CN115034001A - Method, system, equipment and medium for evaluating bearing performance of rusted steel structure - Google Patents
Method, system, equipment and medium for evaluating bearing performance of rusted steel structure Download PDFInfo
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Abstract
The invention discloses a method, a system, equipment and a medium for evaluating the bearing performance of a rusted steel structure, wherein the method comprises the following steps: scanning surface characteristics of a local rust area preselected on a steel structure to be evaluated, and determining a corrosion evaluation index; mapping reconstruction is carried out according to the corrosion surface random representation model and the corrosion evaluation index of the steel structure to be evaluated, and a mapping reconstruction result of the corrosion surface morphology of the steel structure to be evaluated is obtained; establishing a random rust surface finite element geometric model of a basic component of the steel structure to be evaluated according to a mapping reconstruction result of the rust surface appearance of the steel structure to be evaluated, 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 an evaluation result of the bearing performance of the rust steel structure; according to the method, the surface morphology of batch reconstruction is introduced into the finite element model, the calculation result has higher accuracy, and the load-bearing performance prediction and reliability evaluation of the rusted steel structure are realized.
Description
Technical Field
The invention belongs to the technical field of steel structure durability and safety evaluation, and particularly relates to a method, a system, equipment and a medium for evaluating the bearing performance of a rusted steel structure.
Background
The large steel structure engineering which is in the corrosion environment of the ocean, the industry and the like for a long time, such as large industrial buildings, bridges, high-voltage transmission towers, offshore oil production facilities and the like, often has serious corrosion problems; the corrosion causes serious damage to the steel structure and even engineering accidents; how to accurately evaluate the residual service performance of the existing rusted steel structure and prevent engineering accidents is a great problem for engineering technicians.
At present, a weight loss method and a thickness measurement method are the most commonly used methods for evaluating steel corrosion; the corrosion weight loss measurement and calculation are simpler, but have greater limitations, which are mainly reflected in two aspects: firstly, the weight loss method can only evaluate the uniform corrosion degree, and cannot represent the influence of non-uniform corrosion; secondly, a weightlessness method is used for sampling corrosion parts, is a destructive measurement method, is only limited to laboratory analysis and is difficult to apply in actual engineering; the thickness measurement method is a nondestructive measurement method for detecting the thickness of a component through a vernier caliper or an ultrasonic thickness gauge, but generally only can give the thickness of a certain position point, cannot reflect the corrosion condition of the whole component, and has a rough result.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention provides a method, a system, equipment and a medium for evaluating the bearing performance of a corroded steel structure, and aims to solve the technical problems that the existing method for evaluating the corrosion degree and the service performance of the steel structure is insufficient in accuracy, cannot restore the real corrosion morphology, and is easy to damage the original structure.
In order to achieve the purpose, the invention adopts the technical scheme that:
the invention discloses a method for evaluating the bearing performance of a rusted steel structure, which comprises the following steps:
and 6, evaluating the bearing performance of the steel structure to be evaluated according to the bearing performance prediction result of the basic component of the steel structure to be evaluated and the reliability evaluation theory to obtain the evaluation result of the bearing performance of the rusted steel structure.
Further, in the step 1, the process of scanning the surface characteristics of the pre-selected local area on the steel structure to be evaluated to obtain the three-dimensional appearance of the rusted surface of the local area of the steel structure to be evaluated specifically includes:
randomly selecting a local rust area on a steel structure to be evaluated, and carrying out rust removal treatment to obtain the local rust area after the rust removal treatment;
performing surface feature scanning on the local rust area subjected to rust removal treatment by using a three-dimensional non-contact laser scanner to obtain the three-dimensional appearance of the rust surface of the local area of the steel structure to be evaluated; the three-dimensional appearance of the local area rust surface of the steel structure to be evaluated is three-dimensional point cloud coordinate data of the local area rust surface of the steel structure to be evaluated.
Further, in step 2, the corrosion evaluation index comprises a mechanical property evaluation index and a corrosion morphology characterization;
the mechanical property evaluation indexes comprise corrosion rate, non-uniform corrosion rate and corrosion minimum cross-sectional area; the corrosion morphology characterization comprises comprehensive corrosion morphology characterization and pitting morphology characterization; the overall corrosion morphology characterization comprises a corrosion depth average value and a corrosion depth standard deviation; the characterization of the pitting morphology comprises the depth of the rust pit, the diameter-depth ratio of the rust pit, the volume ratio of the rust pit and the density of the rust pit.
Further, in step 3, the rusted surface random representation model of the steel structure to be evaluated comprises a rusted depth random field model of the overall corrosion of the steel structure to be evaluated and a rusted pit random distribution model of pitting corrosion of the steel structure to be evaluated; and the mapping and reconstruction result of the corrosion surface appearance of the steel structure to be evaluated comprises a full corrosion appearance mapping and reconstruction result and a pitting appearance mapping and reconstruction result.
Further, the construction process of the general corrosion topography mapping reconstruction result specifically comprises the following steps:
establishing a corrosion depth random field model of the overall corrosion of the steel structure to be evaluated by using a preset corrosion dynamics model;
substituting the corrosion evaluation index into the corrosion depth random field model of the overall corrosion of the steel structure to be evaluated, and calculating to obtain overall corrosion point cloud coordinate data of the corrosion surface of the steel structure to be evaluated, so as to obtain an overall corrosion morphology mapping reconstruction result;
the process of calculating and obtaining the comprehensive corrosion point cloud coordinate data of the corrosion surface of the steel structure to be evaluated specifically comprises the following steps:
determining a power spectrum of the rust depth of the surface of the steel structure to be evaluated according to the average value of the rust depth of the surface of the steel structure to be evaluated and the standard deviation of the rust depth;
calculating to obtain the coordinate data of the comprehensive corrosion point cloud of the corrosion surface of the steel structure to be evaluated by utilizing a two-dimensional random harmonic function according to the power spectrum of the corrosion depth of the surface of the steel structure to be evaluated, and obtaining the mapping and reconstruction result of the comprehensive corrosion morphology;
the construction process of the pitting topography mapping reconstruction result specifically comprises the following steps:
establishing a rust pit random distribution model of pitting corrosion of a steel structure to be evaluated by using a preset corrosion dynamics model;
substituting the corrosion evaluation index into the corrosion pit random distribution model of the pitting corrosion of the steel structure to be evaluated, and calculating to obtain the pitting point cloud coordinate data of the rusting surface of the steel structure to be evaluated, so as to obtain the pitting appearance mapping reconstruction result;
the process of calculating and obtaining the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated specifically comprises the following steps:
determining the number of the rust pits according to the density of the 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; the pre-calculated surface area of the steel structure to be evaluated is obtained by multiplying the length size and the width size of the surface of the steel structure to be evaluated;
generating random rust pits in batches according to the depth of the rust pits on the surface of the steel structure to be evaluated, the diameter-depth ratio of the rust pits, the shape probability parameter of the rust pits and the number of the rust pits;
and generating random rust pits according to the batches, and calculating to obtain the point cloud coordinate data of the pitting corrosion on the corrosion surface of the steel structure to be evaluated to obtain the pitting corrosion morphology mapping reconstruction result.
Further, in step 4, according to the mapping and reconstructing result of the rusted surface topography of the steel structure to be evaluated, a process of establishing a finite element geometric model of the random rusted surface of the basic member of the steel structure to be evaluated is specifically as follows:
mapping and reconstructing the appearance of the rusted surface of the steel structure to be evaluated, and performing coordinate transformation to obtain random rusted surface point cloud data of a basic component of the steel structure to be evaluated; the point cloud data of the random rusted surface of the basic member of the steel structure to be evaluated is closed cross-section point cloud data;
and constructing a finite element geometric model of the basic component of the steel structure to be evaluated, and assigning the point cloud data of the random rusting surface of the basic component of the steel structure to be evaluated to the finite element geometric model of the basic component of the steel structure to be evaluated to obtain the finite element geometric model of the random rusting surface of the basic component of the steel structure to be evaluated.
Further, in step 5, a finite element parametric simulation method is used to perform finite element simulation calculation on the finite element geometric model of the random corrosion surface 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, specifically the following steps:
and setting material properties of the finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated, applying load and boundary conditions, and carrying out finite element numerical simulation to obtain a load-bearing performance prediction result of the basic component of the steel structure to be evaluated.
The invention also provides a system for evaluating the bearing performance of the rusted steel structure, which comprises the following components:
the scanning module is used for scanning the surface characteristics of a preselected local corrosion area on the steel structure to be evaluated to obtain the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated;
the index module is used for determining corrosion evaluation indexes according to the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated;
the mapping reconstruction module is used for establishing a random characterization model of the corrosion surface of the steel structure to be evaluated by using a preset corrosion dynamics model; mapping and reconstructing the rusty surface appearance of the steel structure to be evaluated according to the rusty surface random representation model of the steel structure to be evaluated and the corrosion evaluation index to obtain a rusty surface appearance mapping and reconstructing result of the steel structure to be evaluated;
the geometric model module is used for establishing a random rust surface finite element geometric model of the basic component of the steel structure to be evaluated according to the mapping and reconstruction result of the rust surface appearance of the steel structure to be evaluated; the basic components of the steel structure to be evaluated comprise a beam component, a column component, a beam-column node and a steel plate component of the steel structure to be evaluated;
the numerical simulation module is used for carrying out finite element simulation calculation on a finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated by using a finite element parametric simulation method to obtain a load-bearing performance prediction result of the basic component of the steel structure to be evaluated;
and the evaluation module is used for evaluating the bearing performance of the steel structure to be evaluated according to the bearing performance prediction result of the basic component of the steel structure to be evaluated and the reliability evaluation theory to obtain the bearing performance evaluation result of the rusted steel structure.
The invention also provides equipment for evaluating the bearing performance of the rusted steel structure, which comprises the following components:
a memory for storing a computer program;
and the processor is used for realizing the steps of the rusted steel structure bearing performance evaluation method when executing the computer program.
The invention also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the steps of the rusted steel structure bearing performance evaluation method.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a method, a system, equipment and a medium for evaluating the bearing performance of a corroded steel structure, which are used for scanning the surface corrosion characteristics of a local area representative of the steel structure to be evaluated, realizing the nondestructive acquisition of corrosion morphology data and avoiding the damage to the original structure; the corrosion evaluation index system established based on the surface morphology can evaluate the uniform corrosion degree and represent the non-uniform corrosion degree, and solves 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 indexes, establishing a corrosion surface characterization model which aims at different corrosion environments and meets certain statistical characteristics, and based on the limited morphology data, the batch mapping reconstruction of the large-size surface morphology of basic members such as corroded steel structure beams, columns and the like can be realized, so that data support is provided for the subsequent structural performance prediction and reliability evaluation; the method introduces the surface appearance reconstructed in batches into a finite element model, can consider the uncertainty of corrosion characteristics, has higher accuracy of a calculation result, realizes the prediction and reliability evaluation of the bearing performance of the corroded steel structure, and solves the problem that actual engineering and mechanical performance tests cannot be repeated; the invention can further enrich the performance evaluation means in the field of durability and safety of the engineering structure and provide technical basis for engineering technicians engaged in detection, evaluation and reinforcement of the existing engineering structure.
Drawings
FIG. 1 is a flow chart of a method for evaluating the bearing performance of a corroded steel structure according to an embodiment;
FIG. 2 is a schematic diagram of a process for scanning the corrosion morphology of a corroded steel structure in the embodiment;
FIG. 3 is a corrosion evaluation index system of a corroded steel structure in the example;
FIG. 4 is a schematic diagram illustrating point cloud coordinate transformation of an H-shaped steel beam in the embodiment; wherein, fig. 4(a) is a schematic diagram of randomly generated surface point cloud arrangement, fig. 4(b) is a schematic diagram of coordinate-converted point cloud arrangement of a cross section of an H-shaped steel beam, fig. 4(c) is a cloud diagram of randomly generated surface points of a cross section of an H-shaped steel beam, and fig. 4(d) is a cloud diagram of coordinate-converted point cloud of an H-shaped steel beam;
FIG. 5 is a schematic diagram of a finite element geometric model of a randomly generated pitting C-shaped steel column in the embodiment; fig. 5(a) is a schematic diagram of randomly generating a point-etched C-shaped steel column integral finite element geometric model, fig. 5(b) is a schematic diagram of randomly generating a point-etched C-shaped steel column finite element geometric model in a partially enlarged manner, and fig. 5(C) is a schematic diagram of randomly generating a point-etched C-shaped steel column finite element geometric model rust pit distribution;
FIG. 6 is a load displacement graph of a bending test load displacement curve of a rusted H-shaped steel beam and a randomly generated finite element model simulation in the embodiment;
FIG. 7 is a load displacement graph of a stress test load displacement curve of a rusted C-shaped steel column and a randomly generated finite element model simulation in the embodiment.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects of the present invention more apparent, the following embodiments further describe the present invention in detail. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a method for evaluating the bearing performance of a rusted steel structure, which comprises the following steps:
randomly selecting a local rust area on a steel structure to be evaluated, and carrying out rust removal treatment to obtain the local rust area after the rust removal treatment;
carrying out surface feature scanning on the local rust area subjected to rust removal treatment by using a three-dimensional non-contact laser scanner to obtain the three-dimensional appearance of the rust surface of the local area of the steel structure to be evaluated; the three-dimensional appearance of the local area rust surface of the steel structure to be evaluated is three-dimensional point cloud coordinate data of the local area rust surface of the steel structure to be evaluated.
The construction process of the general corrosion morphology mapping reconstruction result specifically comprises the following steps:
establishing a corrosion depth random field model of the overall corrosion of the steel structure to be evaluated by using a preset corrosion dynamics model;
substituting the corrosion evaluation index into the corrosion depth random field model of the overall corrosion of the steel structure to be evaluated, and calculating to obtain overall corrosion point cloud coordinate data of the corrosion surface of the steel structure to be evaluated, so as to obtain an overall corrosion morphology mapping reconstruction result;
the process of calculating and obtaining the comprehensive corrosion point cloud coordinate data of the corrosion surface of the steel structure to be evaluated specifically comprises the following steps:
determining a power spectrum of the corrosion depth of the surface of the steel structure to be evaluated according to the average value of the corrosion depth of the surface of the steel structure to be evaluated and the standard deviation of the corrosion depth;
calculating to obtain the coordinate data of the comprehensive corrosion point cloud of the corrosion surface of the steel structure to be evaluated by utilizing a two-dimensional random harmonic function according to the power spectrum of the corrosion depth of the surface of the steel structure to be evaluated, and obtaining the mapping and reconstruction result of the comprehensive corrosion morphology;
the construction process of the pitting topography mapping reconstruction result specifically comprises the following steps:
establishing a rust pit random distribution model of pitting corrosion of a steel structure to be evaluated by using a preset corrosion dynamics model;
substituting the corrosion evaluation index into the corrosion pit random distribution model of the pitting corrosion of the steel structure to be evaluated, and calculating to obtain the pitting point cloud coordinate data of the rusting surface of the steel structure to be evaluated, so as to obtain the pitting appearance mapping reconstruction result;
the process of calculating and obtaining the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated specifically comprises the following steps:
determining the number of the rust pits according to the density of the 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; the pre-calculated surface area of the steel structure to be evaluated is obtained by multiplying the length size and the width size of the surface of the steel structure to be evaluated;
generating random rust pits in batches according to the depth of the rust pits on the surface of the steel structure to be evaluated, the diameter-depth ratio of the rust pits, the shape probability parameter of the rust pits and the number of the rust pits;
and generating random rust pits according to the batches, and calculating to obtain the point cloud coordinate data of the pitting corrosion on the corrosion surface of the steel structure to be evaluated to obtain the pitting corrosion morphology mapping reconstruction result.
The construction process of the finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated specifically comprises the following steps:
mapping and reconstructing the appearance of the rusted surface of the steel structure to be evaluated, and performing coordinate transformation to obtain random rusted surface point cloud data of a basic member of the steel structure to be evaluated; the point cloud data of the random rusted surface of the basic member of the steel structure to be evaluated is closed cross-section point cloud data;
and constructing a finite element geometric model of the basic component of the steel structure to be evaluated, and assigning the point cloud data of the random rusting surface of the basic component of the steel structure to be evaluated to the finite element geometric model of the basic component of the steel structure to be evaluated to obtain the finite element geometric model of the random rusting surface of the basic component of the steel structure to be evaluated.
And 6, evaluating the bearing performance of the steel structure to be evaluated according to the bearing performance prediction result of the basic component of the steel structure to be evaluated and the reliability evaluation theory to obtain the bearing performance evaluation result of the rusted steel structure.
The invention also provides a system for evaluating the bearing performance of the rusted steel structure, which comprises a scanning module, an index module, a mapping reconstruction module, a geometric model module, a numerical simulation module and an evaluation module; the scanning module is used for scanning the surface characteristics of a preselected local corrosion area on the steel structure to be evaluated to obtain the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated; the index module is used for determining corrosion evaluation indexes according to the three-dimensional appearance of the rusted surface of the local area of the steel structure to be evaluated; the mapping and rebuilding module is used for establishing a corrosion surface random representation model of the steel structure to be evaluated by utilizing a preset corrosion kinetic model; mapping and reconstructing the rusty surface appearance of the steel structure to be evaluated according to the rusty surface random characterization model of the steel structure to be evaluated and the corrosion evaluation index to obtain a rusty surface appearance mapping and reconstructing result of the steel structure to be evaluated; the geometric model module is used for establishing a random rust surface finite element geometric model of the basic component of the steel structure to be evaluated according to the mapping and reconstruction result of the rust surface appearance of the steel structure to be evaluated; the basic components of the steel structure to be evaluated comprise a beam component, a column component, a beam-column node and a steel plate component of the steel structure to be evaluated; the numerical simulation module is used for carrying out finite element simulation calculation on a finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated by using a finite element parametric simulation method to obtain a load-bearing performance prediction result of the basic component of the steel structure to be evaluated; and the evaluation module is used for evaluating the bearing performance of the steel structure to be evaluated according to the bearing performance prediction result of the basic component of the steel structure to be evaluated and the reliability evaluation theory to obtain the bearing performance evaluation result of the rusted steel structure.
According to the method and the system for evaluating the bearing performance of the corroded steel structure, the surface corrosion characteristics of the local area representative of the steel structure to be evaluated are scanned, so that the nondestructive acquisition of corrosion morphology data is realized, and the damage to the original structure is avoided; the corrosion evaluation index system established based on the surface morphology can evaluate the uniform corrosion degree and represent the non-uniform corrosion degree, and solves the problem that the original index cannot reflect the influence of non-uniform corrosion; based on the statistical analysis of the morphology data and evaluation indexes, establishing a corrosion surface characterization model which aims at different corrosion environments and meets certain statistical characteristics, and based on the limited morphology data, the batch mapping reconstruction of the large-size surface morphology of basic members such as corroded steel structure beams and columns can be realized, so that data support is provided for the subsequent structural performance prediction and reliability evaluation; the method introduces the surface appearance reconstructed in batches into a finite element model, can consider the uncertainty of corrosion characteristics, has higher accuracy of a calculation result, realizes the bearing performance prediction and reliability evaluation of a corroded steel structure, and solves the problem that actual engineering and mechanical performance tests cannot be repeated.
The invention also provides equipment for evaluating the bearing performance of the rusted steel structure, which comprises the following components: a memory for storing a computer program; and the processor is used for realizing the steps of the rusted steel structure bearing performance evaluation method when the computer program is executed.
When the processor executes the computer program, the method for evaluating the bearing performance of the rusted steel structure is realized, for example: scanning surface characteristics of a preselected local rust area on a steel structure to be evaluated to obtain a three-dimensional appearance of the rust surface of the local area of the steel structure to be evaluated; determining corrosion evaluation indexes according to the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated; establishing a random characterization model of the rusted surface of the steel structure to be evaluated by using a preset corrosion dynamics model; mapping and reconstructing the rusty surface appearance of the steel structure to be evaluated according to the rusty surface random characterization model of the steel structure to be evaluated and the corrosion evaluation index to obtain a rusty surface appearance mapping and reconstructing result of the steel structure to be evaluated; establishing a finite element geometric model of the random rusty surface of the basic component of the steel structure to be evaluated according to the mapping and reconstruction result of the rusty surface topography of the steel structure to be evaluated; the basic components of the steel structure to be evaluated comprise a beam component, a column component, a beam-column node and a steel plate component of the steel structure to be evaluated; carrying out finite element simulation calculation on a finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated by using a finite element parametric simulation method to obtain a load-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 according to the bearing performance prediction result of the basic component of the steel structure to be evaluated and the reliability evaluation theory to obtain the evaluation result of the bearing performance of the rusted steel structure.
Alternatively, the processor implements the functions of the modules in the system when executing the computer program, for example: the scanning module is used for scanning the surface characteristics of a preselected local corrosion area on the steel structure to be evaluated to obtain the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated; the index module is used for determining corrosion evaluation indexes according to the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated; the mapping reconstruction module is used for establishing a random characterization model of the corrosion surface of the steel structure to be evaluated by using a preset corrosion dynamics model; mapping and reconstructing the rusty surface appearance of the steel structure to be evaluated according to the rusty surface random representation model of the steel structure to be evaluated and the corrosion evaluation index to obtain a rusty surface appearance mapping and reconstructing result of the steel structure to be evaluated; the geometric model module is used for establishing a random rust surface finite element geometric model of a basic component of the steel structure to be evaluated according to the mapping and reconstruction result of the rust surface topography of the steel structure to be evaluated; the basic components of the steel structure to be evaluated comprise a beam component, a column component, a beam-column node and a steel plate component of the steel structure to be evaluated; the numerical simulation module is used for carrying out finite element simulation calculation on a finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated by using a finite element parametric simulation method to obtain a load-bearing performance prediction result of the basic component of the steel structure to be evaluated; and the evaluation module is used for evaluating the bearing performance of the steel structure to be evaluated according to the bearing performance prediction result of the basic component of the steel structure to be evaluated and the reliability evaluation theory so as to obtain the evaluation result of the bearing performance of the rusted steel structure.
Illustratively, the computer program may be partitioned into one or more modules/units, stored in the memory and executed by the processor, to implement the invention. The one or more modules/units can be a series of instruction segments of a computer program capable of completing preset functions, and the instruction segments are used for describing the execution process of the computer program in the equipment for evaluating the bearing performance of the corroded steel structure.
The rusted steel structure bearing performance evaluation equipment can be computing equipment such as a desktop computer, a notebook computer, a palm computer and a cloud server. The rusted steel structure bearing performance evaluation equipment can comprise, but is not limited to, a processor and a memory. Those skilled in the art will understand that the above is an example of the rusted steel structure bearing performance evaluation device, and does not constitute a limitation of the rusted steel structure bearing performance evaluation device, and may include more components than the above, or combine some components, or different components, for example, the rusted steel structure bearing performance evaluation device may further include an input/output device, a network access device, a bus, and the like.
The processor may be a Central Processing Unit (CPU), other general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. The general processor can be a microprocessor or the processor can also be any conventional processor and the like, the processor is a control center of the rusted steel structure bearing performance evaluation equipment, and various interfaces and lines are utilized to connect all parts of the whole rusted steel structure bearing performance evaluation equipment.
The memory can be used for storing the computer program and/or the module, and the processor realizes various functions of the equipment for evaluating the bearing performance of the rusted steel structure by running or executing the computer program and/or the module stored in the memory and calling data stored in the memory.
The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid state storage device.
The invention also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the steps of the method for evaluating the bearing performance of the rusted steel structure.
The module/unit integrated with the rusted steel structure bearing performance evaluation system can be stored in a computer readable storage medium if the module/unit is realized in the form of a software functional unit and is sold or used as an independent product.
Based on such understanding, all or part of the processes in the method for evaluating the bearing performance of the corroded steel structure can be realized by the invention, and the processes can also be completed by instructing related hardware through a computer program, wherein 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 method for evaluating the bearing performance of the corroded steel structure can be realized. Wherein the computer program comprises computer program code, which may be in source code form, object code form, executable file or preset intermediate form, etc.
The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer memory, Read-only memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc.
It should be noted that the computer readable storage medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable storage media that does not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
Examples
As shown in fig. 1, the embodiment provides a method for evaluating the bearing performance of a corroded steel structure, which includes: scanning the surface characteristics of the randomly selected local area of the steel structure to be evaluated to obtain the three-dimensional appearance of the rusted surface of the local area of the steel structure to be evaluated; determining a corrosion evaluation index according to the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated; establishing a random characterization model of the rusted surface of the steel structure to be evaluated by using a preset corrosion dynamics model; mapping and reconstructing the rusty surface appearance of the steel structure to be evaluated according to the rusty surface random characterization model of the steel structure to be evaluated and the corrosion evaluation index to obtain a rusty surface appearance mapping and reconstructing result of the steel structure to be evaluated; establishing a finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated according to the mapping and reconstruction result of the rust surface appearance of the steel structure to be evaluated; the basic components of the steel structure to be evaluated comprise a beam component, a column component, a beam-column node and a steel plate component of the steel structure to be evaluated; carrying out finite element simulation calculation on a finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated by using a finite element parametric simulation method to obtain a load-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 according to the bearing performance prediction result of the basic component of the steel structure to be evaluated and the reliability evaluation theory to obtain the evaluation result of the bearing performance of the rusted steel structure.
The method for evaluating the bearing performance of the rusted steel structure specifically comprises the following steps:
visually inspecting the corrosion condition of the basic member of the steel structure to be evaluated, and dividing the corrosion grade and the corrosion range of the basic member of the steel structure to be evaluated; the basic components of the steel structure to be evaluated comprise a beam component, a column component, a beam-column node and a steel plate component of the steel structure to be evaluated;
randomly selecting local rust areas from basic components of the steel structure to be evaluated with different rust grades to serve as rust representative areas of the steel structure to be evaluated;
carrying out mechanical rust removal treatment on the local rust area to obtain a rust-removed local rust area;
performing surface feature scanning on the local rust area subjected to rust removal treatment by using a three-dimensional non-contact laser scanner to obtain the three-dimensional appearance of the rust surface of the local area of the steel structure to be evaluated; the three-dimensional appearance of the local area rust surface of the steel structure to be evaluated can represent the overall corrosion condition of the steel structure to be evaluated, and is three-dimensional point cloud coordinate data of the local area rust surface of the steel structure to be evaluated.
In the embodiment, when the mechanical rust removal treatment is performed on the local rust area, a copper wire is adopted to polish the local rust area; because the hardness of the copper wire is less than that of iron, the damage of the polishing treatment to the surface appearance of a rusted area is avoided; the local rust area after rust removal treatment is wrapped by a preservative film to isolate air, and other preservative measures are adopted to carry out preservative treatment if necessary, so that the accuracy of a surface characteristic scanning result is ensured; after the rust removal treatment, as the original surface of the rusted steel cannot be reserved, the highest point of the surface after the rust removal treatment can be used as a reference surface of the rust depth by default; in order to accurately predict the bearing performance of the rusted steel structure, the positions and the number of the measuring areas can represent the corrosion degree of the whole structure.
The mechanical property evaluation indexes comprise corrosion rate, non-uniform corrosion rate and corrosion minimum cross-sectional area.
The corrosion morphology characterization comprises a comprehensive corrosion morphology characterization and a pitting morphology characterization; the overall corrosion morphology characterization comprises a corrosion depth average value and a corrosion depth standard deviation; the characterization of the pitting morphology comprises the depth of the rust pit, the diameter-depth ratio of the rust pit, the volume ratio of the rust pit and the density of the rust pit.
In this embodiment, before the corrosion morphology characterization is obtained, filtering processing needs to be performed on the scanning data of the three-dimensional morphology of the corrosion surface in the local area of the steel structure to be evaluated, so as to eliminate an image of abrupt noise.
The calculation process of each index parameter in the corrosion evaluation index specifically comprises the following steps:
1) non-uniform rust rate:
where ρ is n Non-uniform corrosion rates; (m-1) (n-1) is the number of all small columns contained between the upper and lower surfaces; Δ z 1 (i) The average height of the ith small column; s x Is the spacing of the scanning points in the x direction; s y Is the spacing of the scanning points in the y direction; v 0 Is the initial volume of the scan area.
2) Corrosion rate:
ρ＝1+ρ n -T max /T 0 (2)
wherein rho is the corrosion rate; t is 0 The initial thickness of the plate in the scanning area is set; t is max The maximum residual thickness of the plate in the scanning area after rusting.
3) Rust minimum cross-sectional area:
wherein, A ma Is the minimum cross-sectional area; m is the number of scanning points in the x direction;
is y ═ y j Average height of ith small quadrangle on the section.
4) Average rust depth:
wherein, t a Is the average value of the 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 ) The depth of rust at the spot was scanned.
5) Standard deviation of rust depth:
wherein, t s Is the standard deviation of rust depth.
6) Density of rust pits:
d p ＝N p /A 0 (6)
wherein d is p Is the rust pit density; n is a radical of hydrogen p The number of rust pits in the scanning area is shown; a. the 0 Is the area of the scan region.
7) Rust pit diameter-depth ratio:
AR＝R/h (7)
wherein AR is the ratio of the diameter to the depth of the rust pit; h is the depth of the rust pit; r is the diameter of the rust pit.
8) The volume ratio of the rust pit:
wherein VB is the volume ratio of the rust pit; v p Is the volume of the rust pit; v rec Is the minimum cuboid volume surrounding the rust pit; n is v The number of small columns in the rust pit is shown; Δ z 1 (i) Is the average height of the small cylinders; r x The diameter of the rust pit in the x direction, R y The diameter of the rust pit in the y direction; wherein, when VB is pi/12, the rust pit is close to the vertebral body; when VB is pi/6, the rust pit is close to a hemisphere; when VB is pi/4, the rust pit is close to a cylinder; when VB is 1, the rust pit is close to a rectangular parallelepiped.
In the embodiment, the random field model of the corrosion depth of the general corrosion of the steel structure to be evaluated is suitable for the random characterization of the general corrosion surface; the construction process of the general corrosion morphology mapping reconstruction result comprises the following steps: establishing a corrosion depth random field model of the overall corrosion of the steel structure to be evaluated by using a preset corrosion dynamics model; substituting the corrosion evaluation index into the comprehensive corroded corrosion depth random field model of the steel structure to be evaluated, and calculating to obtain comprehensive corrosion point cloud coordinate data of the corrosion surface of the steel structure to be evaluated, so as to obtain a comprehensive corrosion morphology mapping reconstruction result; the process of calculating and obtaining the comprehensive corrosion point cloud coordinate data of the corrosion surface of the steel structure to be evaluated specifically comprises the following steps: determining a power spectrum of the rust depth of the surface of the steel structure to be evaluated according to the average value of the rust depth of the surface of the steel structure to be evaluated and the standard deviation of the rust depth; and calculating to obtain the coordinate data of the comprehensive corrosion point cloud of the corrosion surface of the steel structure to be evaluated by utilizing a two-dimensional random harmonic function according to the power spectrum of the corrosion depth of the surface of the steel structure to be evaluated, so as to obtain the mapping and reconstruction result of the comprehensive corrosion morphology.
The specific process is as follows:
1) and (3) performing two-dimensional discrete Fast Fourier Transform (FFT) on the scanning data of the local area of the steel structure to be evaluated:
ω 1p ＝2πp/ms x
ω 2q ＝2πq/ns y
wherein, ω is 1p The p harmonic component wave number in the x direction and the y direction; omega 2q Is the q harmonic component wave number in the x and y directions.
2) Calculating the two-dimensional discrete random field bilateral spectrum density of the scanning data points:
3) fitting the power spectral density calculation:
wherein k is 1 、k 2 Fitting parameters related to corrosion state; under normal atmospheric environment, suggest k 1 、k 2 And is calculated by the following formula:
k 1 ＝0.05t a 0.62 (12)
4) substituting the two-dimensional bilateral power spectral density into a trigonometric function to obtain a comprehensive corrosion random field model:
wherein, P is the number of harmonic components in the x direction; q is the number of harmonic components in the y direction; theta 1pq 、θ 2pq Is uniformly distributed in [0,2 pi ]]Random phase angles in between; omega 1p 、ω 2q P and q harmonic component wave numbers in x and y directions, omega 1p ＝pΔω 1 ＝pω 1u /P，ω 2p ＝qΔω 2 ＝qω 2u /Q；ω 1u 、ω 2u The upper cut-off wavenumber for the random field in the x, y directions is calculated by:
wherein, epsilon is < < 1; preferably, e is 0.0001.
5) The upper cut-off wavenumber ω is known 1u 、ω 2u And generating a surface size, the harmonic component number P, Q being determined by:
wherein L is x 、L y To generate the dimensions of the large-dimension surface in the x, y directions.
6) To avoid the spectrum aliasing phenomenon, the distance between the generating points in the x and y directions needs to satisfy the following condition:
M≥2P，N≥2Q (19)
wherein M, N is the number of points in the x, y directions that generate the large-size surface, S x 、S y To generate the spacing of the points of the large-size surface in the x, y direction.
7) Will determine the size L of the generated surface x And surface dimension L y Thereafter, a general corrosion surface was generated as follows:
s1, standard deviation t of rusting depth s Power spectral density parameter k 1 And a power spectral density parameter k 2 Substituting the above equation (11), determineGeneral corrosion surface power spectral density G;
s2, substituting the general corrosion surface power spectral density G into the formula (15) to determine the upper limit cut-off wave number omega 1u And upper cut-off wavenumber ω 2u ；
S3, setting the surface size L x Surface size L y Upper limit cutoff wave number ω 1u And upper cut-off wavenumber ω 2u Substituting equations (16) to (17), and determining the number P of harmonic components and the number Q of harmonic components; generating a spacing S of dots x Dot spacing S y The number of dots M and the number of dots N;
s4, the parameters are substituted into formula 14, and the large-size general corrosion surface can be randomly generated.
And S5, repeating the above process to generate large-size overall corrosion surfaces in batch.
In this embodiment, the construction process of the pitting topography mapping reconstruction result is as follows:
establishing a rust pit random distribution model of pitting corrosion of a steel structure to be evaluated by using a preset corrosion dynamics model; substituting the corrosion evaluation index into the corrosion pit random distribution model of the pitting corrosion of the steel structure to be evaluated, and calculating to obtain the pitting point cloud coordinate data of the rusting surface of the steel structure to be evaluated, so as to obtain the pitting appearance mapping reconstruction result; the process of calculating and obtaining the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated specifically comprises the following steps: determining the number of the rust pits according to the density of the 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; the pre-calculated surface area of the steel structure to be evaluated is obtained by multiplying the length size and the width size of the surface of the steel structure to be evaluated; generating random rust pits in batches according to the depth of the rust pits on the surface of the steel structure to be evaluated, the diameter-depth ratio of the rust pits, the shape probability parameter of the rust pits and the number of the rust pits; and generating random rust pits according to the batches, and calculating to obtain the point cloud coordinate data of the pitting corrosion on the corrosion surface of the steel structure to be evaluated to obtain the pitting corrosion morphology mapping reconstruction result.
The method specifically comprises the following steps:
1) processing the scanning topography data of the three-dimensional topography of the rusty surface of the local area of the steel structure to be evaluated, gradually creating a binary slice image from top to bottom by using an MATLAB platform along a z-axis, determining an isolated area, namely a rust pit position, by adopting a Floodfil algorithm, marking and numbering, inputting a corresponding number, calculating and extracting corresponding evaluation indexes of the rust pit, and finally realizing the calibration of all rust pit positions and the extraction of rust pit characteristic indexes on the corrosion surface by reducing the slice height.
2) Counting the number of the rust pits in the scanning area, and calculating the density d of the rust pits according to the formula (6) p (ii) a Performing hypothesis test on the extraction results of the depth h and the diameter-depth ratio AR of the rust pit by using a K-S test method, determining the probability distribution form of the depth and the diameter-depth ratio of the rust pit, and calculating the mean value mu of the depth of the rust pit h Average value mu of rust pit diameter-depth ratio AR Standard deviation of depth of rust pit σ h And standard deviation sigma of rust pit diameter-depth ratio AR 。
3) Judging the shape of the rust pit according to the volume ratio VB, wherein when the volume ratio VB is 0-0.4, the shape of the rust pit is a cone; when VB is 0.4-0.7, the rust pit is hemispheroid; when VB is 0.7-1, the rust pit is cylindrical;
the probability coefficients of the three rust pit shapes are:
wherein λ is 1 、λ 2 、λ 3 Ratio of rust pits of cone, hemisphere and cylinder, NP 1 、NP 2 、NP 3 The number of rust pits of the cone, the hemisphere and the cylinder is respectively, and NP is the number of all the rust pits. And (4) arranging the rust pit numbers extracted from the scanning morphology of the local area of the steel structure to be evaluated in an ascending order according to the depth of the rust pits, and counting the number of the rust pits in different rust pit depth intervals to obtain the probability coefficients of the rust pits with different shapes.
5) Obtaining the surface length L of the steel structure to be evaluated x And a width dimension L y Then generating the surface area of the steel structure to be evaluated according to the following process; it is composed ofThe specific generation process is as follows:
s1 according to pit Density (d) p ) And generating the surface size (L) x And L y ) Determining the number NP of rust pits from the formula (6);
s2 mean value mu according to rust pit depth h Average value mu of rust pit diameter-depth ratio AR Standard deviation of depth of rust pit σ h And standard deviation sigma of rust pit diameter-depth ratio AR Randomly generating NP rust pit depth and diameter depth ratio data according to the formula (21);
wherein nrnd is a ratio probability distribution function of pit depth and diameter depth.
S3, arranging the NP pit depth data in ascending order, and according to pit shape probability coefficient lambda 1 、λ 2 、λ 3 And the total rust pit number NP, determining the number NP of the rust pits of the cone, the hemisphere and the cylinder 1 、NP 2 、NP 3 Further determining the depth h of rust pit of cone, hemisphere and cylinder 1 、h 2 、h 3 And the aspect ratio AR 1 、AR 2 、AR 3 。
S4, after generating the geometric characteristics of NP rust pits, the positions of the rust pits are further determined, and the position coordinates (x) 0 ,y 0 ) Can be arranged in the surface region (L) of the plate x ,L y ) And (3) random generation:
s5, writing a single pit surface equation according to the depth, the diameter-depth ratio and the position of pits with different shapes:
a pitting surface with NP pits present can then be expressed as the intersection of NP single pit surfaces:
and S6, repeating the process, and generating the large-size pitting corrosion surface in batches.
The specific process is as follows:
mapping and reconstructing the appearance of the rusted surface of the steel structure to be evaluated, and performing coordinate transformation to obtain random rusted surface point cloud data of a basic member of the steel structure to be evaluated; the point cloud data of the random rusted surface of the basic member of the steel structure to be evaluated is closed cross-section point cloud data;
and constructing a finite element geometric model of the basic component of the steel structure to be evaluated, and assigning the point cloud data of the random rusting surface of the basic component of the steel structure to be evaluated to the finite element geometric model of the basic component of the steel structure to be evaluated to obtain the finite element geometric model of the random rusting surface of the basic component of the steel structure to be evaluated.
In this embodiment, the surface morphology after mapping reconstruction is three-dimensional plane point cloud coordinate data, which is actually an expansion surface of a basic member such as a beam or a column of a steel structure to be evaluated, and the basic member such as a beam or a column with a closed cross section can be formed after coordinate transformation is performed on generated point cloud data; as shown in fig. 4, fig. 4 is a schematic diagram of point cloud coordinate transformation of an H-shaped steel beam in the embodiment; wherein, the attached figure 4(a) is a schematic diagram of randomly generating surface point cloud arrangement, and the attached figure 4(b) is a schematic diagram of H-shaped steel section point cloud arrangement after coordinate transformation; surface AA in fig. 4(b) is transformed from the coordinates of surface a in fig. 4(a), the rest of the surfaces being the same; fig. 4(c) is a randomly generated H-shaped steel beam cross section expansion surface point cloud chart, and fig. 4(d) is an H-shaped steel beam point cloud chart after coordinate conversion, in this embodiment, the H-shaped steel beam point cloud chart after coordinate conversion shown in fig. 4(d) is obtained by the coordinate conversion method shown in fig. 4(a) to fig. 4(b) according to the H-shaped steel beam cross section expansion surface point cloud chart shown in fig. 4 (c).
The following illustrates the coordinate transformation process, assuming that the randomly generated overall surface is the extended surface of the surface 1 and the surface 2, and the surface 1 and the surface 2 are on the same plane, in order to make the surfaces 1 and 2 belong to different planes in space, only one of the surfaces needs to be subjected to coordinate transformation according to a certain angle; the coordinate conversion steps are as follows:
1) assuming that there is an arbitrary point P on the surface, the three-dimensional coordinates in space before and after the coordinate conversion are P 1 (x 1 ,y 1 ,z 1 ) And P 2 (x 2 ,y 2 ,z 2 )。
2) By rotation and translation, the point coordinate P can be determined 1 Conversion to point coordinates P 2 . The conversion formula is as follows:
3) and (3) transforming by using a 3 multiplied by 3 rotation matrix R and a three-dimensional translation vector T, wherein the transformation formula is as follows:
wherein x is 0 、y 0 And z 0 Is three translation parameters, a 11 、a 12 、a 13 、a 21 、a 22 、a 23 、a 31 、a 32 And a 33 Respectively nine directional cosines.
And sequentially assigning the point cloud data after coordinate transformation to model nodes so as to establish a finite element geometric model of basic components such as corrosion beams, columns and the like, wherein the finite element geometric model specifically comprises the following steps: according to the requirement of the finite element geometric model on grid node division, when the point cloud spacing is equal to the required unit grid size, the point cloud spacing can be directly and sequentially endowed; when the point cloud spacing is smaller than the required unit grid size, point clouds can be given to unit nodes at intervals; when the cloud point distance is larger than the size of the needed unit grid, linear difference values can be firstly carried out and then sequentially given; as shown in fig. 5, a schematic diagram of a finite element geometric model of a randomly generated pitting corrosion C-shaped steel column in the embodiment is shown in fig. 5; fig. 5(a) is a schematic diagram of a randomly generated integral finite element geometric model of the pitting corrosion C-shaped steel column, fig. 5(b) is a schematic diagram of a randomly generated local enlargement of a finite element geometric model of the pitting corrosion C-shaped steel column, and fig. 5(C) is a schematic diagram of pit distribution of the randomly generated finite element geometric model of the pitting corrosion C-shaped steel column.
In this embodiment, a finite element numerical simulation method is used to give material properties, loads and boundary conditions to the generated finite element geometric models of the large-batch corrosion beam and column members, and finite element numerical simulation is performed to obtain the prediction results of the bearing performance of the large-batch corrosion beam and column members of the steel structure to be evaluated. As shown in fig. 6 and 7, the load displacement curves of the finite element models of the randomly generated rusty steel beams and rusty steel columns are almost the same as the test values, which shows that the method for evaluating the bearing performance of the rusty steel structure provided by the embodiment has higher precision.
Wherein beta is a reliable index of a rusted steel structure to be evaluated and mu R And σ R Respectively the mean value and standard deviation mu of the bearing capacity of the basic component of the rusted steel structure to be evaluated S And σ S Mean and standard deviation of the structural effect, respectively.
According to the method for evaluating the bearing performance of the corroded steel structure, the local surface of the corroded steel structure is accurately scanned by the non-contact high-resolution three-dimensional surface topography instrument; establishing a corrosion evaluation index system by adopting scanning data of a large representative local corrosion shape; performing index extraction and quantitative evaluation on the characteristics of the corrosion surface by means of a corrosion evaluation index system; a corrosion dynamic model and a random function are adopted to establish a corrosion surface random characterization function, and the surface appearance of the corroded steel can be mapped and reconstructed on a large scale; and evaluating the service performance and reliability of the rusted steel structure through batch random generation and finite element simulation. According to the method, the surface corrosion characteristics of the representative local small area of the steel structure to be evaluated are scanned, so that the nondestructive acquisition of corrosion morphology data is realized, and the damage to the original structure is avoided; the corrosion evaluation index system established based on the surface morphology can evaluate the uniform corrosion degree and represent the non-uniform corrosion degree, and solves the problem that the original index cannot reflect the influence of non-uniform corrosion; based on the statistical analysis of the morphology data and evaluation indexes, establishing a corrosion surface random model which aims at different corrosion environments and meets certain statistical characteristics, and based on the limited morphology data, realizing batch mapping reconstruction of large-size surface morphology of basic components of the corrosion steel structure beam column, and providing data support for subsequent structural performance prediction and reliability evaluation; the method introduces the surface morphology of batch reconstruction into a finite element model, can consider the uncertainty of corrosion characteristics, has higher accuracy of calculation results, realizes the load-bearing performance prediction and reliability evaluation of the corroded steel structure, and solves the problem that actual engineering and mechanical performance tests cannot be repeated; the invention can further enrich the performance evaluation means in the field of engineering structure durability and provide technical basis for engineering technicians engaged in the detection, evaluation and reinforcement of the existing engineering structure.
For a description of a relevant part in the system, the device, and the computer-readable storage medium for evaluating the bearing performance of the corroded steel structure provided by this embodiment, reference may be made to the detailed description of a corresponding part in the method for evaluating the bearing performance of the corroded steel structure described in this embodiment, which is not described herein again.
The above-described embodiment is only one of the embodiments that can implement the technical solution of the present invention, and the scope of the present invention to be claimed is not limited to the embodiment, but includes any changes, substitutions and other embodiments that can be easily conceived by those skilled in the art within the technical scope of the present invention disclosed.
Claims (10)
1. A method for evaluating the bearing performance of a rusted steel structure is characterized by comprising the following steps:
step 1, scanning surface characteristics of a local rust area preselected on a steel structure to be evaluated to obtain the three-dimensional appearance of the rust surface of the local area of the steel structure to be evaluated;
step 2, determining corrosion evaluation indexes according to the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated;
step 3, establishing a random characterization model of the rusted surface of the steel structure to be evaluated by using a preset corrosion dynamics model; mapping and reconstructing the rusty surface appearance of the steel structure to be evaluated according to the rusty surface random characterization model of the steel structure to be evaluated and the corrosion evaluation index to obtain a rusty surface appearance mapping and reconstructing result of the steel structure to be evaluated;
step 4, establishing a random rust surface finite element geometric model of the basic component of the steel structure to be evaluated according to the mapping and reconstruction result of the rust surface appearance of the steel structure to be evaluated; the basic components of the steel structure to be evaluated comprise a beam component, a column component, a beam-column node and a steel plate component of the steel structure to be evaluated;
step 5, carrying out finite element simulation calculation on a finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated by using a finite element parametric simulation method to obtain a load-bearing performance prediction result of the basic component of the steel structure to be evaluated;
and 6, evaluating the bearing performance of the steel structure to be evaluated according to the bearing performance prediction result of the basic component of the steel structure to be evaluated and the reliability evaluation theory to obtain the bearing performance evaluation result of the rusted steel structure.
2. The method for evaluating the bearing performance of the corroded steel structure according to claim 1, wherein in the step 1, the surface feature scanning is carried out on the preselected local area on the steel structure to be evaluated, and the three-dimensional appearance of the corroded surface of the local area of the steel structure to be evaluated is obtained, and the method comprises the following specific steps:
randomly selecting a local rust area on a steel structure to be evaluated, and carrying out rust removal treatment to obtain the local rust area after the rust removal treatment;
carrying out surface feature scanning on the local rust area subjected to rust removal treatment by using a three-dimensional non-contact laser scanner to obtain the three-dimensional appearance of the rust surface of the local area of the steel structure to be evaluated; the three-dimensional appearance of the local area rust surface of the steel structure to be evaluated is three-dimensional point cloud coordinate data of the local area rust surface of the steel structure to be evaluated.
3. The method for evaluating the bearing performance of the corroded steel structure according to claim 1, wherein in the step 2, the corrosion evaluation indexes comprise mechanical property evaluation indexes and corrosion morphology characterization;
the mechanical property evaluation indexes comprise a corrosion rate, a non-uniform corrosion rate and a corrosion minimum cross-sectional area; the corrosion morphology characterization comprises a comprehensive corrosion morphology characterization and a pitting morphology characterization; the overall corrosion morphology characterization comprises a corrosion depth average value and a corrosion depth standard deviation; the characterization of the pitting morphology comprises the depth of the pit, the diameter-depth ratio of the pit, the volume ratio of the pit and the density of the pit.
4. The method for evaluating the bearing performance of the corroded steel structure according to claim 3, wherein in the step 3, the corrosion surface random representation model of the steel structure to be evaluated comprises a corrosion depth random field model of the overall corrosion of the steel structure to be evaluated and a pit random distribution model of the pitting corrosion of the steel structure to be evaluated; and the reconstruction result of the mapping of the rusty surface topography of the steel structure to be evaluated comprises a reconstruction result of the mapping of the overall corrosion topography and a reconstruction result of the mapping of the pitting topography.
5. The method for evaluating the bearing capacity of the corroded steel structure according to claim 4, wherein the construction process of the overall corrosion morphology mapping reconstruction result specifically comprises the following steps:
establishing a corrosion depth random field model of the overall corrosion of the steel structure to be evaluated by using a preset corrosion dynamics model;
substituting the corrosion evaluation index into the corrosion depth random field model of the overall corrosion of the steel structure to be evaluated, and calculating to obtain overall corrosion point cloud coordinate data of the corrosion surface of the steel structure to be evaluated, so as to obtain an overall corrosion morphology mapping reconstruction result;
the process of calculating and obtaining the comprehensive corrosion point cloud coordinate data of the corrosion surface of the steel structure to be evaluated specifically comprises the following steps:
determining a power spectrum of the rust depth of the surface of the steel structure to be evaluated according to the average value of the rust depth of the surface of the steel structure to be evaluated and the standard deviation of the rust depth;
calculating to obtain comprehensive corrosion point cloud coordinate data of the corrosion surface of the steel structure to be evaluated by utilizing a two-dimensional random harmonic function according to the corrosion depth power spectrum of the surface of the steel structure to be evaluated, and obtaining a comprehensive corrosion morphology mapping reconstruction result;
the construction process of the pitting topography mapping reconstruction result specifically comprises the following steps:
establishing a rust pit random distribution model of pitting corrosion of a steel structure to be evaluated by using a preset corrosion dynamics model;
substituting the corrosion evaluation index into the pit random distribution model of the pitting corrosion of the steel structure to be evaluated, and calculating to obtain the pitting point cloud coordinate data of the rusting surface of the steel structure to be evaluated, so as to obtain the pitting morphology mapping reconstruction result;
the process of calculating and obtaining the pitting point cloud coordinate data of the rusted surface of the steel structure to be evaluated specifically comprises the following steps:
determining the number of the rust pits according to the density of the 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; the pre-calculated surface area of the steel structure to be evaluated is obtained by multiplying the length size and the width size of the surface of the steel structure to be evaluated;
generating random rust pits in batches according to the depth of the rust pits on the surface of the steel structure to be evaluated, the diameter-depth ratio of the rust pits, the shape probability parameter of the rust pits and the number of the rust pits;
and generating random rust pits according to the batches, and calculating to obtain the point cloud coordinate data of the pitting corrosion on the corrosion surface of the steel structure to be evaluated to obtain the pitting corrosion morphology mapping reconstruction result.
6. The method for evaluating the bearing performance of the corroded steel structure according to claim 1, wherein in the step 4, a process of establishing a finite element geometric model of the random corroded surface of the basic member of the steel structure to be evaluated according to the mapping and rebuilding result of the corroded surface appearance of the steel structure to be evaluated is specifically as follows:
mapping and reconstructing the appearance of the rusted surface of the steel structure to be evaluated, and performing coordinate transformation to obtain random rusted surface point cloud data of a basic component of the steel structure to be evaluated; the point cloud data of the random rusted surface of the basic member of the steel structure to be evaluated is closed cross-section point cloud data;
and constructing a finite element geometric model of the basic component of the steel structure to be evaluated, and assigning the point cloud data of the random rusted surface of the basic component of the steel structure to be evaluated to the finite element geometric model of the basic component of the steel structure to be evaluated to obtain the random rusted surface finite element geometric model of the basic component of the steel structure to be evaluated.
7. The method for evaluating the bearing performance of the corroded steel structure according to claim 1, wherein in the step 5, a finite element parametric simulation method is used for carrying out finite element simulation calculation on a finite element geometric model of the random corrosion surface of the basic member of the steel structure to be evaluated, so as to obtain a process of predicting the bearing performance of the basic member of the steel structure to be evaluated, and the process is specifically as follows:
and setting material properties of the finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated, applying load and boundary conditions, and carrying out finite element numerical simulation to obtain a load-bearing performance prediction result of the basic component of the steel structure to be evaluated.
8. The utility model provides a corrosion steel construction bearing capacity evaluation system which characterized in that includes:
the scanning module is used for scanning the surface characteristics of a preselected local corrosion area on the steel structure to be evaluated to obtain the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated;
the index module is used for determining corrosion evaluation indexes according to the three-dimensional appearance of the corrosion surface of the local area of the steel structure to be evaluated;
the mapping reconstruction module is used for establishing a random characterization model of the corrosion surface of the steel structure to be evaluated by using a preset corrosion dynamics model; mapping and reconstructing the rusty surface appearance of the steel structure to be evaluated according to the rusty surface random characterization model of the steel structure to be evaluated and the corrosion evaluation index to obtain a rusty surface appearance mapping and reconstructing result of the steel structure to be evaluated;
the geometric model module is used for establishing a random rust surface finite element geometric model of the basic component of the steel structure to be evaluated according to the mapping and reconstruction result of the rust surface appearance of the steel structure to be evaluated; the basic components of the steel structure to be evaluated comprise a beam component, a column component, a beam-column node and a steel plate component of the steel structure to be evaluated;
the numerical simulation module is used for carrying out finite element simulation calculation on a finite element geometric model of the random rust surface of the basic component of the steel structure to be evaluated by using a finite element parametric simulation method to obtain a load-bearing performance prediction result of the basic component of the steel structure to be evaluated;
and the evaluation module is used for evaluating the bearing performance of the steel structure to be evaluated according to the bearing performance prediction result of the basic component of the steel structure to be evaluated and the reliability evaluation theory so as to obtain the evaluation result of the bearing performance of the rusted steel structure.
9. The utility model provides a corrosion steel construction bearing capacity assessment equipment which characterized in that includes:
a memory for storing a computer program;
a processor for implementing the steps of the method for evaluating the bearing capacity of the corroded steel structure according to any one of claims 1 to 7 when the computer program is executed.
10. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of the method for evaluating the load bearing properties of a corroded steel structure as defined in any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115859559A (en) * | 2022-10-12 | 2023-03-28 | 东南大学 | Method for establishing corrosion spectrum for simulating corrosion degree of sling steel wire in service |
| CN117313483A (en) * | 2023-10-13 | 2023-12-29 | 华东交通大学 | Method for evaluating buckling bearing capacity of rusted cold-formed thin-walled steel column |
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- 2022-05-23 CN CN202210563607.5A patent/CN115034001A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115859559A (en) * | 2022-10-12 | 2023-03-28 | 东南大学 | Method for establishing corrosion spectrum for simulating corrosion degree of sling steel wire in service |
| CN115859559B (en) * | 2022-10-12 | 2024-02-09 | 东南大学 | Method for establishing corrosion spectrum for simulating corrosion degree of in-service pull sling steel wire |
| CN117313483A (en) * | 2023-10-13 | 2023-12-29 | 华东交通大学 | Method for evaluating buckling bearing capacity of rusted cold-formed thin-walled steel column |
| CN117313483B (en) * | 2023-10-13 | 2024-06-07 | 华东交通大学 | Method for evaluating buckling bearing capacity of rusted cold-formed thin-walled steel column |
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