CN108628287A - Auto repair scheme intelligent evaluation method and system - Google Patents
Auto repair scheme intelligent evaluation method and system Download PDFInfo
- Publication number
- CN108628287A CN108628287A CN201810394547.2A CN201810394547A CN108628287A CN 108628287 A CN108628287 A CN 108628287A CN 201810394547 A CN201810394547 A CN 201810394547A CN 108628287 A CN108628287 A CN 108628287A
- Authority
- CN
- China
- Prior art keywords
- component
- data
- image information
- vehicle
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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
- G05B23/0221—Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention provides a kind of auto repair scheme intelligent evaluation method and system.Auto repair scheme intelligent evaluation method provided by the present invention, including：Obtain the image information of the first component in vehicle, according to image information and the corresponding preset standard image information of the first component, determine the first position that the first component breaks down, the current Fisrt fault type of the first component is filtered out according to first position and preset first component error listing, corresponding first maintenance program of Fisrt fault type is filtered out according to Fisrt fault type and preset common maintenance program list.A kind of auto repair scheme intelligent evaluation method provided by the invention greatly reduces due to manually needing the man power and material expended to the fault detect maintenance mode of vehicle, to reduce the cost of repair operation for repair shop.
Description
Technical field
Technical field of automobile maintenance of the present invention more particularly to a kind of auto repair scheme intelligent evaluation method and system.
Background technology
Currently, in recent years, with the rapid development of automobile industry, the sales volume of annual automobile is cut more than 20,000,000
Only 2016, the ownership of domestic automobile just had reached 194,400,000.
Wherein, automobile to caused by people's Working Life facility it is self-evident, still, enjoy automobile more offer convenience
While, automobile it is also often desirable to maintain and safeguard.In the prior art, typically car owner is periodically or fixed driving to
After mileage number, car steering is detected and is maintained to repair shop, so that the service worker of repair shop carries out vehicle
Detection, to determine failure cause and repair.
But fully relying on the manually mode to vehicle fault detection at present will certainly cause maintenance factory in vehicle initial survey portion
Divide a large amount of manpower need to set, this will result in the increase of maintenance cost.
Invention content
The present invention provides a kind of auto repair scheme intelligent evaluation method and system, to reduce due to manually to the event of vehicle
Barrier Measuring error mode needs the man power and material expended, to reduce the cost of repair operation for repair shop.
In a first aspect, the present invention provides a kind of auto repair scheme intelligent evaluation method, including：
The image information of the first component in vehicle is obtained, the outside that described image information includes at least the first component is several
What characteristic information；
According to described image information and the corresponding preset standard image information of the first component, the first component is determined
The first position broken down；
It is current that the first component is filtered out according to the first position and the preset first component error listing
Fisrt fault type；
The Fisrt fault type is filtered out according to the Fisrt fault type and preset common maintenance program list
Corresponding first maintenance program.
In a kind of possible design, described according to the Fisrt fault type and preset common maintenance program row
After table filters out corresponding first maintenance program of the Fisrt fault type, further include：
Send intelligent terminal and/or repair shop's server that first maintenance program to the vehicle corresponds to car owner.
In a kind of possible design, the image information for obtaining the first component in vehicle, including：
Obtain the first point cloud data of the first component；
The second point cloud data is generated after removing the miscellaneous point data in first point cloud data；
The first threedimensional model of the first component is generated according to second point cloud data.
It is described according to described image information and the corresponding preset standard figure of the first component in a kind of possible design
As information, the first position that the first component breaks down is determined, including：
First threedimensional model and the corresponding default threedimensional model of the first component are carried out seeking difference operation, obtain
One difference set model；
The first position that the first component breaks down is determined according to the first difference set model.
In a kind of possible design, in obtaining vehicle before the image information of the first component, further include：
Vehicle condition data in car running computer are obtained, the vehicle condition data include first performance data；
Judge whether the first performance data are normal according to first performance data and preset vehicle operation data
Operation data；
If judging result is no, first performance corresponding described is filtered out according to preset performance accessory corresponding lists
One component, wherein the first performance data are operation data of the first performance in the car running computer.
It is described according to described in first performance data and the judgement of preset vehicle operation data in a kind of possible design
Whether first performance data are normal operation data, including：
Judge the first performance data whether in preset first performance normal data section, wherein described first
Performance normal data section is the vehicle in mark time set first performance normal operation described in the car running computer
Operation data section.
Second aspect, the present invention also provides a kind of auto repair scheme intelligent evaluation systems, including：
Acquisition module, the image information for obtaining the first component in vehicle, described image information include at least described the
The external geometric properties information of one component；
Determining module is used for according to described image information and the corresponding preset standard image information of the first component, really
The first position that the fixed first component breaks down；
Screening module, it is described for being filtered out according to the first position and the preset first component error listing
The current Fisrt fault type of the first component；
The screening module is additionally operable to according to the Fisrt fault type and preset common maintenance program list screening
Go out corresponding first maintenance program of the Fisrt fault type.
In a kind of possible design, further include：
Sending module corresponds to the intelligent terminal of car owner and/or repaiies for sending first maintenance program to the vehicle
Manage factory's server.
In a kind of possible design, the acquisition module is specifically used for：
Obtain the first point cloud data of the first component；
The second point cloud data is generated after removing the miscellaneous point data in first point cloud data；
The first threedimensional model of the first component is generated according to second point cloud data.
In a kind of possible design, the determining module is specifically used for：
First threedimensional model and the corresponding default threedimensional model of the first component are carried out seeking difference operation, obtain
One difference set model；
The first position that the first component breaks down is determined according to the first difference set model.
In a kind of possible design, the acquisition module is additionally operable to obtain vehicle condition data in car running computer, the vehicle condition
Data include first performance data；
Judgment module, for judging the first performance number according to first performance data and preset vehicle operation data
According to whether being normal operation data；
The screening module, is additionally operable to first performance data and preset vehicle operation data judges the first performance
Data are abnormal running data, and it is described first corresponding to filter out first performance according to preset performance accessory corresponding lists
Part, wherein the first performance data are operation data of the first performance in the car running computer.
In a kind of possible design, the judgment module is specifically used for：
Judge the first performance data whether in preset first performance normal data section, wherein described first
Performance normal data section is the vehicle in mark time set first performance normal operation described in the car running computer
Operation data section.
A kind of auto repair scheme intelligent evaluation method and system provided by the invention, by obtaining the first component in vehicle
Image information, further according to image information and the corresponding preset standard image information of the first component, determine the first component occur therefore
Then the first position of barrier filters out current the of the first component by first position and preset first component error listing
One fault type finally filters out Fisrt fault type pair according to Fisrt fault type and preset common maintenance program list
The first maintenance program answered.Greatly reduce due to manually needing the manpower and object that expend to the fault detect maintenance mode of vehicle
Power, to reduce the cost of repair operation for repair shop.
Description of the drawings
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, 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 this hair
Some bright embodiments for those of ordinary skill in the art without having to pay creative labor, can be with
Obtain other attached drawings according to these attached drawings.
Fig. 1 is a kind of flow signal of auto repair scheme intelligent evaluation method shown according to an exemplary embodiment
Figure；
Fig. 2 is a kind of flow signal of the auto repair scheme intelligent evaluation method shown according to another exemplary embodiment
Figure；
Fig. 3 is a kind of structural representation of auto repair scheme intelligent evaluation system shown according to an exemplary embodiment
Figure；
Fig. 4 is a kind of structural representation of the auto repair scheme intelligent evaluation system shown according to another exemplary embodiment
Figure.
Specific implementation mode
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
The every other embodiment obtained without creative efforts, shall fall within the protection scope of the present invention.
In the present invention, term " first ", " second " are used for description purposes only, and are not understood to indicate or imply opposite
Importance or the quantity for implicitly indicating indicated technical characteristic.Define " first " as a result, the feature of " second " can be bright
Show or implicitly include one or more this feature.In the description of the present invention, the meaning of " plurality " is two or two
More than a, unless otherwise specifically defined.
Fig. 1 is a kind of flow signal of auto repair scheme intelligent evaluation method shown according to an exemplary embodiment
Figure.As shown in Figure 1, auto repair scheme intelligent evaluation method provided in this embodiment, including：
Step 101, the image information for obtaining the first component in vehicle.
It specifically, can be by the image information of the first component of image acquisition device vehicle, and by the first component
Image information be sent to image processor, wherein the image information of the first component includes the external geometric properties of the first component
Information is worth understanding that ground, the first component can be body structural components, such as fender, front bumper covering, hood
And car door etc., and external geometric properties can be then the resemblance of body structural components.
In a kind of possible embodiment, the detailed process of the image information of the first component in above-mentioned acquisition vehicle can be with
To first pass through the first point cloud data that scanner obtains the first component, the first point cloud data is then removed by points cloud processing software
In miscellaneous point data after generate the second point cloud data, then generate the of the first component according to the second point cloud data in three-dimensional software
One threedimensional model.For example, the point cloud data for obtaining the fender can be scanned by scanner to fender, then pass through
Generate the point cloud data of pure fender after miscellaneous point data in the point cloud data of points cloud processing software removal fender, then
The threedimensional model of fender is generated in three-dimensional software according to the point cloud data of pure fender.
Step 102, according to image information and the corresponding preset standard image information of the first component, determine the first component
The first position of failure.
In obtaining vehicle after the image information of the first component, its preset standard image corresponding with the first component is believed
Breath, to determine first position that the first component breaks down.For example, can be corresponding to the first threedimensional model and the first component pre-
If threedimensional model carries out seeking difference operation, the first difference set model is obtained；Determine that the first component breaks down according to the first difference set model
First position.Continue by taking fender as an example, it can be by the fender threedimensional model generated by point cloud data and preset mark
Quasi- fender threedimensional model carries out seeking difference operation, acquires the not completely overlapped part of the two, then the part is fender deformation
Part, as send failure first position.
Step 103, filtered out according to first position and the preset first component error listing first component it is current the
One fault type.
Specifically, current first of the first component is filtered out according to first position and preset first component error listing
Fault type.It is worth understanding ground, which may include the correspondence of abort situation and fault type, example
If generation abort situation be fender in the middle part of, then corresponding Fisrt fault type can be deformation, crack or be fall paint
Deng.
Step 104 filters out Fisrt fault type according to Fisrt fault type and preset common maintenance program list
Corresponding first maintenance program.
Specifically, first is filtered out according to the Fisrt fault type of above-mentioned determination and preset common maintenance program list
Corresponding first maintenance program of fault type.Be worth understanding ground, common maintenance program list at this can be fault type and
Repair scheme mapping table.For example, when Fisrt fault type is that fender deforms, then corresponding repair scheme can be
Fender shaping.
In order to preferably notify car owner and register in repair shop's server, then the first maintenance program can be sent
The intelligent terminal and/or repair shop's server of car owner are corresponded to vehicle.
In the present embodiment, by obtaining the image information of the first component in vehicle, further according to image information and first
The corresponding preset standard image information of part, determines the first position that the first component breaks down, then by first position and
Preset first component error listing filters out the current Fisrt fault type of the first component, finally according to Fisrt fault type with
And preset common maintenance program list filters out corresponding first maintenance program of Fisrt fault type.Greatly reduce due to artificial
The man power and material expended is needed to the fault detect maintenance mode of vehicle, to reduce the cost of repair operation for repair shop.
Fig. 2 is a kind of flow signal of the auto repair scheme intelligent evaluation method shown according to another exemplary embodiment
Figure.As shown in Fig. 2, a kind of auto repair scheme intelligent evaluation method provided in this embodiment, including：
Step 201 obtains vehicle condition data in car running computer.
Specifically, car running computer is actually an electronic control unit, it is by input circuit, microcomputer and output circuit
Etc. three parts composition.Input circuit receives the signal of sensor and the input of other devices, and processing and amplification are filtered to signal,
It is then converted into the incoming level of certain volt.The existing analog signal of signal of car running computer input circuit is sent to from sensor
There is digital signal, the A/D converter in input circuit can convert analog signals into digital signal, be then passed to micro-
Machine.Above-mentioned pretreated signal is carried out calculation process by microcomputer, and processing data are sent to output circuit.Output circuit
By the power amplification of digital information, some will also be reduced to analog signal, make the adjusting servoelement work that its driving is controlled.
It is stored with the various and relevant data information of travel condition of vehicle in car running computer, includes mainly instant oil consumption, average fuel consumption, remain
The letters such as excess oil amount, course continuation mileage, engine speed, speed, water temperature, admission pressure, accelerating ability, various vehicle sensors voltages
Breath.
By obtaining vehicle condition data in car running computer, vehicle condition data herein can include：Instant oil consumption, average oil
Consumption, Fuel Oil Remaining, course continuation mileage, engine speed, speed, water temperature, admission pressure, accelerating ability, various vehicle sensors electricity
The information datas such as pressure, and first performance data can be any one in these data.And vehicle condition data in car running computer
Acquisition modes can periodically be exported by external equipment, can also be by be located on vehicle be arranged vehicle condition harvester,
Wherein, which is connected with the car running computer of vehicle and server respectively, can be with by vehicle condition harvester
The vehicle condition data in car running computer are obtained in real time, are sent on server by vehicle condition harvester, which can be
The server in the repair shop either shops 4S, analyzes the data collected on server with will pass through, to determine vehicle
Current situation.
Step 202, judged according to first performance data and preset vehicle operation data first performance data whether be
Normal operation data, judging result are no.
Specifically, judge whether first performance data are just according to first performance data and preset vehicle operation data
Normal operation data, wherein preset vehicle operation data can be instant oil consumption, average fuel consumption, Fuel Oil Remaining, course continuation mileage,
The information datas such as engine speed, speed, water temperature, admission pressure, accelerating ability, various vehicle sensors voltages are under normal circumstances
Number.
It, can be by judging above-mentioned first performance data whether in preset first performance in a kind of possible design
In normal data section, wherein first performance normal data section be vehicle in mark time set the described in car running computer
The operation data section of one performance normal operation.For example, in vehicle calibration, the normal water temperature of setting is 5-55 degree, then if
It it is 65 degree by the current water temperature got in car running computer, then explanation is at this point, the water-cooling system of vehicle is in non-normal working
State, there are failures.
Step 203 filters out the corresponding first component of first performance according to preset performance accessory corresponding lists.
Specifically, the corresponding first component of first performance is filtered out according to preset performance accessory corresponding lists, is worth reason
Xie Di is contained in performance accessory corresponding lists corresponding between properties and the related accessory that can lead to this abnormal performance
Relationship, such as tire pressure are too low, and in the table, then the corresponding first component is tire, and the abnormal failure that brakes, in the table, then
The corresponding first component is the brake system associated components such as brake callipers, brake disc.It first passes through and obtains vehicle condition number in car running computer
It is judged that go out the first performance of failure, by performance accessory corresponding lists filter out with the performance-relevant component, then
Emphasis carries out inspection and evaluation to these components, substantially increases efficiency and the accuracy of maintenance.
Step 204, the image information for obtaining the first component in vehicle.
It specifically, can be by the image information of the first component of image acquisition device vehicle, and by the first component
Image information be sent to image processor, wherein the image information of the first component includes the external geometric properties of the first component
Information is worth understanding that ground, the first component can be body structural components, such as fender, front bumper covering, hood
And car door etc., and external geometric properties can be then the resemblance of body structural components.
In a kind of possible embodiment, the detailed process of the image information of the first component in above-mentioned acquisition vehicle can be with
To first pass through the first point cloud data that scanner obtains the first component, the first point cloud data is then removed by points cloud processing software
In miscellaneous point data after generate the second point cloud data, then generate the of the first component according to the second point cloud data in three-dimensional software
One threedimensional model.For example, the point cloud data for obtaining the fender can be scanned by scanner to fender, then pass through
Generate the point cloud data of pure fender after miscellaneous point data in the point cloud data of points cloud processing software removal fender, then
The threedimensional model of fender is generated in three-dimensional software according to the point cloud data of pure fender.
Step 205, according to image information and the corresponding preset standard image information of the first component, determine the first component
The first position of failure.
In obtaining vehicle after the image information of the first component, its preset standard image corresponding with the first component is believed
Breath, to determine first position that the first component breaks down.For example, can be corresponding to the first threedimensional model and the first component pre-
If threedimensional model carries out seeking difference operation, the first difference set model is obtained；Determine that the first component breaks down according to the first difference set model
First position.Continue by taking fender as an example, it can be by the fender threedimensional model generated by point cloud data and preset mark
Quasi- fender threedimensional model carries out seeking difference operation, acquires the not completely overlapped part of the two, then the part is fender deformation
Part, as send failure first position.
Step 206, filtered out according to first position and the preset first component error listing first component it is current the
One fault type.
Specifically, current first of the first component is filtered out according to first position and preset first component error listing
Fault type.It is worth understanding ground, which may include the correspondence of abort situation and fault type, example
If generation abort situation be fender in the middle part of, then corresponding Fisrt fault type can be deformation, crack or be fall paint
Deng.
Step 207 filters out Fisrt fault type according to Fisrt fault type and preset common maintenance program list
Corresponding first maintenance program.
Specifically, first is filtered out according to the Fisrt fault type of above-mentioned determination and preset common maintenance program list
Corresponding first maintenance program of fault type.Be worth understanding ground, common maintenance program list at this can be fault type and
Repair scheme mapping table.For example, when Fisrt fault type is that fender deforms, then corresponding repair scheme can be
Fender shaping.
In order to preferably notify car owner and register in repair shop's server, then the first maintenance program can be sent
The intelligent terminal and/or repair shop's server of car owner are corresponded to vehicle.
Fig. 3 is a kind of structural representation of auto repair scheme intelligent evaluation system shown according to an exemplary embodiment
Figure.As shown in figure 3, a kind of auto repair scheme intelligent evaluation system provided in this embodiment, including：
Acquisition module 301, the image information for obtaining the first component in vehicle, described image information include at least described
The external geometric properties information of the first component；
Determining module 302 is used for according to described image information and the corresponding preset standard image information of the first component,
Determine the first position that the first component breaks down；
Screening module 303, for being filtered out according to the first position and the preset first component error listing
The current Fisrt fault type of the first component；
The screening module 303 is additionally operable to according to the Fisrt fault type and preset common maintenance program list
Filter out corresponding first maintenance program of the Fisrt fault type.
On the basis of the above embodiments, Fig. 4 is a kind of auto repair scheme shown according to another exemplary embodiment
The structural schematic diagram of intelligent evaluation system.As shown in figure 4, auto repair scheme intelligent evaluation system provided in this embodiment, also
Including：
Sending module 304, for send first maintenance program to the vehicle correspond to car owner intelligent terminal and/or
Repair shop's server.
In a kind of possible design, the acquisition module 301 is specifically used for：
Obtain the first point cloud data of the first component；
The second point cloud data is generated after removing the miscellaneous point data in first point cloud data；
The first threedimensional model of the first component is generated according to second point cloud data.
In a kind of possible design, the determining module 302 is specifically used for：
First threedimensional model and the corresponding default threedimensional model of the first component are carried out seeking difference operation, obtain
One difference set model；
The first position that the first component breaks down is determined according to the first difference set model.
In a kind of possible design, the acquisition module 301 is additionally operable to obtain vehicle condition data in car running computer, described
Vehicle condition data include first performance data；
Judgment module 305, for judging the primary according to first performance data and preset vehicle operation data
Whether energy data are normal operation data；
The screening module 303, is additionally operable to first performance data and preset vehicle operation data judges described first
Performance data is abnormal running data, and first performance corresponding described is filtered out according to preset performance accessory corresponding lists
One component, wherein the first performance data are operation data of the first performance in the car running computer.
In a kind of possible design, the judgment module 305 is specifically used for：
Judge the first performance data whether in preset first performance normal data section, wherein described first
Performance normal data section is the vehicle in mark time set first performance normal operation described in the car running computer
Operation data section.
Finally it should be noted that：The above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Present invention has been described in detail with reference to the aforementioned embodiments for pipe, it will be understood by those of ordinary skill in the art that：Its according to
So can with technical scheme described in the above embodiments is modified, either to which part or all technical features into
Row equivalent replacement；And these modifications or replacements, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme.
Claims (10)
1. a kind of auto repair scheme intelligent evaluation method, which is characterized in that including：
The image information of the first component in vehicle is obtained, the external geometry that described image information includes at least the first component is special
Reference ceases；
According to described image information and the corresponding preset standard image information of the first component, determine that the first component occurs
The first position of failure；
Current the of the first component is filtered out according to the first position and the preset first component error listing
One fault type；
The Fisrt fault type is filtered out according to the Fisrt fault type and preset common maintenance program list to correspond to
The first maintenance program.
2. auto repair scheme intelligent evaluation method according to claim 1, which is characterized in that described according to described
One fault type and preset common maintenance program list filter out corresponding first maintenance program of the Fisrt fault type
Later, further include：
Send intelligent terminal and/or repair shop's server that first maintenance program to the vehicle corresponds to car owner.
3. auto repair scheme intelligent evaluation method according to claim 1, which is characterized in that in the acquisition vehicle
The image information of one component, including：
Obtain the first point cloud data of the first component；
The second point cloud data is generated after removing the miscellaneous point data in first point cloud data；
The first threedimensional model of the first component is generated according to second point cloud data.
4. auto repair scheme intelligent evaluation method according to claim 3, which is characterized in that described according to described image
Information and the corresponding preset standard image information of the first component, determine the first position that the first component breaks down,
Including：
First threedimensional model and the corresponding default threedimensional model of the first component are carried out seeking difference operation, it is poor to obtain first
Collect model；
The first position that the first component breaks down is determined according to the first difference set model.
5. auto repair scheme intelligent evaluation method according to claim 1, which is characterized in that first in obtaining vehicle
Before the image information of component, further include：
Vehicle condition data in car running computer are obtained, the vehicle condition data include first performance data；
Judge whether the first performance data are normal operation according to first performance data and preset vehicle operation data
Data；
If judging result is no, it is described first corresponding to filter out first performance according to preset performance accessory corresponding lists
Part, wherein the first performance data are operation data of the first performance in the car running computer.
6. auto repair scheme intelligent evaluation method according to claim 5, which is characterized in that described according to first performance
Data and preset vehicle operation data judge whether the first performance data are normal operation data, including：
Judge the first performance data whether in preset first performance normal data section, wherein the first performance
Normal data section is operation of the vehicle in mark time set first performance normal operation described in the car running computer
Data interval.
7. a kind of auto repair scheme intelligent evaluation system, which is characterized in that including：
Acquisition module, the image information for obtaining the first component in vehicle, described image information include at least described first
The external geometric properties information of part；
Determining module, for according to described image information and the corresponding preset standard image information of the first component, determining institute
State the first position that the first component breaks down；
Screening module, for filtering out described first according to the first position and the preset first component error listing
The current Fisrt fault type of component；
The screening module is additionally operable to filter out institute according to the Fisrt fault type and preset common maintenance program list
State corresponding first maintenance program of Fisrt fault type.
8. auto repair scheme intelligent evaluation system according to claim 7, which is characterized in that further include：
Sending module corresponds to intelligent terminal and/or the repair shop of car owner for sending first maintenance program to the vehicle
Server.
9. auto repair scheme intelligent evaluation system according to claim 7, which is characterized in that the acquisition module, tool
Body is used for：
Obtain the first point cloud data of the first component；
The second point cloud data is generated after removing the miscellaneous point data in first point cloud data；
The first threedimensional model of the first component is generated according to second point cloud data.
10. auto repair scheme intelligent evaluation system according to claim 9, which is characterized in that the determining module, tool
Body is used for：
First threedimensional model and the corresponding default threedimensional model of the first component are carried out seeking difference operation, it is poor to obtain first
Collect model；
The first position that the first component breaks down is determined according to the first difference set model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810394547.2A CN108628287A (en) | 2018-04-27 | 2018-04-27 | Auto repair scheme intelligent evaluation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810394547.2A CN108628287A (en) | 2018-04-27 | 2018-04-27 | Auto repair scheme intelligent evaluation method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108628287A true CN108628287A (en) | 2018-10-09 |
Family
ID=63694950
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810394547.2A Pending CN108628287A (en) | 2018-04-27 | 2018-04-27 | Auto repair scheme intelligent evaluation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108628287A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112004010A (en) * | 2020-08-27 | 2020-11-27 | 北京中都星徽物流有限公司 | Finished vehicle chassis detection system |
| CN112328875A (en) * | 2020-10-30 | 2021-02-05 | 北京精密机电控制设备研究所 | Intelligent equipment maintenance scheme recommendation method based on big data |
| CN113645385A (en) * | 2021-08-07 | 2021-11-12 | 深圳丰汇汽车电子有限公司 | Method and device for diagnosing automobile fault by endoscope |
| CN115469645A (en) * | 2022-09-28 | 2022-12-13 | 中国第一汽车股份有限公司 | Vehicle fault detection method and system based on cloud modeling technology |
| CN116592470A (en) * | 2023-07-18 | 2023-08-15 | 长沙柏汉电子科技股份有限公司 | Central air conditioner control system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006027391A (en) * | 2004-07-14 | 2006-02-02 | Toyota Motor Corp | Failure analyzing system |
| CN106097452A (en) * | 2016-06-22 | 2016-11-09 | 西安文理学院 | One remanufactures part defect model body integration method |
| CN106327344A (en) * | 2016-08-28 | 2017-01-11 | 华南理工大学 | Vehicle fault online detection and early warning device based on internet of vehicles and vehicle fault online detection and early warning method thereof |
| CN107358596A (en) * | 2017-04-11 | 2017-11-17 | 阿里巴巴集团控股有限公司 | A kind of car damage identification method based on image, device, electronic equipment and system |
| CN107945309A (en) * | 2017-11-22 | 2018-04-20 | 深圳市沃特沃德股份有限公司 | The method and device of remote monitoring condition of the vehicle |
-
2018
- 2018-04-27 CN CN201810394547.2A patent/CN108628287A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006027391A (en) * | 2004-07-14 | 2006-02-02 | Toyota Motor Corp | Failure analyzing system |
| CN106097452A (en) * | 2016-06-22 | 2016-11-09 | 西安文理学院 | One remanufactures part defect model body integration method |
| CN106327344A (en) * | 2016-08-28 | 2017-01-11 | 华南理工大学 | Vehicle fault online detection and early warning device based on internet of vehicles and vehicle fault online detection and early warning method thereof |
| CN107358596A (en) * | 2017-04-11 | 2017-11-17 | 阿里巴巴集团控股有限公司 | A kind of car damage identification method based on image, device, electronic equipment and system |
| CN107945309A (en) * | 2017-11-22 | 2018-04-20 | 深圳市沃特沃德股份有限公司 | The method and device of remote monitoring condition of the vehicle |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112004010A (en) * | 2020-08-27 | 2020-11-27 | 北京中都星徽物流有限公司 | Finished vehicle chassis detection system |
| CN112004010B (en) * | 2020-08-27 | 2021-12-10 | 北京中都星徽物流有限公司 | Finished vehicle chassis detection system |
| CN112328875A (en) * | 2020-10-30 | 2021-02-05 | 北京精密机电控制设备研究所 | Intelligent equipment maintenance scheme recommendation method based on big data |
| CN113645385A (en) * | 2021-08-07 | 2021-11-12 | 深圳丰汇汽车电子有限公司 | Method and device for diagnosing automobile fault by endoscope |
| CN115469645A (en) * | 2022-09-28 | 2022-12-13 | 中国第一汽车股份有限公司 | Vehicle fault detection method and system based on cloud modeling technology |
| CN116592470A (en) * | 2023-07-18 | 2023-08-15 | 长沙柏汉电子科技股份有限公司 | Central air conditioner control system |
| CN116592470B (en) * | 2023-07-18 | 2023-10-10 | 长沙柏汉电子科技股份有限公司 | Central air conditioner control system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108628287A (en) | Auto repair scheme intelligent evaluation method and system | |
| CN109910679B (en) | Battery package collision strength monitoring devices | |
| JP4453764B2 (en) | Vehicle diagnostic device, vehicle diagnostic system, and diagnostic method | |
| CN111645664B (en) | Electric vehicle fault analysis method, device and equipment and vehicle | |
| KR102529392B1 (en) | Forward collision-avoidance assist performance inspection system and method thereof | |
| US20020032513A1 (en) | Method and arrangement for controlling a vehicle and/or for providing driver information when there is loss of tire pressure | |
| CN101301872A (en) | Vehicle maintenance prompting system | |
| CN104331066A (en) | Remote vehicle fault diagnosis method | |
| CN108596348A (en) | Vehicle maintenance information method for pushing and system | |
| CN113703429B (en) | Method and device for performing diagnosis of vehicle | |
| CN105761325A (en) | Multi-vehicle-model adaptive vehicle ignition determination method, device and system | |
| US20190112952A1 (en) | Method of preventing bearing seizure and vehicle using the same | |
| CN108646707A (en) | A kind of method and system of the neighbouring repair shop of voice prompt | |
| CN108614540A (en) | Automotive check repair method and its system | |
| CN108803572A (en) | A kind of automobile communication data positioning method, system, device | |
| CN111800508B (en) | Automatic driving fault monitoring method based on big data | |
| CN110578590A (en) | In-use engineering machinery tail gas black smoke purification monitoring system | |
| CN111800314B (en) | Automatic driving fault monitoring system | |
| CN101223055B (en) | Electronic device | |
| US5612667A (en) | In-vehicle barometric pressure detection system | |
| KR20230165225A (en) | Methods and vehicle systems for determining the status of chassis components | |
| CN212766094U (en) | Vehicle video monitoring platform | |
| WO2002040960A1 (en) | Population data acquisition system | |
| JP2005146905A5 (en) | ||
| JP2005146905A (en) | Vehicle condition monitoring system with vehicle condition monitoring device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20181009 |