CN115684272A - Steel structure crack detection method based on infrared camera - Google Patents
Steel structure crack detection method based on infrared camera Download PDFInfo
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- CN115684272A CN115684272A CN202310000626.1A CN202310000626A CN115684272A CN 115684272 A CN115684272 A CN 115684272A CN 202310000626 A CN202310000626 A CN 202310000626A CN 115684272 A CN115684272 A CN 115684272A
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Abstract
The invention discloses a steel structure crack detection method based on an infrared camera, which comprises the following steps: fixing an infrared camera, and continuously shooting by using the infrared camera to obtain a section of video of a fixed machine position; video information preliminary treatment: analyzing and calculating each frame on the image to obtain an average brightness value which is used as a brightness reference value of the frame; establishing a fitting type: analyzing to obtain related parameters in the fitting type, and drawing an image of pixel characteristic parameters according to the related parameters; further processing the video information; performing expansion operation and corrosion operation on the video image information to obtain an image with enhanced heat distribution of the crack under external disturbance; the highlight areas on the image are steel structure crack areas. According to the invention, the infrared camera is used for shooting the steel structure, and then the shot image is analyzed and processed to obtain the heat distribution image caused by the crack disturbance of the steel structure, so that the crack detection result of the steel structure can be rapidly and conveniently obtained.
Description
Technical Field
The invention relates to the technical field of steel structure crack detection, in particular to a steel structure crack detection method based on an infrared camera.
Background
In practical production practice, if the applied material has defects, the applied material will cause great harm and serious consequences. Therefore, it is important to detect defects in materials. The steel material is a commonly used material, and in practical production application, cracks of a steel structure, particularly cracks of a welding part are common problems, and particularly, if cracks exist at a U-shaped rib position in front of bridge deck steel, a large potential safety hazard can be caused. Because the steel structure crack is comparatively secret, it is great to rely on naked eye to discover the degree of difficulty. In the prior art, various steel structure crack detection methods exist, but the crack detection of large-batch steel products cannot be completed in a short time.
In summary, a method for detecting cracks of a steel structure is needed, which can be convenient and fast, and can complete the crack detection of large quantities of steel products in a short time.
Disclosure of Invention
The invention aims to provide a steel structure crack detection method based on an infrared camera, which can conveniently and quickly finish crack detection of large-batch steel structures.
In order to solve the technical problem, the invention provides a steel structure crack detection method based on an infrared camera, which comprises the following steps:
s1, fixing an infrared camera, judging whether a load needs to be applied according to a related scene, and continuously shooting a target object or a target area by using the infrared camera to obtain a section of fixed machine position and a video capable of seeing a crack opening process;
s2, video information preliminary processing: analyzing and calculating the data of each frame on the image in the video to obtain the average brightness value of all pixel points of each frame, and taking the average brightness value as the brightness reference value of the frame;
s3, establishing a fitting type: establishing a fitting type of the image by using the average brightness value, analyzing to obtain related parameters in the fitting type, and drawing the image according to the related parameters;
s4, further processing the video information; performing expansion operation and corrosion operation on the video image information to obtain an image with enhanced heat distribution of the crack of the material under external disturbance; and the highlight area on the image is a steel structure crack area.
Further, before fixing the infrared camera, the photographing time and whether or not the load needs to be applied are determined according to the relevant scene.
Further, in step S3, the fitting established is:
f(x, y, n)=a(x, y)+b(x, y)*J(n);
wherein f (x, y, n) is the brightness value of the pixel point of the video image of the nth frame under x, y coordinates, a (x, y) is the linear term A value, B (x, y) is the linear term B value, and J (n) is the brightness reference value of the nth frame.
Further, in step S3, parameter values of the linear term a value and the linear term B value are determined based on a least square method according to the fitting equation.
Further, in step S3, an image of the pixel brightness value is drawn according to the linear term B value.
Further, in step S4, the video image information is subjected to the expansion operation of 3*3 and the erosion operation of 3*3.
Further, after the step S4 is finished, the detection result of the steel structure crack detection is output according to the detection result.
Compared with the prior art, the invention at least has the following beneficial effects:
the method comprises the steps of continuously shooting a target object or a target area by using an infrared camera to obtain a section of video capable of seeing the crack opening process, analyzing and processing images in the shot video, obtaining an image with enhanced heat distribution of the crack of the steel structure under external disturbance, and further quickly and conveniently obtaining a crack detection result of the steel structure.
Furthermore, the steel structure crack detection method based on the infrared camera is applied to material defect detection, so that defect detection of large-batch steel materials can be rapidly carried out, and the working efficiency is improved.
Drawings
FIG. 1 is a schematic flow chart of an embodiment of the present invention;
FIG. 2 is an example of an infrared image in accordance with an embodiment of the present invention;
FIG. 3 is a drawing of an image according to an embodiment of the present invention.
Detailed Description
The method for detecting cracks in a steel structure based on an infrared camera according to the present invention will be described in more detail with reference to the accompanying schematic drawings, in which preferred embodiments of the present invention are shown, it being understood that those skilled in the art can modify the present invention described herein while still achieving the advantageous effects of the present invention. Accordingly, the following description should be construed as broadly as possible to those skilled in the art and not as limiting the invention.
The invention is described in more detail in the following paragraphs by way of example with reference to the accompanying drawings. Advantages and features of the present invention will become apparent from the following description and from the claims. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is merely for the purpose of facilitating and distinctly claiming the embodiments of the present invention.
The experimental results are combined with related knowledge to learn that: due to the stress concentration at the tip of the steel material, the fracture tip will generate a higher fracture energy due to crack propagation under the action of external loads. The temperature difference caused by the difference in fracture energy can reflect the defect condition of the steel structure. Therefore, the defect detection result of the steel material can be obtained by analyzing the heat distribution in the steel material. However, with infrared transient imaging techniques, the resulting image resolution is low and signal enhancement is required. Therefore, the inventor develops a steel structure crack detection method based on an infrared camera, and the correlation between related parameters and the crack heat release rate is utilized, so that the local heating difference in the process can be amplified, and the steel structure crack detection result can be conveniently and quickly obtained.
The embodiment provides a steel structure crack detection method based on an infrared camera, please refer to fig. 1, which includes the following steps:
s1, fixing an infrared camera, judging whether a load needs to be applied or not according to a relevant scene, and continuously shooting a target object or a target area by using the infrared camera to obtain a section of fixed machine position and a video capable of seeing a crack opening process;
s2, video information preliminary treatment: analyzing and calculating the data of each frame on the image in the video to obtain the average brightness value of all pixel points of each frame, and taking the average brightness value as the brightness reference value of the frame;
s3, establishing a fitting type: establishing a fitting type of the image by using the average brightness value, analyzing to obtain related parameters in the fitting type, and drawing the image according to the related parameters;
s4, further processing the video information; performing expansion operation and corrosion operation on the video image information to obtain an image with enhanced heat distribution of the crack of the material under external disturbance; and the highlight area on the image is a steel structure crack area.
As an example, when determining the photographing time from an actual scene, the determined photographing time requires a process capable of photographing the crack opening. When the steel structure crack detection method based on the infrared camera is applied to a steel structure bridge surface, the shooting time is determined according to the passing interval of vehicles. Because the target area of the measured object generally has artificial disturbance in the shooting process, such as artificial knocking, environmental influence or vehicle passing and other interference factors; in determining the photographing time, the influence of the disturbance factor on the photographing needs to be considered. Specifically, in this embodiment, to the bridge floor, the current vehicle is natural external load, can let the steel construction crack tip of bridge produce strain energy and concentrate to make infrared camera shoot the video of crack under external disturbance smoothly. Referring to fig. 3, as a graph of an average brightness value of each frame of a video obtained in this embodiment when a truck with a rear axle weighing 8 tons passes through a crack of a steel structure, a peak value in an image is a thermal image caused by opening of a micro crack when a wheel passes through, and a crack condition of a steel structure can be clearly determined from the image.
When shooting other steel material structures, if no natural external load exists, the load must be manually applied to shoot the process of crack opening.
In this embodiment, in step S3, the fitting formula established is:
f(x, y, n)=a(x, y)+b(x, y)*J(n)
wherein f (x, y, n) is the brightness value of the pixel point of the video image of the nth frame under x, y coordinates, a (x, y) is the linear term A value, B (x, y) is the linear term B value, and J (n) is the brightness reference value of the nth frame.
In a specific example, the parameter values of the linear term a value and the linear term B value are determined based on a least squares method.
Preferably, the linear term B value is positively correlated with the heat release rate of the steel structure crack, so that the difference of local heating in the process can be amplified, and the image of the pixel brightness value is drawn according to the linear term B value.
Further, the steel structure crack detection method based on the infrared camera can be used as a long-term detection means or a temporary detection method.
The detection method provided by the embodiment can be used as a long-term detection means or a temporary detection means, and can be used for monitoring the state of a bridge or quickly obtaining the defect detection result of a large batch of steel structure materials.
The method comprises the steps of continuously shooting a target object or a target area by using an infrared camera to obtain a section of video capable of seeing the crack opening process, analyzing and processing images in the shot video, obtaining an image with enhanced heat distribution of the crack of the steel structure under external disturbance, and further quickly and conveniently obtaining a crack detection result of the steel structure.
Furthermore, the steel structure crack detection method based on the infrared camera is applied to material defect detection, so that defect detection of large-batch steel materials can be rapidly carried out, and the working efficiency is improved.
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 (7)
1. A steel structure crack detection method based on an infrared camera is characterized by comprising the following steps:
s1, fixing an infrared camera, judging whether a load needs to be applied according to a related scene, and continuously shooting a target object or a target area by using the infrared camera to obtain a section of fixed machine position and a video capable of seeing a crack opening process;
s2, video information preliminary processing: analyzing and calculating the data of each frame on the image in the video to obtain the average brightness value of all pixel points of each frame, and taking the average brightness value as the brightness reference value of the frame;
s3, establishing a fitting type: establishing a fitting type of the image by using the average brightness value, analyzing to obtain related parameters in the fitting type, and drawing the image according to the related parameters;
s4, further processing the video information; performing expansion operation and corrosion operation on the video image information to obtain an image with enhanced heat distribution of the crack of the material under external disturbance; and the highlight area on the image is a steel structure crack area.
2. The infrared camera-based steel structure crack detection method of claim 1, wherein a photographing time and whether a load needs to be applied are determined according to a relevant scene before the infrared camera is fixed.
3. The infrared camera-based steel structure crack detection method as claimed in claim 1, wherein in step S3, the established fitting formula is:
f(x, y, n)=a(x, y)+b(x, y)*J(n);
wherein f (x, y, n) is the brightness value of the pixel point of the video image of the nth frame under x, y coordinates, a (x, y) is the linear term A value, B (x, y) is the linear term B value, and J (n) is the brightness reference value of the nth frame.
4. The infrared camera-based steel structure crack detection method as claimed in claim 3, wherein in step S3, parameter values of the linear term A value and the linear term B value are determined based on a least square method according to the fitting equation.
5. The method for detecting cracks on steel structures based on the infrared camera as claimed in claim 3, wherein in step S3, an image of pixel brightness values is drawn according to the linear term B values.
6. The method for detecting the crack of the steel structure based on the infrared camera as claimed in claim 1, wherein in step S4, the expansion operation of 3*3 and the corrosion operation of 3*3 are performed on video image information.
7. The method for detecting cracks of a steel structure based on an infrared camera as claimed in claim 1, wherein after the step S4 is finished, the detection result of the crack detection of the steel structure is output according to the detection result.
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Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH0972852A (en) * | 1995-09-04 | 1997-03-18 | Nisshin Steel Co Ltd | Detection method for crack of lining refractory in molten-metal receiver container and repair method for crack |
CN106127777A (en) * | 2016-06-27 | 2016-11-16 | 中山大学 | A kind of three dimensions crack separation identification and characterizing method |
JP2017053819A (en) * | 2015-09-11 | 2017-03-16 | 国立大学法人富山大学 | Crack detection method and detection program of concrete |
CN106651872A (en) * | 2016-11-23 | 2017-05-10 | 北京理工大学 | Prewitt operator-based pavement crack recognition method and system |
CN107220931A (en) * | 2017-08-02 | 2017-09-29 | 安康学院 | A kind of high dynamic range images method for reconstructing based on grey-scale map |
CN109743879A (en) * | 2016-12-30 | 2019-05-10 | 同济大学 | A kind of underground pipe gallery leakage detection method based on the processing of Dynamic IR thermography |
CN110264459A (en) * | 2019-06-24 | 2019-09-20 | 江苏开放大学(江苏城市职业学院) | A kind of interstices of soil characteristics information extraction method |
CN111145161A (en) * | 2019-12-28 | 2020-05-12 | 北京工业大学 | Method for processing and identifying pavement crack digital image |
CN112540089A (en) * | 2020-12-16 | 2021-03-23 | 江苏法尔胜材料分析测试有限公司 | Application method of digital imaging system in concrete bridge crack detection and analysis |
CN113916133A (en) * | 2021-10-19 | 2022-01-11 | 中铁隧道局集团路桥工程有限公司 | CCD-based linear array camera and infrared ray composite tunnel crack detection system |
-
2023
- 2023-01-03 CN CN202310000626.1A patent/CN115684272B/en active Active
Patent Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH0972852A (en) * | 1995-09-04 | 1997-03-18 | Nisshin Steel Co Ltd | Detection method for crack of lining refractory in molten-metal receiver container and repair method for crack |
JP2017053819A (en) * | 2015-09-11 | 2017-03-16 | 国立大学法人富山大学 | Crack detection method and detection program of concrete |
CN106127777A (en) * | 2016-06-27 | 2016-11-16 | 中山大学 | A kind of three dimensions crack separation identification and characterizing method |
CN106651872A (en) * | 2016-11-23 | 2017-05-10 | 北京理工大学 | Prewitt operator-based pavement crack recognition method and system |
CN109743879A (en) * | 2016-12-30 | 2019-05-10 | 同济大学 | A kind of underground pipe gallery leakage detection method based on the processing of Dynamic IR thermography |
CN109804119A (en) * | 2016-12-30 | 2019-05-24 | 同济大学 | A kind of asphalt pavement crack development degree detection method based on infrared thermal imagery map analysis |
CN107220931A (en) * | 2017-08-02 | 2017-09-29 | 安康学院 | A kind of high dynamic range images method for reconstructing based on grey-scale map |
CN110264459A (en) * | 2019-06-24 | 2019-09-20 | 江苏开放大学(江苏城市职业学院) | A kind of interstices of soil characteristics information extraction method |
CN111145161A (en) * | 2019-12-28 | 2020-05-12 | 北京工业大学 | Method for processing and identifying pavement crack digital image |
CN112540089A (en) * | 2020-12-16 | 2021-03-23 | 江苏法尔胜材料分析测试有限公司 | Application method of digital imaging system in concrete bridge crack detection and analysis |
CN113916133A (en) * | 2021-10-19 | 2022-01-11 | 中铁隧道局集团路桥工程有限公司 | CCD-based linear array camera and infrared ray composite tunnel crack detection system |
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