Climbing scaffolding deformation monitoring method, medium and equipment based on Beidou GNSS

Abstract

The present invention relates to the field of deformation monitoring, in particular to a deformation monitoring method, medium and device for climbing scaffolds based on Beidou GNSS. It includes: generating a corresponding standard attitude matrix A according to the initial position information; generating a corresponding attitude matrix B to be detected according to the position information to be detected; calculating the similarity value P between A and B; if P < Y1, then calculate the similarity between the two row vectors corresponding to each row in A and B respectively; if the similarity between the two row vectors corresponding to any row is less than the second similarity threshold Y2, then determine the preset deformation monitoring part corresponding to this row as the deformed part. In the present invention, it is possible to determine whether deformation occurs by comparing the similarity between the attitude adjacency matrices corresponding to different monitoring times and the attitude adjacency matrix corresponding to the standard attitude. Deformation monitoring can be carried out automatically, which can save manpower and material resources, and at the same time has low requirements for the site, and can improve practicability.

Description

Background Art

[0002] Super high-rise buildings have the characteristics of large main body, many floors, high height and long construction period. The stability and safety timeliness of super high-rise buildings in the construction process will have higher requirements as the building height increases. In view of the characteristics of super high-rise buildings and the requirements of their construction technology, the climbing frame can automatically rise as the height of the building increases, providing a working platform for workers.

[0003] Super high-rise projects have a long construction period and a complex construction environment. They are seriously affected by seasonal changes (alternating between cold and hot seasons throughout the year), the life of the climbing frame materials themselves (on-site corrosion, external force collision, etc.), and on-site construction (construction measurement and stacking, construction process arrangement, etc.). At the same time, the shape of the climbing frame changes with the changes in the structure shape, involving inclined climbing, etc., especially some extremely severe weather (strong typhoons, heavy snowfall, etc.) will have a great impact on the climbing frame system, which is prone to overturning and collapse accidents. Causing varying degrees of casualties, property losses and impact on the construction period. The safety monitoring system is imperfect, and effective monitoring and management measures need to be taken to establish a complete automatic monitoring and early warning system to prevent accidents.

[0004] At present, deformation monitoring of climbing frames mainly adopts traditional equipment such as total stations and levels. The small angle measurement method or collimation method is used to directly measure the front end deviation. Affected by environmental factors, it requires that the surrounding area of ​​the building must be open, the site requirements are high, and the visibility conditions are good. Due to site restrictions, the distance between the instrument and the building is close, and the instrument elevation angle is too large, which cannot meet the deformation monitoring of super high-rise building climbing frames during construction. It is difficult to obtain the basic data of the whole process of correction forecast and safety prevention in real time and accurately. In addition, there is currently no automated monitoring and early warning system. All measurements are made through traditional monitoring methods, and manual analysis and judgment of whether there are risks such as collapse are performed after post-processing. The degree of automation is low, time-consuming and labor-intensive, and it is difficult to meet the construction progress requirements. Summary of the invention

[0005] In view of the above technical problems, the technical solution adopted by the present invention is:

[0006] According to one aspect of the present invention, a Beidou GNSS-based climbing scaffold deformation monitoring method is provided, which is applied to the climbing scaffold, and a deformation monitoring station is installed at a preset deformation monitoring position of the climbing scaffold to obtain position information corresponding to the preset deformation monitoring position, and generate a corresponding relative position undirected graph; the position information includes Beidou positioning information;

[0007] The method comprises the following steps:

[0008] When the installation and debugging of the climbing scaffolding is completed, the initial position information corresponding to the plurality of preset deformation monitoring parts is obtained;

[0009] Generate a standard attitude matrix A corresponding to the climbing scaffold according to the initial position information; A is an n×n adjacency matrix, where A[i][j] = A[j][i] = d j i , where A[i][j] is the element value of the i-th row and j-th column in A; d j i is the distance value between the initial position information corresponding to the i-th preset deformation monitoring part and the initial position information corresponding to the j-th preset deformation monitoring part; n is the total number of preset deformation monitoring parts, and both i and j belong to [1, n];

[0010] When the preset monitoring condition is reached, obtain the to-be-detected position information currently corresponding to multiple preset deformation monitoring parts;

[0011] Generate a to-be-detected attitude matrix B corresponding to the climbing scaffold according to the to-be-detected position information; B is an n×n adjacency matrix, where B[i][j] = B[j][i] = e j i , where B[i][j] is the element value of the i-th row and j-th column in B; e j i is the distance value between the to-be-detected position information corresponding to the i-th preset deformation monitoring part and the to-be-detected position information corresponding to the j-th preset deformation monitoring part;

[0012] Use spectral similarity to calculate the similarity value P between A and B;

[0013] If P < Y1, calculate the similarity between the two row vectors corresponding to each row in A and B respectively; where Y1 is the first similarity threshold;

[0014] If the similarity between the two row vectors corresponding to any one row is less than the second similarity threshold Y2, determine the preset deformation monitoring part corresponding to this row as the deformed part.

[0015] According to the second aspect of the present invention, there is provided a non-transitory computer-readable storage medium, and the non-transitory computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned deformation monitoring method of the climbing scaffold based on Beidou GNSS is implemented.

[0016] According to the third aspect of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the above-mentioned deformation monitoring method of the climbing scaffold based on Beidou GNSS is implemented.

[0017] The present invention has at least the following beneficial effects:

[0018] In the present invention, by being arranged at a deformation monitoring station at a preset deformation monitoring position of a climbing scaffold, the three-dimensional position information of each deformation monitoring station can be obtained in real time by the Beidou positioning and navigation system. Then, an undirected graph of the attitude corresponding to the climbing scaffold can be formed by these three-dimensional position information, wherein the distance between any two nodes (deformation monitoring stations) is the edge between the two nodes. Thus, whether deformation occurs can be determined by comparing the attitude adjacency matrix corresponding to different monitoring moments with the attitude adjacency matrix corresponding to the standard attitude for similarity.

[0019] In addition, if a preset deformation monitoring part is deformed, the distance between it and other preset deformation monitoring parts will basically change, which is reflected in the adjacency matrix as a significant change in the element value in the row vector corresponding to the deformed node. Therefore, by calculating the similarity of the row vectors row by row, it can be determined which parts are deformed. In addition, the present invention can automatically monitor deformation, save manpower and material resources, and at the same time, the present solution has low site requirements, which can further improve practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 A flowchart of a climbing scaffold deformation monitoring method based on Beidou GNSS provided in an embodiment of the present invention.

[0022] Figure 2 This is a relative installation structure diagram of the deformation reference station and the deformation monitoring station provided in an embodiment of the present invention.

[0023] Figure 3 A structural diagram of a monitoring system corresponding to the Beidou GNSS-based climbing scaffold deformation monitoring method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0025] As a possible embodiment of the present invention, Figure 1As shown, a Beidou GNSS-based climbing scaffold deformation monitoring method is provided, which is applied to a climbing scaffold 3, and a deformation monitoring station 1 is installed at a preset deformation monitoring position of the climbing scaffold 3 to obtain position information corresponding to the preset deformation monitoring position, and generate a corresponding relative position undirected graph. The position information includes Beidou positioning information.

[0026] The preset deformation monitoring location should be selected at a location where the deformation is obvious and representative, which is convenient for the installation of deformation monitoring station 1 and does not hinder the on-site construction. The point should be stable and not affect the use and safety of the climbing frame. The deformation monitoring station 1 can be a Beidou receiver.

[0027] When selecting a Beidou receiver, you should use a Beidou receiver device that is suitable for super-high-rise building climbing scaffolding construction scenarios. Due to the complex surrounding environment of super-high-rise construction, the narrow working surface of the high-altitude climbing scaffolding, and the large interference of construction (tower crane operation, steel structure lifting, concrete pouring, etc.), conventional equipment cannot be used for measurement.

[0028] Beidou receivers must have reliable hardware technology to ensure the continuity of data collection in complex high-altitude environments, stable and efficient data transmission, and the timeliness of data return. Adaptive multi-parameter Beidou III smart terminals that are compatible with 4G / 5G, WiFi, Bluetooth, LoRa, Beidou short messages and other communication methods.

[0029] Characterized in that the monitoring method specifically comprises the following steps:

[0030] S100: When the installation and debugging of the climbing scaffold 3 is completed, initial position information corresponding to a plurality of preset deformation monitoring locations is obtained.

[0031] On the one hand, the position information of the preset deformation monitoring part can directly use the high-precision three-dimensional position information at different times obtained by the deformation monitoring station 1 through the Beidou Global Navigation Satellite System (GNSS).

[0032] On the other hand, Figure 2 As shown, the position information of the preset deformation monitoring part can also be obtained according to the following steps:

[0033] S101: Establish a deformation reference station 2 around the target building. The deformation reference station 2 adopts a forced centering device, uses a Beidou receiver for overall joint measurement and adjustment, and uses a level for elevation measurement. Preferably, the installation point of the deformation reference station 2 is in a hard, stable and reliable area with a wide field of view and no obstacles within a range of more than 15° in elevation angle. There should be no interference sources that strongly interfere with the reception of satellite signals or objects that strongly reflect satellite signals near the point. It has a reliable power supply and should be convenient for network communication.

[0034] S102: Using the Beidou satellite navigation system's differential positioning technology and baseline vector solution method, the position information of each deformation monitoring station 1 relative to the deformation reference station 2 under different conditions is obtained.

[0035] S102 mainly utilizes the differential positioning technology and baseline vector solution method of the Beidou satellite navigation system to obtain high-precision position information of the target object.

[0036] First, the same Beidou satellite is observed at the deformation reference station 2 and the deformation monitoring station 1 that needs to monitor deformation, and the observation data of each is obtained. By comparing the observation data of the deformation reference station 2 and the deformation monitoring station 1, the error source (such as satellite orbit error, atmospheric delay, etc.) can be eliminated or reduced, so as to obtain the accurate position of the deformation monitoring station 1 relative to the deformation reference station 2.

[0037] In the schemes corresponding to S101 and S102, the deformation reference station 2 and multiple deformation monitoring stations 1 together form a new position coordinate reference system, and the deformation reference station 2 is used as the reference in the coordinate system to obtain the position information of multiple deformation monitoring stations 1 relative to the deformation reference station 2, thereby further eliminating or reducing error sources (such as satellite orbit errors, atmospheric delays, etc.), thereby obtaining the precise position changes of the deformation monitoring stations 1 relative to the deformation reference station 2.

[0038] In addition, after S102, the precise position change of the deformation monitoring station 1 relative to the deformation reference station 2 can be obtained by solving the baseline vector, thereby determining whether the corresponding part is deformed. During the solution process, various factors need to be considered, such as satellite geometric distribution, signal quality, atmospheric delay, etc., to ensure the accuracy and reliability of the solution. In deformation monitoring, the deformation monitoring station 1 is placed on an attached lifting external climbing frame that needs to be deformed. As time goes by, the deformation monitoring station 1 will continuously receive Beidou satellite signals and perform differential positioning calculations with the deformation reference station 2. By continuously observing and solving the baseline vector, the deformation information of the monitoring point, such as displacement, settlement, etc., is obtained.

[0039] S200: Generate a standard posture matrix A corresponding to the climbing scaffold 3 according to the initial position information. A is an n×n adjacency matrix, where A[i][j]=A[j][i]=d j i , A[i][j] is the value of the element in row i and column j in A. j i is the distance between the initial position information corresponding to the i-th preset deformation monitoring part and the initial position information corresponding to the j-th preset deformation monitoring part. n is the total number of preset deformation monitoring parts, and i and j both belong to [1, n].

[0040] The climbing scaffold 3 becomes a whole after installation, so the relative position relationship between the multiple deformation monitoring stations 1 installed thereon will not change without deformation. Based on this feature, initial position information is first required to generate a standard posture matrix corresponding to the climbing scaffold 3, so as to facilitate comparison with subsequent posture matrices.

[0041] S300: When the preset monitoring condition is reached, the to-be-detected position information currently corresponding to the plurality of preset deformation monitoring parts is obtained.

[0042] S400: Generate a to-be-detected attitude matrix B corresponding to the climbing scaffold 3 according to the to-be-detected position information. B is an n×n adjacency matrix, where B[i][j]=B[j][i]=e j i , B[i][j] is the value of the element in the i-th row and j-th column of B. j i is the distance value between the to-be-detected position information corresponding to the ith preset deformation monitoring portion and the to-be-detected position information corresponding to the jth preset deformation monitoring portion.

[0043] The preset monitoring conditions include a preset monitoring period or preset meteorological conditions or preset working conditions.

[0044] Specifically, the preset monitoring condition is the trigger condition for starting the automatic deformation monitoring scheme in this embodiment, and the setting of this condition can take into account the above-mentioned multiple scenarios. For example, a monitoring period can be set to perform a test at a preset time interval. In addition, deformation displacement monitoring can be performed under the influence of external loads and bad weather. For example, after certain meteorological weather conditions with complex force conditions such as strong winds and thunderstorms. Detection can also be performed under some special working conditions. For example, during the climbing process of the climbing frame, the climbing trajectory and climbing posture of the climbing frame can be monitored throughout the process to determine whether the climbing trajectory is climbing according to the designed route. If the climbing trajectory deviates from the design expectation, timely adjustment and correction are made. Monitor the deformation displacement of the climbing frame before and after climbing.

[0045] S500: Calculate a similarity value P between A and B using spectral similarity.

[0046] S500 includes:

[0047] S501: Calculate the Laplacian matrices L1 and L2 corresponding to the undirected graph corresponding to the initial position information and the undirected graph corresponding to the position information to be detected. L1 and L2 satisfy the following conditions:

[0048] L1 = D1-A. L2 = D2-B. Wherein, D1 and D2 are the degree matrices corresponding to the undirected graph corresponding to the initial position information and the undirected graph corresponding to the position information to be detected, respectively.

[0049] S502: Generate the similarity value P between A and B based on L1 and L2. P satisfies the following conditions:

[0050] P = d(L1, L2) = ||L1 - L2|| F 。

[0051] Where d(L1, L2) is the spectral norm distance between L1 and L2. ||·|| F is the Frobenius norm (i.e., the square root of the sum of the squares of the absolute values of the elements of the matrix).

[0052] Since the adjacency matrix directly describes the connection structure of the graph, its similarity calculation often focuses on the similarity in the network structure. In this embodiment, the network connection structure between the various nodes in the graph is actually the distance value between the various nodes. In this embodiment, more attention is also paid to the changes in these distance values. Therefore, using spectral similarity calculation can better capture the similarity of the relative position distribution between the nodes.

[0053] S600: If P < Y1, then calculate the similarity between the two row vectors corresponding to each row in A and B in turn. Where Y1 is the first similarity threshold.

[0054] Specifically, take the cosine distance between the two row vectors as the similarity between the two row vectors.

[0055] S601: If P ≥ Y1, then the climbing scaffold 3 has not deformed.

[0056] S700: If the similarity between the two row vectors corresponding to any one row is less than the second similarity threshold Y2, then determine the preset deformation monitoring part corresponding to this row as the deformed part.

[0057] S701: If the similarity between the two row vectors corresponding to all rows is greater than or equal to the second similarity threshold Y2, then the climbing scaffold 3 has not deformed.

[0058] Y1 and Y2 in the above embodiments can be determined according to the data performance when deformation occurs in the actual use scenario. Usually, these thresholds are analyzed and determined and continuously optimized based on the statistical laws of the subsequent measured data. At the initial stage of the project, the initial threshold settings can be determined through multiple rounds of test analysis. And during the implementation of the project, continuously analyze the data change situation and optimize the threshold settings. Based on the statistical laws of the measured data: for some complex stress conditions such as personnel activities, strong winds, thunderstorms, etc., the data calculation and analysis results are used as a reference, and long-term continuous observations are carried out before and after the lifting of the attached lifting scaffold, and the statistical laws of the observed data are analyzed, and these statistical laws are used as the thresholds for structural monitoring.

[0059] In addition, since the degree of deformation in actual use may vary, a corresponding early warning reminder mechanism may be established according to the degree of deformation. Specifically, after determining that the corresponding part is deformed, in this embodiment, the corresponding level of early warning may be generated by comparing the relationship between the actual deformation value (i.e., the measured displacement value) and the preset maximum allowable deformation threshold, thereby more clearly indicating the degree of deformation.

[0060] In this embodiment, three levels of warning can be set to trigger the warning signal early and clearly and accurately describe the degree of deformation. Specifically, the three-level warning state determination in this embodiment can be set according to the content in Table 1 below.

[0061] Table 1

[0062] Serial number Warning level Warning status description 1 Level 1 The measured displacement value reaches 70% to 85% of the maximum allowable deformation threshold 2 Level 2 The measured displacement value reaches 85% to 100% of the maximum allowable deformation threshold 3 Level 3 The measured displacement value reaches the maximum allowable deformation threshold

[0063] In addition, the monitoring system corresponding to the monitoring method in this embodiment is as follows Figure 3 As shown in the figure, it is mainly composed of Beidou monitoring station (deformation monitoring station 1), base station (deformation base station 2) and software service system. The raw data of deformation monitoring station 1 and deformation base station 2 are transmitted to the server through 4G / 5G network for data processing, solution analysis. The system can obtain the millimeter-level three-dimensional time-series displacement change data of each monitoring point, and automatically perform joint calculation and analysis to evaluate the displacement of different monitoring points. These data and analysis results will be displayed on the software platform for the convenience of background personnel to observe and analyze.

[0064] In order to obtain more data related to deformation monitoring and to be able to perform real-time control of related hardware equipment, the software service system of this embodiment also includes existing monitoring software, which has automatic data post-processing and real-time dynamic data processing capabilities at a rate of 1 Hz or above, and can provide three-dimensional coordinates of monitoring points; has the ability to check and alarm the deformation limits of monitoring points, and can set alarms for the maximum deformation of monitoring points and the allowable amount of continuous unidirectional deformation trends; has the ability to store, manage and analyze data; has the ability to automatically manage the entire process; has the ability to output result data; has signal denoising and single epoch deformation solution capabilities; has real-time online data analysis and graphical reporting capabilities; and has the function of monitoring reference point stations and monitoring point stations and adjusting parameters.

[0065] The present invention is a Beidou automated monitoring process method for deformation of super-high-rise building climbing frames, which provides technical demonstration and experience reference for similar projects, assists managers in making scientific decisions, reduces the occurrence of risk events, and protects people's lives and property.

[0066] The technical solution in the present invention is targeted at the characteristics of super-high-rise building climbing frame monitoring. Beidou equipment for super-high-rise buildings is selected, software algorithms are designed, and warning values ​​are proposed to ensure stable and reliable data and timely warnings. Integrating Beidou GNSS, Internet of Things and other technologies, the Beidou data sent by the monitoring equipment is received, stored and managed in real time, realizing 24-hour all-weather deformation monitoring of the climbing frame, evaluating the overall safety performance of the climbing frame, early warning when problems are found, and timely adjustment and reinforcement of the frame to ensure the safety and stability of the frame and prevent the occurrence of malignant accidents such as collapse.

[0067] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0068] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0069] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0070] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as a "circuit", "module" or "system".

[0071] The electronic device according to this embodiment of the present invention is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0072] The electronic device is presented in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: the at least one processor mentioned above, the at least one storage device mentioned above, and a bus connecting different system components (including storage devices and processors).

[0073] The storage stores program codes, which can be executed by the processor, so that the processor executes the steps according to various exemplary embodiments of the present invention described in the above “Exemplary Method” section of this specification.

[0074] The memory may include readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read only memory (ROM).

[0075] The storage may also include a program / utility having a set (at least one) of program modules, such program modules including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include the implementation of a network environment.

[0076] The bus may represent one or more of several types of bus structures including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.

[0077] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may communicate with one or more devices that enable a user to interact with the electronic device, and / or may communicate with any device (e.g., routers, modems, etc.) that enables the electronic device to communicate with one or more other computing devices. Such communication may be performed through an input / output (I / O) interface. Furthermore, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter. The network adapter communicates with other modules of the electronic device through a bus. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0078] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0079] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present invention may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present specification.

[0080] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0081] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0082] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0083] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0084] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0085] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0086] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A deformation monitoring method for climbing scaffolds based on Beidou GNSS, which is applied to climbing scaffolds. A deformation monitoring station is installed at a preset deformation monitoring part of the climbing scaffold to obtain the position information of the corresponding preset deformation monitoring part and generate a corresponding relative position undirected graph; the position information includes Beidou positioning information. It is characterized in that The method includes the following steps: When the installation and commissioning of the climbing scaffold are completed, obtain the initial position information corresponding to multiple preset deformation monitoring parts; According to the initial position information, generate the standard attitude matrix A corresponding to the climbing scaffold; A is an n×n adjacency matrix, where A[i][j]=A[j][i]=d j i , A[i][j] is the value of the element in the i-th row and j-th column of A; d j i is the distance value between the initial position information corresponding to the i-th preset deformation monitoring part and the initial position information corresponding to the j-th preset deformation monitoring part; n is the total number of preset deformation monitoring parts, and both i and j belong to [1, n]; When the preset monitoring conditions are reached, obtain the to-be-detected position information currently corresponding to multiple preset deformation monitoring parts; According to the position information to be detected, generate the attitude matrix B to be detected corresponding to the climbing scaffold; B is an n×n adjacency matrix, where B[i][j]=B[j][i]=e j i , B[i][j] is the value of the element in the i-th row and j-th column of B; e j i is the distance value between the position information to be detected corresponding to the i-th preset deformation monitoring part and the position information to be detected corresponding to the j-th preset deformation monitoring part; Use spectral similarity to calculate the similarity value P between A and B; If P < Y1, then calculate the similarity between the two row vectors corresponding to each row in A and B in turn; where Y1 is the first similarity threshold; If the similarity between the two row vectors corresponding to any one row is less than the second similarity threshold Y2, then determine the preset deformation monitoring part corresponding to this row as the deformed part.

2. The method according to claim 1, characterized in that After using spectral similarity to calculate the similarity value P between A and B, the method further includes: If P ≥ Y1, then the climbing scaffold has not deformed.

3. The method according to claim 1, characterized in that: After calculating the similarity between the two row vectors corresponding to each row in A and B in turn, the method further includes: If the similarity between the two row vectors corresponding to all rows is greater than or equal to the second similarity threshold Y2, then the climbing scaffold has not deformed.

4. The method according to claim 1, characterized in that The use of spectral similarity to calculate the similarity value P between A and B includes: Calculate the Laplacian matrices L1 and L2 corresponding to the undirected graph of the initial position information and the undirected graph of the to-be-detected position information respectively; L1 and L2 satisfy the following conditions: L1 = D1 - A; L2 = D2 - B; where D1 and D2 are the degree matrices corresponding to the undirected graph of the initial position information and the undirected graph of the to-be-detected position information respectively; According to L1 and L2, generate the similarity value P between A and B; P satisfies the following conditions: P=d(L1,L2)=||L1-L2|| F ; Where d(L1, L2) is the spectral norm distance between L1 and L2; ||·|| F is the Frobenius norm.

5. The method according to claim 1, characterized in that: Calculating the similarity between the two row vectors corresponding to each row in A and B includes: Take the cosine distance between the two row vectors as the similarity between the two row vectors.

6. The method according to claim 1, characterized in that The preset monitoring conditions include a preset monitoring period or preset meteorological conditions or preset working conditions.

7. The method according to claim 1, characterized in that The position information of the preset deformation monitoring part is obtained according to the following steps: Establish a deformation reference station around the target building; the deformation reference station adopts a forced centering device, uses a Beidou receiver for overall combined adjustment, and uses a level for elevation measurement; Utilize the differential positioning technology and baseline vector solution method of the Beidou satellite navigation system to obtain the position information of each deformation monitoring station relative to the deformation reference station in different states.

8. The method according to claim 7, characterized in that The installation position of the deformation reference station is in a region with hard texture, firm and reliable, and with an open view. There are no obstacles within the range of elevation angle above 15°.

9. A non-transitory computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the Beidou GNSS-based climbing scaffolding deformation monitoring method as described in any one of claims 1 to 8 is implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the Beidou GNSS-based climbing scaffolding deformation monitoring method as described in any one of claims 1 to 8 is implemented.

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