Method, device and equipment for testing performance of steel composite pipe

Abstract

The invention provides a performance testing method, device and equipment for a steel composite pipe, and the method comprises the steps: collecting geometric dimension data and material data of the steel composite pipe, and obtaining basic data; performing performance index preliminary calculation on the basic data to obtain a preliminary performance index; performing multi-parameter simulation analysis processing on the preliminary performance indexes based on a finite element analysis algorithm to obtain performance index simulation data of the steel composite pipe under different parameter combinations; and on the basis of the performance index simulation data, the limit performance index of the steel composite pipe under the influence of the key parameters is obtained. According to the method, comprehensive calculation is conducted by combining geometric dimension data and material data of the steel composite pipe, multi-parameter simulation analysis is conducted by combining a finite element analysis algorithm, performance index simulation data of the steel composite pipe under various parameter combinations are obtained, and then the limit performance index of the steel composite pipe is tested. The defect that the performance of the steel composite pipe cannot be accurately evaluated at present is overcome.

Description

Technical Field

[0001] The present invention relates to the technical field of performance testing, and particularly relates to a performance testing method, device, and equipment for steel composite pipes. Background Art

[0002] Due to the combination of the high strength of steel and the excellent properties of other materials (such as plastics, ceramics, etc.), such as corrosion resistance and wear resistance, steel composite pipes are widely used in many industries such as petrochemical, municipal water supply and drainage, and ocean engineering. With the continuous development of engineering technology, the performance requirements for steel composite pipes are becoming increasingly stringent. Not only do they need to operate stably under normal working conditions, but they also need to maintain reliable performance under extreme environments and complex stress conditions.

[0003] However, there are many limitations in the traditional performance evaluation methods for steel composite pipes.

[0004] In the performance calculation and analysis stage, empirical formulas or simplified mechanical models were often used for calculation in the past. These methods cannot fully consider the multi-material composite characteristics of steel composite pipes. For example, when calculating the ultimate load and strain, simple empirical formulas are difficult to accurately simulate the influence of changes in different parameters (such as wall thickness, pipe diameter, material combination, etc.) on performance, and cannot provide accurate basis for engineering design, which is likely to cause over-design or under-design of engineering structures, increase engineering costs or pose potential safety hazards.

[0005] In addition, with the expansion of the engineering scale and the acceleration of technological innovation, the structural forms and material combinations of steel composite pipes are becoming increasingly diverse. Traditional performance testing methods are difficult to meet the needs of this rapid development, and cannot efficiently and accurately evaluate the performance of new steel composite pipes, thus unable to ensure the safety and reliability of engineering structures. Summary of the Invention

[0006] The main object of the present invention is to provide a performance testing method, device, and equipment for steel composite pipes, aiming to overcome the defect that the performance of steel composite pipes cannot be accurately evaluated at present.

[0007] To achieve the above object, the present invention provides a performance testing method for steel composite pipes, including the following steps:

[0008] Collect geometric dimension data and material data of the steel composite pipe to obtain basic data;

[0009] Perform preliminary calculation of performance indicators on the basic data to obtain preliminary performance indicators;

[0010] Based on the finite element analysis algorithm, perform multi-parameter simulation analysis on the preliminary performance indicators to obtain simulation data of the performance indicators of the steel composite pipe under different parameter combinations;

[0011] Based on the performance index simulation data, the ultimate performance index of the steel composite pipe under the influence of key parameters is obtained.

[0012] Furthermore, the preliminary performance index includes the preliminary ultimate load and the preliminary strain data.

[0013] Furthermore, after obtaining the ultimate performance index of the steel composite pipe under the influence of key parameters based on the performance index simulation data, it includes:

[0014] Graph plotting and visualization processing are performed on the ultimate performance index of the steel composite pipe under the influence of key parameters to obtain a steel composite pipe performance index chart for assisting engineering design analysis.

[0015] Furthermore, preliminary calculations of performance indices are performed on the basic data to obtain preliminary performance indices, including:

[0016] Based on the basic data, a structural mechanics model is constructed;

[0017] Based on the beam theory algorithm, a force analysis is performed on the constructed structural mechanics model and the preliminary ultimate load is calculated;

[0018] Based on the elastic modulus and Poisson's ratio data of the material, a deformation analysis is performed on the structural mechanics model and the preliminary strain data is calculated;

[0019] The preliminary ultimate load and the preliminary strain data are integrated to obtain the preliminary performance index.

[0020] Furthermore, based on the finite element analysis algorithm, multi-parameter simulation analysis processing is performed on the preliminary performance index to obtain the performance index simulation data of the steel composite pipe under different parameter combinations, including:

[0021] The preliminary performance index is input into the finite element analysis software, with the preliminary ultimate load as the boundary load condition and the preliminary strain data as the initial deformation condition;

[0022] For the wall thickness, pipe diameter, material combination of the inner and outer pipes, and connection method of the steel composite pipe, multiple groups of parameter combinations are set, and a finite element model of the steel composite pipe corresponding to each group of parameter combinations is constructed in the finite element analysis software;

[0023] In the finite element model, a gradually increasing virtual load is applied to the steel composite pipe to simulate the mechanical response process of the steel composite pipe under different load levels;

[0024] The finite element model is solved using the iterative calculation module in the finite element analysis algorithm to obtain the stress distribution data, strain change data, and corresponding ultimate load data of the steel composite pipe at different load stages under each group of parameter combinations;

[0025] Integrate the stress distribution data, strain change data, and ultimate load data for each set of parameter combinations to obtain the simulated performance index data of the steel composite pipe under different parameter combinations.

[0026] Furthermore, based on the simulated performance index data, obtain the ultimate performance index of the steel composite pipe under the influence of key parameters, including:

[0027] Extract the parameter characteristics related to the ultimate performance index of the steel composite pipe from the simulated performance index data based on the data mining algorithm; the parameter characteristics include the wall thickness characteristic, pipe diameter characteristic, material combination characteristic, and connection method characteristic;

[0028] Construct a multiple regression analysis model based on the parameter characteristics, with each parameter characteristic as the independent variable and the ultimate load and strain as the dependent variables, and determine the quantitative relationship expression between each parameter characteristic and the ultimate performance index through regression analysis;

[0029] Analyze the quantitative relationship expression based on the sensitivity analysis algorithm, calculate the sensitivity coefficients of each parameter characteristic, sort the parameter characteristics according to the magnitude of the sensitivity coefficients, and determine the key parameters;

[0030] Substitute the key parameters into the quantitative relationship expression to calculate the ultimate performance index of the steel composite pipe under the influence of the key parameters.

[0031] Furthermore, collect the geometric dimension data and material data of the steel composite pipe to obtain the basic data, including:

[0032] Use a three-dimensional laser scanning device to perform non-contact scanning on the outer contour of the steel composite pipe, obtain its surface point cloud data, and extract the pipe diameter, length, and wall thickness of the steel composite pipe through the point cloud data processing algorithm as the geometric dimension data;

[0033] Emit X-rays by an X-ray fluorescence spectrometer to excite the surface atoms of the steel composite pipe, receive and analyze the characteristic fluorescence spectrum emitted by it, so as to determine the types and contents of various elements constituting the steel composite pipe and determine its material data.

[0034] The present invention also provides a performance testing device for a steel composite pipe, including:

[0035] A collection unit for collecting the geometric dimension data and material data of the steel composite pipe to obtain the basic data;

[0036] A calculation unit for performing preliminary calculation of performance indexes on the basic data to obtain preliminary performance indexes;

[0037] A simulation unit, configured to perform multi-parameter simulation analysis processing on the preliminary performance indicators based on a finite element analysis algorithm, and obtain performance indicator simulation data of the steel composite pipe under different parameter combinations;

[0038] A testing unit, configured to obtain the ultimate performance indicators of the steel composite pipe under the influence of key parameters based on the performance indicator simulation data.

[0039] The present invention also provides a computer device, including a memory and a processor, where a computer program is stored in the memory, and when the processor executes the computer program, the steps of the method described in any one of the above are implemented.

[0040] The present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in any one of the above are implemented.

[0041] The performance testing method, device, and equipment for the steel composite pipe provided by the present invention include: collecting geometric dimension data and material data of the steel composite pipe to obtain basic data; performing preliminary calculation of performance indicators on the basic data to obtain preliminary performance indicators; performing multi-parameter simulation analysis processing on the preliminary performance indicators based on a finite element analysis algorithm to obtain performance indicator simulation data of the steel composite pipe under different parameter combinations; and obtaining the ultimate performance indicators of the steel composite pipe under the influence of key parameters based on the performance indicator simulation data. In the present invention, by combining the geometric dimension data and material data of the steel composite pipe for comprehensive calculation and combining the finite element analysis algorithm for multi-parameter simulation analysis, performance indicator simulation data of the steel composite pipe under various parameter combinations are obtained, and then the ultimate performance indicators of the steel composite pipe are tested, overcoming the defect that the performance of the steel composite pipe cannot be accurately evaluated at present. Description of the Drawings

[0042] Figure 1 is a schematic diagram of the steps of the performance testing method for the steel composite pipe in an embodiment of the present invention;

[0043] Figure 2 is a block diagram of the structure of the performance testing device for the steel composite pipe in an embodiment of the present invention;

[0044] Figure 3 is a schematic block diagram of the structure of the computer device in an embodiment of the present invention.

[0045] The implementation, functional features, and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. Detailed Embodiments

[0046] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and 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.

[0047] Referring to Figure 1 , in an embodiment of the present invention, a method for testing the performance of a steel composite pipe is provided, including the following steps:

[0048] Step S1, collecting geometric dimension data and material data of the steel composite pipe to obtain basic data;

[0049] Step S2, performing a preliminary calculation of performance indicators on the basic data to obtain preliminary performance indicators; the preliminary performance indicators include a preliminary ultimate load and preliminary strain data;

[0050] Step S3, performing multi-parameter simulation analysis processing on the preliminary performance indicators based on a finite element analysis algorithm to obtain performance indicator simulation data of the steel composite pipe under different parameter combinations;

[0051] Step S4, obtaining the ultimate performance indicators of the steel composite pipe under the influence of key parameters based on the performance indicator simulation data.

[0052] In this embodiment, as described in the above step S1, professional measuring tools and testing instruments are used to collect data. For geometric dimensions, high-precision measuring instruments can be used to obtain information such as the pipe diameter, length, and wall thickness of the steel composite pipe to ensure the accuracy of the data. In the collection of material data, material analysis equipment is used to determine the material composition and characteristic data of the steel composite pipe. The above geometric dimension data and material data are summarized and sorted to form basic data, providing an original basis for subsequent performance calculations.

[0053] As described in the above step S2, according to the principles of mechanics of materials, a mechanical model of the steel composite pipe can be constructed using the basic data. Through this model, combined with the mechanical property parameters of the material, corresponding calculation methods are used to obtain the preliminary ultimate load. For example, the maximum load that may be borne is calculated considering different stress modes based on the material strength and structural dimensions. At the same time, the preliminary strain data generated during stress is calculated based on data such as the elastic modulus of the material, thereby obtaining preliminary performance indicators and providing a basic reference for further accurate analysis.

[0054] As described in step S3 above, input the preliminary performance indicators into the finite element analysis software, set the preliminary ultimate load as the boundary load condition, and set the preliminary strain data as the initial deformation condition. For the key parameters of the steel composite pipe, such as wall thickness, pipe diameter, material combination, and connection method, etc., set multiple parameter combinations and construct corresponding finite element models. Apply gradually changing virtual loads to the models in the software, and use the iterative calculation function of the finite element analysis algorithm to solve the mechanical responses of the models under different loads, including stress distribution, strain change, and ultimate load data, so as to obtain the performance index simulation data under different parameter combinations and comprehensively understand the performance of the steel composite pipe under various working conditions.

[0055] As described in step S4 above, adopt data mining and analysis techniques. First, extract the parameter characteristics related to the ultimate performance indicators from the performance index simulation data, such as characteristics like wall thickness and pipe diameter. Based on these characteristics, construct a multiple regression analysis model to determine the quantitative relationship expression between the parameter characteristics and the ultimate performance indicators. Use the sensitivity analysis algorithm to calculate the sensitivity coefficients of each parameter characteristic, and thus determine the key parameters. Finally, substitute the key parameters into the quantitative relationship expression to calculate the ultimate performance indicators of the steel composite pipe under the influence of the key parameters, providing a key basis for engineering design and facilitating precise design and optimization.

[0056] In this embodiment, by combining the geometric dimension data and material data of the steel composite pipe for comprehensive calculation, and combining the finite element analysis algorithm for multi-parameter simulation analysis, the performance index simulation data of the steel composite pipe under various parameter combinations are obtained, and then the ultimate performance indicators of the steel composite pipe are tested, overcoming the defect that the performance of the steel composite pipe cannot be accurately evaluated at present.

[0057] In one embodiment, after obtaining the ultimate performance indicators of the steel composite pipe under the influence of the key parameters based on the performance index simulation data, it includes:

[0058] Draw a graph and perform visualization processing on the ultimate performance indicators of the steel composite pipe under the influence of the key parameters to obtain a performance index graph of the steel composite pipe for assisting engineering design analysis.

[0059] In this embodiment, according to the requirements of engineering design analysis, appropriate chart types are selected, such as line charts, bar charts, three-dimensional surface charts, etc. Taking key parameters as coordinate axes, for example, taking the wall thickness of the pipe as the abscissa, the pipe diameter as the ordinate, and the ultimate performance index (such as ultimate load or ultimate strain) as the vertical coordinate to draw a three-dimensional surface chart can intuitively show the change trend of the ultimate performance of the steel composite pipe under different combinations of pipe diameters and wall thicknesses. Or draw a line chart to show the corresponding change law of the ultimate performance index when a certain key parameter (such as the material combination ratio) changes continuously. Through these charts, engineering designers can more clearly and intuitively understand the relationship between the performance of the steel composite pipe and the key parameters, quickly evaluate the influence of different design parameters on the performance of the steel composite pipe, so as to more efficiently optimize parameters and select schemes in the engineering design process, improve the accuracy and efficiency of engineering design, and at the same time facilitate the display and communication of the performance characteristics and design basis of the steel composite pipe in scenarios such as engineering design review and technical communication.

[0060] In one embodiment, perform a preliminary calculation of the performance index on the basic data to obtain a preliminary performance index, including:

[0061] Based on the basic data, construct a structural mechanics model;

[0062] Based on the beam theory algorithm, perform a force analysis on the constructed structural mechanics model and calculate the preliminary ultimate load;

[0063] Based on the elastic modulus and Poisson's ratio data of the material, perform a deformation analysis on the structural mechanics model and calculate the preliminary strain data;

[0064] Integrate the preliminary ultimate load and the preliminary strain data to obtain a preliminary performance index.

[0065] In this embodiment, the above basic data includes the geometric dimension data of the steel composite pipe (such as pipe diameter, pipe length, wall thickness, etc.) and the material data (such as the type of material, elastic modulus, Poisson's ratio, etc.). When using the above data to construct a structural mechanics model, first, according to the actual shape and force characteristics of the steel composite pipe, simplify it into an ideal model suitable for mechanical analysis. For example, for a long and straight steel composite pipe under axial force or transverse force, it can be simplified into a beam model; if the internal pressure of the pipe is considered, a cylindrical shell model can be constructed, etc. During the model construction process, accurately set the geometric parameters of the model to match the size of the actual steel composite pipe, and at the same time define the material properties of each part of the model according to the material data, such as the elastic modulus and Poisson's ratio of different layer materials, so as to establish a structural mechanics model that can reflect the essence of the mechanical behavior of the steel composite pipe and is convenient for subsequent calculation and analysis.

[0066] After the structural mechanics model is constructed, the beam theory algorithm is used for force analysis. Beam theory is a classic theory in material mechanics used to analyze the mechanical response of beam structures under various loads. For the simplified beam model of the steel composite pipe, its force form is first determined, such as the possible concentrated force, distributed force, bending moment, etc. According to the equilibrium equation of the beam (including the balance of force and the balance of moment), the shear force and bending moment distribution in the beam under these loads are analyzed. Then, combined with the mechanical properties of the material, especially the yield strength or ultimate strength of the material, the ultimate load of the beam under different stress conditions is calculated by the relevant formula. For example, in a simple bending beam, according to the moment of inertia of the section, the bending allowable stress of the material, and the span of the beam, the bending normal stress formula is used to calculate the maximum bending moment that the beam can withstand when it is bent, and then the corresponding ultimate load is obtained. For the case of axial force, the ultimate axial force is calculated based on the axial tensile or compressive strength of the material and the cross-sectional area. Through these calculations based on beam theory, the ultimate load of the steel composite pipe under the simplified model is preliminarily determined, which provides an important basis for evaluating its bearing capacity.

[0067] The elastic modulus and Poisson's ratio of materials are key parameters for describing the elastic deformation characteristics of materials. When performing deformation analysis on structural mechanics models, according to Hooke's law, within the elastic range, stress is proportional to strain, and the proportionality coefficient is the elastic modulus. For the steel composite pipe model, when subjected to external force, the stress distribution (such as axial stress, bending stress, etc.) of each point in the model is calculated according to the determined force conditions, and then the corresponding strain is calculated using the elastic modulus. For example, in axial tension or compression, the axial strain is equal to the axial stress divided by the elastic modulus. At the same time, considering the Poisson effect of the material, that is, the relationship between the lateral strain and the axial strain is determined by the Poisson's ratio. When the steel composite pipe is strained in one direction, a corresponding strain will also be generated in the vertical direction, and this lateral strain is calculated by the Poisson's ratio. By calculating the strain of the model in different force directions and positions, the preliminary strain data of the steel composite pipe are obtained. The above data reflects the deformation of the steel composite pipe when subjected to force, which is indispensable for a comprehensive understanding of its mechanical properties.

[0068] The preliminary ultimate load reflects the maximum load that the steel composite pipe can withstand under specific stress conditions, while the preliminary strain data shows the degree of deformation during the stress process. Integrating these two data to form preliminary performance indicators can make a preliminary performance evaluation of the steel composite pipe from the two aspects of load-bearing capacity and deformation characteristics.

[0069] In one embodiment, the preliminary performance index is subjected to multi-parameter simulation analysis based on a finite element analysis algorithm to obtain performance index simulation data of the steel composite pipe under different parameter combinations, including:

[0070] Input the preliminary performance indicators into finite element analysis software, using the preliminary ultimate load as the boundary load condition and the preliminary strain data as the initial deformation condition;

[0071] Set multiple parameter combinations for the wall thickness, pipe diameter, material combination of the inner and outer pipes, and connection method of the steel composite pipe, and construct a finite element model of the steel composite pipe corresponding to each parameter combination in the finite element analysis software;

[0072] Apply a gradually increasing virtual load to the steel composite pipe in the finite element model to simulate the mechanical response process of the steel composite pipe at different load levels;

[0073] Use the iterative calculation module in the finite element analysis algorithm to solve the finite element model, and obtain the stress distribution data, strain change data, and corresponding ultimate load data of the steel composite pipe at different load stages for each parameter combination;

[0074] Integrate the stress distribution data, strain change data, and ultimate load data for each parameter combination to obtain the performance index simulation data of the steel composite pipe under different parameter combinations.

[0075] In this embodiment, after calculating the preliminary performance indicators (including the preliminary ultimate load and preliminary strain data) of the steel composite pipe, the above data is input into the finite element analysis software. The finite element analysis software is an engineering analysis tool that can accurately simulate and analyze various engineering structures based on complex mathematical models and algorithms.

[0076] Taking the preliminary ultimate load as the boundary load condition means that in the subsequent finite element model simulation process, this ultimate load will be used as an important reference value or limiting condition for the load borne by the steel composite pipe. For example, when simulating the maximum stress situation that the steel composite pipe may encounter in actual use, this preliminary ultimate load defines the upper limit range of the load, making the simulation more realistic and targeted, and helping to accurately evaluate the performance of the steel composite pipe under near-limit load-bearing conditions.

[0077] Taking the preliminary strain data as the initial deformation condition is because in actual engineering scenarios, the steel composite pipe may already have a certain initial deformation before bearing the load, such as minor deformations caused by manufacturing processes, installation procedures, or previous use. By setting such initial deformation conditions, the finite element model can more realistically reflect the initial state of the steel composite pipe, and thus more accurately calculate its mechanical response during the subsequent simulation loading process, making the simulation results more in line with the actual situation.

[0078] In this embodiment, it is clear that key parameters such as the wall thickness, pipe diameter, material combination of the inner pipe and the outer pipe, and connection method of the steel composite pipe have an important impact on its performance. For the above parameters, multiple different parameter combinations are set according to the actual engineering requirements and possible situations. For example, for the wall thickness, different thickness values such as 3 mm, 5 mm, 8 mm, etc. can be set; for the pipe diameter, a series of different diameter values are also selected; for the material combination, the matching of different steels with other materials (such as plastics, ceramics, etc.) is considered; for the connection method, there are various forms such as welding and threaded connection. Through such diversified parameter combination settings, the influence of different parameter values on the performance of the steel composite pipe can be comprehensively studied.

[0079] In the finite element analysis software, a finite element model of the steel composite pipe corresponding to each set of parameter combinations is constructed. The finite element model is a mathematical abstraction and digital representation of the actual steel composite pipe structure. It can accurately simulate the geometric shape, material properties, and connection relationships between various parts of the steel composite pipe. During the construction process, the software will accurately set the geometric dimensions (such as pipe diameter, wall thickness, etc.), material properties (determine the elastic modulus, Poisson's ratio, etc. of the material according to the material combination), and connection method (such as simulating the connection strength of welding) of the model according to the input parameters, so as to create finite element models that can truly reflect the actual situation of the steel composite pipe under different parameter combinations.

[0080] Based on the constructed finite element model, a gradually increasing virtual load is applied to the steel composite pipe through the finite element analysis software. The above gradually increasing method is to simulate the entire process of the steel composite pipe from the unloaded state to gradually bearing different levels of loads until it may reach the ultimate load during actual use. The virtual load can simulate various actual load types, such as axial tension, pressure, bending moment, torque, etc. By reasonably setting parameters such as the magnitude, direction, and action point of the load, the stress conditions faced by the steel composite pipe under different working conditions can be accurately simulated.

[0081] As the virtual load is gradually applied, the finite element model will simulate the mechanical response process of the steel composite pipe under different load levels according to its built-in mechanical principles and algorithms. It includes the change of stress distribution inside the steel composite pipe, the generation and development of strain, and possible deformation situations, etc. For example, when applying axial tension, the model will calculate the stress distribution along the axial direction inside the steel composite pipe at different tension values, as well as the corresponding axial strain and possible axial elongation deformation, etc., so as to comprehensively simulate the actual mechanical behavior of the steel composite pipe under different load levels.

[0082] The iterative calculation module in the finite element analysis algorithm is the key part to achieve accurate solution of the finite element model. It is based on complex mathematical methods, such as numerical solutions (such as Newton iteration method, etc.) to solve a series of complex equations such as mechanical equilibrium equations and constitutive equations involved in the finite element model. By continuously performing iterative calculations, the real solution is gradually approached, so as to obtain the exact solution of the finite element model under given conditions (such as specific parameter combinations, virtual loads, etc.). By solving the finite element model using the above-mentioned iterative calculation module, the stress distribution data, strain change data and corresponding limit load data of the steel composite pipe at different load stages under each set of parameter combinations can be obtained. The stress distribution data reflects the stress conditions of various parts of the steel composite under different loads, which can be intuitively displayed in the finite element software through color mapping and other methods; the strain change data shows the deformation degree changes of various parts of the steel composite pipe under different loads; and the corresponding limit load data is the maximum load value that the steel composite pipe can withstand under a specific parameter combination. These data are crucial for a comprehensive understanding of the performance of the steel composite pipe under different parameter combinations.

[0083] After obtaining the stress distribution data, strain change data and ultimate load data of the steel composite pipe at different load stages under each parameter combination, these data need to be integrated and processed. The data of each stage under the same parameter combination are summarized and sorted, and repeated and redundant information is removed to form a complete data set that can fully reflect the performance of the steel composite pipe under this parameter combination. Finally, the performance index simulation data of the steel composite pipe under different parameter combinations are obtained. The above simulation data contains information on the stress distribution, strain change and ultimate load of the steel composite pipe under different parameter combinations, which can fully and accurately reflect the performance of the steel composite pipe under different parameter settings.

[0084] In one embodiment, based on the performance index simulation data, the limit performance index of the steel composite pipe under the influence of key parameters is obtained, including:

[0085] Extracting parameter characteristics related to the ultimate performance index of the steel composite pipe from the performance index simulation data based on a data mining algorithm; the parameter characteristics include pipe wall thickness characteristics, pipe diameter characteristics, material combination characteristics and connection method characteristics;

[0086] A multivariate regression analysis model is constructed based on the parameter characteristics, with each parameter characteristic as an independent variable and the ultimate load and strain as dependent variables, and a quantitative relationship expression between each parameter characteristic and the ultimate performance index is determined through regression analysis;

[0087] Analyze the quantitative relationship expression based on the sensitivity analysis algorithm, calculate the sensitivity coefficient of each parameter feature, sort the parameter features according to the size of the sensitivity coefficient, and determine the key parameters;

[0088] Substitute the key parameters into the quantitative relationship expression to calculate the ultimate performance index of the steel composite pipe under the influence of the key parameters.

[0089] In this embodiment, the data mining algorithm can automatically identify and extract valuable information patterns from a large amount of performance index simulation data. In this embodiment, parameter characteristics closely related to the ultimate performance index of the steel composite pipe are found from the performance index simulation data obtained from the previous finite element analysis. These algorithms are usually based on multidisciplinary knowledge such as statistics and machine learning, such as technical means like cluster analysis and association rule mining. By analyzing a large number of data points, the internal connections and potential laws between the data are discovered, so as to screen out the factors that have a significant impact on the ultimate performance index and abstract them into quantifiable parameter characteristics.

[0090] For the steel composite pipe, focus on the wall thickness characteristics, pipe diameter characteristics, material combination characteristics, and connection method characteristics. The wall thickness characteristics are not only simple thickness values, but may also include the variation law of the thickness at different parts of the pipe body, the proportional relationship between the thickness and other dimensions of the pipe body, etc.; the pipe diameter characteristics involve aspects such as the outer diameter, inner diameter, and uniformity of the pipe diameter; the material combination characteristics cover information such as the types of the inner pipe and outer pipe materials, their respective physical and chemical properties, and the synergistic effects generated by their mutual combination; the connection method characteristics describe the connection form (such as welding method, connection strength, etc.) of the connection part between the inner pipe and the outer pipe and the distribution of the connection part in the overall pipe body structure, etc. These parameter characteristics can comprehensively reflect the influence of the structure and material properties of the steel composite pipe on its ultimate performance.

[0091] The multiple regression analysis model is a statistical model used to establish the mathematical relationship between multiple independent variables and the dependent variable. In this solution, the extracted wall thickness characteristics, pipe diameter characteristics, material combination characteristics, and connection method characteristics are used as independent variables, while the ultimate load and strain are used as dependent variables to construct the model. The construction of this model is based on a large amount of performance index simulation data. Through the fitting analysis of these data, an attempt is made to find a mathematical function form that can best describe the relationship between the independent variables and the dependent variable. For example, a linear regression model (if the data shows an approximate linear relationship) or a non-linear regression model (such as polynomial regression, exponential regression, etc., if the data relationship is more complex) may be adopted.

[0092] After constructing the model framework, the specific quantitative relationship expressions between each parameter feature and the ultimate performance index are determined through regression analysis techniques. During the regression analysis process, according to the characteristics of the data and the requirements of the model, optimization algorithms such as the least squares method are used to estimate the parameter values in the model, minimizing the error between the model prediction values and the actual performance index simulation data. The finally obtained quantitative relationship expressions can clearly show the degree and manner of the influence of each parameter feature on the ultimate load and strain in the form of mathematical formulas. For example, specific functional relationships between the ultimate load and parameters such as the wall thickness of the pipe, pipe diameter, and material elastic modulus may be obtained, as well as similar expressions for strain and the above parameters. These expressions provide an accurate mathematical basis for deeply understanding the internal relationship between the performance and parameters of the steel composite pipe.

[0093] The sensitivity analysis algorithm is used to evaluate the degree of influence of small changes in each independent variable (i.e., parameter feature) on the change of the dependent variable (ultimate performance index) in a multivariable system (such as the regression model constructed above). Common sensitivity analysis methods include local sensitivity analysis and global sensitivity analysis. Local sensitivity analysis mainly focuses on the influence of parameter changes on the result near a specific parameter point; global sensitivity analysis considers the influence situation within the entire parameter value range. In this solution, by inputting the quantitative relationship expression into the sensitivity analysis algorithm, the sensitivity coefficient of each parameter feature is calculated.

[0094] The larger the sensitivity coefficient, the greater the change in the ultimate performance index caused by a small change in this parameter feature, which means that this parameter has a more critical influence on the ultimate performance of the steel composite pipe. The parameter features are sorted according to the magnitude of the calculated sensitivity coefficients, and the parameters ranked at the top are the key parameters. For example, if the sensitivity coefficient of the wall thickness feature is much larger than other parameter features, then the wall thickness is a key parameter affecting the ultimate performance of the steel composite pipe. Determining the key parameters helps to focus on these factors with the most significant influence on performance during the engineering design and optimization process, thereby improving the design efficiency and accuracy, and also providing a clear direction for further research on the performance of the steel composite pipe.

[0095] After determining the key parameters, substituting the values of the above key parameters into the quantitative relationship expression obtained through regression analysis before, the ultimate performance index of the steel composite pipe under the influence of the key parameters can be calculated. The significance of this step is that, based on the clear key parameters, it can quickly and accurately predict the ultimate performance of the steel composite pipe under specific key parameter values. For example, if the key parameters of a certain steel composite pipe are known, by substituting them into the corresponding quantitative relationship expression, the ultimate load and ultimate strain of the steel composite pipe can be directly calculated, providing a convenient and reliable performance evaluation tool for engineering designers, which helps in the selection and design optimization of steel composite pipes according to specific requirements in practical engineering applications.

[0096] In one embodiment, geometric dimension data and material data of the steel composite pipe are collected to obtain basic data, including:

[0097] A three-dimensional laser scanning device is used to perform non-contact scanning on the outer contour of the steel composite pipe to obtain its surface point cloud data. The pipe diameter, length, and wall thickness of the steel composite pipe are extracted through a point cloud data processing algorithm as geometric dimension data;

[0098] The surface atoms of the steel composite pipe are excited by X-rays emitted by an X-ray fluorescence spectrometer, and the characteristic fluorescence spectra emitted are received and analyzed to determine the types and contents of various elements constituting the steel composite pipe, thereby determining its material data.

[0099] In this embodiment, the above three-dimensional laser scanning device is an advanced measurement tool. It obtains the three-dimensional information of the object surface by emitting laser beams onto the surface of the steel composite pipe and receiving the reflected laser signals. The laser beams emitted form dense points on the object surface, and the set of these points constitutes the surface point cloud data.

[0100] The above non-contact scanning method has many advantages. First, it will not cause any physical damage to the surface of the steel composite pipe, which is particularly important for some steel composite pipes that have been installed at the engineering site or whose surfaces need to be kept intact. Second, it can quickly and efficiently obtain a large amount of surface point data, covering the entire outer contour of the steel composite pipe. Compared with traditional manual measurement tools (such as calipers, tape measures, etc.), it can more comprehensively and accurately reflect the actual shape and size characteristics of the steel composite pipe.

[0101] During the scanning process, the laser beam moves on the surface of the steel composite pipe according to a certain scanning path and frequency, continuously emitting and receiving laser signals. As the scanning progresses, the device records the coordinate positions and reflection intensities of each laser point in three-dimensional space and other information. These information are summarized to form rich surface point cloud data. These data points are densely distributed on the surface of the steel composite pipe, describing the appearance form of the steel composite pipe from different angles and positions.

[0102] The collected surface point cloud data usually contains a large amount of original information, which may have some problems such as noise points (inaccurate data points caused by environmental interference, equipment accuracy, etc.) and the disorder of the data. Therefore, it is necessary to process it through point cloud data processing algorithms. The point cloud data processing algorithm will first perform a filtering and denoising operation, identifying and removing those noise points that significantly deviate from the normal data distribution through a preset mathematical algorithm to improve the quality and accuracy of the data. For example, a statistical filtering algorithm can be used to determine which points are noise points based on the statistical characteristics of the spatial distribution of the data points and remove them. Next, contour fitting based on spatial geometric features is a key step. By analyzing the spatial distribution law of the remaining valid point cloud data, geometric algorithms are used to fit these points into geometric contours that can accurately represent the shape of the steel composite pipe. For example, for the straight part of the steel composite pipe, it may be fitted into the contour of a cylinder; for the curved or special-shaped parts, more complex geometric fitting methods will be adopted according to the actual situation.

[0103] After completing the contour fitting, the geometric dimension data such as the pipe diameter, length, and wall thickness of the steel composite pipe can be accurately calculated based on the fitted geometric contour. For the calculation of the pipe diameter, it can be determined according to the diameter parameter of the fitted cylinder; the length is determined by the range of the point cloud data along the pipe axis direction; the wall thickness can be calculated by analyzing the distance between the inner and outer contours. These extracted geometric dimension data will serve as important basic information for the steel composite pipe and be used for subsequent performance analysis and other operations.

[0104] In this embodiment, the above X-ray fluorescence spectrometer is a professional instrument for analyzing the elemental composition of substances. Its working principle is based on the inner shell electron transition phenomenon of atoms. When the X-rays emitted by the X-ray fluorescence spectrometer irradiate the surface of the steel composite pipe, the inner shell electrons of the atoms on the surface of the steel composite pipe will obtain sufficient energy to undergo a transition, jumping from the inner shell orbit to the outer shell orbit.

[0105] When the above-excited electrons return to the inner shell orbit at a later time, they will release the excess energy in the form of emitting characteristic fluorescence spectra. The fluorescence spectra emitted during the inner shell electron transition and return processes of atoms of different elements have unique characteristics, just like everyone has a unique fingerprint, and these characteristic fluorescence spectra correspond one-to-one with the types of elements.

[0106] After the above-mentioned instrument emits X-rays to excite the atoms on the surface of the steel composite pipe, it will receive the characteristic fluorescence spectrum emitted by the atoms on the surface of the steel composite pipe through a detector. Then, the received spectrum is analyzed using spectral analysis software. During the analysis process, by comparing the received spectral characteristics with the standard spectral characteristics of known elements, the types of various elements that make up the steel composite pipe can be determined. For example, if the received spectral characteristics match the standard spectral characteristics of iron element, then it can be determined that the steel composite pipe contains iron element.

[0107] Meanwhile, by analyzing the spectral intensity, the content of each element can be further determined. Generally speaking, there is a certain quantitative relationship between the content of an element and the spectral intensity. Through a pre-established calibration curve (obtained by measuring standard samples with known content) or by using a quantitative analysis algorithm, the content of each element in the steel composite pipe can be accurately calculated based on the received spectral intensity. After determining the types and contents of various elements that make up the steel composite pipe, the material data of the steel composite pipe is obtained. The above-mentioned material data is crucial for understanding the basic performance characteristics of the steel composite pipe (such as strength, corrosion resistance, etc.) and is an important basis for subsequent performance calculation and analysis.

[0108] Refer to Figure 2 , in another embodiment of the present invention, a performance testing device for a steel composite pipe is further provided, including:

[0109] An acquisition unit, configured to acquire the geometric dimension data and material data of the steel composite pipe to obtain basic data;

[0110] A calculation unit, configured to perform preliminary calculation of performance indicators on the basic data to obtain preliminary performance indicators;

[0111] A simulation unit, configured to perform multi-parameter simulation analysis processing on the preliminary performance indicators based on the finite element analysis algorithm to obtain performance indicator simulation data of the steel composite pipe under different parameter combinations;

[0112] A testing unit, configured to obtain the ultimate performance indicators of the steel composite pipe under the influence of key parameters based on the performance indicator simulation data.

[0113] In this embodiment, for the specific implementation of each unit in the above device embodiment, please refer to that described in the above method embodiment, and details are not described herein again.

[0114] Refer to Figure 3 , in an embodiment of the present invention, a computer device is further provided. The computer device can be a server, and its internal structure can be as Figure 3As shown in the figure. The computer device includes a processor, a memory, a display screen, an input device, a network interface, and a database connected through a system bus. Among them, the processor of the computer design is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. The computer program, when executed by the processor, implements the above method.

[0115] Those skilled in the art can understand that Figure 3 the structure shown in the figure is only a block diagram of some structures related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0116] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0117] In summary, the performance test method, device, and equipment for steel composite pipes provided in the embodiments of the present invention include: collecting geometric dimension data and material data of the steel composite pipe to obtain basic data; performing preliminary calculation of performance indicators on the basic data to obtain preliminary performance indicators; performing multi-parameter simulation analysis on the preliminary performance indicators based on a finite element analysis algorithm to obtain performance indicator simulation data of the steel composite pipe under different parameter combinations; and obtaining the ultimate performance indicators of the steel composite pipe under the influence of key parameters based on the performance indicator simulation data. In the present invention, by combining the geometric dimension data and material data of the steel composite pipe for comprehensive calculation and combining the finite element analysis algorithm for multi-parameter simulation analysis, the performance indicator simulation data of the steel composite pipe under various parameter combinations is obtained, and then the ultimate performance indicators of the steel composite pipe are tested, overcoming the defect that the performance of the steel composite pipe cannot be accurately evaluated at present.

[0118] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium provided by the present invention and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, etc.

[0119] It should be noted that in this document, the terms "include", "comprise", or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, apparatus, article, or method including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, apparatus, article, or method including that element.

[0120] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A performance testing method for a steel composite pipe, characterized in that: The following steps are involved: Collect geometric dimension data and material data of steel composite pipe to obtain basic data; Performing preliminary calculation of performance indicators on the basic data to obtain preliminary performance indicators; Based on the finite element analysis algorithm, a multi-parameter simulation analysis is performed on the preliminary performance index to obtain performance index simulation data of the steel composite pipe under different parameter combinations; Based on the performance index simulation data, the limit performance index of the steel composite pipe under the influence of key parameters is obtained.

2. The performance testing method of the steel composite pipe according to claim 1, characterized in that: The preliminary performance indicators include preliminary ultimate load and preliminary strain data.

3. The performance testing method of the steel composite pipe according to claim 1, characterized in that: After obtaining the limit performance index of the steel composite pipe under the influence of key parameters based on the performance index simulation data, the method includes: The ultimate performance index of the steel composite pipe under the influence of key parameters is plotted and visualized to obtain a steel composite pipe performance index chart for auxiliary engineering design analysis.

4. The performance testing method of the steel composite pipe according to claim 1, characterized in that: The basic data is subjected to preliminary calculation of performance indicators to obtain preliminary performance indicators, including: Based on the basic data, construct a structural mechanics model; Based on the beam theory algorithm, the constructed structural mechanics model is subjected to stress analysis and the preliminary ultimate load is calculated; Perform deformation analysis on the structural mechanics model and calculate preliminary strain data based on the elastic modulus and Poisson's ratio data of the material; The preliminary ultimate load and preliminary strain data are integrated to obtain preliminary performance indicators.

5. The performance testing method of the steel composite pipe according to claim 2, characterized in that: Based on the finite element analysis algorithm, the preliminary performance indicators are subjected to multi-parameter simulation analysis and processing to obtain the performance index simulation data of the steel composite pipe under different parameter combinations, including: Inputting the preliminary performance index into finite element analysis software, using the preliminary limit load as the boundary load condition, and using the preliminary strain data as the initial deformation condition; According to the wall thickness, diameter, material combination of the inner and outer pipes, and connection method of the steel composite pipe, multiple parameter combinations are set, and a finite element model of the steel composite pipe corresponding to each parameter combination is constructed in the finite element analysis software; In the finite element model, a gradually increasing virtual load is applied to the steel composite pipe to simulate the mechanical response process of the steel composite pipe under different load levels; The finite element model is solved using the iterative calculation module in the finite element analysis algorithm to obtain the stress distribution data, strain change data and corresponding ultimate load data of the steel composite pipe at different load stages under each set of parameter combinations; The stress distribution data, strain change data and ultimate load data under each parameter combination are integrated to obtain the performance index simulation data of the steel composite pipe under different parameter combinations.

6. The performance testing method of the steel composite pipe according to claim 1, characterized in that: Based on the performance index simulation data, the limit performance index of the steel composite pipe under the influence of key parameters is obtained, including: Extracting parameter characteristics related to the ultimate performance index of the steel composite pipe from the performance index simulation data based on a data mining algorithm; the parameter characteristics include pipe wall thickness characteristics, pipe diameter characteristics, material combination characteristics and connection method characteristics; A multivariate regression analysis model is constructed based on the parameter characteristics, with each parameter characteristic as an independent variable and the ultimate load and strain as dependent variables, and a quantitative relationship expression between each parameter characteristic and the ultimate performance index is determined through regression analysis; Analyze the quantitative relationship expression based on the sensitivity analysis algorithm, calculate the sensitivity coefficient of each parameter feature, sort the parameter features according to the size of the sensitivity coefficient, and determine the key parameters; The key parameters are substituted into the quantitative relationship expression to calculate the limit performance index of the steel composite pipe under the influence of the key parameters.

7. The performance testing method of the steel composite pipe according to claim 1, characterized in that: Collect the geometric dimension data and material data of the steel composite pipe to obtain basic data, including: The appearance profile of the steel composite pipe is non-contactly scanned by a 3D laser scanning device to obtain its surface point cloud data. The diameter, length, and wall thickness of the steel composite pipe are extracted as geometric dimension data through a point cloud data processing algorithm. The X-ray fluorescence spectrometer emits X-rays to excite the atoms on the surface of the steel composite pipe, receives and analyzes the characteristic fluorescence spectrum emitted, thereby determining the types and contents of the elements constituting the steel composite pipe and determining its material data.

8. A performance testing device for a steel composite pipe, characterized in that: include: The acquisition unit is used to acquire geometric dimension data and material data of the steel composite pipe to obtain basic data; A calculation unit, used to perform preliminary calculation of performance indicators on the basic data to obtain preliminary performance indicators; A simulation unit, used for performing multi-parameter simulation analysis on the preliminary performance index based on a finite element analysis algorithm to obtain performance index simulation data of the steel composite pipe under different parameter combinations; The testing unit is used to obtain the limit performance index of the steel composite pipe under the influence of key parameters based on the performance index simulation data.

9. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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