Scaffold stability analysis method and device

Abstract

The invention discloses a scaffold stability analysis method and device. The scaffold stability analysis method comprises the following steps: acquiring a node flexural rigidity random value interval of a scaffold; material parameters and geometric parameters of the scaffold are determined, joint freedom degrees at the overlapping positions of transverse rod units, longitudinal rod units and spring units of the scaffold are coupled, real constants of the spring units are randomly valued in a joint flexural rigidity random valuing interval, and a scaffold structure model is formed; adding constraints and initial defects to the scaffold structure model according to an actual application scene; applying a first load to the scaffold structure model, and performing nonlinear buckling analysis; and according to a result obtained by nonlinear buckling analysis, a buckling coefficient and a buckling mode which can indicate stability are extracted. According to the scaffold stability analysis method, the error of scaffold stability analysis is reduced, and the obtained buckling coefficient and buckling mode capable of indicating the stability are more accurate.

Description

Technical Field

[0001] The present application relates to the technical field of scaffolding, and in particular to a scaffolding stability analysis method and device. Background Art

[0002] Scaffolding refers to temporary facilities built at the construction site to meet the needs of construction work, mainly composed of steel pipes, fasteners, scaffolding boards, connectors, etc. Its main function is to provide a working platform and passage for construction workers, facilitate high-altitude operations and hang safety nets and other safety measures.

[0003] At present, technicians have studied the mechanical properties of the socket-type wheel-lock steel pipe scaffolding connection nodes and the scaffolding as a whole through experimental and simulation methods, summarized the influence of factors such as the material structure and geometric dimensions of the connection nodes on the overall stability of the scaffolding, and clarified the overall buckling capacity of the scaffolding; and by combining the initial geometric defects of the scaffolding with the eigenvalue buckling of the scaffolding, a nonlinear buckling analysis was carried out to find the influence of the initial geometric defects on the overall stability of the scaffolding.

[0004] However, in the study of scaffolding stability, the nodes used in the numerical model of the frame established by technicians are mostly under ideal conditions, and do not include any problems of reduced node bending stiffness due to factors such as wear of node components and position differences when connecting nodes. As a result, the results of the stability analysis of the scaffolding under ideal conditions are greater than the stability of the scaffolding in actual projects, which in turn results in large errors. Summary of the invention

[0005] The embodiments of the present application provide a scaffolding stability analysis method and device, thereby solving the technical problem in the prior art that the result of stability analysis of a scaffolding under ideal conditions is greater than the stability of the scaffolding in actual engineering, thereby causing a large error.

[0006] In the first aspect, an embodiment of the present application provides a scaffolding stability analysis method, which includes: obtaining a random value interval of the node bending stiffness of the scaffolding; determining the material parameters and geometric parameters of the scaffolding, and coupling the node degrees of freedom at the overlapping points of each cross bar unit, longitudinal bar unit and spring unit of the scaffolding, and randomly taking the real constant of each spring unit within the random value interval of the node bending stiffness to form a scaffolding structure model; adding constraints and initial defects to the scaffolding structure model according to actual application scenarios; applying a first load to the scaffolding structure model, and performing a nonlinear buckling analysis; and extracting the buckling coefficient and buckling mode that can indicate stability based on the results obtained from the nonlinear buckling analysis.

[0007] In combination with the first aspect, in a possible implementation method, obtaining the random value interval of the node bending stiffness of the scaffolding includes: obtaining the moment-rotation curve determined by the scaffolding bending test; based on the moment-rotation curve, determining the area enclosed between the maximum curve and the minimum curve of the ultimate bending bearing capacity of the scaffolding as the random value interval of the node bending stiffness.

[0008] In combination with the first aspect, in a possible implementation method, adding constraints and initial defects to the scaffolding structure model according to the actual application scenario includes: completely fixing the sweeping rod of the scaffolding structure model and applying lateral constraints to the top of the scaffolding structure model; adding the initial defects to the scaffolding structure model.

[0009] In combination with the first aspect, in a possible implementation, the adding of initial defects to the scaffolding structure model includes: applying a second load to each top of the scaffolding structure model, and performing an eigenvalue buckling analysis to obtain a first-order buckling mode; and adding a preset proportion of the amplitude of the first-order buckling mode as the initial defect to the scaffolding structure model.

[0010] In combination with the first aspect, in a possible implementation manner, the preset ratio is 1 / 100.

[0011] In combination with the first aspect, in a possible implementation manner, the geometric parameters include the number of horizontal spans, the number of vertical spans, and the number of steps of the scaffolding.

[0012] In the second aspect, an embodiment of the present application provides a scaffolding stability analysis device, which includes: an acquisition module for acquiring a random value interval of the node bending stiffness of the scaffolding; a modeling module for determining the material parameters and geometric parameters of the scaffolding, and coupling the node degrees of freedom at the overlapping points of each cross bar unit, longitudinal bar unit and spring unit of the scaffolding, and randomly taking the real constant of each spring unit within the random value interval of the node bending stiffness to form a scaffolding structure model; an adding module for adding constraints and initial defects to the scaffolding structure model according to actual application scenarios; an analysis module for applying a first load to the scaffolding structure model and performing a nonlinear buckling analysis; an extraction module for extracting the buckling coefficient and buckling mode that can indicate stability based on the results obtained from the nonlinear buckling analysis.

[0013] In combination with the second aspect, in a possible implementation method, the acquisition module is specifically used to: obtain the moment-rotation curve determined by the scaffolding bending test; based on the moment-rotation curve, determine the area enclosed between the maximum curve and the minimum curve of the scaffolding's ultimate bending bearing capacity as the random value interval of the node bending stiffness.

[0014] In combination with the second aspect, in a possible implementation, the adding module includes: a first adding module, used to completely fix the sweeping rod of the scaffolding structure model and apply lateral constraints to the top of the scaffolding structure model; a second adding module, used to add the initial defect to the scaffolding structure model.

[0015] In combination with the second aspect, in a possible implementation, the second adding module is specifically used to: apply a second load to each top of the scaffolding structure model, and perform eigenvalue buckling analysis to obtain a first-order buckling mode; and add a preset proportion of the first-order buckling mode as the initial defect to the scaffolding structure model.

[0016] In combination with the second aspect, in a possible implementation manner, the preset ratio is H / 100, where H represents the amplitude of the first-order buckling mode.

[0017] In combination with the second aspect, in a possible implementation manner, the geometric parameters include the number of horizontal spans, the number of vertical spans, and the number of steps of the scaffolding.

[0018] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect or any possible implementation method of the first aspect when executing the computer program.

[0019] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the method described in the first aspect or any possible implementation method of the first aspect is implemented.

[0020] The technical solution provided in the embodiments of the present application has at least the following technical effects: An embodiment of the present application provides a scaffolding stability analysis method. In the scaffolding structure model constructed in the method, spring units are used to replace the nodes of the actual scaffolding. By randomly taking values ​​of the real constants of each spring unit within the random value interval of the node bending stiffness, the scaffolding structure model takes into account the situation where random defects exist in the node bending stiffness; and, before performing nonlinear buckling analysis, constraints and initial defects are added to the scaffolding structure model, so that the scaffolding structure model more accurately reflects the fixing method and existing defects of the actual scaffolding; therefore, the method reduces the error of the scaffolding stability analysis, and the obtained buckling coefficient and buckling mode that can indicate stability are more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 A flow chart of a scaffold stability analysis method provided in an embodiment of the present application; Figure 2 A schematic diagram of a scaffolding structure model provided in an embodiment of the present application; Figure 3A-3D A schematic diagram of a scaffold bending test provided in an embodiment of the present application; Figure 4 The bending moment-rotation angle curve of the scaffold provided in the embodiment of the present application; Figure 5 A random value interval of the node bending stiffness of the scaffold provided in the embodiment of the present application; Figure 6 In an example of using the scaffold stability analysis method provided in an embodiment of the present application to study the effect of the size of the random value interval of the node bending stiffness on the overall stability of the scaffold, two sets of buckling coefficients are obtained; Fig. 7A for Figure 6 A top view of the buckling mode corresponding to the buckling coefficient located at the upper layer in the buckling coefficient of the random value interval of 0.25 times the node bending stiffness; Figure 7B for Figure 6 A top view of the buckling mode corresponding to the buckling coefficient at the lower layer in the buckling coefficient of the random value interval of 0.25 times the node bending stiffness; Figure 7C for Figure 6 Stereoscopic diagram of buckling modes corresponding to random value intervals of mid-node bending stiffness; Fig.7D for Figure 6 Top view of the buckling mode corresponding to the random value interval of the mid-node bending stiffness; Figure 8 The scaffold stability analysis method provided in the embodiment of the present application is used to study the buckling coefficients corresponding to the scaffolds with different numbers of layers in another example of scaffolds with different numbers of layers whose node bending stiffness is randomly selected within the random value interval of the node bending stiffness; Fig. 9In another example of using the scaffold stability analysis method provided in the embodiment of the present application to study the influence of the node bending stiffness on the overall stability of the scaffold with or without a wall tie within the random value interval of the node bending stiffness, the buckling coefficient corresponding to the scaffold with or without a wall tie is provided; Fig.10 A schematic diagram of the structure of a scaffolding stability analysis device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0024] The embodiment of the present application provides a scaffold stability analysis method, which includes steps S101 to S105. Figure 1 shown.

[0025] S101: Obtain a random value interval of the node bending stiffness of the scaffold.

[0026] The random value range of the node bending stiffness is set in advance to provide a basis for the subsequent selection of real constants of each spring unit of the scaffolding.

[0027] S102: determining material parameters and geometric parameters of the scaffold, coupling the node degrees of freedom at the overlapped positions of the crossbar units, longitudinal bar units and spring units of the scaffold, and randomly selecting the real constants of the spring units within the random value interval of the node bending stiffness, to form a scaffold structure model; Specifically, the geometric parameters of the scaffolding include the number of horizontal spans, vertical spans and steps of the scaffolding; the material parameters of the scaffolding include tensile strength, compressive strength, bending strength, yield strength and elastic modulus.

[0028] By coupling the node degrees of freedom at the overlap of each crossbar unit, longitudinal bar unit and spring unit of the scaffold, the various parts of the scaffold with determined material parameters and geometric parameters can be assembled together; the spring unit is used to replace the nodes of the actual scaffold. By randomly selecting the real constants of each spring unit within the random value interval of the node bending stiffness, the scaffolding structure model formed takes into account the situation where the bending stiffness of each node has random defects, reducing the error caused by the stability analysis of the scaffold under ideal conditions.

[0029] The number of units at different positions is not the same. There are a maximum of nine units at the internal nodes of the scaffolding, including: two X-direction cross bar units, two Y-direction cross bar units, and two spring units that replace the X-direction scaffolding nodes, two spring units that replace the Y-direction scaffolding nodes, and longitudinal bar units; the number of node units at the corners is at least five units, including: one X-direction cross bar unit and spring unit, one Y-direction cross bar unit and spring unit, and longitudinal bar unit.

[0030] Exemplarily, ANSYS is used to establish a scaffolding structure model; specifically, the material parameters and geometric parameters of the scaffolding are first determined, and based on the determined material parameters and geometric parameters, beam188 units are used in ANSYS to establish the crossbar units and longitudinal bar units of the scaffolding, and the nonlinear spring unit Combin39 is used to replace the semi-rigid nodes of the scaffolding; then the node degrees of freedom at the overlap of each crossbar, longitudinal bar unit and spring unit are coupled by the "CP" command; finally, the real constants of each spring unit are randomly selected within the random interval of the node bending stiffness by using the "do" loop command and the "Rand" command. At this time, due to the different positions of the nodes, the number of bending spring units (SC) is also different, thereby forming an overall structural model of the scaffolding considering the presence of random defects in the node bending stiffness, such as Figure 2 shown.

[0031] S103: Add constraints and initial defects to the scaffolding structure model according to the actual application scenario.

[0032] In the scaffolding structure model established in step S102, the top and bottom of the scaffolding structure model are in a free state, which is different from the state of the scaffolding in the actual application scenario. Constraints are added to the scaffolding structure model according to the actual application scenario, that is, constraints are set on the top and bottom of the scaffolding, so that the scaffolding structure model after adding constraints accurately reflects the scaffolding fixing method in the actual application scenario.

[0033] Due to reasons such as material properties, processing accuracy, installation quality, and construction errors, there are usually initial defects in the actual scaffolding compared to the ideal scaffolding structure model. The initial defects include material defects, geometric defects, connection defects, and construction errors. Adding initial defects to the scaffolding structure model enables the scaffolding structure model to reflect the defects of the actual scaffolding, thereby reducing the error of the scaffolding stability analysis.

[0034] S104: Apply the first load to the scaffolding structure model and perform nonlinear buckling analysis.

[0035] The first load applied to the scaffolding structure model represents the workers, materials, etc. carried by the actual scaffolding during use, and then through step S104, the nonlinear buckling that may occur in the actual scaffolding during use can be analyzed.

[0036] S105: Based on the results of nonlinear buckling analysis, the buckling coefficient and buckling mode that can indicate stability are extracted.

[0037] Among them, the product of the maximum value of the buckling coefficient and the first load is the critical force when the scaffolding buckles in actual situations.

[0038] In the scaffolding stability analysis method provided in the embodiment of the present application, the scaffolding structure model uses spring units to replace the nodes of the actual scaffolding, and the real constants of each spring unit are randomly selected within the random value interval of the node bending stiffness. Before performing the nonlinear buckling analysis, initial constraints and initial defects are added to the scaffolding structure model, so that the established scaffolding structure model can more accurately reflect the actual scaffolding, and the buckling coefficient and buckling mode indicating stability obtained by performing nonlinear buckling analysis on the scaffolding structure model have smaller errors.

[0039] In some embodiments of the present application, step S101 specifically includes step S201 to step S202.

[0040] S201: Obtain the bending moment-rotation angle curve determined by the scaffolding bending test.

[0041] When executing step S201, according to the actual situation and design requirements, several groups of scaffolding nodes are subjected to bending tests, such as FIG. 3A to FIG. 3D As shown, the moment-rotation curve of the scaffolding node under the actual state is obtained, as shown in Figure 4 The obtained bending moment-rotation curve can describe the deformation behavior of the scaffolding and is an important basis for judging the bearing capacity of the scaffolding.

[0042] S202: According to the bending moment-rotation curve, the area enclosed by the maximum curve and the minimum curve of the ultimate bending bearing capacity of the scaffold is determined as the random value interval of the node bending stiffness.

[0043] The bending stiffness of the node is a key parameter of the scaffolding, which directly affects the overall stability and bearing capacity of the scaffolding. However, due to the influence of various factors such as material properties, manufacturing accuracy, and installation quality, the bending stiffness of the node usually has a certain degree of randomness. The maximum curve of the ultimate bending bearing capacity represents the maximum bending bearing capacity that the scaffolding node can withstand under ideal or optimal conditions. The minimum curve of the ultimate bending bearing capacity represents the minimum bending bearing capacity that the scaffolding node can withstand under unfavorable or worst conditions.

[0044] The random value interval of the node bending stiffness obtained by executing step S202 is as follows: Figure 5 As shown. Due to the randomness of the node bending stiffness of the scaffold, its actual value may fall anywhere between the maximum curve and the minimum curve. The random value interval of the node bending stiffness obtained by executing step S202 helps to more comprehensively evaluate the stability and bearing capacity of the scaffold, especially when considering uncertainty and risk.

[0045] In some embodiments of the present application, step S103 specifically includes step S301 to step S302.

[0046] S301: Completely fix the sweeping rod of the scaffolding structure model, and apply lateral constraints to the top of the scaffolding structure model.

[0047] The sweeping rod of the scaffolding structure model is completely fixed, which means that the sweeping rod of the actual scaffolding is fixed to the ground, and the lateral constraint imposed on the top of the scaffolding structure model represents the wall connection member. After executing step S301, the constraints imposed on the scaffolding structure model and the actual scaffolding are the same, so that the scaffolding structure model more accurately reflects the application scenario of the actual scaffolding.

[0048] S302: Adding initial defects to the scaffolding structure model.

[0049] Furthermore, step S302 specifically includes step S401 to step S402.

[0050] S401: Apply a second load to each top of the scaffolding structure model, and perform an eigenvalue buckling analysis to obtain a first-order buckling mode.

[0051] The second load can stimulate the potential buckling behavior of the scaffolding structure model, so that the buckling mode of the scaffolding structure model can be more clearly identified in the eigenvalue buckling analysis.

[0052] Eigenvalue buckling analysis is a linear stability analysis method that can predict the buckling behavior of the scaffolding structure model under the second load. The buckling mode and buckling factor of the scaffolding structure model can be obtained through the eigenvalue buckling analysis. The buckling mode can represent the shape change of the scaffolding structure model when buckling occurs, and the buckling factor represents the ratio between the load required when the scaffolding structure model buckles and the current load.

[0053] S402: Adding a preset proportion of the amplitude of the first-order buckling mode as an initial defect to the scaffolding structure model.

[0054] In the eigenvalue buckling analysis of the scaffolding structure model, multiple buckling modes are obtained, which are arranged in order from small to large buckling factors. The first-order buckling mode is the mode with the smallest buckling factor and is also the most likely buckling mode. Therefore, in the stability analysis of the scaffolding structure model, using the preset ratio of the amplitude of the first-order buckling mode as the initial defect can more accurately simulate the initial defects existing in the actual scaffolding, thereby reducing the error of the scaffolding stability analysis results.

[0055] Exemplarily, the preset ratio is 1 / 100.

[0056] It should be noted that in some other embodiments of the present application, when implementing step S302, the parameters of the initial defects can be set directly in the scaffolding structure model according to measured data or empirical values, for example, the initial bending value, node deflection angle, etc. can be directly input into the scaffolding structure model.

[0057] In a specific example, the above scaffolding stability analysis method is used to study the influence of the random value interval of the node bending stiffness on the overall stability of the scaffolding. It should be noted that the random value interval of the node bending stiffness in this example is determined by the above steps S201 and S202.

[0058] Specifically, the random value interval of the node bending stiffness is proportionally reduced to 0.25 times as a comparison, and the above scaffolding stability analysis method is executed 300 times in a cycle. The two sets of buckling coefficients obtained are as follows: Figure 6 As shown, Figure 6 Rs represents the random value interval of the node bending stiffness. The buckling coefficient of the random value interval of 0.25 times the node bending stiffness has a stratified phenomenon. Fig. 7A for Figure 6 A top view of the buckling mode corresponding to the buckling coefficient located at the upper layer in the buckling coefficient of the random value interval of 0.25 times the node bending stiffness; Figure 7B for Figure 6 Top view of the buckling mode corresponding to the buckling coefficient of the lower layer in the buckling coefficient range of 0.25 times the node flexural stiffness. Figure 7C and Fig.7D Respectively Figure 6 Stereo and top views of the buckling modes corresponding to random intervals of midnode flexural stiffness.

[0059] From the perspective of discreteness, the differences in the bending stiffness of the scaffolding nodes have a certain impact on the overall stability of the scaffolding, and by comparing Figure 6From the random value interval of node bending stiffness and the size of the buckling coefficient in the random value interval of 0.25 times the node bending stiffness, it can be found that: the larger the overall value of the random value interval of node bending stiffness, the better the overall stability of the scaffolding; in particular, the buckling coefficient in the random value interval of 0.25 times the node bending stiffness has a stratification phenomenon. By observing its buckling mode, it can be found that the buckling coefficient of the scaffolding is mostly determined by the buckling mode. In the top view of the buckling mode, it is found that the overall stability of the scaffolding when the frame undergoes torsional deformation is worse than the stability of the frame when only bending deformation occurs.

[0060] In another specific example, the above-mentioned scaffolding stability analysis method is used to study the influence of the scaffolding with random node bending stiffness in the random value interval of the node bending stiffness, the number of scaffolding layers changes from 4 to 10, and the presence or absence of wall connecting parts at the top of the 4-layer scaffolding on the overall stability performance of the scaffolding. It should be noted that the random value interval of the node bending stiffness in this example is determined by the above-mentioned steps S201 and S202. The above-mentioned scaffolding stability analysis method is iterated 300 times, and the results are as follows: Figure 8 and Fig. 9 shown.

[0061] From the perspective of discreteness, the stability of scaffolding with a low number of floors is more affected by the difference in node bending stiffness than that of scaffolding with a high number of floors, and the stability of scaffolding with wall ties is more affected by the difference in node bending stiffness. From the perspective of data size, the stability of scaffolding with a low number of floors is higher than that of scaffolding with a high number of floors, and setting wall ties at the top will greatly improve the stability of the scaffolding.

[0062] It can be seen from the above two specific examples that the scaffolding stability analysis method provided in the embodiment of the present application can be applied to the study of most scaffolding overall stability issues, which reflects that the method has strong adaptability and high efficiency.

[0063] like Figure 6 As shown, the embodiment of the present application further provides a scaffold stability analysis device 1000 , which includes an acquisition module 1001 , a modeling module 1002 , an adding module 1003 , an analysis module 1004 and an extraction module 1005 .

[0064] The acquisition module 1001 is used to obtain the random value interval of the node bending stiffness of the scaffold. The modeling module 1002 is used to determine the material parameters and geometric parameters of the scaffold, and couple the node degrees of freedom at the overlap of each crossbar unit, longitudinal bar unit and spring unit of the scaffold, and randomly take the real constant of each spring unit within the random value interval of the node bending stiffness to form a scaffolding structure model. The adding module 1003 is used to add constraints and initial defects to the scaffolding structure model according to the actual application scenario. The analysis module 1004 is used to apply the first load to the scaffolding structure model and perform nonlinear buckling analysis. The extraction module 1005 is used to extract the buckling coefficient and buckling mode that can indicate stability based on the results obtained from the nonlinear buckling analysis.

[0065] Among them, the geometric parameters include the number of horizontal spans, vertical spans and steps of the scaffolding.

[0066] The acquisition module 1001 is specifically used to: obtain the bending moment-rotation curve determined by the scaffold bending test; according to the bending moment-rotation curve, determine the area enclosed between the maximum curve and the minimum curve of the scaffold's ultimate bending bearing capacity as the random value interval of the node bending stiffness.

[0067] The adding module 1003 includes a first adding module and a second adding module. The first adding module is used to completely fix the sweeping rod of the scaffolding structure model and apply lateral constraints on the top of the scaffolding structure model; the second adding module is used to add initial defects to the scaffolding structure model.

[0068] The second adding module is specifically used for: applying a second load to each top of the scaffolding structure model, and performing eigenvalue buckling analysis to obtain a first-order buckling mode; and adding a preset proportion of the amplitude of the first-order buckling mode as an initial defect to the scaffolding structure model.

[0069] Exemplarily, the preset ratio is 1 / 100.

[0070] The devices or modules described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. For the convenience of description, the above system is described by dividing it into various modules according to its functions. When implementing the embodiments of the present application, the functions of each module can be implemented in the same or more software and / or hardware. Of course, the module that implements a certain function can also be implemented by combining multiple sub-modules or sub-units.

[0071] Some modules in the apparatus described in the present application may also be computer executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform specific tasks or implement specific abstract data types.

[0072] An embodiment of the present application also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned scaffolding stability analysis method is implemented.

[0073] The embodiment of the present application also provides a computer-readable storage medium, which stores computer-readable instructions. When the computer-readable instructions are executed by a processor, the above-mentioned scaffolding stability analysis method is implemented.

[0074] The above-mentioned storage media include but are not limited to random access memory (RAM), read-only memory (ROM), cache, hard disk drive (HDD) or memory card (Memory Card).

[0075] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other. Each embodiment focuses on the differences from other embodiments.

[0076] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present application.

Claims

1. A scaffold stability analysis method, characterized in that: include: Obtain the random value interval of the node bending stiffness of the scaffolding; Determine the material parameters and geometric parameters of the scaffold, couple the node degrees of freedom at the overlapped positions of the crossbar units, longitudinal bar units and spring units of the scaffold, and randomly select the real constants of the spring units within the random value interval of the node bending stiffness to form a scaffold structure model; Adding constraints and initial defects to the scaffolding structure model according to actual application scenarios; Applying a first load to the scaffolding structure model and performing a nonlinear buckling analysis; Based on the results of the nonlinear buckling analysis, buckling coefficients and buckling modes that can indicate stability are extracted.

2. The method according to claim 1, characterized in that The step of obtaining the random value interval of the node bending stiffness of the scaffold comprises: Obtain the bending moment-rotation curve determined by the scaffolding bending test; According to the bending moment-rotation angle curve, the area enclosed between the maximum curve and the minimum curve of the ultimate bending bearing capacity of the scaffold is determined as the random value interval of the node bending stiffness.

3. The method according to claim 1, characterized in that Adding constraints and initial defects to the scaffolding structure model according to the actual application scenario includes: Completely fix the sweeping rod of the scaffolding structure model and apply lateral constraints to the top of the scaffolding structure model; The initial defects are added to the scaffolding structure model.

4. The method according to claim 3, characterized in that: The adding of initial defects to the scaffolding structure model comprises: Applying a second load to each top of the scaffolding structure model, and performing an eigenvalue buckling analysis to obtain a first-order buckling mode; A preset proportion of the amplitude of the first-order buckling mode is added to the scaffolding structure model as the initial defect.

5. The method according to claim 4, characterized in that The preset ratio is 1 / 100.

6. The method according to claim 1, characterized in that The geometric parameters include the number of horizontal spans, vertical spans and steps of the scaffold.

7. A scaffolding stability analysis device, characterized in that: include: An acquisition module is used to obtain a random value interval of the node bending stiffness of the scaffold; A modeling module, used to determine the material parameters and geometric parameters of the scaffold, couple the node degrees of freedom at the overlapped positions of the crossbar units, longitudinal bar units and spring units of the scaffold, and randomly select the real constants of the spring units within the random value interval of the node bending stiffness to form a scaffolding structure model; An adding module is used to add constraints and initial defects to the scaffolding structure model according to actual application scenarios; An analysis module, used for applying a first load to the scaffolding structure model and performing a nonlinear buckling analysis; The extraction module is used to extract the buckling coefficient and buckling mode that can indicate the stability according to the results obtained by the nonlinear buckling analysis.

8. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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