CN116304148A - Data matching method for vehicle accessory transaction - Google Patents
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Abstract
The invention relates to a data matching method for vehicle accessory transaction, which relates to the technical field of blockchain, and comprises the steps that a data acquisition module acquires a shot image of a frame number uploaded by a user; the data analysis module is used for analyzing the resolution of the shot image of the frame number acquired by the data acquisition module and determining whether the resolution of the shot image of the frame number is qualified or not; when the data matching module is matched with the vehicle type, the data acquisition module acquires vehicle accessory data uploaded by a user, and the data analysis module analyzes the vehicle accessory data and determines an analysis result; the data matching module determines whether the vehicle accessory is matched with the vehicle accessory according to the analysis result; the data analysis module analyzes the damage index of the vehicle accessory and judges whether the accessory is maintained or replaced according to the damage index; the problem that the information matching of the vehicle needs to manually collect the information and check the inventory, which is time-consuming and easy to miss is effectively solved.
Description
Technical Field
The invention relates to the technical field of blockchain, in particular to a data matching method for vehicle accessory transactions.
Background
At present, with the vigorous development of the domestic automobile after-market industry, the efficiency of traditional off-line automobile to store maintenance repair is very low, most of the on-line automobiles are reserved by telephone or queued to store, store staff is required to manually collect and check the inventory for information matching of the automobiles, time is consumed, and once the inventory is omitted, the situation of part shortage and user use delay possibly occurs, so that the requirements of repair factories cannot be met.
Chinese patent publication No.: CN105678610a discloses a system and a method for managing electronic commerce transactions of automobile accessories, which comprises an accessory transaction platform, a merchant end and a user end, wherein the accessory transaction platform correlates and matches accessory manufacturers, accessory brands, accessory types, accessory categories and accessory basic information, monitors and counts the whole transaction process, sets the accessory basic information through the merchant end, manages the pre-selling, putting on shelf and putting off shelf of the accessories, checks and counts the transaction information, and a consumer searches and screens the accessory information, the accessory merchant information and price through the user end to select proper accessory ordering. The invention establishes a special automobile accessory platform and provides a management method thereof, establishes subordinate and association relations among accessories and establishes direct corresponding relations with vehicles, thereby providing convenience and diversity for consumers to select accessories and providing a platform for accessory dealers to sell accessories. Therefore, the management system and the method for the e-commerce transaction of the automobile parts have the following problems:
1. matching information to vehicles requires store personnel to manually gather and check inventory, which is time consuming and prone to missing information.
2. The maintenance and communication efficiency for the vehicle accessories is lower.
Disclosure of Invention
Therefore, the invention provides a data matching method for vehicle accessory transaction, which is used for solving the problems that the information matching of vehicles in the prior art is time-consuming and is easy to miss.
To achieve the above object, the present invention provides a data matching method for vehicle accessory transactions, including:
s1, a data acquisition module acquires a shooting image of a frame number uploaded by a user;
s2, the data analysis module analyzes the resolution of the shot image of the frame number acquired by the data acquisition module, and whether the resolution of the shot image of the frame number is qualified or not is determined;
when the data analysis module determines that the resolution of the shot image of the frame number is qualified, the data matching module mobilizes a database to autonomously match the vehicle model, when the resolution of the shot image of the frame number is determined to be unqualified, the data analysis module determines interpolation of interpolation processing on the shot image of the frame number, and the data matching module matches the shot image of the frame number which is completed by interpolation with the vehicle types in the database and determines whether the matching is successful or not according to the number of the matched vehicle types;
step S3, when the data matching module is matched with the vehicle type, the data acquisition module acquires vehicle accessory data uploaded by a user, and the data analysis module analyzes the vehicle accessory data and determines an analysis result;
step S4, the data matching module determines whether the vehicle accessory is matched according to the analysis result;
s5, analyzing the damage degree of the vehicle accessories by the data analysis module, and judging to repair or replace the accessories according to the damage degree;
in the step S3, when the data analysis module determines that the vehicle accessory data uploaded by the user is text data, the text analysis unit of the data analysis module extracts text in the text data and matches the text with accessory information in the database, and when the data analysis module determines that the vehicle accessory data uploaded by the user is picture data, the image analysis unit of the data analysis module identifies resolution of the vehicle accessory image.
Further, in the step S2, when the data analysis module analyzes the resolution of the captured image of the frame number acquired by the data acquisition module, the data analysis module determines the resolution Q1 of the captured image of the frame number, compares the resolution Q1 with a preset resolution Q, determines whether the resolution of the frame number image is qualified according to the comparison result,
if Q1 is less than Q, the data analysis module judges that the resolution of the shot image of the frame number is not qualified;
and if Q1 is more than or equal to Q, the data analysis module judges that the resolution of the shot image of the frame number is qualified.
Further, in the step S2, when the data analysis module determines that the resolution of the photographed image of the frame number is not acceptable, a first resolution difference Δqa between the resolution Q1 of the photographed image of the frame number and a preset resolution Q is calculated, Δqa=q-Q1 is set, and a corresponding interpolation is determined according to a comparison result of the first resolution difference and the preset resolution difference to process the photographed image of the frame number,
wherein the data analysis module is provided with a first preset resolution difference delta Q1, a second preset resolution difference delta Q2, a first interpolation W1, a second interpolation W2 and a third interpolation W3, wherein delta Q1 < [ delta ] Q2, W1 < W2 < W3,
if delta Qa is less than or equal to delta Q1, the data analysis module judges that a first interpolation W1 is selected to process the photographed image of the frame number;
if delta Q1 is less than delta Qa is less than or equal to delta Q2, the data analysis module judges that a second interpolation W2 is selected to process the photographed image of the frame number;
and if delta Qa > [ delta ] Q2, the data analysis module judges that a third interpolation W3 is selected to process the photographed image of the frame number.
Further, in the step S2, when the data analysis module determines that the resolution of the shot image of the frame number is qualified or the shot image processing of the frame number is completed, the data matching module matches the shot image of the frame number with a frame number corresponding to a vehicle type in the database, and compares the number P of matched vehicle types with the number of preset vehicle types, wherein the data analysis module is further provided with a first number P1 of preset vehicle types and a second number P2 of preset vehicle types, P1 < P2,
if p=p1, the data analysis module determines that the vehicle type matching is completed;
if P1 is more than P and less than or equal to P2, the data analysis module determines to adjust the interpolation;
if P is more than P2, the data analysis module performs error reporting processing.
Further, in the step S2, when the data analysis module determines that the interpolation is adjusted, calculating a vehicle type number difference Δp between the matched vehicle type number P and a second preset vehicle type number P2, setting Δp=p2-P, adjusting interpolation of the captured image of the frame number according to a comparison result of the vehicle type number difference and the preset vehicle type number difference,
wherein the data analysis module is provided with a first vehicle type preset difference value delta P1, a second vehicle type preset difference value delta P2, a first interpolation coefficient x1, a second interpolation coefficient x2 and a third interpolation coefficient x3, x1 is more than 1 and less than x2 and x3 is more than 1.5,
if delta P is less than or equal to delta P1, the data analysis module judges that a first interpolation coefficient x3 is selected to adjust the interpolation;
if delta P1 is less than delta P2, the data analysis module judges that a second interpolation coefficient x2 is selected to adjust the interpolation;
if delta P > -delta P2, the data analysis module judges that a third interpolation coefficient x1 is selected to adjust the interpolation;
when the data analysis module determines that the interpolation coefficient adjusted for interpolation is xi, i=1, 2,3 is set, the adjusted interpolation is set to Wa, wa=wc×xi, c is 1,2,3, xi is the interpolation coefficient.
Further, in the step S3, when the data analysis module analyzes the vehicle accessory data, if the vehicle accessory data is text data, the text analysis unit of the data analysis module extracts text in the text data and matches the text with accessory information in the database, and if the matching is consistent with the accessory in the database, the matching is completed; if the matching of the accessories is not consistent in the database, searching in big data;
when the data analysis module analyzes the vehicle accessory data, if the vehicle accessory data is image data, the image analysis unit of the data analysis module identifies the resolution of the vehicle accessory image, the data analysis module calculates the resolution Q2 of the vehicle accessory image, compares the resolution Q2 of the vehicle accessory image with a preset resolution Q, determines whether the resolution of the vehicle accessory image meets the standard according to the comparison result,
if Q2 is less than Q, the data analysis module judges that the resolution of the vehicle accessory image does not reach the standard;
and if Q2 is more than or equal to Q, the data analysis module judges that the resolution of the vehicle accessory image meets the standard.
Further, when the data analysis module determines that the resolution of the vehicle accessory image meets the standard, if the database is not matched with the vehicle accessory, matching is carried out in big data; if only one vehicle accessory is matched in the database, the matching is completed; and if the matching results of various vehicle accessories exist in the database, adjusting the preset resolution.
Further, when the data analysis module determines to adjust the preset resolution, determining a vehicle accessory type R in the matching result, determining a correction coefficient of the corresponding preset resolution according to the comparison result of the vehicle accessory type and the preset vehicle accessory type in the matching result,
wherein the data analysis module is provided with a first preset vehicle accessory type R1, a second preset vehicle accessory type R2, a second preset resolution difference delta Q4, a first resolution correction coefficient k1, a second resolution correction coefficient k2 and a third resolution correction coefficient k3, R1 is more than R2, k1 is more than 1 and k2 is more than 1 and k3 is less than 1.2,
if R is less than or equal to R1, the data analysis module judges that a first preset resolution correction coefficient k1 is selected to adjust the preset resolution;
if R1 is more than R and less than or equal to R2, the data analysis module judges that a second preset resolution correction coefficient k2 is selected to adjust the preset resolution;
if R is more than R2, the data analysis module judges that a third preset resolution correction coefficient k3 is selected to adjust the preset resolution;
when the data analysis module determines that the correction coefficient for the preset resolution is ki, setting i=1, 2,3, and setting the adjusted preset resolution as Qj, wherein qj=q×ki, and ki is the correction coefficient of the preset resolution.
Further, when the data analysis module determines that the resolution of the vehicle accessory image does not reach the standard, a second resolution difference DeltaQb between the resolution Q2 of the vehicle accessory image and a preset resolution Q is calculated, deltaQb=Q-Q2 is set, and corresponding interpolation is determined according to the comparison result of the second resolution difference and the preset resolution difference so as to process the vehicle accessory image, wherein a fourth interpolation W4, W3 < W4 is further arranged in the data analysis module,
if delta Qb is less than or equal to delta Q1, the data analysis module judges that a second interpolation W2 is selected to process the vehicle accessory image;
if DeltaQ 1 < DeltaQbis less than or equal to DeltaQ 2, the data analysis module judges that a third interpolation W3 is selected to process the vehicle accessory image;
if DeltaQb > DeltaQ2, the data analysis module determines to select a fourth interpolation W4 to process the vehicle accessory image.
Further, in the step S5, when the data matching module determines that the vehicle accessory is matched according to the analysis result, calculating a damage index Z of the vehicle accessory, setting z=u/u0+e/E0, determining to repair or replace the vehicle accessory according to a comparison result of the damage index of the accessory and a preset damage index,
wherein the data analysis module is provided with a first preset damage index Z1, U is the crack length of the vehicle accessory, U0 is the preset crack length of the vehicle accessory, E is the number of damaged parts of the vehicle accessory, E0 is the number of preset damaged parts of the vehicle accessory,
if Z is less than or equal to Z1, the data analysis module judges that the vehicle accessory is maintained;
if Z is greater than Z1, the data analysis module determines to replace the vehicle accessory.
Compared with the prior art, the invention has the beneficial effects that when the related information of the vehicle is identified based on the VIN code in the traditional mode, the user is required to manually input 17-bit VIN code characters, and the irregularity of the VIN code composition is required to be carefully input by the user, so that the time spent by the user in the process of filling the VIN code is longer, the error rate is higher, and the frame number image is identified and processed through the data analysis module, thereby avoiding the occurrence of input errors and further improving the experience and communication efficiency of the user;
especially, after matching the model to the vehicle, when selecting the vehicle accessory, not only can direct text search, can use the image to carry out the discernment of accessory in addition, when the image resolution is not enough, thereby the interpolation of data analysis module can adjust the image resolution, need not to take a photograph again and upload again, and then make user's operation more simple and convenient, further improved the maintenance efficiency between user and the shop assistant.
Further, after the damage index of the vehicle accessory is matched with the preset damage index, the data analysis module compares the calculated damage index of the vehicle accessory with the preset damage index to judge the damage degree of the vehicle accessory, and the accessory is judged to be maintained or replaced according to the damage index of the vehicle accessory, so that maintenance efficiency is further improved, and meanwhile the risk of missing information is reduced.
Furthermore, the invention manually creates the micro-letter group between the service provider and the repair shop by customer service personnel, and can automatically match corresponding maintenance accessories in the micro-letter group according to vehicle information, so that the information is more transparent, and a fair and efficient platform is established between the repair shop and the service provider.
In particular, the invention can carry out online transaction through data matching, is not limited to the traditional telephone reservation mode or store queuing for maintenance and vehicle accessory replacement, can ensure that maintenance information and flow are not limited to places, and users can make a bill and pay online at any time and any place by themselves without reprocessing to the store, thereby further improving maintenance and communication efficiency.
Furthermore, the invention analyzes and processes the image through the data analysis module, and the system background updates the database at any time so as to ensure that the information of the vehicle model and the vehicle fittings in the database can be updated in time, thereby further avoiding the problems that the information matching of the vehicle needs manual information collection and inventory checking by a clerk, which is time-consuming and easy to miss.
Further, in the invention, when the data analysis module determines that the vehicle accessory data uploaded by the user is text data, the text analysis unit of the data analysis module extracts text in the text data and matches the text with accessory information in the database, and when the data analysis module determines that the vehicle accessory data uploaded by the user is picture data, the image analysis unit of the data analysis module identifies resolution of the vehicle accessory image, so that the operation of the user is simpler and more convenient, and the efficiency of vehicle maintenance and communication is further improved.
In particular, when the resolution of the frame number picture is unqualified, the interpolation of the shot image of the frame number is adjusted according to the comparison result of the vehicle type difference value and the preset vehicle type difference value, so that the resolution of the frame number picture is adjusted, the operation of a user is further simplified, and the accuracy is improved.
Drawings
FIG. 1 is a flow chart of the data matching method for vehicle accessory transactions;
FIG. 2 is a logical block diagram of the data matching method for vehicle accessory transactions;
fig. 3 is a logic block diagram of the data matching method for vehicle accessory transactions.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1-3, fig. 1 is a flow chart of the data matching method for vehicle accessory transactions; FIG. 2 is a logical block diagram of the data matching method for vehicle accessory transactions; fig. 3 is a logic block diagram of the data matching method for vehicle accessory transactions.
According to the embodiment of the invention, the customer service personnel manually create the micro-letter groups between the service provider and the repair shop, each micro-letter group is in one-to-one correspondence with one repair shop, and the service provider and the repair shop are distinguished by ID numbers.
The invention discloses a data matching method for vehicle accessory transaction, which comprises the following steps:
s1, a data acquisition module acquires a shooting image of a frame number uploaded by a user;
s2, the data analysis module analyzes the resolution of the shot image of the frame number acquired by the data acquisition module, and whether the resolution of the shot image of the frame number is qualified or not is determined;
when the data analysis module determines that the resolution of the shot image of the frame number is qualified, the data matching module mobilizes a database to autonomously match the vehicle model, when the resolution of the shot image of the frame number is determined to be unqualified, the data analysis module determines interpolation of interpolation processing on the shot image of the frame number, and the data matching module matches the shot image of the frame number which is completed by interpolation with the vehicle types in the database and determines whether the matching is successful or not according to the number of the matched vehicle types;
step S3, when the data matching module is matched with the vehicle type, the data acquisition module acquires vehicle accessory data uploaded by a user, and the data analysis module analyzes the vehicle accessory data and determines an analysis result;
step S4, the data matching module determines whether the vehicle accessory is matched according to the analysis result;
s5, analyzing the damage degree of the vehicle accessories by the data analysis module, and judging to repair or replace the accessories according to the damage degree;
in the step S3, when the data analysis module determines that the vehicle accessory data uploaded by the user is text data, the text analysis unit of the data analysis module extracts text in the text data and matches the text with accessory information in the database, and when the data analysis module determines that the vehicle accessory data uploaded by the user is picture data, the image analysis unit of the data analysis module identifies resolution of the vehicle accessory image.
Specifically, in the step S2, when the data analysis module analyzes the resolution of the captured image of the frame number acquired by the data acquisition module, the data analysis module determines the resolution Q1 of the captured image of the frame number, compares the resolution Q1 with a preset resolution Q, determines whether the resolution of the frame number image is qualified according to the comparison result,
if Q1 is less than Q, the data analysis module judges that the resolution of the shot image of the frame number is not qualified;
and if Q1 is more than or equal to Q, the data analysis module judges that the resolution of the shot image of the frame number is qualified.
Specifically, in the step S2, when the data analysis module determines that the resolution of the photographed image of the frame number is not acceptable, a first resolution difference Δqa between the resolution Q1 of the photographed image of the frame number and a preset resolution Q is calculated, Δqa=q-Q1 is set, and a corresponding interpolation is determined according to a comparison result of the first resolution difference and the preset resolution difference to process the photographed image of the frame number,
wherein the data analysis module is provided with a first preset resolution difference delta Q1, a second preset resolution difference delta Q2, a first interpolation W1, a second interpolation W2 and a third interpolation W3, wherein delta Q1 < [ delta ] Q2, W1 < W2 < W3,
if delta Qa is less than or equal to delta Q1, the data analysis module judges that a first interpolation W1 is selected to process the photographed image of the frame number;
if delta Q1 is less than delta Qa is less than or equal to delta Q2, the data analysis module judges that a second interpolation W2 is selected to process the photographed image of the frame number;
and if delta Qa > [ delta ] Q2, the data analysis module judges that a third interpolation W3 is selected to process the photographed image of the frame number.
Specifically, in the step S2, when the data analysis module determines that the resolution of the shot image of the frame number is qualified or the shot image processing of the frame number is completed, the data matching module matches the shot image of the frame number with a frame number corresponding to a vehicle type in the database, and compares the number P of matched vehicle types with the number of preset vehicle types, wherein the data analysis module is further provided with a first number P1 of preset vehicle types and a second number P2 of preset vehicle types, P1 < P2,
if p=p1, the data analysis module determines that the vehicle type matching is completed;
if P1 is more than P and less than or equal to P2, the data analysis module determines to adjust the interpolation;
if P is more than P2, the data analysis module performs error reporting processing.
Specifically, in the step S2, when the data analysis module determines that the interpolation is adjusted, calculating a vehicle type number difference Δp between the matched vehicle type number P and a second preset vehicle type number P2, setting Δp=p2-P, adjusting the interpolation of the captured image of the frame number according to the comparison result of the vehicle type number difference and the preset vehicle type number difference,
wherein the data analysis module is provided with a first vehicle type preset difference value delta P1, a second vehicle type preset difference value delta P2, a first interpolation coefficient x1, a second interpolation coefficient x2 and a third interpolation coefficient x3, x1 is more than 1 and less than x2 and x3 is more than 1.5,
if delta P is less than or equal to delta P1, the data analysis module judges that a first interpolation coefficient x3 is selected to adjust the interpolation;
if delta P1 is less than delta P2, the data analysis module judges that a second interpolation coefficient x2 is selected to adjust the interpolation;
if delta P > -delta P2, the data analysis module judges that a third interpolation coefficient x1 is selected to adjust the interpolation;
when the data analysis module determines that the interpolation coefficient adjusted for interpolation is xi, i=1, 2,3 is set, the adjusted interpolation is set to Wa, wa=wc×xi, c is 1,2,3, xi is the interpolation coefficient.
Specifically, in the step S3, when the data analysis module analyzes the vehicle accessory data, if the vehicle accessory data is text data, the text analysis unit of the data analysis module extracts text in the text data and matches the text with accessory information in a database, and if matching is consistent with the accessory in the database, matching is completed; if the matching of the accessories is not consistent in the database, searching in big data;
when the data analysis module analyzes the vehicle accessory data, if the vehicle accessory data is image data, the image analysis unit of the data analysis module identifies the resolution of the vehicle accessory image, the data analysis module calculates the resolution Q2 of the vehicle accessory image, compares the resolution Q2 of the vehicle accessory image with a preset resolution Q, determines whether the resolution of the vehicle accessory image meets the standard according to the comparison result,
if Q2 is less than Q, the data analysis module judges that the resolution of the vehicle accessory image does not reach the standard;
and if Q2 is more than or equal to Q, the data analysis module judges that the resolution of the vehicle accessory image meets the standard.
Specifically, when the data analysis module determines that the resolution of the vehicle accessory image meets the standard, if the vehicle accessory is not matched in the database, matching is performed in big data; if only one vehicle accessory is matched in the database, the matching is completed; and if the matching results of various vehicle accessories exist in the database, adjusting the preset resolution.
Specifically, when the data analysis module determines to adjust the preset resolution, determining a vehicle accessory type R in the matching result, determining a correction coefficient of the corresponding preset resolution according to a comparison result of the vehicle accessory type and the preset vehicle accessory type in the matching result,
wherein the data analysis module is provided with a first preset vehicle accessory type R1, a second preset vehicle accessory type R2, a second preset resolution difference delta Q4, a first resolution correction coefficient k1, a second resolution correction coefficient k2 and a third resolution correction coefficient k3, R1 is more than R2, k1 is more than 1 and k2 is more than 1 and k3 is less than 1.2,
if R is less than or equal to R1, the data analysis module judges that a first preset resolution correction coefficient k1 is selected to adjust the preset resolution;
if R1 is more than R and less than or equal to R2, the data analysis module judges that a second preset resolution correction coefficient k2 is selected to adjust the preset resolution;
if R is more than R2, the data analysis module judges that a third preset resolution correction coefficient k3 is selected to adjust the preset resolution;
when the data analysis module determines that the correction coefficient for the preset resolution is ki, setting i=1, 2,3, and setting the adjusted preset resolution as Qj, wherein qj=q×ki, and ki is the correction coefficient of the preset resolution.
Specifically, when the data analysis module determines that the resolution of the vehicle accessory image does not reach the standard, a second resolution difference DeltaQb between the resolution Q2 of the vehicle accessory image and a preset resolution Q is calculated, deltaQb=Q-Q2 is set, and corresponding interpolation is determined according to the comparison result of the second resolution difference and the preset resolution difference so as to process the vehicle accessory image, wherein a fourth interpolation W4, W3 < W4 is further arranged in the data analysis module,
if delta Qb is less than or equal to delta Q1, the data analysis module judges that a second interpolation W2 is selected to process the vehicle accessory image;
if DeltaQ 1 < DeltaQbis less than or equal to DeltaQ 2, the data analysis module judges that a third interpolation W3 is selected to process the vehicle accessory image;
if DeltaQb > DeltaQ2, the data analysis module determines to select a fourth interpolation W4 to process the vehicle accessory image.
Specifically, in the step S5, when the data matching module determines that the vehicle accessory is matched according to the analysis result, the damage index Z of the vehicle accessory is calculated, z=u/u0+e/E0 is set, the data analysis module determines to repair or replace the vehicle accessory according to the comparison result of the damage index of the accessory and a preset damage index,
wherein the data analysis module is provided with a first preset damage index Z1, U is the crack length of the vehicle accessory, U0 is the preset crack length of the vehicle accessory, E is the number of damaged parts of the vehicle accessory, E0 is the number of preset damaged parts of the vehicle accessory,
if Z is less than or equal to Z1, the data analysis module judges that the vehicle accessory is maintained;
if Z is greater than Z1, the data analysis module determines to replace the vehicle accessory.
According to the embodiment of the invention, the customer service personnel manually create the micro-letter groups between the service provider and the repair shop, each micro-letter group is in one-to-one correspondence with one service provider and one repair shop, and the service provider and the repair shop are distinguished by ID numbers; the repair shop can directly shoot the image of the frame number in the WeChat group, the vehicle model of the vehicle is automatically identified after the identification is successful, when the vehicle model is successfully identified, the image acquisition module analyzes according to the acquired text data or image data of the vehicle accessory and matches the acquired text data or image data with the vehicle accessory in the database, and after the matching is successful, the data analysis module analyzes the damage index of the vehicle accessory and selects to repair or replace according to the damage degree.
In the embodiment of the invention, when a repair shop makes an order for a certain vehicle accessory, the system autonomously judges whether a service provider has an inventory, if so, a button can be clicked to make the order and pay through WeChat, and if the inventory is insufficient, the system can prompt that the inventory is insufficient and the order making operation cannot be performed.
In the embodiment of the invention, after a repair shop places an order for a certain vehicle accessory, a service provider clicks a receiving button on a system to finish shipping operation, packages the vehicle accessory offline and distributes the vehicle accessory to a management shop, and clicks a receiving button to finish receiving the vehicle accessory after the repair shop receives the vehicle accessory, so that the order is finished.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A data matching method for vehicle accessory transactions, comprising:
s1, a data acquisition module acquires a shooting image of a frame number uploaded by a user;
s2, the data analysis module analyzes the resolution of the shot image of the frame number acquired by the data acquisition module, and whether the resolution of the shot image of the frame number is qualified or not is determined;
when the data analysis module determines that the resolution of the shot image of the frame number is qualified, the data matching module mobilizes a database to autonomously match the vehicle model, when the resolution of the shot image of the frame number is determined to be unqualified, the data analysis module determines interpolation of interpolation processing on the shot image of the frame number, and the data matching module matches the shot image of the frame number which is completed by interpolation with the vehicle types in the database and determines whether the matching is successful or not according to the number of the matched vehicle types;
step S3, when the data matching module is matched with the vehicle type, the data acquisition module acquires vehicle accessory data uploaded by a user, and the data analysis module analyzes the vehicle accessory data and determines an analysis result;
step S4, the data matching module determines whether the vehicle accessory is matched according to the analysis result;
s5, analyzing the damage degree of the vehicle accessories by the data analysis module, and judging to repair or replace the accessories according to the damage degree;
in the step S3, when the data analysis module determines that the vehicle accessory data uploaded by the user is text data, the text analysis unit of the data analysis module extracts text in the text data and matches the text with accessory information in the database, and when the data analysis module determines that the vehicle accessory data uploaded by the user is picture data, the image analysis unit of the data analysis module identifies resolution of the vehicle accessory image.
2. The data matching method for vehicle accessory transactions according to claim 1, wherein in the step S2, when the data analysis module analyzes the resolution of the photographed image of the vehicle frame number collected by the data collection module, the data analysis module determines the resolution Q1 of the photographed image of the vehicle frame number, compares the resolution Q1 with a preset resolution Q, determines whether the resolution of the vehicle frame number image is qualified according to the comparison result,
if Q1 is less than Q, the data analysis module judges that the resolution of the shot image of the frame number is not qualified;
and if Q1 is more than or equal to Q, the data analysis module judges that the resolution of the shot image of the frame number is qualified.
3. The data matching method for vehicle accessory transactions according to claim 2, wherein in the step S2, when the data analysis module determines that the resolution of the photographed image of the vehicle frame number is not acceptable, a first resolution difference Δqa between the resolution Q1 of the photographed image of the vehicle frame number and a preset resolution Q is calculated, Δqa=q-Q1 is set, and a corresponding interpolation is determined according to a comparison result of the first resolution difference and the preset resolution difference to process the photographed image of the vehicle frame number,
wherein the data analysis module is provided with a first preset resolution difference delta Q1, a second preset resolution difference delta Q2, a first interpolation W1, a second interpolation W2 and a third interpolation W3, wherein delta Q1 < [ delta ] Q2, W1 < W2 < W3,
if delta Qa is less than or equal to delta Q1, the data analysis module judges that a first interpolation W1 is selected to process the photographed image of the frame number;
if delta Q1 is less than delta Qa is less than or equal to delta Q2, the data analysis module judges that a second interpolation W2 is selected to process the photographed image of the frame number;
and if delta Qa > [ delta ] Q2, the data analysis module judges that a third interpolation W3 is selected to process the photographed image of the frame number.
4. The data matching method for vehicle accessory transactions according to claim 3, wherein in said step S2, when said data analysis module determines that the resolution of the photographed image of the vehicle frame number is acceptable or the photographed image processing of the vehicle frame number is completed, said data matching module matches the photographed image of the vehicle frame number with a vehicle frame number corresponding to a vehicle type in said database and compares the number P of matched vehicle types with a preset number of vehicle types, wherein said data analysis module is further provided with a first preset number P1 of vehicle types and a second preset number P2 of vehicle types, P1 < P2,
if p=p1, the data analysis module determines that the vehicle type matching is completed;
if P1 is more than P and less than or equal to P2, the data analysis module determines to adjust the interpolation;
if P is more than P2, the data analysis module performs error reporting processing.
5. The data matching method for vehicle accessory transactions according to claim 4, wherein in the step S2, when the data analysis module determines that the interpolation is adjusted, a vehicle type number difference Δp between the matched vehicle type number P and a second preset vehicle type number P2 is calculated, Δp=p2-P is set, the interpolation of the photographed image of the vehicle frame number is adjusted according to the comparison result of the vehicle type number difference and the preset vehicle type number difference, and the adjusted interpolation is set to W4, w4=wc×xi, c is 1,2,3, xi is an interpolation coefficient.
6. The data matching method for vehicle accessory transaction according to claim 5, wherein in the step S3, when the data analysis module analyzes the vehicle accessory data, if the vehicle accessory data is text data, the text analysis unit of the data analysis module extracts text in the text data and matches the text with accessory information in a database, and if the matching is consistent with the accessory matching in the database, the matching is completed; if the matching of the accessories is not consistent in the database, searching in big data;
when the data analysis module analyzes the vehicle accessory data, if the vehicle accessory data is image data, the image analysis unit of the data analysis module identifies the resolution of the vehicle accessory image, the data analysis module calculates the resolution Q2 of the vehicle accessory image, compares the resolution Q2 of the vehicle accessory image with a preset resolution Q, determines whether the resolution of the vehicle accessory image meets the standard according to the comparison result,
if Q2 is less than Q, the data analysis module judges that the resolution of the vehicle accessory image does not reach the standard;
and if Q2 is more than or equal to Q, the data analysis module judges that the resolution of the vehicle accessory image meets the standard.
7. The data matching method for vehicle accessory transactions of claim 6, wherein when the data analysis module determines that the resolution of the vehicle accessory image meets the standard, matching is performed in big data if no vehicle accessory is matched in the database; if only one vehicle accessory is matched in the database, the matching is completed; and if the matching results of various vehicle accessories exist in the database, adjusting the preset resolution.
8. The method according to claim 7, wherein when the data analysis module determines that the preset resolution is adjusted, a vehicle accessory type R in the matching result is determined, a correction coefficient of the corresponding preset resolution is determined according to a comparison result of the vehicle accessory type and the preset vehicle accessory type in the matching result, and the corrected preset resolution is set to Qj, qj=q×ki, ki is the correction coefficient of the preset resolution.
9. The data matching method for vehicle accessory transactions according to claim 8, wherein when the data analysis module determines that the resolution of the vehicle accessory image does not reach the standard, a second resolution difference Δqb between the resolution Q2 of the vehicle accessory image and a preset resolution Q is calculated, Δqb=q-Q2 is set, and a corresponding interpolation is determined according to a comparison result of the second resolution difference and the preset resolution difference to process the vehicle accessory image, wherein a fourth interpolation W4, W3 < W4,
if delta Qb is less than or equal to delta Q1, the data analysis module judges that a second interpolation W2 is selected to process the vehicle accessory image;
if DeltaQ 1 < DeltaQbis less than or equal to DeltaQ 2, the data analysis module judges that a third interpolation W3 is selected to process the vehicle accessory image;
if DeltaQb > DeltaQ2, the data analysis module determines to select a fourth interpolation W4 to process the vehicle accessory image.
10. The data matching method for vehicle accessory transactions according to claim 9, wherein in the step S5, when the data matching module determines that the vehicle accessory is matched according to the analysis result, the damage index Z of the vehicle accessory is calculated, z=u/u0+e/E0 is set, the data analysis module determines to repair or replace the vehicle accessory according to the comparison result of the damage index of the accessory and a preset damage index,
wherein the data analysis module is provided with a first preset damage index Z1, U is the crack length of the vehicle accessory, U0 is the preset crack length of the vehicle accessory, E is the number of damaged parts of the vehicle accessory, E0 is the number of preset damaged parts of the vehicle accessory,
if Z is less than or equal to Z1, the data analysis module judges that the vehicle accessory is maintained;
if Z is greater than Z1, the data analysis module determines to replace the vehicle accessory.
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