Risk assessment method based on steel structure grid

Abstract

The invention discloses a risk assessment method based on a steel structure net rack, and belongs to the technical field of building structure safety assessment, and the method comprises the steps: S10, carrying out the sampling detection of a steel material of the steel structure net rack, obtaining the performance parameters of the steel material, and enabling the performance parameters to comprise mechanical parameters; s20, geometric parameters and load parameters of the steel structure net rack are obtained based on the mechanical parameters, wherein the geometric parameters comprise the length of a rod piece, node coordinates and the span and height of the net rack; and S30, screening the performance parameters, the geometric parameters and the load parameters, and removing abnormal values of the performance parameters, the geometric parameters and the load parameters. By combining the performance parameters, the geometric parameters and the load parameters, the safety performance of the steel structure grid frame under different working conditions can be comprehensively evaluated, the collected stress data can be analyzed through a machine learning method, the stress distribution prediction model is constructed, the stress concentration area can be more accurately determined, and the safety performance of the steel structure grid frame under different working conditions is improved. Therefore, the potential risk of the structure is comprehensively evaluated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of building structure safety assessment, and particularly relates to a risk assessment method based on a steel structure net rack. BACKGROUND

[0002] The steel structure net rack is a common space structure form, has the advantages of beautiful appearance, reasonable stress, fast construction, etc., and is widely used in large public buildings such as exhibition centers, sports venues, airports and stations. Since the structural safety of the steel structure net rack is directly related to the safety of the building in use and the safety of people's lives and property, it is very important to detect its safety.

[0003] For this research, the application number CN202111052458.8 provides a health monitoring device and method for a steel structure net rack, which includes a steel structure net rack, a vibrating string sensor, a data acquisition unit and an upper computer server. The data acquisition unit is electrically connected with the vibrating string sensor and the upper computer server. The steel structure net rack is connected with the vibrating string sensor and the data acquisition unit. The upper computer server receives the data sent by the data acquisition unit for analysis to determine whether the steel structure net rack is healthy. The technology can automatically adjust the model parameters according to the judgment result, so that the model after parameter adjustment outputs the latest fluctuation prediction interval to replace the historical fluctuation prediction interval, thereby realizing dynamic updating of the fluctuation prediction interval and improving the health monitoring accuracy of the steel structure net rack.

[0004] Another application number CN202010266562.6 provides a method for monitoring the lifting of an out-of-limit steel structure net rack, which includes S1, establishing an initial model of the steel structure net rack, simulating the construction process, determining the stress concentration point, determining the deflection value, obtaining the optimized bar model diagram, and establishing an initial model; S2, according to the optimized bar model diagram, the actual net rack is constructed; after the construction is completed, the actual net rack is scanned in three dimensions, and a secondary model is established according to the actual net rack, the secondary model is compared with the initial model, the deviation is modified, and the consistency of the two is ensured; S3, arranging a safety monitoring system, including a limited stress monitoring system and a target point displacement monitoring system. The technology adopts the method of modeling, monitoring and adjusting, compares the numerical values of stress, strain and displacement with the warning values, and avoids the occurrence of sudden safety events.

[0005] However, for the risk assessment of the net rack structure under complex working conditions, such as multiple load combinations and nonlinear load actions, the above-mentioned evaluation methods have certain limitations. The existing evaluation methods are mostly based on linear load action for evaluation, and the nonlinear response under complex working conditions is not considered, which makes it difficult to evaluate the potential safety risk of the net rack structure. SUMMARY

[0006] In view of the above problems existing in the prior art of building structure safety assessment, the present application is proposed.

[0007] Therefore, one of the purposes of the present application is to provide a risk assessment method based on a steel structure grid, which can comprehensively evaluate the safety performance of the steel structure grid under different working conditions by combining performance parameters, geometric parameters and load parameters, and can more accurately determine the stress concentration area by analyzing the collected stress data through a machine learning method to construct a stress distribution prediction model, thereby comprehensively evaluating the potential risks of the structure.

[0008] To solve the above technical problems, the present application provides the following technical solutions:

[0009] The present application provides a risk assessment method based on a steel structure grid, comprising the following steps:

[0010] Step S10: Sampling and detecting the steel material of the steel structure grid to obtain the performance parameters of the steel material, the performance parameters including mechanical parameters;

[0011] Step S20: Obtaining the geometric parameters and load parameters of the steel structure grid based on the mechanical parameters, the geometric parameters including the length of the rod, the node coordinates, the grid span and the height;

[0012] Step S30: Screening and removing outliers of the performance parameters, geometric parameters and load parameters, and converting the performance parameters, geometric parameters and load parameters into dimensionless standardized data, and simultaneously constructing a steel structure grid data model based on the standardized data, and performing correlation analysis on the performance parameters, geometric parameters and load parameters in the steel structure grid data model;

[0013] Step S40: Based on the results of the correlation analysis, performing static analysis and modal analysis on the steel structure grid under different load parameters, calculating the response parameters of each rod, and evaluating the load-carrying capacity and stability of the steel structure grid according to the calculated response parameters, the response parameters including stress, strain and displacement;

[0014] Step S50: Generating a risk prediction model according to the evaluation results of the load-carrying capacity and stability of the steel structure grid, and performing risk training on the collected performance parameters, geometric parameters and load parameters in the risk prediction model, the risk training taking the response parameters, load parameters and performance parameters as input features, and taking the damage state of the steel structure grid as output features, and analyzing the regular influence of different response parameters, load parameters and performance parameters on the risk of the steel structure grid;

[0015] Step S60: according to the law, the preset safety threshold of the load parameter is affected, if the load parameter collected in the future period exceeds the safety threshold, it is determined that the steel structure net rack has a safety risk, otherwise, it is not determined.

[0016] As a preferred scheme of the present application, wherein:

[0017] In the step S10, the mechanical parameters include yield strength, tensile strength, elastic modulus and elongation;

[0018] In the step S20, the load parameter is the load distribution of the steel structure net rack, the load distribution includes constant load and live load, and the stress concentration area of the steel structure net rack under the load is determined according to the load distribution.

[0019] As a preferred scheme of the present application, wherein: in the step S20, the stress concentration area of the steel structure net rack under the load is determined according to the load distribution, which is determined by machine learning method, and the steps include:

[0020] Collecting stress data of the steel structure net rack under different load parameters;

[0021] Extracting features associated with the stress data from the load parameters; the associated features include load size;

[0022] Training the stress data by machine learning algorithm to construct a stress distribution prediction model;

[0023] According to the stress distribution prediction model, the stress distribution under the new load parameter is predicted, and the stress concentration area is determined.

[0024] As a preferred scheme of the present application, wherein: in the step S40, the response parameters of each rod are calculated, and the calculation is carried out according to the following formula:

[0025]

[0026] In the formula, σ represents the axial stress, F represents the axial force borne by the rod, and A represents the cross-sectional area of the rod;

[0027]

[0028] In the formula, ∈ represents the axial strain, ΔΒ represents the axial deformation of the rod, and L represents the original length of the rod;

[0029]

[0030] In the formula, u represents displacement, M represents the bending moment on the rod, E represents the elastic modulus of the material of the rod, I represents the sectional moment of inertia of the rod, L represents the original length of the rod, and x represents the coordinate along the length direction of the rod.

[0031] As a preferred scheme of the present application, wherein: the area of the shed roof of the steel structure space truss is obtained, based on the area of the shed roof, at least 6 load test points are divided in the middle of the shed roof and are distributed around, the area of the 6 load test points distributed around is one third of the area of the shed roof, the length of each load test point from the edge of the shed roof is calculated, different loads are applied to each load test point, the load bearing capacity and stability of the steel structure space truss are calculated in the length, and the following formula is used to calculate:

[0032]

[0033] In the formula, C i represents the load bearing capacity of the i th load test point, P i represents the load applied to the i th load test point, and H represents the safety factor, which is determined according to the design specification when the steel structure space truss is built;

[0034] Based on the above formula, the following formula is obtained:

[0035]

[0036] In the formula, S i represents the stability of the i th load test point;

[0037] According to the above formula, the load bearing capacity and stability of the steel structure space truss are comprehensively evaluated, wherein the comprehensive load bearing capacity C 总 is as follows:

[0038]

[0039] The comprehensive stability S 总 is as follows:

[0040]

[0041] As a preferred scheme of the present application, wherein: according to the calculated length of each load test point from the edge of the shed roof, the length is equally divided into different interval segments, in each interval segment, the maximum load bearing capacity of each interval segment is calculated based on the calculated load bearing capacity and stability of the steel structure space truss, and the following formula is used:

[0042] In the formula, C 段 represents the load bearing capacity of each interval segment;

[0043] In the formula, P总 wherein, S represents the sum of the loads applied in all interval segments, n represents the number of interval segments, and H represents a safety factor, which is determined according to a design specification when the steel structure grid is constructed;

[0044] According to the calculated maximum bearing capacity, a critical threshold value of the load is preset, and if the load on the corresponding interval segment in a future period exceeds the critical threshold value, it is determined that the steel structure grid has a safety risk; otherwise, it is not determined.

[0045] As a preferred scheme of the present application, if it is determined that the steel structure grid has a safety risk due to the load on the corresponding interval segment exceeding the critical threshold value, the load changes of adjacent interval segments are collected based on the load on the corresponding interval segment, and the correlation influence of the load changes of adjacent interval segments on the load on the corresponding interval segment is calculated as follows:

[0046]

[0047]

[0048] wherein, P i represents the load of the i-th interval segment, which is the corresponding interval segment; P i-1 and P i+1 are the loads of adjacent interval segments, is the load change amount of the previous interval segment, is the load change amount of the next interval segment.

[0049] As a preferred scheme of the present application, according to the calculated correlation influence, if the load on the corresponding interval segment causes the load of any one of the adjacent interval segments to change significantly, it is determined that the part of the steel structure grid corresponding to the adjacent interval segment has a safety risk, and load positioning is performed on the corresponding part in the steel structure grid; and the safety risk of the corresponding part is evaluated based on the critical threshold value, and the evaluation method includes:

[0050] If the load on the corresponding part exceeds the critical threshold value by 3%, it is determined that the safety risk is low;

[0051] If the load on the corresponding part exceeds the critical threshold value by 6%, it is determined that the safety risk is moderate;

[0052] If the load on the corresponding part exceeds the critical threshold value by 9%, it is determined that the safety risk is high.

[0053] A terminal comprising a processor, an input interface, an output interface and a memory, which are connected to each other, wherein the memory is configured to store a computer program comprising program instructions, and the processor is configured to invoke the program instructions to execute the method as described above.

[0054] A computer-readable storage medium storing a computer program comprising program instructions, which, when executed by a processor, cause the processor to execute the method as described above.

[0055] Advantages:

[0056] 1、The present application can comprehensively evaluate the safety performance of steel structure net rack under different working conditions by combining performance parameters, geometric parameters and load parameters, and can more accurately determine the stress concentration area by analyzing the collected stress data through a machine learning method, thereby comprehensively evaluating the potential risks of the structure.

[0057] 2、Through static analysis and modal analysis, the response parameters (such as stress, strain and displacement) of each rod are calculated, and the load-carrying capacity and stability of the steel structure net rack are evaluated based on these parameters, providing accurate mechanical evaluation results, and through a machine learning algorithm, the stress data is trained to build a stress distribution prediction model, which can more accurately predict the stress distribution under new load parameters, thereby improving the accuracy of risk assessment.

[0058] 3、By calculating the correlation influence of load changes of adjacent interval segments and the load of the current interval segment, the safety influence of load changes on the steel structure net rack can be more accurately evaluated, providing a reference for dynamic monitoring and maintenance of the steel structure net rack. BRIEF DESCRIPTION OF DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor. Among them:

[0060] Fig. 1 The method flowchart of the embodiments of the present application;

[0061] Fig. 2 The flowchart structure diagram of the embodiments of the present application. DETAILED DESCRIPTION

[0062] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the embodiments of the present application will be described clearly and completely below with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the described embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present application.

[0063] Since the prior art has certain limitations for risk assessment of the grid structure under complex working conditions. The existing evaluation methods are mostly based on linear load action for evaluation, and the nonlinear response under complex working conditions is not considered enough, and it is difficult to evaluate the potential safety risk of the grid structure.

[0064] Based on this, the present application provides a risk assessment method based on a steel structure grid, which can comprehensively evaluate the safety performance of the steel structure grid under different working conditions by combining performance parameters, geometric parameters and load parameters, and can analyze the collected stress data by a machine learning method to construct a stress distribution prediction model, which can more accurately determine the stress concentration area, so as to comprehensively evaluate the potential risk of the structure.

[0065] The present application will be further described below through embodiments and in combination with the drawings.

[0066] Reference Figs. 1-2 For an embodiment of the present application, the embodiment provides a risk assessment method based on a steel structure grid, comprising the following steps:

[0067] Step S10: Sampling and detecting the steel material of the steel structure grid to obtain the performance parameters of the steel material, and the performance parameters include mechanical parameters;

[0068] In the present embodiment, the actual performance parameters of the steel material are obtained through sampling and detection, ensuring the accuracy of the evaluation;

[0069] And yield strength, tensile strength, elastic modulus and elongation, etc. These parameters comprehensively cover the main mechanical properties of steel, providing a basis for subsequent structure evaluation;

[0070] At the same time, based on the actual detection data, the evaluation error caused by inaccurate material performance assumption is reduced, and the reliability of the evaluation result is improved;

[0071] Step S20: obtaining the geometric parameters and load parameters of the steel structure grid based on the mechanical parameters, and the geometric parameters include the length of the rod, the node coordinates, the grid span and the height;

[0072] In one possible implementation in this embodiment, the geometric dimensions of the steel structure net rack are accurately measured by using a measuring device such as a three-dimensional laser scanner or a total station, and compared with the design drawings to check whether there is a geometric deviation;

[0073] In this embodiment, the material performance is combined with the geometric parameters and the load parameters to form a complete evaluation system, ensuring the systematicness and comprehensiveness of the evaluation;

[0074] At the same time, the load distribution is determined to provide targeted input for subsequent static analysis and modal analysis, improving the pertinence and effectiveness of the evaluation;

[0075] Step S30: The performance parameters, geometric parameters and load parameters are screened and subjected to outlier processing, and the performance parameters, geometric parameters and load parameters are converted into standardized data without dimension, and a steel structure net rack data model is constructed based on the standardized data, and the performance parameters, geometric parameters and load parameters in the steel structure net rack data model are subjected to correlation analysis;

[0076] In this embodiment, the parameters are converted into standardized data without dimension, which facilitates subsequent analysis and calculation, for example, the material performance parameters, geometric size deviation and load size are normalized to the interval [0, 1] respectively;

[0077] The data are converted into standardized data without dimension, which eliminates the influence of different dimensions and orders of magnitude and improves the comparability and analysis efficiency of the data;

[0078] Step S40: Based on the results of the correlation analysis, the steel structure net rack is subjected to static analysis and modal analysis under different load parameters, the response parameters of each rod are calculated, the carrying capacity and stability of the steel structure net rack are evaluated according to the calculated response parameters, and the response parameters include stress, strain and displacement;

[0079] In this embodiment, the key rod and the weak position are determined to provide the focus object for subsequent risk evaluation;

[0080] Modal analysis can evaluate the response of the structure under dynamic load, which provides a basis for dynamic performance evaluation such as seismic resistance and wind resistance of the structure, and the carrying capacity and stability of the structure are evaluated through the response parameters, which can timely find potential safety problems and provide risk early warning in advance;

[0081] Step S50: generating a risk prediction model according to the evaluation results of the bearing capacity and stability of the steel structure grid, and training the collected performance parameters, geometric parameters and load parameters in the risk prediction model, wherein the risk training takes the response parameters, load parameters and performance parameters as input features, and takes the damage state of the steel structure grid as output features, and analyzes the regular influence of different response parameters, load parameters and performance parameters on the risk of the steel structure grid;

[0082] In this embodiment, the influence of different parameters on the risk of the structure is analyzed through risk training, which provides a scientific basis for optimizing design and maintenance strategy;

[0083] Step S60: presetting a safety threshold for the load parameter according to the regular influence, and if the load parameter collected in the future period exceeds the safety threshold, it is determined that the steel structure grid has a safety risk; otherwise, it is not determined;

[0084] In step S10, the mechanical parameters include yield strength, tensile strength, elastic modulus and elongation;

[0085] In step S20, the load parameter is the load distribution of the steel structure grid, and the load distribution includes constant load and live load, and the stress concentration area of the steel structure grid under the load is determined according to the load distribution;

[0086] In this embodiment, the constant load includes the weight of the structure, the weight of the roof material, etc.;

[0087] The live load includes personnel activity, equipment load, wind load, snow load, etc.

[0088] In step S20, the stress concentration area of the steel structure grid under the load is determined according to the load distribution, which is determined by a machine learning method, and the steps include:

[0089] Collecting stress data of the steel structure grid under different load parameters;

[0090] Extracting features associated with the stress data from the load parameters; the associated features include load size;

[0091] Training the stress data by a machine learning algorithm to construct a stress distribution prediction model;

[0092] According to the stress distribution prediction model, the stress distribution under new load parameters is predicted to determine the stress concentration area,

[0093] In step S40, the response parameters of each member are calculated according to the following formula:

[0094]

[0095] In the formula, σ represents the axial stress, F represents the axial force borne by the rod, and A represents the cross-sectional area of the rod.

[0096]

[0097] In the formula, ∈ represents the axial strain, ΔΒ represents the axial deformation of the rod, and L represents the original length of the rod.

[0098]

[0099] In the formula, u represents the displacement, M represents the bending moment borne by the rod, E represents the elastic modulus of the material of the rod, I represents the sectional moment of inertia of the rod, L represents the original length of the rod, and x represents the coordinate along the length direction of the rod.

[0100] On the basis of the above, the canopy area of the steel structure net rack is obtained, and based on the canopy area, at least six load test points are distributed around the middle of the canopy. The area around the six load test points is one third of the canopy area. The length of each load test point from the edge of the canopy is calculated, different loads are applied to each load test point, the carrying capacity and stability of the steel structure net rack are calculated in the length, and the following formula is used to calculate:

[0101]

[0102] In the formula, C i represents the carrying capacity of the i-th load test point, P i represents the load applied to the i-th load test point, and H represents the safety factor, which is determined according to the design specification when the steel structure net rack is built.

[0103] Based on the above formula, the following formula is obtained:

[0104]

[0105] In the formula, S i represents the stability of the i-th load test point.

[0106] According to the above formula, the carrying capacity and stability of the steel structure net rack are comprehensively evaluated, wherein the comprehensive carrying capacity C 总 is as follows:

[0107]

[0108] The comprehensive stability S 总 is as follows:

[0109]

[0110] Further, according to the length of each load test point from the edge of the shed roof, the length is equally divided into different interval segments, in each interval segment, the maximum bearing capacity of each interval segment is calculated based on the calculated bearing capacity and stability of the steel structure net rack, as follows:

[0111] wherein C 段 represents the bearing capacity of each interval segment;

[0112] wherein P 总 represents the total of the load applied in all interval segments, n represents the number of interval segments, and H represents the safety factor, which is determined according to the design specification when the steel structure net rack is built;

[0113] According to the calculated maximum bearing capacity, a critical threshold of the load is preset, if the load on the corresponding interval segment in the future period exceeds the critical threshold, it is determined that the steel structure net rack has a safety risk; otherwise, it is not determined,

[0114] The embodiment needs to emphasize that if the steel structure net rack is determined to have a safety risk due to the load on the corresponding interval segment exceeding the critical threshold, the load change of the adjacent interval segment is collected based on the load on the corresponding interval segment, and the correlation influence of the load change of the adjacent interval segment and the load on the corresponding interval segment is calculated, as follows:

[0115]

[0116] wherein P i represents the load of the i-th interval segment, which is the corresponding interval segment; P i-1 and P i+1 are the loads of the adjacent interval segments, is the load change amount of the previous interval segment, is the load change amount of the next interval segment;

[0117] In the embodiment, the load changes of the adjacent interval segments are over-collected, the influence of the load change on the structure is dynamically evaluated, the dynamicity and real-time of the evaluation are improved, at the same time, the correlation influence of the load change is calculated, which can identify the propagation path and influence range of the load change, and provide a basis for local reinforcement and maintenance of the structure;

[0118] On the basis of the above, according to the calculated correlation influence, if the load on the corresponding interval segment causes the load of any one adjacent interval segment to change, it is determined that the part corresponding to the adjacent interval segment in the steel structure net rack has a safety risk, and load positioning is performed on the corresponding part in the steel structure net rack; at the same time, the safety risk existing in the corresponding part is evaluated based on the critical threshold, and the evaluation methods include:

[0119] If the load on the corresponding part exceeds the critical threshold of 3%, the safety risk is determined to be low risk;

[0120] If the load on the corresponding part exceeds the critical threshold of 6%, the safety risk is determined to be medium risk;

[0121] If the load on the corresponding part exceeds the critical threshold of 9%, the safety risk is determined to be high risk;

[0122] In this embodiment, the safety risk is graded by the critical threshold, which can more intuitively reflect the safety state of the structure and provide specific decision basis for maintenance and management;

[0123] And the load positioning of the part with risk can quickly locate the problem area and improve the maintenance efficiency.

[0124] A terminal comprising a processor, an input interface, an output interface and a memory, the processor, the input interface, the output interface and the memory are connected to each other, wherein the memory is used to store a computer program, the computer program comprises program instructions, the processor is configured to invoke the program instructions, and is used to execute the method as described above.

[0125] A computer readable storage medium, the computer readable storage medium stores a computer program, the computer program comprises program instructions, the program instructions, when executed by a processor, cause the processor to execute the method as described above.

[0126] In summary, the present application can comprehensively evaluate the safety performance of the steel structure net rack under different working conditions by combining performance parameters, geometric parameters and load parameters, and can analyze the collected stress data by a machine learning method, construct a stress distribution prediction model, and more accurately determine the stress concentration area, so as to comprehensively evaluate the potential risk of the structure.

[0127] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit it, although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the present application, and all should be covered in the scope of the claims of the present application.

Claims

1. A risk assessment method based on steel structure space frame, characterized in that, Includes the following steps: step S10: Sample and test the steel material of the steel structure space frame to obtain the performance parameters of the steel material, including mechanical parameters; Step S20: Obtain the geometric parameters and load parameters of the steel structure space frame based on the mechanical parameters. The geometric parameters include member length, node coordinates, space frame span, and height. Step S30: Screen and remove outliers from the performance parameters, geometric parameters, and load parameters, and convert the performance parameters, geometric parameters, and load parameters into dimensionless standardized data. At the same time, construct a steel structure space frame data model based on the standardized data, and perform correlation analysis on the performance parameters, geometric parameters, and load parameters within the steel structure space frame data model. Step S40: Based on the results of the correlation analysis, perform static and modal analysis on the steel structure space frame under different load parameters, calculate the response parameters of each member, and evaluate the bearing capacity and stability of the steel structure space frame based on the calculated response parameters. The response parameters include stress, strain and displacement. Step S50: Generate a risk prediction model based on the assessment results of the bearing capacity and stability of the steel structure space frame. Perform risk training on the collected performance parameters, geometric parameters and load parameters in the risk prediction model. The risk training uses the response parameters, load parameters and performance parameters as input features and the damage state of the steel structure space frame as output features. Analyze the regular influence of different response parameters, load parameters and performance parameters on the risk of the steel structure space frame. Step S60: According to the aforementioned pattern, a preset safety threshold for load parameters is affected. If the load parameters collected in future time periods exceed the safety threshold, it is determined that the steel structure space frame has a safety risk. Conversely, no judgment is made.

2. The risk assessment method based on a steel structure space frame as described in claim 1, characterized in that, In step S10, the mechanical parameters include yield strength, tensile strength, elastic modulus, and elongation. In step S20, the load parameter is the load distribution of the statistical steel structure space frame, which includes dead load and live load, and the stress concentration area of ​​the steel structure space frame under load is determined based on the load distribution.

3. The risk assessment method based on a steel structure space frame as described in claim 2, characterized in that, In step S20, the stress concentration areas of the steel structure space frame under load are determined based on the load distribution, and this determination is performed using machine learning methods. The steps include: Collect stress data of steel space frame under different load parameters; Extract features associated with the stress data from the load parameters; the associated features include load magnitude. A stress distribution prediction model is constructed by training the stress data using machine learning algorithms. Based on the stress distribution prediction model, the stress distribution under the new load parameters is predicted, and the stress concentration area is determined.

4. The risk assessment method based on a steel structure space frame as described in claim 1, characterized in that, In step S40, the response parameters of each member are calculated using the following formula: In the formula, σ represents axial stress, F represents the axial force on the member, and A represents the cross-sectional area of ​​the member. In the formula, ∈ represents axial strain, ΔB represents the axial deformation of the rod, and L represents the original length of the rod; In the formula, u represents displacement, M represents bending moment on the member, E represents elastic modulus of the member material, I represents moment of inertia of the member section, L represents original length of the member, and x represents coordinate along the length of the member.

5. The risk assessment method based on a steel structure space frame as described in claim 1, characterized in that, Obtain the roof area of ​​the steel structure space frame. Based on the roof area, divide the middle of the roof into at least 6 surrounding load test points. The area of ​​the 6 surrounding load test points is one-third of the roof area. Calculate the length of each load test point from the edge of the roof. Apply different loads to each load test point. Calculate the load-bearing capacity and stability of the steel structure space frame within the calculated lengths using the following formula: In the formula, C i P represents the bearing capacity of the i-th load test point. i H represents the load applied to the i-th load test point, and H represents the safety factor, which is determined according to the design specifications when constructing the steel structure space frame. Based on the above formula, the following formula is derived: In the formula, S i Indicates the stability of the i-th load test point; Based on the above formula, the load-bearing capacity and stability of the steel structure space frame are comprehensively evaluated, where the comprehensive load-bearing capacity C 总 As shown below: Overall stability S 总 As shown below:

6. The risk assessment method based on a steel structure space frame as described in claim 5, characterized in that, Based on the calculated distance from each load test point to the edge of the roof, the lengths are equally divided into different intervals. Within each interval, the maximum bearing capacity is calculated based on the calculated bearing capacity and stability of the steel structure space frame, as shown below: Among them, C 段 This indicates the carrying capacity of each interval segment; In the formula, P 总 This represents the total load applied in all the intervals, where n represents the number of intervals and H represents the safety factor, which is determined according to the design specifications for constructing the steel structure space frame. Based on the calculated maximum bearing capacity, a critical threshold for the load is preset. If the load on the corresponding interval in the future exceeds the critical threshold, the steel structure space frame is determined to have a safety risk; otherwise, no determination is made.

7. The risk assessment method based on a steel structure space frame as described in claim 6, characterized in that, If the steel structure space frame is deemed to have a safety risk because the load on the corresponding interval exceeds the critical threshold, then the load changes of adjacent intervals are collected based on the load on this corresponding interval, and the correlation between the load changes of adjacent intervals and the load on the corresponding interval is calculated, as shown below: In the formula, P i This represents the load of the i-th interval segment, where the i-th interval segment is the corresponding interval segment; P i-1 and P i+1 For the loads of adjacent intervals, This represents the load change in the previous interval. This represents the load change in the next interval.

8. The risk assessment method based on a steel structure space frame as described in claim 7, characterized in that, Based on the calculated correlation effects, if the load on the corresponding interval segment causes an increase in the load on any adjacent interval segment, then the portion of the steel structure space frame corresponding to this adjacent interval segment is determined to have a safety risk, and the load on this corresponding portion is located within the steel structure space frame; simultaneously, the safety risk of the corresponding portion is assessed based on the critical threshold, and the assessment methods include: If the load on the corresponding part exceeds the critical threshold by 3%, the safety risk is determined to be low. If the load on the corresponding part exceeds the critical threshold by 6%, the safety risk is determined to be medium risk. If the load on the corresponding part exceeds the critical threshold by 9%, the safety risk is determined to be high.

9. A terminal, characterized in that, The system includes a processor, an input interface, an output interface, and a memory, which are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to invoke the program instructions to execute the method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1 to 8.

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