CN110599481A - Cement prefabricated plate detection system based on image recognition - Google Patents
Cement prefabricated plate detection system based on image recognition Download PDFInfo
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- CN110599481A CN110599481A CN201910881820.9A CN201910881820A CN110599481A CN 110599481 A CN110599481 A CN 110599481A CN 201910881820 A CN201910881820 A CN 201910881820A CN 110599481 A CN110599481 A CN 110599481A
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- 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
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- G06T7/0004—Industrial image inspection
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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- 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
- G01N2021/8887—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 based on image processing techniques
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Abstract
The invention discloses a cement precast slab detection system based on image recognition, which comprises: the device comprises an external bracket, a first photoelectric sensor, a second photoelectric sensor, a mobile platform, a guide rail, an image acquisition unit, a mobile carrier, a servo motor, a motion controller and an industrial personal computer; the photoelectric sensor is used for detecting the position of the mobile platform; the mobile platform is used for carrying the precast slab to be detected to move; the image acquisition unit is used for scanning the precast slab to be detected to obtain a scanned image; the image acquisition unit transmits the acquired scanning image to the industrial personal computer, the industrial personal computer analyzes the scanning image, and whether the precast slab to be detected is qualified is judged based on the analysis result; the detection system can monitor the production process of the prefabricated slab in real time, alarm production abnormity in time and feed back the production abnormity to relevant personnel for correction; the workload of workers only relying on naked eyes for identification is greatly reduced, and the product quality and precision are guaranteed.
Description
Technical Field
The invention relates to the field of optical detection, in particular to a cement precast slab detection system based on image recognition.
Background
In the current concrete precast slab production manufacturing process, to the specification of prefabricated slab, the accuracy of size and dimension is controlled the experience and the proficiency that lean on site worker entirely, the position of reinforcement rib is also judged by workman's naked eye entirely with high in the prefabricated slab simultaneously, wherein to the determination of built-in fitting position probably because personnel are different there are some deviations, the reinforcing bar length that leads to the prefabricated slab to stretch out all around differs, do not have especially good way to carry out real-time tracking and correction, through the research discovery to prior art, it is very necessary to design one set of full automatization optical detection equipment and carry out real-time tracking detection.
Disclosure of Invention
In the existing production process of the prefabricated plate, the quality of the prefabricated plate is different from the quality standard required by production only by human factors through judgment and correction, the installation process is very difficult possibly due to inaccurate sizes of the periphery of the prefabricated plate, meanwhile, the steel bar part is a framework of the prefabricated plate, the quality of the produced prefabricated plate is uneven if no rigid detection standard exists, and the use of the products is undoubtedly a great hidden danger of engineering quality. By the aid of the image recognition-based cement precast slab detection system, production abnormity can be timely alarmed and fed back to relevant personnel for correction in the process of precast slab production in real time. The workload of workers only relying on naked eyes for identification is greatly reduced, and the product quality and the precision are ensured.
In order to achieve the above object, the present application provides a system for detecting a cement precast slab based on image recognition, the system comprising:
the device comprises an external bracket, a first photoelectric sensor, a second photoelectric sensor, a mobile platform, a guide rail, an image acquisition unit, a mobile carrier, a servo motor, a motion controller and an industrial personal computer;
the system comprises an external support, a detection area, a first photoelectric sensor, a second photoelectric sensor, an industrial personal computer and a control computer, wherein the external support is arranged on the ground, the detection area is arranged between the external support and the ground, the first photoelectric sensor is arranged on the inner walls of the external supports on two sides of the inlet end of the detection area respectively, the second photoelectric sensor is arranged on the inner walls of the external supports on two sides of the outlet end of the detection area respectively, and the first photoelectric sensor and the second photoelectric sensor are used for detecting the; the mobile platform is used for carrying the precast slab to be detected to move; the guide rail is arranged at the top of the detection area, and two ends of the guide rail respectively extend to the inlet end and the outlet end of the detection area; the image acquisition unit and the mobile carrier are both arranged in the detection area, the image acquisition unit is used for scanning the precast slab to be detected in the detection area under the control of the industrial personal computer to obtain a scanned image, the image acquisition unit is arranged on the mobile carrier, the servo motor is used for driving the mobile carrier to move on the guide rail, and the motion controller controls the servo motor under the control of the industrial personal computer; the image acquisition unit transmits the acquired scanning image to the industrial personal computer, and the industrial personal computer analyzes the scanning image and judges whether the prefabricated plate to be detected is qualified or not based on the analysis result.
Preferably, when a mobile platform carrying the precast slabs to be detected enters a detection area, the first photoelectric sensor is triggered, the industrial personal computer receives trigger information of the first photoelectric sensor and controls the image acquisition unit to enter an initialization state, the mobile platform continues to move along the direction from the inlet end of the detection area to the outlet end of the detection area, when the mobile platform triggers the second photoelectric sensor, the industrial personal computer sends an instruction to stop the mobile platform from moving, the industrial personal computer controls the image acquisition unit to acquire images of the precast slabs to be detected, the industrial personal computer controls the mobile carrier to carry the image acquisition unit to move from the outlet end of the detection area to the inlet end of the detection area for continuous scanning, and the images obtained by scanning are transmitted to the industrial personal.
Preferably, 2 first photoelectric sensors are symmetrically arranged on the inner walls of the outer supports on two sides of the inlet end of the detection area, and 2 second photoelectric sensors are symmetrically arranged on the inner walls of the outer supports on two sides of the outlet end of the detection area.
Preferably, the image acquisition unit includes: industrial scanning cameras and LED light sources.
Preferably, the industrial personal computer analyzes the scanned image, and specifically comprises:
extracting feature maps from the scanned images using a series of convolutions + firing;
acquiring the approximate position of the target from the extracted feature map in a network training mode;
continuing training based on the obtained approximate position of the target to obtain the accurate position of the target;
with the obtained target accurate position, a target for classification is obtained from the feature map and posing into data of a fixed length.
Preferably, the posing forms data with fixed length, and specifically includes:
step 1: and mapping the ROI to a position corresponding to the feature map according to the input image:
step 2: the positions obtained in the step (1) are extracted and divided into a plurality of grid structures with the same size, and the number of the grid structures is the same as the dimension of final output;
and step 3: performing maximum pooling operation on each grid structure;
and 4, step 4: finally, the output with fixed size is obtained.
Preferably, the industrial personal computer analyzes the scanned image and extracts related parameters from the scanned image, and the method comprises the following steps: the size specification of each prefabricated plate, the position and the size of the embedded part, the length of the reinforcing rib, the length and the thickness of the steel plate extending out of the periphery of the prefabricated plate are compared with an original design database of a built model in real time, and whether the prefabricated plate to be detected is qualified or not is judged based on a comparison result.
Preferably, if the comparison result shows that the precast slab to be detected is unqualified, the industrial personal computer conducts trial display on the display screen and reminds field workers to correct the precast slab.
Preferably, the precast slab to be detected is located in a precast slab die, and the precast slab die is fixed on the upper surface of the moving platform.
Preferably, the system comprises 2 mutually symmetrical guide rails, the 2 guide rails are symmetrically arranged at the top in the outer support, and the moving carrier is in sliding connection with the 2 guide rails.
One or more technical solutions provided by the present application have at least the following technical effects or advantages:
by the detection system, unqualified and non-standard parts in the production process of the prefabricated slab can be found in time. The production quality of the prefabricated slab is guaranteed, and the workload of naked eye detection in the aspect of manpower is reduced; and defects which can not be seen by naked eyes are found, so that the engineering quality and the personal safety are ensured.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention;
FIG. 1 is a schematic side view of a system for detecting a cement precast slab based on image recognition according to the present invention;
FIG. 2 is a schematic diagram of a main body of a cement precast slab detection system based on image recognition in the invention;
FIG. 3 is a schematic diagram of the control logic of the detection system for the cement precast slab based on image recognition in the invention;
the system comprises a base, a light source, a prefabricated plate mould and a movable platform, wherein the light source comprises a light source 1, a light source, a photoelectric sensor 3, a movable carrier 4, a Y-axis motion guide rail 6, an industrial scanning camera 7, an LED light source 8.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflicting with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described and thus the scope of the present invention is not limited by the specific embodiments disclosed below.
Referring to fig. 1-3, the present application provides a system for detecting a cement precast slab based on image recognition, wherein the whole set of system for detecting a cement precast slab comprises the following parts: mechanical structure, bottom hardware application, camera controller, motion controller, industrial computer. The mechanical structure in turn substantially comprises: the present invention is not particularly limited, and the embodiment of the present invention is described in terms of a Y-axis direction, and various mechanical connectors. The underlying hardware applications include: the device comprises an industrial scanning camera, an LED light source, a Y-axis servo motor and a photoelectric sensor.
The whole system engineering process is as follows:
when the system is pushed by a moving platform provided with a prefabricated plate manufacturing mould, the photoelectric sensors symmetrically arranged on two sides of the front end of the system are triggered for the first time, the system is prompted that the prefabricated plate moving platform is ready to enter a detection system, and a photographing system (comprising an industrial scanning camera, an LED light source and a camera controller) is initialized and ready to work. And when the symmetrical photoelectric sensors at the two sides of the rear end of the system are triggered again, the system sends an instruction to stop the moving platform to continue propelling. At the moment, the front and the rear pairs of photoelectric sensors are triggered simultaneously, which indicates that the whole mobile platform completely enters the photographing area. The system starts to work, the industrial personal computer issues an instruction to turn on the industrial scanning camera and the LED light source, the Y-axis servo motor starts to work to drive the industrial scanning camera and the LED light source which are positioned below the guide rail in the Y-axis direction in the frame to start moving in the Y direction from an initial starting point at one end to the other end and continuously scanning, when the industrial scanning camera and the LED light source move to a limited position at the other end, the Y-axis servo motor stops moving, the camera stops scanning, and the LED light source is turned. After a period of time, the Y-axis servo motor starts to move again, the industrial scanning camera and the LED light source are driven to move to the initial position from the limited position in the opposite direction, and the next batch of prefabricated plate moving platforms enter the detection area. At the moment, the whole scanning process is completely finished, the camera controller transmits the scanning result back to the industrial personal computer in real time, and image analysis is carried out by a corresponding algorithm, wherein the algorithm analysis mainly uses a Fast R-CNN method:
the basic structure of the Fast R-CNN method comprises the following 4 parts:
1. a feature extraction section: extracting feature map from original image by using a series of convolution + firing;
2. the RPN part: acquiring the approximate position of the target from the feature map in a network training mode;
3. section of Propusal Layer: continuing training by using the approximate position obtained by the RPN to obtain a more accurate position;
4. ROI Pooling part: using the accurate position obtained in the previous step to extract the target to be used for classification from the feature map, and posing the target into data with fixed length;
the above principle realizes the process of one prosal cutout, firstly cuts out the prosal, cuts out the position of the corresponding candidate area on the feature map according to the relative coordinate of the prosal, then carries out resize to a unified size on the feature map which is cut out, usually the resize can adopt the specific pooling operation, and the concrete operation is as follows:
and mapping the ROI to a position corresponding to the feature map according to the input image: since the real position of the input pro-visual is relative to the original image, and the ROI popping acts on the output feature map of the convolutional layer, it needs to be mapped to the corresponding position of the feature map;
the positions obtained above are extracted and divided into a plurality of blocks (grid structures) with the same size, and the number of the blocks is the same as the dimension of final output;
performing maximum pooling operation on each block;
finally, obtaining output with fixed size;
and finally extracting relevant parameters including the dimension of each prefabricated plate, the position and the dimension of the embedded part, the length of the reinforcing ribs, the length and the thickness of the reinforcing steel bars extending out of the periphery of the prefabricated plate and the like, comparing the extracted parameters with the original design database of the built model in real time, directly displaying the results on a display screen of an industrial personal computer if the extracted parameters are abnormal, and reminding field workers to correct the defects in time.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. An image recognition-based cement precast slab detection system is characterized by comprising:
the device comprises an external bracket, a first photoelectric sensor, a second photoelectric sensor, a mobile platform, a guide rail, an image acquisition unit, a mobile carrier, a servo motor, a motion controller and an industrial personal computer;
the system comprises an external support, a detection area, a first photoelectric sensor, a second photoelectric sensor, an industrial personal computer and a control computer, wherein the external support is arranged on the ground, the detection area is arranged between the external support and the ground, the first photoelectric sensor is arranged on the inner walls of the external supports on two sides of the inlet end of the detection area respectively, the second photoelectric sensor is arranged on the inner walls of the external supports on two sides of the outlet end of the detection area respectively, and the first photoelectric sensor and the second photoelectric sensor are used for detecting the; the mobile platform is used for carrying the precast slab to be detected to move; the guide rail is arranged at the top of the detection area, and two ends of the guide rail respectively extend to the inlet end and the outlet end of the detection area; the image acquisition unit and the mobile carrier are both arranged in the detection area, the image acquisition unit is used for scanning the precast slab to be detected in the detection area under the control of the industrial personal computer to obtain a scanned image, the image acquisition unit is arranged on the mobile carrier, the servo motor is used for driving the mobile carrier to move on the guide rail, and the motion controller is used for controlling the servo motor under the control of the industrial personal computer; the image acquisition unit transmits the acquired scanning image to the industrial personal computer, and the industrial personal computer analyzes the scanning image and judges whether the prefabricated plate to be detected is qualified or not based on the analysis result.
2. The system for detecting the cement precast slab based on the image recognition is characterized in that:
when a mobile platform carrying a precast slab to be detected enters a detection area, a first photoelectric sensor is triggered, an industrial personal computer receives trigger information of the first photoelectric sensor and controls an image acquisition unit to enter an initialization state, the mobile platform continuously moves along the direction from an inlet end of the detection area to an outlet end of the detection area, when the mobile platform triggers a second photoelectric sensor, the industrial personal computer sends an instruction to stop the mobile platform from moving, the industrial personal computer controls the image acquisition unit to acquire images of the precast slab to be detected, the industrial personal computer controls a mobile carrier carrying the image acquisition unit to move from the outlet end of the detection area to the inlet end of the detection area for continuous scanning, and the images obtained by scanning are transmitted to the industrial personal computer.
3. The system for detecting the cement precast slabs based on the image recognition as recited in claim 1, wherein 2 first photoelectric sensors are symmetrically installed on the inner walls of the outer supports on both sides of the entrance end of the detection area, and 2 second photoelectric sensors are symmetrically installed on the inner walls of the outer supports on both sides of the exit end of the detection area.
4. The system for detecting the cement precast slab based on the image recognition is characterized in that the image acquisition unit comprises: industrial scanning cameras and LED light sources.
5. The system for detecting the cement precast slab based on the image recognition as recited in claim 1, wherein the industrial personal computer analyzes the scanned image, and specifically comprises:
(1) image acquisition: continuously shooting the precast slab by means of an LED light source and an industrial scanning camera, converting the shot image into a digital image, and storing the digital image in a computer;
(2) image enhancement: carrying out corresponding filtering noise reduction processing on the acquired image;
(3) image recognition: extracting key factors in the image after the image enhancement processing, including: the size of the whole precast slab, the length and the number of the steel bars, and the position and the size of an embedded part in the precast slab; comparing the extracted parameters with data in the original factory database, and judging the model of the prefabricated plate;
(4) data processing and judging: and (4) comparing the data extracted in the step (3) with the original design size, quantity, position and size in the model database, judging whether the data meet the original design requirements, and outputting the judgment result to a computer display screen to remind a worker whether the data need to be changed.
6. The system for detecting the cement precast slab based on the image recognition as recited in claim 5, wherein the outputting of the data with a fixed length specifically comprises:
step 1: after image recognition is carried out according to the collected images, different information of required characteristics is extracted by utilizing the obtained information such as accurate positions, and the characteristics comprise: forming a related characteristic map by the length and the width of the precast slab and the length and the thickness of the steel bar;
step 2: the positions of the characteristic information obtained in the step 1 are extracted and divided into a plurality of grid structures with the same size, and the number of the grid structures is the same as the dimension of final output;
and step 3: performing maximum pooling operation on each grid structure;
and 4, step 4: finally, the output with fixed size is obtained.
7. The system for detecting the cement precast slab based on the image recognition as recited in claim 1, wherein an industrial personal computer analyzes the scanned image and extracts related parameters from the scanned image, and the system comprises: the size specification of each prefabricated plate, the position and the size of the embedded part, the length of the reinforcing rib, the length and the thickness of the steel plate extending out of the periphery of the prefabricated plate are compared with an original design database of a built model in real time, and whether the prefabricated plate to be detected is qualified or not is judged based on a comparison result.
8. The system for detecting the cement precast slabs based on the image recognition is characterized in that if the precast slabs to be detected are judged to be unqualified according to the comparison result, the industrial personal computer displays the precast slabs on the display screen in real time and reminds field workers of correction.
9. The system for detecting the cement precast slabs based on the image recognition is characterized in that the precast slabs to be detected are located in a precast slab mold, and the precast slab mold is fixed on the upper surface of the moving platform.
10. The system for detecting the cement precast slab based on the image recognition is characterized in that the system comprises 2 guide rails which are symmetrical with each other, the 2 guide rails are symmetrically arranged at the top in an external bracket, and a moving carrier is connected with the 2 guide rails in a sliding mode.
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| CN113390875A (en) * | 2021-07-21 | 2021-09-14 | 华东交通大学 | Method for improving crack detection precision of steel fiber concrete |
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| CN115126266A (en) * | 2022-07-04 | 2022-09-30 | 中铁二十局集团第二工程有限公司 | Construction method of embedded part |
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| CN117095294B (en) * | 2023-08-24 | 2024-06-25 | 中建安装集团黄河建设有限公司 | Precast floor slab construction quality diagnosis method, medium and system |
| CN117808356A (en) * | 2023-12-29 | 2024-04-02 | 江苏方力建设有限公司 | Concrete member quality control method and system based on visual monitoring |
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| CN117571720B (en) * | 2024-01-12 | 2024-03-22 | 贵州科筑创品建筑技术有限公司 | Method, device and system for detecting concrete appearance bubbles and storage medium |
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