment function, safety function and the like, the fault detection function is not comprehensive, and a user can hardly obtain the specific condition of vehicle operation from the vehicle-mounted computer of the vehicle, so that the fault cannot be evaluated and prevented.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, one objective of the present invention is to provide a vehicle safety early warning method, which can monitor vehicle operation data in real time and improve user experience.
The second purpose of the invention is to provide a big data platform analysis device.
The third purpose of the invention is to provide a vehicle safety early warning method.
The fourth purpose of the invention is to provide a vehicle-mounted terminal.
A fifth object of the invention is to propose a non-transitory computer storage medium.
A sixth object of the invention is to propose a vehicle.
In order to achieve the above object, a first aspect of the present invention provides a vehicle safety precaution method, including: acquiring fault alarm operation data; determining the fault type according to the fault alarm operation data and a vehicle early warning model; generating fault early warning information according to the fault type; and sending the fault early warning information to an early warning management end corresponding to the fault type.
According to the vehicle safety early warning method provided by the embodiment of the invention, based on the preset vehicle early warning model, when the fault alarm operation data of the vehicle is acquired, the fault type is determined according to the fault alarm operation data and the vehicle early warning model, and the fault alarm information is sent to the early warning management end in time, namely, the fault type is refined based on the vehicle early warning model, the vehicle safety operation condition is evaluated in real time by acquiring the vehicle fault alarm operation data in real time, and the fault early warning information is sent to the early warning management end, so that the real-time monitoring and early warning of the vehicle safety are realized, the resource sharing between the vehicle and the vehicle enterprise is realized, the vehicle which is about to break down, the vehicle which has broken down or the intermittent slight early warning information is effectively managed, the early warning monitoring can be carried out on the vehicle of a user in advance, the maintenance of the user is convenient, and the fault analyzer can not accurately point out the fault problem, the contradiction between the vehicle owner and the maintenance manufacturer is caused, and therefore the user experience is improved.
In some embodiments, determining a fault scenario from the fault alert operational data and a vehicle early warning model comprises: inputting the fault alarm operation data into each vehicle early warning model in a vehicle early warning model database; obtaining the matching probability of the fault alarm operation data and each vehicle early warning model; determining a target vehicle early warning model with the highest probability of matching with the fault alarm operation data; and determining the fault type according to the target vehicle early warning model.
In some embodiments, the early warning administration end includes at least one of an after-market platform, a rescue maintenance platform, a vehicle 4S store, a vehicle enterprise host plant, and a user mobile terminal.
In some embodiments, the vehicle safety warning method further includes: acquiring vehicle data in each vehicle database of a vehicle data center; establishing a new vehicle early warning model according to the vehicle data; and updating a vehicle early warning model database according to the new vehicle early warning model, extracting a characteristic analysis result of the new vehicle early warning model, and sending the characteristic analysis result to the vehicle-mounted terminal.
In some embodiments, building a new vehicle early warning model from the vehicle data includes: the method comprises the steps of carrying out text analysis on vehicle public opinion data, carrying out analysis on driving behavior data, carrying out analysis on voice data and video image data in the driving process, and carrying out analysis on fault alarm operation data to obtain an analysis result so as to establish a vehicle early warning model.
In some embodiments, a vehicle safety warning method includes: and displaying the fault early warning information.
In order to achieve the above object, a second aspect of the present invention provides a big data platform analysis apparatus, including: a first processor; a display connected with the first processor; a first memory communicatively coupled to the first processor; the first memory stores a plurality of vehicle databases and instructions executable by the first processor, and the first processor implements the vehicle safety warning method of the above embodiment when executing the instructions.
According to the big data platform analysis device provided by the embodiment of the invention, the vehicle safety early warning method provided by the embodiment is realized when the first processor executes the instruction, the early warning monitoring can be carried out on the vehicle in advance, the maintenance by a user is facilitated, the contradiction between a vehicle owner and a maintenance manufacturer caused by the fact that a fault analyzer cannot accurately point out the fault problem is avoided, and the user experience is improved.
In order to achieve the above object, a vehicle safety warning method according to a third aspect of the present invention includes: acquiring vehicle communication bus data; determining that the vehicle has a fault according to the communication bus data and a preset alarm fault constraint rule, wherein the preset alarm fault constraint rule is a qualitative rule which is satisfied by the communication bus data and a corresponding preset threshold value; and sending fault alarm operation data to a big data platform analysis device.
According to the vehicle safety early warning method provided by the embodiment of the invention, based on the preset alarm fault constraint rule, when the real-time communication bus data of the vehicle meets the preset alarm fault constraint rule, the vehicle is determined to have a fault, and the fault alarm operation data is sent to the big data platform analysis device, so that the fault can be classified to further determine the scene and the fault type of the fault, more precise fault early warning is realized, data support is provided for vehicle safety early warning, the vehicle owner and the after-sales can know the fault of the vehicle in time, and the user experience is improved.
In some embodiments, the vehicle safety warning method further includes: receiving alarm fault constraint rule updating data; and updating an alarm fault qualitative rule database according to the alarm fault constraint rule.
In order to achieve the above object, a fourth aspect of the present invention provides a vehicle-mounted terminal, including: a second processor; a second memory communicatively coupled to the second processor; the second memory stores instructions executable by the second processor, and the instructions, when executed by the second processor, implement the vehicle safety precaution method of the above embodiment.
According to the vehicle-mounted terminal provided by the embodiment of the invention, the second processor executes the vehicle safety early warning method provided by the embodiment, so that early warning monitoring can be performed on the vehicle of the user in advance, the maintenance of the user is facilitated, and the contradiction between a vehicle owner and a maintenance manufacturer caused by the fact that a fault analyzer cannot accurately point out a fault is avoided, thereby improving the user experience.
In order to achieve the above object, a fifth aspect of the present invention provides a non-transitory computer storage medium having a computer program stored thereon, where the computer program is executed to implement the vehicle safety warning method of the above embodiment, or the computer program is executed to implement the vehicle safety warning method of the above embodiment.
In order to achieve the above object, a sixth aspect of the present invention provides a vehicle including: the vehicle-mounted terminal is connected with the communication bus and used for acquiring communication bus data to evaluate vehicle faults.
According to the vehicle provided by the embodiment of the invention, the vehicle-mounted terminal is used for acquiring the communication bus data to evaluate the vehicle fault, so that the problem that the fault analyzer cannot accurately point out the fault is avoided, the contradiction between a vehicle owner and a maintenance manufacturer is avoided, and the user experience is improved.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow diagram of a vehicle safety warning method according to one embodiment of the invention;
FIG. 2 is a flow diagram of a vehicle safety warning method according to one embodiment of the invention;
FIG. 3 is a schematic block diagram of a vehicle safety enforcement monitoring system according to one embodiment of the present invention;
FIG. 4 is a block diagram of a big data platform analytics device, according to one embodiment of the present invention;
FIG. 5 is a flow diagram of a vehicle safety warning method according to one embodiment of the present invention;
FIG. 6 is a flow diagram of a decision tree for a vehicle early warning model according to one embodiment of the invention;
FIG. 7 is a flow diagram of a vehicle safety warning method according to one embodiment of the invention;
FIG. 8 is a block diagram of a vehicle mounted terminal according to one embodiment of the present invention;
FIG. 9 is a block diagram of a vehicle according to one embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below, the embodiments described with reference to the drawings being illustrative, and the embodiments of the present invention will be described in detail below.
In the running process of the vehicle, due to the lack of fault prejudgment, the impending fault of the vehicle cannot be pre-warned in advance, so that the rescue and maintenance are passive, and the fault detector cannot accurately detect the fault problem of the vehicle under many conditions, thereby causing the contradiction between a vehicle owner and a maintenance manufacturer. The vehicle safety early warning method provided by the embodiment of the invention can evaluate the running condition of the vehicle in real time and early warn the fault information of the vehicle in advance.
According to the vehicle early warning method, early vehicle historical data are used for training a vehicle early warning model by applying big data and a machine learning prediction algorithm, fault types are identified based on the vehicle early warning model, corresponding early warning prompts are carried out, and safety early warning of the vehicle is achieved.
The vehicle safety early warning method according to the embodiment of the first aspect of the present invention is described below with reference to fig. 1 to 7, and is used for a big data platform data analysis end, such as a server, where the big data platform data analysis end may perform data interaction with a vehicle-mounted terminal.
As shown in fig. 1, the vehicle safety warning method according to the embodiment of the present invention at least includes steps S1 to S4.
And step S1, acquiring fault alarm operation data.
In the embodiment, the vehicle-mounted terminal is used for acquiring vehicle auxiliary equipment information, vehicle fault alarm operation information and the like in real time, judging whether a vehicle has a fault or not according to a preset constraint rule, for example, detecting whether vehicle real-time operation data sends vehicle early warning information or not by adopting a decision tree model, and uploading the acquired fault alarm operation data to a big data platform data analysis end such as a server in real time through a 4G/5G communication module when the vehicle is determined to have the fault.
And step S2, determining the fault type according to the fault alarm operation data and the vehicle early warning model.
The vehicle early warning model can be a big data model which is generated by training based on vehicle basic data, real-time operation data, historical data and the like and corresponds to faults in different application scenes, fault alarm operation data serves as input of the vehicle early warning model, the matching degree of the fault alarm operation data and the corresponding fault type of the model can be obtained through the vehicle early warning model, and if the fault alarm operation data and the corresponding fault type of the model are matched, the vehicle fault is considered to belong to the corresponding type of the vehicle early warning model, and then early warning of different types of faults can be carried out.
In the embodiment, vehicle early warning models are stored in a vehicle early warning model database of a big data platform data analysis end, fault alarm operation data are input into each vehicle early warning model, the fault alarm operation data are classified through the built-in vehicle early warning models, and the specific application scene of the fault alarm operation data is determined so as to further determine the fault types, such as battery early warning faults, braking faults and the like.
In short, when the vehicle-mounted terminal preliminarily determines that a fault occurs according to qualitative constraint rules, vehicle fault alarm operation information is uploaded to the big data platform data analysis terminal, the big data platform data analysis terminal further identifies and classifies fault alarm operation data on the basis of a vehicle early warning model, a fault occurrence scene is judged, the type of the fault is determined, the fault primarily determined by the vehicle-mounted terminal is further analyzed and classified, the fault occurrence scene is determined, the fault type is refined, and real-time monitoring and early warning of vehicle safety are achieved.
And step S3, generating fault early warning information according to the fault type.
In an embodiment, the Vehicle fault information database is mainly used for storing information such as Vehicle Identification Number (VIN), fault type, fault module, and fault time of a Vehicle, and generating corresponding fault early warning information according to different fault types, for example, generating rescue maintenance early warning information according to a rescue maintenance fault.
And step S4, sending the fault early warning information to an early warning management end corresponding to the fault type.
For example, in some embodiments, the early warning administration end may include at least one of an after-market platform, a rescue maintenance platform, a vehicle 4S store, a vehicle enterprise host plant, and a user mobile terminal.
In the embodiment, for a certain time after receiving the fault early warning information, for example, after receiving the rescue maintenance early warning information, the warning module sends the fault early warning information to the early warning management terminal in time according to the received fault early warning information, and the early warning management terminal takes corresponding measures to inform an after-sale maintenance team when receiving the warning information of the vehicle in time, so that a user has time to rescue in advance, passive maintenance is avoided, the fault problem of the vehicle can be known without using a fault analyzer, the contradiction between a vehicle owner and a maintenance manufacturer in the vehicle maintenance process is avoided, the maintenance loss of the after-sale maintenance team is reduced, and the user experience is improved.
According to the vehicle safety early warning method provided by the embodiment of the invention, based on the preset vehicle early warning model, when the fault alarm operation data of the vehicle is acquired, the fault type is determined according to the fault alarm operation data and the vehicle early warning model, and the fault alarm information is sent to the early warning management end in time, namely, the fault type is refined based on the vehicle early warning model, the vehicle safety operation condition is evaluated in real time by acquiring the vehicle fault alarm operation data in real time, and the fault early warning information is sent to the early warning management end, so that the real-time monitoring and early warning of the vehicle safety are realized, the resource sharing between the vehicle and a vehicle enterprise host factory is realized, the vehicle which is about to fail, the vehicle which has failed or the intermittent slight early warning information is effectively managed, the early warning monitoring can be carried out on the vehicle of a user in advance, the maintenance of the user is convenient, and the fault analyzer can not accurately point out the fault problem, the contradiction between the vehicle owner and the maintenance manufacturer is caused, and therefore the user experience is improved.
In some embodiments, determining the type of fault from the fault-alarm operating data and the vehicle-early-warning models includes inputting the fault-alarm operating data into each vehicle-early-warning model in a vehicle-early-warning model database; obtaining the matching probability of the fault alarm operation data and each vehicle early warning model; determining a target vehicle early warning model with the highest probability of matching with the fault alarm operation data; and determining the fault type according to the target vehicle early warning model.
In the embodiment, a plurality of vehicle early warning models such as a battery early warning model, a brake system early warning model, a temperature early warning model and the like are stored in a vehicle early warning model database of a big data platform data analysis end, for example, a vehicle-mounted terminal with too high battery temperature determines a battery fault, battery fault alarm operation data is input into each vehicle early warning model stored in a vehicle, the matching rate of the battery fault alarm operation data and each vehicle early warning model is calculated, and when the matching rate of the battery fault alarm operation data and a certain vehicle early warning model such as the battery early warning model is the highest, the battery early warning model with the highest matching rate is determined as a target vehicle early warning model, so that the fault type of the vehicle is determined as the battery fault, and further the battery early warning model can be sent to a rescue maintenance platform, a user mobile terminal and the like for early warning.
In some embodiments, the vehicle safety warning method further includes: acquiring vehicle data in each vehicle database of a vehicle data center; establishing a new vehicle early warning model according to the vehicle data; and updating the vehicle early warning model database according to the new vehicle early warning model, extracting the characteristic analysis result of the new vehicle early warning model, sending the characteristic analysis result to the vehicle-mounted terminal, and updating the qualitative rule base of the vehicle-mounted terminal so as to provide support for optimizing the primary fault early warning evaluation of the vehicle-mounted terminal.
In the embodiment, the vehicle data center of the big data platform data analysis end is mainly used for carrying out real-time statistics and analysis on vehicle fault alarm operation data uploaded by the vehicle-mounted terminal, and for a vehicle owner user or an alarm module which receives an alarm fault lasting for a certain time, the vehicle data center timely sends vehicle safety early warning related information to the early warning management end.
As shown in fig. 3, each vehicle database of the vehicle data center may include a vehicle assembly production database, which is mainly used for storing information such as frame number, production date, vehicle type, engine and battery pack codes of vehicle production offline; the vehicle sale database is mainly used for storing frame numbers, vehicle models, sale dates, inventory states, update dates, dealer information and the like of vehicle sales; the Vehicle after-sale maintenance database is mainly used for storing VIN (Vehicle Identification Number), maintenance state record, maintenance date and information of replacement parts of the Vehicle; the vehicle basic information database is mainly used for storing the VIN, the vehicle type, the vehicle configuration and the information of the owner user of the vehicle; the vehicle fault information database is mainly used for storing information of VIN, fault type, fault module, fault time and the like of the vehicle; the vehicle real-time operation database is mainly used for storing the latest vehicle operation data information such as VIN, latest real-time and the like of the vehicle; the vehicle historical operation database is mainly used for storing the information of the frame number and the historical data of the vehicle; the vehicle early warning model database is mainly used for storing vehicle early warning algorithm models.
Further, establishing a new vehicle early warning model according to the vehicle data comprises: the method comprises the steps of carrying out text analysis on vehicle public opinion data, carrying out analysis on driving behavior data, carrying out analysis on voice data and video image data in the driving process, and carrying out analysis on fault alarm operation data to obtain an analysis result so as to establish a vehicle early warning model.
Specifically, as shown in fig. 3, the public opinion text analysis unit of the big data platform data analysis end is mainly used for performing text analysis on automobile public opinion data by using a big data text mining method, performing preprocessing, keyword text segmentation and word library enrichment on the content of comment data, and extracting high-frequency words and tag information in the comment data; the driving behavior analysis unit is mainly used for analyzing the driving behavior of each user according to the established automobile user image and scoring corresponding driving behaviors; the voice analysis unit is mainly used for analyzing the uploaded voice information of the user in the driving process, and can verify the identity of the user and the control habit of the user; the video analysis unit is mainly used for analyzing the uploaded video image in the cab of the user so as to verify the identity of the user and the driving behavior of the user; the fault module analysis unit is mainly used for analyzing different modules according to uploaded user alarm fault information, calculating the fault probability, storing the results in a vehicle early warning database by integrating the results of vehicle related data with different dimensions, issuing the extracted analysis result of the new vehicle early warning model to a vehicle-mounted terminal, and updating and perfecting the vehicle early warning model database.
In some embodiments, the vehicle safety warning method further includes: and displaying fault early warning information. For example, a display screen can be arranged at the data analysis end of the big data platform and used for displaying fault early warning information and other monitoring data, as shown in fig. 3, a vehicle data big screen monitoring module at the data analysis end of the big data platform is mainly used for receiving real-time fault early warning information of a vehicle and displaying the fault information to a new energy vehicle data monitoring big screen, a specially-assigned person is provided under special conditions to manually review early warning vehicle monitoring information and send the early warning data to an early warning data processing end through the monitoring module, and when the early warning management end receives the vehicle fault early warning information in real time, corresponding measures are timely taken to dispose the fault early warning vehicle.
The vehicle safety precaution method according to the embodiment of the invention is described in detail below with reference to fig. 2, and as shown in fig. 2, it is a flowchart of the vehicle safety precaution method according to an embodiment of the invention.
Step S31, start.
And step S32, acquiring real-time running data of the vehicle, and performing operations of removing abnormal constants, removing redundant data, complementing null data, extracting data and the like on the running data.
Step S33, judging whether to carry out alarm fault evaluation detection, if yes, executing step S34; if not, go to step S39.
And step S34, uploading the fault alarm operation data of the current vehicle in real time.
And step S35, the big data platform analysis end carries out real-time statistical analysis on the received fault alarm operation data of the vehicle.
Step S36, whether the alarm fault exceeds a certain time, if yes, step S38 is executed; if not, go to step S39.
And step S37, sending fault early warning information.
And step S38, deeply analyzing the vehicle alarming behavior and establishing a vehicle early warning model.
Step S39 ends.
The vehicle safety early warning method according to the embodiment of the present invention is described below with reference to fig. 3, and as shown in fig. 3, is a schematic structural diagram of a vehicle safety implementation monitoring system according to an embodiment of the present invention.
By applying big data and a machine learning algorithm, early vehicle historical data of an enterprise are subjected to model training to obtain a vehicle early warning model which is arranged on a vehicle-mounted terminal, the data are continuously uploaded to a big data platform analysis end, a vehicle early warning module of a vehicle data center is updated through analysis of a vehicle safety deep mining module, fault early warning information is displayed through a vehicle data large screen monitoring module and is sent to an early warning administration end in real time to be provided for a vehicle owner user, when the vehicle early warning model is trained on the basis of the vehicle historical data, a characteristic analysis result is continuously fed back to the vehicle-mounted terminal, the fault probability is verified on the latest real-time data, rapid and accurate early warning is realized, the vehicle owner user and an after-sales maintenance team can know the early warning information of the vehicle in advance, and the loss and the negligence of the after-sales maintenance team in the process of maintenance are reduced, rescue passiveness is avoided, user experience is improved, and independent brand public praise and influence of enterprise and vehicle are improved.
In summary, according to the vehicle safety early warning method provided by the embodiment of the invention, the fault alarm operation data of the vehicle is acquired, the fault type is determined according to the fault alarm operation data and the vehicle early warning model preset in the vehicle, and the fault alarm information is sent to the early warning management end, namely, the vehicle safety operation condition is evaluated in real time by acquiring the vehicle fault alarm operation data in real time, the fault early warning information is sent to the early warning management end by a user, so that resource sharing between the vehicle and a vehicle enterprise host factory is realized, the vehicle which is about to fail or the vehicle which has failed is effectively managed, early warning monitoring can be performed on the vehicle of the user in advance, the user can conveniently maintain, the problem that a fault analyzer cannot accurately point out the fault problem is avoided, and the contradiction between a vehicle owner and a maintenance manufacturer is caused, so that the user experience is improved.
The following describes a big data platform analysis apparatus according to an embodiment of the second aspect of the present invention with reference to the drawings.
FIG. 4 is a block diagram of a big data platform analytics device, in accordance with one embodiment of the present invention. As shown in fig. 4, the big data platform analysis device 10 according to the embodiment of the present invention includes a first processor 11, a display 12, and a first memory 13.
Wherein, the display 12 is connected with the first processor 11, the first memorizer 13 that the first processor 11 communicates and connects; the first memory 13 stores a plurality of vehicle databases and instructions executable by the first processor 11, and the first processor implements the vehicle safety warning method mentioned in the above embodiment when executing the instructions.
According to the big data platform analysis device 10 provided by the embodiment of the invention, the vehicle safety early warning method provided by the embodiment is realized when the first processor 11 executes the instruction, the early warning monitoring can be performed on the vehicle of the user in advance, the maintenance of the user is facilitated, the problem that the fault analyzer cannot accurately point out the fault is avoided, the contradiction between the vehicle owner and the maintenance manufacturer is caused, and the user experience is improved.
A vehicle safety warning method according to a third aspect of the present invention, which is applied to a vehicle-mounted terminal, is described below with reference to the drawings.
Fig. 5 is a flowchart of a vehicle safety warning method according to an embodiment of the present invention, and as shown in fig. 5, the vehicle safety warning method according to the embodiment of the present invention includes at least steps S21, S22, and S23.
In step S21, vehicle communication bus data is acquired.
In an embodiment, the intelligent vehicle-mounted terminal is used for acquiring information of vehicle auxiliary equipment, vehicle operation alarm state information and the like, wherein a Controller Area Network (CAN) data acquisition module is mainly used for acquiring module data parameters of each Network on a CAN bus of a vehicle, such as battery capacity, motor state, temperature, engine, alarm information and the like of the vehicle.
And step S22, determining that the vehicle has a fault according to the communication bus data and a preset alarm fault constraint rule, wherein the preset alarm fault constraint rule is a qualitative rule satisfied by the communication bus data and a corresponding preset threshold value.
The constraint rule is simpler than a vehicle early warning model, for example, whether the vehicle is in fault is determined based on threshold judgment, for example, the motor temperature exceeds a preset temperature threshold, that is, the motor is determined to be in fault. Therefore, in the embodiment, the vehicle fault is pre-judged on the basis of the constraint rule at the vehicle-mounted terminal, and further analyzed and classified through a large data platform data analysis terminal such as a server on the basis of a vehicle early warning model, so that the occurrence scene of the fault is determined, the fault type is refined, and the real-time monitoring and early warning of the vehicle safety are realized.
In the embodiment, at the vehicle-mounted terminal, a preset constraint rule, for example, a built-in machine learning algorithm module, includes a tire pressure monitoring algorithm, a mileage jump algorithm, a battery temperature detection algorithm, an engine fault discrimination algorithm, and the like, and a machine learning algorithm is adopted to detect communication bus data to determine whether a vehicle has a fault.
For example, a decision tree algorithm is used to determine the vehicle fault, as shown in fig. 6, which is a flowchart of a decision tree of a vehicle early warning model according to an embodiment of the present invention. The specific process is as follows:
and step S41, whether the tire pressure of the vehicle is normal. If yes, go to step S42; if not, go to step S43.
And step S42, failure early warning information is not sent.
Step S43, continuously judging whether the temperature of the battery motor is normal, if so, executing step S44; if not, go to step S45.
And step S44, failure early warning information is not sent.
Step S45, continuing to judge whether the engine is normal, if yes, executing step S46; if not, go to step S47.
And step S46, failure early warning information is not sent.
Step S47, continuously judging whether the battery charge state is normal, if yes, executing step S48; if not, go to step S49.
And step S48, failure early warning information is not sent.
Step S49, a vehicle failure is sent.
Through the method, various segmentation modes of each rule are traversed until the best segmentation point is found, the segmentation point is segmented into two nodes, and the best segmentation point and segmentation are continuously searched for the two nodes until each node can be judged to be in fault.
And step S23, sending the fault alarm operation data to a big data platform analysis device.
In the embodiment, when the vehicle is determined to have a fault, the fault alarm operation data is uploaded to the enterprise new energy automobile big data platform analysis device of the vehicle enterprise host factory in real time through the 4G/5G communication module.
According to the vehicle safety early warning method provided by the embodiment of the invention, based on the preset alarm fault constraint rule, when the real-time communication bus data of the vehicle meets the preset alarm fault constraint rule, the vehicle is determined to have a fault, and the fault alarm operation data is sent to the big data platform analysis device, so that the fault can be classified to further determine the scene and the fault type of the fault, more precise fault early warning is realized, data support is provided for vehicle safety early warning, the vehicle owner and the after-sales can know the fault of the vehicle in time, and the user experience is improved.
In some embodiments, the vehicle safety warning method further includes: receiving alarm fault constraint rule updating data; and updating the alarm fault qualitative rule database according to the alarm fault constraint rule updating data, receiving the alarm fault constraint rule updating data by the vehicle-mounted terminal, verifying and predicting the probability of the alarm fault on the latest real-time data, and improving the accuracy of fault detection by continuously updating the alarm fault qualitative rule database.
The vehicle safety precaution method according to the embodiment of the invention is described in detail below with reference to fig. 7, and as shown in fig. 7, it is a flowchart of the vehicle safety precaution method according to an embodiment of the invention.
And step S51, the vehicle-mounted terminal performs early warning fault detection on the current operation data of the vehicle through a preset warning fault constraint rule when receiving the operation data information of the vehicle CAN bus in real time.
Step S52, detecting whether vehicle early warning information is sent or not by adopting a machine learning algorithm, and if so, executing step S53; if not, go to step S57.
And step S53, sending fault early warning information, and uploading the vehicle operation data to a big data platform analysis end for data analysis.
And step S54, when the big data platform analysis end receives the early warning information and the vehicle running data of the vehicle, the data is further analyzed by combining the vehicle safety analysis depth module through the vehicle center related data.
And step S55, displaying the analysis result of the big data platform analysis end on a vehicle data big screen monitoring module, and manually checking if necessary.
And step S56, uploading the vehicle early warning information to an early warning management end in real time, and feeding the result back to the vehicle owner user, the vehicle after sale, the vehicle 4S shop, the rescue maintenance, the vehicle enterprise host factory and the like so as to take corresponding measures conveniently.
Step S57 ends.
In summary, according to the vehicle safety early warning method provided by the embodiment of the invention, based on the preset alarm fault constraint rule, when the vehicle real-time communication bus data meets the preset alarm fault constraint rule, the vehicle is determined to have a fault, and the fault alarm operation data is sent to the big data platform analysis device, so that the fault can be classified to further determine the scene and the fault type of the fault, more precise fault early warning is realized, data support is provided for vehicle safety early warning, a vehicle owner and an after-sales vehicle can know the fault of the vehicle in time, and user experience is improved.
In some embodiments, the vehicle-mounted terminal receives the alarm fault constraint rule update data, and updates the alarm fault qualitative rule database according to the alarm fault constraint rule update data, so that the constraint rule of the vehicle-mounted terminal during fault evaluation detection can be further improved, and the accuracy of fault evaluation detection is improved. For example, a vehicle safety deep mining module of a large data platform data analysis end performs deep mining according to data of a vehicle data center to generate a new or more complete vehicle early warning model, a vehicle early warning model database of the vehicle data center is updated, alarm fault constraint rule updating data is sent to a vehicle-mounted terminal, and the vehicle-mounted terminal updates an alarm fault qualitative rule base, so that an alarm fault constraint rule can be completed, and the accuracy of alarm fault evaluation detection performed by the vehicle-mounted terminal is improved.
A vehicle-mounted terminal according to a fourth aspect embodiment of the present invention is described below with reference to the drawings.
Fig. 8 is a block diagram of the in-vehicle terminal according to an embodiment of the present invention, and as shown in fig. 8, the in-vehicle terminal 20 of an embodiment of the present invention includes a second processor 21 and a second memory 22.
A second memory 22 to which the second processor 21 is communicatively connected; the second memory 22 stores instructions executable by the second processor 21, and the instructions, when executed by the second processor 21, implement the vehicle safety warning method mentioned in the above embodiment.
According to the vehicle-mounted terminal 20 provided by the embodiment of the invention, the second processor 21 executes the vehicle safety early warning method provided by the embodiment, so that early warning monitoring can be performed on the vehicle of the user in advance, the maintenance of the user is facilitated, and the contradiction between a vehicle owner and a maintenance manufacturer caused by the fact that a fault analyzer cannot accurately point out a fault problem is avoided, thereby improving the user experience.
A non-transitory computer storage medium of an embodiment of a fifth aspect of the present invention has a computer program stored thereon, and the computer program is executed to implement the vehicle safety warning method mentioned in the above embodiment.
A vehicle according to a sixth aspect of the invention is described below with reference to the drawings.
Fig. 9 is a block diagram of a vehicle according to an embodiment of the present invention, and as shown in fig. 9, a vehicle 30 according to an embodiment of the present invention includes a communication bus 31 and the in-vehicle terminal 20 mentioned in the above embodiment, the in-vehicle terminal 20 is connected to the communication bus 31, and the in-vehicle terminal 20 is used for acquiring communication bus data to evaluate a vehicle fault.
According to the vehicle 30 of the embodiment of the invention, the vehicle-mounted terminal 20 is used for acquiring the communication bus data to evaluate the vehicle fault, so that the problem that the fault analyzer cannot accurately point out the fault is avoided, the contradiction between a vehicle owner and a maintenance manufacturer is avoided, and the user experience is improved.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (12)
1. A vehicle safety early warning method is characterized by comprising the following steps:
acquiring fault alarm operation data;
determining the fault type according to the fault alarm operation data and a vehicle early warning model;
generating fault early warning information according to the fault type;
and sending the fault early warning information to an early warning management end corresponding to the fault type.
2. The vehicle safety precaution method of claim 1, wherein determining the fault type based on the fault alert operation data and a vehicle precaution model comprises:
inputting the fault alarm operation data into each vehicle early warning model in a vehicle early warning model database;
obtaining the matching probability of the fault alarm operation data and each vehicle early warning model;
determining a target vehicle early warning model with the highest probability of matching with the fault alarm operation data;
and determining the fault type according to the target vehicle early warning model.
3. The vehicle safety precaution method according to claim 1, wherein the precaution management terminal includes at least one of an after-sales platform, a rescue maintenance platform, a vehicle 4S shop, a vehicle enterprise host factory, and a user mobile terminal.
4. The vehicle safety warning method according to claim 1, further comprising:
acquiring vehicle data in each vehicle database of a vehicle data center;
establishing a new vehicle early warning model according to the vehicle data;
and updating a vehicle early warning model database according to the new vehicle early warning model, extracting a characteristic analysis result of the new vehicle early warning model, and sending the characteristic analysis result to the vehicle-mounted terminal.
5. The vehicle safety precaution method according to claim 4, wherein establishing a new vehicle precaution model based on the vehicle data includes:
the method comprises the steps of carrying out text analysis on vehicle public opinion data, carrying out analysis on driving behavior data, carrying out analysis on voice data and video image data in the driving process, and carrying out analysis on fault alarm operation data to obtain an analysis result so as to establish a vehicle early warning model.
6. The vehicle safety precaution method according to claim 1, comprising: and displaying the fault early warning information.
7. A big data platform analysis device, comprising:
a first processor;
a display connected with the first processor;
a first memory communicatively coupled to the first processor;
wherein the first memory has stored therein a plurality of vehicle databases and instructions executable by the first processor, the instructions when executed by the first processor implementing the vehicle safety precaution method of any one of claims 1-6.
8. A vehicle safety early warning method is characterized by comprising the following steps:
acquiring vehicle communication bus data;
determining that the vehicle has a fault according to the communication bus data and a preset alarm fault constraint rule, wherein the preset alarm fault constraint rule is a qualitative rule which is satisfied by the communication bus data and a corresponding preset threshold value;
and sending fault alarm operation data to a big data platform analysis device.
9. The vehicle safety warning method according to claim 8, further comprising:
receiving alarm fault constraint rule updating data;
and updating the alarm fault qualitative rule database according to the alarm fault constraint rule updating data.
10. A vehicle-mounted terminal characterized by comprising:
a second processor;
a second memory communicatively coupled to the second processor;
the second memory stores instructions executable by the second processor, and the instructions, when executed by the second processor, implement the vehicle safety precaution method of claim 8 or 9.
11. A non-transitory computer storage medium having stored thereon a computer program, wherein the computer program is executed to implement the vehicle safety warning method of any one of claims 1 to 6, or the computer program is executed to implement the vehicle safety warning method of claim 8 or 9.
12. A vehicle characterized by comprising a communication bus and the in-vehicle terminal of claim 10, the in-vehicle terminal being connected to the communication bus, the in-vehicle terminal being configured to acquire communication bus data to evaluate a vehicle fault.
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