Glass curtain wall facing wall climbing robot and automatic detection method

Abstract

The application discloses a wall-climbing robot for a glass curtain wall and an automatic detection method. The wall-climbing robot comprises a robot body and a multifunctional detection device integrated on the robot body, and the robot body is provided with a wireless transmission device and a wall-climbing device. The multifunctional detection device comprises an excitation source device, an impact sensing device and a visual detection device. The excitation source device is used for providing a preset quality excitation source, the impact sensing device is used for collecting impact sensing information, and the visual detection device is used for collecting image information. The application can realize comprehensive automatic detection of a target glass curtain wall, efficient and accurate detection of defects of the target glass curtain wall, high automation level, short detection period and greatly improved safety factor.

Description

Technical Field

[0001] This disclosure relates to the field of structural engineering damage detection, and in particular to a wall-climbing robot for glass curtain walls and an automated detection method. Background Technology

[0002] Glass curtain walls are multifunctional building envelope structures that integrate lighting, rain protection, wind protection, and thermal insulation. With the increasing aesthetic demands of urban construction and the growing need for high-rise buildings, glass curtain walls, as a synthesis of architectural technology, function, structure, and art, have been widely used in the field of building structures, especially in high-rise buildings. Due to the diverse range of architectural designs and the structural characteristics required by high-rise buildings, the forms and structural support methods of glass curtain walls have become increasingly complex. Under the long-term effects of wind and temperature loads under normal conditions, high-rise glass curtain walls will inevitably develop some defects over time, such as scratches and spontaneous breakage of glass panels, aging and corrosion of structural adhesives, and stress relaxation and deformation of the supporting structure.

[0003] Currently, most glass curtain wall inspections rely on human operators working at heights to inspect the quality of each pane of glass. This manual inspection is inefficient, costly, and dangerous. Furthermore, existing automated inspection methods, such as photoelasticity, are only effective for detecting spontaneous breakage defects in safety glass, while natural vibration methods can only detect defects in the bottom curtain wall structure and cannot meet the comprehensive damage inspection needs of high-rise glass curtain walls.

[0004] In summary, the existing publicly available solutions cannot achieve comprehensive detection of hidden damage to glass panels, structural adhesives, and supporting structures. The detection results obtained are relatively one-sided, resulting in limited testing areas, long testing cycles, and low detection accuracy. Summary of the Invention

[0005] In view of this, the present disclosure provides a wall-climbing robot for glass curtain walls and an automated inspection method, which at least partially solves the problems of long inspection cycle, one-sided inspection results and low inspection accuracy in the prior art.

[0006] In a first aspect, embodiments of this disclosure provide a wall-climbing robot for glass curtain walls, comprising:

[0007] The robot body is equipped with a wireless transmission device, a wall-climbing device, and a support device.

[0008] The support device includes a support connector and a vacuum suction cup with an air damping and vibration isolation unit, wherein the vacuum suction cup is used to adhere to the adjacent units on both sides of the glass curtain wall unit to be tested.

[0009] A multi-functional detection device is integrated into the robot body; the multi-functional detection device includes an excitation source device, an impact sensing device, and a visual detection device. The excitation source device is used to provide a preset mass excitation source, the impact sensing device is used to collect impact sensing information, and the visual detection device is used to collect image information.

[0010] Optionally, the excitation source device includes a lifting support and a high-precision fully automatic force hammer with an air damping and vibration isolation unit;

[0011] The impact sensing device includes a low-frequency accelerometer, an ultrasonic sensor, a low-frequency microphone, a microwave radar, and a miniature laser Doppler vibration meter; the miniature laser Doppler vibration meter and the microwave radar are mounted on the robot body via a rotating device;

[0012] The visual inspection equipment includes an industrial camera, a hyperspectral sensor, and a 3D scanner.

[0013] A second aspect of this application provides an automated inspection method for glass curtain walls, the method comprising:

[0014] Construct a three-dimensional model based on the actual information of the target glass curtain wall;

[0015] Finite element analysis is performed on the three-dimensional model to obtain simulated modal response information; wherein, the simulated modal response information includes several mode shapes, the natural frequencies corresponding to each mode shape, and the damage level range;

[0016] Based on the simulated modal response information, a detection strategy is obtained; wherein, the detection strategy includes a modal measurement sensor selection strategy, a modal measurement detection point setting position, and a modal measurement robot walking path, and the modal measurement detection point setting position is a measurement point position that can excite all target modes;

[0017] Based on the detection strategy, an excitation test is performed to obtain actual natural frequency response information; wherein, the actual natural frequency response information includes several actual natural frequency mode shapes and fundamental frequencies of each mode.

[0018] Based on the simulated modal response information and the actual natural frequency response information, the defect type of the target glass curtain wall is obtained.

[0019] Optionally, performing finite element analysis on the three-dimensional model to obtain simulated modal response information includes:

[0020] Based on the aforementioned three-dimensional model, a finite element model is established;

[0021] The finite element model is analyzed based on preset parameters to obtain the simulated modal response information;

[0022] The preset parameters include material properties and boundary conditions.

[0023] Optionally, the several modes of vibration include the first mode of vibration, the second mode of vibration, the third mode of vibration, the fourth mode of vibration, and the fifth mode of vibration of the curtain wall unit component.

[0024] Optionally, the damage level range includes a single damage range and a mixed damage range. The single damage range includes a no-damage segment and multiple-damage segments, and the mixed damage range includes a no-single-damage segment, a single-double-damage segment, and a double-triple-damage segment.

[0025] Optionally, the step of performing stimulus testing based on the detection strategy to obtain actual inherent frequency response information includes:

[0026] Based on the modal measurement sensor selection strategy, modal measurement sensors are deployed at the modal measurement detection points, and a high-precision fully automatic force hammer is used for excitation to obtain the actual natural frequency response information.

[0027] Optionally, the several orders of actual natural frequency mode shapes include the first order actual natural frequency mode shape, the second order actual natural frequency mode shape, the third order actual natural frequency mode shape, the fourth order actual natural frequency mode shape, and the fifth order actual natural frequency mode shape.

[0028] The fundamental frequencies of each modal include the first, second, third, fourth, and fifth vibration frequencies.

[0029] Optionally, obtaining the defect type of the target glass curtain wall based on the simulated modal response information and the actual natural frequency response information includes:

[0030] Based on the actual inherent frequency response information, the inherent frequency test frequency is obtained;

[0031] Determine whether the natural frequency test frequency belongs to the single damage range. If so, directly obtain the defect type of the target glass curtain wall.

[0032] If not, the inherent frequency test frequency is processed according to a preset error to obtain a corrected data range;

[0033] Based on the range of mixed damage, the defect type of the target glass curtain wall is obtained.

[0034] Optionally, before constructing the 3D model, the method further includes: determining whether the target glass curtain wall has a preset crack state based on the actual information of the target glass curtain wall;

[0035] If so, the target glass curtain wall is determined to be an abnormal area, and a new target area without the preset crack state is selected for detection.

[0036] An updated 3D model is constructed based on the target region to be detected.

[0037] The wall-climbing robot for glass curtain walls disclosed in this application can perform automated field testing, enabling damage detection of glass curtain walls at high altitudes and in areas inaccessible to inspection personnel. It also allows for non-destructive testing of glass curtain wall structures. Furthermore, this solution efficiently integrates impact-vibration, impact-response, microwave radar, laser Doppler vibration measurement, machine vision, and hyperspectral testing methods. During the inspection process, it can achieve efficient detection and real-time analysis of the safety performance of glass curtain wall structures, effectively improving the accuracy and efficiency of damage detection testing for glass curtain wall structures.

[0038] The automated detection method for structural defects in glass curtain walls provided in this disclosure first collects actual information about the target glass curtain wall to ensure that the constructed model is consistent with the target glass curtain wall information; then, it simulates and analyzes the constructed three-dimensional model under ideal conditions to obtain theoretical data information to guide the actual measurement of the target glass curtain wall; finally, it compares and analyzes the measured data to accurately and comprehensively obtain the defect types of the target glass curtain wall, with a high degree of automation, high precision, high reliability, and high safety level.

[0039] The above description is merely an overview of the technical solution disclosed herein. In order to better understand the technical means of this disclosure and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart illustrating a specific embodiment of the automated inspection method for glass curtain walls in this application.

[0042] Figure 2 for Figure 1 A flowchart illustrating the method for obtaining simulated modal response information.

[0043] Figure 3 This is a schematic diagram of the first five modal vibration frequencies of a curtain wall unit component.

[0044] Figure 4 This is a trend graph showing the first five natural frequencies of curtain wall unit components under different damage types.

[0045] Figure 5 for Figure 1 A flowchart illustrating the method for obtaining the defect types of the target glass curtain wall.

[0046] Figure 6 This is a three-dimensional schematic diagram of the wall-climbing robot facing a glass curtain wall in this application.

[0047] Figure 7 for Figure 6 Another perspective diagram.

[0048] Figure 8 for Figure 6 A diagram showing the view from below.

[0049] Figure 9 This is a perspective diagram illustrating the types of defects in a glass curtain wall.

[0050] Figure 10 This is a schematic diagram of the damage to the supporting structure.

[0051] Figure 11 This is a schematic diagram of the function of a support bracket with a vacuum suction cup.

[0052] Figure 12 This is a side view of a support bracket with a vacuum suction cup.

[0053] Figure 13 This is a flowchart illustrating another specific embodiment of the automated inspection method for glass curtain walls in this application.

[0054] Figure 14 This is a schematic diagram of the framework of the automated inspection system for glass curtain walls in this application.

[0055] Explanation of reference numerals in the attached drawings: 1. Wall-climbing robot; 11. Robot body; 12. Wireless transmission device; 13. Lateral track; 14. Negative pressure device; 15. Suspension device; 16. Longitudinal track; 17. Support bracket; 2. Contact accelerometer; 3. Industrial camera; 4. High-precision fully automatic force hammer; 5. Rotary table; 6. Miniature laser Doppler vibration meter; 7. Microwave radar; 8. Low-frequency microphone; 9. Hyperspectral sensor; 10. 3D scanner; 20. Glass panel; 21. Surface damage; 22. Hidden damage; 23. Vacuum suction cup; 24. Air vibration damping unit; 31. Support structure; 32. Structural adhesive area. Detailed Implementation

[0056] The present disclosure will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the disclosure. Furthermore, it should be noted that, for ease of description, only the parts relevant to the present disclosure are shown in the accompanying drawings.

[0057] It should be noted that, where there is no conflict, the embodiments and features described in this disclosure can be combined with each other. The technical solutions of this disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0058] Unless otherwise stated, the exemplary implementations / embodiments shown are to be understood as providing exemplary features of various details that provide ways in which the technical concepts of this disclosure can be implemented in practice. Therefore, unless otherwise stated, the features of various implementations / embodiments may be additionally combined, separated, interchanged and / or rearranged without departing from the technical concepts of this disclosure.

[0059] The use of crosshairs and / or shading in the accompanying drawings is generally used to clarify the boundaries between adjacent components. Thus, unless otherwise stated, the presence or absence of crosshairs or shading does not convey or indicate any preference or requirement for the specific material, material properties, dimensions, proportions, commonalities between the illustrated components, or any other characteristics, properties, etc., of the components. Furthermore, in the accompanying drawings, the dimensions and relative dimensions of components may be exaggerated for clarity and / or descriptive purposes. When exemplary embodiments can be implemented differently, a specific process sequence may be performed in a different order than that described. For example, two consecutively described processes may be performed substantially simultaneously or in the reverse order of their description. Furthermore, the same reference numerals denote the same components.

[0060] When a component is referred to as being "on" or "above" another component, "connected to," or "joined to" another component, the component may be directly on, directly connected to, or directly joined to the other component, or there may be intermediate components. However, when a component is referred to as being "directly on" another component, "directly connected to," or "directly joined to" another component, there are no intermediate components. Therefore, the term "connection" can refer to a physical connection, an electrical connection, etc., and may or may not have intermediate components.

[0061] For descriptive purposes, this disclosure may use spatial relative terms such as “below,” “under,” “below,” “down,” “above,” “above,” “higher,” and “side (e.g., in a “sidewall”)” to describe the relationship between one component and another component as shown in the accompanying drawings. In addition to the orientations depicted in the drawings, the spatial relative terms are also intended to encompass different orientations of the device during use, operation, and / or manufacture. For example, if the device in the drawings is flipped, a component described as “below” or “under” another component or feature would subsequently be positioned “above” said other component or feature. Thus, the exemplary term “below” can encompass both “above” and “below” orientations. Furthermore, the device may be otherwise positioned (e.g., rotated 90 degrees or in other orientations), thus interpreting the spatial relative descriptive terms used herein accordingly.

[0062] The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used herein, unless the context clearly indicates otherwise, the singular forms “a” and “the” are intended to include the plural forms as well. Furthermore, when the terms “comprising” and / or “including” and variations thereof are used in this specification, it indicates the presence of the stated features, integrals, steps, operations, parts, components, and / or groups thereof, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, parts, components, and / or groups thereof. It should also be noted that, as used herein, the terms “substantially,” “about,” and other similar terms are used as approximate terms rather than as terms of degree, thus explaining the inherent biases in measurements, calculated values, and / or provided values ​​that would be recognized by one of ordinary skill in the art.

[0063] Reference Figure 1 The first aspect of this application discloses an automated detection method for defects in glass curtain wall structures, the method comprising:

[0064] S10, Based on the actual information of the target glass curtain wall, construct a three-dimensional model (i.e., construct a three-dimensional model of the target glass curtain wall). The actual information includes the structure, dimensions, materials, and other information of the target glass curtain wall.

[0065] S20, Modal Simulation Analysis: Perform finite element analysis on a three-dimensional model to obtain simulated modal response information.

[0066] The simulated modal response information includes several mode shapes, the natural frequencies corresponding to each mode shape, and the mapping relationship.

[0067] In this embodiment, other finite element analysis software such as ANSYS and ABAQUS can be used to perform finite element analysis on the three-dimensional model.

[0068] S30: Based on the simulated modal response information, a detection strategy is obtained.

[0069] The detection strategy includes the selection strategy for modal measurement sensors, the setting location of modal measurement detection points, and the walking path of the modal measurement robot. The setting location of the modal measurement detection points is the measurement point location that can excite all target modes.

[0070] S40, Modal Measurement Analysis: Based on the detection strategy, excitation tests are performed to obtain the actual natural frequency response information.

[0071] The actual natural frequency response information includes several actual natural frequency mode shapes and fundamental frequencies of each mode.

[0072] S50, Comparative Analysis: Based on simulated modal response information and actual natural frequency response information, the defect type of the target glass curtain wall is obtained.

[0073] This application first collects actual information about the target glass curtain wall to ensure that the constructed model is consistent with the target glass curtain wall information; then, it simulates and analyzes the constructed three-dimensional model under ideal conditions to obtain theoretical data information to guide the actual measurement of the target glass curtain wall; finally, it compares and analyzes the measured data to accurately and comprehensively obtain the defect types of the target glass curtain wall, with a high degree of automation, high precision, high reliability, and high safety level.

[0074] In this application, since glass curtain walls have different specifications and types, a three-dimensional model of the target glass curtain wall is constructed before the actual measurement. The three-dimensional model includes all the details of the target glass curtain wall, especially the structural adhesive, weather-resistant adhesive, and support system of the curtain wall, which are set with different damping parameters and contact types to ensure that the constraints of each part of the constructed three-dimensional model are consistent with the actual situation.

[0075] For the collection of actual information, the following technical solutions can be adopted: For glass curtain walls in the air, the following feasible solutions can be adopted to collect their actual information: 1) Manual on-site survey: Dispatch professional surveyors to the site to conduct on-site surveys and obtain relevant information such as the shape, area, and structure of the curtain wall through visual observation, measuring instruments, etc.; 2) Aerial drone (UAV) photography: Use aerial drones (UAVs) with high-definition cameras to take pictures of the curtain wall's shape and details in order to obtain the curtain wall's three-dimensional information. To obtain more detailed information, methods such as multi-angle, multi-height fixed-point photography and capturing the reflection of light at different frequency bands can be used; 3) High-altitude robot: Using a high-altitude robot, the robot is suspended on the surface of the glass curtain wall to be tested, and a support bracket with vacuum suction cups is used to attach the robot to the adjacent glass surfaces of the glass curtain wall unit to be tested, thereby eliminating the influence of added mass and robot vibration on the test results, and conducting detection and surveying of the glass curtain wall unit to obtain detailed information about the glass curtain wall; 4) 3D laser scanning: A 3D laser scanner is used to scan the glass curtain wall to obtain high-precision, large-area point cloud data, and then a three-dimensional model of the curtain wall is constructed using point cloud reconstruction tools. Of course, different combinations can also be used according to different needs to achieve the goal of accurately collecting actual information about the curtain wall.

[0076] Reference Figure 2 The method for obtaining simulated modal response information specifically includes the following steps:

[0077] S21. Based on the three-dimensional model, a finite element model is established.

[0078] S22, Analyze the finite element model based on preset parameters to obtain the simulated modal response information.

[0079] The preset parameters include material properties and boundary conditions.

[0080] In this embodiment, the several modal vibration modes include the first five modal vibration modes of the curtain wall unit component, namely the first, second, third, fourth and fifth modal vibration modes of the curtain wall unit component; the fundamental frequency of each modal includes the first, second, third, fourth and fifth vibration frequencies.

[0081] In this embodiment, based on the set material properties and boundary conditions, the natural frequencies and mode shapes of each mode of the structure are solved in the finite element model. The specific parameters obtained are the mode shapes of the first five modes of the curtain wall unit component, where the frequency corresponding to the first mode is the fundamental frequency of the curtain wall unit.

[0082] In this embodiment, the damage level range includes a single damage range and a mixed damage range. The single damage range includes a no-damage segment and multiple damage segments, and the mixed damage range includes a no-single damage segment, a single-double damage segment, and a double-triple damage segment.

[0083] The results of modal simulation analysis are used to guide the actual measurement. During the actual measurement, the first 1-5 target modes of the test object can all be excited by the target position of the force hammer. It is worth noting that the sensor should not be placed at the node position of the target mode, otherwise the mode will not be measured.

[0084] Reference Figure 3 The first five modal vibration frequencies of the curtain wall unit components obtained through modal simulation analysis show that, within the same modal mode, the frequencies corresponding to the damage type decrease from no damage, single-sided damage, double-sided damage, to three-sided damage; while within different modal modes, the frequencies corresponding to the same damage type increase from the first-order modal mode to the fifth-order modal mode.

[0085] Furthermore, obtaining the detection strategy can include the following steps: 1) Analyzing and processing the simulated modal response data to obtain the structural and modal response characteristics of the glass curtain wall. Signal processing methods, such as modal curvature, modal strain energy, modal guarantee criteria, wavelet analysis, and fast Fourier transform, can be used to reduce the dimensionality and filter the data to extract key information. 2) Designing a sensor selection strategy based on the simulated modal response data; determining the type and number of sensors to be used based on the modal response characteristics and force characteristics, such as accelerometers, displacement sensors, and vibrating wire sensors. 3) Determining the location of modal measurement detection points: determining the location of detection points that can excite all target modes based on the modal response characteristics and structural characteristics. Generally, sensors can be suspended at each node of the curtain wall, and excitation sources or hammer sources can be set near the suspension points to ensure that the target modal response signals can be measured. 4) Designing the movement path of the modal measurement robot: determining the robot movement path based on factors such as the location of the detection points, the structure of the curtain wall, and access conditions. The robot should be able to fully cover the curtain wall surface and ensure the accuracy and precision of the measurement data. 5) Determination of various detection parameters, including: wind speed, wind direction, ambient temperature, frequency and amplitude of the detection excitation signal; combining the above steps, a detection strategy can be obtained based on the simulated modal response data. This strategy can guide the excitation test and the setting of detection points, providing a foundation and guarantee for subsequent actual excitation measurements.

[0086] The method for obtaining actual natural frequency response information includes: based on the modal measurement sensor selection strategy, setting up modal measurement sensors at the modal measurement detection point, using a high-precision fully automatic force hammer for excitation, and obtaining the actual natural frequency response information.

[0087] The selection of sensors in the modal measurement sensor selection strategy includes the following criteria: First, the frequency testing range of the sensor should be able to cover the target detection frequency. Specifically, the frequency testing range of the modal measurement sensor should completely cover or even exceed the modal vibration frequencies corresponding to the first five modal modes of the curtain wall unit components. Second, the sensitivity of the sensor should be suitable for the structural characteristics. In the curtain wall unit, the longitudinal vibration amplitude in the simulated modal analysis is large, while the lateral vibration amplitude is small. Therefore, a sensor with moderate sensitivity can be selected to measure longitudinal vibration, while a sensor with higher sensitivity should be selected to measure lateral vibration. If the sensitivity is too low, it will be difficult to detect defect information.

[0088] In this embodiment, the several actual natural frequency mode shapes preferably include a first actual natural frequency mode shape, a second actual natural frequency mode shape, a third actual natural frequency mode shape, a fourth actual natural frequency mode shape, and a fifth actual natural frequency mode shape; the fundamental frequency of each mode includes a first vibration frequency, a second vibration frequency, a third vibration frequency, a fourth vibration frequency, and a fifth vibration frequency.

[0089] Reference Figure 4 and Figure 5 The specific trends of the natural frequencies with respect to the damage type include the polynomial relationships of the first, second, third, fourth, and fifth modal modes.

[0090] In this embodiment, the polynomial relationship of the first-order mode shape is: y1 = 11.543x1 2 -93.321x1+201.92; where x1 is the first natural frequency.

[0091] The polynomial equation for the second-order modal vibration is: y² = 8.9243x² 2 -104.32x2+301.56; where x2 is the second natural frequency.

[0092] The polynomial equation for the third-order modal vibration is: y³ = 20.823x³ 2 -171.75x3+427.61; where x3 is the third natural frequency.

[0093] The polynomial equation for the fourth-order modal vibration is: y⁴ = 15.796x⁴ 2 -163.21x4+492.47; where x4 is the fourth natural frequency.

[0094] The polynomial equation for the fifth-order modal vibration is: y5 = 2.7225x5 2-98.388x5+455.78; where x5 is the fifth natural frequency.

[0095] The method for obtaining the defect type of the target glass curtain wall specifically includes the following steps:

[0096] S51, based on the actual inherent frequency response information, obtains the inherent frequency test frequency.

[0097] S52, determine whether the natural frequency test frequency belongs to a single damage range. If yes, directly obtain the defect type of the target glass curtain wall; if no, process the natural frequency test frequency according to the preset error to obtain the corrected data range; in this embodiment, the preset error is 5%.

[0098] S53. Based on the mixed damage range and the corrected data range, the defect type of the target glass curtain wall is obtained. Specifically, the three intervals of no-single damage segment, single-double damage segment, and double-triple damage segment are each divided into five equal parts. At this time, the interval formed by the adjacent points before and after the fundamental frequency of the four damage conditions of no damage, single damage, double damage, and triple damage is the damage judgment interval of this type. The remaining intervals are mixed damage intervals of no-single damage segment, single-double damage segment, and double-triple damage segment. The corrected data range is determined according to the size of the area of ​​each interval it falls into, so that the defect type of the target glass curtain wall can be accurately obtained.

[0099] In one embodiment of this application, the target glass curtain wall does not spontaneously explode, so a three-dimensional model can be directly constructed based on the collected actual information.

[0100] In another embodiment of this application, before constructing the three-dimensional model, the method further includes: determining whether the target glass curtain wall has a preset crack state based on the actual information of the target glass curtain wall;

[0101] If so, the target glass curtain wall is determined to be an abnormal area, and a new target area without preset cracks is selected (i.e., the test is moved to the next test area).

[0102] An updated 3D model is constructed based on the target region to be detected.

[0103] The preset crack state is a multi-crack state; the abnormal area includes areas where spontaneous explosions are possible.

[0104] It should be noted that the simulation in this application is for the purpose of guiding actual testing. Therefore, during the initial data collection, a preliminary judgment can be made on the target glass curtain wall before modeling, that is, to determine whether the target glass curtain wall is prone to spontaneous breakage. If spontaneous breakage is present, forcibly conducting actual testing will cause greater damage to the target glass curtain wall. Therefore, there is no need to conduct subsequent actual testing, and it is meaningless to simulate a target glass curtain wall that is prone to spontaneous breakage.

[0105] Furthermore, the methods for determining whether a target glass curtain wall is prone to spontaneous breakage can include the following points: 1) If the cracked edge of the glass is neat, the number of cracks is small, and the crack line is a tortuous single line or double line, then spontaneous breakage can be determined; 2) If the crack line of the glass is perpendicular to the edge of the glass, then spontaneous breakage can be considered, and it should be further determined whether the phenomenon is caused by bending stress or by defects at the edge of the glass; 3) If the crack line in the middle area of ​​the glass is mostly arc-shaped, then spontaneous breakage can be determined.

[0106] Reference Figures 6 to 8 In this application, the wall-climbing robot 1 is used for the stimulation test. Specifically, the wall-climbing robot 1 includes a robot body 11 and a multi-functional testing device integrated into the robot body 11. The robot body 11 is equipped with a wireless transmission device 12 and a wall-climbing device. In this embodiment, preferably, the robot body 11 is equipped with a suspension device 15, which can cooperate with an external suspension system. The wall-climbing device is a negative pressure device 14. The inner side of the robot body 11 is also equipped with a transverse track 13 and a longitudinal track 16 to facilitate movement on the glass curtain wall. The robot body 11 is equipped with a support bracket 17, and the ends of the support bracket are respectively equipped with vacuum suction cups 21 of air vibration damping units 24 to facilitate adsorption onto the adjacent glass of the glass curtain wall unit under test.

[0107] The multifunctional detection equipment includes an excitation source device, an impact sensing device, and a visual inspection device. The excitation source device is used to provide a preset quality excitation source, the impact sensing device is used to collect impact sensing information, and the visual inspection device is used to collect image information.

[0108] The excitation source equipment includes a lifting support and a high-precision fully automatic hammer 4 with an air damping and vibration isolation unit. The high-precision fully automatic hammer 4 serves as a controllable, high-quality excitation source with high accuracy. The impact sensing equipment includes a low-frequency accelerometer (i.e., a contact accelerometer 2), an ultrasonic sensor, a low-frequency microphone 8, a microwave radar 7, and a miniature laser Doppler vibration meter 6. The miniature laser Doppler vibration meter 6 and the microwave radar 7 are mounted on the robot body 11 via a rotating device, preferably a rotary table 5, capable of 360-degree in-situ rotation. The visual inspection equipment includes an industrial camera 3, a hyperspectral sensor 9, and a 3D scanner 10. Through this multi-functional inspection equipment, comprehensive and synchronous detection of defects in the glass curtain wall can be achieved, improving the accuracy of damage testing and solving the technical bottlenecks faced in non-destructive testing of glass curtain wall structures.

[0109] Furthermore, a miniature laser Doppler vibration meter 6 and a microwave radar 7 are located on the outside of the robot body 11. Four sets of high-precision fully automatic force hammers 4, each equipped with an air damping unit, are located on the left and right sides of the robot body 11. Four sets of contact accelerometers 2 are mounted on the robot body 11 via lifting guide rail clamps. Low-frequency microphones 8 are mounted on the side of the robot body 11 via connectors; in this embodiment, four sets of low-frequency microphones 8 are also provided. An industrial camera 3, a hyperspectral sensor 9, and a 3D scanner 10 are located on the inside of the robot body 11 to facilitate target area detection and data acquisition.

[0110] The wall-climbing robot 1 provided in this application for glass curtain walls can realize integrated automated testing of impact-acoustic vibration, impact-response, laser Doppler vibration measurement, microwave radar 7, machine vision, and hyperspectral imaging. Using the adsorption wall-climbing robot 1 as a carrier, it can perform collaborative inspection of glass curtain wall structures, realize comprehensive synchronous detection of glass curtain wall defects, improve the accuracy of damage testing, and solve the technical bottleneck faced by non-destructive testing of glass curtain wall structures.

[0111] Among them, digital image analysis (industrial camera 3), 3D point cloud map (3D scanner 10), and hyperspectral (rubber strip infrared aging) test are used for efficient identification of apparent damage 21, while impact-acoustic vibration (based on low frequency microphone 8), impact-response (based on contact accelerometer 2), laser Doppler vibration measurement and microwave radar 7 are used for efficient identification of hidden damage 22.

[0112] The method disclosed in this application uses an adsorption-type wall-climbing robot 1 as a carrier, which can independently achieve tapping excitation, thus enabling simultaneous testing of apparent damage 21 and hidden damage 22 of the curtain wall.

[0113] The method disclosed in this application uses an automatic hammer to excite the surface damage 21, while an industrial camera 3, a hyperspectral imager, and a 3D scanner 10 capture the surface damage 21. Simultaneously, under the action of vibration, a low-frequency microphone 8, a low-frequency accelerometer, a microwave radar 7, and a laser Doppler can capture and analyze the vibration signal. Overall, it achieves efficient integration and collaborative testing of impact-acoustic vibration, impact-response, machine vision, hyperspectral imaging, 3D point cloud mapping, and laser vibration measurement methods. This enables integrated, synchronous, and accurate testing of both surface damage 21 and hidden damage 22 of glass curtain walls, which can compensate for the shortcomings of existing detection methods, overcome the technical bottleneck of high-altitude operations, improve the automation level of glass curtain wall structural damage detection, and significantly improve testing efficiency and identification accuracy.

[0114] Furthermore, the method may include one or more multifunctional integrated wirelessly controlled suspended negative pressure adsorption wall-climbing robots 1.

[0115] Existing methods for detecting defects in glass curtain walls are based on material appearance defect testing, such as photoelastic testing of impurities in glass panels, on-site tensile testing of structural adhesives, and natural frequency testing of glass detachment in glass curtain wall structures. These methods require sampling during testing, making it impossible to comprehensively cover all existing curtain wall damage forms with a single test, and they can also cause damage to the glass curtain wall itself during the testing process. The automated detection method for defects in high-rise building glass curtain wall systems disclosed in this application employs a wall-climbing robot to improve the automation level of the detection, enabling damage detection of glass curtain walls at high altitudes and in areas difficult for inspection personnel to access. It efficiently integrates impact-acoustic vibration, impact-response, microwave radar, laser Doppler vibration measurement, machine vision, and hyperspectral testing methods, improving the accuracy and efficiency of glass curtain wall structural damage detection.

[0116] Reference Figures 9 to 12 The defects that may exist in the glass panel 20 include apparent damage 21 and hidden damage 22. Apparent damage 21 includes glass cracks, and hidden damage 22 includes loose support structure 31 and aging of structural adhesive in structural adhesive area 32. The support bracket 17 with vacuum suction cup 23 is supported on both sides of the glass curtain wall unit to be tested. During the test, the suction force of the suction cup is adjusted to the maximum to reduce the influence of the added mass on the glass curtain wall unit to be tested. In contrast, there is an air vibration damping unit 23 between the vacuum suction cup and the support bracket to reduce the impact of vibration generated by excitation on the inspection robot body 11.

[0117] Furthermore, the data in this embodiment can also be transmitted via a 5G network. The obtained time-domain curves are systematically analyzed on a high-performance workstation. The analysis results can be used to identify defects in individual / single-sided glass curtain walls and to qualitatively determine the health status of individual / single-sided glass curtain walls. The identification results are uploaded to a cloud platform to display the health status characteristics of the entire glass curtain wall envelope in the form of an image, thereby providing relevant reference for government departments and other organizations.

[0118] Reference Figure 13In another embodiment of this application, the automated inspection method for glass curtain walls specifically includes: 1) visually inspecting apparent defects; 2) determining whether the apparent defects exist. If so, stopping the tapping, the vision device records the position of the glass and the apparent defects, then changing the test point, and the wall-climbing robot crawls to the next test point for testing; if not, lowering the support bracket to support the robot body, increasing the suction force of the vacuum suction cup to a stable and measurable stage, and then controlling the hammer to start tapping, and the test begins. 3) Data is acquired using a low-frequency microphone, a low-frequency scanning laser Doppler, and a low-frequency accelerometer to obtain mode shapes and frequencies. Based on the mode shapes obtained from the three methods, it is determined whether the mode shapes measured by the three methods are consistent. If not, the mode shapes are re-acquired. If so, a preliminary judgment is made by comparing them with the theoretical mode shapes to determine whether damage exists in each case. If not, the support bracket is lowered and the suction force of the vacuum suction cup is reduced to a stable crawling level. Then, the wall-climbing robot crawls to the next test point for testing. If damage is found, the damage location is recorded, and the frequency damage range is obtained based on the frequency. Then, the damage type is determined step by step according to the frequency damage range method. A preliminary analysis is performed first, followed by a detailed analysis.

[0119] The preliminary analysis includes fundamental frequency analysis, which incorporates segmented intervals based on the fundamental frequencies of four operating conditions.

[0120] Detailed analysis includes: determining whether the natural frequency test frequency belongs to a single damage range; if so, directly obtaining the defect type of the target glass curtain wall; if not, processing the natural frequency test frequency with a 5% error to obtain a corrected data range. Then, based on the mixed damage range and the corrected data range, the defect type of the target glass curtain wall is obtained. Specifically, the three intervals—no-single damage segment, single-double damage segment, and double-triple damage segment—are each divided into five equal parts. At this point, the interval formed by the adjacent points before and after the fundamental frequency of the four damage conditions (no damage, single damage, double damage, and triple damage) is the damage determination interval for that type. The remaining intervals are mixed damage intervals of the no-single damage segment, single-double damage segment, and double-triple damage segment. The corrected data range is determined according to the area of ​​each interval it falls into, thus accurately obtaining the defect type of the target glass curtain wall.

[0121] For a system with n degrees of freedom, let its mass matrix be M, damping matrix be C, and stiffness matrix be K. Let X represent the modal vector of the structure, which has the following form:

[0122] X = [x1, x2, x3…x] n ] T ;where x i The displacement of the i-th mode shape is given by the system's equation of motion: It is the second derivative of the displacement mode vector. It is the first derivative of the displacement mode vector, and F is the external force vector.

[0123] Modal testing of the curtain wall structure system can yield parameters such as the natural frequencies of the structure under different modes. The natural frequency parameters are the fundamental parameters of the modal testing, and the formula for each parameter is as follows:

[0124] Natural frequency formula: Where ω mn is the natural frequency of the plate enclosed by the nodal lines of the m and nth modes, D represents the bending stiffness of the glass plate, ρ and h represent the density of the material and the thickness of the glass plate, respectively, a and b represent the width and length of the glass plate, respectively, m and n are the modal orders of the simply supported plate in the transverse direction, and Δm and Δn are the "edge effect coefficients" corresponding to the modal orders in each direction.

[0125] Therefore, in the theoretical calculations, it is unnecessary to consider the added mass of the wall-climbing robot adhering to the surface of the glass curtain wall structure, or to reduce the vibration of the wall-climbing robot caused by the hammer impact. Compared with adhesive wall-climbing robots, this offers significant advantages.

[0126] Reference Figure 14 The second aspect of this application discloses an automated detection system for defects in glass curtain wall structures, the system comprising:

[0127] The module is configured to build a 3D model based on the actual information of the target glass curtain wall.

[0128] The modal simulation analysis module is configured to perform finite element analysis on a three-dimensional model to obtain simulated modal response information. The simulated modal response information includes several mode shapes, the natural frequencies corresponding to each mode shape, and the damage level range.

[0129] The detection strategy acquisition module is configured to obtain the detection strategy based on the simulated modal response information. The detection strategy includes the modal measurement sensor selection strategy, the modal measurement detection point setting position, and the modal measurement robot walking path. The modal measurement detection point setting position is the measurement point position that can excite all target modes.

[0130] The modal measurement module is configured to perform excitation tests based on a detection strategy to obtain actual natural frequency response information; the actual natural frequency response information includes several actual natural frequency mode shapes and fundamental frequencies of each mode.

[0131] The analysis module is configured to obtain the defect type of the target glass curtain wall based on simulated modal response information and actual natural frequency response information.

[0132] In the description of this specification, the references to terms such as "one embodiment / mode," "some embodiments / modes," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment / mode or example is included in at least one embodiment / mode or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment / mode or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments / modes or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments / modes or examples described in this specification, as well as the features of different embodiments / modes or examples.

[0133] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0134] Those skilled in the art should understand that the above embodiments are merely for illustrating the present disclosure and are not intended to limit the scope of the disclosure. Those skilled in the art can make other changes or modifications based on the above disclosure, and these changes or modifications still fall within the scope of the present disclosure.

Claims

1. An automated inspection method for glass curtain walls, characterized in that, The method includes: Construct a three-dimensional model based on the actual information of the target glass curtain wall; Finite element analysis is performed on the three-dimensional model to obtain simulated modal response information. This simulated modal response information includes several modal shapes, the natural frequencies corresponding to each modal shape, and the damage level range. The several modal shapes include the first, second, third, fourth, and fifth modal shapes of the curtain wall unit component. The damage level range includes single damage ranges and mixed damage ranges. The single damage range includes no-damage segments and multiple-damage segments, and the mixed damage range includes no-single-damage segments, single-double-damage segments, and double-triple-damage segments. Based on the simulated modal response information, a detection strategy is obtained; wherein, the detection strategy includes a modal measurement sensor selection strategy, a modal measurement detection point setting position, and a modal measurement robot walking path, and the modal measurement detection point setting position is a measurement point position that can excite all target modes; Based on the detection strategy, an excitation test is performed to obtain actual natural frequency response information; wherein, the actual natural frequency response information includes several actual natural frequency mode shapes and fundamental frequencies of each mode. Based on the simulated modal response information and the actual natural frequency response information, the defect type of the target glass curtain wall is obtained, specifically including: obtaining the natural frequency test frequency based on the actual natural frequency response information; determining whether the natural frequency test frequency belongs to the single damage range; if so, directly obtaining the defect type of the target glass curtain wall; if not, processing the natural frequency test frequency according to a preset error to obtain a corrected data range; and obtaining the defect type of the target glass curtain wall based on the mixed damage range.

2. The automated inspection method for glass curtain walls according to claim 1, characterized in that, The step of performing finite element analysis on the three-dimensional model to obtain simulated modal response information includes: Based on the aforementioned three-dimensional model, a finite element model is established; The finite element model is analyzed based on preset parameters to obtain the simulated modal response information; The preset parameters include material properties and boundary conditions.

3. The automated inspection method for glass curtain walls according to claim 2, characterized in that, The step of performing stimulus testing based on the detection strategy to obtain actual inherent frequency response information includes: Based on the modal measurement sensor selection strategy, modal measurement sensors are deployed at the modal measurement detection points, and a high-precision fully automatic force hammer is used for excitation to obtain the actual natural frequency response information.

4. The automated inspection method for glass curtain walls according to claim 3, characterized in that, The actual natural frequency mode shapes of several orders include the first actual natural frequency mode shape, the second actual natural frequency mode shape, the third actual natural frequency mode shape, the fourth actual natural frequency mode shape, and the fifth actual natural frequency mode shape; The fundamental frequencies of each modal include the first, second, third, fourth, and fifth vibration frequencies.

5. The automated inspection method for glass curtain walls according to claim 1, characterized in that, The process before building the 3D model also includes: Based on the actual information of the target glass curtain wall, determine whether the target glass curtain wall has a preset crack state; If so, the target glass curtain wall is determined to be an abnormal area, and a new target area without the preset crack state is selected for detection. An updated 3D model is constructed based on the target region to be detected.

6. A wall-climbing robot for use with glass curtain walls, characterized in that, The wall-climbing robot for performing the excitation test in the automated inspection method for glass curtain walls according to any one of claims 1-5 includes: The robot body is equipped with a wireless transmission device and a wall-climbing device. A multi-functional detection device is integrated into the robot body; the multi-functional detection device includes an excitation source device, an impact sensing device, and a visual detection device. The excitation source device is used to provide a preset mass excitation source, the impact sensing device is used to collect impact sensing information, and the visual detection device is used to collect image information.

7. The wall-climbing robot for glass curtain walls according to claim 6, characterized in that, The excitation source device includes a lifting support and a high-precision fully automatic force hammer with an air damping and vibration isolation unit. The impact sensing device includes a low-frequency accelerometer, an ultrasonic sensor, a low-frequency microphone, a microwave radar, and a miniature laser Doppler vibration meter; the miniature laser Doppler vibration meter and the microwave radar are mounted on the robot body via a rotating device; The visual inspection equipment includes an industrial camera, a hyperspectral sensor, and a 3D scanner.

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