CN113533206A - Industrial detection system and method for industrial Internet - Google Patents
Industrial detection system and method for industrial Internet Download PDFInfo
- Publication number
- CN113533206A CN113533206A CN202110846915.4A CN202110846915A CN113533206A CN 113533206 A CN113533206 A CN 113533206A CN 202110846915 A CN202110846915 A CN 202110846915A CN 113533206 A CN113533206 A CN 113533206A
- Authority
- CN
- China
- Prior art keywords
- product
- image
- detection
- light
- light rays
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 183
- 238000000034 method Methods 0.000 title claims abstract description 40
- 230000005540 biological transmission Effects 0.000 claims abstract description 15
- 230000008569 process Effects 0.000 claims description 28
- 238000009826 distribution Methods 0.000 claims description 10
- 238000010191 image analysis Methods 0.000 claims description 4
- 238000004519 manufacturing process Methods 0.000 description 13
- 238000007689 inspection Methods 0.000 description 7
- 230000001360 synchronised effect Effects 0.000 description 6
- 230000000694 effects Effects 0.000 description 5
- 230000009471 action Effects 0.000 description 3
- 238000010923 batch production Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000010521 absorption reaction Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 230000031700 light absorption Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 238000004590 computer program Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000000149 penetrating effect Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
Abstract
The invention is suitable for the technical field of industrial detection, and particularly relates to an industrial detection system and method of an industrial internet, wherein the method comprises the following steps: emitting detection light rays to a product and receiving feedback light rays reflected by the product, wherein the feedback light rays at least comprise reflection light rays and transmission light rays; acquiring an image of a product to obtain a product detection image; analyzing the feedback light and generating a marking area in the product detection image; and comparing the product detection image in the marking area with a preset standard image to generate a detection result and storing the detection result. According to the invention, the light rays passing through the product are analyzed to directly obtain the internal quality and the surface problems of the product, and the image detection is assisted to perform recheck on the areas of the product possibly having the product quality problems, so that on the premise of ensuring the detection efficiency, the detection accuracy is greatly improved, the manual use is reduced, all products can be ensured to be checked, and the problem of missed detection is avoided.
Description
Technical Field
The invention belongs to the technical field of industrial detection, and particularly relates to an industrial detection system and method of an industrial internet.
Background
With the rapid development of society, internet technology is gradually applied to various aspects of people's life. No matter the clothes and the eating houses, the internet technology is applied. With the further development of the industry, the industry gradually enters the internet era.
The essence of the industrial internet is that equipment, production lines, factories, suppliers, products and customers are closely connected and fused through an open and global industrial-level network platform, and various element resources in industrial economy are efficiently shared, so that the cost is reduced, the efficiency is increased, the manufacturing industry is helped to extend the industrial chain, and the transformation development of the manufacturing industry is promoted through an automatic and intelligent production mode. The industrial internet is connected with human-computer through intelligent machine connection, combines software and big data analysis, reconstructs global industry, stimulates productivity, and makes the world better, faster, safer, cleaner and more economical.
In the industry, the quality detection of products flowing on a production line is often needed, and in the quality detection process, most of the products are mainly detected by manual work, the efficiency of the manual detection is low, and in the case of batch products, only the spot inspection can be carried out, so that the missed fishes are easy to exist.
Disclosure of Invention
The embodiment of the invention aims to provide an industrial detection method for industrial Internet, aiming at solving the problems in the background technology.
The embodiment of the invention is realized in such a way that an industrial detection method of an industrial internet comprises the following steps:
emitting detection light rays to a product and receiving feedback light rays reflected by the product, wherein the feedback light rays at least comprise reflection light rays and transmission light rays;
acquiring an image of the product to obtain a product detection image, wherein the image acquisition process and the process of emitting detection light to the product are synchronously performed;
analyzing feedback light, and generating a marking area in a product detection image, wherein the product detection image in the marking area is an area where the quality of the current product possibly has a problem;
and comparing the product detection image in the marking area with a preset standard image to generate a detection result and storing the detection result.
Preferably, the step of emitting the detection light to the product and receiving the feedback light reflected from the product specifically includes:
obtaining standard thickness information of a product;
selecting detection light rays with different intensities according to the standard thickness information, and vertically emitting the detection light rays to the product;
and receiving the transmitted light rays passing through the product and the reflected light rays reflected by the product to obtain feedback light rays.
Preferably, the step of acquiring an image of the product to obtain a product detection image specifically includes:
acquiring an image of a product to obtain a first product image;
adjusting the image of the first product image to obtain a second product image;
and carrying out gray processing on the second product image to obtain a product detection image.
Preferably, the
Analyzing the feedback light and generating a marking area in the product detection image, which specifically comprises the following steps:
generating an equal thickness line in a product detection image according to the transmission light in the feedback light, wherein the thickness of each part on the equal thickness line is the same;
generating a roughness distribution grid in the product detection image according to the reflected light in the feedback light;
and generating a marking area according to the equal thickness line and the roughness distribution grid in the product detection image, wherein the marking area is an area suspected of having quality problems.
Preferably, the step of comparing the product detection image in the marking area with a preset standard image to generate and store a detection result specifically includes:
continuously marking the marked area, and intercepting parts of the product detection image positioned in the marked area one by one to obtain image blocks to be verified;
calling a corresponding standard image from a preset standard image library according to the information of the product;
and comparing the image block to be verified with the standard image, and generating a detection result.
Preferably, the detection light is infrared light.
Preferably, in the step of acquiring the image of the product to obtain the product detection image, different areas of the product are synchronously acquired, and finally spliced to obtain the product detection image.
Another object of an embodiment of the present invention is to provide an industrial detection system of an industrial internet, the system including:
the light ray detection module is used for emitting detection light rays to the product and receiving feedback light rays reflected by the product, wherein the feedback light rays at least comprise reflection light rays and transmission light rays;
the image acquisition module is used for acquiring an image of the product to obtain a product detection image, and the image acquisition process and the process of emitting detection light to the product are synchronously carried out;
the image analysis module is used for analyzing the feedback light and generating a marking area in the product detection image, wherein the product detection image in the marking area is an area where the quality of the current product possibly has a problem;
and the image comparison module is used for comparing the product detection image in the marking area with a preset standard image, generating a detection result and storing the detection result.
Preferably, the light detection module includes:
the information acquisition unit is used for acquiring standard thickness information of a product;
the intensity selection unit is used for selecting detection light rays with different intensities according to the standard thickness information and vertically emitting the detection light rays to the product;
and the light receiving unit is used for simultaneously receiving the transmitted light passing through the product and the reflected light reflected by the product to obtain feedback light.
Preferably, the image acquisition module includes:
the acquisition unit is used for acquiring images of the product to obtain a first product image;
the image adjusting unit is used for adjusting the image of the first product image to obtain a second product image;
and the gray processing unit is used for carrying out gray processing on the second product image to obtain a product detection image.
According to the industrial detection method of the industrial internet, provided by the embodiment of the invention, the light rays of the products are analyzed after the light rays pass through the products, so that the problems of the internal quality and the surface of the products are directly obtained, and the image detection is assisted, so that the regions of the products possibly having the product quality problems are rechecked, therefore, on the premise of ensuring the detection efficiency, the detection accuracy is greatly improved, the manual use is reduced, all the products can be ensured to be detected, and the problem of missed detection is avoided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart of an industrial detection method of an industrial internet according to an embodiment of the present invention;
FIG. 2 is a flowchart of steps provided by an embodiment of the present invention for emitting detection light to a product and receiving feedback light reflected from the product;
FIG. 3 is a flowchart illustrating steps of acquiring an image of a product to obtain a product inspection image according to an embodiment of the present invention;
FIG. 4 is a flowchart of the steps provided by an embodiment of the present invention for analyzing feedback light and generating a mark region on a product inspection image;
FIG. 5 is a flowchart of generating a detection result according to an embodiment of the present invention;
FIG. 6 is an architecture diagram of an industrial inspection system for industrial Internet according to an embodiment of the present invention;
FIG. 7 is a flowchart of a light detecting module according to an embodiment of the present invention;
fig. 8 is a flowchart of an image acquisition module according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
In the description of the present application, it is also to be noted that, unless otherwise explicitly specified or limited, the terms "disposed" and "connected" are to be interpreted broadly, e.g., as being either fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
In the industry, the quality detection of products flowing on a production line is often needed, and in the quality detection process, most of the products are mainly detected by manual work, the efficiency of the manual detection is low, and in the case of batch products, only the spot inspection can be carried out, so that the missed fishes are easy to exist.
In the invention, the light rays passing through the product are analyzed to directly obtain the internal quality and the surface problems of the product, and the image detection is assisted to recheck the area of the product possibly having the product quality problems, so that on the premise of ensuring the detection efficiency, the detection accuracy is greatly improved, the manual use is reduced, all the products can be ensured to be checked, and the problem of missed detection is avoided.
As shown in fig. 1, an embodiment of the present invention provides an industrial detection method for an industrial internet, where the method includes:
s100, emitting detection light rays to the product and receiving feedback light rays reflected by the product, wherein the feedback light rays at least comprise reflection light rays and transmission light rays.
For factories, many products need to be inspected, such as glass production, plastic plate production, or veneer production, and during the production process, the inspection needs to be performed, generally, in order to ensure the product quality, an experimental batch is made in advance, parameters of formal batch production are determined through the experimental batch, and after the production parameters are determined, the formal production is started, but although the production parameters are determined, the product quality is not completely determined by the parameters, and environmental factors are also important; therefore, quality problems are likely to occur when sampling inspection is performed in the official lot.
In this step, the detection light is emitted to the product, and for the light, the emitted light is the same, and after the light is emitted, a part of the light directly passes through the product to reach the opposite side of the product, and the other part of the light is directly reflected back by the product.
S200, carrying out image acquisition on the product to obtain a product detection image, wherein the image acquisition process and the process of emitting detection light to the product are carried out synchronously.
In this step, carry out image acquisition to the product, can adopt multiunit camera lens to carry out synchronous shooting, each camera lens shoots an area of product, will obtain a plurality of "incomplete" images like this, then splice the image that obtains to finally obtain complete product detection image, through setting up multiunit camera lens, can guarantee that the product that the camera lens was shot can not take place to warp, produce the distortion in order to avoid being in the region of marginalization position, guaranteed analysis results's accuracy, image acquisition process and the process of detecting light to the product transmission go on in step, thereby can guarantee that the product detection image that gathers can with this moment received feedback light phase-match, do not have the time difference, or reduce the time difference.
S300, analyzing the feedback light, and generating a marking area in the product detection image, wherein the product detection image in the marking area is an area where the current product may have quality problems.
In this step, the reflected light and the transmitted light in the feedback light are analyzed simultaneously, since the product absorbs the light after the light penetrates through the product, the intensity of the light is weakened after the light penetrates through the product, and the light absorption effect is the same for the product made of the same material, and the greater the thickness of the product, the stronger the light absorption effect is, the thickness of the product can be detected finally according to the intensity of the light penetrating through the product, and the rougher the surface of the product is for the reflected light, the fewer the light can be reflected directly back, so that if the roughness in each area can be judged according to the reflected light, the surface quality of the product can be evaluated finally, the above process is only a preliminary judgment, and the points with quality problems in the preliminary judgment are marked in the product detection image, thereby obtaining a mark region.
And S400, comparing the product detection image in the marking area with a preset standard image, generating a detection result and storing the detection result.
In the step, the standard image is called out first, the product which completely meets the standard is shot in the process of carrying out experimental batch production, so that the standard is stored, the product is called out in the process of detecting the product and is used as the standard for judging the quality of the product, the product detection image in the marking area is compared with the preset standard image, so that whether the product has quality problems in the area can be further determined, and finally, the detection result is generated according to the comparison result and is stored.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of emitting the detection light to the product and receiving the feedback light reflected from the product specifically includes:
and S101, acquiring standard thickness information of the product.
In this step, to different products, its thickness is different, and in order to guarantee quality detection's effect, needs the intensity of control detection light, and detection light must can see through the product to still guarantee to see through the detection light of product and still have certain intensity, consequently according to the standard thickness information of showpiece, thereby judge the detection light that needs to adopt which kind of intensity.
And S102, selecting detection light rays with different intensities according to the standard thickness information, and vertically emitting the detection light rays to the product.
In this step, after the standard thickness information is determined, the detection light with the corresponding intensity is selected, the detection light can directly penetrate through the product, a part of light is reflected, and when the detection light is emitted, the detection light is ensured to be perpendicular to the product, so that the reflection light can be received conveniently.
And S103, receiving the transmitted light passing through the product and the reflected light reflected by the product simultaneously to obtain feedback light.
In this step, the transmission light that passes through the product and the reflection light that is reflected by the product are accepted simultaneously, all set up receiving arrangement at the both sides of product, receive the transmission light that passes through the product and the reflection light that is reflected by the product respectively to obtain feedback light.
As shown in fig. 3, as a preferred embodiment of the present invention, the step of acquiring an image of a product to obtain a product detection image specifically includes:
s201, carrying out image acquisition on the product to obtain a first product image.
In the step, a plurality of groups of camera lenses are adopted for synchronous shooting, each camera lens shoots an area of the product, so that a plurality of incomplete images can be obtained, the obtained images are spliced, and therefore a complete product detection image is finally obtained, and a first product image is obtained.
S202, image adjustment is carried out on the first product image to obtain a second product image.
In this step, since the product or the image capturing device may have a certain offset, in this process, the image needs to be adjusted, that is, the first product image is rotated, so that the first product image is in a preset position, and the second product image is obtained.
And S203, carrying out gray level processing on the second product image to obtain a product detection image.
In this step, the higher the color richness of the image is, the more the data processing amount of the image is increased in the data processing process, and if the networking processing is performed, the larger the data transmission amount is, and in order to improve the data transmission efficiency, the gray processing is performed on the image, so that the product detection image is obtained.
As a preferred embodiment of the present invention, as shown in FIG. 4, the
Analyzing the feedback light and generating a marking area in the product detection image, which specifically comprises the following steps:
s301, according to the transmission light in the feedback light, an equal thickness line is generated in the product detection image, and the thickness of each position on the equal thickness line is the same.
In this step, the intensity losses of the detection light rays passing through different areas of the product are different, so that the thickness of the product at all positions can be reversely deduced according to the intensity loss condition of the detection light rays, the detection image of the product is marked in a line mode, so that equal thickness lines are formed, a closed area is formed between the equal thickness lines, and the thickness difference in the closed area is within a preset range.
And S302, generating a roughness distribution grid in the product detection image according to the reflected light rays in the feedback light rays.
In the step, the reflected light is analyzed, so that the roughness distribution condition of each area of the product can be obtained, then the roughness distribution grids are generated in the product detection image, so that the roughness in the same roughness distribution grid is ensured to be the same, the size of the specific grid is determined according to the requirement, if the requirement on the precision is high, the size of the grid is smaller, otherwise, the size of the grid is larger.
And S303, generating a marking area according to the uniform thickness line and the roughness distribution grid in the product detection image, wherein the marking area is an area suspected of having quality problems.
In this step, a marking area is generated according to the isopachous line and the roughness distribution grid in the product detection image, and the position of the corresponding product in the area is considered to be suspected to have a quality problem, and the area needs to be further checked.
As shown in fig. 5, as a preferred embodiment of the present invention, the step of comparing the product detection image in the mark area with a preset standard image to generate a detection result and storing the detection result specifically includes:
s401, continuously marking the marked area, and intercepting parts, located in the marked area, in the product detection image one by one to obtain image blocks to be verified.
In the step, the marking area is continuously marked to determine the sequence of detecting the products in the marking area, then the parts, which are positioned in the marking area, in the product detection image are intercepted one by one to obtain the blocks to be verified, and the checking is carried out according to the sequence.
S402, calling the corresponding standard image from a preset standard gallery according to the information of the product.
In the step, a standard image is selected, the standard image is preset in a standard gallery, the standard gallery is determined during experimental batch, each product has a standard image of the product, and the standard image can be directly called according to product information.
And S403, comparing the image block to be verified with the standard image, and generating a detection result.
In the step, the image block to be verified is compared with the standard image, and whether the area has a problem or not can be directly judged through comparison, so that the product is determined to be an unqualified product.
As shown in fig. 6, the industrial detection system for the industrial internet according to the present invention includes:
the light detecting module 100 is configured to emit detecting light to the product and receive feedback light reflected from the product, where the feedback light at least includes reflected light and transmitted light.
In the system, the light detection module 100 emits detection light to the product, and for the light, the emitted light is the same, and after the light is emitted, a part of the light directly passes through the product to reach the opposite side of the product, and the other part of the light is directly reflected back by the product.
The image acquisition module 200 is configured to acquire an image of a product to obtain a product detection image, and the image acquisition process and the process of emitting detection light to the product are performed synchronously.
In the system, the image acquisition module 200 acquires images of products, and can adopt a plurality of groups of camera lenses to carry out synchronous shooting, each camera lens shoots an area of the product, so that a plurality of 'incomplete' images can be obtained, and then the obtained images are spliced, so that complete product detection images are finally obtained.
And the image analysis module 300 is configured to analyze the feedback light and generate a marked area in the product detection image, where the product detection image in the marked area is an area where a quality problem may exist in the current product.
In this system, image analysis module 300 carries out simultaneous analysis to the reflection light and the transmission light in the feedback light, because light is behind seeing through the product, the product will absorb it, therefore light sees through after, its intensity will weaken, and to the product of material in the same, the absorption effect to light is the same, and its thickness is big more, and the absorption effect to light is stronger, then finally can detect the thickness of product according to the intensity of the light that sees through behind the product.
And the image comparison module 400 is configured to compare the product detection image in the mark area with a preset standard image, generate a detection result, and store the detection result.
In the system, the image comparison module 400 calls out a standard image first, and in the process of carrying out experimental batch production, a product completely meeting the standard is shot so as to be stored, and in the process of detecting the product, the product is called out to be used as a standard for judging the quality of the product.
As shown in fig. 7, the light detecting module provided by the present invention includes:
the information acquisition unit 101 is used for acquiring standard thickness information of a product.
In the present module, the information acquisition unit 101 directly acquires standard thickness information of a product.
And the intensity selection unit 102 is used for selecting the detection light rays with different intensities according to the standard thickness information and vertically emitting the detection light rays to the product.
In this module, after confirming standard thickness information, select the detection light that corresponds intensity, should detect light and can directly pass the product to there is some light to be reflected, when the emission detects light, will guarantee that it is perpendicular with the product, thereby be convenient for receive reflection light.
And the light receiving unit 103 is used for simultaneously receiving the transmitted light passing through the product and the reflected light reflected by the product to obtain feedback light.
In this module, the light receiving unit 103 receives the transmitted light passing through the product and the reflected light reflected by the product at the same time, and both sides of the product are provided with receiving devices for receiving the transmitted light passing through the product and the reflected light reflected by the product, respectively, thereby obtaining the feedback light.
As shown in fig. 8, the image acquisition module provided for the present invention includes:
the acquisition unit 201 is configured to perform image acquisition on a product to obtain a first product image.
In this module, the acquisition unit 201 adopts multiple groups of cameras to perform synchronous shooting, and then splices the obtained images, so as to finally obtain a complete product detection image and obtain a first product image.
The image adjusting unit 202 is configured to perform image adjustment on the first product image to obtain a second product image.
In this module, the image adjusting unit 202 adjusts the image, that is, rotates the first product image, so that the first product image is at a preset position, thereby obtaining a second product image.
And the gray processing unit 203 is configured to perform gray processing on the second product image to obtain a product detection image.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile 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), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. An industrial detection method of industrial internet, characterized in that the method comprises:
emitting detection light rays to a product and receiving feedback light rays reflected by the product, wherein the feedback light rays at least comprise reflection light rays and transmission light rays;
acquiring an image of the product to obtain a product detection image, wherein the image acquisition process and the process of emitting detection light to the product are synchronously performed;
analyzing feedback light, and generating a marking area in a product detection image, wherein the product detection image in the marking area is an area where the quality of the current product possibly has a problem;
and comparing the product detection image in the marking area with a preset standard image to generate a detection result and storing the detection result.
2. The industrial detection method for the industrial internet as claimed in claim 1, wherein the step of emitting the detection light to the product and receiving the feedback light reflected from the product comprises:
obtaining standard thickness information of a product;
selecting detection light rays with different intensities according to the standard thickness information, and vertically emitting the detection light rays to the product;
and receiving the transmitted light rays passing through the product and the reflected light rays reflected by the product to obtain feedback light rays.
3. The industrial detection method of the industrial internet according to claim 1, wherein the step of acquiring the image of the product to obtain the detection image of the product specifically comprises:
acquiring an image of a product to obtain a first product image;
adjusting the image of the first product image to obtain a second product image;
and carrying out gray processing on the second product image to obtain a product detection image.
4. The industrial detection method for the industrial internet as claimed in claim 1, wherein the step of analyzing the feedback light and generating the mark area in the product detection image specifically comprises:
generating an equal thickness line in a product detection image according to the transmission light in the feedback light, wherein the thickness of each part on the equal thickness line is the same;
generating a roughness distribution grid in the product detection image according to the reflected light in the feedback light;
and generating a marking area according to the equal thickness line and the roughness distribution grid in the product detection image, wherein the marking area is an area suspected of having quality problems.
5. The industrial detection method of the industrial internet according to claim 1, wherein the step of comparing the product detection image in the marked area with a preset standard image to generate and store a detection result specifically comprises:
continuously marking the marked area, and intercepting parts of the product detection image positioned in the marked area one by one to obtain image blocks to be verified;
calling a corresponding standard image from a preset standard image library according to the information of the product;
and comparing the image block to be verified with the standard image, and generating a detection result.
6. The industrial detection method for the industrial internet as claimed in claim 1, wherein the detection light is infrared.
7. The industrial detection method for the industrial internet according to any one of claims 1 to 6, wherein in the step of performing image acquisition on the product to obtain the product detection image, different areas of the product are synchronously image-acquired and finally spliced to obtain the product detection image.
8. An industrial detection system of an industrial internet, the system comprising:
the light ray detection module is used for emitting detection light rays to the product and receiving feedback light rays reflected by the product, wherein the feedback light rays at least comprise reflection light rays and transmission light rays;
the image acquisition module is used for acquiring an image of the product to obtain a product detection image, and the image acquisition process and the process of emitting detection light to the product are synchronously carried out;
the image analysis module is used for analyzing the feedback light and generating a marking area in the product detection image, wherein the product detection image in the marking area is an area where the quality of the current product possibly has a problem;
and the image comparison module is used for comparing the product detection image in the marking area with a preset standard image, generating a detection result and storing the detection result.
9. The industrial detection system of industrial internet as claimed in claim 8, wherein the light detection module comprises:
the information acquisition unit is used for acquiring standard thickness information of a product;
the intensity selection unit is used for selecting detection light rays with different intensities according to the standard thickness information and vertically emitting the detection light rays to the product;
and the light receiving unit is used for simultaneously receiving the transmitted light passing through the product and the reflected light reflected by the product to obtain feedback light.
10. The industrial detection system of industrial internet according to claim 8, wherein the image capturing module comprises:
the acquisition unit is used for acquiring images of the product to obtain a first product image;
the image adjusting unit is used for adjusting the image of the first product image to obtain a second product image;
and the gray processing unit is used for carrying out gray processing on the second product image to obtain a product detection image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110846915.4A CN113533206A (en) | 2021-07-26 | 2021-07-26 | Industrial detection system and method for industrial Internet |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110846915.4A CN113533206A (en) | 2021-07-26 | 2021-07-26 | Industrial detection system and method for industrial Internet |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113533206A true CN113533206A (en) | 2021-10-22 |
Family
ID=78120903
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110846915.4A Pending CN113533206A (en) | 2021-07-26 | 2021-07-26 | Industrial detection system and method for industrial Internet |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113533206A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114965481A (en) * | 2022-05-12 | 2022-08-30 | 湖南晶讯光电股份有限公司 | Automatic optical detection defect detection method, system and equipment |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1576831A (en) * | 2003-07-02 | 2005-02-09 | 优志旺电机株式会社 | Wiring pattern check up apparatus |
| CN101501474A (en) * | 2006-06-07 | 2009-08-05 | 秦内蒂克有限公司 | Optical inspection |
| CN202533384U (en) * | 2012-05-03 | 2012-11-14 | 河南义腾新能源科技有限公司 | Defect detection system applied in battery diaphragm preparation process |
| CN108362703A (en) * | 2017-12-14 | 2018-08-03 | 北京木业邦科技有限公司 | A kind of veneer detection method and detection device based on artificial intelligence |
| CN110057841A (en) * | 2019-05-05 | 2019-07-26 | 电子科技大学 | A kind of defect inspection method based on transmittance structure light |
| CN110441323A (en) * | 2019-07-11 | 2019-11-12 | 大族激光科技产业集团股份有限公司 | The method for polishing and system of product surface |
| CN211347985U (en) * | 2019-11-08 | 2020-08-25 | 北京大恒图像视觉有限公司 | Machine vision detection device applied to surface detection industry |
| CN213456718U (en) * | 2020-09-09 | 2021-06-15 | 安徽高哲信息技术有限公司 | Double-light-source grain interior detection device |
| CN113155853A (en) * | 2020-08-13 | 2021-07-23 | 株式会社名南制作所 | Defect detection system, defect detection method, and program for detecting defects of plate-like wood |
-
2021
- 2021-07-26 CN CN202110846915.4A patent/CN113533206A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1576831A (en) * | 2003-07-02 | 2005-02-09 | 优志旺电机株式会社 | Wiring pattern check up apparatus |
| CN101501474A (en) * | 2006-06-07 | 2009-08-05 | 秦内蒂克有限公司 | Optical inspection |
| CN202533384U (en) * | 2012-05-03 | 2012-11-14 | 河南义腾新能源科技有限公司 | Defect detection system applied in battery diaphragm preparation process |
| CN108362703A (en) * | 2017-12-14 | 2018-08-03 | 北京木业邦科技有限公司 | A kind of veneer detection method and detection device based on artificial intelligence |
| CN110057841A (en) * | 2019-05-05 | 2019-07-26 | 电子科技大学 | A kind of defect inspection method based on transmittance structure light |
| CN110441323A (en) * | 2019-07-11 | 2019-11-12 | 大族激光科技产业集团股份有限公司 | The method for polishing and system of product surface |
| CN211347985U (en) * | 2019-11-08 | 2020-08-25 | 北京大恒图像视觉有限公司 | Machine vision detection device applied to surface detection industry |
| CN113155853A (en) * | 2020-08-13 | 2021-07-23 | 株式会社名南制作所 | Defect detection system, defect detection method, and program for detecting defects of plate-like wood |
| CN213456718U (en) * | 2020-09-09 | 2021-06-15 | 安徽高哲信息技术有限公司 | Double-light-source grain interior detection device |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114965481A (en) * | 2022-05-12 | 2022-08-30 | 湖南晶讯光电股份有限公司 | Automatic optical detection defect detection method, system and equipment |
| CN114965481B (en) * | 2022-05-12 | 2023-11-07 | 湖南晶讯光电股份有限公司 | Automatic optical detection defect detection method, system and equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110570410B (en) | Detection method for automatically identifying and detecting weld defects | |
| CN102441737B (en) | Apparatus and method for determining shape of end of welding bead | |
| CN111156923A (en) | Workpiece detection method, workpiece detection device, computer equipment and storage medium | |
| CN109579718B (en) | Method and device for detecting welding seam parameters, computer equipment and storage medium | |
| KR101702841B1 (en) | Method for monitoring defect in polaroid films | |
| JP5538220B2 (en) | Non-uniformity inspection method for polarizing plate using image analysis, and automatic non-uniformity inspection system for polarizing plate using the same | |
| CN113533206A (en) | Industrial detection system and method for industrial Internet | |
| US20160321792A1 (en) | System and a method for automatic recipe validation and selection | |
| CN115937170A (en) | Circuit board detection method and device, computer equipment and storage medium | |
| CN112129773B (en) | Wood surface defect detection method, device, equipment, system and storage medium | |
| CN109696240A (en) | Detection method, device and the readable storage medium storing program for executing of the semiconductor laser overall situation uniformity | |
| CN114813760A (en) | Surface defect detection device and surface defect detection method | |
| CN115272961A (en) | VR equipment early warning monitoring method and system based on artificial intelligence | |
| KR20230013206A (en) | Welding area inspection system and method thereof for assessing the risk based on artificial intelligence | |
| KR20140148067A (en) | Method for discriminating defect of optical films | |
| CN114813783A (en) | Chip surface flaw detection method | |
| CN115272258A (en) | Metal cylindrical surface defect detection method, system and medium based on machine vision | |
| KR20220088154A (en) | Examination apparatus and method of the same | |
| CN111566438B (en) | Image acquisition method and system | |
| CN111412941A (en) | Method and device for detecting mounting quality | |
| CN117808814A (en) | Welding defect detection and identification method and system based on machine vision | |
| US10255671B1 (en) | System and method for capture of high resolution/high magnification images | |
| CN117710369B (en) | Metal aluminum phosphate film defect detection method and system based on computer vision technology | |
| Byrne* et al. | Comparative analysis of vision systems for electroplating surface quality inspection | |
| CN114813746B (en) | Method, system, storage medium and equipment for curved needle detection based on machine vision |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20211022 |
|
| RJ01 | Rejection of invention patent application after publication |