JP2005172683A - Method of determining kind of defect by infrared method in concrete check system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a statistical defect determination method for determining a defect in a concrete structure by a statistical analytical method for a mode, a standard deviation value and the like, based on a temperature distribution and a temperature change obtained from an infrared thermal image of the concrete structure picked up by infrared cameras. <P>SOLUTION: An initial temperature of a surface of the concrete structure is imaged by the first infrared camera, a change of an infrared energy quantity on the surface of the concrete structure after heated is imaged by the second infrared camera, the temperature distribution is prepared by subtracting a numeral data before heated from a numeral data after heated in every corresponding cell, the temperature distribution is divided further into a plurality of determination ranges by a vertical and lateral matrix system, the mode and the standard deviation value are calculated in every section of the temperature distribution divided into the determination ranges, and are compared with those of a part assumed preliminarily as a sound part to determine a corresponding kind of defect out of a cavity, a crack, a rock pocket and the like. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  In the present invention, the types of defects, such as cavities, cracks, and junkers, that are manifested or inherent in a concrete structure are detected by the infrared camera (or infrared sensor, the same shall apply hereinafter) of the thermographic device. The present invention relates to a statistical defect determination method for determining by a statistical analysis method such as a mode value and a standard deviation value from a temperature difference distribution obtained from an infrared thermal image obtained by imaging a change.

Traditionally, regular periodic inspections such as tunnel lining concrete were generally performed by visual inspection and hammering inspection. However, recently, research and development of a concrete inspection system technology that identifies and determines surface defects and internal defects by analyzing the temperature distribution image of the surface of a concrete structure taken with a high-definition camera or with an infrared camera of a thermography device. For example, it is disclosed in Patent Document 1 and the like.
Similarly, techniques for pre-predicting the presence / absence and possibility of defects by imaging with an infrared camera of a thermography apparatus are disclosed in the following Patent Documents 2, 3, and 4 and are known.

JP 2002-257744 A Japanese Patent Laid-Open No. 5-307013 Japanese Patent Laid-Open No. 9-311029 JP 2001-74678 A

  As described above, a technique for imaging the amount of infrared energy radiated from the surface of a concrete structure with an infrared camera of a thermography device is already known. However, there are various methods for processing the imaged temperature data, and no technology that can satisfy the defect type determination method for concrete structures has yet been found.

For example, in Patent Document 1, a high-definition camera device and an infrared camera of a thermography device are mounted as imaging devices (paragraph numbers [0052] and [0053]), and an internal cavity and surface of a concrete structure. Regarding the evaluation of defects and the like, it is described that the output result of the electromagnetic wave radar is superposed on the temperature distribution by infrared rays (paragraph numbers [0076] to [0079]).
Japanese Patent Application Laid-Open No. H10-228561 discloses a technique for capturing infrared image data and visible image data, obtaining contour images for the two types of data, and comparing and displaying the obtained two contour image data.

  In Patent Document 3, infrared rays emitted from a concrete wall heated by a heater are picked up by an infrared camera, and the picked-up temperature distribution image is analyzed by an image processing device. It is described that the portion is determined to be normal (paragraph number [0016]).

Patent Document 4 discloses a technique for heating a tunnel inner wall with far infrared rays, measuring a temperature deviation with an infrared camera immediately after heating, measuring a normal portion and a cavity portion of the inner wall, and predicting the possibility of peeling in advance. It is disclosed.
As described above, the conventional technology images the change in the amount of infrared energy emitted from the surface of a concrete structure by an infrared camera of a high-vision camera device, particularly a thermography device, and calculates the temperature distribution on the surface of the concrete structure. Although it is the content which visualizes and pinpoints a defect location, some omissions are recognized.

  That is, the inspector determines the high temperature part from the visualized temperature distribution on the surface of the concrete structure, and determines whether or not the location is dangerous. This series of operations not only requires a lot of labor for the operator, but also makes it very easy for inspection errors to occur due to human error. Moreover, it is very difficult even for a skilled person to determine the type of defect such as what kind of defect the high-temperature part is, that is, whether it is a cavity, crack, or jumper. .

  An object of the present invention is to analyze a temperature difference distribution obtained from an infrared thermal image of a surface of a concrete structure imaged from an infrared camera of a thermography apparatus by a statistical method, and to efficiently identify a defect location and the type of the defect. The object is to provide a method for determining with high accuracy.

As means for solving the above-mentioned problems, the defect type determination method by the infrared method of the concrete inspection system according to the invention described in claim 1,
The surface of the concrete structure is heated, the change in the amount of infrared energy (temperature distribution) emitted from the surface of the concrete structure after heating is imaged with an infrared camera as temperature data, and the temperature difference obtained from the infrared thermal image It is a method of identifying the type of defects such as cavities, cracks, junkers etc. by statistical analysis methods such as mode value and standard deviation value,
The initial temperature of the surface of the concrete structure is imaged by the first infrared camera, the surface of the same concrete structure is heated immediately after the measurement, and the infrared energy radiated from the surface of the concrete structure by the second infrared camera after the heating Imaging the change in quantity;
Infrared images before and after heating at the same position imaged by the first and second infrared cameras are divided into vertical and horizontal matrix methods, and numerical data for each square is calculated and filled, and from the numerical data after heating before heating Subtracting the numerical data of each of the corresponding squares to create a temperature difference distribution, further dividing the temperature difference distribution into a plurality of determination ranges by a vertical and horizontal matrix method,
Calculate at least the mode value and standard deviation value for each temperature difference distribution section divided into the judgment range, and compare with the values that are considered to be healthy parts in advance, and any defect types such as cavities, cracks, and jumpers. And the step of determining whether or not.

According to the defect type determination method by the infrared method of the concrete inspection system according to the invention described in claim 1,
The initial temperature of the surface of the concrete structure before heating is imaged with the first infrared camera, and the change in the amount of infrared energy emitted from the surface of the concrete structure after heating is further imaged with the second infrared camera. The temperature difference distribution is created from the infrared thermal images acquired from the first and second infrared cameras, and the mode value and the standard deviation value are calculated and compared with values preliminarily regarded as healthy portions. This makes it possible to reliably determine which type of defect is a cavity, a crack, a jumper, or the like. Therefore, anyone can easily and efficiently determine the defect type with high accuracy without being influenced by the skill of the inspector.

  Below, with reference to drawings, the defect type determination method by the infrared method of the concrete inspection system which concerns on the invention described in Claim 1 is demonstrated.

  FIG. 1 is a diagram schematically showing a concrete inspection system 1. The concrete inspection system 1 includes an inspection traveling vehicle 2 and an image analysis device 3 that receives, analyzes, and determines each data.

  As shown in FIG. 2, the inspection traveling vehicle 2 has a self-propelled ability capable of speed control and a steering mechanism, or a central portion on one side surface of a vehicle body 20 of a vehicle traveling on a track. For example, a panel heater 21 as a heating means is installed so as to face the concrete wall of the tunnel to be inspected. An infrared thermography device 22 for imaging a change (temperature change) of the amount of infrared energy radiated from the surface of the concrete structure immediately after being heated by the panel heater 21, and an encoder (as a means for measuring position information of the inspection position) It is configured as a so-called infrared measurement vehicle equipped with necessary equipment such as a position measuring device such as a rotary rangefinder and a laser displacement meter.

  In particular, a first infrared camera 23 for imaging the initial temperature of the surface of the concrete structure before heating is installed on one side of the machine base 24 at a position ahead of the position of the panel heater 21 in the traveling direction of the vehicle. ing. Then, a change (temperature change) in the amount of infrared energy radiated from the surface of the concrete structure immediately after heating is imaged at a position behind the panel heater 21 on the same vehicle body 20 in the traveling direction of the vehicle. A second infrared camera 25 is installed on the machine base 26 with the same angle of view as the first infrared camera 23. Furthermore, on the same machine base 26, it is possible to photograph and inspect defects exposed on the surface of the concrete structure, such as cracks that appear on the surface of the concrete structure, with the same angle of view as the second infrared camera 25. A high-definition camera 27 is also installed. Of course, the configuration is not limited to this. For example, two infrared cameras 23 and 25 can be installed as a set so that wide-angle imaging can be performed.

The image analysis device 3 includes an input device 4 composed of a keyboard, a mouse and an interface for capturing captured images, an output device 5 composed of a monitor and a printer, a central processing unit 6 composed mainly of a CPU, a hard disk, The storage device 7 includes a writable storage medium such as a magnetic disk and a drive device.
Therefore, the image analysis apparatus 3 is a so-called stand-alone personal computer, and not only a custom-made computer but also a general personal computer or a general-purpose computer is preferably used. As the central processing unit 6, an operating system such as Windows (registered trademark) 2000 and me of Microsoft Corporation is preferably used.

  The central processing unit 6 captures the captured infrared thermal image or converts it into numerical data, an image processing unit that performs operations such as temperature difference distribution, and the like. It comprises a comparison / determination unit that compares and determines the type of defect. The storage device 7 records and stores data such as all captured and captured moving image data, infrared thermal image data, all captured still image data, temperature difference distribution data, and defect type list data.

FIG. 3 shows a series of flowcharts of the defect type determination method by the infrared method according to the present invention, which is performed using the concrete inspection system 1 of FIG. Hereinafter, it demonstrates along the flowchart of FIG.
First, Steps A to C are for acquiring data of a concrete structure necessary for defect type determination, and are contents of steps performed in one traveling of the inspection traveling vehicle 2.
In step A, as the traveling vehicle 2 for inspection shown in FIG. 2 travels, the infrared cameras 23 and 23 mounted on the front side in the traveling direction image the initial temperature of the surface of the concrete structure.
Immediately in step B, the panel heater 21 mounted at the intermediate position of the inspection traveling vehicle 2 heats the surface of the concrete structure.
Thereafter, in Step C, the change in the amount of infrared energy emitted from the surface of the heated concrete structure is imaged by the second infrared cameras 25 and 25 mounted on the rear side in the traveling direction of the inspection traveling vehicle 2.

In step D, a temperature difference distribution is created based on the infrared thermal image (still image) at the same position acquired by the first and second infrared cameras 23 and 25 in steps A to C.
Specifically, the image processing unit of the central processing unit 6 first converts the infrared thermal image 70 after heating into numerical data with reference to the color module 71 or the temperature module 72 as shown in FIG. 4A. As shown in 4B, the temperature data 73 after heating is created by filling the numerical data in each cell divided into vertical and horizontal matrix systems. And the pre-heating temperature distribution 74 as shown to FIG. 4C is created with the same processing method.
Then, the temperature difference distribution 75 as shown in FIG. 5 is created by subtracting the numerical data before heating from the numerical data after heating for each corresponding square. 4B and 4C, for example, the temperature after heating shown in FIG. 4B is 22 ° C., and the temperature before heating shown in FIG. 4B is 20 ° C. The temperature is calculated as 1.0 ° C. Incidentally, in the illustrated example, it is the temperature difference for each basket that divides the imaging target into a size of 50 cm square.

  In step E, the temperature difference distribution of FIG. 4 is further divided into a plurality of determination ranges by a vertical and horizontal matrix system as shown in FIG. 6 by the arithmetic processing unit of the central processing unit 6. This operation is preprocessing for determining the type of defect for each section. In the example shown in the figure, a total of 9 cm, 3 cm in length and 3 mm in width, is set as one section, for example, a section in the upper left corner is set as section A.

  Next, in step F, a mode value and a standard deviation value for each section of the temperature difference distribution 75 are calculated. First, for example, in section A shown in FIG. 6, the arithmetic processing unit of the central processing unit 6 totals the number of temperature distributions to create a temperature distribution totaling table as shown in FIG. 7A. In short, the temperature difference of 1.0 ° C is 2 pieces, the temperature difference of 1.1 ° C is 4 pieces, the temperature difference of 1.2 ° C is 2 pieces, and the temperature difference of 1.3 ° C is 1 piece. It is a result. The tabulation table of FIG. 7A can be further created in the temperature distribution graph of FIG. 7B. According to FIG. 7B, it is obvious that the mode value of the temperature distribution is 1.1 ° C. This series of processing is performed for each section. Further, a standard deviation value (scattering or variation) for each section is also calculated based on the temperature distribution summary table. These are operations by so-called statistical methods.

In step G, the defect location and the defect type are specified by the comparison / determination unit of the central processing unit 6 from the mode value and standard deviation value for each section calculated in step F.
As a method for determining the type of defect based on the mode value, for example, as shown in FIG. 8, the mode value of a healthy part and a mode value indicating a cavity, a crack, and a jumper previously derived by a test defect structure or the like. The defect location or the type of defect is determined for each section. That is, it is determined by comparing and examining the mode value indicating the type of each degradation and the mode value calculated for each category. The reason why the mode (temperature difference) between the cavity and the jumper is high is that an air layer is structurally present, so that when heated, the degree of heat diffusion is lower than the soundness and the temperature is unlikely to decrease. In addition, a phenomenon occurs in which the temperature at the jumper portion is less likely to decrease than at the hollow portion. Therefore, the comparison with each mode value surely determines the defect location and the defect type.

  The method for determining the type of defect in the standard deviation value is, for example, as shown in FIG. 9, with reference to the standard deviation value of the healthy part derived in advance and the standard deviation value indicating the cavity, crack, and jumper. The defect location and the type of defect are determined every time. That is, it is determined by comparing and examining the standard deviation value indicating the type of each degradation and the standard deviation value calculated for each category. When compared with the graph for determining the defect type in FIG. The standard deviation value means that the higher the value is, the larger the dispersion of the temperature distribution is, and the smaller the value is, the smaller the dispersion of the temperature distribution is.

  In step H, the result of the defect type determined in step G is created as a defect type list 91 as shown in FIG. 10 and output and displayed on the monitor or printer of the output device 5 (claim 2). invention). The defect type list 91 displays items such as the mesh number indicating the address of the infrared thermal image, the X and Y coordinate positions indicating the location of the defect location, and the defect type. Further, as shown in FIG. 10B, it is possible to display the type of defect on the temperature difference distribution 75 in which the determination range is divided as shown in FIG.

  Although the embodiments have been described with reference to the drawings, the present invention is not limited to the illustrated examples, and includes a range of design changes and application variations that are usually made by those skilled in the art without departing from the technical idea thereof. I will mention it just in case. For example, the type of defect can be determined not only by the method using the mode value and standard deviation value described above but also by other statistical methods.

It is the figure which showed the outline of the concrete inspection system which concerns on this invention. It is a front view of the traveling vehicle for inspection which images the surface of a concrete structure. It is a flowchart of the defect kind determination method by the infrared method of the concrete inspection system which concerns on this invention. A is a diagram showing an infrared thermal image. B is a diagram showing a temperature distribution after heating. C is a diagram showing a temperature distribution before heating. It is the figure which showed temperature difference distribution. It is the figure which showed an example which divided temperature difference distribution into the judgment range. A is the figure which showed the temperature analysis totalization table of the division A of FIG. B is a graph of the temperature distribution summary table. It is the figure which showed the basic value which determines the kind of defect by mode value. It is the figure which showed the basic value which determines the kind of defect by a standard deviation value. A is a figure which shows an example of a defect kind location list. B is a diagram showing an example in which the type of defect is displayed in the division of the determination range.

Explanation of symbols

23, 25 Infrared camera 21 Panel heater

Claims (1)

The surface of the concrete structure is heated, the change in the amount of infrared energy (temperature distribution) emitted from the surface of the concrete structure after heating is imaged with an infrared camera as temperature data, and the temperature difference obtained from the infrared thermal image It is a method of identifying the type of defects such as cavities, cracks, junkers etc. by statistical analysis methods such as mode value and standard deviation value,
Imaging the initial temperature of the surface of the concrete structure with the first infrared camera, heating the surface of the same concrete structure immediately after the measurement, and infrared energy radiated from the surface of the concrete structure by the second infrared camera after the heating Imaging the change in quantity;
Infrared images before and after heating at the same position imaged by the first and second infrared cameras are divided into vertical and horizontal matrix methods, and numerical data for each square is calculated and filled, and from the numerical data after heating before heating Subtracting the numerical data of each of the corresponding squares to create a temperature difference distribution, further dividing the temperature difference distribution into a plurality of determination ranges by a vertical and horizontal matrix method,
Calculate at least the mode value and standard deviation value for each temperature difference distribution divided into the judgment range, and compare with the value that is considered to be a healthy part in advance, and it is any defect type such as cavity, crack, junker, etc. A method for determining a defect type by an infrared method of a concrete inspection system.

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