A method, system, device and medium for evaluating the bearing performance of corroded steel structures

Abstract

The invention discloses a method, system, equipment and medium for evaluating the bearing performance of a corroded steel structure, comprising: performing surface feature scanning on a pre-selected local corroded area on a steel structure to be evaluated, and determining a corrosion evaluation index; performing mapping reconstruction according to a random characterization model of the corroded surface of the steel structure to be evaluated and the corrosion evaluation index, and obtaining a morphology mapping reconstruction result of the corroded surface of the steel structure to be evaluated; establishing a random corroded surface finite element geometric model of a basic component of the steel structure to be evaluated according to the morphology mapping reconstruction result of the corroded surface of the steel structure to be evaluated, and performing finite element simulation calculation to obtain a bearing performance prediction result of the basic component of the steel structure to be evaluated, and evaluating the bearing performance of the steel structure to be evaluated to obtain a bearing performance evaluation result of the corroded steel structure; the invention introduces the surface morphology reconstructed in batches into the finite element model, and the calculation result has higher accuracy, thereby realizing the prediction of the bearing performance and reliability evaluation of the corroded steel structure.

Description

Technical Field

[0001] The present invention belongs to the technical field of durability and safety evaluation of steel structures, and in particular relates to a method, system, equipment and medium for evaluating the bearing performance of corroded steel structures. Background Art

[0002] Large steel structure projects that are exposed to marine, industrial and other corrosive environments for a long time, such as large industrial buildings, bridges, high-voltage transmission towers, offshore oil facilities, etc., often have serious corrosion problems; corrosion causes serious damage to steel structures and even leads to engineering accidents; how to accurately evaluate the remaining service performance of existing corroded steel structures and prevent the occurrence of engineering accidents is a major problem faced by engineering and technical personnel.

[0003] At present, the weight loss method and thickness measurement method are the most commonly used methods for evaluating steel corrosion; the measurement and calculation of corrosion weight loss are relatively simple, but have great limitations, mainly in two aspects: first, the weight loss method can only evaluate the degree of uniform corrosion, and cannot characterize the impact of non-uniform corrosion; second, the weight loss method takes samples at the corroded part, which is actually a destructive measurement method, limited to laboratory analysis, and difficult to apply in actual engineering; the thickness measurement method detects the thickness of the component through a vernier caliper or an ultrasonic thickness gauge, which is a non-destructive measurement method, but usually can only give the thickness of a certain point, cannot reflect the overall corrosion condition of the component, and the result is relatively rough. Summary of the invention

[0004] In view of the technical problems existing in the prior art, the present invention provides a method, system, equipment and medium for evaluating the bearing performance of corroded steel structures, so as to solve the technical problems that the existing methods for evaluating the degree of corrosion and service performance of steel structures are insufficiently accurate, cannot restore the true corrosion morphology, and are prone to damage to the original structure.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] The invention discloses a method for evaluating the bearing performance of a corroded steel structure, comprising the following steps:

[0007] Step 1: Scan the surface features of the pre-selected local corroded area on the steel structure to be evaluated to obtain the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated;

[0008] Step 2: determining the corrosion evaluation index according to the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated;

[0009] Step 3: using a preset corrosion kinetics model, establish a random characterization model of the corroded surface of the steel structure to be evaluated; mapping and reconstructing the corroded surface morphology of the steel structure to be evaluated according to the random characterization model of the corroded surface of the steel structure to be evaluated and the corrosion evaluation index, and obtaining a mapping and reconstruction result of the corroded surface morphology of the steel structure to be evaluated;

[0010] Step 4: According to the reconstruction result of the corroded surface morphology mapping of the steel structure to be evaluated, a random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated is established; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column nodes and steel plate components of the steel structure to be evaluated;

[0011] Step 5: Using a finite element parametric simulation method, a finite element simulation calculation is performed on a random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated, so as to obtain a prediction result of the bearing performance of the basic component of the steel structure to be evaluated;

[0012] Step 6: According to the load-bearing performance prediction results of the basic components of the steel structure to be evaluated and the reliability evaluation theory, the load-bearing performance of the steel structure to be evaluated is evaluated to obtain the load-bearing performance evaluation result of the corroded steel structure.

[0013] Furthermore, in step 1, the surface feature scanning is performed on the pre-selected local area of ​​the steel structure to be evaluated to obtain the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated, which is specifically as follows:

[0014] Randomly select a local rusted area on the steel structure to be evaluated, and perform rust removal treatment to obtain the local rusted area after rust removal treatment;

[0015] A three-dimensional non-contact laser scanner is used to scan the surface features of the local rusted area after the rust removal treatment to obtain a three-dimensional morphology of the rusted surface of the local area of ​​the steel structure to be evaluated; wherein the three-dimensional morphology of the rusted surface of the local area of ​​the steel structure to be evaluated is the three-dimensional point cloud coordinate data of the rusted surface of the local area of ​​the steel structure to be evaluated.

[0016] Furthermore, in step 2, the corrosion evaluation index includes a mechanical property evaluation index and a corrosion morphology characterization;

[0017] Among them, the mechanical property evaluation indicators include corrosion rate, non-uniform corrosion rate and minimum cross-sectional area of ​​corrosion; the corrosion morphology characterization includes overall corrosion morphology characterization and pitting morphology characterization; the overall corrosion morphology characterization includes the average corrosion depth and the standard deviation of the corrosion depth; the pitting morphology characterization includes rust pit depth, rust pit diameter-to-depth ratio, rust pit volume ratio and rust pit density.

[0018] Furthermore, in step 3, the random characterization model of the corroded surface of the steel structure to be evaluated includes a random field model of the corrosion depth of the overall corrosion of the steel structure to be evaluated and a random distribution model of rust pits of the pitting corrosion of the steel structure to be evaluated; the morphology mapping reconstruction result of the corroded surface of the steel structure to be evaluated includes a reconstruction result of the overall corrosion morphology mapping and a reconstruction result of the pitting morphology mapping.

[0019] Furthermore, the construction process of the overall corrosion morphology mapping reconstruction result is as follows:

[0020] Using the preset corrosion dynamics model, a random field model of corrosion depth of the overall corrosion of the steel structure to be evaluated is established;

[0021] Substituting the corrosion evaluation index into the random field model of the corrosion depth of the steel structure to be evaluated, calculating the coordinate data of the overall corrosion point cloud of the corroded surface of the steel structure to be evaluated, that is, obtaining the overall corrosion morphology mapping reconstruction result;

[0022] The process of calculating the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated is as follows:

[0023] Determining a power spectrum of the corrosion depth on the surface of the steel structure to be evaluated according to the average value of the corrosion depth on the surface of the steel structure to be evaluated and the standard deviation of the corrosion depth;

[0024] According to the power spectrum of the corrosion depth on the surface of the steel structure to be evaluated, using a two-dimensional random harmonic function, the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated is calculated, that is, the overall corrosion morphology mapping reconstruction result is obtained;

[0025] The construction process of the pitting morphology mapping reconstruction result is as follows:

[0026] Using the preset corrosion kinetics model, a random distribution model of rust pits for pitting corrosion of the steel structure to be evaluated is established;

[0027] Substituting the corrosion evaluation index into the random distribution model of rust pits of the steel structure to be evaluated, and calculating the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated, that is, obtaining the pitting morphology mapping reconstruction result;

[0028] The process of calculating the pitting point cloud coordinate data of the corroded surface of the steel structure to be evaluated is as follows:

[0029] Determine the number of rust pits according to the density of rust pits on the surface of the steel structure to be evaluated and the pre-calculated surface area of ​​the steel structure to be evaluated; wherein the pre-calculated surface area of ​​the steel structure to be evaluated is calculated by multiplying the surface length dimension and the width dimension of the steel structure to be evaluated;

[0030] Generating random rust pits in batches according to the rust pit depth, rust pit diameter-to-depth ratio, rust pit shape probability parameter and the number of rust pits on the surface of the steel structure to be evaluated;

[0031] According to the batch generation of random rust pits, the pitting point cloud coordinate data of the corroded surface of the steel structure to be evaluated is calculated, that is, the pitting morphology mapping reconstruction result is obtained.

[0032] Furthermore, in step 4, the process of establishing a random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated according to the corroded surface morphology mapping reconstruction result of the steel structure to be evaluated is as follows:

[0033] The rusted surface morphology mapping reconstruction result of the steel structure to be evaluated is subjected to coordinate transformation to obtain random rusted surface point cloud data of the basic components of the steel structure to be evaluated; wherein the random rusted surface point cloud data of the basic components of the steel structure to be evaluated is closed section point cloud data;

[0034] A finite element geometric model of a basic component of the steel structure to be evaluated is constructed, and the random corroded surface point cloud data of the basic component of the steel structure to be evaluated is assigned to the finite element geometric model of the basic component of the steel structure to be evaluated, so as to obtain a random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated.

[0035] Furthermore, in step 5, a finite element parametric simulation method is used to perform finite element simulation calculation on a random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated, so as to obtain a load-bearing performance prediction result of the basic component of the steel structure to be evaluated, as follows:

[0036] For the random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated, material properties are set, loads and boundary conditions are applied, and finite element numerical simulation is performed to obtain the load-bearing performance prediction results of the basic component of the steel structure to be evaluated.

[0037] The present invention also provides a system for evaluating the bearing performance of a corroded steel structure, comprising:

[0038] A scanning module is used to scan the surface features of the pre-selected local corroded area on the steel structure to be evaluated, and obtain the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated;

[0039] An indicator module is used to determine the corrosion evaluation index according to the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated;

[0040] A mapping and reconstruction module is used to establish a random characterization model of the corroded surface of the steel structure to be evaluated by using a preset corrosion dynamics model; and to map and reconstruct the morphology of the corroded surface of the steel structure to be evaluated according to the random characterization model of the corroded surface of the steel structure to be evaluated and the corrosion evaluation index, so as to obtain a mapping and reconstruction result of the morphology of the corroded surface of the steel structure to be evaluated;

[0041] A geometric model module is used to establish a random corrosion surface finite element geometric model of the basic components of the steel structure to be evaluated according to the reconstruction result of the corrosion surface morphology mapping of the steel structure to be evaluated; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column nodes and steel plate components of the steel structure to be evaluated;

[0042] A numerical simulation module is used to perform finite element simulation calculation on a random corroded surface finite element geometric model of a basic component of the steel structure to be evaluated by using a finite element parametric simulation method, so as to obtain a prediction result of the bearing performance of the basic component of the steel structure to be evaluated;

[0043] The evaluation module is used to evaluate the bearing performance of the steel structure to be evaluated based on the bearing performance prediction results of the basic components of the steel structure to be evaluated and the reliability evaluation theory, so as to obtain the bearing performance evaluation result of the corroded steel structure.

[0044] The present invention also provides a device for evaluating the bearing performance of a corroded steel structure, comprising:

[0045] Memory for storing computer programs;

[0046] A processor is used to implement the steps of the method for evaluating the bearing performance of corroded steel structures when executing the computer program.

[0047] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for evaluating the bearing performance of a corroded steel structure are implemented.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The present invention provides a method, system, device and medium for evaluating the bearing capacity of a corroded steel structure. By scanning the surface corrosion features of a representative local area of ​​the steel structure to be evaluated, non-destructive acquisition of corrosion morphology data is achieved, thereby avoiding damage to the original structure. The corrosion evaluation index system established based on the surface morphology can evaluate both the uniform corrosion degree and the non-uniform corrosion degree, thus solving the problem that the original index cannot reflect the influence of non-uniform corrosion. Based on the statistical analysis of morphology data and evaluation indexes, a corrosion surface characterization model for different corrosion environments that meets certain statistical characteristics is established, and large-scale table representation of basic components such as corroded steel structure beams and columns can be achieved based on limited morphology data. Batch mapping and reconstruction of surface morphology provides data support for subsequent structural performance prediction and reliability assessment; finite element analysis software is used to perform numerical calculations on the bearing performance of corroded beams, columns and other components that have been batch mapped and reconstructed. This method introduces the batch reconstructed surface morphology into the finite element model, which can take into account the uncertainty of corrosion characteristics. The calculation results have higher accuracy, realize the prediction of bearing performance and reliability assessment of corroded steel structures, and solve the problem that actual engineering and mechanical performance tests cannot be repeated. The present invention can further enrich the performance evaluation methods in the field of durability and safety of engineering structures, and provide a technical basis for engineering and technical personnel engaged in the detection, evaluation and reinforcement of existing engineering structures. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a flow chart of the method for evaluating the bearing performance of a corroded steel structure described in the embodiment;

[0051] Figure 2 Schematic diagram of the corrosion morphology scanning process of the rusted steel structure in the embodiment;

[0052] Figure 3 It is the corrosion evaluation index system of the rusted steel structure in the embodiment;

[0053] Figure 4 This is a schematic diagram of the point cloud coordinate conversion of the H-beam in the embodiment; wherein, Figure 4 (a) is a schematic diagram of randomly generated surface point cloud arrangement. Figure 4 (b) is a schematic diagram of the point cloud arrangement of the H-beam cross section after coordinate transformation. Figure 4 (c) is the randomly generated surface point cloud of the H-beam cross section. Figure 4 (d) is the point cloud image of the H-beam after coordinate transformation;

[0054] Figure 5 This is a schematic diagram of the finite element geometric model of the randomly generated pitting C-shaped steel column in the embodiment; wherein, Figure 5 (a) is a schematic diagram of the overall finite element geometric model of the randomly generated pitting C-shaped steel column. Figure 5 (b) is a partial enlarged schematic diagram of the finite element geometric model of the randomly generated pitting C-shaped steel column. Figure 5 (c) Schematic diagram of rust pit distribution of the finite element geometric model of randomly generated pitted C-shaped steel column;

[0055] Figure 6 The load-displacement curve of the bending test of the corroded H-steel beam in the embodiment and the load-displacement diagram simulated by the randomly generated finite element model;

[0056] Figure 7 It is the load-displacement curve of the compression test of the corroded C-shaped steel column in the embodiment and the load-displacement diagram simulated by the randomly generated finite element model. DETAILED DESCRIPTION

[0057] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail in the following specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0058] The present invention provides a method for evaluating the bearing performance of a corroded steel structure, comprising the following steps:

[0059] Step 1: Scan the surface features of the pre-selected local corroded area on the steel structure to be evaluated to obtain the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; wherein the specific process of the surface feature scanning is as follows:

[0060] Randomly select a local rusted area on the steel structure to be evaluated, and perform rust removal treatment to obtain the local rusted area after rust removal treatment;

[0061] A three-dimensional non-contact laser scanner is used to scan the surface features of the local rusted area after the rust removal treatment to obtain a three-dimensional morphology of the rusted surface of the local area of ​​the steel structure to be evaluated; wherein the three-dimensional morphology of the rusted surface of the local area of ​​the steel structure to be evaluated is the three-dimensional point cloud coordinate data of the rusted surface of the local area of ​​the steel structure to be evaluated.

[0062] Step 2, determining the corrosion evaluation index according to the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; wherein the corrosion evaluation index includes a mechanical property evaluation index and a corrosion morphology characterization; the mechanical property evaluation index includes a corrosion rate, a non-uniform corrosion rate and a minimum cross-sectional area of ​​corrosion; the corrosion morphology characterization includes a comprehensive corrosion morphology characterization and a pitting morphology characterization; the comprehensive corrosion morphology characterization includes an average corrosion depth and a standard deviation of the corrosion depth; the pitting morphology characterization includes a rust pit depth, a rust pit diameter-to-depth ratio, a rust pit volume ratio and a rust pit density.

[0063] Step 3, using the corrosion evaluation index and the preset corrosion dynamics model, establish a random characterization model of the rusted surface of the steel structure to be evaluated; wherein the random characterization model of the rusted surface of the steel structure to be evaluated includes a random field model of the rust depth of the overall corrosion of the steel structure to be evaluated and a random distribution model of rust pits of the pitting corrosion of the steel structure to be evaluated; according to the random characterization model of the rusted surface of the steel structure to be evaluated, the rusted surface morphology of the steel structure to be evaluated is mapped and reconstructed to obtain a rusted surface morphology mapping reconstruction result of the steel structure to be evaluated; wherein the rusted surface morphology mapping reconstruction result of the steel structure to be evaluated includes a comprehensive corrosion morphology mapping reconstruction result and a pitting morphology mapping reconstruction result.

[0064] The construction process of the comprehensive corrosion morphology mapping reconstruction result is as follows:

[0065] Using the preset corrosion dynamics model, a random field model of corrosion depth of the overall corrosion of the steel structure to be evaluated is established;

[0066] Substituting the corrosion evaluation index into the random field model of the corrosion depth of the steel structure to be evaluated, calculating the coordinate data of the overall corrosion point cloud of the corroded surface of the steel structure to be evaluated, that is, obtaining the overall corrosion morphology mapping reconstruction result;

[0067] The process of calculating the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated is as follows:

[0068] Determining a power spectrum of the corrosion depth on the surface of the steel structure to be evaluated according to the average value of the corrosion depth on the surface of the steel structure to be evaluated and the standard deviation of the corrosion depth;

[0069] According to the power spectrum of the corrosion depth on the surface of the steel structure to be evaluated, using a two-dimensional random harmonic function, the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated is calculated, that is, the overall corrosion morphology mapping reconstruction result is obtained;

[0070] The construction process of the pitting morphology mapping reconstruction result is as follows:

[0071] Using the preset corrosion kinetics model, a random distribution model of rust pits for pitting corrosion of the steel structure to be evaluated is established;

[0072] Substituting the corrosion evaluation index into the random distribution model of rust pits of the steel structure to be evaluated, and calculating the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated, that is, obtaining the pitting morphology mapping reconstruction result;

[0073] The process of calculating the pitting point cloud coordinate data of the corroded surface of the steel structure to be evaluated is as follows:

[0074] Determine the number of rust pits according to the density of rust pits on the surface of the steel structure to be evaluated and the pre-calculated surface area of ​​the steel structure to be evaluated; wherein the pre-calculated surface area of ​​the steel structure to be evaluated is calculated by multiplying the surface length dimension and the width dimension of the steel structure to be evaluated;

[0075] Generating random rust pits in batches according to the rust pit depth, rust pit diameter-to-depth ratio, rust pit shape probability parameter and the number of rust pits on the surface of the steel structure to be evaluated;

[0076] According to the batch generation of random rust pits, the pitting point cloud coordinate data of the corroded surface of the steel structure to be evaluated is calculated, that is, the pitting morphology mapping reconstruction result is obtained.

[0077] Step 4: According to the reconstruction result of the corroded surface morphology mapping of the steel structure to be evaluated, a random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated is established; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column nodes and steel plate components of the steel structure to be evaluated.

[0078] The process of constructing the finite element geometric model of the random corrosion surface of the basic component of the steel structure to be evaluated specifically includes the following steps:

[0079] The rusted surface morphology mapping reconstruction result of the steel structure to be evaluated is subjected to coordinate transformation to obtain random rusted surface point cloud data of the basic components of the steel structure to be evaluated; wherein the random rusted surface point cloud data of the basic components of the steel structure to be evaluated is closed section point cloud data;

[0080] A finite element geometric model of a basic component of the steel structure to be evaluated is constructed, and the random corroded surface point cloud data of the basic component of the steel structure to be evaluated is assigned to the finite element geometric model of the basic component of the steel structure to be evaluated, so as to obtain a random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated.

[0081] Step 5: Using a finite element parametric simulation method, perform finite element simulation calculation on the random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated, and obtain the bearing performance prediction results of the basic components of the steel structure to be evaluated; specifically, for the random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated, set material properties, apply loads and boundary conditions, and perform finite element numerical simulation to obtain the bearing performance prediction results of the basic components of the steel structure to be evaluated.

[0082] Step 6: According to the load-bearing performance prediction results of the basic components of the steel structure to be evaluated and the reliability evaluation theory, the load-bearing performance of the steel structure to be evaluated is evaluated to obtain the load-bearing performance evaluation result of the corroded steel structure.

[0083] The present invention also provides a bearing performance evaluation system for a corroded steel structure, comprising a scanning module, an index module, a mapping and reconstruction module, a geometric model module, a numerical simulation module and an evaluation module; the scanning module is used to perform surface feature scanning on a pre-selected local corroded area on the steel structure to be evaluated, so as to obtain a three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; the index module is used to determine a corrosion evaluation index according to the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; the mapping and reconstruction module is used to establish a random characterization model of the corroded surface of the steel structure to be evaluated by using a preset corrosion dynamics model; according to the random characterization model of the corroded surface of the steel structure to be evaluated and the corrosion evaluation index, the corroded surface morphology of the steel structure to be evaluated is mapped and reconstructed to obtain a mapping of the corroded surface morphology of the steel structure to be evaluated a geometric model module, used to establish a random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated according to the morphology mapping and reconstruction results of the corroded surface of the steel structure to be evaluated; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column nodes and steel plate components of the steel structure to be evaluated; a numerical simulation module, used to perform finite element simulation calculations on the random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated using a finite element parametric simulation method, and obtain the bearing performance prediction results of the basic components of the steel structure to be evaluated; an evaluation module, used to evaluate the bearing performance of the steel structure to be evaluated according to the bearing performance prediction results of the basic components of the steel structure to be evaluated and the reliability evaluation theory, and obtain the bearing performance evaluation results of the corroded steel structure.

[0084] The method and system for evaluating the bearing capacity of a corroded steel structure described in the present invention scan the surface corrosion features of a representative local area of ​​the steel structure to be evaluated, thereby achieving non-destructive acquisition of corrosion morphology data and avoiding damage to the original structure. The corrosion evaluation index system established based on the surface morphology can evaluate both the uniform corrosion degree and the non-uniform corrosion degree, thereby solving the problem that the original index cannot reflect the influence of non-uniform corrosion. Based on the statistical analysis of the morphology data and the evaluation index, a corrosion surface characterization model is established for different corrosion environments and meets certain statistical characteristics. Based on the finite morphology data, batch mapping and reconstruction of large-scale surface morphologies of basic components such as corroded steel structure beams and columns can be achieved, thereby providing data support for subsequent structural performance prediction and reliability evaluation. Finite element analysis software is used to perform numerical calculations on the bearing capacity of components such as corroded beams and columns that are batch mapped and reconstructed. This method introduces the batch reconstructed surface morphology into the finite element model, thereby considering the uncertainty of the corrosion features, and the calculation results have higher accuracy, thereby achieving predictions and reliability evaluations of the bearing capacity of corroded steel structures and solving the problem that actual engineering and mechanical performance tests cannot be repeated.

[0085] The present invention also provides a device for evaluating the bearing performance of a corroded steel structure, comprising: a memory for storing a computer program; and a processor for implementing the steps of a method for evaluating the bearing performance of a corroded steel structure when executing the computer program.

[0086] When the processor executes the computer program, the steps of the above-mentioned method for evaluating the bearing performance of corroded steel structures are implemented, for example: performing surface feature scanning on a pre-selected local corroded area on the steel structure to be evaluated to obtain a three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; determining a corrosion evaluation index based on the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; using a preset corrosion kinetics model to establish a random characterization model of the corroded surface of the steel structure to be evaluated; mapping and reconstructing the corroded surface morphology of the steel structure to be evaluated based on the random characterization model of the corroded surface of the steel structure to be evaluated and the corrosion evaluation index to obtain a mapping and reconstruction result of the corroded surface morphology of the steel structure to be evaluated; and The morphology mapping reconstruction result of the corroded surface of the steel structure to be evaluated is used to establish a random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column nodes and steel plate components of the steel structure to be evaluated; using a finite element parametric simulation method, a finite element simulation calculation is performed on the random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated, and a bearing performance prediction result of the basic components of the steel structure to be evaluated is obtained; according to the bearing performance prediction result of the basic components of the steel structure to be evaluated and the reliability evaluation theory, the bearing performance of the steel structure to be evaluated is evaluated, and a bearing performance evaluation result of the corroded steel structure is obtained.

[0087] Alternatively, when the processor executes the computer program, the functions of each module in the above system are realized, for example: a scanning module is used to perform surface feature scanning on a pre-selected local corroded area on the steel structure to be evaluated, so as to obtain a three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; an index module is used to determine a corrosion evaluation index according to the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; a mapping and reconstruction module is used to establish a random characterization model of the corroded surface of the steel structure to be evaluated using a preset corrosion dynamics model; according to the random characterization model of the corroded surface of the steel structure to be evaluated and the corrosion evaluation index, the morphology of the corroded surface of the steel structure to be evaluated is mapped and reconstructed to obtain a mapping and reconstruction result of the morphology of the corroded surface of the steel structure to be evaluated; a geometric model module is used to perform surface feature scanning on the pre-selected local corroded area of ​​the steel structure to be evaluated, so as ... three-dimensional morphology of the corroded surface of the steel structure to be evaluated; a mapping and reconstruction module is used to perform surface feature scanning on the pre-selected local corroded area of ​​the steel structure to be evaluated, so as to obtain a three-dimensional morphology of the corroded surface of the steel structure to be evaluated; a mapping and reconstruction module is used to perform surface feature scanning on the pre-selected local corroded area of ​​the steel structure to be evaluated, so as to obtain a three-dimensional morphology of the corroded surface of the steel structure to be evaluated; a mapping and reconstruction module is used to perform surface feature scanning on the pre-selected local corroded area of ​​the steel structure to be evaluated, so as to obtain a three-dimensional morphology of the corroded surface of the steel structure to Used to establish a random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated according to the reconstruction results of the corroded surface morphology mapping of the steel structure to be evaluated; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column nodes and steel plate components of the steel structure to be evaluated; a numerical simulation module, used to use a finite element parametric simulation method to perform finite element simulation calculations on the random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated, and obtain the bearing performance prediction results of the basic components of the steel structure to be evaluated; an evaluation module, used to evaluate the bearing performance of the steel structure to be evaluated according to the bearing performance prediction results of the basic components of the steel structure to be evaluated and the reliability evaluation theory, and obtain the bearing performance evaluation results of the corroded steel structure.

[0088] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of completing preset functions, and the instruction segments are used to describe the execution process of the computer program in the corroded steel structure bearing performance evaluation device.

[0089] The bearing performance evaluation device of the corroded steel structure can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The bearing performance evaluation device of the corroded steel structure can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above is an example of a bearing performance evaluation device for a corroded steel structure, and does not constitute a limitation on the bearing performance evaluation device for a corroded steel structure. It can include more components than the above, or a combination of certain components, or different components. For example, the bearing performance evaluation device of the corroded steel structure can also include input and output devices, network access devices, buses, etc.

[0090] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The processor is the control center of the rusted steel structure bearing performance evaluation device, and uses various interfaces and lines to connect various parts of the entire rusted steel structure bearing performance evaluation device.

[0091] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the corroded steel structure bearing performance evaluation device by running or executing the computer program and / or module stored in the memory and calling the data stored in the memory.

[0092] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0093] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for evaluating the bearing performance of a corroded steel structure are implemented.

[0094] If the modules / units integrated in the corroded steel structure bearing performance evaluation system are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0095] Based on such understanding, the present invention implements all or part of the processes in the above-mentioned method for evaluating the bearing performance of corroded steel structures, and can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above-mentioned method for evaluating the bearing performance of corroded steel structures can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or preset intermediate form, etc.

[0096] The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0097] It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electrical carrier signals and telecommunication signals.

[0098] Example

[0099] As attached Figure 1 As shown, this embodiment provides a method for evaluating the bearing performance of a corroded steel structure, including: performing surface feature scanning on a randomly selected local area of ​​the steel structure to be evaluated to obtain a three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; determining a corrosion evaluation index based on the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; using a preset corrosion dynamics model to establish a random characterization model of the corroded surface of the steel structure to be evaluated; mapping and reconstructing the corroded surface morphology of the steel structure to be evaluated based on the random characterization model of the corroded surface of the steel structure to be evaluated and the corrosion evaluation index to obtain a mapping and reconstruction result of the corroded surface morphology of the steel structure to be evaluated; and determining a corrosion evaluation index based on the three-dimensional morphology of the corroded surface of the steel structure to be evaluated. The rust surface morphology mapping reconstruction result is used to establish a random rust surface finite element geometric model of the basic components of the steel structure to be evaluated; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column nodes and steel plate components of the steel structure to be evaluated; using the finite element parametric simulation method, the random rust surface finite element geometric model of the basic components of the steel structure to be evaluated is simulated and calculated to obtain the bearing performance prediction results of the basic components of the steel structure to be evaluated; according to the bearing performance prediction results of the basic components of the steel structure to be evaluated and the reliability evaluation theory, the bearing performance of the steel structure to be evaluated is evaluated to obtain the bearing performance evaluation results of the corroded steel structure.

[0100] The method for evaluating the bearing capacity of a corroded steel structure described in this embodiment specifically comprises the following steps:

[0101] Step 1: Scan the surface features of the pre-selected local area on the steel structure to be evaluated to obtain the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated, as shown in the attached figure. Figure 2 As shown; wherein, the surface feature scanning process is as follows:

[0102] Conduct visual inspection on the corrosion status of the basic components of the steel structure to be evaluated, and classify the corrosion grade and corrosion range of the basic components of the steel structure to be evaluated; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column joints and steel plate components of the steel structure to be evaluated;

[0103] Among the basic components of the steel structure to be evaluated with different corrosion levels, local corrosion areas are randomly selected as representative corrosion areas of the steel structure to be evaluated;

[0104] Performing mechanical rust removal on the local rusted area to obtain a local rusted area after rust removal;

[0105] A three-dimensional non-contact laser scanner is used to perform surface feature scanning on the local rusted area after the rust removal treatment to obtain a three-dimensional morphology of the rusted surface of the local area of ​​the steel structure to be evaluated; wherein the three-dimensional morphology of the rusted surface of the local area of ​​the steel structure to be evaluated can represent the overall corrosion condition of the steel structure to be evaluated, and the three-dimensional morphology of the rusted surface of the local area of ​​the steel structure to be evaluated is the three-dimensional point cloud coordinate data of the rusted surface of the local area of ​​the steel structure to be evaluated.

[0106] In this embodiment, when the local rusted area is subjected to mechanical rust removal treatment, the local rusted area is grinded with copper wire; since the hardness of copper wire is less than that of iron, the grinding treatment can avoid damaging the surface morphology of the rusted area; the local rusted area after the rust removal treatment is wrapped with plastic wrap to isolate the air, and other anti-corrosion measures are taken for anti-corrosion treatment when necessary to ensure the accuracy of the surface feature scanning results; after the rust removal treatment, since the original surface of the rusted steel material cannot be retained, the highest point of the surface after the rust removal treatment can be used as the reference surface for the rust depth; in order to accurately predict the bearing capacity of the corroded steel structure, the position and number of the measurement areas should be able to represent the degree of corrosion of the entire structure.

[0107] Step 2: Determine the corrosion evaluation index according to the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated, as shown in the attached figure. Figure 3As shown; wherein, the corrosion evaluation indexes include two categories; one category is the macroscopic mechanical property evaluation index, which is used to evaluate the mechanical properties of the basic components of the steel structure to be evaluated; the other category is the microscopic corrosion morphology characterization, which is used to characterize the corrosion morphology of the basic components of the steel structure to be evaluated.

[0108] The mechanical property evaluation indexes include corrosion rate, non-uniform corrosion rate and minimum corrosion cross-sectional area.

[0109] The corrosion morphology characterization includes overall corrosion morphology characterization and pitting morphology characterization; the overall corrosion morphology characterization includes the average corrosion depth and the standard deviation of the corrosion depth; the pitting morphology characterization includes the rust pit depth, the rust pit diameter-to-depth ratio, the rust pit volume ratio and the rust pit density.

[0110] In this embodiment, before obtaining the corrosion morphology representation, the scanning data of the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated needs to be filtered to eliminate the image of sudden change noise.

[0111] The calculation process of each indicator parameter in the corrosion evaluation index is as follows:

[0112] 1) Non-uniform corrosion rate:

[0113]

[0114] Among them, ρ n is the non-uniform corrosion rate; (m-1)(n-1) is the number of all small cylinders contained between the upper and lower surfaces; Δz1(i) is the average height of the i-th small cylinder; s x is the spacing of the scanning points in the x direction; s y is the spacing of scanning points in the y direction; V0 is the initial volume of the scanning area.

[0115] 2) Corrosion rate:

[0116] ρ=1+ρ n -T max / T0 (2)

[0117] Where ρ is the corrosion rate; T0 is the initial thickness of the plate in the scanning area; T max It is the maximum residual thickness of the plate in the scanned area after rusting.

[0118] 3) Minimum cross-sectional area of ​​corrosion:

[0119]

[0120] Among them, A ma is the minimum cross-sectional area; m is the number of scanning points in the x direction; y=y jThe average height of the i-th small quadrilateral on the cross section.

[0121] 4) Average corrosion depth:

[0122]

[0123] Among them, t a is the average corrosion depth; m is the number of scanning points in the x direction; n is the number of scanning points in the y direction; z(x i ,y j ) is the corrosion depth of the scanning point.

[0124] 5) Standard deviation of corrosion depth:

[0125]

[0126] Among them, t s is the standard deviation of corrosion depth.

[0127] 6) Rust pit density:

[0128] d p =N p / A0 (6)

[0129] Among them, d p is the rust pit density; N p is the number of rust pits in the scanning area; A0 is the area of ​​the scanning area.

[0130] 7) Rust pit diameter to depth ratio:

[0131] AR=R / h (7)

[0132] Among them, AR is the rust pit diameter-to-depth ratio; h is the rust pit depth; R is the rust pit diameter.

[0133] 8) Rust pit volume ratio:

[0134]

[0135] Wherein, VB is the volume ratio of rust pit; V p is the volume of the rust pit; V rec is the minimum cuboid volume surrounding the rust pit; n v is the number of small columns in the rust pit; Δz1(i) is the average height of the small columns; R x is the diameter of the rust pit in the x direction, R y is the diameter of the rust pit in the y direction; when VB = π / 12, the rust pit is close to a cone; when VB = π / 6, the rust pit is close to a hemisphere; when VB = π / 4, the rust pit is close to a cylinder; when VB = 1, the rust pit is close to a cuboid.

[0136] Step 3, using a preset corrosion dynamics model, establish a random characterization model of the rusted surface of the steel structure to be evaluated; wherein the random characterization model of the rusted surface of the steel structure to be evaluated includes a random field model of the rust depth of the overall corrosion of the steel structure to be evaluated and a random distribution model of rust pits of the pitting corrosion of the steel structure to be evaluated; according to the random characterization model of the rusted surface of the steel structure to be evaluated and the corrosion evaluation index, the rusted surface morphology of the steel structure to be evaluated is mapped and reconstructed to obtain a rusted surface morphology mapping reconstruction result of the steel structure to be evaluated; wherein the rusted surface morphology mapping reconstruction result of the steel structure to be evaluated includes a comprehensive corrosion morphology mapping reconstruction result and a pitting morphology mapping reconstruction result.

[0137] In this embodiment, the random field model of corrosion depth of the overall corrosion of the steel structure to be evaluated is suitable for random characterization of the overall corrosion surface; the construction process of the overall corrosion morphology mapping reconstruction result is: using a preset corrosion dynamics model to establish a random field model of corrosion depth of the overall corrosion of the steel structure to be evaluated; substituting the corrosion evaluation index into the random field model of corrosion depth of the overall corrosion of the steel structure to be evaluated, and calculating the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated, that is, obtaining the overall corrosion morphology mapping reconstruction result; wherein, the process of calculating the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated is as follows: determining the power spectrum of the corrosion depth of the steel structure to be evaluated according to the average value of the corrosion depth of the steel structure to be evaluated and the standard deviation of the corrosion depth; according to the power spectrum of the corrosion depth of the steel structure to be evaluated, using a two-dimensional random harmonic function, calculating the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated, that is, obtaining the overall corrosion morphology mapping reconstruction result.

[0138] The specific process is as follows:

[0139] 1) Perform two-dimensional discrete fast Fourier transform (FFT) on the scanned data of the local area of ​​the steel structure to be evaluated:

[0140]

[0141] ω 1p =2πp / ms x

[0142] ω 2q =2πq / ns y

[0143] Among them, ω 1p is the wave number of the pth harmonic component in the x and y directions; ω 2q is the qth harmonic component wave number in the x and y directions.

[0144] 2) Calculate the bilateral spectral density of the discrete two-dimensional random field of the scanned data points:

[0145]

[0146] 3) Fit the power spectrum density calculation results:

[0147]

[0148] Among them, k1 and k2 are fitting parameters related to the corrosion state. Under normal atmospheric conditions, it is recommended that k1 and k2 be calculated using the following formula:

[0149] k1=0.05t a 0.62 (12)

[0150]

[0151] 4) Substitute the two-dimensional bilateral power spectral density into the trigonometric function to obtain the comprehensive corrosion random field model:

[0152]

[0153] Where P is the number of harmonic components in the x direction; Q is the number of harmonic components in the y direction; θ 1pq ,θ 2pq is a random phase angle uniformly distributed between [0,2π]; ω 1p ,ω 2q is the pth and qth harmonic component wave number in the x and y directions, ω 1p =pΔω1=pω 1u / P,ω 2p =qΔω2=qω 2u / Q;ω 1u ,ω 2u is the upper cutoff wave number of the random field in the x and y directions, calculated by the following formula:

[0154]

[0155] Among them, ∈<<1; preferably, ∈ is 0.0001.

[0156] 5) Known upper cutoff wave number ω 1u ,ω 2u And the size of the generated surface, the number of harmonic components P, Q is determined by the following formula:

[0157]

[0158]

[0159] Among them, L x , L y To generate the dimensions of the large surface in the x and y directions.

[0160] 6) To avoid spectrum aliasing, the spacing between generated points in the x and y directions must meet the following conditions:

[0161]

[0162] M≥2P,N≥2Q (19)

[0163] Among them, M and N are the number of points in the x and y directions of the generated large-size surface, S x , S y The spacing of points in the x and y directions to generate a large-scale surface.

[0164] 7) The generated surface size L is determined x and surface size L y After that, the fully corroded surface is generated according to the following process:

[0165] S1, the standard deviation of corrosion depth t s , power spectrum density parameter k1 and power spectrum density parameter k2 are substituted into the above formula (11) to determine the power spectrum density G of the overall corrosion surface;

[0166] S2. Substitute the power spectrum density G of the overall corrosion surface into the above formula (15) to determine the upper cutoff wave number ω 1u and the upper cutoff wave number ω 2u ;

[0167] S3, the surface size L x , Surface size L y , upper cutoff wave number ω 1u and the upper cutoff wave number ω 2u Substituting into equations (16) to (17), we can determine the number of harmonic components P and Q; the spacing S of the generated points x , the spacing between points S y , the number of points M and the number of points N;

[0168] S4. Substituting the above parameters into equation 14, a large-scale fully corroded surface can be randomly generated.

[0169] S5. Repeat the above process to generate large-sized fully corroded surfaces in batches.

[0170] In this embodiment, the construction process of the pitting morphology mapping reconstruction result is as follows:

[0171] A rust pit random distribution model of pitting of the steel structure to be evaluated is established by using a preset corrosion dynamics model; the corrosion evaluation index is substituted into the rust pit random distribution model of pitting of the steel structure to be evaluated, and the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated is calculated, that is, the pitting morphology mapping reconstruction result is obtained; wherein, the process of calculating the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated is specifically as follows: the number of rust pits is determined according to the rust pit density on the surface of the steel structure to be evaluated and the pre-calculated surface area of ​​the steel structure to be evaluated; wherein, the pre-calculated surface area of ​​the steel structure to be evaluated is calculated by multiplying the surface length dimension and the width dimension of the steel structure to be evaluated; random rust pits are generated in batches according to the rust pit depth, the rust pit diameter-to-depth ratio, the rust pit shape probability parameter and the number of rust pits on the surface of the steel structure to be evaluated; according to the batch generated random rust pits, the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated is calculated, that is, the pitting morphology mapping reconstruction result is obtained.

[0172] The specific steps include:

[0173] 1) The scanning morphological data of the three-dimensional morphology of the local area of ​​the corroded surface of the steel structure to be evaluated are processed, and the binary slice images are gradually created from top to bottom along the z-axis using the MATLAB platform. The Floodfill algorithm is used to determine the position of the isolated area, i.e., the rust pit, and mark and number it. The corresponding number is input, and the corresponding evaluation index of the rust pit is calculated and extracted. By reducing the slice height, the position calibration of all rust pits on the corrosion surface and the extraction of rust pit characteristic indicators are finally achieved.

[0174] 2) Count the number of rust pits in the scanned area and calculate the rust pit density d according to formula (6) p ; Use the KS test method to perform hypothesis testing on the extraction results of rust pit depth h and rust pit diameter-to-depth ratio AR, determine the probability distribution form of rust pit depth and diameter-to-depth ratio, and calculate the mean value μ of rust pit depth h 、The average value of the rust pit diameter-depth ratio μ AR , standard deviation of rust pit depth σ h And the standard deviation of the rust pit diameter-depth ratio σ AR .

[0175] 3) The shape of the rust pit is determined by the volume ratio VB. When the volume ratio VB = 0-0.4, the rust pit is a cone; when VB = 0.4-0.7, the rust pit is a hemisphere; when VB = 0.7-1, the rust pit is a cylinder;

[0176] The probability coefficients of the above three rust pit shapes are:

[0177]

[0178] Among them, λ1, λ2, λ3 are the proportions of cone, hemisphere, and cylinder rust pits, respectively; NP1, NP2, NP3 are the numbers of cone, hemisphere, and cylinder rust pits, respectively; NP is the number of all rust pits. The rust pit numbers extracted from the scanned morphology of the local area of ​​the steel structure to be evaluated are arranged in ascending order according to the depth of the rust pits, and the number of rust pits in different rust pit depth ranges is counted to obtain the probability coefficients of rust pits of different shapes.

[0179] 5) Obtain the surface length dimension L of the steel structure to be evaluated x and width size L y , and then the pre-calculated surface area of ​​the steel structure to be evaluated is generated according to the following process; the specific generation process is as follows:

[0180] S1, according to the rust pit density (d p ) and the resulting surface size (L x and L y ), the number of rust pits NP is determined by formula (6);

[0181] S2, according to the mean value μ of the rust pit depth h 、The average value of the rust pit diameter-depth ratio μ AR , standard deviation of rust pit depth σ h And the standard deviation of the rust pit diameter-depth ratio σ AR , randomly generate NP rust pit depth and diameter-to-depth ratio data according to formula (21);

[0182]

[0183] Among them, nrnd is the probability distribution function of rust pit depth and diameter-to-depth ratio.

[0184] S3. Arrange the generated NP rust pit depth data in ascending order, and determine the number NP1, NP2, NP3 of cone, hemisphere, and cylinder rust pits according to the rust pit shape probability coefficients λ1, λ2, λ3 and the total number NP of rust pits, and then determine the rust pit depths h1, h2, h3 and diameter-to-depth ratios AR1, AR2, AR3 of the cone, hemisphere, and cylinder rust pits.

[0185] S4. After generating the geometric features of NP rust pits, the position of the rust pits needs to be further determined. The position coordinates (x0, y0) can be within the range (L x ,L y ) is randomly generated:

[0186]

[0187] S5. According to the depth, diameter-to-depth ratio and position of rust pits of different shapes, write the surface equation of a single rust pit:

[0188]

[0189] The pitting surface with NP rust pits can be expressed as the intersection of NP single rust pit surfaces:

[0190]

[0191] S6. Repeat the above process to batch generate large-sized pitting surfaces.

[0192] Step 4: According to the reconstruction result of the corroded surface morphology mapping of the steel structure to be evaluated, a random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated is established; wherein the basic components of the steel structure to be evaluated include beam components and column components of the steel structure to be evaluated.

[0193] The specific process is as follows:

[0194] The rusted surface morphology mapping reconstruction result of the steel structure to be evaluated is subjected to coordinate transformation to obtain random rusted surface point cloud data of the basic components of the steel structure to be evaluated; wherein the random rusted surface point cloud data of the basic components of the steel structure to be evaluated is closed section point cloud data;

[0195] A finite element geometric model of a basic component of the steel structure to be evaluated is constructed, and the random corroded surface point cloud data of the basic component of the steel structure to be evaluated is assigned to the finite element geometric model of the basic component of the steel structure to be evaluated, so as to obtain a random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated.

[0196] In this embodiment, the surface morphology after mapping and reconstruction is three-dimensional plane point cloud coordinate data, which is actually the unfolded surface of the basic components such as beams and columns of the steel structure to be evaluated. The generated point cloud data must be transformed into coordinates before the basic components such as beams and columns with closed cross-sections can be formed; as shown in the attached figure, Figure 4 As shown, attached Figure 4 A schematic diagram of the point cloud coordinate transformation of the H-beam in the embodiment is given in FIG. Figure 4 (a) is a schematic diagram of randomly generated surface point cloud arrangement. Figure 4 (b) is a schematic diagram of the point cloud arrangement of the H-beam cross section after coordinate transformation; Figure 4 The surface AA in (b) is composed of the attached Figure 4 Surface A in (a) is obtained through coordinate transformation, and the same is true for the other surfaces; Figure 4 (c) is a randomly generated surface point cloud of the H-beam cross section. Figure 4 (d) is the point cloud diagram of the H-beam after coordinate transformation. Figure 4 (a) To the attached Figure 4 (b) shows the coordinate transformation method, according to the attached Figure 4 (c) The surface point cloud of the H-beam cross section is developed, and the following Figure 4(d) is the point cloud image of the H-shaped steel beam after coordinate transformation.

[0197] The following example illustrates the coordinate transformation process. Assume that the randomly generated overall surface is the unfolded surface of surface 1 and surface 2, and surface 1 and surface 2 are on the same plane. In order to make surface 1 and surface 2 skew surfaces in space, it is only necessary to perform coordinate transformation on one of the surfaces at a certain angle. The coordinate transformation steps are as follows:

[0198] 1) Assume that there is an arbitrary point P on the surface. Its three-dimensional coordinates in space before and after coordinate transformation are P1(x1, y1, z1) and P2(x2, y2, z2).

[0199] 2) Through rotation and translation, point coordinates P1 can be converted to point coordinates P2. The conversion formula is as follows:

[0200]

[0201] 3) Use the 3×3 rotation matrix R and the three-dimensional translation vector T for transformation. The transformation formula is as follows:

[0202]

[0203] Among them, x0, y0 and z0 are three translation parameters, a 11 、a 12 、a 13 、a 21 、a 22 、a 23 、a 31 、a 32 and a 33 They are the nine direction cosines respectively.

[0204] The point cloud data after coordinate transformation are assigned to the model nodes in sequence, so as to establish the finite element geometric model of basic components such as corroded beams and columns. The details are as follows: according to the needs of the finite element geometric model for grid node division, when the point cloud spacing is equal to the required unit grid size, it can be directly assigned in sequence; when the point cloud spacing is smaller than the required unit grid size, the point cloud can be assigned to the unit node at intervals; when the cloud point spacing is larger than the required unit grid size, linear interpolation can be performed first and then assigned in sequence; as shown in the attached figure, Figure 5 As shown, attached Figure 5 A schematic diagram of the finite element geometric model of the randomly generated pitting C-shaped steel column in the embodiment is given in FIG. Figure 5 (a) is a schematic diagram of the overall finite element geometric model of the randomly generated pitting C-shaped steel column. Figure 5 (b) is a partial enlarged schematic diagram of the finite element geometric model of the randomly generated pitting C-shaped steel column. Figure 5 (c) Schematic diagram of rust pit distribution in the finite element geometric model of randomly generated pitted C-shaped steel column.

[0205] Step 5: Using a finite element parametric simulation method, perform finite element simulation calculation on the random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated, and obtain the bearing performance prediction results of the basic components of the steel structure to be evaluated; specifically, for the random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated, set material properties, apply loads and boundary conditions, and perform finite element numerical simulation to obtain the bearing performance prediction results of the basic components of the steel structure to be evaluated.

[0206] In this embodiment, the finite element numerical simulation method is used to assign material properties, loads and boundary conditions to the finite element geometric model of the large number of corroded beams and column components generated, and the finite element numerical simulation is performed to obtain the prediction results of the bearing performance of the large number of corroded beams and column components of the steel structure to be evaluated. Figure 6 and attached Figure 7 As shown, the load-displacement curves of the finite element model of the randomly generated surface corroded steel beams and corroded steel columns are almost the same as the test values, indicating that the method for evaluating the bearing performance of corroded steel structures proposed in this embodiment has high accuracy.

[0207] Step 6: According to the bearing performance prediction results of the basic components of the steel structure to be evaluated and the reliability evaluation theory, the bearing performance of the steel structure to be evaluated is evaluated to obtain the bearing performance evaluation results of the corroded steel structure; specifically, a statistical analysis is performed on the bearing performance prediction results of a large number of corroded beams and columns, and according to the reliability evaluation theory, the reliability index and failure probability of the structure are calculated by formula (27) to evaluate the bearing performance of the corroded steel structure to be evaluated.

[0208]

[0209] Among them, β is the reliable index of the corroded steel structure to be evaluated, μ R and σ R are the mean and standard deviation of the bearing capacity of the basic components of the corroded steel structure to be evaluated, μ S and σ S are the mean and standard deviation of the structural effect, respectively.

[0210] The method for evaluating the bearing capacity of a corroded steel structure described in this embodiment comprises the following steps: performing precise morphological scanning of the local surface of the corroded steel structure by a non-contact high-resolution three-dimensional surface profiler; establishing a corrosion evaluation index system using a large amount of representative local corrosion morphological scanning data; extracting indicators and quantitatively evaluating corrosion surface characteristics with the aid of the corrosion evaluation index system; establishing a random characterization function of the corrosion surface by using a corrosion kinetics model and a random function, which can perform mass mapping and reconstruction of the surface morphology of the corroded steel; and evaluating the service performance and reliability of the corroded steel structure by mass random generation and finite element simulation. The present invention scans the surface corrosion features of a local small area representative of the steel structure to be evaluated, thereby realizing non-destructive acquisition of corrosion morphology data and avoiding damage to the original structure. The corrosion evaluation index system established based on the surface morphology can evaluate both the uniform corrosion degree and the non-uniform corrosion degree, thereby solving the problem that the original index cannot reflect the influence of non-uniform corrosion. Based on the statistical analysis of the morphology data and the evaluation index, a random model of the corrosion surface that meets certain statistical characteristics for different corrosion environments is established, and based on the finite morphology data, batch mapping and reconstruction of the large-scale surface morphology of the basic components of the beams and columns of the corroded steel structure can be realized, thereby providing data support for subsequent structural performance prediction and reliability evaluation. The finite element analysis software is used to perform numerical calculation of the bearing performance of the batch-mapped and reconstructed corroded beam and column components. The method introduces the batch-reconstructed surface morphology into the finite element model, thereby considering the uncertainty of the corrosion features, and the calculation result has higher accuracy, thereby realizing the prediction of the bearing performance and reliability evaluation of the corroded steel structure, thereby solving the problem that the actual engineering and mechanical performance tests cannot be repeated. The present invention can further enrich the performance evaluation methods in the field of engineering structure durability, and provide a technical basis for engineering and technical personnel engaged in the detection, evaluation and reinforcement of existing engineering structures.

[0211] The description of the relevant parts of the system, device and computer-readable storage medium for evaluating the bearing performance of a corroded steel structure provided in this embodiment can be found in the detailed description of the corresponding parts of the method for evaluating the bearing performance of a corroded steel structure described in this embodiment, and will not be repeated here.

[0212] The above embodiment is only one of the implementation methods that can realize the technical solution of the present invention. The scope of protection claimed by the present invention is not limited only to this embodiment, but also includes changes, replacements and other implementation methods that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention.

Claims

1. A method for evaluating the bearing performance of a corroded steel structure, characterized in that: The following steps are involved: Step 1: Scan the surface features of the pre-selected local corroded area on the steel structure to be evaluated to obtain the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; Step 2: determining the corrosion evaluation index according to the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; Step 3: using a preset corrosion kinetics model, establish a random characterization model of the corroded surface of the steel structure to be evaluated; mapping and reconstructing the corroded surface morphology of the steel structure to be evaluated according to the random characterization model of the corroded surface of the steel structure to be evaluated and the corrosion evaluation index, and obtaining a mapping and reconstruction result of the corroded surface morphology of the steel structure to be evaluated; Step 4: According to the reconstruction result of the corroded surface morphology mapping of the steel structure to be evaluated, a random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated is established; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column nodes and steel plate components of the steel structure to be evaluated; Step 5: Using a finite element parametric simulation method, a finite element simulation calculation is performed on a random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated, so as to obtain a prediction result of the bearing performance of the basic component of the steel structure to be evaluated; Step 6: According to the load-bearing performance prediction results of the basic components of the steel structure to be evaluated and the reliability evaluation theory, the load-bearing performance of the steel structure to be evaluated is evaluated to obtain the load-bearing performance evaluation result of the corroded steel structure; The morphology mapping and reconstruction results of the corroded surface of the steel structure to be evaluated include the overall corrosion morphology mapping and reconstruction results and the pitting corrosion morphology mapping and reconstruction results; The construction process of the comprehensive corrosion morphology mapping reconstruction result is as follows: Using the preset corrosion dynamics model, a random field model of corrosion depth of the overall corrosion of the steel structure to be evaluated is established; Substitute the corrosion evaluation index into the random field model of the corrosion depth of the steel structure to be evaluated, and calculate the coordinate data of the overall corrosion point cloud of the corroded surface of the steel structure to be evaluated, that is, obtain the reconstruction result of the overall corrosion morphology mapping; The process of calculating the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated is as follows: Determine the power spectrum of the corrosion depth on the surface of the steel structure to be evaluated according to the average value of the corrosion depth on the surface of the steel structure to be evaluated and the standard deviation of the corrosion depth; According to the power spectrum of the corrosion depth on the surface of the steel structure to be evaluated, the two-dimensional random harmonic function is used to calculate the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated, that is, the overall corrosion morphology mapping reconstruction result is obtained; The construction process of the pitting morphology mapping reconstruction results is as follows: Using the preset corrosion kinetics model, a random distribution model of rust pits for pitting corrosion of the steel structure to be evaluated is established; Substituting the corrosion evaluation index into the random distribution model of the pitting of the steel structure to be evaluated, the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated is calculated, that is, the pitting morphology mapping reconstruction result is obtained; The process of calculating the pitting point cloud coordinate data of the corroded surface of the steel structure to be evaluated is as follows: Determine the number of rust pits according to the density of rust pits on the surface of the steel structure to be evaluated and the pre-calculated surface area of ​​the steel structure to be evaluated; wherein the pre-calculated surface area of ​​the steel structure to be evaluated is calculated by multiplying the surface length dimension and the width dimension of the steel structure to be evaluated; Generate random rust pits in batches according to the rust pit depth, rust pit diameter-to-depth ratio, rust pit shape probability parameters and the number of rust pits on the surface of the steel structure to be evaluated; Based on the batch generation of random rust pits, the pitting point cloud coordinate data of the corroded surface of the steel structure to be evaluated is calculated, that is, the pitting morphology mapping reconstruction result is obtained.

2. A method for evaluating the bearing capacity of a corroded steel structure according to claim 1, characterized in that: In step 1, the surface feature scanning is performed on the pre-selected local area of ​​the steel structure to be evaluated to obtain the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated, which is specifically as follows: Randomly select a local rusted area on the steel structure to be evaluated, and perform rust removal treatment to obtain the local rusted area after rust removal treatment; A three-dimensional non-contact laser scanner is used to scan the surface features of the local rusted area after the rust removal treatment to obtain a three-dimensional morphology of the rusted surface of the local area of ​​the steel structure to be evaluated; wherein the three-dimensional morphology of the rusted surface of the local area of ​​the steel structure to be evaluated is the three-dimensional point cloud coordinate data of the rusted surface of the local area of ​​the steel structure to be evaluated.

3. A method for evaluating the bearing performance of a corroded steel structure according to claim 1, characterized in that: In step 2, the corrosion evaluation index includes a mechanical property evaluation index and a corrosion morphology characterization; Among them, the mechanical property evaluation indicators include corrosion rate, non-uniform corrosion rate and minimum cross-sectional area of ​​corrosion; the corrosion morphology characterization includes overall corrosion morphology characterization and pitting morphology characterization; the overall corrosion morphology characterization includes the average corrosion depth and the standard deviation of the corrosion depth; the pitting morphology characterization includes rust pit depth, rust pit diameter-to-depth ratio, rust pit volume ratio and rust pit density.

4. A method for evaluating the bearing performance of a corroded steel structure according to claim 3, characterized in that: In step 3, the random characterization model of the corroded surface of the steel structure to be evaluated includes a random field model of the corrosion depth of the overall corrosion of the steel structure to be evaluated and a random distribution model of rust pits of the pitting corrosion of the steel structure to be evaluated.

5. A method for evaluating the bearing performance of a corroded steel structure according to claim 1, characterized in that: In step 4, the process of establishing a random corroded surface finite element geometric model of the basic components of the steel structure to be evaluated according to the corroded surface morphology mapping reconstruction result of the steel structure to be evaluated is as follows: The rusted surface morphology mapping reconstruction result of the steel structure to be evaluated is subjected to coordinate transformation to obtain random rusted surface point cloud data of the basic components of the steel structure to be evaluated; wherein the random rusted surface point cloud data of the basic components of the steel structure to be evaluated is closed section point cloud data; A finite element geometric model of a basic component of the steel structure to be evaluated is constructed, and the random corroded surface point cloud data of the basic component of the steel structure to be evaluated is assigned to the finite element geometric model of the basic component of the steel structure to be evaluated, so as to obtain a random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated.

6. A method for evaluating the bearing performance of a corroded steel structure according to claim 1, characterized in that: In step 5, the process of performing finite element simulation calculation on the random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated by using the finite element parametric simulation method to obtain the load-bearing performance prediction result of the basic component of the steel structure to be evaluated is as follows: For the random corroded surface finite element geometric model of the basic component of the steel structure to be evaluated, material properties are set, loads and boundary conditions are applied, and finite element numerical simulation is performed to obtain the load-bearing performance prediction results of the basic component of the steel structure to be evaluated.

7. A system for evaluating the bearing performance of corroded steel structures, characterized in that: include: A scanning module is used to scan the surface features of the pre-selected local corroded area on the steel structure to be evaluated, and obtain the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; An indicator module is used to determine the corrosion evaluation index according to the three-dimensional morphology of the corroded surface of the local area of ​​the steel structure to be evaluated; A mapping and reconstruction module is used to establish a random characterization model of the corroded surface of the steel structure to be evaluated by using a preset corrosion dynamics model; and to map and reconstruct the morphology of the corroded surface of the steel structure to be evaluated according to the random characterization model of the corroded surface of the steel structure to be evaluated and the corrosion evaluation index, so as to obtain a mapping and reconstruction result of the morphology of the corroded surface of the steel structure to be evaluated; A geometric model module is used to establish a random corrosion surface finite element geometric model of the basic components of the steel structure to be evaluated according to the reconstruction result of the corrosion surface morphology mapping of the steel structure to be evaluated; wherein the basic components of the steel structure to be evaluated include beam components, column components, beam-column nodes and steel plate components of the steel structure to be evaluated; A numerical simulation module is used to perform finite element simulation calculation on a random corroded surface finite element geometric model of a basic component of the steel structure to be evaluated by using a finite element parametric simulation method, so as to obtain a prediction result of the bearing performance of the basic component of the steel structure to be evaluated; An evaluation module, used to evaluate the bearing performance of the steel structure to be evaluated based on the bearing performance prediction results of the basic components of the steel structure to be evaluated and the reliability evaluation theory, and obtain the bearing performance evaluation result of the corroded steel structure; The morphology mapping and reconstruction results of the corroded surface of the steel structure to be evaluated include the overall corrosion morphology mapping and reconstruction results and the pitting corrosion morphology mapping and reconstruction results; The construction process of the comprehensive corrosion morphology mapping reconstruction result is as follows: Using the preset corrosion dynamics model, a random field model of corrosion depth of the overall corrosion of the steel structure to be evaluated is established; Substitute the corrosion evaluation index into the random field model of the corrosion depth of the steel structure to be evaluated, and calculate the coordinate data of the overall corrosion point cloud of the corroded surface of the steel structure to be evaluated, that is, obtain the reconstruction result of the overall corrosion morphology mapping; The process of calculating the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated is as follows: Determine the power spectrum of the corrosion depth on the surface of the steel structure to be evaluated according to the average value of the corrosion depth on the surface of the steel structure to be evaluated and the standard deviation of the corrosion depth; According to the power spectrum of the corrosion depth on the surface of the steel structure to be evaluated, the two-dimensional random harmonic function is used to calculate the overall corrosion point cloud coordinate data of the corroded surface of the steel structure to be evaluated, that is, the overall corrosion morphology mapping reconstruction result is obtained; The construction process of the pitting morphology mapping reconstruction results is as follows: Using the preset corrosion kinetics model, a random distribution model of rust pits for pitting corrosion of the steel structure to be evaluated is established; Substituting the corrosion evaluation index into the random distribution model of the pitting of the steel structure to be evaluated, the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated is calculated, that is, the pitting morphology mapping reconstruction result is obtained; The process of calculating the pitting point cloud coordinate data of the corroded surface of the steel structure to be evaluated is as follows: Determine the number of rust pits according to the density of rust pits on the surface of the steel structure to be evaluated and the pre-calculated surface area of ​​the steel structure to be evaluated; wherein the pre-calculated surface area of ​​the steel structure to be evaluated is calculated by multiplying the surface length dimension and the width dimension of the steel structure to be evaluated; Generate random rust pits in batches according to the rust pit depth, rust pit diameter-to-depth ratio, rust pit shape probability parameters and the number of rust pits on the surface of the steel structure to be evaluated; Based on the batch generation of random rust pits, the pitting point cloud coordinate data of the corroded surface of the steel structure to be evaluated is calculated, that is, the pitting morphology mapping reconstruction result is obtained.

8. A device for evaluating the bearing capacity of a corroded steel structure, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the method for evaluating the bearing performance of a corroded steel structure as described in any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for evaluating the bearing performance of a corroded steel structure as described in any one of claims 1 to 6 are implemented.

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