WO2022080610A1 - System for determining thermally abnormal part of outer wall of building by using thermal image and real image, and method therefor - Google Patents

System for determining thermally abnormal part of outer wall of building by using thermal image and real image, and method therefor Download PDF

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WO2022080610A1
WO2022080610A1 PCT/KR2021/004387 KR2021004387W WO2022080610A1 WO 2022080610 A1 WO2022080610 A1 WO 2022080610A1 KR 2021004387 W KR2021004387 W KR 2021004387W WO 2022080610 A1 WO2022080610 A1 WO 2022080610A1
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thermal
building
real image
wall
temperature distribution
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PCT/KR2021/004387
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French (fr)
Korean (ko)
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김창민
박관용
박창영
장향인
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(주)미래환경플랜건축사사무소
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Publication of WO2022080610A1 publication Critical patent/WO2022080610A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N25/00—Investigating or analyzing materials by the use of thermal means
    • G01N25/72—Investigating presence of flaws
    • E—FIXED CONSTRUCTIONS
    • E04—BUILDING
    • E04B—GENERAL BUILDING CONSTRUCTIONS; WALLS, e.g. PARTITIONS; ROOFS; FLOORS; CEILINGS; INSULATION OR OTHER PROTECTION OF BUILDINGS
    • E04B1/00—Constructions in general; Structures which are not restricted either to walls, e.g. partitions, or floors or ceilings or roofs
    • E04B1/62—Insulation or other protection; Elements or use of specified material therefor
    • E04B1/74—Heat, sound or noise insulation, absorption, or reflection; Other building methods affording favourable thermal or acoustical conditions, e.g. accumulating of heat within walls
    • E04B1/76—Heat, sound or noise insulation, absorption, or reflection; Other building methods affording favourable thermal or acoustical conditions, e.g. accumulating of heat within walls specifically with respect to heat only
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/60—Radiation pyrometry, e.g. infrared or optical thermometry using determination of colour temperature
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J2005/0077—Imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
    • G01K2213/00—Temperature mapping

Definitions

  • the present invention relates to a system and method for determining a thermal anomaly of a building, and more particularly, to a system and a method for determining a thermal anomaly of an exterior wall of a building using a thermal image and a real image.
  • thermal imaging cameras are mainly used to find these thermal anomalies, it is not easy to find an exact thermal anomaly because various components such as windows, doors, vehicles, and outdoor units are arranged on the exterior wall of the building.
  • Another object of the present invention is to provide a method for determining a thermal abnormality portion of an exterior wall of a building using a thermal image and a real image.
  • a system for determining a portion of a thermal abnormality on an exterior wall of a building using a thermal image and a real image includes: a real image camera module for generating a real image by photographing the exterior wall of the building; a thermal imaging camera module for generating a thermal image by photographing the exterior wall of the building; It may be configured to include an exterior wall temperature distribution identification module configured to determine an exterior wall temperature distribution of the exterior wall of the building using a real image generated by the real image camera module and a thermal image generated by the thermal imaging camera module.
  • thermo abnormality region extraction module for extracting a thermal abnormality region using the external wall temperature distribution identified by the external wall temperature distribution identification module.
  • a method for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image includes: generating a real image by a real image camera module photographing an exterior wall of the building; generating, by a thermal imaging camera module, a thermal image by photographing the exterior wall of the building;
  • the external wall temperature distribution determining module may be configured to include the step of identifying the external wall temperature distribution of the building outer wall using the real image generated by the real image camera module and the thermal image generated by the thermal image camera module.
  • the thermal abnormality site extraction module may be configured to further include the step of extracting the thermal abnormality site using the outer wall temperature distribution identified by the outer wall temperature distribution determining module.
  • the system and method for determining the thermal abnormality of the exterior wall of the building using the above-described thermal image and the real image it is configured to identify the temperature distribution by dividing the region of the exterior wall of the building using the real image and the thermal image, so that the window of the exterior wall of the building.
  • FIG. 1 is a schematic diagram of a thermal abnormality determination process of an exterior wall of a building according to the present invention.
  • FIG. 2 is a block diagram of a system for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image according to an embodiment of the present invention.
  • FIG. 3 is an exemplary diagram of a result of classification of a real image according to an embodiment of the present invention.
  • FIG. 4 is a graph illustrating a temperature distribution of a thermal image and setting a critical temperature according to an embodiment of the present invention.
  • FIG 5 is an exemplary view of an image obtained by extracting a thermal abnormality portion of an exterior wall of a building according to an embodiment of the present invention.
  • FIG. 6 is a flowchart of a method for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image according to an embodiment of the present invention.
  • first, second, A, and B may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component. and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.
  • FIG. 1 is a schematic diagram of a thermal abnormality determination process of an exterior wall of a building according to the present invention.
  • a real image and a thermal image are acquired for the same outer wall of a building. Then, in the real image, each area is divided by a wall, a window, other objects that cover the exterior wall of the building, and the background. It is configured to grasp the temperature distribution by the thermal image for the area divided by the wall in the real image, and to extract the defective thermal abnormality from the temperature distribution of the wall area.
  • FIG. 2 is a block diagram of a system for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image according to an embodiment of the present invention.
  • FIG. 3 is an exemplary diagram of a result of classification of a real image according to an embodiment of the present invention
  • FIG. 4 is a graph relating to a temperature distribution and a critical temperature setting of a thermal image according to an embodiment of the present invention
  • FIG. 5 is a diagram of the present invention It is an exemplary view of an image obtained by extracting a thermal abnormality portion of an outer wall of a building according to an embodiment of the present invention.
  • the system 100 for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image includes a real image camera module 101, a thermal image camera module 102, and a real image.
  • the real image camera module 101 may be configured to generate a real image by photographing an exterior wall of a building.
  • the thermal imaging camera module 102 may be configured to generate a thermal image by photographing an exterior wall of a building.
  • the real image database 103 may be configured such that a real image of the outer wall of the building is stored in advance.
  • the region classification module 104 may be configured to separate the region of the real image generated by the real image camera module 101 into a wall, a window, other objects covering the exterior wall of the building, and a background, respectively.
  • the region classification module 104 may be configured to first perform learning for region classification with reference to a real image previously stored in the real image database 103 using a convolutional neural network model.
  • the area division module 104 is configured to separate the area of the building exterior wall from the real image generated by the real image camera module 102 into walls, windows, other objects (vehicles, outdoor units, etc.) covering the exterior wall of the building, and the background, respectively. can be
  • the region mask assignment module 105 may be configured to assign and display a region mask including index information to each region divided by the region classification module 104 .
  • the index information may be set to a wall, a window, other objects covering the exterior wall of a building, and a background, respectively.
  • FIG. 3 shows an image semantically divided into such an exterior wall of a building, in which a green area is a wall, an orange area is a window, and a yellow area is other areas.
  • the scaling module 106 applies an area interpolation algorithm to adjust the size of the real image generated by the real image camera module 101 to be the same as the size of the thermal image generated by the thermal image camera module 102 to contrast with each other. can be
  • the scaling module 106 applies an area interpolation algorithm to minimize the error when the real image is reduced to the size of the thermal image.
  • the external wall temperature distribution determining module 107 may be configured to grasp the temperature distribution of the area divided by the wall by the area mask in the contrast result thermal image of the scaling module 106 .
  • the external wall temperature distribution identification module 107 may be configured to remove the background temperature distribution from the thermal image and determine the temperature distribution of the exterior wall of the building.
  • the external wall temperature distribution identification module 107 may be configured to generate a temperature histogram from the thermal image, and apply a kernel density estimation algorithm to the generated temperature histogram to estimate the temperature distribution.
  • the automatic threshold temperature setting module 108 may be configured to automatically set a threshold temperature for classifying a normal region and an abnormal region by analyzing the temperature distribution detected by the external wall temperature distribution identification module 107 .
  • the threshold temperature automatic setting module 108 may be configured to include a maximum limit calculation unit 108a, a maximum point selection unit 108b and a defect threshold temperature selection unit 108c.
  • a maximum limit calculation unit 108a a maximum point selection unit 108b
  • a defect threshold temperature selection unit 108c a defect threshold temperature selection unit 108c
  • the maximum value limit calculation unit 108a calculates the maximum value of the temperature distribution estimated by the outer wall temperature distribution determining module 107 according to Equation 1 below. from the maximum limit can be configured to calculate
  • the maximum point selection unit 108b is the maximum value limit
  • the two local maxima with the highest frequency of the temperature distribution among the local maxima of the larger temperature distribution. may be configured to select
  • the defect critical temperature selection unit 108c is a defect critical temperature for determining a thermal abnormality at a temperature having the lowest frequency of temperature distribution between two maximum points according to Equation 2 below. It can be configured to select
  • the thermal anomaly extraction module 109 may be configured to extract a thermal anomaly from the wall using the threshold temperature automatically set in the automatic threshold temperature setting module 109 .
  • the thermal anomaly extraction module 109 has a maximum limit If there is only one larger maximal point, it is judged that there is no thermal anomaly in the thermal image, and the limit of the maximal value is Fault if two or more larger maximums exist Maximum points above the critical temperature Areas with the following temperature distribution It may be configured to be determined as a thermal abnormality site.
  • FIG. 5 shows that a defect region is found by extracting two maximum points from each of the wall region 1 and the wall region 2 in the real image and the thermal image.
  • FIG. 6 is a flowchart of a method for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image according to an embodiment of the present invention.
  • the real image camera module 101 creates a real image by photographing the exterior wall of the building ( S101 ).
  • the thermal imaging camera module 102 generates a thermal image by photographing the exterior wall of the building ( S102 ).
  • the external wall temperature distribution identification module 107 uses the real image generated by the real image camera module 101 and the thermal image generated by the thermal image camera module 102 to determine the external wall temperature distribution of the building exterior wall do (S103).
  • the thermal anomaly extraction module 109 extracts a thermal anomaly using the outer wall temperature distribution identified by the outer wall temperature distribution determining module 107 ( S104 ).
  • the present invention relates to a system and method for determining a thermal abnormality of a building, and can be applied to the design, construction, and maintenance markets of buildings.

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Abstract

Disclosed are a system for determining a thermally abnormal part of the outer wall of a building by using a thermal image and a real image, and a method therefor. The system comprises: a real image camera module for generating a real image by photographing the outer wall of a building; a thermal image camera module for generating a thermal image by photographing the outer wall of the building; an outer wall temperature distribution acquisition module for acquiring the outer wall temperature distribution of the outer wall of the building by using the real image generated by the real image camera module and the thermal image generated by the thermal image camera module; and a thermally abnormal part extraction module for extracting a thermally abnormal part by using the outer wall temperature distribution acquired by the outer wall temperature distribution acquisition module. According to the system for determining a thermally abnormal part of the outer wall of a building by using a thermal image and a real image, and the method therefor, which have been described above, a real image and a thermal image are used to identify regions of the outer wall of the building so that a temperature distribution is acquired, and thus a thermally abnormal part can be accurately found regardless of the presence of various components such as windows of the outer wall of the building, doors, vehicles, and outdoor air conditioner units.

Description

열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템과 그 방법System and method for determining thermal anomalies of exterior walls of buildings using thermal and real images
본 발명은 건물의 열적 이상 부위 판단 시스템과 그 방법에 관한 것으로서, 구체적으로는 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템과 그 방법에 관한 것이다.The present invention relates to a system and method for determining a thermal anomaly of a building, and more particularly, to a system and a method for determining a thermal anomaly of an exterior wall of a building using a thermal image and a real image.
건물 외벽에 단열이 잘 안되거나 열 손실이 발생하는 경우 그 열적 이상 부위를 통해 에너지 손실과 재실 쾌적성의 저하를 유발하게 된다.In the case of poor insulation or heat loss on the outer wall of the building, energy loss and deterioration of occupancy comfort are caused through the thermal abnormality.
이러한 열적 이상 부위를 찾아내기 위해 주로 열화상 카메라를 이용하고 있으나, 건물 외벽에는 창, 문, 차량, 실외기 등의 다양한 구성들이 배치되기 때문에 정확한 열적 이상 부위를 찾는 것이 쉽지 않다.Although thermal imaging cameras are mainly used to find these thermal anomalies, it is not easy to find an exact thermal anomaly because various components such as windows, doors, vehicles, and outdoor units are arranged on the exterior wall of the building.
이러한 구성들은 동일한 환경에서도 서로 다른 온도 분포를 갖기 때문에 열적 이상 부위가 아닌 부위에 열적 이상이 발생한 것으로 판단하기도 한다.Since these components have different temperature distributions even in the same environment, it is sometimes judged that a thermal abnormality occurs in a non-thermal abnormal region.
이에, 열화상을 통해 정확한 열적 이상 부위를 찾아낼 수 있는 방안이 요구 된다.Accordingly, there is a need for a method capable of finding an accurate thermal anomaly through thermal imaging.
본 발명의 목적은 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템을 제공하는 데 있다.SUMMARY OF THE INVENTION It is an object of the present invention to provide a system for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image.
본 발명의 다른 목적은 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 방법을 제공하는 데 있다.Another object of the present invention is to provide a method for determining a thermal abnormality portion of an exterior wall of a building using a thermal image and a real image.
상술한 본 발명의 목적에 따른 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템은, 건물 외벽을 촬영하여 실화상을 생성하는 실화상 카메라 모듈; 상기 건물 외벽을 촬영하여 열화상을 생성하는 열화상 카메라 모듈; 상기 실화상 카메라 모듈에 의해 생성된 실화상 및 상기 열화상 카메라 모듈에 의해 생성된 열화상을 이용하여 상기 건물 외벽의 외벽 온도 분포를 파악하는 외벽 온도 분포 파악 모듈을 포함하도록 구성될 수 있다.According to an aspect of the present invention, a system for determining a portion of a thermal abnormality on an exterior wall of a building using a thermal image and a real image includes: a real image camera module for generating a real image by photographing the exterior wall of the building; a thermal imaging camera module for generating a thermal image by photographing the exterior wall of the building; It may be configured to include an exterior wall temperature distribution identification module configured to determine an exterior wall temperature distribution of the exterior wall of the building using a real image generated by the real image camera module and a thermal image generated by the thermal imaging camera module.
여기서, 상기 외벽 온도 분포 파악 모듈에 의해 파악된 외벽 온도 분포를 이용하여 열적 이상 부위를 추출하는 열적 이상 부위 추출 모듈을 더 포함하도록 구성될 수 있다.Here, it may be configured to further include a thermal abnormality region extraction module for extracting a thermal abnormality region using the external wall temperature distribution identified by the external wall temperature distribution identification module.
상술한 본 발명의 목적에 따른 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 방법은, 실화상 카메라 모듈이 건물 외벽을 촬영하여 실화상을 생성하는 단계; 열화상 카메라 모듈이 상기 건물 외벽을 촬영하여 열화상을 생성하는 단계; 외벽 온도 분포 파악 모듈이 상기 실화상 카메라 모듈에 의해 생성된 실화상 및 상기 열화상 카메라 모듈에 의해 생성된 열화상을 이용하여 상기 건물 외벽의 외벽 온도 분포를 파악하는 단계를 포함하도록 구성될 수 있다.According to the object of the present invention, a method for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image includes: generating a real image by a real image camera module photographing an exterior wall of the building; generating, by a thermal imaging camera module, a thermal image by photographing the exterior wall of the building; The external wall temperature distribution determining module may be configured to include the step of identifying the external wall temperature distribution of the building outer wall using the real image generated by the real image camera module and the thermal image generated by the thermal image camera module. .
여기서, 열적 이상 부위 추출 모듈이 상기 외벽 온도 분포 파악 모듈에 의해 파악된 외벽 온도 분포를 이용하여 열적 이상 부위를 추출하는 단계를 더 포함하도록 구성될 수 있다.Here, the thermal abnormality site extraction module may be configured to further include the step of extracting the thermal abnormality site using the outer wall temperature distribution identified by the outer wall temperature distribution determining module.
상술한 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템과 그 방법에 의하면, 실화상과 열화상을 이용하여 건물 외벽의 영역을 구분하여 온도 분포를 파악하도록 구성됨으로써, 건물 외벽의 창, 문, 차량, 실외기 등의 다양한 구성들의 존재에도 불구하고 정확한 열적 이상 부위를 찾아낼 수 있는 효과가 있다.According to the system and method for determining the thermal abnormality of the exterior wall of the building using the above-described thermal image and the real image, it is configured to identify the temperature distribution by dividing the region of the exterior wall of the building using the real image and the thermal image, so that the window of the exterior wall of the building In spite of the existence of various components such as , doors, vehicles, outdoor units, etc., there is an effect of accurately detecting thermal abnormalities.
도 1은 본 발명에 따른 건물 외벽의 열적 이상 판단 프로세스의 모식도이다.1 is a schematic diagram of a thermal abnormality determination process of an exterior wall of a building according to the present invention.
도 2는 본 발명의 일 실시예에 따른 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템의 블록 구성도이다.2 is a block diagram of a system for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image according to an embodiment of the present invention.
도 3은 본 발명의 일 실시예에 따른 실화상의 구분 결과의 예시도이다.3 is an exemplary diagram of a result of classification of a real image according to an embodiment of the present invention.
도 4는 본 발명의 일 실시예에 따른 열화상의 온도 분포 및 임계 온도 설정에 관한 그래프이다.4 is a graph illustrating a temperature distribution of a thermal image and setting a critical temperature according to an embodiment of the present invention.
도 5는 본 발명의 일 실시예에 따른 건물 외벽의 열적 이상 부위를 추출한 이미지의 예시도이다.5 is an exemplary view of an image obtained by extracting a thermal abnormality portion of an exterior wall of a building according to an embodiment of the present invention.
도 6은 본 발명의 일 실시예에 따른 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 방법의 흐름도이다.6 is a flowchart of a method for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image according to an embodiment of the present invention.
본 발명은 다양한 변경을 가할 수 있고 여러 가지 실시예를 가질 수 있는 바, 특정 실시 예들을 도면에 예시하고 발명을 실시하기 위한 구체적인 내용에 상세하게 설명하고자 한다. 그러나, 이는 본 발명을 특정한 실시 형태에 대해 한정하려는 것이 아니며, 본 발명의 사상 및 기술 범위에 포함되는 모든 변경, 균등물 내지 대체물을 포함하는 것으로 이해되어야 한다. 각 도면을 설명하면서 유사한 참조부호를 유사한 구성요소에 대해 사용하였다.Since the present invention can have various changes and can have various embodiments, specific embodiments are illustrated in the drawings and will be described in detail in the detailed content for carrying out the invention. However, this is not intended to limit the present invention to specific embodiments, and it should be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention. In describing each figure, like reference numerals have been used for like elements.
제1, 제2, A, B 등의 용어는 다양한 구성요소들을 설명하는데 사용될 수 있지만, 상기 구성요소들은 상기 용어들에 의해 한정되어서는 안 된다. 상기 용어들은 하나의 구성요소를 다른 구성요소로부터 구별하는 목적으로만 사용된다. 예를 들어, 본 발명의 권리 범위를 벗어나지 않으면서 제1 구성요소는 제2 구성요소로 명명될 수 있고, 유사하게 제2 구성요소도 제1 구성요소로 명명될 수 있다. 및/또는 이라는 용어는 복수의 관련된 기재된 항목들의 조합 또는 복수의 관련된 기재된 항목들 중의 어느 항목을 포함한다.Terms such as first, second, A, and B may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component. and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.
어떤 구성요소가 다른 구성요소에 "연결되어" 있다거나 "접속되어" 있다고 언급된 때에는, 그 다른 구성요소에 직접적으로 연결되어 있거나 또는 접속되어 있을 수도 있지만, 중간에 다른 구성요소가 존재할 수도 있다고 이해되어야 할 것이다. 반면에, 어떤 구성요소가 다른 구성요소에 "직접 연결되어" 있다거나 "직접 접속되어" 있다고 언급된 때에는, 중간에 다른 구성요소가 존재하지 않는 것으로 이해되어야 할 것이다.When an element is referred to as being “connected” or “connected” to another element, it is understood that it may be directly connected or connected to the other element, but other elements may exist in between. it should be On the other hand, when it is said that a certain element is "directly connected" or "directly connected" to another element, it should be understood that the other element does not exist in the middle.
본 출원에서 사용한 용어는 단지 특정한 실시예를 설명하기 위해 사용된 것으로, 본 발명을 한정하려는 의도가 아니다. 단수의 표현은 문맥상 명백하게 다르게 뜻하지 않는 한, 복수의 표현을 포함한다. 본 출원에서, "포함하다" 또는 "가지다" 등의 용어는 명세서상에 기재된 특징, 숫자, 단계, 동작, 구성요소, 부품 또는 이들을 조합한 것이 존재함을 지정하려는 것이지, 하나 또는 그 이상의 다른 특징들이나 숫자, 단계, 동작, 구성요소, 부품 또는 이들을 조합한 것들의 존재 또는 부가 가능성을 미리 배제하지 않는 것으로 이해되어야 한다.The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as “comprise” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.
다르게 정의되지 않는 한, 기술적이거나 과학적인 용어를 포함해서 여기서 사용되는 모든 용어들은 본 발명이 속하는 기술 분야에서 통상의 지식을 가진 자에 의해 일반적으로 이해되는 것과 동일한 의미를 가지고 있다. 일반적으로 사용되는 사전에 정의되어 있는 것과 같은 용어들은 관련 기술의 문맥 상 가지는 의미와 일치하는 의미를 가지는 것으로 해석되어야 하며, 본 출원에서 명백하게 정의하지 않는 한, 이상적이거나 과도하게 형식적인 의미로 해석되지 않는다.Unless defined otherwise, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not
이하, 본 발명에 따른 바람직한 실시예를 첨부된 도면을 참조하여 상세하게 설명한다.Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings.
도 1은 본 발명에 따른 건물 외벽의 열적 이상 판단 프로세스의 모식도이다.1 is a schematic diagram of a thermal abnormality determination process of an exterior wall of a building according to the present invention.
도 1을 참조하면, 먼저 동일한 건물 외벽에 대해 실화상 및 열화상을 취득한다. 그리고 실화상에서 벽체, 창문, 건물 외벽을 가리는 기타 물체, 배경으로 각각 영역을 구분한다. 실화상에서 벽체로 구분된 영역에 대해 해당 열화상에 의한 온도 분포를 파악하고, 그 벽체 영역의 온도 분포로부터 하자가 있는 열적 이상 부위를 추출하도록 구성된다.Referring to FIG. 1 , first, a real image and a thermal image are acquired for the same outer wall of a building. Then, in the real image, each area is divided by a wall, a window, other objects that cover the exterior wall of the building, and the background. It is configured to grasp the temperature distribution by the thermal image for the area divided by the wall in the real image, and to extract the defective thermal abnormality from the temperature distribution of the wall area.
도 2는 본 발명의 일 실시예에 따른 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템의 블록 구성도이다. 그리고 도 3은 본 발명의 일 실시예에 따른 실화상의 구분 결과의 예시도이고, 도 4는 본 발명의 일 실시예에 따른 열화상의 온도 분포 및 임계 온도 설정에 관한 그래프이고, 도 5는 본 발명의 일 실시예에 따른 건물 외벽의 열적 이상 부위를 추출한 이미지의 예시도이다.2 is a block diagram of a system for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image according to an embodiment of the present invention. And FIG. 3 is an exemplary diagram of a result of classification of a real image according to an embodiment of the present invention, FIG. 4 is a graph relating to a temperature distribution and a critical temperature setting of a thermal image according to an embodiment of the present invention, and FIG. 5 is a diagram of the present invention It is an exemplary view of an image obtained by extracting a thermal abnormality portion of an outer wall of a building according to an embodiment of the present invention.
도 2를 참조하면, 본 발명의 일 실시예에 따른 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템(100)은 실화상 카메라 모듈(101), 열화상 카메라 모듈(102), 실화상 데이터베이스(103), 영역 구분 모듈(104), 영역 마스크 부여 모듈(105), 스케일링 모듈(106), 외벽 온도 분포 파악 모듈(107), 임계 온도 자동 설정 모듈(108), 열적 이상 부위 추출 모듈(109)을 포함하도록 구성될 수 있다.Referring to FIG. 2 , the system 100 for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image according to an embodiment of the present invention includes a real image camera module 101, a thermal image camera module 102, and a real image. Image database 103, region classification module 104, region mask application module 105, scaling module 106, external wall temperature distribution identification module 107, critical temperature automatic setting module 108, thermal abnormality region extraction module (109).
이하, 세부적인 구성에 대하여 설명한다.Hereinafter, a detailed configuration will be described.
실화상 카메라 모듈(101)은 건물 외벽을 촬영하여 실화상을 생성하도록 구성될 수 있다.The real image camera module 101 may be configured to generate a real image by photographing an exterior wall of a building.
열화상 카메라 모듈(102)은 건물 외벽을 촬영하여 열화상을 생성하도록 구성될 수 있다.The thermal imaging camera module 102 may be configured to generate a thermal image by photographing an exterior wall of a building.
실화상 데이터베이스(103)는 건물 외벽의 실화상이 미리 저장되도록 구성될 수 있다.The real image database 103 may be configured such that a real image of the outer wall of the building is stored in advance.
영역 구분 모듈(104)은 실화상 카메라 모듈(101)에 의해 생성된 실화상의 영역을 벽체, 창문, 건물 외벽을 가리는 기타 물체 및 배경으로 각각 구분하도록 구성될 수 있다.The region classification module 104 may be configured to separate the region of the real image generated by the real image camera module 101 into a wall, a window, other objects covering the exterior wall of the building, and a background, respectively.
구체적으로는 영역 구분 모듈(104)이 먼저 합성곱 신경망 모델을 이용하여 실화상 데이버테이스(103)에 미리 저장된 실화상을 참조하여 영역 구분을 위한 학습을 수행하도록 구성될 수 있다.Specifically, the region classification module 104 may be configured to first perform learning for region classification with reference to a real image previously stored in the real image database 103 using a convolutional neural network model.
그리고 영역 구분 모듈(104)이 실화상 카메라 모듈(102)에 의해 생성된 실화상으로부터 건물 외벽의 영역을 벽체, 창문, 건물 외벽을 가리는 기타 물체(차량, 실외기 등) 및 배경으로 각각 구분하도록 구성될 수 있다.And the area division module 104 is configured to separate the area of the building exterior wall from the real image generated by the real image camera module 102 into walls, windows, other objects (vehicles, outdoor units, etc.) covering the exterior wall of the building, and the background, respectively. can be
영역 마스크 부여 모듈(105)은 영역 구분 모듈(104)에 의해 구분된 각 영역에 대해 색인 정보를 포함하는 영역 마스크를 부여하여 표시하도록 구성될 수 있다. 색인 정보는 벽체, 창문, 건물 외벽을 가리는 기타 물체, 배경으로 각각 설정될 수 있다. 도 3은 이러한 건물 외벽을 의미론적으로 구분한 영상을 나타내고 있으며, 녹색 영역은 벽체이고, 주황색 영역은 창문 그리고 노란색 영역은 기타 영역으로 표시되어 있다.The region mask assignment module 105 may be configured to assign and display a region mask including index information to each region divided by the region classification module 104 . The index information may be set to a wall, a window, other objects covering the exterior wall of a building, and a background, respectively. FIG. 3 shows an image semantically divided into such an exterior wall of a building, in which a green area is a wall, an orange area is a window, and a yellow area is other areas.
스케일링 모듈(106)은 면적 보간 알고리즘을 적용하여 실화상 카메라 모듈(101)에 의해 생성된 실화상의 크기를 열화상 카메라 모듈(102)에 의해 생성된 열화상의 크기와 동일하게 조정하여 상호 대비하도록 구성될 수 있다.The scaling module 106 applies an area interpolation algorithm to adjust the size of the real image generated by the real image camera module 101 to be the same as the size of the thermal image generated by the thermal image camera module 102 to contrast with each other. can be
일반적으로 열화상의 크기가 실화상에 비해 작게 생성되기 때문에 실화상을 열화상의 크기로 축소할 때 그 오류를 최소화할 수 있도록 스케일링 모듈(106)에서 면적 보간 알고리즘을 적용한다.In general, since the size of the thermal image is generated smaller than that of the real image, the scaling module 106 applies an area interpolation algorithm to minimize the error when the real image is reduced to the size of the thermal image.
외벽 온도 분포 파악 모듈(107)은 스케일링 모듈(106)의 대비 결과 열화상에서 영역 마스크에 의해 벽체로 구분된 영역의 온도 분포를 파악하도록 구성될 수 있다.The external wall temperature distribution determining module 107 may be configured to grasp the temperature distribution of the area divided by the wall by the area mask in the contrast result thermal image of the scaling module 106 .
외벽 온도 분포 파악 모듈(107)은 열화상에서 배경의 온도 분포를 제거하고 건물 외벽의 온도 분포를 파악하도록 구성될 수 있다.The external wall temperature distribution identification module 107 may be configured to remove the background temperature distribution from the thermal image and determine the temperature distribution of the exterior wall of the building.
외벽 온도 분포 파악 모듈(107)은 열화상에서 온도 히스토그램을 생성하고, 생성된 온도 히스토그램에 대해 커널 밀도 추정 알고리즘을 적용하여 온도 분포를 추정하도록 구성될 수 있다.The external wall temperature distribution identification module 107 may be configured to generate a temperature histogram from the thermal image, and apply a kernel density estimation algorithm to the generated temperature histogram to estimate the temperature distribution.
임계 온도 자동 설정 모듈(108)은 외벽 온도 분포 파악 모듈(107)에서 파악된 온도 분포를 분석하여 정상 영역과 이상 영역을 구분하기 위한 임계 온도를 자동 설정하도록 구성될 수 있다.The automatic threshold temperature setting module 108 may be configured to automatically set a threshold temperature for classifying a normal region and an abnormal region by analyzing the temperature distribution detected by the external wall temperature distribution identification module 107 .
임계 온도 자동 설정 모듈(108)은 극대값 한계 계산부(108a), 극대점 선정부(108b) 및 하자 임계 온도 선정부(108c)를 포함하도록 구성될 수 있다. 이하, 세부적인 구성에 대하여 설명한다.The threshold temperature automatic setting module 108 may be configured to include a maximum limit calculation unit 108a, a maximum point selection unit 108b and a defect threshold temperature selection unit 108c. Hereinafter, a detailed configuration will be described.
먼저 극대값 한계 계산부(108a)는 하기 수학식 1에 따라 외벽 온도 분포 파악 모듈(107)에서 추정되는 온도 분포의 최대값
Figure PCTKR2021004387-appb-I000001
으로부터 극대값 한계
Figure PCTKR2021004387-appb-I000002
를 계산하도록 구성될 수 있다.First, the maximum value limit calculation unit 108a calculates the maximum value of the temperature distribution estimated by the outer wall temperature distribution determining module 107 according to Equation 1 below.
Figure PCTKR2021004387-appb-I000001
from the maximum limit
Figure PCTKR2021004387-appb-I000002
can be configured to calculate
Figure PCTKR2021004387-appb-M000001
Figure PCTKR2021004387-appb-M000001
여기서,
Figure PCTKR2021004387-appb-I000003
는 0.05로 설정될 수 있다.here,
Figure PCTKR2021004387-appb-I000003
may be set to 0.05.
그리고 극대점 선정부(108b)는 극대값 한계
Figure PCTKR2021004387-appb-I000004
보다 큰 온도 분포의 극대값 중에서 온도 분포의 빈도가 가장 큰 두 개의 극대점
Figure PCTKR2021004387-appb-I000005
을 선정하도록 구성될 수 있다.And the maximum point selection unit 108b is the maximum value limit
Figure PCTKR2021004387-appb-I000004
The two local maxima with the highest frequency of the temperature distribution among the local maxima of the larger temperature distribution.
Figure PCTKR2021004387-appb-I000005
may be configured to select
그리고 하자 임계 온도 선정부(108c)는 하기 수학식 2에 따라 두 개의 극대점 사이에서 온도 분포의 빈도가 가장 낮은 온도를 열적 이상 부위를 판단하기 위한 하자 임계 온도
Figure PCTKR2021004387-appb-I000006
로 선정하도록 구성될 수 있다.And, the defect critical temperature selection unit 108c is a defect critical temperature for determining a thermal abnormality at a temperature having the lowest frequency of temperature distribution between two maximum points according to Equation 2 below.
Figure PCTKR2021004387-appb-I000006
It can be configured to select
Figure PCTKR2021004387-appb-M000002
Figure PCTKR2021004387-appb-M000002
열적 이상 부위 추출 모듈(109)은 임계 온도 자동 설정 모듈(109)에서 자동 설정된 임계 온도를 이용하여 벽체 중 열적 이상 부위를 추출하도록 구성될 수 있다.The thermal anomaly extraction module 109 may be configured to extract a thermal anomaly from the wall using the threshold temperature automatically set in the automatic threshold temperature setting module 109 .
구체적으로는 열적 이상 부위 추출 모듈(109)은 극대값 한계
Figure PCTKR2021004387-appb-I000007
보다 큰 극대점이 하나만 존재하는 경우 열화상에 열적 이상 부위가 존재하지 않는 것으로 판단하며, 극대값 한계
Figure PCTKR2021004387-appb-I000008
보다 큰 극대점이 둘 이상 존재하는 경우 하자 임계 온도 이상 극대점
Figure PCTKR2021004387-appb-I000009
이하의 온도 분포를 갖는 부위를
Figure PCTKR2021004387-appb-I000010
열적 이상 부위로 판단하도록 구성될 수 있다.Specifically, the thermal anomaly extraction module 109 has a maximum limit
Figure PCTKR2021004387-appb-I000007
If there is only one larger maximal point, it is judged that there is no thermal anomaly in the thermal image, and the limit of the maximal value is
Figure PCTKR2021004387-appb-I000008
Fault if two or more larger maximums exist Maximum points above the critical temperature
Figure PCTKR2021004387-appb-I000009
Areas with the following temperature distribution
Figure PCTKR2021004387-appb-I000010
It may be configured to be determined as a thermal abnormality site.
도 5에서는 실화상 및 열화상에서 벽 영역 1과 벽 영역 2에서 극대점을 각각 2개씩 추출하여 하자 영역을 찾아내는 것을 나타내고 있다.FIG. 5 shows that a defect region is found by extracting two maximum points from each of the wall region 1 and the wall region 2 in the real image and the thermal image.
도 6은 본 발명의 일 실시예에 따른 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 방법의 흐름도이다.6 is a flowchart of a method for determining a thermal abnormality of an exterior wall of a building using a thermal image and a real image according to an embodiment of the present invention.
도 6을 참조하면, 실화상 카메라 모듈(101)이 건물 외벽을 촬영하여 실화상을 생성한다(S101).Referring to FIG. 6 , the real image camera module 101 creates a real image by photographing the exterior wall of the building ( S101 ).
다음으로, 열화상 카메라 모듈(102)이 건물 외벽을 촬영하여 열화상을 생성한다(S102).Next, the thermal imaging camera module 102 generates a thermal image by photographing the exterior wall of the building ( S102 ).
다음으로, 외벽 온도 분포 파악 모듈(107)이 실화상 카메라 모듈(101)에 의해 생성된 실화상 및 열화상 카메라 모듈(102)에 의해 생성된 열화상을 이용하여 건물 외벽의 외벽 온도 분포를 파악한다(S103).Next, the external wall temperature distribution identification module 107 uses the real image generated by the real image camera module 101 and the thermal image generated by the thermal image camera module 102 to determine the external wall temperature distribution of the building exterior wall do (S103).
다음으로, 열적 이상 부위 추출 모듈(109)이 외벽 온도 분포 파악 모듈(107)에 의해 파악된 외벽 온도 분포를 이용하여 열적 이상 부위를 추출한다(S104).Next, the thermal anomaly extraction module 109 extracts a thermal anomaly using the outer wall temperature distribution identified by the outer wall temperature distribution determining module 107 ( S104 ).
이상 실시예를 참조하여 설명하였지만, 해당 기술 분야의 숙련된 당업자는 하기의 특허청구범위에 기재된 본 발명의 사상 및 영역으로부터 벗어나지 않는 범위 내에서 본 발명을 다양하게 수정 및 변경시킬 수 있음을 이해할 수 있을 것이다.Although it has been described with reference to the above embodiments, those skilled in the art can understand that various modifications and changes can be made to the present invention without departing from the spirit and scope of the present invention as set forth in the following claims. There will be.
본 발명은 건물의 열적 이상 부위 판단 시스템과 그 방법에 관한 것으로서, 건물의 설계, 시공, 유지보수 시장에 적용될 수 있다.The present invention relates to a system and method for determining a thermal abnormality of a building, and can be applied to the design, construction, and maintenance markets of buildings.

Claims (4)

  1. 건물 외벽을 촬영하여 실화상을 생성하는 실화상 카메라 모듈;a real image camera module for generating a real image by photographing an exterior wall of a building;
    상기 건물 외벽을 촬영하여 열화상을 생성하는 열화상 카메라 모듈;a thermal imaging camera module for generating a thermal image by photographing the exterior wall of the building;
    상기 실화상 카메라 모듈에 의해 생성된 실화상 및 상기 열화상 카메라 모듈에 의해 생성된 열화상을 이용하여 상기 건물 외벽의 외벽 온도 분포를 파악하는 외벽 온도 분포 파악 모듈을 포함하는 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템.Thermal images and real images comprising an exterior wall temperature distribution identification module that grasps the exterior wall temperature distribution of the exterior wall of the building using the real image generated by the real image camera module and the thermal image generated by the thermal imaging camera module A system for judging the thermal abnormality of the exterior wall of a building.
  2. 제1항에 있어서,According to claim 1,
    상기 외벽 온도 분포 파악 모듈에 의해 파악된 외벽 온도 분포를 이용하여 열적 이상 부위를 추출하는 열적 이상 부위 추출 모듈을 더 포함하도록 구성되는 것을 특징으로 하는 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 시스템.Thermal anomaly of the exterior wall of a building using thermal images and real images, characterized in that it further comprises a thermal abnormality extraction module for extracting thermal abnormalities using the exterior wall temperature distribution identified by the exterior wall temperature distribution identification module judgment system.
  3. 실화상 카메라 모듈이 건물 외벽을 촬영하여 실화상을 생성하는 단계;generating, by a real image camera module, a real image by photographing an exterior wall of the building;
    열화상 카메라 모듈이 상기 건물 외벽을 촬영하여 열화상을 생성하는 단계;generating, by a thermal imaging camera module, a thermal image by photographing the exterior wall of the building;
    외벽 온도 분포 파악 모듈이 상기 실화상 카메라 모듈에 의해 생성된 실화상 및 상기 열화상 카메라 모듈에 의해 생성된 열화상을 이용하여 상기 건물 외벽의 외벽 온도 분포를 파악하는 단계를 포함하는 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 방법.Thermal image and real, comprising the step of determining, by an external wall temperature distribution identification module, the external wall temperature distribution of the exterior wall of the building using the real image generated by the real image camera module and the thermal image generated by the thermal imaging camera module A method for determining thermal anomalies of exterior walls of buildings using burns.
  4. 제3항에 있어서,4. The method of claim 3,
    열적 이상 부위 추출 모듈이 상기 외벽 온도 분포 파악 모듈에 의해 파악된 외벽 온도 분포를 이용하여 열적 이상 부위를 추출하는 단계를 더 포함하도록 구성되는 것을 특징으로 하는 열화상 및 실화상을 이용한 건물 외벽의 열적 이상 부위 판단 방법.Thermal anomaly of the building exterior wall using a thermal image and real image, characterized in that the thermal abnormality extraction module further comprises the step of extracting the thermal abnormality region using the external wall temperature distribution identified by the external wall temperature distribution identification module How to determine an abnormal area.
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