CN116883374A - Defect detection method and system for industrial production - Google Patents
Defect detection method and system for industrial production Download PDFInfo
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Abstract
The application is suitable for the technical field of image detection, and provides a defect detection method and system for industrial production, wherein the method comprises the following steps: receiving a track test program and characteristic elements input by a user; collecting a background image which does not contain a product to be detected; acquiring moving track image information of a product to be detected at a test position according to the track test program, wherein the moving track image information comprises a plurality of moving track images; identifying characteristic areas on each moving track image, and integrating all the characteristic areas in the moving track image information to obtain a complete track graph; determining a standard track graph according to a track test program; and comparing the complete track graph with the standard track graph to determine a defect track area. Therefore, the application applies the image detection to the detection of the dynamic characteristics of the product, and the user can automatically obtain the defect track area only by determining the track test program and the characteristic elements during the detection, thereby having simple operation.
Description
Technical Field
The application relates to the technical field of image detection, in particular to a defect detection method and system for industrial production.
Background
Image detection is widely applied to industrial production, for example, detection of surface scratches, surface flatness, chromatic aberration and the like of products, an object of the image detection at present is basically a static feature, and for some products capable of moving, for example, a mechanical arm is often required to detect dynamic features of the product, for example, whether a motion track of the mechanical arm meets requirements or not, and at present, detection of the dynamic features often requires special detection equipment, so that the detection cost is high, the operation is complex, and the detection efficiency is low. Therefore, there is a need to provide a defect detection method and system for industrial production, which aims to solve or alleviate the above problems.
Disclosure of Invention
Aiming at the defects in the prior art, the application aims to provide a defect detection method and a defect detection system for industrial production, so as to solve or alleviate the problems in the background art.
The application is realized in that a defect detection method for industrial production comprises the following steps:
receiving a track test program and characteristic elements input by a user;
collecting a background image which does not contain a product to be detected;
acquiring moving track image information of a product to be detected at a test position according to the track test program, wherein the moving track image information comprises a plurality of moving track images;
identifying characteristic areas on each moving track image, and integrating all the characteristic areas in the moving track image information to obtain a complete track graph;
determining a standard track graph according to a track test program;
and comparing the complete track graph with the standard track graph, determining a defect track area, and marking the defect at the defect track area.
As a further scheme of the application: the step of identifying the characteristic areas on each moving track image and integrating all the characteristic areas in the moving track image information to obtain a complete track graph specifically comprises the following steps:
identifying a characteristic region on each running track image according to the characteristic elements, and deducting the characteristic region;
and pasting all the subtracted characteristic areas on the corresponding positions of the background image, and integrating to obtain a complete track graph.
As a further scheme of the application: the step of determining the standard track graph according to the track test program specifically comprises the following steps:
calling the program file name of the track test program;
inputting program file names into a standard track library, wherein the standard track library comprises all program file names, and each program file name corresponds to a standard track graph;
and outputting a standard track graph corresponding to the track test program.
As a further scheme of the application: the step of comparing the complete track pattern with the standard track pattern to determine the defect track area specifically comprises the following steps:
dividing the complete track graph and the standard track graph into N sub-areas;
calculating the similarity between each sub-region in the complete track graph and the sub-region at the corresponding position in the standard track graph, and judging that the sub-region in the complete track graph has defects when the similarity is smaller than a set similarity value;
and integrating all the subareas with defects in the complete track graph to obtain a defect track area.
As a further scheme of the application: the method further comprises the step of checking timeliness of the running track, and the method comprises the following specific steps of:
the method comprises the steps of retrieving time information on moving track images, wherein each M images in the moving track image information are marked with time information on one moving track image, and the time information represents the starting time of a track test program;
adding the time information to the corresponding characteristic region in the complete track graph;
and comparing the position of the characteristic region in the complete track graph with the position of the corresponding characteristic region in the standard track graph according to the time information, and judging whether a time error exists or not, wherein the standard track graph is marked with the time information, and each time information corresponds to the characteristic region.
Another object of the present application is to provide a defect detection system for industrial production, the system comprising:
the program characteristic determining module is used for receiving a track test program and characteristic elements input by a user;
the background image acquisition module is used for acquiring a background image which does not contain the product to be detected;
the track image acquisition module is used for acquiring moving track image information of a product to be detected at a test position according to the track test program, wherein the moving track image information comprises a plurality of moving track images;
the complete track acquisition module is used for identifying the characteristic areas on each moving track image and integrating all the characteristic areas in the moving track image information to obtain a complete track graph;
the standard track determining module is used for determining a standard track graph according to the track test program;
and the defect area determining module is used for comparing the complete track graph with the standard track graph, determining a defect track area and marking the defect at the defect track area.
As a further scheme of the application: the complete track acquisition module comprises:
the characteristic region identification unit is used for identifying the characteristic region on each running track image according to the characteristic elements and deducting the characteristic region;
and the characteristic region pasting unit is used for pasting all the subtracted characteristic regions on the corresponding positions of the background image and integrating to obtain a complete track graph.
As a further scheme of the application: the standard track determination module comprises:
a file name calling unit for calling the program file name of the track test program;
the file name input unit is used for inputting the program file names into the standard track library, wherein the standard track library comprises all the program file names, and each program file name corresponds to one standard track graph;
and the standard track output unit is used for outputting a standard track graph corresponding to the track test program.
As a further scheme of the application: the defect area determining module includes:
the track graph dividing unit is used for dividing the complete track graph and the standard track graph into N sub-areas;
the defect judging unit is used for calculating the similarity between each sub-region in the complete track graph and the sub-region at the corresponding position in the standard track graph, and judging that the sub-region in the complete track graph has defects when the similarity is smaller than a set similarity value;
and the defect track area unit is used for integrating all the sub-areas with defects in the complete track graph to obtain a defect track area.
As a further scheme of the application: the system also comprises an timeliness detection module, wherein the timeliness detection module specifically comprises:
the time information calling unit is used for calling time information on the moving track images, wherein each M images are arranged at intervals in the moving track image information, one moving track image is marked with the time information, and the time information represents the starting time of the track test program;
the time information labeling unit is used for adding the time information to the corresponding characteristic area in the complete track graph;
and the region position comparison unit is used for comparing the position of the characteristic region in the complete track graph with the corresponding characteristic region in the standard track graph according to the time information, judging whether a time error exists or not, wherein the standard track graph is marked with the time information, and each time information corresponds to the characteristic region.
Compared with the prior art, the application has the beneficial effects that:
the application applies image detection to the detection of the dynamic characteristics of the product, and when in detection, a user can automatically obtain a defect track area by only determining a track test program and characteristic elements, so that the operation is simple and the detection efficiency is high.
Drawings
FIG. 1 is a flow chart of a method for detecting defects in industrial processes.
FIG. 2 is a flow chart of identifying feature areas in a defect inspection method for industrial production.
FIG. 3 is a flow chart of determining a standard track pattern in a defect detection method for industrial production.
FIG. 4 is a flow chart of determining a defect track area in a defect detection method for industrial production.
Fig. 5 is a flowchart for checking timeliness of a running track in a defect detection method for industrial production.
FIG. 6 is a schematic diagram of a defect detection system for industrial production.
FIG. 7 is a schematic diagram of a complete track acquisition module in a defect detection system for industrial production.
FIG. 8 is a schematic diagram of a standard track determination module in a defect detection system for industrial production.
Fig. 9 is a schematic diagram showing the structure of a defect area determining module in a defect detecting system for industrial production.
FIG. 10 is a schematic diagram of a time-efficiency detection module in a defect detection system for industrial production.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clear, the present application will be described in further detail with reference to the accompanying drawings and specific embodiments. 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 application.
Specific implementations of the application are described in detail below in connection with specific embodiments.
As shown in fig. 1, an embodiment of the present application provides a defect detection method for industrial production, which includes the following steps:
s100, receiving a track test program and characteristic elements input by a user;
s200, collecting a background image which does not contain a product to be detected;
s300, acquiring moving track image information of a product to be detected at a test position according to the track test program, wherein the moving track image information comprises a plurality of moving track images;
s400, identifying characteristic areas on each moving track image, and integrating all the characteristic areas in the moving track image information to obtain a complete track graph;
s500, determining a standard track graph according to a track test program;
s600, comparing the complete track pattern with the standard track pattern, determining a defect track area, and marking the defect at the defect track area.
It should be noted that, in the prior art, the object detected by the image is basically a static feature, for some products capable of moving, for example, a manipulator, a dynamic feature of the product is often required to be detected, for example, whether a motion track of the manipulator meets a requirement, at present, a special detection device is often required to detect the dynamic feature, so that the detection cost is high, the operation is complex, and the detection efficiency is low.
In the embodiment of the application, firstly, a user needs to determine a track test program and characteristic elements according to a product to be detected, for example, the product to be detected is a manipulator, the track test program is a manipulator test program, the characteristic elements are red points at the moving end part of the manipulator, and then the user can paste red stickers on the moving end part of the manipulator; then the camera acquires a background image which does not contain the product to be detected, the camera is fixed, a test position is arranged in front of the camera, the background of each image shot by the camera is the same, then the test can be formally performed, the camera acquires moving track image information of the product to be detected, which is obtained according to the track test program at the test position, and the moving track image information comprises a plurality of moving track images; the embodiment of the application can automatically identify the characteristic region on each running track image, wherein the characteristic region is a red point region, and then, the whole track graph can be obtained by integrating all the characteristic regions in the running track image information; and then determining a standard track pattern according to a track test program, wherein the standard track pattern is obtained by moving a standard qualified manipulator according to the track test program, and comparing the complete track pattern with the standard track pattern to determine the defect track area. Therefore, the embodiment of the application applies the image detection to the detection of the dynamic characteristics of the product, and when in detection, a user can automatically obtain the defect track area only by determining the track test program and the characteristic elements, so that the operation is simple, the detection efficiency is high, and the popularization is worth.
As shown in fig. 2, as a preferred embodiment of the present application, the step of identifying the feature area on each moving track image, and integrating all the feature areas in the moving track image information to obtain a complete track graph specifically includes:
s401, identifying a characteristic region on each running track image according to the characteristic elements, and deducting the characteristic region;
s402, pasting all the subtracted characteristic areas on the corresponding positions of the background image, and integrating to obtain a complete track graph.
In the embodiment of the application, the characteristic area on each running track image is required to be identified according to the characteristic elements input by the user, the color of the characteristic elements is preferential, the color of the characteristic elements does not appear on the body of the product to be detected, does not appear in the image background, is easy to identify, the characteristic area is automatically deducted after the characteristic area is identified, and then all the deducted characteristic areas are stuck on the corresponding positions of the background image, so that the complete track graph can be obtained.
As shown in fig. 3, as a preferred embodiment of the present application, the step of determining a standard track pattern according to a track test program specifically includes:
s501, calling the program file name of the track test program;
s502, inputting program file names into a standard track library, wherein the standard track library comprises all program file names, and each program file name corresponds to a standard track graph;
s503, outputting a standard track graph corresponding to the track test program.
In the embodiment of the application, a standard track library is established in advance, wherein the standard track library comprises all program file names, and each program file name corresponds to one standard track graph. Each track test program has a program file name, the program file name is input into a standard track library, a corresponding standard track graph is automatically output, and the standard track graph is used for detecting and verifying the complete track graph of a product to be detected.
As shown in fig. 4, as a preferred embodiment of the present application, the step of comparing the complete track pattern with the standard track pattern to determine the defect track area specifically includes:
s601, dividing a complete track graph and a standard track graph into N sub-areas;
s602, calculating the similarity between each sub-region in the complete track graph and the sub-region at the corresponding position in the standard track graph, and judging that the sub-region in the complete track graph has defects when the similarity is smaller than a set similarity value;
s603, integrating all the sub-areas with defects in the complete track graph to obtain a defect track area.
In the embodiment of the application, when the complete track graph is compared with the standard track graph, the complete track graph and the standard track graph are firstly divided into N sub-areas, N is a fixed value set in advance, N is a positive integer, the larger N is, the more accurate the comparison result is, then the similarity between each sub-area in the complete track graph and the sub-area at the corresponding position in the standard track graph is calculated, when the similarity is smaller than a set similarity value, the defect of the sub-area in the complete track graph is judged, when the similarity is larger than or equal to the set similarity value, the sub-area in the complete track graph is judged to be normal, and finally the defect track areas are obtained by integrating all the sub-areas with defects in the complete track graph.
As shown in fig. 5, as a preferred embodiment of the present application, the method further includes checking the timeliness of the running track, which includes the following specific steps:
s701, retrieving time information on a moving track image, wherein each M images are arranged at intervals in the moving track image information, the time information is marked on one moving track image, and the time information represents the starting time of a track test program;
s702, adding the time information to the corresponding characteristic region in the complete track graph;
s703, comparing the position of the characteristic region in the complete track graph with the position of the corresponding characteristic region in the standard track graph according to the time information, and judging whether a time error exists or not, wherein the standard track graph is marked with the time information, and each time information corresponds to the characteristic region.
In the embodiment of the application, the moving track image information consists of a plurality of frames of moving track images, and because the acquisition time between adjacent frames is basically the same, every interval of M frames of images, M is a fixed value set in advance, M is a positive integer, and only one frame of moving track image is marked with time information, and the time information represents the starting time of a track test program. The time information on the running track image is called, the time information is added to the corresponding characteristic area in the complete track graph, for example, ten time information are respectively: the standard track graph is also marked with time information of 1.2 seconds, 2.4 seconds, 3.6 seconds, 4.8 seconds, 6.0 seconds, 7.2 seconds, 8.4 seconds, 9.6 seconds, 10.8 seconds and 12.0 seconds, each time information corresponds to a characteristic area, then the characteristic areas in the complete track graph are compared with the corresponding characteristic areas in the standard track graph according to the time information, ten characteristic areas are compared in position, and when the position difference is larger than a set difference value, the existence of time errors is judged. In this way, even if the complete trace pattern of the product to be detected is acceptable, the running speed is not acceptable, and it can be detected.
As shown in fig. 6, an embodiment of the present application further provides a defect detection system for industrial production, where the system includes:
a program feature determining module 100, configured to receive a trajectory test program and feature elements input by a user;
the background image acquisition module 200 is used for acquiring a background image which does not contain the product to be detected;
the track image acquisition module 300 is used for acquiring moving track image information of a product to be detected at a test position according to the track test program, wherein the moving track image information comprises a plurality of moving track images;
the complete track acquisition module 400 is configured to identify a feature area on each moving track image, and integrate all feature areas in the moving track image information to obtain a complete track graph;
the standard track determining module 500 is configured to determine a standard track pattern according to a track test program;
the defect area determining module 600 is configured to compare the complete track pattern with the standard track pattern, determine a defect track area, and mark a defect at the defect track area.
As shown in fig. 7, as a preferred embodiment of the present application, the complete track acquisition module 400 includes:
a feature region identifying unit 401, configured to identify a feature region on each moving track image according to the feature elements, and subtract the feature region;
and the feature region pasting unit 402 is configured to paste all the subtracted feature regions on corresponding positions of the background image, and integrate to obtain a complete track graph.
As shown in fig. 8, as a preferred embodiment of the present application, the standard trajectory determining module 500 includes:
a file name retrieving unit 501, configured to retrieve a program file name of the track test program;
a file name input unit 502, configured to input a program file name into a standard track library, where the standard track library includes all program file names, and each program file name corresponds to a standard track graph;
and the standard track output unit 503 is configured to output a standard track pattern corresponding to the track test program.
As shown in fig. 9, as a preferred embodiment of the present application, the defect area determining module 600 includes:
a track pattern dividing unit 601, configured to divide the complete track pattern and the standard track pattern into N sub-areas;
the defect judging unit 602 is configured to calculate a similarity between each sub-region in the complete track graph and a sub-region in a corresponding position in the standard track graph, and judge that a defect exists in the sub-region in the complete track graph when the similarity is smaller than a set similarity value;
and the defect track area unit 603 is configured to integrate all the sub-areas with defects in the complete track graph to obtain a defect track area.
As shown in fig. 10, as a preferred embodiment of the present application, the system further includes an aging detection module 700, where the aging detection module 700 specifically includes:
a time information retrieving unit 701, configured to retrieve time information on a moving track image, where each M images in the moving track image information are each provided with a piece of time information marked on the moving track image, and the time information represents a start time of a track test program;
a time information labeling unit 702, configured to add the time information to a corresponding feature area in the complete track graph;
the region position comparing unit 703 is configured to compare the position of the feature region in the complete track graph with the corresponding feature region in the standard track graph according to the time information, and determine whether a time error exists, where the standard track graph is marked with time information, and each time information corresponds to a feature region.
The foregoing description of the preferred embodiments of the present application should not be taken as limiting the application, but rather should be understood to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the application.
It should be understood that, although the steps in the flowcharts of the embodiments of the present application are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
Other embodiments of the present disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (10)
1. A defect detection method for industrial production, characterized in that the method comprises the following steps:
receiving a track test program and characteristic elements input by a user;
collecting a background image which does not contain a product to be detected;
acquiring moving track image information of a product to be detected at a test position according to the track test program, wherein the moving track image information comprises a plurality of moving track images;
identifying characteristic areas on each moving track image, and integrating all the characteristic areas in the moving track image information to obtain a complete track graph;
determining a standard track graph according to a track test program;
and comparing the complete track graph with the standard track graph, determining a defect track area, and marking the defect at the defect track area.
2. The method for detecting defects in industrial production according to claim 1, wherein the step of identifying the feature area on each moving track image and integrating all the feature areas in the moving track image information to obtain a complete track pattern specifically comprises:
identifying a characteristic region on each running track image according to the characteristic elements, and deducting the characteristic region;
and pasting all the subtracted characteristic areas on the corresponding positions of the background image, and integrating to obtain a complete track graph.
3. The method for detecting defects in industrial production according to claim 1, wherein the step of determining a standard track pattern according to a track test program comprises:
calling the program file name of the track test program;
inputting program file names into a standard track library, wherein the standard track library comprises all program file names, and each program file name corresponds to a standard track graph;
and outputting a standard track graph corresponding to the track test program.
4. The method for detecting defects in industrial production according to claim 1, wherein the step of comparing the complete track pattern with the standard track pattern to determine the defect track area comprises:
dividing the complete track graph and the standard track graph into N sub-areas;
calculating the similarity between each sub-region in the complete track graph and the sub-region at the corresponding position in the standard track graph, and judging that the sub-region in the complete track graph has defects when the similarity is smaller than a set similarity value;
and integrating all the subareas with defects in the complete track graph to obtain a defect track area.
5. The defect detection method for industrial production according to claim 1, further comprising checking timeliness of the running track, comprising the steps of:
the method comprises the steps of retrieving time information on moving track images, wherein each M images in the moving track image information are marked with time information on one moving track image, and the time information represents the starting time of a track test program;
adding the time information to the corresponding characteristic region in the complete track graph;
and comparing the position of the characteristic region in the complete track graph with the position of the corresponding characteristic region in the standard track graph according to the time information, and judging whether a time error exists or not, wherein the standard track graph is marked with the time information, and each time information corresponds to the characteristic region.
6. A defect detection system for industrial production, the system comprising:
the program characteristic determining module is used for receiving a track test program and characteristic elements input by a user;
the background image acquisition module is used for acquiring a background image which does not contain the product to be detected;
the track image acquisition module is used for acquiring moving track image information of a product to be detected at a test position according to the track test program, wherein the moving track image information comprises a plurality of moving track images;
the complete track acquisition module is used for identifying the characteristic areas on each moving track image and integrating all the characteristic areas in the moving track image information to obtain a complete track graph;
the standard track determining module is used for determining a standard track graph according to the track test program;
and the defect area determining module is used for comparing the complete track graph with the standard track graph, determining a defect track area and marking the defect at the defect track area.
7. The defect detection system for industrial production of claim 6, wherein the complete trajectory acquisition module comprises:
the characteristic region identification unit is used for identifying the characteristic region on each running track image according to the characteristic elements and deducting the characteristic region;
and the characteristic region pasting unit is used for pasting all the subtracted characteristic regions on the corresponding positions of the background image and integrating to obtain a complete track graph.
8. The defect detection system for industrial production of claim 6, wherein the standard trajectory determination module comprises:
a file name calling unit for calling the program file name of the track test program;
the file name input unit is used for inputting the program file names into the standard track library, wherein the standard track library comprises all the program file names, and each program file name corresponds to one standard track graph;
and the standard track output unit is used for outputting a standard track graph corresponding to the track test program.
9. The defect detection system for industrial production of claim 6, wherein the defect region determination module comprises:
the track graph dividing unit is used for dividing the complete track graph and the standard track graph into N sub-areas;
the defect judging unit is used for calculating the similarity between each sub-region in the complete track graph and the sub-region at the corresponding position in the standard track graph, and judging that the sub-region in the complete track graph has defects when the similarity is smaller than a set similarity value;
and the defect track area unit is used for integrating all the sub-areas with defects in the complete track graph to obtain a defect track area.
10. The defect detection system for industrial production of claim 6, further comprising a timeliness detection module, the timeliness detection module specifically comprising:
the time information calling unit is used for calling time information on the moving track images, wherein each M images are arranged at intervals in the moving track image information, one moving track image is marked with the time information, and the time information represents the starting time of the track test program;
the time information labeling unit is used for adding the time information to the corresponding characteristic area in the complete track graph;
and the region position comparison unit is used for comparing the position of the characteristic region in the complete track graph with the corresponding characteristic region in the standard track graph according to the time information, judging whether a time error exists or not, wherein the standard track graph is marked with the time information, and each time information corresponds to the characteristic region.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310896944.0A CN116883374A (en) | 2023-07-20 | 2023-07-20 | Defect detection method and system for industrial production |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310896944.0A CN116883374A (en) | 2023-07-20 | 2023-07-20 | Defect detection method and system for industrial production |
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