CN116188411A - Method and system for detecting paint surface, film thickness and quality of automobile - Google Patents
Method and system for detecting paint surface, film thickness and quality of automobile Download PDFInfo
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Abstract
The application relates to an automobile paint surface and film thickness quality detection method, which relates to the field of automobile detection and comprises the steps of acquiring automobile paint surface and film thickness data on line, wherein the automobile paint surface and film thickness data comprise a vehicle model, a three-dimensional model cloud image of the automobile paint surface and the film thickness data; inquiring various quality defects and film thickness expert dictionary library model data of a paint cloud image model of a preset vehicle surface corresponding to the vehicle model from a database; judging whether the paint surface is normal or not by comparing and deeply learning a three-dimensional data model of the paint surface and the film thickness of the vehicle and a quality cloud image model of the paint surface of an expert dictionary library; generating and executing a difference information prompt instruction according to the difference position information, wherein the difference information prompt instruction is used for prompting a difference position, a difference position paint quality confirmation model type and a preset paint quality three-dimensional cloud image model corresponding to the difference position to a detector; various quality defects of the paint cloud image model and film thickness expert dictionary library model data can be dynamically added and maintained. The application has the effect of improving detection efficiency.
Description
Technical Field
The application relates to the field of automobile detection, in particular to an automobile paint surface and film thickness quality detection method.
Background
At present, the problem of purchasing a second-hand vehicle is that a power system, a chassis and an appearance are not remarkable, a user can know whether a vehicle has an accident or not from the paint surface of the vehicle, if the second-hand vehicle belongs to the accident, the paint surface of the vehicle is affirmed to have marks such as metal plates or paint spraying repair and the like, and the repair range is larger, so that the detection of the second-hand accident vehicle is only related, the paint surface detection project is indispensable, the history of the accident of the size of the vehicle is revealed, and whether the vehicle belongs to the accident vehicle is judged.
Aiming at the related technology, when the vehicles are detected at present, when the vehicles have the condition of paint spraying and repairing, a detector needs to find a paint spraying place and shoot the paint spraying place to leave a record, and when the vehicles needing to be detected are more, the detection in the mode takes longer, and the detection efficiency is lower.
Disclosure of Invention
In order to improve detection efficiency, the application provides an automobile paint surface and film thickness quality detection method.
In a first aspect, the present application provides a method for detecting paint surface and film thickness quality of an automobile, which adopts the following technical scheme:
a method for detecting the paint surface and the film thickness quality of an automobile comprises the following steps:
acquiring vehicle information, wherein the vehicle information comprises a vehicle model and a vehicle paint three-dimensional model;
inquiring a preset paint three-dimensional model corresponding to the vehicle model from a database according to the vehicle model;
comparing the vehicle paint three-dimensional model with a preset paint three-dimensional model;
if the vehicle paint three-dimensional model is overlapped with the preset paint three-dimensional model, generating a paint normal prompting instruction and executing the paint normal prompting instruction, wherein the paint normal prompting instruction is used for prompting a inspector that the paint is normal;
if the vehicle paint three-dimensional model is not overlapped with the preset paint three-dimensional model, acquiring difference position information;
and generating and executing a difference information prompt instruction according to the difference position information, wherein the difference information prompt instruction is used for prompting a difference position, a difference position paint surface model and a preset paint surface three-dimensional model corresponding to the difference position to a detector.
By adopting the technical scheme, the system scans the vehicle to be detected, acquires the vehicle paint data, acquires the vehicle paint three-dimensional model in a three-dimensional modeling mode, acquires the vehicle model input by a detector, automatically queries the preset paint three-dimensional model corresponding to the vehicle model from the database, compares the two models, detects whether the two models coincide, indicates that the paint is normal if the two models coincide, executes a paint normal prompt command, and prompts the detector that the paint is normal. If the two models are not overlapped, the difference position information is automatically acquired, a difference position information prompt instruction is executed, and a phase detector prompts the difference position, the difference position paint surface model and the preset paint surface three-dimensional model, so that the phenomenon that the detector shoots one by one is reduced when detecting a plurality of vehicles, and the detection efficiency is improved.
Optionally, if the vehicle paint three-dimensional model is not overlapped with the preset paint three-dimensional model, the step of obtaining the difference position information includes:
acquiring a difference position;
and generating and executing an abnormal marking instruction according to the difference position, wherein the abnormal marking instruction is used for marking the difference position of the three-dimensional model of the vehicle paint surface and then the abnormal marking.
By adopting the technical scheme, the system acquires the positions where the paint surfaces have differences, performs the operation of abnormal marking, and performs the abnormal marking on the three-dimensional model of the vehicle paint surfaces, so that the detection personnel can find the abnormal positions conveniently.
Optionally, after the step of comparing the vehicle paint three-dimensional model with the preset paint three-dimensional model, the method includes:
acquiring roof film thickness data and whole vehicle film thickness data;
comparing the roof film thickness data with the whole vehicle film thickness data;
if the whole vehicle film thickness data is equal to the vehicle roof film thickness data, generating and executing a film thickness normal prompt instruction, wherein the film thickness sign prompt instruction is used for prompting a inspector that the whole vehicle film thickness is normal;
if the whole car film thickness data is different from the car roof film thickness data, acquiring a film thickness abnormal position;
and generating and executing a film thickness abnormal position prompt instruction according to the film thickness abnormal position, wherein the film thickness abnormal position prompt instruction is used for prompting a detector of the film thickness abnormal position.
By adopting the technical scheme, the system detects the thickness of the roof, scans the thickness of the whole car at the same time, compares the thickness data of the roof with the thickness data of the whole car, and if the thickness data of the whole car is identical to the thickness data of the roof, proves that the thickness of the whole car is normal, executes the operation of prompting the thickness of the whole car to be normal, prompts the detection personnel to the thickness of the whole car to be normal, if the thickness of the whole car is different from the thickness of the roof, automatically acquires the thickness abnormal position, executes the operation of prompting the thickness abnormal position, prompts the detection personnel to the thickness abnormal position, and is convenient for the detection personnel to accurately know the thickness abnormal position.
Optionally, after generating the film thickness abnormal position prompt instruction according to the film thickness abnormal position and executing the steps, the method includes:
obtaining abnormal film thickness data;
inquiring a paint-compensating film thickness interval corresponding to the abnormal film thickness data from a preset database;
judging whether the abnormal film thickness data is positioned in a paint-repairing film thickness section or not;
if the paint is in the paint repairing film thickness interval, generating and executing a paint repairing prompt instruction, wherein the paint repairing prompt instruction is used for prompting a inspector to repair paint at an abnormal position.
By adopting the technical scheme, the system acquires the abnormal film thickness data, compares the abnormal film thickness data with the paint repair film thickness section, judges whether the abnormal film thickness data is positioned in the paint repair film thickness section, and if the abnormal film thickness data is positioned in the paint repair film thickness section, proves that paint repair is performed at the abnormal position, executes paint repair prompt operation, prompts paint repair at the abnormal position to the detection personnel, and is further beneficial to reducing the process of judging the abnormal position by the detection personnel.
Optionally, after the step of judging whether the abnormal film thickness data is located in the paint repair film thickness interval, the method includes:
if the abnormal film thickness data exceeds the paint repair film thickness interval threshold value, inquiring a sheet metal repair film thickness interval corresponding to the abnormal film thickness data from a preset database;
judging whether the abnormal film thickness data is positioned in a sheet metal repair film thickness section or not;
if the position is located in the sheet metal repair film thickness section, a sheet metal repair prompt instruction is generated and executed, and the sheet metal repair prompt instruction is used for prompting a detector to repair the sheet metal at an abnormal position.
Through adopting above-mentioned technical scheme, when unusual membrane thickness output exceeded the interval threshold value of lacquer film thickness of mending, contrast unusual membrane thickness data and panel beating restoration film thickness interval, if unusual membrane thickness data is located panel beating restoration film thickness interval, carry out the operation of panel beating restoration suggestion, indicate to the inspection crew that unusual position department has carried out the panel beating restoration, be favorable to reducing the inspection crew and judge whether carry out the process of panel beating restoration.
Optionally, the step of comparing the vehicle paint three-dimensional model with the preset paint three-dimensional model includes:
generating and executing a model splitting instruction according to the vehicle paint three-dimensional model, wherein the model splitting instruction is used for splitting the vehicle paint three-dimensional model;
acquiring a key model mark position;
generating a model marking instruction according to the key model marking position, and executing the model marking instruction to mark on the three-dimensional model according to the key model marking position;
obtaining a marked three-dimensional model according to the model marking instruction;
and generating and executing a key model mark position retest instruction according to the marked three-dimensional model, wherein the key model mark position retest instruction is used for repeatedly detecting paint surface data for the key model mark position.
By adopting the technical scheme, the system splits the generated vehicle paint three-dimensional model according to the structure, obtains the key model marking position recorded by the detection personnel, marks the three-dimensional model according to the key model marking position, scans the paint at the key model marking position again, and re-detects the paint, thereby being beneficial to reducing the phenomenon of false detection and improving the detection accuracy.
Optionally, after generating a model splitting instruction according to the vehicle paint three-dimensional model and executing the steps, the method includes:
acquiring the service life of a structure and the registration time of a vehicle;
comparing the service life of the structure with the vehicle registration time;
if the service life of the structure is equal to the vehicle registration time, generating and executing a structure non-replacement prompting instruction, wherein the structure non-replacement prompting instruction is used for prompting a inspector that the vehicle structure is not replaced;
if the service life of the structure is less than the vehicle registration time, generating a structure replacement prompt instruction corresponding to the structure and executing the structure replacement prompt instruction, wherein the structure replacement prompt instruction is used for prompting a inspector that the structure is replaced.
Through adopting above-mentioned technical scheme, the system acquires the life of each structure, compares life and vehicle registration time, if structure life and vehicle registration time etc. simultaneously, carries out the operation that the suggestion structure was not changed, and the suggestion that should structure is not changed to the inspector, if structure life is less than vehicle registration time, carries out the operation that the suggestion is changed to the structure, and suggestion inspector should structure is changed, is favorable to reducing the inspector and carries out the operation of inspection to the structure one by one.
In a second aspect, the present application provides an automotive paint and film thickness quality inspection system.
Automobile paint surface and film thickness quality detecting system includes:
the information acquisition module is used for acquiring a vehicle model and a vehicle paint three-dimensional model;
the paint surface comparison module is used for comparing the vehicle paint surface three-dimensional model with a preset paint surface three-dimensional model;
the paint surface sign prompt module is used for prompting the detection personnel that the paint surface is normal;
the difference information prompt module is used for prompting difference information to the detection personnel.
In a third aspect, the present application provides a computer device, which adopts the following technical scheme: comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and execute any one of the automobile paint surface and film thickness quality detection methods.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical solutions: a computer program capable of being loaded by a processor and executing any one of the above-described methods for detecting the paint and film thickness quality of an automobile is stored.
In summary, the application comprises at least one of the following beneficial technical effects of the automobile paint surface and film thickness quality detection method:
1. the system scans the vehicle to be detected, acquires vehicle paint data, acquires a vehicle paint three-dimensional model in a three-dimensional modeling mode, acquires the vehicle model input by a detector, automatically queries a preset paint three-dimensional model corresponding to the vehicle model from a database, compares the two models, detects whether the two models coincide, if so, indicates that the paint is normal, executes a paint normal prompt command, and prompts the detector that the paint is normal. If the two models are not overlapped, the difference position information is automatically acquired, a difference position information prompt instruction is executed, and a phase detector prompts the difference position, the difference position paint surface model and the preset paint surface three-dimensional model, so that the phenomenon that the detector shoots one by one is reduced when detecting a plurality of vehicles, and the detection efficiency is improved.
Drawings
FIG. 1 is a schematic flow chart of a method for detecting the paint surface and the film thickness quality of an automobile.
Fig. 2 is a flow chart of sub-steps of S1051 in one embodiment of the present application.
FIG. 3 is a complementary flow chart of a method for detecting paint and film thickness quality of an automobile in one embodiment of the present application.
Fig. 4 is a flow chart of sub-steps of S205 in one embodiment of the present application.
Fig. 5 is a flow chart of sub-steps of S205 in one embodiment of the present application.
FIG. 6 is a complementary flow chart of a method for detecting paint and film thickness quality of an automobile in one embodiment of the present application.
Fig. 7 is a flow chart of sub-steps of S301 in one embodiment of the present application.
Fig. 8 is a block diagram of a module for implementing detection of paint and film thickness quality of an automobile in an embodiment of the application.
Reference numerals illustrate: 1. an information acquisition module; 2. a paint surface comparison module; 3. a paint surface sign prompt module; 4. a difference information prompt module; 5. a paint surface abnormality prompting module; 6. a film thickness abnormality prompting module; 7. a paint repair judging module; 8. a sheet metal repair judging module; 9. and a retest prompting module.
Detailed Description
The present application is described in further detail below with reference to the accompanying drawings.
A method for detecting the paint surface and film thickness of car features that when the paint surface of car is detected, the abnormal position is automatically found, and the abnormal film thickness is found to prompt the detection personnel.
In one embodiment, referring to fig. 1, to improve detection efficiency, the method includes the steps of:
s101, acquiring vehicle information;
specifically, the system scans the detected vehicle to obtain vehicle paint data, a three-dimensional modeling mode is adopted to obtain a three-dimensional model of the vehicle paint, and meanwhile, the system obtains the vehicle model input by the detection personnel.
S102, inquiring a preset paint three-dimensional model corresponding to the vehicle model from a database;
s103, comparing the vehicle paint three-dimensional model with a preset paint three-dimensional model;
specifically, after the system obtains the vehicle model, a preset paint three-dimensional model corresponding to the vehicle model is queried from a preset database, the two models are compared, and the system detects whether the two models are coincident.
S104, if the vehicle paint three-dimensional model is overlapped with a preset paint model, generating a paint normal prompt instruction and executing;
specifically, if the vehicle paint three-dimensional model is overlapped with the preset paint three-dimensional model, the paint is normal, the operation of normal prompt of the paint is executed, and the detection personnel is prompted that the vehicle paint is normal.
S105, if the vehicle paint three-dimensional model is not overlapped with the preset paint three-dimensional model, acquiring difference position information;
s106, generating a difference information prompt instruction and executing the difference information prompt instruction;
specifically, by comparing and deeply learning the expert dictionary library paint quality cloud picture model, if the vehicle paint three-dimensional model is not overlapped with the preset paint three-dimensional model, the system automatically acquires the difference position information, executes the operation of the difference position information prompt, prompts the difference position, the difference position paint model and the preset paint three-dimensional model to detection personnel, and the detection personnel can finish detection by printing the difference position information.
In one embodiment, referring to fig. 2, to facilitate the detection personnel to find the abnormal location, after S105, the following specific steps are included:
s1051, obtaining a difference position;
s1052, generating and executing an abnormal coordinate instruction;
specifically, after the system detects that the vehicle paint surface is abnormal, the system automatically searches for a difference position, queries abnormal paint surface data types from a preset database, compares the detected difference position, judges abnormal paint surface types at the difference position, and comprises paint sagging, paint film impurities, paint film pinholes and paint film orange peel, performs abnormal marking operation according to the abnormal paint surface types, performs abnormal marking at a vehicle paint surface three-dimensional model, and further facilitates detection personnel to find the abnormal position, and meanwhile judges the abnormal paint surface types.
In one embodiment, referring to fig. 3, in order for the inspector to accurately understand the abnormal film thickness position, after S103, the method comprises the following specific steps:
s201, acquiring roof film thickness data and whole vehicle film thickness data;
specifically, the system acquires the thickness of the whole car through the laser reflection system, detects the thickness of the roof, and collects the thickness of the whole car and the thickness of the roof.
S202, comparing the vehicle roof film thickness data with the vehicle film thickness data;
s203, if the whole vehicle film thickness data is equal to the roof film thickness data, generating film thickness normal prompt execution and executing;
specifically, the roof film thickness data and the whole vehicle film thickness data are compared, the roof is of a structure which is not easy to damage, the film thickness is normal, if the whole vehicle film thickness data are identical to the roof film thickness data, the operation of film thickness normal prompt is executed, and the detection personnel is prompted that the whole vehicle film thickness is normal.
S204, if the whole car film thickness data is different from the car roof film thickness data, acquiring a film thickness abnormal position;
s205, generating and executing a film thickness abnormal position prompt instruction;
specifically, if the whole vehicle film thickness data is different from the vehicle roof film thickness data, the system automatically acquires the position of the film thickness abnormality, performs film thickness abnormality marking on the vehicle paint three-dimensional model, simultaneously executes the operation of prompting the film thickness abnormality position, prompts the position of the film thickness abnormality to a detector, and is convenient for the detector to accurately know the position of the film thickness abnormality, and the vehicle roof film thickness data can be dynamically added and maintained.
In one embodiment, referring to fig. 4, to reduce the process of the inspector' S judgment of the paint repair place, after S205, the following specific steps are included:
s2051, acquiring abnormal film thickness data;
s2052, inquiring a paint-supplementing film thickness interval corresponding to the abnormal film thickness from a preset database;
specifically, the system acquires abnormal film thickness data, for example, 250 μm, and searches a paint repair film thickness section corresponding to the abnormal film thickness from a preset database, for example, 150 μm to 300 μm.
S2053, judging whether the abnormal film thickness data is positioned in a paint film thickness section;
s2054, if the abnormal film thickness data is located in the paint repair film thickness section, generating a paint repair prompt instruction and executing the paint repair prompt instruction;
specifically, the abnormal film thickness data is in the paint repair film thickness interval, paint repair prompt operation is executed, paint repair is prompted to the abnormal film thickness position of the position to be detected by a detector, and therefore the process of judging whether paint repair is performed to the abnormal position by the detector is facilitated to be reduced.
In one embodiment, referring to fig. 5, in order to reduce the process of determining whether the sheet metal repair is performed by the inspector, after S2053, the method includes the following specific steps:
s2055, if the abnormal film thickness data exceeds the paint repair film thickness interval threshold value, inquiring a sheet metal repair film thickness interval corresponding to the abnormal film thickness data from a preset database;
s2056, judging whether the abnormal film thickness data is positioned in a sheet metal repair film thickness section;
s2057, if the abnormal film thickness data is located in the film thickness repairing section of the metal plate, generating a metal plate repairing prompt instruction and executing the metal plate repairing prompt instruction;
specifically, the abnormal film thickness data takes 350 μm as an example, the abnormal film thickness data exceeds a paint-compensating film thickness interval threshold value, a sheet metal repair film thickness interval corresponding to the abnormal film thickness is inquired from a preset database, the sheet metal repair film thickness interval takes 300 μm to 500 μm as an example, whether the abnormal film thickness data is located in the sheet metal repair film thickness interval is judged, the 350 μm is located in the sheet metal repair film thickness interval, further, the operation of sheet metal repair prompt is executed, the sheet metal repair is carried out at the abnormal position to prompt the detection personnel, and further, the process that the detection personnel judges whether the abnormal position is subjected to the sheet metal repair is reduced.
In one embodiment, referring to fig. 6, in order to reduce the false detection phenomenon, after S103, the method specifically includes the following steps:
s301, generating a model splitting instruction according to a vehicle paint three-dimensional model and executing the model splitting instruction;
specifically, the system separates the model according to the structure according to the three-dimensional model of the vehicle paint surface, taking a vehicle door and a vehicle body as examples.
S302, acquiring a key model mark position;
s303, generating and executing a model marking instruction;
s304, acquiring a marked three-dimensional model;
s305, generating and executing a retest instruction of the mark position of the key model;
specifically, the system acquires the key model marking position recorded by the detection personnel, marks the key model marking position on the three-dimensional model, and rescans the paint surface at the key model marking position to re-detect the paint surface data, thereby being beneficial to reducing the phenomenon of false detection and improving the detection accuracy.
In one embodiment, referring to fig. 7, in order to reduce the operations of checking the structure by the inspector one by one, after S301, the following steps are specifically included:
s3011, acquiring service life of a structure and vehicle registration time;
s3012, comparing the service life of the structure with the registration time of the vehicle;
s3013, if the service life of the structure is equal to the registration time of the vehicle, generating a structure non-replacement prompt instruction and executing the instruction;
s3014, if the service life of the structure is less than the vehicle registration time, generating a structure replacement prompt instruction corresponding to the structure and executing the instruction;
specifically, the system acquires the service life of each structure, compares the service life with the vehicle registration time, takes the service life of the structure as an example, and takes the service life of the structure as 5 years, the vehicle registration time is the same as the service life of the structure as the vehicle registration time, executes the operation of prompting that the structure is not replaced, and prompts that the structure is not replaced by a phase detector. The service life of the structure is 3 years as an example, the registration time of the vehicle is 5 years as an example, the service life of the structure is less than the registration time of the vehicle, the operation of prompting the replacement of the structure is executed, and the detection personnel is prompted to replace the structure, so that the detection personnel can be reduced to check the structure one by one.
In one embodiment, referring to fig. 8, based on the above-mentioned method for detecting the paint surface and the film thickness quality of an automobile, there is provided a system for detecting the paint surface and the film thickness quality of an automobile, which comprises the following modules:
the information acquisition module 1 is used for acquiring a vehicle model and a vehicle paint three-dimensional model;
the paint surface comparison module 2 is used for comparing the vehicle paint surface three-dimensional model with a preset paint surface three-dimensional model;
the paint sign prompt module 3 is used for prompting the detection personnel that the paint is normal;
the difference information prompting module 4 is used for prompting difference information to a detector;
the paint surface abnormality prompting module 5 is used for displaying abnormal positions to detection personnel;
the film thickness abnormality prompting module 6 is used for displaying the film thickness abnormality position to a detector;
the paint repair judging module 7 is used for judging whether the vehicle is subjected to paint repair or not;
the metal plate repair judging module 8 is used for judging whether the vehicle is subjected to metal plate repair or not;
the retest prompting module 9 is used for repeatedly detecting the vehicle paint surface;
in one embodiment, a computer device is provided that includes a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of a method for detecting automotive paint and film thickness quality as described above. The step of an automobile paint and film thickness quality detection method may be the step of an automobile paint and film thickness quality detection method of each of the above embodiments.
In one embodiment, a computer readable storage medium storing a computer program capable of being loaded by a processor and performing an automotive paint and film thickness quality detection method as described above is provided, for example, comprising: various media capable of storing program codes, such as a U disk, a removable hard disk, a Read-only memory (ROM), a random access memory (RandomAccessMemory, RAM), a magnetic disk, or an optical disk
The foregoing are all preferred embodiments of the present application, and are not intended to limit the scope of the present application in any way, therefore: all equivalent changes in structure, shape and principle of this application should be covered in the protection scope of this application.
Claims (10)
1. The method for detecting the thickness and quality of the automobile paint surface is characterized by comprising the following steps of:
acquiring vehicle information, wherein the vehicle information comprises a vehicle model and a vehicle paint three-dimensional model;
inquiring a preset paint three-dimensional model corresponding to the vehicle model from a database according to the vehicle model;
comparing the vehicle paint three-dimensional model with a preset paint three-dimensional model;
if the vehicle paint three-dimensional model is overlapped with the preset paint three-dimensional model, generating a paint normal prompting instruction and executing the paint normal prompting instruction, wherein the paint normal prompting instruction is used for prompting a inspector that the paint is normal;
if the vehicle paint three-dimensional model is not overlapped with the preset paint three-dimensional model, acquiring difference position information;
and generating and executing a difference information prompt instruction according to the difference position information, wherein the difference information prompt instruction is used for prompting a difference position, a difference position paint surface model and a preset paint surface three-dimensional model corresponding to the difference position to a detector.
2. The method for detecting the quality of a paint surface and a film thickness of an automobile according to claim 1, wherein the step of obtaining the difference position information if the three-dimensional model of the paint surface of the automobile is not overlapped with the three-dimensional model of the preset paint surface comprises:
acquiring a difference position;
and generating and executing an abnormal marking instruction according to the difference position, wherein the abnormal marking instruction is used for marking the difference position of the three-dimensional model of the vehicle paint surface and then the abnormal marking.
3. The method for detecting the quality of the paint surface and the film thickness of the automobile according to claim 1, wherein after the step of comparing the three-dimensional model of the paint surface of the automobile with the three-dimensional model of the preset paint surface, the method comprises the steps of:
acquiring roof film thickness data and whole vehicle film thickness data;
comparing the roof film thickness data with the whole vehicle film thickness data;
if the whole vehicle film thickness data is equal to the vehicle roof film thickness data, generating and executing a film thickness normal prompt instruction, wherein the film thickness sign prompt instruction is used for prompting a inspector that the whole vehicle film thickness is normal;
if the whole car film thickness data is different from the car roof film thickness data, acquiring a film thickness abnormal position;
and generating and executing a film thickness abnormal position prompt instruction according to the film thickness abnormal position, wherein the film thickness abnormal position prompt instruction is used for prompting a detector of the film thickness abnormal position.
4. The method for detecting the quality of a paint surface and a film thickness of an automobile according to claim 3, wherein the method comprises, after generating a film thickness abnormality position indication instruction based on the film thickness abnormality position and executing the steps of:
obtaining abnormal film thickness data;
inquiring a paint-compensating film thickness interval corresponding to the abnormal film thickness data from a preset database;
judging whether the abnormal film thickness data is positioned in a paint-repairing film thickness section or not;
if the paint is in the paint repairing film thickness interval, generating and executing a paint repairing prompt instruction, wherein the paint repairing prompt instruction is used for prompting a inspector to repair paint at an abnormal position.
5. The method for detecting the thickness and quality of paint film of an automobile according to claim 4, wherein after the step of judging whether the abnormal thickness data is located in the paint film thickness section, comprising:
if the abnormal film thickness data exceeds the paint repair film thickness interval threshold value, inquiring a sheet metal repair film thickness interval corresponding to the abnormal film thickness data from a preset database;
judging whether the abnormal film thickness data is positioned in a sheet metal repair film thickness section or not;
if the position is located in the sheet metal repair film thickness section, a sheet metal repair prompt instruction is generated and executed, and the sheet metal repair prompt instruction is used for prompting a detector to repair the sheet metal at an abnormal position.
6. The method for detecting the quality of the paint surface and the film thickness of the automobile according to claim 1, wherein the step of comparing the three-dimensional model of the paint surface of the automobile with the three-dimensional model of the preset paint surface comprises the steps of:
generating and executing a model splitting instruction according to the vehicle paint three-dimensional model, wherein the model splitting instruction is used for splitting the vehicle paint three-dimensional model;
acquiring a key model mark position;
generating a model marking instruction according to the key model marking position, and executing the model marking instruction to mark on the three-dimensional model according to the key model marking position;
obtaining a marked three-dimensional model according to the model marking instruction;
and generating and executing a key model mark position retest instruction according to the marked three-dimensional model, wherein the key model mark position retest instruction is used for repeatedly detecting paint surface data for the key model mark position.
7. The method for detecting the quality of the paint surface and the film thickness of the automobile according to claim 6, wherein after generating a model splitting instruction and executing the steps according to the three-dimensional model of the paint surface of the automobile, the method comprises the steps of:
acquiring the service life of a structure and the registration time of a vehicle;
comparing the service life of the structure with the vehicle registration time;
if the service life of the structure is equal to the vehicle registration time, generating and executing a structure non-replacement prompting instruction, wherein the structure non-replacement prompting instruction is used for prompting a inspector that the vehicle structure is not replaced;
if the service life of the structure is less than the vehicle registration time, generating a structure replacement prompt instruction corresponding to the structure and executing the structure replacement prompt instruction, wherein the structure replacement prompt instruction is used for prompting a inspector that the structure is replaced.
8. An automotive paint and film thickness quality detection system, comprising:
the information acquisition module (1) is used for acquiring a vehicle model and a vehicle paint three-dimensional model;
the paint surface comparison module (2) is used for comparing the vehicle paint surface three-dimensional model with a preset paint surface three-dimensional model;
the paint surface sign prompt module (3) is used for prompting a detector that the paint surface is normal;
and the difference information prompt module (4) is used for prompting the difference information to the detection personnel.
9. A computer device, characterized by: comprising a memory and a processor, said memory having stored thereon a computer program capable of being loaded by the processor and performing the method according to any of claims 1 to 7.
10. A computer-readable storage medium, characterized by: a computer program being stored which can be loaded by a processor and which performs the method according to any one of claims 1 to 7.
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