CN113808094A - Ray detection welding defect image rating system and method - Google Patents
Ray detection welding defect image rating system and method Download PDFInfo
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Abstract
The invention discloses a ray detection welding defect image rating system, which comprises: the system comprises an image acquisition module, an image processing module, a comprehensive rating module and a system management module, wherein the image acquisition module is used for acquiring defect images to be classified and transmitting the images to be classified to the image processing module; the image processing module is used for identifying the defect image to be classified, performing error analysis on the identified defect image to be classified, generating an analysis result and transmitting the analysis result to the comprehensive rating module; the comprehensive rating module is used for rating different types of defect images according to the analysis result; and the system management module is used for counting the data after the defective image is graded so as to generate a comprehensive calculation result. Through the data processing of the rating system, the comprehensive calculation rating of the negative film can be quickly completed, and the accuracy of the rating is high.
Description
Technical Field
The invention relates to the technical field of defect detection, in particular to a system and a method for grading welding defect images through ray detection.
Background
The problems that the construction site environment is complex, the welding quality requirement is extremely high, the follow-up remaining problem is difficult to process and the like are often existed in the welding process in the industrial scene, and the problems need to be solved urgently. In the whole construction process, nondestructive inspection is carried out on each welding place, a large number of radiographic films are generated in the whole process, each film needs to be evaluated by a certified film evaluation expert, and a large amount of labor cost and time cost are consumed in the whole process. And the physical film also has the problems of difficult preservation, large storage space occupation and the like.
Moreover, the negative needs to be rated after flaw detection operation is carried out by using a ray detector, and the negative rating is taken as a very important step, but is in a state of manual evaluation at present, so that the accuracy is poor, and the speed is very low.
Disclosure of Invention
Accordingly, there is a need for a radiation inspection welding defect image rating system that solves the above-mentioned problems.
According to one aspect of the invention, a ray inspection welding defect image rating system is provided, comprising:
image acquisition module, image processing module, comprehensive rating module and system management module, wherein:
the image acquisition module is used for acquiring a defect image to be classified and transmitting the image to be classified to the image processing module;
the image processing module is used for identifying the defect image to be classified, performing error analysis on the identified defect image to be classified, generating an analysis result and transmitting the analysis result to the comprehensive rating module;
the comprehensive rating module is used for rating different types of defect images according to the analysis result;
and the system management module is used for counting the data after the defective image is graded so as to generate a comprehensive calculation result.
According to some embodiments, the image acquisition module comprises a scanner, and the image acquisition module is used for acquiring a defect image to be classified, and specifically comprises:
and carrying out digital processing on the defect image by a scanner, wherein the defect image data comprises the thickness of the plate in the negative film, the defect type and the number of the defects.
According to some embodiments, the image processing module identifying the defect image data to be classified comprises:
and preprocessing the defect image to identify the data of the defect image and extract the characteristic information of the welding defect.
According to some embodiments, the image processing module comprises an image recognition model, and the specific steps of preprocessing the defect image comprise:
cutting the to-be-detected defect image according to a fixed width to obtain a to-be-detected defect image with a standard square size;
putting the to-be-detected defect image with the standard square size into an image recognition model to obtain a defect mask and a defect category of the to-be-detected image;
and carrying out reverse transformation on the defect mask and reducing the size of the mask image to complete the recombination of the mask image and obtain a defect area.
According to some embodiments, the error analysis comprises in particular:
and if the defect does not meet the preset calculation condition in the input information of the defect, not calculating the defect and outputting an analysis result.
According to some embodiments, the comprehensive rating module comprises a ray guided wave detector, and the comprehensive rating module is configured to rate different types of defect images according to an analysis result, and the specific steps of the rating are as follows:
calibrating the ray guided wave detector, wherein the calibration comprises a symmetric signal and an asymmetric signal;
starting a ray guided wave detector to carry out detection and collect detection data to obtain a distance-amplitude curve of each butt weld asymmetric signal in the front and back directions of a detection point of the detected pipeline, carrying out detection data analysis, and focusing the weld of which the distance-amplitude curve of each butt weld asymmetric signal is above a-32 dB noise line;
the method comprises the steps of evaluating the butt weld defects, grading according to the severity of the butt weld defects, wherein the amplitude of an asymmetric signal is I grade when being smaller than-25 dB, the amplitude of the asymmetric signal is II grade when being between-25 dB and-124 dB, and the amplitude of the asymmetric signal is III grade when being larger than-12 dB;
and comprehensively rating the defects of the butt weld of the pipeline by combining the severity grade and the focusing result of the defects of the butt weld.
According to some embodiments, the statistics of the data after the rating of the defect image by the system management module specifically includes:
and (4) normalizing the data after the defective image is graded, performing centralized management on the system, distributing corresponding access authority, and maintaining the normal operation of the whole system.
According to some embodiments, the system management module further comprises a query statistics module, which is used for querying information such as defect images and ray guided wave detection nondestructive testing reports according to different conditions input by a user, and displaying query results in pages.
The invention also provides a ray detection welding defect image rating method, which realizes the rating method corresponding to any scheme, and specifically comprises the following steps:
acquiring a defect image to be classified;
identifying the defect image to be classified, carrying out error analysis on the defect image to be classified, generating an analysis result, and sending a rating instruction according to the analysis result;
and grading the different types of defect images according to the grading instruction.
According to some embodiments, the method includes identifying the defect image to be classified, performing error analysis on the identified defect image to be classified to generate an analysis result, sending a rating instruction according to the analysis result, and rating different types of defect images according to the rating instruction, specifically:
digitally processing the defect image by a scanner;
preprocessing the defect image data to identify the category of the welding defect and extract characteristic information of the welding defect;
if the defect data do not meet the preset calculation condition, the defect data are not calculated and an analysis result is output; the defects accord with preset calculation conditions, and different types of defect images are graded;
and counting the rated data of the defect images to generate a comprehensive calculation result.
Compared with the prior art, the invention has the following beneficial effects:
in the above embodiment, the image processing module identifies the defect images to be classified acquired by the image acquisition module, performs error analysis on the identified defect images to obtain analysis results, and ranks the different types of defect images according to the analysis results. In practical application, the welding defect film rating system only needs to scan the defect film through the system, and the comprehensive calculation rating of the film can be quickly completed through data processing of the rating system, and the accuracy of rating is high.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a structural flow diagram of a ray inspection welding defect image rating system provided by the present invention;
FIG. 2 is a schematic flow chart of a ray inspection welding defect image rating system provided by the present invention;
fig. 3 is a schematic flow chart of an image rating method for detecting welding defects by using rays according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
The invention provides a ray detection welding defect image rating system, please refer to fig. 1-2, the negative film rating system comprises an image acquisition module, an image processing module, a comprehensive rating module and a system management module. The image acquisition module is used for acquiring a defect image to be classified and transmitting the image to be classified to the image processing module. The image processing module is used for identifying the defect images to be classified, performing error analysis on the defect images to be classified to generate an analysis result, and transmitting the analysis result to the comprehensive rating module. And the comprehensive rating module is used for rating different types of defect images according to the analysis result. And the system management module is used for counting the data after the defective image is graded so as to generate a comprehensive calculation result.
In the above embodiment, the image processing module identifies the defect images to be classified acquired by the image acquisition module, performs error analysis on the identified defect images to obtain analysis results, and ranks the different types of defect images according to the analysis results. In practical application, the welding defect film rating system only needs to scan the defect film through the system, and the comprehensive calculation rating of the film can be quickly completed through data processing of the rating system, and the accuracy of rating is high.
According to some embodiments, the image acquisition module comprises a scanner, and the image acquisition module is configured to acquire a defect image to be classified, and specifically includes subjecting the defect image to digital processing by the scanner, where the defect image data includes a thickness of a plate in the negative, a defect type, and a number of defects.
The image processing module identifies the defect image data to be classified, and the image processing module preprocesses the defect image to identify the defect image data and extract the characteristic information of the welding defect.
The image processing module comprises an image recognition model, and the specific steps of preprocessing the defect image comprise the operations of image enhancement, background removal and the like on the defect image, and cutting the defect image to be detected according to a fixed width to obtain the defect image to be detected with a standard square size; putting the to-be-detected defect image with the standard square size into an image recognition model to obtain a defect mask and a defect category of the to-be-detected image; and carrying out reverse transformation on the defect mask and reducing the size of the mask image to complete the recombination of the mask image and obtain a defect area.
In addition, the error analysis specifically includes not calculating the defect and outputting an analysis result if the defect does not meet a preset calculation condition when the information of the defect is input.
The comprehensive rating module comprises a ray guided wave detector, and is used for rating different types of defect images according to analysis results, and the specific steps of rating are as follows:
calibrating the ray guided wave detector, wherein the calibration comprises a symmetric signal and an asymmetric signal;
starting a ray guided wave detector to carry out detection and collect detection data to obtain a distance-amplitude curve of each butt weld asymmetric signal in the front and back directions of a detection point of the detected pipeline, carrying out detection data analysis, and focusing the weld of which the distance-amplitude curve of each butt weld asymmetric signal is above a-32 dB noise line;
and (4) evaluating the butt weld defects, and grading according to the severity of the butt weld defects, wherein the amplitude of the asymmetric signal is I grade when being less than-25 dB, the amplitude of the asymmetric signal is II grade between-25 dB and-124 dB, and the amplitude of the asymmetric signal is III grade when being more than-12 dB.
And comprehensively rating the defects of the butt weld of the pipeline by combining the severity grade and the focusing result of the defects of the butt weld. When the severity level of the butt weld defect is I level, the comprehensive rating focusing on a single direction or two directions is 2 level, and the comprehensive rating focusing on three directions is 1 level; when the severity grade of the butt weld defect is grade II, the comprehensive grade focusing on a single direction or two directions is grade 3, and the comprehensive grade focusing on three directions is grade 1; when the severity grade of the butt weld defect is grade III, the comprehensive grade focused in a single direction or two directions is grade 3, and the comprehensive grade focused in three directions is grade 1; the asymmetric signals focused in a single direction, two directions and three directions are butt weld asymmetric signals respectively having extreme values in one direction, two directions and three directions.
The system management module is used for counting the data after the defective image rating, specifically comprising the steps of normalizing the data after the defective image rating, performing centralized management on the system, distributing corresponding access authority, and maintaining the normal operation of the whole system.
The system management module also comprises a query statistic module which is used for querying information such as defect images, ray guided wave detection nondestructive testing reports and the like according to different conditions input by a user and displaying query results in pages.
Example 2
The embodiment of the invention also provides a method for grading the welding defect image of the ray detection based on a ray detection welding defect image grading system, which comprises the following specific steps as shown in figure 3:
s1, acquiring a defect image to be classified;
s2, identifying the defect images to be classified, performing error analysis on the identified defect images to be classified to generate an analysis result, and sending a rating instruction according to the analysis result;
and S3, grading the different types of defect images according to the grading instructions.
According to some embodiments, in step S2, the defect image to be classified is identified, and the error analysis is performed on the defect image to be classified to generate an analysis result, specifically: digitally processing the defect image by a scanner; and preprocessing the defect image data to identify the category of the welding defect and extract characteristic information of the welding defect.
Further, in step S3, a rating instruction is sent according to the analysis result, different types of defect images are rated according to the rating instruction, specifically, if the defect data does not meet the preset calculation condition, the defect data is not calculated and the analysis result is output; and (3) enabling the defects to accord with preset calculation conditions, grading different types of defect images, and counting the graded data of the defect images to generate a comprehensive calculation result.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements 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 radiographic inspection welding defect image rating system, comprising: image acquisition module, image processing module, comprehensive rating module and system management module, wherein:
the image acquisition module is used for acquiring a defect image to be classified and transmitting the image to be classified to the image processing module;
the image processing module is used for identifying the defect image to be classified, performing error analysis on the identified defect image to be classified, generating an analysis result and transmitting the analysis result to the comprehensive rating module;
the comprehensive rating module is used for rating different types of defect images according to the analysis result;
and the system management module is used for counting the data after the defective image is graded so as to generate a comprehensive calculation result.
2. The radiographic inspection welding defect image rating system of claim 1, wherein the image acquisition module comprises a scanner, and the image acquisition module is configured to acquire a defect image to be classified, and specifically comprises:
and carrying out digital processing on the defect image by a scanner, wherein the defect image data comprises the thickness of the plate in the negative film, the defect type and the number of the defects.
3. The radiographic inspection welding defect image rating system of claim 2, wherein the image processing module identifying the defect image data to be classified comprises:
and preprocessing the defect image to identify the data of the defect image and extract the characteristic information of the welding defect.
4. The radiographic inspection welding defect image rating system of claim 3, wherein the image processing module comprises an image recognition model, and the specific steps of preprocessing the defect image comprise:
cutting the to-be-detected defect image according to a fixed width to obtain a to-be-detected defect image with a standard square size;
putting the to-be-detected defect image with the standard square size into an image recognition model to obtain a defect mask and a defect category of the to-be-detected image;
and carrying out reverse transformation on the defect mask and reducing the size of the mask image to complete the recombination of the mask image and obtain a defect area.
5. The radiographic inspection welding defect image rating system of claim 4, wherein the error analysis specifically comprises:
and if the defect does not meet the preset calculation condition in the input information of the defect, not calculating the defect and outputting an analysis result.
6. The image rating system for the radiation detection welding defects of claim 5, wherein the comprehensive rating module comprises a radiation detector, the comprehensive rating module is used for rating different types of defect images according to the analysis result, and the specific steps of the rating are as follows:
calibrating the ray guided wave detector, wherein the calibration comprises a symmetric signal and an asymmetric signal;
starting a ray guided wave detector to carry out detection and collect detection data to obtain a distance-amplitude curve of each butt weld asymmetric signal in the front and back directions of a detection point of the detected pipeline, carrying out detection data analysis, and focusing the weld of which the distance-amplitude curve of each butt weld asymmetric signal is above a-32 dB noise line;
the method comprises the steps of evaluating the butt weld defects, grading according to the severity of the butt weld defects, wherein the amplitude of an asymmetric signal is I grade when being smaller than-25 dB, the amplitude of the asymmetric signal is II grade when being between-25 dB and-124 dB, and the amplitude of the asymmetric signal is III grade when being larger than-12 dB;
and comprehensively rating the defects of the butt weld of the pipeline by combining the severity grade and the focusing result of the defects of the butt weld.
7. The radiographic inspection welding defect image rating system of claim 6, wherein the statistics of the rated data of the defect image by the system management module specifically comprises:
and (4) normalizing the data after the defective image is graded, performing centralized management on the system, distributing corresponding access authority, and maintaining the normal operation of the whole system.
8. A radiographic inspection welding defect image rating system as defined in claim 7,
the system management module also comprises a query statistic module which is used for querying information such as defect images, ray guided wave detection nondestructive testing reports and the like according to different conditions input by a user and displaying query results in pages.
9. A method for grading an image of a radiation detection welding defect is characterized by comprising the following steps:
acquiring a defect image to be classified;
identifying the defect image to be classified, carrying out error analysis on the defect image to be classified, generating an analysis result, and sending a rating instruction according to the analysis result;
and grading the different types of defect images according to the grading instruction.
10. The method for grading the welding defect image for ray detection according to claim 9, wherein the defect image to be classified is identified, the identified defect image to be classified is subjected to error analysis to generate an analysis result, a grading instruction is sent according to the analysis result, and different types of defect images are graded according to the grading instruction, specifically:
digitally processing the defect image by a scanner;
preprocessing the defect image data to identify the category of the welding defect and extract characteristic information of the welding defect;
if the defect data do not meet the preset calculation condition, the defect data are not calculated and an analysis result is output; the defects accord with preset calculation conditions, and different types of defect images are graded;
and counting the rated data of the defect images to generate a comprehensive calculation result.
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