Crack detection system and method for historic building

Abstract

The invention provides a crack detection system and method for an ancient building, and the method comprises the steps: collecting and analyzing a first surface image of the ancient building, obtaining the state data of a surface protection layer of the ancient building, determining the erosion feature information of the surface of the ancient building, and calibrating the erosion of the surface of the ancient building caused by the defects of the protection layer; based on the erosion characteristic information, a crack easily-induced area existing on the surface of the ancient building is determined, so that the range of identifying cracks on the surface of the ancient building is narrowed; acquiring and analyzing a second surface image of the crack easy-to-induce area to obtain crack state data so as to identify and position calibrate a structural crack of the crack easy-to-induce area, and screening and positioning a class of cracks with relatively large influence degree on the surface of the ancient building; and directional non-contact detection is carried out on the structural crack to obtain structural parameter data of the structural crack, so that the change trend of the structural crack is identified, the crack expansion change trend of the surface of the historic building is accurately predicted, and a reliable reference basis is provided for formulating a scheme for subsequently protecting and maintaining the historic building. And the reliability of historic building crack detection is improved.

Description

Technical Field

[0001] The present invention relates to the field of building monitoring, and in particular to a crack detection system and method for ancient buildings. Background Art

[0002] Ancient buildings are all wooden structures. Under the long-term effects of sunlight and wind and rain, a large number of cracks will form on the surface of ancient buildings. These cracks increase the contact area between the ancient buildings and the external environment, providing a hotbed for the erosion of wind and rain. In order to accurately, reliably and effectively protect ancient buildings in real time, it is necessary to conduct refined detection of the crack state on the surface of ancient buildings. At present, high-definition camera technology can be used to shoot the surface of ancient buildings, and image recognition and analysis technology can be combined to obtain crack data on the surface of ancient buildings. However, the above method only shoots a single process on the surface of the ancient building, which can only obtain conventional data such as the number and size of cracks on the surface of the ancient building, and cannot accurately predict the change trend of cracks on the surface of the ancient building, reducing the credibility of crack detection on the surface of the ancient building and the reference value of crack detection data for taking protection and restoration measures for ancient buildings. Summary of the invention

[0003] The purpose of the present invention is to provide a crack detection system and method for ancient buildings, which collect and analyze the first surface image of the ancient building to obtain the surface protection layer status data of the ancient building, thereby determining the erosion characteristic information of the surface of the ancient building, and calibrating the erosion caused by the defects of the protection layer on the surface of the ancient building; further, based on the erosion characteristic information, determine the crack-prone area on the surface of the ancient building, thereby narrowing the range of crack identification on the surface of the ancient building; collect and analyze the second surface image of the crack-prone area to obtain crack status data, thereby identifying and calibrating the position of structural cracks in the crack-prone area, and screening and locating a type of cracks with a greater degree of impact on the surface of the ancient building; further perform directional non-contact detection on the structural cracks to obtain the structural parameter data of the structural cracks, thereby identifying the change trend of the structural cracks, accurately predicting the change trend of crack expansion on the surface of the ancient building, providing a reliable reference basis for the formulation of subsequent protection and maintenance plans for the ancient buildings, and improving the credibility of crack detection in the ancient buildings.

[0004] The present invention is achieved through the following technical solutions:

[0005] Crack detection system for historic buildings, including:

[0006] A first image acquisition and analysis module, used to acquire a first surface image of the ancient building, analyze the first surface image, and obtain surface protection layer status data of the ancient building;

[0007] A crack-prone area determination module, used to determine the erosion characteristic information of the surface of the ancient building based on the surface protection layer state data; based on the erosion characteristic information, determine the crack-prone area on the surface of the ancient building;

[0008] A second image acquisition and analysis module is used to acquire a second surface image of the crack-prone area, analyze the second surface image, and obtain crack state data of the crack-prone area;

[0009] A structural crack identification and calibration module, used to identify all structural cracks in the crack-prone area based on the crack state data, and to calibrate the positions of the structural cracks;

[0010] A non-contact detection module, used to perform directional non-contact detection on the crack-prone area based on the position calibration result of the structural crack, and obtain structural parameter data of the structural crack;

[0011] The crack change trend determination module is used to identify the change trend of the structural cracks based on the structural parameter data.

[0012] Optionally, the first image acquisition and analysis module is used to acquire a first surface image of the ancient building, analyze the first surface image, and obtain the surface protection layer state data of the ancient building, including:

[0013] Perform infrared scanning and shooting on the surface of the ancient building to obtain an infrared scanning image of the surface of the ancient building; perform light intensity distribution recognition on the infrared scanning image to obtain light reflection intensity distribution data of the infrared scanning image in the infrared spectrum band; based on the light reflection intensity distribution data, obtain surface protection layer coverage data and surface protection layer thickness distribution data of the ancient building;

[0014] The crack-prone area determination module is used to determine the erosion characteristic information of the surface of the ancient building based on the surface protection layer state data; based on the erosion characteristic information, determine the crack-prone area on the surface of the ancient building, including:

[0015] Based on the surface protection layer coverage data and the surface protection layer thickness distribution data, the average surface erosion rate of all grid areas corresponding to the surface of the ancient building is estimated; the average surface erosion rate is compared with a preset erosion rate threshold; if the average surface erosion rate is greater than the preset erosion rate threshold, the corresponding grid area is determined as a crack-prone area; otherwise, the corresponding grid area is not determined as a crack-prone area.

[0016] Optionally, the second image acquisition and analysis module is used to acquire a second surface image of the crack-prone area, analyze the second surface image, and obtain crack state data of the crack-prone area, including:

[0017] Perform binocular photography on the crack-prone area to obtain a surface binocular image of the crack-prone area; generate a corresponding surface three-dimensional image based on the binocular parallax of the surface binocular image; perform crack contour recognition on the surface three-dimensional image to obtain crack length change data and crack width change data of the crack-prone area, which are used as the crack state data;

[0018] The structural crack identification and calibration module is used to identify all structural cracks in the crack-prone area based on the crack state data, and calibrate the positions of the structural cracks, including:

[0019] Based on the crack length change data and the crack width change data, the area value of the crack is determined; if the area value is greater than a preset area threshold, the crack is determined to be a structural crack; otherwise, the crack is not determined to be a structural crack; and based on the boundary contour data of the structural crack, the position of the structural crack in the crack-prone area is determined.

[0020] Optionally, the non-contact detection module is used to perform directional non-contact detection on the crack-prone area based on the position calibration result of the structural crack to obtain structural parameter data of the structural crack, including:

[0021] Based on the position of the structural crack in the crack-prone region, directional structured light projection detection is performed on the crack-prone region to obtain a reflected light pattern image of the structural crack to the structured light; and the reflected light pattern image is analyzed to obtain surface profile data of the structural crack in the depth direction;

[0022] The crack change trend determination module is used to identify the change trend of the structural cracks based on the structural parameter data, including:

[0023] Based on the surface profile data, the location point information where the structural cracks deepen and expand in the depth direction is identified.

[0024] Crack detection methods for ancient buildings include:

[0025] Collecting a first surface image of the ancient building, analyzing the first surface image to obtain surface protection layer status data of the ancient building; determining erosion characteristic information of the surface of the ancient building based on the surface protection layer status data; determining crack-prone areas on the surface of the ancient building based on the erosion characteristic information;

[0026] Acquire a second surface image of the crack-prone area, analyze the second surface image, and obtain crack state data of the crack-prone area; based on the crack state data, identify all structural cracks in the crack-prone area, and calibrate the positions of the structural cracks;

[0027] Based on the position calibration result of the structural crack, a directional non-contact detection is performed on the crack-prone area to obtain structural parameter data of the structural crack; based on the structural parameter data, a change trend of the structural crack is identified.

[0028] Optionally, collecting a first surface image of the ancient building, analyzing the first surface image to obtain surface protection layer status data of the ancient building; determining erosion characteristic information of the surface of the ancient building based on the surface protection layer status data; and determining crack-prone areas on the surface of the ancient building based on the erosion characteristic information, including:

[0029] Perform infrared scanning and shooting on the surface of the ancient building to obtain an infrared scanning image of the surface of the ancient building; perform light intensity distribution recognition on the infrared scanning image to obtain light reflection intensity distribution data of the infrared scanning image in the infrared spectrum band; based on the light reflection intensity distribution data, obtain surface protection layer coverage data and surface protection layer thickness distribution data of the ancient building;

[0030] Based on the surface protection layer coverage data and the surface protection layer thickness distribution data, the average surface erosion rate of all grid areas corresponding to the surface of the ancient building is estimated; the average surface erosion rate is compared with a preset erosion rate threshold; if the average surface erosion rate is greater than the preset erosion rate threshold, the corresponding grid area is determined as a crack-prone area; otherwise, the corresponding grid area is not determined as a crack-prone area.

[0031] Optionally, collecting a second surface image of the crack-prone area, analyzing the second surface image to obtain crack state data of the crack-prone area; identifying all structural cracks in the crack-prone area based on the crack state data, and calibrating the positions of the structural cracks, includes:

[0032] Perform binocular photography on the crack-prone area to obtain a surface binocular image of the crack-prone area; generate a corresponding surface three-dimensional image based on the binocular parallax of the surface binocular image; perform crack contour recognition on the surface three-dimensional image to obtain crack length change data and crack width change data of the crack-prone area, which are used as the crack state data;

[0033] Based on the crack length change data and the crack width change data, the area value of the crack is determined; if the area value is greater than a preset area threshold, the crack is determined to be a structural crack; otherwise, the crack is not determined to be a structural crack; and based on the boundary contour data of the structural crack, the position of the structural crack in the crack-prone area is determined.

[0034] Optionally, based on the position calibration result of the structural crack, directional non-contact detection is performed on the crack-prone area to obtain structural parameter data of the structural crack; based on the structural parameter data, identifying the change trend of the structural crack, including:

[0035] Based on the position of the structural crack in the crack-prone region, directional structured light projection detection is performed on the crack-prone region to obtain a reflected light pattern image of the structural crack to the structured light; and the reflected light pattern image is analyzed to obtain surface profile data of the structural crack in the depth direction;

[0036] Based on the surface profile data, the location point information where the structural cracks deepen and expand in the depth direction is identified.

[0037] Optionally, the method further includes judging the type of the grid area based on the average surface erosion rate obtained by multiple estimations, including:

[0038] Step S1: Assume that the average surface erosion rate estimated by the i-th acquisition is X i , then the coefficient of variation of the corresponding average surface erosion rate after n acquisitions is:

[0039]

[0040] In the above formula (1), S n is the coefficient of variation of the average surface erosion rate corresponding to n acquisitions;

[0041] Step S2: Assume that the preset erosion rate threshold is X0, then the cross coefficient between the corresponding surface average erosion rate after n acquisitions and the preset erosion rate threshold is:

[0042]

[0043] In the above formula (2), J n is the cross coefficient between the average surface erosion velocity corresponding to n acquisitions and the preset erosion velocity threshold;

[0044] Step S3, judging the type of the grid area according to the calculation results of the above steps S1 and S2,

[0045]

[0046] In the above formula (3), f(n) is the judgment value of the type of the grid area; when f(n) = 0, it indicates that the grid area does not belong to the crack-prone area; when f(n) = 1, it indicates that the grid area belongs to the crack-prone area; when f(n) = 2, it indicates that the grid area belongs to the area where serious damage has occurred.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The crack detection system and method for ancient buildings provided in the present application collect and analyze the first surface image of the ancient building to obtain the surface protection layer status data of the ancient building, thereby determining the erosion characteristic information of the surface of the ancient building, and calibrating the erosion caused by the defects of the protection layer on the surface of the ancient building; based on the erosion characteristic information, determine the crack-prone areas on the surface of the ancient building, thereby narrowing the scope of identifying cracks on the surface of the ancient building; collect and analyze the second surface image of the crack-prone areas to obtain crack status data, thereby identifying and calibrating the position of structural cracks in the crack-prone areas, and screening and locating a type of cracks with a greater impact on the surface of the ancient building; and also perform directional non-contact detection on the structural cracks to obtain the structural parameter data of the structural cracks, thereby identifying the changing trend of the structural cracks, and accurately predicting the expansion trend of the cracks on the surface of the ancient building, providing a reliable reference basis for the formulation of subsequent protection and maintenance plans for the ancient buildings, and improving the credibility of crack detection in the ancient buildings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0050] Figure 1 A schematic structural diagram of a crack detection system for ancient buildings provided by the present invention.

[0051] Figure 2A schematic flow chart of a crack detection method for ancient buildings provided by the present invention. DETAILED DESCRIPTION

[0052] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. It is to be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only some structures related to the present application are shown in the accompanying drawings, rather than all structures. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0053] The terms "including" and "having" and any variations thereof in this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0054] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0055] See also Figure 1 As shown, an embodiment of the present application provides a crack detection system for ancient buildings. The crack detection system for ancient buildings includes:

[0056] A first image acquisition and analysis module, used to acquire a first surface image of the ancient building, analyze the first surface image, and obtain surface protection layer status data of the ancient building;

[0057] A crack-prone area determination module is used to determine the erosion characteristic information of the surface of the ancient building based on the surface protection layer state data; based on the erosion characteristic information, determine the crack-prone area on the surface of the ancient building;

[0058] A second image acquisition and analysis module is used to acquire a second surface image of the crack-prone area, analyze the second surface image, and obtain crack state data of the crack-prone area;

[0059] A structural crack identification and calibration module is used to identify all structural cracks in the crack-prone area based on the crack state data, and to calibrate the positions of the structural cracks;

[0060] A non-contact detection module is used to perform directional non-contact detection on the crack-prone area based on the position calibration result of the structural crack to obtain structural parameter data of the structural crack;

[0061] The crack change trend determination module is used to identify the change trend of the structural cracks based on the structural parameter data.

[0062] The beneficial effects of the above embodiments are as follows: the crack detection system for ancient buildings collects and analyzes the first surface image of the ancient building to obtain the surface protection layer status data of the ancient building, thereby determining the erosion characteristic information of the surface of the ancient building, and calibrating the erosion caused by the defects of the protection layer on the surface of the ancient building; based on the erosion characteristic information, the crack-prone areas on the surface of the ancient building are determined, thereby narrowing the scope of identifying cracks on the surface of the ancient building; the second surface image of the crack-prone areas is collected and analyzed to obtain the crack status data, thereby identifying and calibrating the location of structural cracks in the crack-prone areas, and screening and locating a type of cracks with a greater impact on the surface of the ancient building; the structural cracks are also directed non-contact detection is performed to obtain the structural parameter data of the structural cracks, thereby identifying the changing trend of the structural cracks, and accurately predicting the expansion trend of the cracks on the surface of the ancient building, providing a reliable reference basis for the formulation of subsequent protection and maintenance plans for the ancient buildings, and improving the credibility of crack detection in the ancient buildings.

[0063] In another embodiment, the first image acquisition and analysis module is used to acquire a first surface image of the ancient building, analyze the first surface image, and obtain the surface protection layer state data of the ancient building, including:

[0064] Perform infrared scanning and photographing on the surface of the ancient building to obtain an infrared scanning image of the surface of the ancient building; perform light intensity distribution recognition on the infrared scanning image to obtain light reflection intensity distribution data of the infrared scanning image in the infrared spectrum band; based on the light reflection intensity distribution data, obtain surface protection layer coverage data and surface protection layer thickness distribution data of the ancient building;

[0065] The crack-prone area determination module is used to determine the erosion characteristic information of the surface of the ancient building based on the surface protection layer state data; based on the erosion characteristic information, determine the crack-prone area on the surface of the ancient building, including:

[0066] Based on the surface protection layer coverage data and the surface protection layer thickness distribution data, the surface average erosion rate of all grid areas corresponding to the surface of the ancient building is estimated; the surface average erosion rate is compared with a preset erosion rate threshold; if the surface average erosion rate is greater than the preset erosion rate threshold, the corresponding grid area is determined as a crack-prone area; otherwise, the corresponding grid area is not determined as a crack-prone area.

[0067] The beneficial effects of the above embodiments are that the ancient building is a wooden structure. In order to protect the surface of the wooden structure during the construction process, paint is usually applied on the surface of the ancient building to form a corresponding surface protection layer. After a long period of exposure to the sun and rain, the corresponding surface protection layer of the ancient building will inevitably be eroded or even fall off, so that the wooden part of the surface of the ancient building is directly exposed to the external environment, and the area of ​​the surface of the ancient building directly exposed to the external environment is more likely to crack than the area covered with the surface protection layer. In order to comprehensively and accurately identify the erosion and shedding status of surface protective layers such as paint on the surface of ancient buildings, the surface of the ancient buildings is infrared scanned and photographed to obtain an infrared scan image of the surface of the ancient buildings. It should be noted that the area of ​​the ancient building surface directly exposed to the external environment is compared with the area covered with the surface protection layer. The two areas have different reflectivity to light in the infrared spectrum band. By performing light intensity distribution identification on the infrared scan image, the light reflection intensity distribution data of the infrared scan image in the infrared spectrum band is obtained, and the surface protection layer coverage data and surface protection layer thickness distribution data of the ancient building are further obtained. In this way, the surface protection status of the ancient building can be obtained without the need for contact invasive detection of the surface protection layer of the ancient building, providing an accurate basis for the subsequent identification of crack-prone areas on the surface of the ancient building. In addition, based on the surface protection layer coverage data and the surface protection layer thickness distribution data, the average surface erosion rate of all grid areas corresponding to the surface of the ancient building (that is, the average area of ​​surface erosion within the grid area per unit time) is estimated, and then the threshold value of the average surface erosion rate is compared, so as to accurately and quickly determine whether each grid area belongs to an area prone to cracks, so as to facilitate further testing of only the areas prone to cracks, and effectively narrow the detection area of ​​the surface of the ancient building.

[0068] In another embodiment, the second image acquisition and analysis module is used to acquire a second surface image of the crack-prone area, analyze the second surface image, and obtain crack state data of the crack-prone area, including:

[0069] The crack-prone region is photographed by binoculars to obtain a binocular image of the surface of the crack-prone region; based on the binocular parallax of the surface binocular image, a corresponding surface three-dimensional image is generated; the crack contour is identified on the surface three-dimensional image to obtain crack length change data and crack width change data of the crack-prone region, which are used as the crack state data; wherein the crack length change data refers to the size change data of the crack in its own length direction; the crack width change data refers to the size change data of the crack in its own width direction;

[0070] The structural crack identification and calibration module is used to identify all structural cracks in the crack-prone area based on the crack state data, and to calibrate the positions of the structural cracks, including:

[0071] Based on the crack length change data and the crack width change data, the area value of the crack is determined; if the area value is greater than a preset area threshold, the crack is determined to be a structural crack; otherwise, the crack is not determined to be a structural crack; and based on the boundary contour data of the structural crack, the position of the structural crack in the crack-prone induction area is determined.

[0072] The beneficial effect of the above embodiment is that the boundary of the crack-prone area is used as a reference to take binocular photography of the crack-prone area to obtain a three-dimensional image of the surface of the crack-prone area, so that all cracks existing on the surface of the crack-prone area can be quantitatively identified in terms of size dimension, thereby accurately determining the crack shape of the crack-prone area. In addition, based on the crack length change data and the crack width change data, the area value of the crack is determined, and the threshold value of the area value of the crack is compared, so as to accurately distinguish whether the crack is a structural crack; wherein the structural crack refers to a crack that occupies a large area in the crack-prone area and will further induce more other cracks. Based on the boundary contour data of the structural crack, the position of the structural crack in the crack-prone area is determined, so that the precise range can be limited for the subsequent directional non-contact detection of the structural crack.

[0073] In another embodiment, the non-contact detection module is used to perform directional non-contact detection on the crack-prone area based on the position calibration result of the structural crack to obtain structural parameter data of the structural crack, including:

[0074] Based on the position of the structural crack in the crack-prone region, a directional structured light projection detection is performed on the crack-prone region to obtain a reflected light pattern image of the structural crack to the structured light; and the reflected light pattern image is analyzed to obtain surface profile data of the structural crack in the depth direction.

[0075] The crack change trend determination module is used to identify the change trend of the structural crack based on the structural parameter data, including:

[0076] Based on the surface profile data, the location point information where the structural crack deepens and expands in the depth direction is identified.

[0077] The beneficial effect of the above embodiment is that the position of the structural crack in the crack-prone area is used as a reference, and the crack-prone area is projected with directional structured light for detection. The crack-prone area will reflect the structured light projected thereon, thereby forming a corresponding reflected light pattern, and the reflected light pattern is imaged; the reflected light pattern image is then analyzed to obtain the surface contour morphology data of the structural crack in the depth direction, so as to accurately calibrate the morphological state of the structural crack. AI analysis and identification is also performed based on the surface contour morphology data to obtain the location point information of the structural crack in the depth direction where the crack deepens and expands, thereby locating the location points inside the structural crack that may induce the crack to further deepen and expand, so as to facilitate the subsequent implementation of corresponding repair methods for the corresponding location points, and avoid further increase and deepening of cracks on the surface of the ancient building.

[0078] See also Figure 2 As shown, an embodiment of the present application provides a crack detection method for ancient buildings. The crack detection method for ancient buildings includes:

[0079] Collecting a first surface image of the ancient building, analyzing the first surface image to obtain surface protection layer status data of the ancient building; determining erosion characteristic information of the surface of the ancient building based on the surface protection layer status data; determining crack-prone areas on the surface of the ancient building based on the erosion characteristic information;

[0080] Acquire a second surface image of the crack-prone region, analyze the second surface image, and obtain crack state data of the crack-prone region; based on the crack state data, identify all structural cracks in the crack-prone region, and calibrate the positions of the structural cracks;

[0081] Based on the position calibration result of the structural crack, a directional non-contact detection is performed on the crack-prone area to obtain structural parameter data of the structural crack; based on the structural parameter data, a change trend of the structural crack is identified.

[0082] The beneficial effects of the above embodiments are as follows: the crack detection method for ancient buildings collects and analyzes the first surface image of the ancient building to obtain the surface protection layer status data of the ancient building, thereby determining the erosion characteristic information of the surface of the ancient building, and calibrating the erosion caused by the defects of the protection layer on the surface of the ancient building; based on the erosion characteristic information, the crack-prone areas on the surface of the ancient building are determined, thereby narrowing the scope of identifying cracks on the surface of the ancient building; the second surface image of the crack-prone areas is collected and analyzed to obtain the crack status data, thereby identifying and calibrating the location of structural cracks in the crack-prone areas, and screening and locating a type of cracks with a greater impact on the surface of the ancient building; and the structural cracks are also directed non-contact detection is performed to obtain the structural parameter data of the structural cracks, thereby identifying the changing trend of the structural cracks, and accurately predicting the expansion trend of the cracks on the surface of the ancient building, providing a reliable reference basis for the formulation of subsequent protection and maintenance plans for the ancient buildings, and improving the credibility of crack detection in the ancient buildings.

[0083] In another embodiment, a first surface image of an ancient building is collected, and the first surface image is analyzed to obtain surface protection layer status data of the ancient building; based on the surface protection layer status data, erosion characteristic information of the surface of the ancient building is determined; based on the erosion characteristic information, a crack-prone area on the surface of the ancient building is determined, including:

[0084] Perform infrared scanning and photographing on the surface of the ancient building to obtain an infrared scanning image of the surface of the ancient building; perform light intensity distribution recognition on the infrared scanning image to obtain light reflection intensity distribution data of the infrared scanning image in the infrared spectrum band; based on the light reflection intensity distribution data, obtain surface protection layer coverage data and surface protection layer thickness distribution data of the ancient building;

[0085] Based on the surface protection layer coverage data and the surface protection layer thickness distribution data, the surface average erosion rate of all grid areas corresponding to the surface of the ancient building is estimated; the surface average erosion rate is compared with a preset erosion rate threshold; if the surface average erosion rate is greater than the preset erosion rate threshold, the corresponding grid area is determined as a crack-prone area; otherwise, the corresponding grid area is not determined as a crack-prone area.

[0086] The beneficial effects of the above embodiments are that the ancient building is a wooden structure. In order to protect the surface of the wooden structure during the construction process, paint is usually applied on the surface of the ancient building to form a corresponding surface protection layer. After a long period of exposure to the sun and rain, the corresponding surface protection layer of the ancient building will inevitably be eroded or even fall off, so that the wooden part of the surface of the ancient building is directly exposed to the external environment, and the area of ​​the surface of the ancient building directly exposed to the external environment is more likely to crack than the area covered with the surface protection layer. In order to comprehensively and accurately identify the erosion and shedding status of surface protective layers such as paint on the surface of ancient buildings, the surface of the ancient buildings is infrared scanned and photographed to obtain an infrared scan image of the surface of the ancient buildings. It should be noted that the area of ​​the ancient building surface directly exposed to the external environment is compared with the area covered with the surface protection layer. The two areas have different reflectivity to light in the infrared spectrum band. By performing light intensity distribution identification on the infrared scan image, the light reflection intensity distribution data of the infrared scan image in the infrared spectrum band is obtained, and the surface protection layer coverage data and surface protection layer thickness distribution data of the ancient building are further obtained. In this way, the surface protection status of the ancient building can be obtained without the need for contact invasive detection of the surface protection layer of the ancient building, providing an accurate basis for the subsequent identification of crack-prone areas on the surface of the ancient building. In addition, based on the surface protection layer coverage data and the surface protection layer thickness distribution data, the average surface erosion rate of all grid areas corresponding to the surface of the ancient building (that is, the average area of ​​surface erosion within the grid area per unit time) is estimated, and then the threshold value of the average surface erosion rate is compared, so as to accurately and quickly determine whether each grid area belongs to an area prone to cracks, so as to facilitate further testing of only the areas prone to cracks, and effectively narrow the detection area of ​​the surface of the ancient building.

[0087] In another embodiment, collecting a second surface image of the crack-prone region, analyzing the second surface image to obtain crack state data of the crack-prone region; based on the crack state data, identifying all structural cracks in the crack-prone region, and calibrating the positions of the structural cracks, includes:

[0088] The crack-prone region is photographed by binoculars to obtain a surface binocular image of the crack-prone region; a corresponding surface three-dimensional image is generated based on the binocular parallax of the surface binocular image; crack contours are identified on the surface three-dimensional image to obtain crack length change data and crack width change data of the crack-prone region, which are used as the crack state data;

[0089] Based on the crack length change data and the crack width change data, the area value of the crack is determined; if the area value is greater than a preset area threshold, the crack is determined to be a structural crack; otherwise, the crack is not determined to be a structural crack; and based on the boundary contour data of the structural crack, the position of the structural crack in the crack-prone induction area is determined.

[0090] The beneficial effect of the above embodiment is that the boundary of the crack-prone area is used as a reference to take binocular photography of the crack-prone area to obtain a three-dimensional image of the surface of the crack-prone area, so that all cracks existing on the surface of the crack-prone area can be quantitatively identified in terms of size dimension, thereby accurately determining the crack shape of the crack-prone area. In addition, based on the crack length change data and the crack width change data, the area value of the crack is determined, and the threshold value of the area value of the crack is compared, so as to accurately distinguish whether the crack is a structural crack; wherein the structural crack refers to a crack that occupies a large area in the crack-prone area and will further induce more other cracks. Based on the boundary contour data of the structural crack, the position of the structural crack in the crack-prone area is determined, so that the precise range can be limited for the subsequent directional non-contact detection of the structural crack.

[0091] In another embodiment, based on the position calibration result of the structural crack, a directional non-contact detection is performed on the crack-prone area to obtain structural parameter data of the structural crack; based on the structural parameter data, a change trend of the structural crack is identified, including:

[0092] Based on the position of the structural crack in the crack-prone region, a directional structured light projection detection is performed on the crack-prone region to obtain a reflected light pattern image of the structural crack to the structured light; and the reflected light pattern image is analyzed to obtain surface profile data of the structural crack in the depth direction.

[0093] Based on the surface profile data, the location point information where the structural crack deepens and expands in the depth direction is identified.

[0094] The beneficial effect of the above embodiment is that the position of the structural crack in the crack-prone area is used as a reference, and the crack-prone area is projected with directional structured light for detection. The crack-prone area will reflect the structured light projected thereon, thereby forming a corresponding reflected light pattern, and the reflected light pattern is imaged; the reflected light pattern image is then analyzed to obtain the surface contour morphology data of the structural crack in the depth direction, so as to accurately calibrate the morphological state of the structural crack. AI analysis and identification is also performed based on the surface contour morphology data to obtain the location point information of the structural crack in the depth direction where the crack deepens and expands, thereby locating the location points inside the structural crack that may induce the crack to further deepen and expand, so as to facilitate the subsequent implementation of corresponding repair methods for the corresponding location points, and avoid further increase and deepening of cracks on the surface of the ancient building.

[0095] In another embodiment, the method further includes determining the type of the grid area based on the average surface erosion rate obtained by multiple estimations, including:

[0096] Step S1: Assume that the average surface erosion rate estimated by the i-th acquisition is X i , then the coefficient of variation of the corresponding average surface erosion rate after n acquisitions is:

[0097]

[0098] In the above formula (1), S n is the coefficient of variation of the average surface erosion rate corresponding to n acquisitions;

[0099] Step S2: Assume that the preset erosion rate threshold is X0, then the cross coefficient between the corresponding surface average erosion rate after n acquisitions and the preset erosion rate threshold is:

[0100]

[0101] In the above formula (2), J n is the cross coefficient between the average surface erosion velocity corresponding to n acquisitions and the preset erosion velocity threshold;

[0102] Step S3, judging the type of the grid area according to the calculation results of the above steps S1 and S2,

[0103]

[0104] In the above formula (3), f(n) is the judgment value of the type of the grid area; when f(n) = 0, it indicates that the grid area does not belong to the crack-prone area; when f(n) = 1, it indicates that the grid area belongs to the crack-prone area; when f(n) = 2, it indicates that the grid area belongs to the area where serious damage has occurred.

[0105] The beneficial effects of the above embodiments are that, due to the complex and changeable environment in which the ancient buildings are located, in addition to the erosion from the natural environment, they will also be disturbed by other external factors, causing changes in the surface protective layer, such as human damage, sudden accidents, etc., which will cause the thickness of the surface protective layer to change significantly, and the corresponding surface average erosion rate must be greater than the preset erosion rate threshold. However, if only the corresponding grid area is determined as a crack-prone area, and subsequent maintenance is carried out according to the processing procedures for crack-prone areas, the speed of damage to the ancient buildings will inevitably be accelerated, because under the interference of such external factors, especially when human damage has caused major damage to the surface of the ancient buildings, it is not only a crack-prone area, but also an area that urgently needs to be repaired and protected, so higher-level measures are required to maintain it. In order to accurately distinguish between crack-prone areas and areas that have been severely damaged, it is convenient to carry out protective repairs in a timely manner, and avoid the situation where the damage to the ancient buildings is aggravated or cannot be repaired due to repairs too late. The above process is based on the collected erosion rate data. By calculating the coefficient of variation of the erosion rate and its relationship with the erosion rate threshold, it accurately judges the areas on the surface of the ancient buildings that are prone to cracks and the areas that have suffered serious damage, thereby avoiding the situation where the damage to the ancient buildings is aggravated or they cannot be repaired due to failure to identify the areas that urgently need repair and repair too late.

[0106] In general, the crack detection system and method for ancient buildings collect and analyze the first surface image of the ancient building to obtain the surface protection layer status data of the ancient building, thereby determining the erosion characteristic information of the surface of the ancient building, and calibrating the erosion caused by the defects of the protection layer on the surface of the ancient building; based on the erosion characteristic information, the crack-prone areas on the surface of the ancient building are determined, thereby narrowing the scope of identifying cracks on the surface of the ancient building; the second surface image of the crack-prone areas is collected and analyzed to obtain the crack status data, thereby identifying and calibrating the position of structural cracks in the crack-prone areas, and screening and locating a type of cracks with a greater impact on the surface of the ancient building; and the structural cracks are also directed non-contact detection is performed on the structural cracks to obtain the structural parameter data of the structural cracks, thereby identifying the changing trend of the structural cracks, and accurately predicting the expansion trend of the cracks on the surface of the ancient building, providing a reliable reference basis for the formulation of subsequent protection and maintenance plans for the ancient buildings, and improving the credibility of crack detection in the ancient buildings.

[0107] The above is only a specific implementation of the present invention, and any other improvements made based on the concept of the present invention are considered to be within the protection scope of the present invention.

Claims

1. A crack detection system for ancient buildings, characterized in that: include: A first image acquisition and analysis module, used to acquire a first surface image of the ancient building, analyze the first surface image, and obtain surface protection layer status data of the ancient building; A crack-prone area determination module, used to determine the erosion characteristic information of the surface of the ancient building based on the surface protection layer state data; Based on the erosion characteristic information, determining the crack-prone areas on the surface of the ancient building; A second image acquisition and analysis module is used to acquire a second surface image of the crack-prone area, analyze the second surface image, and obtain crack state data of the crack-prone area; A structural crack identification and calibration module, used to identify all structural cracks in the crack-prone area based on the crack state data, and to calibrate the positions of the structural cracks; A non-contact detection module, used to perform directional non-contact detection on the crack-prone area based on the position calibration result of the structural crack, and obtain structural parameter data of the structural crack; The crack change trend determination module is used to identify the change trend of the structural cracks based on the structural parameter data.

2. The crack detection system for ancient buildings according to claim 1, characterized in that: The first image acquisition and analysis module is used to acquire a first surface image of the ancient building, analyze the first surface image, and obtain the surface protection layer status data of the ancient building, including: Perform infrared scanning and shooting on the surface of the ancient building to obtain an infrared scanning image of the surface of the ancient building; perform light intensity distribution recognition on the infrared scanning image to obtain light reflection intensity distribution data of the infrared scanning image in the infrared spectrum band; based on the light reflection intensity distribution data, obtain surface protection layer coverage data and surface protection layer thickness distribution data of the ancient building; The crack-prone area determination module is used to determine the erosion characteristic information of the surface of the ancient building based on the surface protection layer state data; based on the erosion characteristic information, determine the crack-prone area on the surface of the ancient building, including: Based on the surface protection layer coverage data and the surface protection layer thickness distribution data, the average surface erosion rate of all grid areas corresponding to the surface of the ancient building is estimated; the average surface erosion rate is compared with a preset erosion rate threshold; if the average surface erosion rate is greater than the preset erosion rate threshold, the corresponding grid area is determined as a crack-prone area; otherwise, the corresponding grid area is not determined as a crack-prone area.

3. The crack detection system for ancient buildings according to claim 1, characterized in that: The second image acquisition and analysis module is used to acquire a second surface image of the crack-prone area, analyze the second surface image, and obtain crack state data of the crack-prone area, including: The crack-prone region is photographed by binoculars to obtain a surface binocular image of the crack-prone region; a corresponding surface three-dimensional image is generated based on the binocular parallax of the surface binocular image; crack contours are identified on the surface three-dimensional image to obtain crack length change data and crack width change data of the crack-prone region, which are used as the crack state data; the structural crack identification and calibration module is used to identify all structural cracks in the crack-prone region based on the crack state data, and to calibrate the positions of the structural cracks, including: Based on the crack length change data and the crack width change data, the area value of the crack is determined; if the area value is greater than a preset area threshold, the crack is determined to be a structural crack; otherwise, the crack is not determined to be a structural crack; and based on the boundary contour data of the structural crack, the position of the structural crack in the crack-prone induction area is determined.

4. The crack detection system for ancient buildings according to claim 1, characterized in that: The non-contact detection module is used to perform directional non-contact detection on the crack-prone area based on the position calibration result of the structural crack to obtain structural parameter data of the structural crack, including: Based on the position of the structural crack in the crack-prone region, directional structured light projection detection is performed on the crack-prone region to obtain a reflected light pattern image of the structural crack to the structured light; and the reflected light pattern image is analyzed to obtain surface profile data of the structural crack in the depth direction; The crack change trend determination module is used to identify the change trend of the structural cracks based on the structural parameter data, including: Based on the surface profile data, the location point information where the structural cracks deepen and expand in the depth direction is identified.

5. A crack detection method for ancient buildings, characterized in that: include: Collecting a first surface image of the ancient building, analyzing the first surface image, and obtaining surface protection layer status data of the ancient building; Based on the surface protection layer state data, determining the erosion characteristic information of the surface of the ancient building; Based on the erosion characteristic information, determining the crack-prone areas on the surface of the ancient building; Collecting a second surface image of the crack-prone area, analyzing the second surface image, and obtaining crack state data of the crack-prone area; Based on the crack state data, identifying all structural cracks in the crack-prone area, and calibrating the positions of the structural cracks; Based on the position calibration result of the structural crack, a directional non-contact detection is performed on the crack-prone area to obtain structural parameter data of the structural crack; Based on the structural parameter data, a change trend of the structural cracks is identified.

6. The crack detection method for ancient buildings according to claim 5, characterized in that: Collecting a first surface image of the ancient building, analyzing the first surface image to obtain surface protection layer status data of the ancient building; and determining erosion characteristic information of the surface of the ancient building based on the surface protection layer status data; Based on the erosion characteristic information, determining the crack-prone areas on the surface of the ancient building, including: Perform infrared scanning and shooting on the surface of the ancient building to obtain an infrared scanning image of the surface of the ancient building; perform light intensity distribution recognition on the infrared scanning image to obtain light reflection intensity distribution data of the infrared scanning image in the infrared spectrum band; based on the light reflection intensity distribution data, obtain surface protection layer coverage data and surface protection layer thickness distribution data of the ancient building; Based on the surface protection layer coverage data and the surface protection layer thickness distribution data, the average surface erosion rate of all grid areas corresponding to the surface of the ancient building is estimated; the average surface erosion rate is compared with a preset erosion rate threshold; if the average surface erosion rate is greater than the preset erosion rate threshold, the corresponding grid area is determined as a crack-prone area; otherwise, the corresponding grid area is not determined as a crack-prone area.

7. The crack detection method for ancient buildings according to claim 5, characterized in that: Collecting a second surface image of the crack-prone area, analyzing the second surface image, and obtaining crack state data of the crack-prone area; Based on the crack state data, all structural cracks in the crack-prone area are identified, and positions of the structural cracks are calibrated, including: The crack-prone area is photographed by binocular to obtain a surface binocular image of the crack-prone area; based on the binocular parallax of the surface binocular image, a corresponding surface three-dimensional image is generated; crack contour recognition is performed on the surface three-dimensional image to obtain crack length change data and crack width change data of the crack-prone area, which are used as the crack state data; based on the crack length change data and the crack width change data, the area value of the crack is determined; if the area value is greater than a preset area threshold, the crack is determined as a structural crack; otherwise, the crack is not determined as a structural crack; and based on the boundary contour data of the structural crack, the position of the structural crack in the crack-prone area is determined.

8. The crack detection method for ancient buildings according to claim 5, characterized in that: Based on the position calibration result of the structural crack, a directional non-contact detection is performed on the crack-prone area to obtain structural parameter data of the structural crack; Based on the structural parameter data, identifying a change trend of the structural cracks includes: Based on the position of the structural crack in the crack-prone region, directional structured light projection detection is performed on the crack-prone region to obtain a reflected light pattern image of the structural crack to the structured light; and the reflected light pattern image is analyzed to obtain surface profile data of the structural crack in the depth direction; Based on the surface profile data, the location point information where the structural cracks deepen and expand in the depth direction is identified.

9. The crack detection method for ancient buildings according to claim 6, characterized in that: The method further includes determining the type of the grid area based on the average surface erosion rate obtained by multiple estimations, including: Step S1: Assume that the average surface erosion rate estimated by the i-th acquisition is X i , then the coefficient of variation of the corresponding average surface erosion rate after n acquisitions is: In the above formula (1), S n is the coefficient of variation of the average surface erosion rate corresponding to n acquisitions; Step S2: Assume that the preset erosion rate threshold is X0, then the cross coefficient between the corresponding surface average erosion rate after n acquisitions and the preset erosion rate threshold is: In the above formula (2), J n is the cross coefficient between the average surface erosion velocity corresponding to n acquisitions and the preset erosion velocity threshold; Step S3, judging the type of the grid area according to the calculation results of the above steps S1 and S2, In the above formula (3), f(n) is the judgment value of the type of the grid area; when f(n) = 0, it indicates that the grid area does not belong to the crack-prone area; when f(n) = 1, it indicates that the grid area belongs to the crack-prone area; when f(n) = 2, it indicates that the grid area belongs to the area where serious damage has occurred.

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