CN105094119B - A kind of vehicle-mounted expert diagnosing method and system - Google Patents
A kind of vehicle-mounted expert diagnosing method and system Download PDFInfo
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- CN105094119B CN105094119B CN201510518603.5A CN201510518603A CN105094119B CN 105094119 B CN105094119 B CN 105094119B CN 201510518603 A CN201510518603 A CN 201510518603A CN 105094119 B CN105094119 B CN 105094119B
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
- G05B23/0227—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
- G05B23/0229—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions knowledge based, e.g. expert systems; genetic algorithms
Abstract
This application provides a kind of vehicle-mounted expert diagnosing methods and system, this method to include：Failure is carried out to vehicle in real time to intercept；Fault data is obtained when listening to failure and starts timer, the fault data and failure the moment, which occur, is stored in tabular form in error listing；The faulty equipment that diagnosis is treated according to the error listing carries out fault diagnosis.This method is intercepted by carrying out failure to vehicle in real time, when a failure occurs it, fault data is stored into row-column list so that engineer is by remotely directly diagnosing, quickly positions the root to go wrong, human cost and time cost are considerably reduced, meets user to intelligentized demand.
Description
Technical field
This application involves expert diagnosis technical field more particularly to a kind of vehicle-mounted expert diagnosing method and systems.
Background technology
With the fast development of mobile technology of Internet of things, big data cloud backstage technology, information industry is constantly to having
The potentiality of industry are excavated, and go to promote traditional industries again with the thinking of information industry, it will are opened up for traditional industries new
Situation, and following automobile new energy wisdom vehicle that be electronic information, software dominate, are mainly reflected in：Itself monitoring and pipe
Control, Information share and exchange, unified command and scheduling, automatic Pilot, new energy etc..
At present, all it is by simply obtaining some basic automobile CAN-bus data simultaneously for the information of vehicles of automobile
It shows, and automobile CAN-bus data is not carried out with comprehensive analysis and is excavated with depth.In addition, existing vehicle is normally only
With conventional funcs such as display, amusement, navigation, when vehicle breaks down, engineer scene is needed to check data, analysis
Then data could position problematic root, not only waste human cost and time cost in this way, but also can not meet user couple
Intelligentized demand.
Invention content
In view of this, this application provides a kind of vehicle-mounted expert diagnosing method and system, to overcome in the prior art to vapour
Vehicle fault location not only waste of manpower cost and time cost, but also the problem of user is to intelligentized demand can not be met.
To achieve the above object, this application provides following technical schemes：
A kind of vehicle-mounted expert diagnosing method, this method include：
Failure is carried out to vehicle in real time to intercept；
Fault data is obtained when listening to failure and starts timer, by the fault data and failure occur the moment with
Tabular form is stored in error listing；
The faulty equipment that diagnosis is treated according to the error listing carries out fault diagnosis.
It is preferably, described that the fault data and failure occur after the moment is stored in tabular form in error listing,
It further includes：
The data source for meeting preset time range in the fault data is remotely stored and is locally stored.
Preferably, it is described that the data source for meeting preset time range in the fault data is subjected to remotely storage and local
Storage includes：
The data source is copied in first queue, and passes through wireless network and is uploaded to cloud backstage remotely to be deposited
Storage；
The data source is copied in second queue, saving scene data source, and number is written into the field data source
According to library to be locally stored.
Preferably, described intercepted in real time to vehicle progress failure specifically includes：
The data of CAN bus are uploaded in the buffer cycles queue of the preset length built in advance；
The data in the buffer cycles queue are intercepted using dominant symbols position detecting thread, judge current time wherein one
Whether a ID sequences break down；
When listening to failure generation, start timer and carry out timing, otherwise, continue to intercept next ID sequences.
Preferably, it is described that the fault data and failure generation moment are stored in error listing with tabular form and wrapped
It includes：
When failure name, the device id of guilty culprit equipment, fault occurrence frequency, failure in the fault data is occurred
It carves to correspond and be stored in the error listing.
Preferably, it is described faulty equipment to be diagnosed to be selected to carry out event according to the fault data stored in the error listing
Barrier diagnosis includes：
The institute that the faulty equipment is parsed according to the error listing is faulty；
Choose as needed it is described it is faulty in failure to be analyzed；
The corresponding fault data of the failure to be analyzed is found out according to the error listing；
Fault diagnosis is carried out to the faulty equipment to be diagnosed according to the fault data.
A kind of vehicle-mounted expert diagnostic system, the system include：
Module is intercepted, is intercepted for carrying out failure to vehicle in real time；
First memory module, for obtaining fault data when module listens to failure and starting timer when described intercept,
The fault data is stored in tabular form in error listing；
Diagnostic module, the faulty equipment that the error listing for being uploaded according to first memory module treats diagnosis carry out
Fault diagnosis.
Preferably, which further includes：
Second memory module, for the data source for meeting preset time range in the fault data remotely to be stored
Be locally stored.
Preferably, second memory module includes：
Remote storage modules for the data source to be copied in first queue, and pass through wireless network and are uploaded to cloud
Backstage is remotely to be stored；
Module is locally stored, for the data source to be copied in second queue, saving scene data source, and by described in
Database is written to be locally stored in field data source.
Preferably, the module of intercepting includes：
Buffer cycles module, for the data of CAN bus to be uploaded to the buffer cycles team of the preset length built in advance
In row；
Failure intercepts module, for intercepting the data in the buffer cycles queue using dominant symbols position detecting thread,
Judge whether current time one of ID sequences break down；
Judgment module, it is no for when the failure intercepts module and listens to failure generation, starting timer and carrying out timing
Then, continue to intercept next ID sequences.
Preferably, first memory module is specifically used for failure name, the guilty culprit equipment in the fault data
Device id, fault occurrence frequency, failure occur the moment correspond be stored in the error listing.
Preferably, the diagnostic module includes：
Parsing module, it is faulty for parsing the institute of the faulty equipment according to the error listing；
Choose module, for choose as needed what the parsing module parsed it is faulty in failure to be analyzed；
Searching module, it is corresponding for finding out the failure to be analyzed of the selection module selection according to the error listing
Fault data；
Fault diagnosis module, for being set according to the fault data that the searching module is found to the failure to be diagnosed
It is standby to carry out fault diagnosis.
By above technical scheme it is found that this application provides a kind of vehicle-mounted expert diagnosing methods and system, this method to include：
Failure is carried out to vehicle in real time to intercept；Fault data is obtained when listening to failure and starts timer, by the fault data
It is stored in error listing with tabular form with the failure generation moment；According to the error listing treat the faulty equipment of diagnosis into
Row fault diagnosis.This method is intercepted by carrying out failure to vehicle in real time, and when a failure occurs it, fault data is deposited into row-column list
Storage so that engineer is by remotely directly being diagnosed, quickly position the root to go wrong, considerably reduce human cost with
Time cost meets user to intelligentized demand.
Description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of invention, for those of ordinary skill in the art, without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is the flow chart of a kind of vehicle-mounted expert diagnosing method that the embodiment of the present application one provides；
Fig. 2 is a kind of flow chart of method intercepted in real time to vehicle progress failure that the embodiment of the present application one provides；
Fig. 3 is the flow chart of a kind of method of carry out fault diagnosis that the embodiment of the present application one provides；
Fig. 4 is the flow chart of a kind of vehicle-mounted expert diagnosing method that the embodiment of the present application two provides；
Fig. 5 is the structure diagram of a kind of vehicle-mounted expert diagnostic system that the embodiment of the present application three provides；
Fig. 6 is a kind of structure diagram for intercepting module that the embodiment of the present application three provides；
Fig. 7 is the structure diagram of a kind of diagnostic module that the embodiment of the present application three provides；
Fig. 8 is the structure diagram of a kind of vehicle-mounted expert diagnostic system that the embodiment of the present application four provides.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other without making creative work
Embodiment shall fall within the protection scope of the present invention.
Not only waste of manpower cost and time cost, but also can not meet user are positioned to vehicle failure in the prior art to overcome
The problem of to intelligentized demand, this application provides a kind of vehicle-mounted expert diagnosing method and system, concrete scheme are as described below：
Embodiment one
The embodiment of the present application one provides a kind of vehicle-mounted expert diagnosing method, and as shown in FIG. 1, FIG. 1 is the embodiment of the present application
A kind of flow chart of the one vehicle-mounted expert diagnosing method provided.This method includes：
S101：Failure is carried out to vehicle in real time to intercept.
Specifically, as shown in Fig. 2, Fig. 2 be the embodiment of the present application one provide it is a kind of in real time to vehicle carry out failure intercept
Method flow chart.It specifically includes：
S201：The data of CAN bus are uploaded in the buffer cycles queue of the preset length built in advance.
In this application, it needs to build the buffer cycles queue that length is N in advance, for saving scene.Specific length
It does not limit, can set according to actual needs in this application.
S202：The data in buffer cycles queue are intercepted using dominant symbols position detecting thread, judge current time wherein
Whether one ID sequence breaks down.
Start dominant symbols position detecting thread, for judging current time t, whether certain ID sequence breaks down.Specifically,
Whether CAN bus agreement has some fault bit information, breaks down for decision node equipment when formulating.But it depends alone
These fault bits are prompted, and are the real causes that bad analysis failure occurs；And for those in-and-out failures, there are no under
Hand or even these hidden danger can be neglected.And common OBD (On-Board Diagnostic, onboard diagnostic system) diagnosis,
It is limited to be not only data source, it is often more important that, its data source is result data, and it is related that no step attribute also is difficult to extraction
Property feature, engineer according to OBD diagnostic results also very important person to go to analyze, it is time-consuming, be also not easy positioning sometimes and be out of order generation
Root.
S203：When listening to failure generation, start timer and carry out timing, otherwise, continue to intercept next ID sequences.
At the time of not only having had recorded failure generation, but also can be the acquisition of fault data by starting timer in the application
Basis of time is provided.
S102：Fault data is obtained when listening to failure and starts timer, the moment is occurred into for fault data and failure
It is stored in error listing with tabular form.
Wherein, in this application, fault data and failure generation moment are stored in error listing with tabular form and wrapped
It includes：
Moment one is occurred into for failure name, the device id of guilty culprit equipment, fault occurrence frequency, the failure in fault data
One correspondence is stored in error listing.
Specifically, in once igniting power up, the node device ID to break down in bus can learn implementor name
Claim；The frequency that various failures occur under the equipment can assess the performance of node device；The failure generation moment can quickly position
Source of reference data to be analyzed has saved the time that the data source at moment occurs for traversal matching failure.
Above-mentioned data are established into a malfunction index table, can realize and quickly position data source to be analyzed, without traversal
All data sources are matched, it is efficient.
S103：The faulty equipment that diagnosis is treated according to error listing carries out fault diagnosis.
Wherein, in this application, as shown in figure 3, Fig. 3 is a kind of carry out fault diagnosis that the embodiment of the present application one provides
The flow chart of method.Specifically, faulty equipment to be diagnosed is selected to carry out failure according to the fault data stored in error listing
Diagnosis includes：
S301：The institute that faulty equipment is parsed according to error listing is faulty.
Faulty equipment to be diagnosed is selected, the institute that faulty equipment is parsed according to error listing is faulty.
S302：Choose as needed it is faulty in failure to be analyzed.
S303：The corresponding fault data of failure to be analyzed is found out according to error listing.
The t at the time of failure occurs can be quickly found out, and then quickly navigate in database according to equipment fault list
Data source in (t- Δs T, t+ Δ T)：
Wherein, dominant symbols reason investigation includes：
I) the step feature of the interior ID sequences of extraction (t- Δs T, t+ Δ T)；
) pair ii it is possible that dominant symbols investigate one by one.
Hidden failure reason investigation includes：
I) the high other ID sequences of the matching degree of correlation；
Ii) judge whether the ID sequences have Spline smoothing；
Iii) to the ID sequences of the high degree of correlation with step attribute, it is iterated analysis.
S304：The faulty equipment that diagnosis is treated according to fault data carries out fault diagnosis.
According to above-mentioned steps as a result,
I) the reason of failure is most likely to occur is found, and provides corresponding instruction；
Ii) equipment of combination failure occurrence frequency, fault level, guilty culprit etc. analyzes vehicle performance, and provides automobile
Maintain opinion.
The diagnostic method that the embodiment of the present application one provides, can not only there is the node device historical failure on supporting bus
Inquiry, statistics and prompting are had for the often property sent out failure, and the reliability of node device, stability, anti-interference is assessed for engineer
The offers such as ability and equipment work optimum environmental demand instruct foundation, and data, analysis are checked in Replacing engineering teacher scene
Data quickly position the root to go wrong, and local diagnosis and remote diagnosis, powerful database platform is supported greatly to reduce
Human cost and time cost, meet demand of the user to Vehicular intelligent.
Embodiment two
On the basis of embodiment one, the embodiment of the present application two provides another vehicle-mounted expert diagnosing method, this method
In addition to including step as shown in Figure 1, it is stored in error listing with tabular form by fault data and failure generation moment
Afterwards, it further includes：
The data source for meeting preset time range in fault data is remotely stored and is locally stored.
Specifically, as shown in figure 4, Fig. 4 is the flow of a kind of vehicle-mounted expert diagnosing method that the embodiment of the present application two provides
Figure, Fig. 4 replace with the step S102 in Fig. 1：
S102：Fault data is obtained when listening to failure and starts timer, the moment is occurred into for fault data and failure
It is stored in error listing with tabular form, and the data source for meeting preset time range in fault data is remotely stored
Be locally stored.
In timer carries out timing course, if there is new failure, timer will postpone delay seconds, record
Data source in delay seconds.
Other corresponding portions may refer to the description of embodiment one, repeat no more in the present embodiment.
Specifically, the data source for meeting preset time range in fault data is remotely stored and is locally stored packet
It includes：
Data source is copied in first queue, and passes through wireless network and is uploaded to cloud backstage remotely to be stored.
It copies in the data source to first queue in buffer cycles queue in (t- Δs T, t+ Δ T), it will be in first queue
Data source is sent to backstage by 3G or other wireless transmission methods, remotely to be stored.
Data source is copied in second queue, saving scene data source, and by field data source be written database with into
Row is locally stored.
It copies in the data source to second queue in buffer cycles queue in (t- Δs T, t+ Δ T), and will be in second queue
Data source write-in database to be locally stored.
In the application, the data source before and after the failure generation moment in bus is the data source with step attribute, for event
Precisely analysis and correlation analysis are helpful for barrier.The storage that data source is allowed a choice, since the data of bus are a straight hairs
It send, no small expense can be carried out, and some data are also of little use for diagnosing to storage tape by adding up to get off for a long time, and this Shen
The data that please be stored significantly reduce storage overhead, and for failure cause diagnosis, are very important, because such as
Fruit data source can not extract step attribute, correlative character, and the accuracy for diagnosis is also influential.
The present invention is especially difficult the data reproduced by these key messages under data-base recording.This kind of data compare
It is special, when being due to some failures and the when of generation and disappear.This kind of failure, it is relatively difficult for fault recurrence,
It is time-consuming, it is not easy to be captured, but bring no small harm sometimes.This kind of failure, for example, BMS, that is, battery management system
System, due to single battery, there is differences, and the threshold value threshold sets for leading to some batteries are not to match very much, may result in this
A little single batteries are overcharged or are crossed and put, and influence the performance and used life of battery, and then influence the bulking property of entire battery pack
Energy, service life, vehicle course continuation mileage.The duration is very short sometimes for this kind of failure, it is not easy to it is found, but long-term accumulation
Go down, be a chronic malignant tumor.
This diagnostic method carries out mining analysis to bus data, extracts data step feature, can quickly navigate to failure
The stronger failure of point, especially concealment is equivalent to and has matched an expert grade diagnosis house keeper to automobile, escorts all the way.
In addition, this solution in addition to supporting local data library storage, also supports the long-range storage in cloud backstage.To mass data
Professional data storage and inquiry are provided, gathered engineer for many years to the analysis logic and algorithm that have broken down, energy
Data, analysis data are checked in enough Replacing engineering teacher scenes, quickly vouch the root that position is gone wrong.
Expert diagnosis can be diagnosed locally, can need the failure analyzed with artificial selection, can also be on cloud backstage
It carries out remote diagnosis and remote technology support is provided.Pass through data mining and analysis, analysis vehicle performance, driving habit, for peace
Full driving, green, which drive, provides expert's instruction.
By above technical scheme it is found that this method that the embodiment of the present application two provides, not only realizes one energy of embodiment
The technique effect of realization, and automobile bus data local data library storage and teledata library storage, in feelings such as emergency episodes
Convenient for in-situ FTIR spectroelectrochemitry under condition, intelligence can touch terminal, user can select failure, and analyze, and man-machine interaction effect is good.
Embodiment three
On the basis of embodiment one, the embodiment of the present application three provides a kind of vehicle-mounted expert diagnostic system, such as Fig. 5 institutes
Show, Fig. 5 is the structure diagram of a kind of vehicle-mounted expert diagnostic system that the embodiment of the present application three provides.The system includes：It intercepts
Module 401, the first memory module 402 and diagnostic module 403, wherein,
Module 401 is intercepted, is intercepted for carrying out failure to vehicle in real time.
As shown in fig. 6, Fig. 6 is a kind of structure diagram for intercepting module that the embodiment of the present application three provides, this intercepts mould
Block includes：Buffer cycles module 501, failure intercept module 502 and judgment module 503, wherein,
Buffer cycles module 501, for the data of CAN bus to be uploaded to the buffer cycles of the preset length built in advance
In queue.
Failure intercepts module 502, for intercepting the data in buffer cycles queue using dominant symbols position detecting thread, sentences
Whether disconnected current time one of ID sequences break down.
Judgment module 503, it is no for when failure intercepts module and listens to failure generation, starting timer and carrying out timing
Then, continue to intercept next ID sequences.
First memory module 402, for obtaining fault data when intercepting module 401 and listen to failure and starting timing
Fault data is stored in tabular form in error listing by device.
First memory module is specifically used for sending out failure name, the device id of guilty culprit equipment, the failure in fault data
Raw frequency, failure occur moment one-to-one correspondence and are stored in the error listing.
Diagnostic module 403, the error listing for being uploaded according to the first memory module 402 treat the faulty equipment of diagnosis into
Row fault diagnosis.
Specifically, as shown in fig. 7, the structure diagram of a kind of diagnostic module that Fig. 7 is provided for the embodiment of the present application three, is somebody's turn to do
Diagnostic module includes：Parsing module 601 chooses module 602, searching module 603 and fault diagnosis module 604, wherein,
Parsing module 601, it is faulty for parsing the institute of faulty equipment according to error listing；
Choose module 602, for choose as needed what parsing module 601 parsed institute it is faulty in it is to be analyzed former
Barrier；
Searching module 603, for finding out the corresponding event of failure to be analyzed chosen module 602 and chosen according to error listing
Hinder data；
Fault diagnosis module 604, the fault data for being found according to searching module 603 treat the faulty equipment of diagnosis
Carry out fault diagnosis.
It specifically repeats no more in this embodiment, can be found in the description of one corresponding portion of embodiment in detail.
Example IV
On the basis of embodiment three, present application example four provides another vehicle-mounted expert diagnostic system, such as Fig. 8 institutes
Show, Fig. 8 is the structure diagram of a kind of vehicle-mounted expert diagnostic system that the embodiment of the present application four provides.The system is removed and includes Fig. 5
Outside shown structure, further include：
Second memory module 404, for the data source for meeting preset time range in fault data remotely to be stored
Be locally stored.
Specifically, the second memory module includes：
Remote storage modules for data source to be copied in first queue, and pass through wireless network and are uploaded to cloud backstage
Remotely to be stored；
Module is locally stored, for data source to be copied in second queue, saving scene data source, and by field data
Database is written to be locally stored in source.
It specifically repeats no more in the present embodiment, reference can be made to the description of other embodiment relevant portion.
By above technical scheme it is found that the vehicle-mounted expert diagnostic system that the embodiment of the present application three and example IV are provided,
There can not only be the node device historical failure inquiry on supporting bus, statistics and prompting are had for the often property sent out failure, be work
The offers such as reliability, stability, antijamming capability and the equipment work optimum environmental demand of Cheng Shi assessment node devices refer to
Foundation is led, and data, analysis data are checked in Replacing engineering teacher scene, quickly position the root to go wrong, support local diagnosis
And remote diagnosis, powerful database platform considerably reduce human cost and time cost, meet user to vehicle intelligence
The demand of energyization.
Finally, it is to be noted that, herein, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or orders.Moreover, term " comprising ", "comprising" or its any other variant meaning
Covering non-exclusive inclusion, so that process, method, article or equipment including a series of elements not only include that
A little elements, but also including other elements that are not explicitly listed or further include for this process, method, article or
The intrinsic element of equipment.In the absence of more restrictions, the element limited by sentence "including a ...", is not arranged
Except also there are other identical elements in the process, method, article or apparatus that includes the element.
Each embodiment is described by the way of progressive in this specification, the highlights of each of the examples are with other
The difference of embodiment, just to refer each other for identical similar portion between each embodiment.
The foregoing description of the disclosed embodiments enables professional and technical personnel in the field to realize or using the application.
A variety of modifications of these embodiments will be apparent for those skilled in the art, it is as defined herein
General Principle can in other embodiments be realized in the case where not departing from spirit herein or range.Therefore, the application
The embodiments shown herein is not intended to be limited to, and is to fit to and the principles and novel features disclosed herein phase one
The most wide range caused.
Claims (10)
1. a kind of vehicle-mounted expert diagnosing method, which is characterized in that this method includes：
Failure is carried out to vehicle in real time to intercept；
Fault data is obtained when listening to failure and starts timer, is occurred into for the fault data and failure with list the moment
Form is stored in error listing；
The faulty equipment that diagnosis is treated according to the error listing carries out fault diagnosis；
The faulty equipment progress fault diagnosis that diagnosis is treated according to the error listing includes：
The institute that the faulty equipment is parsed according to the error listing is faulty；
Choose as needed it is described it is faulty in failure to be analyzed；
The corresponding fault data of the failure to be analyzed is found out according to the error listing；
Fault diagnosis is carried out to the faulty equipment to be diagnosed according to the fault data；
It further includes：Failure cause is found according to the result of the fault diagnosis, provides corresponding instruction；The failure cause
Including：Dominant symbols reason and hidden failure reason.
2. according to the method described in claim 1, it is characterized in that, described occur the moment to arrange by the fault data and failure
After sheet form is stored in error listing, further include：
The data source for meeting preset time range in the fault data is remotely stored and is locally stored.
3. according to the method described in claim 2, it is characterized in that, described will meet preset time range in the fault data
Data source remotely stored and be locally stored including：
The data source is copied in first queue, and passes through wireless network and is uploaded to cloud backstage remotely to be stored；
The data source is copied in second queue, saving scene data source, and database is written into the field data source
To be locally stored.
4. according to the method described in claim 1, it is characterized in that, described intercepted in real time to vehicle progress failure specifically includes：
The data of CAN bus are uploaded in the buffer cycles queue of the preset length built in advance；
The data in the buffer cycles queue are intercepted using dominant symbols position detecting thread, judge current time one of ID
Whether sequence breaks down；
When listening to failure generation, start timer and carry out timing, otherwise, continue to intercept next ID sequences.
5. according to the method described in claim 1, it is characterized in that, described occur the moment to arrange by the fault data and failure
Sheet form is stored in error listing and includes：
Moment one is occurred into for failure name, the device id of guilty culprit equipment, fault occurrence frequency, the failure in the fault data
One correspondence is stored in the error listing.
6. a kind of vehicle-mounted expert diagnostic system, which is characterized in that the system includes：
Module is intercepted, is intercepted for carrying out failure to vehicle in real time；
First memory module, for when it is described intercept to obtain when module listens to failure fault data and start timer, by institute
Fault data is stated to be stored in error listing with tabular form；
Diagnostic module, the faulty equipment that the error listing for being uploaded according to first memory module treats diagnosis carry out failure
Diagnosis；
The diagnostic module includes：
Parsing module, it is faulty for parsing the institute of the faulty equipment according to the error listing；
Choose module, for choose as needed what the parsing module parsed it is faulty in failure to be analyzed；
Searching module, for finding out the corresponding failure of failure to be analyzed of the selection module selection according to the error listing
Data；
Fault diagnosis module, for according to the fault data that the searching module is found to the faulty equipment to be diagnosed into
Row fault diagnosis and, failure cause is found according to the result of the fault diagnosis, provides corresponding instruction；The event
Barrier reason includes：Dominant symbols reason and hidden failure reason.
7. system according to claim 6, which is characterized in that the system further includes：
Second memory module, for the data source for meeting preset time range in the fault data to be carried out remotely storage and this
Ground stores.
8. system according to claim 7, which is characterized in that second memory module includes：
Remote storage modules for the data source to be copied in first queue, and pass through wireless network and are uploaded to cloud backstage
Remotely to be stored；
Module is locally stored, for the data source to be copied in second queue, saving scene data source, and by the scene
Database is written to be locally stored in data source.
9. system according to claim 6, which is characterized in that the module of intercepting includes：
Buffer cycles module, for the data of CAN bus to be uploaded in the buffer cycles queue of the preset length built in advance；
Failure intercepts module, for intercepting the data in the buffer cycles queue using dominant symbols position detecting thread, judges
Current time, whether one of ID sequences broke down；
Judgment module, for when the failure intercepts module and listens to failure generation, starting timer and carrying out timing, otherwise,
Continue to intercept next ID sequences.
10. system according to claim 6, which is characterized in that first memory module is specifically used for the failure
The device id of failure name, guilty culprit equipment in data, fault occurrence frequency, failure occur moment one-to-one correspondence and are stored in institute
It states in error listing.
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| CN105867351B (en) * | 2016-04-29 | 2019-06-28 | 大连楼兰科技股份有限公司 | Vehicle trouble code acquires the method and device with historical data analysis diagnosis in real time |
| CN109213113A (en) * | 2017-07-04 | 2019-01-15 | 百度在线网络技术（北京）有限公司 | Vehicular diagnostic method and system |
| WO2021217626A1 (en) * | 2020-04-30 | 2021-11-04 | 上海华东汽车信息技术有限公司 | Vehicle data processing method and apparatus, computer device, and storage medium |
| CN111815803A (en) * | 2020-06-19 | 2020-10-23 | 安徽安凯汽车股份有限公司 | New energy automobile fault storage system and detection method |
| CN112054843A (en) * | 2020-08-21 | 2020-12-08 | 武汉光迅信息技术有限公司 | Optical signal transmission system and method |
| CN114090130A (en) * | 2021-11-26 | 2022-02-25 | 上海星融汽车科技有限公司 | Method and system for preloading execution logic |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1783161A (en) * | 2004-12-04 | 2006-06-07 | 现代奥途纳特株式会社 | System and method for controlling remote distance vehicle using remote distance information processing system |
| CN102830690A (en) * | 2012-05-04 | 2012-12-19 | 王蓉 | Data processing system of automobile fault data |
| CN102945042A (en) * | 2012-11-14 | 2013-02-27 | 深圳市元征科技股份有限公司 | Standard fault code extracting method based on professional diagnosis |
| CN102981496A (en) * | 2012-11-14 | 2013-03-20 | 深圳市元征科技股份有限公司 | Remote control and data storage method based on vehicle professional diagnosis |
| CN103226065A (en) * | 2013-04-10 | 2013-07-31 | 苏州市职业大学 | Intelligent automobile performance monitoring system based on onboard automatic diagnosis system |
-
2015
- 2015-08-21 CN CN201510518603.5A patent/CN105094119B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1783161A (en) * | 2004-12-04 | 2006-06-07 | 现代奥途纳特株式会社 | System and method for controlling remote distance vehicle using remote distance information processing system |
| CN102830690A (en) * | 2012-05-04 | 2012-12-19 | 王蓉 | Data processing system of automobile fault data |
| CN102945042A (en) * | 2012-11-14 | 2013-02-27 | 深圳市元征科技股份有限公司 | Standard fault code extracting method based on professional diagnosis |
| CN102981496A (en) * | 2012-11-14 | 2013-03-20 | 深圳市元征科技股份有限公司 | Remote control and data storage method based on vehicle professional diagnosis |
| CN103226065A (en) * | 2013-04-10 | 2013-07-31 | 苏州市职业大学 | Intelligent automobile performance monitoring system based on onboard automatic diagnosis system |
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|---|---|
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