KR20240066600A - Concrete structure crack inspection system using laser scanner and unmanned aerial vehicle - Google Patents

Abstract

The present invention generates cracks in the structure by binarizing and differential processing the surface shape information of the structure collected through a laser scanner and the image obtained through the lighting that emits visible light of different wavelengths mounted on the unmanned aerial vehicle and the camera that captures the same. This is about a concrete structure crack inspection system using a laser scanner and unmanned aerial vehicle that can inspect.
The concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle according to the present invention is mounted on an unmanned aerial vehicle and is a light directed at the structure to be inspected. The first and second lights emit visible light of different wavelengths and are used to illuminate the structure to be inspected. A laser scanner that detects surface shape information of a structure by irradiating laser light, a camera mounted on the unmanned air vehicle to photograph the structure, a controller mounted on the unmanned air vehicle to control the camera, first light, and second light, same inspection It includes an image processor that inspects defects occurring in the structure by processing the first image captured when the first light is emitted at the point and the second image captured when the second light is emitted.

Description

{Concrete structure crack inspection system using laser scanner and unmanned aerial vehicle}

The present invention relates to a concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle. More specifically, the surface shape information of the structure collected through a laser scanner and lighting that emits visible light of different wavelengths mounted on an unmanned aerial vehicle It relates to a concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle that can inspect cracks in a structure by binarizing and differential processing images acquired through a camera that captures the image.

Large structures and facilities built in the process of developing into an industrial society suffer structural damage due to defects in the design and construction process or various factors that were not considered at the time of design, and as the period of use of these structures passes, they gradually deteriorate. Its safety is greatly threatened. For example, in the case of structures with severe structural damage, there are frequent cases where the service life is shortened to a level that falls far short of the design service life planned at the time of design.

Accordingly, efforts are urgently needed to ensure the long-term safety and operability of building structures. In particular, large structures such as buildings, bridges, dams, etc. are continuously exposed to various operating loads, shocks from external objects, earthquakes, wind loads, wave loads, corrosion, etc., so the problem of ensuring the safety of structures from these is an economic and social issue. It is becoming an issue of great interest. In order to accurately diagnose the safety of these large structures, monitoring of structural behavior through appropriate experimental measurements, technology to dynamically analyze structural damage, and diagnostic technology through analysis to model structural damage are required.

Technologies used to detect damage to these large structures include material non-destructive testing methods, positive displacement measurement methods, and vibration characteristic measurement methods. For example, among these, the method of estimating damage to a structure using positive displacement measurement and vibration characteristics is usually called System Identification (SID). This structural identification technique (SID) is a method of estimating structural characteristics by measuring the behavior of the structural system and modeling it through structural analysis.

As mentioned above, non-destructive testing technology for evaluating abnormal behavior of structures is a cutting-edge technology that is highly utilized across industries such as machinery, aviation, shipbuilding, and construction. In particular, in the case of large infrastructure facilities such as ultra-long bridges and high-rise buildings, abnormal behavior causes damage, which in turn causes enormous economic damage and serious human casualties, so the operation of flawless behavior evaluation is essential.

Accordingly, periodic safety inspections are being conducted on major social infrastructure facilities, but they are mainly limited to visual inspections of accessible points by inspectors. In addition, there is a lack of manpower and resources required for inspection and inspection of inaccessible facilities. The reality is that the inspection cycle is limited due to inspection difficulties. In addition, in order to complement the problems of the non-destructive diagnosis method according to the above-mentioned conventional technology, there is a need to develop an algorithm technology that can detect local damage to vulnerable members early through a local measurement system.

Meanwhile, in Korea, as the number of aging special bridges increases rapidly, the number of regular inspections is also increasing, and a significant portion of these inspections are carried out visually.

In addition, research is being actively conducted to replace visual inspection by using unmanned aerial vehicles (UAVs) and image processing techniques.

The concrete structure crack inspection technology applied to conventional computer image processing, including Patent Publication No. 2003-83359, basically acquires an image, which is a digital image, by photographing the surface of the concrete structure, and processes the obtained image using a computer algorithm to capture the corresponding image. To determine whether a crack exists in an area, the imaging information obtained from the camera is given a value that uniformly increases or decreases from light to dark depending on the light and dark, and this is binarized. ) processing detects dark areas that contrast sharply with the background, which is mainly bright areas.

In other words, a value between 0 and 255, commonly used as gray scale, is set for each pixel of the raw imaging information acquired through the camera, and the darkest and brightest parts are divided into the darkest and brightest parts. After quantifying the brightness of each pixel by assigning 0 and 225 respectively, binarization is performed to assign a single value to pixels above and below a certain standard value, for example, by averaging the grayscale values of all pixels to obtain the average value. After setting the standard value, imaging information is processed by assigning 0 to pixels that exceed the standard value and assigning 1 to pixels that fall below the standard value.

Through conventional computer image processing applied concrete structure crack inspection technology, including the above-mentioned patent publication No. 2003-83359, it has become possible to secure the speed, convenience, and safety of crack inspection. However, this prior technology basically uses imaged information. Since it was simply divided into light and dark parts and the dark part was considered as a crack, there was bound to be a limit to the detection accuracy of the crack.

In other words, there are frequent malfunctions in which depressed areas with lower brightness compared to the non-cracked surface of the structure, which is the background, or areas with lower brightness compared to the surrounding areas due to deposits of foreign substances, are detected as crack formation areas by considering them as dark areas in contrast to the bright background.

Accordingly, the area where a crack was not formed and foreign matter was simply deposited was mistaken for a crack area, and unnecessary processing such as raising an alarm or separately storing imaging information was performed, which resulted in a decrease in inspection efficiency and an erosion of computer resources. .

Japanese Patent Publication No. 2018-128278 (2018.08.16) Republic of Korea Patent Publication No. 10-2170054 (2020.10.26)

The present invention was created to solve the above problems, and is a concrete structure crack inspection using a laser scanner and an unmanned aerial vehicle that provides information on the overall appearance of the structure to be inspected along with the captured image and prevents misjudgment of the crack area due to foreign substances, etc. The purpose is to provide a system.

The concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle according to the present invention is mounted on an unmanned aerial vehicle and is a light directed at the structure to be inspected. The first and second lights emit visible light of different wavelengths and are used to illuminate the structure to be inspected. A laser scanner that detects surface shape information of a structure by irradiating laser light, a camera mounted on the unmanned air vehicle to photograph the structure, a controller mounted on the unmanned air vehicle to control the camera, first light, and second light, same inspection It includes an image processor that inspects defects occurring in the structure by processing the first image taken when the first light is emitted at the point and the second image taken when the second light is emitted.

The image processor is an information device with a built-in memory device and is connected to the laser scanner and controller to store the surface shape information of the structure and the image information captured by the camera in the memory device, and the image information captured when the first light is emitted at the same inspection point is stored in the memory device. It is desirable to generate a first binary image and a second binary image by binarizing the first image and the second image captured when the second light is emitted, and to generate a difference image by differentiating the first binary image and the second binary image. do.

The image processor assigns logical values of 1 and 0 to pixels below the brightness average for all pixels and pixels above the brightness average, respectively, to generate a first binary image and a second binary image from the first image and the second image, respectively. It is desirable to do so.

The concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle according to the present invention can solve the problem of conventional computer image processing-based crack inspection that misjudges foreign substances as cracks, thereby improving the accuracy of computer image processing-based concrete structure crack inspection. It can be improved dramatically.

1 is a conceptual diagram showing the configuration of a concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle according to an embodiment of the present invention;
Figure 2 is a conceptual diagram showing the state of performing crack inspection of a bridge structure through a concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle of the present invention;
Figure 3 is a block diagram showing the configuration of a concrete structure crack inspection system using the laser scanner and unmanned aerial vehicle of Figure 1;
Figure 4 is a diagram showing images at each stage of inspection through the concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle of the present invention.

Hereinafter, a concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle according to an embodiment of the present invention will be described in detail with reference to the attached drawings. Since the present invention can be subject to various changes and can have various forms, specific embodiments will be illustrated in the drawings and described in detail in the text. However, this is not intended to limit the present invention to a specific disclosed form, and should be understood to include all changes, equivalents, and substitutes included in the spirit and technical scope of the present invention. While describing each drawing, similar reference numerals are used for similar components. In the attached drawings, the dimensions of the structures are enlarged from the actual size for clarity of the present invention.

Terms such as first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, a first component may be named a second component, and similarly, the second component may also be named a first component without departing from the scope of the present invention.

The terms used in this application are only used to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, "include" or "have" Terms such as are intended to designate the presence of features, numbers, steps, operations, components, parts, or a combination thereof described in the specification, but are intended to indicate the presence of one or more other features, numbers, steps, operations, components, parts, or It should be understood that the existence or addition possibility of combinations of these is not excluded in advance.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the technical field to which the present invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted in an ideal or excessively formal sense unless explicitly defined in the present application. No.

The concrete structure crack inspection system using a laser scanner and an unmanned aerial vehicle according to the present invention is for inspecting whether cracks (C) have appeared in concrete structures (10) such as various buildings and bridges. As shown in FIG. 1, a laser scanner 30 is installed around the structure 10 to be inspected and extracts surface shape information of the structure 10 by radiating laser light to the structure 10, and a laser scanner 30 is installed around the structure 10 to be inspected. It consists of an unmanned aerial vehicle (20) that flies, and an image processor (50) that receives image information and surface shape information of the structure from the unmanned aerial vehicle (20) and the laser scanner (30), respectively.

In the present invention, the surface shape information of the structure 10 acquired through the laser scanner 30 is obtained as the laser light emitted from the laser scanner 30 is reflected from the surface of the structure 10. It is established by extracting the three-dimensional coordinates of the surface of the structure 10, and is stored in the memory of the image processor 50 along with the image information acquired by the camera 40, which will be described later. The information recorded at the same time is stored in the same structure 10. It is treated as image information and surface shape information.

Therefore, by checking the image information and surface shape information recorded at the same time, the user of the system to which the present invention is applied can easily identify the structure or inspection point on the structure corresponding to the image information through the surface shape information in crack inspection through image information. It can be specified.

Meanwhile, the actual determination of whether a crack has occurred in the present launch is performed through processing of image information acquired by the camera 40, and as shown in FIG. 2, an unmanned air vehicle flying around the inspection target structure 10 An image of the surface of the structure 10 is obtained by the camera 40 mounted on the unmanned aerial vehicle 20.

In addition, in the present invention, a first light 41 and a second light 42 are connected and selectively tuned to the camera 40. In addition, as shown in FIG. 3, the camera 40 and the second light 42 are configured. It consists of a controller 45 connected to the first light 41 and the second light 42, the controller 45, and the image processor 50.

In the present invention, the controller 45 connected to the camera 40, the first light 41, and the second light 42 controls the camera 40, the first light 41, and the second light 42. At the same time, wireless communication with the image processor 50 is also performed, and the controller 45 and the image processor 50 are equipped with a wireless communication module that satisfies the same communication protocol.

That is, while the laser scanner 30 and the image processor 50 are connected by wire, the controller 45 and the image processor 50 mounted on the unmanned aerial vehicle 20 are connected wirelessly, and thus the laser scanner installed on the ground The surface shape information of the structure 10 generated in (30) is input to the image processor 50 through wired communication, while the image information transmitted from the controller 45 of the unmanned aerial vehicle 20 is input into the image processor 50 through wireless communication. It is transmitted to the processor 50.

The first light 41 and the second light 42 are installed to point in the same direction as the camera 40 and illuminate the surface of the structure 10, such as a bridge, which is the subject. These first lights 41 ) and the second lighting 42 are configured to irradiate visible light of different wavelengths.

For example, the first light 41 may emit visible light of a red wavelength and the second light 42 may emit visible light of a yellow wavelength, and these first lights 41 and second lights ( 42) are not turned on at the same time but are turned on alternately, so that the structure 10, which is the subject, is not illuminated with different wavelengths of light at the same time.

As described above, the visible light emitted from the first light 41 and the second light 42 has different wavelengths, that is, colors. It is preferable that these different colors be of a series of colors that are as clearly distinguished as possible. In the following, for convenience of explanation and ease of understanding, the case where the first light 41 and the second light 42 emit red light and yellow light, respectively, as illustrated above, will be applied.

In this invention, when an inspection start command is input from an inspector while the unmanned aerial vehicle 20 is temporarily stopped at an inspection point of the structure 10, that is, in a hovering state or flying at a low speed, the controller 45 first Second, after turning on the first light 41, the camera 40 is operated to obtain a first image 71, which is raw imaging information about the structure 10, which is the illuminated subject, and this first image (71) is wirelessly transmitted to the image processor (50), and thirdly, the first light (41) is turned off.

The inspector's command to start the inspection can be input through manipulation of a wireless controller connected to the controller 45, and the transmitted first image 71 is stored in the memory of the image processor 50.

In this way, immediately after the storage of the first image 71 in the memory of the image processor 50 and the turning off of the first light 41 are completed, the same process is also performed for the second light 42 at the same point. That is, the controller 45 first turns on the second light 42 and then secondly operates the camera 40 to produce a second image 72, which is raw imaging information about the structure 10, which is the illuminated subject. is acquired and transmitted wirelessly to the image processor 50, and thirdly, the second light 42 is turned off.

Accordingly, the image processor 50 converts the first image 71, which is an image under the red light illumination of the first light 41, and the second image 72, which is an image under the yellow light illumination of the second light 42, into the structure to be inspected. In (10), the same shooting area can be secured.

The above-described process consists of a number of steps, such as the first light 41 and the second light 42 being sequentially turned on and off and two camera 40 shootings are performed. However, this series of procedures is performed by a controller ( Not only is this performed by the camera 40, the first light 41, and the second light 42, which are automatically and electrically controlled by 45), but the camera 40, which is the controlled object, is also an optical device capable of instantaneous operation. It can be performed all at once in such a short time that the inspector cannot even feel it.

In particular, the above-mentioned series of procedures can be completed within an instantaneous time of about one tenth of a second, so hovering is not required for a long time, and can be performed without difficulty even in low-speed flight rather than stationary flight.

When the storage of the second image 72 and the turning off of the second light 42 are completed and the shooting of a single point is completed, the inspector moves the unmanned aerial vehicle 20 to the next inspection point and repeats the above-described process. This process is repeated at predetermined intervals for the entire inspection section, that is, so that no missing parts occur and the first image 71 and the second image 72 for the entire inspection section are secured.

The image processor 50 processes the first image 71 and the second image 72 for each inspection point stored in its memory device, and is operated by a computer such as a desktop computer or laptop computer equipped with a predetermined image processing program. It can be configured, and a wireless module that performs wireless communication with the controller 45 is mounted as described above.

That is, the image processor 50 in the present invention is a computer equipped with a program that performs computer processing on image information, and performs wireless communication with the controller 45 of the unmanned aerial vehicle 20 and the laser scanner 30. ) is connected by wire to collect information.

Computational image processing performed in the image processor 50 of the present invention includes binarization processing, and the binarization processing is performed on the first image 71 and the second image 72 acquired for each inspection point. Binarization using basically the same technique is performed on a plurality of first images 71 and second images 72 acquired at each point. Hereinafter, the first image 71 and the second images 72 acquired at one inspection point will be described. Only the processing of the image 72 will be described.

In addition, for ease of understanding, as shown in FIG. 4, the subsequent processing will be explained by taking as an example the case where red-colored mud foreign matter (F) and cracks (C) are formed in the light gray concrete structure 10.

For binarization processing, the image processor 50 first calculates the average brightness value for all pixels of the first image 71 captured when the first light 41 emits light.

The first image 71 includes a plurality of pixels, and each pixel is given brightness information by the visible light emitted from the first light 41 reflected from the surface of the structure 10, which is the subject, and the image processor 50 ) calculates the average brightness value of the first image 71 by adding up the brightness information of all pixels and dividing it by the number of pixels.

As described above, the first light 41 emits red light, so a large amount of visible light from the first light 41 is reflected not only on the surface of the concrete structure 10, which has a light gray tone close to white, but also on the red-colored mud foreign matter F. On the other hand, at the crack C of the concrete structure 10, the light irradiated into the crack C is not reflected, thereby forming a dark part.

Therefore, the average brightness value of the first image 71 is smaller than the brightness information of the pixels on the surface of the light gray concrete structure 10 and the pixels in the mud foreign matter (F) portion, that is, it is darker, and is lower than the brightness information of the pixels in the crack (C) portion. It becomes bigger, that is, brighter.

The image processor 50 also processes the second image 72 captured when the second light 42 emits light in the same manner as above. The second light 42 emits yellow light and is a light gray concrete While a large amount of reflected light is formed on the surface of the structure 10, the formation of reflected light is low in the mud foreign matter (F) area and the crack (C) area.

Therefore, the average brightness value of the second image 72 is smaller than the brightness information of the surface pixels of the light gray concrete structure 10, that is, it is darker, and is larger than the brightness information of the pixels in the mud foreign matter (F) area and the pixels in the crack (C) area. In other words, it becomes brighter.

Ultimately, in the first image 71 taken when the first light 41 emits red light and the second image 72 taken when the second light 42 emits yellow light, the crack C is Both the first image 71 and the second image 72 are detected as dark areas, but the foreign matter (F) area is detected as a bright area in the first image 71, while it is detected as a dark area in the second image 72. Taking this into account, only the parts detected as dark areas in both the first image (71) and the second image (72) are identified as cracks (C), and only in either the first image (71) or the second image (72). The part detected as dark is considered a foreign substance (F).

If the above-described process is explained from the perspective of logical operations performed during computer processing, after calculating the brightness average value, the image processor 50 assigns a logical value of 1 to pixels with brightness information below the reference brightness average value and processes them as dark areas. And, pixels with brightness information that exceeds the average brightness value are given a logical value of 0 and processed as highlights.

Therefore, in the first image 71, the pixels of the concrete structure 10 and the mud foreign matter (F) portion are given a logical value of 0 and are treated as highlights, and only the pixels of the crack (C) portion are given a logical value of 1. In the second image 72, the pixels in the structure 10 are given a logic value of 0 and processed as a bright part, but the pixels in the foreign matter (F) and crack (C) parts are treated as bright. A logical value of is given and processed as shadow.

When the binarization process is completed, the image processor 50 performs difference processing to generate a difference image 90.

In differential processing, the logical value for each pixel of the first binary image 81 and the logical value for each pixel of the second binary image 82 are logically multiplied (∧). That is, if the two logical values are the same, the logical value is maintained, If they are different, the difference image 90 is generated by calculating in a way that 0 is given as a logical value.

Therefore, after differential processing is performed, the concrete structure 10 part of the first binary image 81 and the concrete structure 10 part of the second binary image 82 are 0 by the logical product operation 0∧0=0. The logic value of is maintained, and the foreign matter (F) part of the first binary image 81 and the foreign matter (F) part of the second binary image 82 have a logical value of 0 by the logical product operation 0∧1=0. is given, and the logical value of 1 is maintained in the crack (C) portion of the first binary image 81 and the crack (C) portion of the second binary image 82 by the logical product operation 1∧1=1. .

As a result, only the crack (C) portion is displayed in the difference image 90 that is finally generated through the above-described binarization and difference processing, and the foreign matter (F) portion is not displayed.

Meanwhile, the image processor 50 can perform additional processing, such as separately storing the difference image 90 in a storage medium within the image processor 50 or outputting a warning sound when a crack (C) occurs in the difference image 90. there is.

The description of the presented embodiments is provided to enable any person skilled in the art to use or practice the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the scope of the invention. Thus, the present invention is not limited to the embodiments presented herein, but is to be construed in the broadest scope consistent with the principles and novel features presented herein.

10: Structure
20: Unmanned aerial vehicle
30: Laser scanner
40: Camera
41: 1st light
42: 2nd lighting
45: controller
50: image processor
71: 1st video
72: Second video
81: first binary image
82: Second binary image
90: difference image

Claims (3)

First and second lights that are mounted on the unmanned aerial vehicle and point to the structure to be inspected and emit visible light of different wavelengths;
A laser scanner that detects surface shape information of the structure by radiating laser light to the structure being inspected;
A camera mounted on the unmanned aerial vehicle to photograph the structure;
A controller mounted on the unmanned aerial vehicle to control a camera, first light, and second light;
An image processor that inspects defects occurring in the structure by processing the first image taken when the first light emits and the second image taken when the second light emits at the same inspection point.
Concrete structure crack inspection system using a laser scanner and unmanned aerial vehicle. According to clause 1,
The image processor is an information device with a built-in memory device and is connected to the laser scanner and controller to store the surface shape information of the structure and the image information captured by the camera in the memory device, and the image information captured when the first light is emitted at the same inspection point is stored in the memory device. The first binary image and the second binary image are generated by binarizing the first image and the second image taken when the second light is emitted, and the difference image is generated by differentiating the first binary image and the second binary image. to do
Concrete structure crack inspection system using a laser scanner and unmanned aerial vehicle. According to clause 2,
The image processor assigns logical values of 1 and 0 to pixels below the brightness average for all pixels and pixels above the brightness average, respectively, to generate a first binary image and a second binary image from the first image and the second image, respectively. characterized by
Concrete structure crack inspection system using a laser scanner and unmanned aerial vehicle.