House structure defect detection method and system

Abstract

The invention provides a house structure defect detection method and system. The method comprises the steps that a panoramic image corresponding to a target house is collected in real time through a mooring unmanned aerial vehicle; analyzing the panoramic image to respectively extract a house structure image and a house appearance image corresponding to the target house from the panoramic image, and judging whether the target house meets a first preset requirement in real time according to the house appearance image based on a first preset rule; if it is judged that the target house meets a first preset requirement in real time according to the house appearance image based on the first preset rule, whether the target house meets a second preset requirement or not is judged in real time according to the house structure image based on a second preset rule; and if it is judged that the target house meets a second preset requirement in real time according to the house structure image based on a second preset rule, correspondingly judging that the target house does not have defects, and generating a corresponding detection report in real time. According to the invention, whether the house has defects can be objectively and accurately judged, and the detection efficiency is correspondingly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of house detection, and in particular to a method and system for detecting defects in house structures. Background Art

[0002] With the development of the times and the advancement of science and technology, people have been able to build various types of buildings. However, as time goes by, all types of buildings will age, and aging houses will produce certain safety hazards. Therefore, it is necessary to inspect the houses regularly to ensure the safety of people.

[0003] Among them, in the actual detection process, due to the large size of the house, the existing shooting devices can only capture partial images of the house. Based on this, most of the existing technologies use manual inspection during the detection process. However, although manual inspection can complete the inspection of the house to a certain extent, manual inspection takes a long time and requires manual subjective judgment based on their work experience to decide whether the house has defects. This detection method is also prone to missed detections and false detections, which correspondingly reduces the detection accuracy and efficiency. Summary of the invention

[0004] Based on this, the purpose of the present invention is to provide a method and system for detecting structural defects of a house, so as to solve the problem that most of the existing technologies rely on manual detection, which leads to missed detection and false detection in the detection process.

[0005] The first aspect of the embodiment of the present invention proposes:

[0006] A method for detecting structural defects of a building, wherein the method comprises:

[0007] When receiving the target house input by the user in real time, a panoramic image corresponding to the target house is collected in real time by a tethered drone;

[0008] Analyzing the panoramic image to extract a house structure image and a house appearance image corresponding to the target house from the panoramic image, and judging in real time whether the target house meets a first preset requirement based on the house appearance image based on a first preset rule;

[0009] If it is determined in real time based on the first preset rule according to the house appearance image that the target house meets the first preset requirement, it is determined in real time based on the house structure image whether the target house meets the second preset requirement according to the second preset rule;

[0010] If it is determined in real time based on the second preset rule and according to the house structure image that the target house meets the second preset requirement, it is correspondingly determined that there are no defects in the target house, and a corresponding inspection report is generated in real time.

[0011] The beneficial effect of the present invention is that by adopting a tethered drone, a panoramic image of a target house can be completely collected, based on which, a house structure image and a house appearance image for subsequent analysis can be further extracted. Furthermore, a judgment is first made based on the current house appearance image, and only after the first judgment meets the requirements will a subsequent secondary judgment be made, that is, a secondary judgment is further made based on the house structure image, and whether the current target house has defects can be determined based on the judgment result, thereby eliminating the manual judgment process and correspondingly improving the detection accuracy and detection efficiency.

[0012] Furthermore, the step of judging in real time whether the target house meets the first preset requirement according to the house appearance image based on the first preset rule includes:

[0013] When the exterior image of the house is acquired in real time, a matching target three-dimensional program is called out in real time from a preset database;

[0014] A target three-dimensional space is created in real time by the target three-dimensional program, and a plurality of reference planes are created in real time in the target three-dimensional space, wherein the plurality of reference planes are arranged according to preset orientations;

[0015] It is determined whether the target house meets the first preset requirement according to the house appearance image and the correspondence between the plurality of reference planes.

[0016] Furthermore, the step of judging whether the target house meets the first preset requirement according to the house appearance image and the plurality of reference planes includes:

[0017] When a plurality of reference surfaces are acquired in real time, a corresponding target identifier is added to each reference surface;

[0018] Based on the target identifier, local appearance images corresponding to the orientation of each reference surface are selected in real time from the house appearance image, and each local appearance image is mapped to the inside of the reference surface corresponding thereto;

[0019] Whether the target house meets the first preset requirement is determined according to each of the local appearance images and each of the reference planes.

[0020] Furthermore, the step of judging whether the target house meets the first preset requirement according to each of the local appearance images and each of the reference planes includes:

[0021] When each of the local appearance images is acquired in real time, stereo processing is performed on each of the local appearance images according to the reference plane to generate a corresponding local three-dimensional model in real time;

[0022] Performing splicing processing on each of the local three-dimensional models to generate a three-dimensional house model corresponding to the target house in real time, and determining in real time whether the surface of the three-dimensional house model is damaged;

[0023] If it is determined in real time that the surface of the three-dimensional model of the house is not damaged, then it is correspondingly determined that the surface of the target house has no defects and satisfies the first preset requirement.

[0024] Furthermore, the step of judging in real time whether the target house meets the second preset requirement according to the house structure image based on the second preset rule includes:

[0025] When the house structure image is acquired in real time, a corresponding house internal structure model is generated in real time according to the house structure image by the target three-dimensional program;

[0026] The internal structure model of the house is mapped to the interior of the three-dimensional model of the house to generate a corresponding overall model of the house in real time, and whether the target house meets the second preset requirement is determined in real time based on the overall model of the house.

[0027] Furthermore, the step of determining in real time whether the target house meets the second preset requirement according to the overall house model includes:

[0028] When the overall model of the house is acquired in real time, the overall model of the house is scanned in its entirety to generate a corresponding scanned image in real time;

[0029] Determine in real time whether there are structural defects inside the overall model of the house according to the scanned image;

[0030] If it is determined in real time based on the scanned image that the structural defects do not exist inside the overall model of the house, then it is correspondingly determined that the target house meets the second preset requirement.

[0031] Furthermore, the step of generating a corresponding test report in real time includes:

[0032] When the detection report is obtained in real time, the detection report is encrypted to generate a corresponding encrypted report, and the encrypted report is sent to the user terminal of the staff member accordingly.

[0033] The second aspect of the embodiment of the present invention proposes:

[0034] A building structure defect detection system, wherein the system comprises:

[0035] A collection module, for collecting a panoramic image corresponding to the target house in real time through a tethered drone when receiving the target house input by the user in real time;

[0036] a parsing module, configured to parse the panoramic image to extract a house structure image and a house appearance image corresponding to the target house from the panoramic image, and determine in real time whether the target house meets a first preset requirement based on the house appearance image based on a first preset rule;

[0037] A judgment module, configured to judge in real time whether the target house meets the first preset requirement based on the house structure image based on a second preset rule, if judging in real time based on the house appearance image based on a first preset rule that the target house meets the first preset requirement;

[0038] The execution module is used to determine that there are no defects in the target house and generate a corresponding inspection report in real time if it is determined in real time based on the second preset rule according to the house structure image that the target house meets the second preset requirement.

[0039] Furthermore, the parsing module is specifically used for:

[0040] When the exterior image of the house is acquired in real time, a matching target three-dimensional program is called out in real time from a preset database;

[0041] A target three-dimensional space is created in real time by the target three-dimensional program, and a plurality of reference planes are created in real time in the target three-dimensional space, wherein the plurality of reference planes are arranged according to preset orientations;

[0042] It is determined whether the target house meets the first preset requirement according to the house appearance image and the correspondence between the plurality of reference planes.

[0043] Furthermore, the parsing module is specifically used for:

[0044] When a plurality of reference surfaces are acquired in real time, a corresponding target identifier is added to each reference surface;

[0045] Based on the target identifier, local appearance images corresponding to the orientation of each reference surface are selected in real time from the house appearance image, and each local appearance image is mapped to the inside of the reference surface corresponding thereto;

[0046] Whether the target house meets the first preset requirement is determined according to each of the local appearance images and each of the reference planes.

[0047] Furthermore, the parsing module is specifically used for:

[0048] When each of the local appearance images is acquired in real time, stereo processing is performed on each of the local appearance images according to the reference plane to generate a corresponding local three-dimensional model in real time;

[0049] Performing splicing processing on each of the local three-dimensional models to generate a three-dimensional house model corresponding to the target house in real time, and determining in real time whether the surface of the three-dimensional house model is damaged;

[0050] If it is determined in real time that the surface of the three-dimensional model of the house is not damaged, then it is correspondingly determined that the surface of the target house has no defects and satisfies the first preset requirement.

[0051] Furthermore, the judgment module is specifically used for:

[0052] When the house structure image is acquired in real time, a corresponding house internal structure model is generated in real time according to the house structure image by the target three-dimensional program;

[0053] The internal structure model of the house is mapped to the interior of the three-dimensional model of the house to generate a corresponding overall model of the house in real time, and whether the target house meets the second preset requirement is determined in real time based on the overall model of the house.

[0054] Furthermore, the judgment module is specifically used for:

[0055] When the overall model of the house is acquired in real time, the overall model of the house is scanned in its entirety to generate a corresponding scanned image in real time;

[0056] Determine in real time whether there are structural defects inside the overall model of the house according to the scanned image;

[0057] If it is determined in real time based on the scanned image that the structural defects do not exist inside the overall model of the house, then it is correspondingly determined that the target house meets the second preset requirement.

[0058] Furthermore, the judgment module is specifically used for:

[0059] When the detection report is obtained in real time, the detection report is encrypted to generate a corresponding encrypted report, and the encrypted report is sent to the user terminal of the staff member accordingly.

[0060] The third aspect of the embodiment of the present invention proposes:

[0061] A computer comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned building structure defect detection method when executing the computer program.

[0062] The fourth aspect of the embodiments of the present invention proposes:

[0063] A readable storage medium stores a computer program, wherein when the program is executed by a processor, the building structure defect detection method as described above is implemented.

[0064] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 A flow chart of a building structure defect detection method provided by a first embodiment of the present invention;

[0066] Figure 2 This is a structural block diagram of a building structure defect detection system provided in the third embodiment of the present invention.

[0067] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0068] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0069] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0070] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0071] See also Figure 1, shown is a house structure defect detection method provided by the first embodiment of the present invention. The house structure defect detection method provided by this embodiment can determine whether the target house has defects based on the judgment result, thereby eliminating the process of manual judgment and correspondingly improving the detection accuracy and detection efficiency.

[0072] Specifically, this embodiment provides:

[0073] A method for detecting structural defects of a house, comprising the following steps:

[0074] Step S10, when the target house input by the user is received in real time, a panoramic image corresponding to the target house is collected in real time by a tethered drone;

[0075] Step S20, analyzing the panoramic image to extract a house structure image and a house appearance image corresponding to the target house in the panoramic image, and judging in real time whether the target house meets a first preset requirement based on the house appearance image based on a first preset rule;

[0076] Step S30, if it is determined in real time based on the first preset rule according to the house appearance image that the target house meets the first preset requirement, then it is determined in real time based on the house structure image whether the target house meets the second preset requirement based on the second preset rule;

[0077] Step S40: If it is determined in real time based on the second preset rule and according to the house structure image that the target house meets the second preset requirement, it is determined that there are no defects in the target house, and a corresponding inspection report is generated in real time.

[0078] Specifically, in this embodiment, it should be noted that in order to objectively and accurately detect whether a house has defects, it is necessary to objectively and accurately obtain the appearance information and internal information of the house, wherein the appearance information is mainly used to determine whether the outer surface of the house has defects, and correspondingly, the internal information is mainly used to determine whether the internal structure of the house has defects. Based on this, before performing actual detection, it is necessary to determine a clear detection target. Specifically, the server set in the background will receive the target house input by the user in real time. Based on this, the current server will immediately enable the corresponding tethered drone, and can further collect the panoramic image of the current target house in real time through the tethered drone. At the same time, in order to obtain the required house information in a timely manner, the present invention will further parse and process the current panoramic image. Preferably, the present invention will further extract the required house structure image and house appearance image from the current panoramic image through the existing image parsing algorithm, and perform subsequent processing accordingly.

[0079] Furthermore, after obtaining the required house appearance image and house structure image respectively through the above steps, corresponding processing will be performed immediately. Preferably, the present invention will immediately judge in real time whether the appearance of the current target house meets the first preset requirement according to the current house appearance image according to the first preset rule set in advance. Specifically, if so, a subsequent secondary judgment will be performed, that is, the present invention will further judge in real time whether the current target house meets the second preset requirement according to the second preset rule set in advance. Specifically, if so, it can be directly judged that there are no house defects in the current target house, that is, the current house is still in normal use, and a corresponding inspection report can be generated at the same time. Correspondingly, if one of the judgment results in the above two judgment processes is no, it can be directly judged that the current target house has corresponding house defects, that is, the current house is not in normal use. Based on this, corresponding maintenance processing is required, so that it can objectively and accurately judge whether the above target house has defects, which correspondingly improves the inspection efficiency.

[0080] Second embodiment

[0081] Furthermore, the step of judging in real time whether the target house meets the first preset requirement according to the house appearance image based on the first preset rule includes:

[0082] When the exterior image of the house is acquired in real time, a matching target three-dimensional program is called out in real time from a preset database;

[0083] A target three-dimensional space is created in real time by the target three-dimensional program, and a plurality of reference planes are created in real time in the target three-dimensional space, wherein the plurality of reference planes are arranged according to preset orientations;

[0084] It is determined whether the target house meets the first preset requirement according to the house appearance image and the correspondence between the plurality of reference planes.

[0085] Furthermore, the step of judging whether the target house meets the first preset requirement according to the house appearance image and the plurality of reference planes includes:

[0086] When a plurality of reference surfaces are acquired in real time, a corresponding target identifier is added to each reference surface;

[0087] Based on the target identifier, local appearance images corresponding to the orientation of each reference surface are selected in real time from the house appearance image, and each local appearance image is mapped to the inside of the reference surface corresponding thereto;

[0088] Whether the target house meets the first preset requirement is determined according to each of the local appearance images and each of the reference planes.

[0089] Furthermore, the step of judging whether the target house meets the first preset requirement according to each of the local appearance images and each of the reference planes includes:

[0090] When each of the local appearance images is acquired in real time, stereo processing is performed on each of the local appearance images according to the reference plane to generate a corresponding local three-dimensional model in real time;

[0091] Performing splicing processing on each of the local three-dimensional models to generate a three-dimensional house model corresponding to the target house in real time, and determining in real time whether the surface of the three-dimensional house model is damaged;

[0092] If it is determined in real time that the surface of the three-dimensional model of the house is not damaged, then it is correspondingly determined that the surface of the target house has no defects and satisfies the first preset requirement.

[0093] Furthermore, the step of judging in real time whether the target house meets the second preset requirement according to the house structure image based on the second preset rule includes:

[0094] When the house structure image is acquired in real time, a corresponding house internal structure model is generated in real time according to the house structure image by the target three-dimensional program;

[0095] The internal structure model of the house is mapped to the interior of the three-dimensional model of the house to generate a corresponding overall model of the house in real time, and whether the target house meets the second preset requirement is determined in real time based on the overall model of the house.

[0096] Furthermore, the step of determining in real time whether the target house meets the second preset requirement according to the overall house model includes:

[0097] When the overall model of the house is acquired in real time, the overall model of the house is scanned in its entirety to generate a corresponding scanned image in real time;

[0098] Determine in real time whether there are structural defects inside the overall model of the house according to the scanned image;

[0099] If it is determined in real time based on the scanned image that the structural defects do not exist inside the overall model of the house, then it is correspondingly determined that the target house meets the second preset requirement.

[0100] Furthermore, the step of generating a corresponding test report in real time includes:

[0101] When the detection report is obtained in real time, the detection report is encrypted to generate a corresponding encrypted report, and the encrypted report is sent to the user terminal of the staff member accordingly.

[0102] In addition, in the present embodiment, it is also necessary to explain that after the required house structure image and house appearance image are respectively obtained through the above steps, in order to be able to objectively and accurately judge whether the current house appearance image meets the above-mentioned first preset requirement, preferably, after the present invention obtains the required house appearance image in real time, it will first call out three-dimensional software such as UG and SolidWorks in real time in the preset database, and further create a corresponding target three-dimensional space therein through the three-dimensional software. At the same time, a number of reference planes are further formed inside the current target three-dimensional space. Specifically, the current number of reference planes are arranged according to the directions of front, back, left, right, up and down. Based on this, in order to facilitate subsequent identification and to improve processing efficiency accordingly, the present invention will further add corresponding target identifiers to each current reference surface, and further filter out local appearance images corresponding to the orientation of each current reference surface in the above-mentioned house appearance image in real time according to the order of the current target identifiers. At the same time, in order to facilitate subsequent processing, it is also necessary to further map each current local appearance image to the interior of the corresponding reference surface, and further perform three-dimensional processing on the corresponding local appearance image inside the current reference surface, so as to further generate the required local three-dimensional model. Based on this, it is only necessary to immediately perform splicing processing on each current local three-dimensional model to correspondingly splice the required three-dimensional model of the house, and at this time it is only necessary to determine in real time whether the surface of the current three-dimensional model of the house is damaged. Specifically, if so, it can be directly determined that there are no defects on the surface of the current target house, and the above-mentioned first preset requirement is met accordingly.

[0103] Further, after judging in real time through the above steps that the above target house meets the first preset requirement, a subsequent secondary judgment will be immediately performed at this time. Preferably, the present invention will further generate a corresponding house internal structure model in real time according to the house structure image currently acquired through the above target three-dimensional program, and map the current house internal structure model to the interior of the above house three-dimensional model accordingly, so as to finally generate the required house overall model. Based on this, the current house overall model is immediately scanned in its entirety, and the required scanned image can be scanned accordingly. At the same time, it is finally judged in real time according to the current scanned image whether there are structural defects such as cracks, collapses and damages inside the current house overall model. Specifically, if not, it can be directly determined that there are no defects on the exterior and interior of the current target house, and a corresponding test report can be further generated. On this basis, in order to improve the confidentiality performance of the test report, corresponding encryption processing will be performed, and the required encrypted report will be finally generated, so that the encrypted report can be sent to the user terminal of the staff accordingly, which correspondingly improves the detection efficiency.

[0104] See also Figure 2 , the third embodiment of the present invention provides:

[0105] A building structure defect detection system, wherein the system comprises:

[0106] A collection module, for collecting a panoramic image corresponding to the target house in real time through a tethered drone when receiving the target house input by the user in real time;

[0107] a parsing module, configured to parse the panoramic image to extract a house structure image and a house appearance image corresponding to the target house from the panoramic image, and determine in real time whether the target house meets a first preset requirement based on the house appearance image based on a first preset rule;

[0108] A judgment module, configured to judge in real time whether the target house meets the first preset requirement based on the house structure image based on a second preset rule, if judging in real time based on the house appearance image based on a first preset rule that the target house meets the first preset requirement;

[0109] The execution module is used to determine that there are no defects in the target house and generate a corresponding inspection report in real time if it is determined in real time based on the second preset rule according to the house structure image that the target house meets the second preset requirement.

[0110] Furthermore, the parsing module is specifically used for:

[0111] When the exterior image of the house is acquired in real time, a matching target three-dimensional program is called out in real time from a preset database;

[0112] A target three-dimensional space is created in real time by the target three-dimensional program, and a plurality of reference planes are created in real time in the target three-dimensional space, wherein the plurality of reference planes are arranged according to preset orientations;

[0113] It is determined whether the target house meets the first preset requirement according to the house appearance image and the correspondence between the plurality of reference planes.

[0114] Furthermore, the parsing module is specifically used for:

[0115] When a plurality of reference surfaces are acquired in real time, a corresponding target identifier is added to each reference surface;

[0116] Based on the target identifier, local appearance images corresponding to the orientation of each reference surface are selected in real time from the house appearance image, and each local appearance image is mapped to the inside of the reference surface corresponding thereto;

[0117] Whether the target house meets the first preset requirement is determined according to each of the local appearance images and each of the reference planes.

[0118] Furthermore, the parsing module is specifically used for:

[0119] When each of the local appearance images is acquired in real time, stereo processing is performed on each of the local appearance images according to the reference plane to generate a corresponding local three-dimensional model in real time;

[0120] Performing splicing processing on each of the local three-dimensional models to generate a three-dimensional house model corresponding to the target house in real time, and determining in real time whether the surface of the three-dimensional house model is damaged;

[0121] If it is determined in real time that the surface of the three-dimensional model of the house is not damaged, then it is correspondingly determined that the surface of the target house has no defects and satisfies the first preset requirement.

[0122] Furthermore, the judgment module is specifically used for:

[0123] When the house structure image is acquired in real time, a corresponding house internal structure model is generated in real time according to the house structure image by the target three-dimensional program;

[0124] The internal structure model of the house is mapped to the interior of the three-dimensional model of the house to generate a corresponding overall model of the house in real time, and whether the target house meets the second preset requirement is determined in real time based on the overall model of the house.

[0125] Furthermore, the judgment module is specifically used for:

[0126] When the overall model of the house is acquired in real time, the overall model of the house is scanned in its entirety to generate a corresponding scanned image in real time;

[0127] Determine in real time whether there are structural defects inside the overall model of the house according to the scanned image;

[0128] If it is determined in real time based on the scanned image that the structural defects do not exist inside the overall model of the house, then it is correspondingly determined that the target house meets the second preset requirement.

[0129] Furthermore, the judgment module is specifically used for:

[0130] When the detection report is obtained in real time, the detection report is encrypted to generate a corresponding encrypted report, and the encrypted report is sent to the user terminal of the staff member accordingly.

[0131] A fourth embodiment of the present invention provides a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the building structure defect detection method as described above when executing the computer program.

[0132] A fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the building structure defect detection method as described above.

[0133] In summary, the building structure defect detection method and system provided by the above embodiments of the present invention can determine whether the target building has defects based on the judgment results, thereby eliminating the process of manual judgment and correspondingly improving the detection accuracy and efficiency.

[0134] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0135] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0136] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0137] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0138] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0139] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A method for detecting structural defects of a building, characterized in that: The method comprises: When receiving the target house input by the user in real time, a panoramic image corresponding to the target house is collected in real time by a tethered drone; Analyzing the panoramic image to extract a house structure image and a house appearance image corresponding to the target house from the panoramic image, and judging in real time whether the target house meets a first preset requirement based on the house appearance image based on a first preset rule; If it is determined in real time based on the first preset rule according to the house appearance image that the target house meets the first preset requirement, it is determined in real time based on the house structure image whether the target house meets the second preset requirement according to the second preset rule; If it is determined in real time based on the second preset rule and according to the house structure image that the target house meets the second preset requirement, it is correspondingly determined that there are no defects in the target house, and a corresponding inspection report is generated in real time.

2. The building structure defect detection method according to claim 1, characterized in that: The step of judging in real time whether the target house meets the first preset requirement according to the house appearance image based on the first preset rule comprises: When the exterior image of the house is acquired in real time, a matching target three-dimensional program is called out in real time from a preset database; A target three-dimensional space is created in real time by the target three-dimensional program, and a plurality of reference planes are created in real time in the target three-dimensional space, wherein the plurality of reference planes are arranged according to preset orientations; It is determined whether the target house meets the first preset requirement according to the house appearance image and the correspondence between the plurality of reference planes.

3. The building structure defect detection method according to claim 2, characterized in that: The step of judging whether the target house meets the first preset requirement according to the house appearance image and the reference planes comprises: When a plurality of reference surfaces are acquired in real time, a corresponding target identifier is added to each reference surface; Based on the target identifier, local appearance images corresponding to the orientation of each reference surface are screened out in real time in the house appearance image, and each local appearance image is mapped to the inside of the reference surface corresponding thereto; Whether the target house meets the first preset requirement is determined according to each of the local appearance images and each of the reference planes.

4. The building structure defect detection method according to claim 3, characterized in that: The step of judging whether the target house meets the first preset requirement according to each of the local appearance images and each of the reference planes comprises: When each of the local appearance images is acquired in real time, stereo processing is performed on each of the local appearance images according to the reference plane to generate a corresponding local three-dimensional model in real time; Performing splicing processing on each of the local three-dimensional models to generate a three-dimensional house model corresponding to the target house in real time, and determining in real time whether the surface of the three-dimensional house model is damaged; If it is determined in real time that the surface of the three-dimensional model of the house is not damaged, then it is correspondingly determined that the surface of the target house has no defects and satisfies the first preset requirement.

5. The building structure defect detection method according to claim 4, characterized in that: The step of judging in real time whether the target house meets the second preset requirement according to the house structure image based on the second preset rule comprises: When the house structure image is acquired in real time, a corresponding house internal structure model is generated in real time according to the house structure image by the target three-dimensional program; The internal structure model of the house is mapped to the interior of the three-dimensional model of the house to generate a corresponding overall model of the house in real time, and whether the target house meets the second preset requirement is determined in real time based on the overall model of the house.

6. The building structure defect detection method according to claim 5, characterized in that: The step of determining in real time whether the target house meets the second preset requirement according to the overall house model comprises: When the overall model of the house is acquired in real time, the overall model of the house is scanned in its entirety to generate a corresponding scanned image in real time; Determine in real time whether there are structural defects inside the overall model of the house according to the scanned image; If it is determined in real time based on the scanned image that the structural defects do not exist inside the overall model of the house, then it is correspondingly determined that the target house meets the second preset requirement.

7. The building structure defect detection method according to claim 6, characterized in that: The step of generating a corresponding test report in real time comprises: When the detection report is obtained in real time, the detection report is encrypted to generate a corresponding encrypted report, and the encrypted report is sent to the user terminal of the staff member accordingly.

8. A building structure defect detection system, characterized in that: The system comprises: A collection module, for collecting a panoramic image corresponding to the target house in real time through a tethered drone when receiving the target house input by the user in real time; a parsing module, configured to parse the panoramic image to extract a house structure image and a house appearance image corresponding to the target house from the panoramic image, and determine in real time whether the target house meets a first preset requirement based on the house appearance image based on a first preset rule; A judgment module, configured to judge in real time whether the target house meets the first preset requirement based on the house structure image based on a second preset rule, if judging in real time based on the house appearance image based on a first preset rule that the target house meets the first preset requirement; The execution module is used to determine that there are no defects in the target house and generate a corresponding inspection report in real time if it is determined in real time based on the second preset rule according to the house structure image that the target house meets the second preset requirement.

9. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the building structure defect detection method as described in any one of claims 1 to 7 is implemented.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the building structure defect detection method as described in any one of claims 1 to 7 is implemented.

Images