A communication tower structure defect detection method and system

Abstract

This invention relates to the field of defect detection technology and provides a method and system for detecting structural defects in communication towers. The method includes the following steps: receiving strain information uploaded by a strain sensor, the strain information including the sensor number and strain data; determining the strain location and stress on the communication tower based on the strain information; marking the strain location and stress in the finite element model of the tower, and determining relevant structural beam information based on the strain location and stress; determining aerial photography information based on the relevant structural beam information, the aerial photography information including several aerial photography numbers, each corresponding to an aerial photography position and angle; receiving aerial photography detection images, each aerial photography detection image being bound to an aerial photography number; retrieving non-destructive images of the structural beams based on the aerial photography numbers; comparing the non-destructive images of the structural beams with the corresponding aerial photography detection images to determine the defect area. This invention only requires relatively detailed aerial photography of the relevant structural beams, significantly improving the efficiency of UAV aerial photography and image processing speed.

Description

Technical Field

[0001] This invention relates to the field of defect detection technology, specifically to a method and system for detecting structural defects in communication towers. Background Technology

[0002] Currently, the main methods for detecting structural defects in communication towers include manual inspection and drone-based detection. Manual inspection involves inspectors carrying binoculars and using vehicles or walking to visually inspect the towers. This method is relatively mature and can detect some existing defects and even more serious ones. However, it is labor-intensive and often cannot be carried out in mountainous areas or areas affected by natural disasters, nor can it identify defects in various blind spots at higher tower locations.

[0003] While drone-based identification and detection methods can obtain a wider range of tower inspection data, primarily using image recognition to identify tower defects, the large size of communication towers makes it difficult to quickly acquire clear images of every structural beam using drone aerial photography, resulting in the failure to detect minor structural defects. Therefore, a method and system for detecting structural defects in communication towers are needed to address these issues. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a method and system for detecting structural defects in communication towers, so as to solve the problems existing in the above-mentioned background technology.

[0005] This invention is implemented as follows: a method for detecting structural defects in communication towers, the method comprising the following steps:

[0006] Receive strain information uploaded by a strain sensor, the strain information including sensor number and strain data;

[0007] Determine the strain location and stress on the communication tower based on strain information;

[0008] The strain location and stress are marked in the finite element model of the tower, and the relevant structural beam information is determined based on the strain location and stress.

[0009] Aerial photography information is determined based on relevant structural beam information. The aerial photography information includes several aerial photography numbers, each aerial photography number corresponding to an aerial photography position and angle. Aerial photography detection images are received, and each aerial photography detection image is bound to an aerial photography number.

[0010] Based on the aerial photography number, retrieve the non-destructive image of the structural beam, compare the non-destructive image of the structural beam with the corresponding aerial inspection image, and determine the defect area.

[0011] As a further aspect of the present invention: the step of determining the strain location and stress on the communication tower based on strain information specifically includes:

[0012] Input the sensor number into the sensor installation information database, which includes all sensor numbers. Each sensor number corresponds to the strain location, strain direction and elastic modulus.

[0013] Output the corresponding strain location, strain direction, and elastic modulus. Calculate the stress based on the strain data, strain direction, and elastic modulus.

[0014] As a further aspect of the present invention: the step of determining the relevant structural beam information based on strain location and stress specifically includes:

[0015] The stress is added one by one at the corresponding strain positions in the finite element model of the tower;

[0016] The first structural beam that experiences strain in the finite element model of the iron tower is retrieved, the stress added in the finite element model of the iron tower is removed, the mechanical properties of the retrieved first structural beam are adjusted, and the second structural beam that experiences strain at this time is determined.

[0017] Based on the strain information, determine whether the second structural beam has actually experienced strain. If yes, determine the corresponding first structural beam as the relevant structural beam; if no, determine the corresponding first structural beam as the normal structural beam.

[0018] Information on all identified structural beams is obtained by summarizing all relevant structural beams.

[0019] As a further aspect of the present invention: the step of determining aerial photography information based on relevant structural beam information specifically includes:

[0020] Extract the structural beam number from the relevant structural beam information;

[0021] Input the structural beam number into the aerial photography parameter library, which contains all structural beam numbers. Each structural beam number corresponds to an aerial photography number, aerial photography position, aerial photography angle, and a non-destructive image of the structural beam.

[0022] Output the corresponding aerial photography number, location, and angle, and integrate them to obtain the aerial photography information.

[0023] As a further aspect of the present invention: the step of comparing the non-destructive image of the structural beam with the corresponding aerial inspection image to determine the defect area specifically includes:

[0024] The aerial inspection image is rotated, scaled, and cropped based on the non-destructive image of the structural beam to ensure consistency between the two;

[0025] Import corresponding non-destructive images and aerial inspection images of structural beams, and use OpenCV's subtract function to determine the distinguishing regions between the aerial inspection images and the non-destructive images of structural beams;

[0026] Based on the distinguishing regions, the defective regions are determined and marked.

[0027] As a further aspect of the present invention: the step of rotating, scaling, and cropping the aerial inspection image based on the non-destructive image of the structural beam specifically includes:

[0028] Identify the main structural beams in non-destructive images and aerial inspection images of structural beams;

[0029] The main structural beams are sharpened and outlined, and the aerial inspection images are rotated, scaled, and cropped based on the contour differences between the two main structural beams.

[0030] Another object of the present invention is to provide a communication tower structural defect detection system, the system comprising:

[0031] The strain information receiving module is used to receive strain information uploaded by the strain sensor, the strain information including the sensor number and strain data;

[0032] The stress information determination module is used to determine the strain location and stress on the communication tower based on strain information.

[0033] The relevant structural beam module is used to mark the strain location and stress in the finite element model of the tower, and to determine the relevant structural beam information based on the strain location and stress.

[0034] The aerial photography information determination module is used to determine aerial photography information based on relevant structural beam information. The aerial photography information includes several aerial photography numbers, each aerial photography number corresponding to an aerial photography position and an aerial photography angle. It receives aerial photography detection images, and each aerial photography detection image is bound to an aerial photography number.

[0035] The defect area determination module is used to retrieve the non-destructive image of the structural beam based on the aerial photography number, compare the non-destructive image of the structural beam with the corresponding aerial inspection image, and determine the defect area.

[0036] As a further aspect of the present invention: the stress information determination module includes:

[0037] The sensor number input unit is used to input the sensor number into the sensor installation information database, which includes all sensor numbers, and each sensor number corresponds to the strain location, strain direction and elastic modulus.

[0038] The stress calculation unit is used to output the corresponding strain location, strain direction, and elastic modulus, and to calculate the stress based on the strain data, strain direction, and elastic modulus.

[0039] As a further aspect of the present invention: the relevant structural beam module includes:

[0040] The model stress-adding element is used to add the stress at the corresponding strain positions of the finite element model of the tower one by one;

[0041] The mechanical property adjustment unit is used to retrieve the first structural beam that has undergone strain in the finite element model of the iron tower, remove the stress added in the finite element model of the iron tower, adjust the mechanical properties of the retrieved first structural beam, and determine the second structural beam that has undergone strain at this time.

[0042] The structural beam strain determination unit is used to determine whether the second structural beam has actually experienced strain based on strain information. If it has, the corresponding first structural beam is determined to be a relevant structural beam; if not, the corresponding first structural beam is determined to be a normal structural beam.

[0043] The structural beam information aggregation unit is used to aggregate all identified relevant structural beams to obtain relevant structural beam information.

[0044] As a further aspect of the present invention: the aerial photography information determination module includes:

[0045] The structural beam number extraction unit is used to extract the number of each structural beam from the relevant structural beam information;

[0046] The structural beam number input unit is used to input the structural beam number into the aerial photography parameter library. The aerial photography parameter library contains all structural beam numbers, and each structural beam number corresponds to an aerial photography number, aerial photography position, aerial photography angle, and a non-destructive image of the structural beam.

[0047] The aerial photography information determination unit is used to output the corresponding aerial photography number, aerial photography location, and aerial photography angle, and integrate them to obtain aerial photography information.

[0048] Compared with the prior art, the beneficial effects of the present invention are:

[0049] This invention determines the strain location and stress on a communication tower based on strain information, marks the strain location and stress in the tower's finite element model, determines relevant structural beam information based on the strain location and stress, and then determines aerial photography information based on the relevant structural beam information. Thus, only relatively detailed aerial photography of the relevant structural beams is required, significantly improving the efficiency of UAV aerial photography and image processing speed. Furthermore, this invention retrieves non-destructive images of the structural beams based on the aerial photography number, compares these images with the corresponding aerial inspection images to determine defect areas, making image comparison and recognition more accurate and efficient. Attached Figure Description

[0050] Figure 1 This is a flowchart of a method for detecting structural defects in communication towers.

[0051] Figure 2 This is a flowchart for determining strain location and stress in a method for detecting structural defects in communication towers.

[0052] Figure 3 This is a flowchart illustrating the process of determining relevant structural beam information based on strain location and stress in a method for detecting structural defects in communication towers.

[0053] Figure 4 This is a flowchart illustrating the process of determining aerial photographic information based on relevant structural beam information in a method for detecting structural defects in communication towers.

[0054] Figure 5 This is a flowchart illustrating the process of determining the defect area in a method for detecting structural defects in communication towers.

[0055] Figure 6 This is a flowchart illustrating the rotation, scaling, and cropping of aerial images in a method for detecting structural defects in communication towers.

[0056] Figure 7 This is a schematic diagram of a communication tower structural defect detection system.

[0057] Figure 8 This is a schematic diagram of the stress information determination module in a communication tower structural defect detection system.

[0058] Figure 9 This is a structural diagram of a structural beam module in a communication tower structural defect detection system.

[0059] Figure 10 This is a schematic diagram of the aerial information determination module in a communication tower structural defect detection system. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0061] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0062] like Figure 1 As shown in the figure, this invention provides a method for detecting structural defects in communication towers, the method comprising the following steps:

[0063] S100, Receive strain information uploaded by strain sensor, the strain information including sensor number and strain data;

[0064] S200 determines the strain location and stress on the communication tower based on strain information;

[0065] S300 marks the strain location and stress in the finite element model of the tower, and determines the relevant structural beam information based on the strain location and stress.

[0066] S400, determine aerial photography information based on relevant structural beam information. The aerial photography information includes several aerial photography numbers, each aerial photography number corresponding to an aerial photography position and angle. Receive aerial photography detection images, each aerial photography detection image being bound to an aerial photography number.

[0067] The S500 retrieves the non-destructive image of the structural beam based on the aerial photography number, compares the non-destructive image of the structural beam with the corresponding aerial inspection image, and determines the defect area.

[0068] It should be noted that the UAV identification and detection method can obtain a wider range of tower inspection data. It mainly uses image recognition to identify tower defects. However, due to the large size of communication towers, it is difficult to quickly obtain clear images of each structural beam through UAV aerial photography, resulting in the problem that small structural defects are not detected. The embodiments of the present invention aim to solve the above problems.

[0069] In this embodiment of the invention, a finite element model of the communication tower is first constructed. This model reveals the stress conditions of various structural components within the tower. Then, numerous strain sensors are installed on the tower, their placement determined by the structural stress. After installation, the strain sensors transmit strain information, including sensor numbers and strain data. This embodiment automatically determines the strain locations and stresses on the tower based on this information, marking these locations and stresses in the finite element model. Based on the strain locations and stresses, relevant structural beam information is determined. This information includes one or more related structural beams, which may contain defects that are the primary cause of strain. Aerial photography information can then be determined based on this beam information, requiring only detailed aerial photography of the relevant structural beams. This significantly improves the efficiency of UAV aerial photography and image processing speed. The aerial photography information includes several aerial photography numbers, each corresponding to an aerial photography location and angle. The UAV simply needs to reach the designated location and take photos at the specified angle, making the process quick and convenient. After the drone completes the shooting, it sends aerial inspection images. Each aerial inspection image is bound to an aerial inspection number. Then, in this embodiment of the invention, the undamaged image of the structural beam is retrieved according to the aerial inspection number. The undamaged image of the structural beam is compared with the corresponding aerial inspection image to determine the defect area. The undamaged image of the structural beam is a picture of the intact beam structure obtained in advance according to the aerial inspection position and angle. In this way, the image comparison and recognition is more accurate and efficient.

[0070] like Figure 2 As shown, in a preferred embodiment of the present invention, the step of determining the strain location and stress on the communication tower based on strain information specifically includes:

[0071] S201, Input the sensor number into the sensor installation information database. The sensor installation information database includes all sensor numbers, and each sensor number corresponds to the strain location, strain direction and elastic modulus.

[0072] S202 outputs the corresponding strain location, strain direction, and elastic modulus. The stress is calculated based on the strain data, strain direction, and elastic modulus.

[0073] In this embodiment of the invention, a sensor installation information database is established in advance. The sensor installation information database includes the numbers of all installed sensors. Each sensor number corresponds to the strain position, strain direction and elastic modulus. When the sensor number is input into the sensor installation information database, the corresponding strain position, strain direction and elastic modulus will be automatically output. The stress can be calculated based on the strain data, strain direction and elastic modulus.

[0074] like Figure 3 As shown, in a preferred embodiment of the present invention, the step of determining the relevant structural beam information based on strain location and stress specifically includes:

[0075] S301, add the stress at the corresponding strain position of the finite element model of the tower one by one;

[0076] S302, retrieve the first structural beam that has undergone strain in the finite element model of the iron tower, cancel the stress added in the finite element model of the iron tower, adjust the mechanical properties of the retrieved first structural beam, and determine the second structural beam that has undergone strain at this time;

[0077] S303, determine whether the second structural beam has actually experienced strain based on the strain information. If yes, determine the corresponding first structural beam as the relevant structural beam; if no, determine the corresponding first structural beam as the normal structural beam.

[0078] S304, summarize all identified relevant structural beams to obtain relevant structural beam information.

[0079] In this embodiment of the invention, to identify potentially defective structural beams, stress is added to the corresponding strain locations in the finite element model of the tower. Adding external force to the tower's finite element model inevitably causes strain in other parts of the model. At this point, the first structural beam exhibiting strain in the tower's finite element model is retrieved, and then the added stress is removed. The first structural beam is likely the defective beam. The mechanical properties of the retrieved first structural beam are adjusted; these properties can include material properties and stress properties. Next, the second structural beam exhibiting strain is identified. The strain in the second structural beam is due to a change in the mechanical properties of the first structural beam. If the second structural beam exists in the strain information, it indicates that the second structural beam has indeed undergone strain, and the mechanical properties of the corresponding first structural beam are likely to have changed in the actual structure. Based on this, it can be determined whether the second structural beam has actually undergone strain based on the strain information. If so, the corresponding first structural beam is identified as a defective structural beam; otherwise, it is identified as a normal structural beam. Finally, all identified defective structural beams are summarized to obtain the relevant structural beam information.

[0080] like Figure 4 As shown in the preferred embodiment of the present invention, the step of determining aerial photography information based on relevant structural beam information specifically includes:

[0081] S401, extract the structural beam number from the relevant structural beam information;

[0082] S402, input the structural beam number into the aerial photography parameter library. The aerial photography parameter library contains all structural beam numbers. Each structural beam number corresponds to an aerial photography number, aerial photography position, aerial photography angle, and a non-destructive image of the structural beam.

[0083] S403 outputs the corresponding aerial photography number, location, and angle, which are then integrated to obtain the aerial photography information.

[0084] In this embodiment of the invention, an aerial photography parameter library is established in advance. The aerial photography parameter library contains all structural beam numbers. Each structural beam number corresponds to an aerial photography number, aerial photography position, aerial photography angle, and a non-destructive image of the structural beam. By inputting the structural beam number into the aerial photography parameter library, aerial photography information containing the aerial photography number, aerial photography position, and aerial photography angle can be directly obtained.

[0085] like Figure 5 As shown, in a preferred embodiment of the present invention, the step of comparing the non-destructive image of the structural beam with the corresponding aerial inspection image to determine the defect area specifically includes:

[0086] S501, rotate, scale and crop the aerial inspection image based on the non-destructive image of the structural beam to make the two correspond to each other;

[0087] S502: Import the corresponding non-destructive image and aerial inspection image of the structural beam, and determine the difference region between the aerial inspection image and the non-destructive image of the structural beam based on the subtract function of OpenCV.

[0088] S503, Determine the defect area based on the distinguishing area, and mark the defect area.

[0089] In this embodiment of the invention, before comparing and identifying the non-destructive image of the structural beam with the corresponding aerial inspection image, the aerial inspection image needs to be rotated, scaled, and cropped to ensure that the two correspond. Then, the corresponding non-destructive image of the structural beam and the aerial inspection image are imported into the image software. Based on the subtract function of OpenCV, the difference regions between the aerial inspection image and the non-destructive image of the structural beam are determined. These difference regions are the defect regions.

[0090] like Figure 6 As shown, in a preferred embodiment of the present invention, the step of rotating, scaling, and cropping the aerial inspection image based on the non-destructive image of the structural beam specifically includes:

[0091] S5011, identify the main structural beam in non-destructive images and aerial inspection images of structural beams;

[0092] S5012, sharpen the outline of the main structural beam, and rotate, scale and crop the aerial detection image according to the contour difference of the main structural beam.

[0093] In this embodiment of the invention, it is easy to understand that both the non-destructive image of the structural beam and the aerial inspection image contain a main structural beam, i.e. the subject of the photograph. The main structural beam is sharpened and outlined. The aerial inspection image is rotated, scaled, and cropped according to the contour differences of the main structural beams in the two images, so that the size and position of the contours of the two main structural beams are completely corresponding, and the sizes of the two images are corresponding.

[0094] like Figure 7 As shown in the figure, this embodiment of the invention also provides a communication tower structural defect detection system, the system comprising:

[0095] The strain information receiving module 100 is used to receive strain information uploaded by the strain sensor, the strain information including the sensor number and strain data;

[0096] The stress information determination module 200 is used to determine the strain location and stress on the communication tower based on strain information.

[0097] The related structural beam module 300 is used to mark the strain location and stress in the finite element model of the tower and determine the related structural beam information based on the strain location and stress.

[0098] The aerial photography information determination module 400 is used to determine aerial photography information based on relevant structural beam information. The aerial photography information includes several aerial photography numbers, each aerial photography number corresponding to an aerial photography position and an aerial photography angle. It receives aerial photography detection images, and each aerial photography detection image is bound to an aerial photography number.

[0099] The defect area determination module 500 is used to retrieve the non-destructive image of the structural beam according to the aerial photography number, compare the non-destructive image of the structural beam with the corresponding aerial photography inspection image, and determine the defect area.

[0100] like Figure 8 As shown, in a preferred embodiment of the present invention, the stress information determination module 200 includes:

[0101] The sensor number input unit 201 is used to input the sensor number into the sensor installation information database, which includes all sensor numbers, and each sensor number corresponds to the strain position, strain direction and elastic modulus.

[0102] The stress calculation unit 202 is used to output the corresponding strain location, strain direction and elastic modulus, and to calculate the stress based on the strain data, strain direction and elastic modulus.

[0103] like Figure 9 As shown, in a preferred embodiment of the present invention, the related structural beam module 300 includes:

[0104] The model stress adding unit 301 is used to add the stress one by one at the corresponding strain position of the finite element model of the iron tower;

[0105] The mechanical property adjustment unit 302 is used to retrieve the first structural beam that has undergone strain in the finite element model of the iron tower, cancel the stress added in the finite element model of the iron tower, adjust the mechanical properties of the retrieved first structural beam, and determine the second structural beam that has undergone strain at this time.

[0106] The structural beam strain determination unit 303 is used to determine whether the second structural beam has actually experienced strain based on the strain information. If it has, the corresponding first structural beam is determined to be a related structural beam; if not, the corresponding first structural beam is determined to be a normal structural beam.

[0107] The structural beam information aggregation unit 304 is used to aggregate all identified relevant structural beams to obtain relevant structural beam information.

[0108] like Figure 10 As shown, in a preferred embodiment of the present invention, the aerial photography information determination module 400 includes:

[0109] Structural beam number extraction unit 401 is used to extract each structural beam number from the relevant structural beam information;

[0110] The structural beam number input unit 402 is used to input the structural beam number into the aerial photography parameter library. The aerial photography parameter library contains all structural beam numbers, and each structural beam number corresponds to an aerial photography number, aerial photography position, aerial photography angle, and a non-destructive image of the structural beam.

[0111] The aerial photography information determination unit 403 is used to output the corresponding aerial photography number, aerial photography location and aerial photography angle, and integrate them to obtain aerial photography information.

[0112] The above description only details the preferred embodiments of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0113] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0114] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0115] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the disclosure in the specification and embodiments. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

Claims

1. A method for detecting structural defects in communication towers, characterized in that, The method includes the following steps: Receive strain information uploaded by a strain sensor, the strain information including sensor number and strain data; Determine the strain location and stress on the communication tower based on strain information; The strain location and stress are marked in the finite element model of the tower, and the relevant structural beam information is determined based on the strain location and stress. Aerial photography information is determined based on relevant structural beam information. The aerial photography information includes several aerial photography numbers, each aerial photography number corresponding to an aerial photography position and angle. Aerial photography detection images are received, and each aerial photography detection image is bound to an aerial photography number. Retrieve the non-destructive image of the structural beam based on the aerial photography number, compare the non-destructive image of the structural beam with the corresponding aerial inspection image, and determine the defect area; The step of determining the strain location and stress on the communication tower based on strain information specifically includes: inputting the sensor number into the sensor installation information database, which includes all sensor numbers, each corresponding to a strain location, strain direction, and elastic modulus; outputting the corresponding strain location, strain direction, and elastic modulus; and calculating the stress based on the strain data, strain direction, and elastic modulus. The step of determining the relevant structural beam information based on strain location and stress specifically includes: adding the stress at the corresponding strain location in the finite element model of the tower one by one; retrieving the first structural beam in the finite element model of the tower that has experienced strain, removing the stress added in the finite element model of the tower, adjusting the mechanical properties of the retrieved first structural beam, and determining the second structural beam that has experienced strain at this time; determining whether the second structural beam has actually experienced strain based on the strain information; if yes, determining the corresponding first structural beam as the relevant structural beam; if no, determining the corresponding first structural beam as the normal structural beam; and summarizing all determined relevant structural beams to obtain the relevant structural beam information.

2. The method for detecting structural defects in communication towers according to claim 1, characterized in that, The step of determining aerial photography information based on relevant structural beam information specifically includes: Extract the structural beam number from the relevant structural beam information; Input the structural beam number into the aerial photography parameter library, which contains all structural beam numbers. Each structural beam number corresponds to an aerial photography number, aerial photography position, aerial photography angle, and a non-destructive image of the structural beam. Output the corresponding aerial photography number, location, and angle, and integrate them to obtain the aerial photography information.

3. The method for detecting structural defects in communication towers according to claim 1, characterized in that, The step of comparing the non-destructive image of the structural beam with the corresponding aerial inspection image to determine the defect area specifically includes: The aerial inspection image is rotated, scaled, and cropped based on the non-destructive image of the structural beam to ensure consistency between the two; Import corresponding non-destructive images and aerial inspection images of structural beams, and use OpenCV's subtract function to determine the distinguishing regions between the aerial inspection images and the non-destructive images of structural beams; Based on the distinguishing regions, the defective regions are determined and marked.

4. The method for detecting structural defects in communication towers according to claim 3, characterized in that, The steps of rotating, scaling, and cropping the aerial inspection image based on the non-destructive image of the structural beam specifically include: Identify the main structural beams in non-destructive images and aerial inspection images of structural beams; The main structural beams are sharpened and outlined, and the aerial inspection images are rotated, scaled, and cropped based on the contour differences between the two main structural beams.

5. A communication tower structural defect detection system, used to perform the communication tower structural defect detection method as described in any one of claims 1 to 4, characterized in that, The system includes: The strain information receiving module is used to receive strain information uploaded by the strain sensor, the strain information including the sensor number and strain data; The stress information determination module is used to determine the strain location and stress on the communication tower based on strain information. The relevant structural beam module is used to mark the strain location and stress in the finite element model of the tower, and to determine the relevant structural beam information based on the strain location and stress. The aerial photography information determination module is used to determine aerial photography information based on relevant structural beam information. The aerial photography information includes several aerial photography numbers, each aerial photography number corresponding to an aerial photography position and an aerial photography angle. It receives aerial photography detection images, and each aerial photography detection image is bound to an aerial photography number. The defect area determination module is used to retrieve the non-destructive image of the structural beam based on the aerial photography number, compare the non-destructive image of the structural beam with the corresponding aerial inspection image, and determine the defect area.

6. The communication tower structural defect detection system according to claim 5, characterized in that, The stress information determination module includes: The sensor number input unit is used to input the sensor number into the sensor installation information database, which includes all sensor numbers, and each sensor number corresponds to the strain location, strain direction and elastic modulus. The stress calculation unit is used to output the corresponding strain location, strain direction, and elastic modulus, and to calculate the stress based on the strain data, strain direction, and elastic modulus.

7. The communication tower structural defect detection system according to claim 5, characterized in that, The relevant structural beam module includes: The model stress-adding element is used to add the stress at the corresponding strain positions of the finite element model of the tower one by one; The mechanical property adjustment unit is used to retrieve the first structural beam that has undergone strain in the finite element model of the iron tower, remove the stress added in the finite element model of the iron tower, adjust the mechanical properties of the retrieved first structural beam, and determine the second structural beam that has undergone strain at this time. The structural beam strain determination unit is used to determine whether the second structural beam has actually experienced strain based on strain information. If it has, the corresponding first structural beam is determined to be a relevant structural beam; if not, the corresponding first structural beam is determined to be a normal structural beam. The structural beam information aggregation unit is used to aggregate all identified relevant structural beams to obtain relevant structural beam information.

8. The communication tower structural defect detection system according to claim 5, characterized in that, The aerial photography information determination module includes: The structural beam number extraction unit is used to extract the number of each structural beam from the relevant structural beam information; The structural beam number input unit is used to input the structural beam number into the aerial photography parameter library. The aerial photography parameter library contains all the structural beam numbers, and each structural beam number corresponds to an aerial photography number, aerial photography position, aerial photography angle, and a non-destructive image of the structural beam. The aerial photography information determination unit is used to output the corresponding aerial photography number, aerial photography location, and aerial photography angle, and integrate them to obtain aerial photography information.

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