Appliance bearing capacity determination method and device, computer equipment and storage medium

Abstract

The invention relates to an appliance bearing capacity determination method and device, computer equipment and a storage medium. The method comprises the steps of obtaining rust layer thickness data of a to-be-detected appliance; fusing the thickness data of the rust layer into the initial finite element model of the to-be-detected appliance to obtain a target finite element model of which the thickness data of the rust layer is removed; and according to the target finite element model, determining the bearing capacity of the to-be-tested appliance after corrosion. According to the above scheme, the obtained rust layer thickness data of the to-be-measured appliance is fused into the initial finite element model, so that the obtained target finite element model not only comprises geometric parameters, material attributes, physical constraints and loads of the to-be-measured appliance, but also comprises a connection relationship between internal devices of the to-be-measured appliance; the residual thickness data is obtained by removing the rust layer thickness data after the to-be-tested appliance is rusted, so that the structure data of the to-be-tested appliance after being rusted is more accurate, and the accuracy of mechanical property analysis of the appliance is improved.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a method, device, computer equipment and storage medium for determining the carrying capacity of an appliance. Background Art

[0002] The corrosion of tools will weaken the cross-sectional area of ​​tools, resulting in a decrease in the load-bearing capacity of tools. When tools are subjected to heavy loads or encounter extreme weather conditions, the reduction in cross-sectional area and the decrease in load-bearing capacity caused by corrosion will make tools more susceptible to deformation or damage when subjected to stress. Therefore, the analysis of the mechanical properties of tools after corrosion is crucial for the safe use of tools.

[0003] In traditional technologies, analysis methods for the effect of corrosion on the mechanical properties of equipment usually cannot accurately obtain the structural data of the equipment after corrosion, thereby reducing the accuracy of the analysis of the mechanical properties of the equipment. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment and storage medium for determining the bearing capacity of an instrument to address the above-mentioned technical problems, which can improve the accuracy of the analysis of the mechanical properties of the instrument.

[0005] In a first aspect, the present application provides a method for determining a load-bearing capacity of an appliance, comprising:

[0006] Obtaining rust layer thickness data of the instrument to be tested;

[0007] The rust layer thickness data is integrated into the initial finite element model of the device to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads and connection relationships between internal components of the device to be tested;

[0008] The bearing capacity of the device to be tested after corrosion is determined according to the target finite element model.

[0009] In one embodiment, determining the bearing capacity of the device to be tested after corrosion according to the target finite element model includes:

[0010] Determining the remaining thickness data of the device to be tested according to the target finite element model;

[0011] The bearing capacity of the device to be tested after corrosion is determined based on the corresponding relationship between the candidate thickness data and the candidate bearing capacity, as well as the remaining thickness data.

[0012] In one embodiment, the step of fusing the rust layer thickness data into the initial finite element model of the device to be tested to obtain a target finite element model with the rust layer thickness data removed includes:

[0013] Determining rust layer simulation data of the device to be tested according to the rust layer thickness data of the device to be tested;

[0014] The rust layer simulation data is integrated into the initial finite element model of the device to be tested to obtain a target finite element model with the rust layer thickness data removed.

[0015] In one embodiment, the rust layer thickness data includes rust layer thickness data of each rusted part of the device to be tested;

[0016] The step of determining the rust layer simulation data of the device to be tested according to the rust layer thickness data of the device to be tested comprises:

[0017] acquiring an instrument image of the instrument to be tested;

[0018] Determining various rusted locations in the tool to be tested according to the tool image;

[0019] Obtain pixel position information of each rusted part in the tool image;

[0020] The pixel position information of each rusted part and the corresponding rust layer thickness data are correlated and fitted to obtain the rust layer simulation data of the instrument to be tested.

[0021] In one embodiment, the step of obtaining the rust layer thickness data of the device to be tested includes:

[0022] For each rusted part, a thickness gauge is used to collect rust layer thickness data at multiple collection points of the rusted part at preset distance intervals;

[0023] The rust layer thickness data of the multiple collection points are all used as the rust layer thickness data of the rusted part.

[0024] In one embodiment, the step of obtaining the rust layer thickness data of the device to be tested includes:

[0025] Obtaining rust layer thickness data of the device to be tested under a test environment;

[0026] The product of the rust layer thickness data of the instrument to be tested under the test environment and the conversion coefficient is used as the rust layer thickness data of the instrument to be tested; wherein the conversion coefficient is determined according to the difference between the actual use environment of the instrument to be tested and the test environment.

[0027] In a second aspect, the present application also provides a device for determining the bearing capacity of an appliance, comprising:

[0028] An acquisition module is used to obtain the rust layer thickness data of the instrument to be tested;

[0029] A fusion module, used for fusing the rust layer thickness data into the initial finite element model of the instrument to be tested, to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads of the instrument to be tested, and connection relationships between internal components of the instrument to be tested;

[0030] The determination module is used to determine the bearing capacity of the device to be tested after corrosion according to the target finite element model.

[0031] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0032] Obtaining rust layer thickness data of the instrument to be tested;

[0033] The rust layer thickness data is integrated into the initial finite element model of the device to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads and connection relationships between internal components of the device to be tested;

[0034] The bearing capacity of the device to be tested after corrosion is determined according to the target finite element model.

[0035] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0036] Obtaining rust layer thickness data of the instrument to be tested;

[0037] The rust layer thickness data is integrated into the initial finite element model of the device to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads and connection relationships between internal components of the device to be tested;

[0038] The bearing capacity of the device to be tested after corrosion is determined according to the target finite element model.

[0039] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0040] Obtaining rust layer thickness data of the instrument to be tested;

[0041] The rust layer thickness data is integrated into the initial finite element model of the device to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads and connection relationships between internal components of the device to be tested;

[0042] The bearing capacity of the device to be tested after corrosion is determined according to the target finite element model.

[0043] The above-mentioned method, device, computer equipment and storage medium for determining the bearing capacity of the instrument obtain the rust layer thickness data of the instrument to be tested; and fuse the rust layer thickness data into the initial finite element model of the instrument to be tested to obtain a target finite element model after removing the rust layer thickness data; and then determine the bearing capacity of the instrument to be tested after rusting according to the target finite element model. The above scheme fuses the obtained rust layer thickness data of the instrument to be tested into the initial finite element model, so that the obtained target finite element model includes not only the geometric parameters, material properties, physical constraints, loads and connection relationships between the internal components of the instrument to be tested, but also the remaining thickness data of the instrument to be tested after removing the rust layer thickness data, so that the structural data of the instrument to be tested after rusting is more accurate, thereby improving the accuracy of the analysis of the mechanical properties of the instrument. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 is a flow chart of a method for determining the bearing capacity of an appliance in one embodiment;

[0046] Figure 2 A schematic diagram of a process for determining the bearing capacity of a device to be tested after corrosion in one embodiment;

[0047] Figure 3 A schematic diagram of a process for obtaining a target finite element model in one embodiment;

[0048] Figure 4 A schematic diagram of rust layer simulation data in one embodiment;

[0049] Figure 5 A schematic diagram of a process for determining rust layer simulation data of a device to be tested in one embodiment;

[0050] Figure 6 A schematic diagram of rust layer simulation data in another embodiment;

[0051] Figure 7 is a schematic diagram of an interface of a fitting software in one embodiment;

[0052] Figure 8 A schematic diagram of a process for obtaining rust layer thickness data of a device to be tested in one embodiment;

[0053] Fig. 9 A schematic diagram of a process for obtaining rust layer thickness data of a device to be tested in another embodiment;

[0054] Fig.10 is a flow chart of a method for determining the bearing capacity of an appliance in another embodiment;

[0055] Fig.11 is a structural block diagram of a device for determining the bearing capacity of an appliance in one embodiment;

[0056] Fig.12 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0058] The method for determining the load-bearing capacity of an appliance provided in the embodiment of the present application can be applied to the application scenario of mechanical performance analysis of the appliance after corrosion.

[0059] The method can be executed by a server or by a terminal with a certain computing power. The server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car devices, projection devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc.

[0060] In an exemplary embodiment, Figure 1 As shown, a method for determining the bearing capacity of an appliance is provided, and the method is applied to a server as an example for explanation, and includes the following steps:

[0061] S101, obtaining rust layer thickness data of the instrument to be tested.

[0062] For example, the instrument to be tested may be a device that is prone to rust, such as a metal instrument. In the field of electric power, the instrument to be tested may be a transmission tower or other equipment. Non-contact equipment may be used to collect rust thickness data of the instrument to be tested.

[0063] It should be noted that obtaining the rust layer thickness data of the instrument to be tested can be carried out in two stages, wherein the first stage may be the stage when the instrument is not fully corroded, that is, the stage when the morphology of the rust layer will still change; the second stage may be the stage when the instrument is fully corroded, that is, the stage when the morphology of the rust layer will not change.

[0064] In the first stage, the infrared photothermal thickness measurement method can be used to grid the rust thickness data of the instrument, that is, the surface morphology of the rust layer is gridded, and the infrared photothermal thickness measurement method is used to detect the rust thickness data of the grid points respectively, and the fitting software is used to fit to obtain the three-dimensional morphology of the rust layer; then the rust surface morphology of the instrument can be photographed, and the corresponding relationship between the rust surface morphology and the rust thickness data can be established; and the corresponding rust surface morphology and rust thickness data can be used to train the machine learning model. When obtaining the rust thickness data of the instrument to be tested, the surface morphology image data of the instrument to be tested can be directly obtained, and the surface morphology image data of the instrument to be tested can be input into the trained machine learning model to obtain the rust thickness data of the instrument to be tested.

[0065] In the second stage, the finite element method can be used to model the structure of the entire instrument to be tested and perform meshing; in each rust layer detection cycle, the infrared light thermal thickness measurement method can be used to detect the rust layer thickness data of each model node position to obtain the rust layer thickness data of the instrument to be tested. Then, the rust layer thickness data of the instrument to be tested can be assigned to the finite element model, and the rust layer thickness data can be subtracted from the finite element model to obtain the contour of the instrument to be tested after corrosion.

[0066] S102, integrating the rust layer thickness data into the initial finite element model of the device to be tested, and obtaining a target finite element model with the rust layer thickness data removed.

[0067] The initial finite element model of the device under test includes at least the geometric parameters, material properties, physical constraints, loads, and connection relationships between the internal components of the device under test, etc. For example, the geometric parameters are the geometric shape and size of the device under test, and then the finite element model is created according to the geometric parameters of the device under test through computer-aided design (CAD) software or special finite element pre-processing software.

[0068] Material properties can be the material characteristics of each unit, such as elastic modulus, Poisson's ratio, density, etc. These properties determine the behavior of the unit when subjected to force. The unit is obtained by meshing the finite element model. The density of the mesh and the shape of the unit have a great influence on the accuracy of the analysis results and the calculation efficiency.

[0069] Physical constraints can be physical constraints of the finite element model, such as fixed supports, displacement constraints, etc. Physical constraints restrict the movement of certain parts of the finite element model in specific directions.

[0070] Load can be understood as external force or pressure applied to the finite element model, such as gravity, wind load, temperature load, etc. The load will cause deformation and stress distribution of the finite element model.

[0071] The connection relationship between the internal components of the device under test can be understood as the connection mode and contact conditions between different parts in the finite element model, such as welding, bolt connection, friction contact, etc. In addition, the initial finite element model can also include solution settings, which include solution type (such as static, dynamic, heat conduction, etc.), convergence criteria, iterative methods, etc. These settings determine the accuracy of the analysis and the calculation time.

[0072] Exemplarily, the rust thickness data can be integrated into the initial finite element model of the instrument to be tested, that is, the rust thickness data is removed from the thickness of the instrument to be tested in the finite element model to obtain a target finite element model without the rust thickness data. In this way, the finite element model of the instrument to be tested after rusting without the rust thickness data can be determined.

[0073] S103, determining the bearing capacity of the device to be tested after corrosion according to the target finite element model.

[0074] It should be noted that the bearing capacity of the instrument to be tested is closely related to the thickness and structure of the instrument to be tested. After the instrument to be tested is corroded, the thickness and structure of the instrument to be tested will change, such as thickness reduction or deformation, etc.; accordingly, the bearing capacity of the instrument to be tested will also change, so the remaining thickness and structure of the instrument to be tested after corrosion can be determined based on the rust layer thickness data of the instrument to be tested, and then the bearing capacity of the instrument to be tested after corrosion can be determined based on the remaining thickness and structure of the instrument to be tested after corrosion.

[0075] For example, the target finite element model reflects the residual thickness and structure of the instrument under test under the influence of the rust layer thickness data, and then the bearing capacity of the instrument after rusting can be determined based on the residual thickness and structure of the instrument under test reflected by the target finite element model.

[0076] The above-mentioned method for determining the bearing capacity of the instrument obtains the rust layer thickness data of the instrument to be tested; and fuses the rust layer thickness data into the initial finite element model of the instrument to be tested to obtain a target finite element model after the rust layer thickness data is removed; and then determines the bearing capacity of the instrument to be tested after rusting according to the target finite element model. The above-mentioned scheme fuses the obtained rust layer thickness data of the instrument to be tested into the initial finite element model, so that the obtained target finite element model includes not only the geometric parameters, material properties, physical constraints, loads of the instrument to be tested, and the connection relationship between the internal components of the instrument to be tested, but also includes the remaining thickness data of the instrument to be tested after the rust layer thickness data is removed, so that the structural data of the instrument to be tested after rusting is more accurate, thereby improving the accuracy of the analysis of the mechanical properties of the instrument.

[0077] Exemplarily, a corresponding relationship between the thickness of the device to be tested and the bearing capacity may be pre-established, and then the actual bearing capacity of the device to be tested may be determined according to the actual thickness of the device to be tested.

[0078] See also Figure 2 , Figure 2 A schematic diagram of a process for determining the bearing capacity of a device to be tested after corrosion is provided, which specifically includes the following steps:

[0079] S201, determining the remaining thickness data of the device to be tested according to the target finite element model.

[0080] Exemplarily, the target finite element model is obtained by removing the rust layer thickness data from the initial finite element model, that is, the target finite element model reflects the residual thickness of the device under test after the initial thickness of the device under test changes under the influence of the rust layer thickness data. Based on this, the residual thickness data of the device under test can be determined according to the target finite element model.

[0081] S202, determining the bearing capacity of the device to be tested after corrosion according to the corresponding relationship between the candidate thickness data and the candidate bearing capacity, and the remaining thickness data.

[0082] Exemplarily, the bearing capacity of the apparatus to be tested with different thicknesses can be measured in advance. For example, the bearing capacity of the apparatus to be tested under each thickness data can be obtained, and the bearing capacity of the apparatus to be tested under each thickness data can be determined according to the bearing capacity calculation formula of the apparatus to be tested; and then each thickness data and the corresponding bearing capacity are matched one by one to obtain the corresponding relationship between the candidate thickness data and the candidate bearing capacity.

[0083] Furthermore, the candidate bearing capacity corresponding to the remaining thickness data can be found out from the correspondence between the candidate thickness data and the candidate bearing capacity, and the candidate bearing capacity can be determined as the bearing capacity of the device to be tested after corrosion.

[0084] In the embodiment of the present application, by establishing a corresponding relationship between candidate thickness data and candidate bearing capacities, the bearing capacity corresponding to the remaining thickness data can be quickly queried, thereby improving the efficiency of determining the bearing capacity of the device to be tested after corrosion.

[0085] In some optional implementations, the three-dimensional contour of the rust layer can be determined based on the rust layer thickness data, and the determined three-dimensional contour can be merged with the initial finite element model to facilitate a more intuitive understanding of the thickness data of the rusted instrument under test.

[0086] For example, see Figure 3 , Figure 3 A schematic diagram of a process for obtaining a target finite element model is provided, which specifically includes the following steps:

[0087] S301, determining rust layer simulation data of the instrument to be tested according to rust layer thickness data of the instrument to be tested.

[0088] For example, according to the rust layer thickness data of the instrument to be tested, based on the model of the instrument to be tested, 3D drawing software can be used to construct the rust layer simulation data of the instrument to be tested. For example, a thickness gauge (such as a magnetic thickness gauge, an eddy current thickness gauge, or an ultrasonic thickness gauge) can be used to accurately measure the rust layer of the instrument to be tested, and the rust layer thickness data of each measuring point can be recorded and drawn into a table or chart to construct the rust layer simulation data.

[0089] Furthermore, a 3D model of the instrument to be tested can be constructed using 3D drawing software (such as SolidWorks, AutoCAD, etc.) according to the actual size and shape of the instrument to be tested. The collected rust layer thickness data can be imported into the 3D drawing software and associated with the model of the instrument to be tested. The height or color of the model surface can be adjusted according to the data to reflect the distribution of the rust layer. In the 3D drawing software, simulation tools or plug-ins can also be used to construct a simulation model of the rust layer according to the rust layer thickness data, that is, rust layer simulation data. The rust layer simulation data can accurately reflect the shape, thickness, and distribution of the rust layer.

[0090] For example, see Figure 4 , Figure 4 A schematic diagram of rust layer simulation data is provided. Among them, X Lable represents the position coordinate of the X axis, Y Lable represents the coordinate of the Y axis, and Depth represents the rust layer thickness data, which can be understood as the coordinate of the Z axis. Each collection point is represented by a number, and the value in the bracket after the number represents the thickness data in mm; different colors represent different rust layer depths.

[0091] In the embodiment of the present application, by generating three-dimensional rust layer simulation data, the corrosion condition of the instrument to be tested can be more intuitively reflected.

[0092] S302, integrating the rust layer simulation data into the initial finite element model of the device to be tested, and obtaining a target finite element model with the rust layer thickness data removed.

[0093] Furthermore, the rust layer simulation data obtained through the three-dimensional drawing software can be imported into the initial finite element model, that is, the rust layer simulation data can be integrated into the initial finite element model of the instrument to be tested; for example, the rust layer thickness data can be used as a basis for modifying geometric parameters or material properties. For example, the material properties of the affected area can be adjusted based on experimental data or empirical formulas according to the rust layer thickness data. For example, the rust layer may cause changes in parameters such as the yield strength and elastic modulus of the material. That is, "removing" the rust layer thickness data in the initial finite element model is actually to simulate the state after the rust layer is removed by adjusting the geometric shape and material properties, thereby obtaining the target finite element model with the rust layer thickness data removed.

[0094] In an embodiment of the present application, rust layer simulation data is constructed based on the rust layer thickness data, and then the rust layer simulation data is integrated into the initial finite element model of the instrument to be tested. This can more accurately simulate the state of the instrument to be tested after the rust layer is removed, thereby making the obtained target finite element model more reliable, thereby improving the accuracy of determining the bearing capacity of the instrument to be tested after rusting.

[0095] In some optional implementations, the position information of each rusted part in the instrument to be tested and the corresponding rust layer thickness data can be collected. In this case, the rust layer thickness data includes the rust layer thickness data of each rusted part of the instrument to be tested; then, the position information of each rusted part and the corresponding rust layer thickness data can be fitted to obtain the rust layer simulation data of the instrument to be tested.

[0096] For example, see Figure 5 , Figure 5 A schematic diagram of a process for determining rust layer simulation data of a device to be tested is provided, which specifically includes the following steps:

[0097] S501, obtaining an instrument image of the instrument to be tested.

[0098] For example, the device to be tested may be a device that is prone to rust, such as a metal device. In the field of electric power, the device to be tested may be a transmission tower or other equipment.

[0099] The instrument image of the instrument to be tested is used to reflect the structure, position and other information of the instrument to be tested. Optionally, a high-resolution camera device may be used to obtain the instrument image of the instrument to be tested.

[0100] S502, determining rusted locations in the tool to be tested according to the tool image.

[0101] For example, rusted parts usually appear as reddish brown or black spots, patches or layered structures on the surface, and may also be accompanied by loss of gloss and surface roughness. Feature recognition can be performed on the tool image based on the features of the rusted parts to determine the rusted parts in the tool image.

[0102] S503, obtaining pixel position information of each rusted part in the tool image.

[0103] A coordinate system of the tool image may be established, and pixel position information of each rusted portion in the tool image may be determined based on the coordinate system of the tool image.

[0104] S504, performing correlation fitting on the pixel position information of each rusted part and the corresponding rust layer thickness data to obtain rust layer simulation data of the instrument to be tested.

[0105] Exemplarily, the position of each rusted part in the instrument image of the instrument to be tested can be determined based on the pixel position information of each rusted part; and the thickness of the rust layer in the instrument image of the instrument to be tested can be determined based on the rust layer thickness data; then the pixel position information of each rusted part and the corresponding rust layer thickness data are correlated and fitted to determine the rust layer thickness data at each position in the instrument image of the instrument to be tested, that is, to obtain the rust layer simulation data of the instrument to be tested. Among them, the rust layer simulation data of the instrument to be tested can be two-dimensional data or three-dimensional data, which is used to intuitively reflect the rust condition of the instrument to be tested. For example, the rust layer simulation data can accurately reflect the shape, thickness, distribution and other characteristics of the rust layer.

[0106] For example, the pixel position information of each rusted part can be understood as the position coordinates of each rusted part in the coordinate system of the tool image, and thus the first position coordinates and the second position coordinates of each rusted part in the coordinate system of the tool to be tested can be determined according to the position information of each rusted part. The first position coordinates can be the coordinates corresponding to the X-axis, and the second coordinates can be the position coordinates corresponding to the Y-axis.

[0107] The rust thickness data of each rusted part can be regarded as the rust thickness of each rusted part on the Z axis, and thus the third position coordinate of each rusted part in the coordinate system of the device to be tested can be determined according to the rust thickness data of each rusted part. That is, the third position coordinate can be the position coordinate corresponding to the Z axis.

[0108] Furthermore, the first position coordinate, the second position coordinate, the third position coordinate and the instrument image of the instrument to be tested can be correlated and fitted to obtain the rust layer simulation data of the instrument to be tested. That is, a three-dimensional view including each rusted part in the instrument image and the corresponding rust layer thickness data can be obtained. The obtained three-dimensional rust layer simulation data can be referred to in the above embodiment. Figure 4 .

[0109] Optionally, the rust layer simulation data of the test equipment can also be two-dimensional simulation data, see Figure 6 , Figure 6 Another schematic diagram of rust layer simulation data is provided. The rust layer simulation data may include each collection point of each rusted part in the tool image and the rust layer thickness data of each collection point. In this way, it is also convenient to intuitively understand the rust condition of the tool to be tested.

[0110] For example, a fitting software can be developed in advance. Figure 7 , Figure 7 A schematic diagram of the interface of a fitting software is provided. The interface shows an image stitching function module, a stitching result display module and a thickness measurement result display module. Taking the test instrument as a transmission tower as an example, in the image stitching function module, the user can enter the ultra-high voltage line number (e.g. 12), the tower number (e.g. 34), the geographical location of the tower, the detection time and the detection point, etc.; then select a certain picture under the image directory, that is, select the instrument image of the test instrument for rust layer fitting; and can select the rust layer thickness data under the rust layer thickness data path.

[0111] Furthermore, you can choose whether to crop the image and enter the X-axis and Y-axis coordinates of the acquisition point; then click the "Start Stitching" button, and the generated stitching result can be seen in Figure 6 The generated thickness measurement results can be found in Figure 4 In this way, rust layer simulation data can be generated, which can more intuitively reflect the rust condition of the instrument under test.

[0112] In some optional implementations, in order to more accurately obtain the rust layer thickness data of the instrument to be tested, the rust layer thickness data of multiple collection points at each rusted part may be collected.

[0113] For example, see Figure 8 , Figure 8 A schematic diagram of a process for obtaining rust thickness data of a device to be tested is provided, which specifically includes the following steps:

[0114] S801, for each rusted part, using a thickness gauge to collect rust layer thickness data at multiple collection points of the rusted part at preset distance intervals.

[0115] Exemplarily, the preset distance interval may be set according to the interval at which the instrument image is grid-divided. For example, if the instrument image is grid-divided at an interval of 5 mm, the preset distance interval may be set to 5 mm.

[0116] For each rusted part, a thickness gauge can be used to collect rust thickness data at multiple collection points of the rusted part at preset distance intervals. The thickness gauge can be a laser thermal thickness gauge or an infrared thermal thickness gauge. For example, taking the instrument to be tested as an iron tower, if the rusted part is at a high altitude, the UAV high-stabilization gimbal can be used to drive the thickness gauge to perform multi-point measurement of a single rusted part, and the amount of measurement data can be determined according to the size of the rusted part and the preset distance interval. If the rusted part is at the bottom, a handheld or ground-mounted thickness measuring device can be used to detect the rust thickness data of the rusted part one by one.

[0117] S802, using the rust layer thickness data of the multiple collection points as the rust layer thickness data of the rusted part.

[0118] For example, the rust thickness data of multiple collection points can be used as the rust thickness data of the rusted part. In the process of generating rust layer simulation data, each rusted part can fit the rust thickness data of each collection point, so that the local corrosion situation is more accurate, and the generated rust layer simulation data is more reliable.

[0119] In some optional implementations, in order to more conveniently obtain the rust layer thickness data of the instrument to be tested, a laboratory can be used to simulate the actual use environment of the instrument to be tested, and the rust layer thickness data of the instrument to be tested under the test environment can be converted to the actual use environment. Even if the actual use environment of the instrument to be tested is not reached, the rust layer thickness data of the instrument to be tested can be accurately obtained.

[0120] For example, see Fig. 9 , Fig. 9 Another schematic diagram of a process for obtaining rust thickness data of a device to be tested is provided, which specifically includes the following steps:

[0121] S901, obtaining rust layer thickness data of the instrument to be tested under the test environment.

[0122] For example, taking the transmission tower as an example, in the actual use environment of the transmission tower, the concentration of air pollutants is generally high. The main polluting gases are SO2, NO2, CO and O3. The air pollution index is usually moderate pollution, with a concentration of 11ug / m 3 The concentration of NO2 is 66ug / m 3 , the concentration of CO is 2ug / m 3 , the concentration of O3 is 19ug / m 3 These air pollutants are easily soluble in water and react with water to produce acidic substances such as HNO3 and H2SO3, which directly cause rust to the transmission towers in the area. At the same time, the acidic substances dissolve in water and produce electrochemical reactions with the transmission towers, causing secondary corrosion.

[0123] Based on this, the corrosion test can be carried out in the laboratory on the material with the same material as the transmission tower. For example, taking the material of the transmission tower as Q235 steel, a dry and wet immersion test of a 2 mol / L NaHSO3 solution is carried out. The experimental temperature is 40°C, and the main ions in the experimental solution are Na + , H + 、SO3 2- These ions are common ions detected in the actual use environment of transmission towers.

[0124] In this way, the actual rust thickness data of the instrument under the test environment can be obtained.

[0125] S902, taking the product of the rust layer thickness data of the instrument to be tested under the test environment and the conversion coefficient as the rust layer thickness data of the instrument to be tested.

[0126] For example, the conversion coefficient between the test environment and the actual use environment of the instrument can be determined based on the gas concentration in the actual use environment of the instrument and the ion concentration in the test environment, that is, the difference between the actual use environment of the instrument under test and the test environment.

[0127] Furthermore, the product of the rust layer thickness data of the instrument to be tested under the test environment and the conversion coefficient can be used as the rust layer thickness data of the instrument to be tested.

[0128] In an embodiment of the present application, the rust layer thickness data of the instrument to be tested is determined based on the rust layer thickness data of the instrument to be tested and the conversion coefficient under the test environment. While simplifying the process of obtaining the rust layer thickness data of the instrument to be tested, the accuracy of the rust layer thickness data of the instrument to be tested can also be ensured.

[0129] In some optional implementations, see Fig.10 , Fig.10 A flow chart of another method for determining the bearing capacity of an apparatus is provided, which specifically includes the following steps:

[0130] S1001, obtaining rust layer thickness data of the instrument to be tested under a test environment.

[0131] S1002, taking the product of the rust layer thickness data of the instrument to be tested under the test environment and the conversion coefficient as the rust layer thickness data of the instrument to be tested.

[0132] S1003, determining rust layer simulation data of the instrument to be tested according to the rust layer thickness data of the instrument to be tested.

[0133] S1004, integrating the rust layer simulation data into the initial finite element model of the device to be tested, and obtaining a target finite element model with the rust layer thickness data removed.

[0134] S1005, determining the remaining thickness data of the device to be tested according to the target finite element model.

[0135] S1006, determining the bearing capacity of the device to be tested after corrosion according to the corresponding relationship between the candidate thickness data and the candidate bearing capacity, and the remaining thickness data.

[0136] The specific process of the above S1001 to S1006 can refer to the description of the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0137] Furthermore, the execution order of the above steps is only an exemplary description and is not used to limit the execution steps. Other execution orders of the steps are within the protection scope of the embodiments of the present application.

[0138] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0139] Based on the same inventive concept, the embodiment of the present application also provides a device for determining the bearing capacity of an appliance for implementing the above-mentioned method for determining the bearing capacity of an appliance. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more embodiments of the device for determining the bearing capacity of an appliance provided below can refer to the limitations of the method for determining the bearing capacity of an appliance above, and will not be repeated here.

[0140] In an exemplary embodiment, Fig.11 As shown, a device for determining the bearing capacity of an appliance is provided, comprising:

[0141] An acquisition module 10 is used to acquire the rust layer thickness data of the instrument to be tested;

[0142] A fusion module 20 is used to fuse the rust layer thickness data into the initial finite element model of the instrument to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads and connection relationships between internal components of the instrument to be tested;

[0143] The determination module 30 is used to determine the bearing capacity of the device to be tested after corrosion according to the target finite element model.

[0144] The above-mentioned device for determining the bearing capacity of an instrument obtains the rust layer thickness data of the instrument to be tested; and fuses the rust layer thickness data into the initial finite element model of the instrument to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; and then determines the bearing capacity of the instrument to be tested after corrosion according to the target finite element model. The above-mentioned scheme fuses the obtained rust layer thickness data of the instrument to be tested into the initial finite element model, so that the obtained target finite element model includes not only the geometric parameters, material properties, physical constraints, loads of the instrument to be tested, and the connection relationship between the internal components of the instrument to be tested, but also the remaining thickness data of the instrument to be tested after the rust layer thickness data is removed, so that the structural data of the instrument to be tested after corrosion is more accurate, thereby improving the accuracy of the analysis of the mechanical properties of the instrument.

[0145] In one embodiment, the determination module 30 is specifically configured to:

[0146] According to the target finite element model, the remaining thickness data of the device to be tested is determined; according to the corresponding relationship between the candidate thickness data and the candidate bearing capacity, and the remaining thickness data, the bearing capacity of the device to be tested after rusting is determined.

[0147] In one embodiment, the fusion module 20 specifically includes:

[0148] A determination unit, used to determine rust layer simulation data of the instrument to be tested according to the rust layer thickness data of the instrument to be tested;

[0149] The fusion unit is used to fuse the rust layer simulation data into the initial finite element model of the instrument to be tested, so as to obtain a target finite element model with the rust layer thickness data removed.

[0150] In one embodiment, the rust layer thickness data includes rust layer thickness data of each rusted part of the instrument to be tested; the determination unit is specifically used for:

[0151] Acquire an instrument image of the instrument to be tested; determine each rusted part in the instrument to be tested according to the instrument image; obtain pixel position information of each rusted part in the instrument image; correlate and fit the pixel position information of each rusted part with the corresponding rust layer thickness data to obtain rust layer simulation data of the instrument to be tested.

[0152] In one embodiment, the acquisition module 10 is specifically used for:

[0153] For each rusted part, a thickness gauge is used to collect rust layer thickness data at multiple collection points of the rusted part at preset distance intervals; the rust layer thickness data of the multiple collection points are all used as the rust layer thickness data of the rusted part.

[0154] In one embodiment, the acquisition module 10 is specifically used for:

[0155] Obtain the rust layer thickness data of the instrument under test in the test environment; take the product of the rust layer thickness data of the instrument under test in the test environment and the conversion coefficient as the rust layer thickness data of the instrument under test; wherein the conversion coefficient is determined according to the difference between the actual use environment of the instrument under test and the test environment.

[0156] Each module in the above-mentioned apparatus for determining the bearing capacity of an appliance can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0157] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig.12 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device 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 equipment corrosion data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining the carrying capacity of an equipment is implemented.

[0158] Those skilled in the art will understand that Fig.12 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0159] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0160] Obtaining rust layer thickness data of the instrument to be tested;

[0161] The rust layer thickness data is integrated into the initial finite element model of the instrument to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads and connection relationships between internal components of the instrument to be tested;

[0162] According to the target finite element model, the bearing capacity of the instrument to be tested after rusting is determined.

[0163] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0164] According to the target finite element model, the remaining thickness data of the device to be tested is determined; according to the corresponding relationship between the candidate thickness data and the candidate bearing capacity, and the remaining thickness data, the bearing capacity of the device to be tested after rusting is determined.

[0165] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0166] According to the rust layer thickness data of the instrument to be tested, the rust layer simulation data of the instrument to be tested is determined; the rust layer simulation data is integrated into the initial finite element model of the instrument to be tested to obtain the target finite element model with the rust layer thickness data removed.

[0167] In one embodiment, the rust layer thickness data includes the rust layer thickness data of each rusted part of the instrument to be tested; when the processor executes the computer program, the following steps are also implemented:

[0168] Acquire an instrument image of the instrument to be tested; determine each rusted part in the instrument to be tested according to the instrument image; obtain pixel position information of each rusted part in the instrument image; correlate and fit the pixel position information of each rusted part with the corresponding rust layer thickness data to obtain rust layer simulation data of the instrument to be tested.

[0169] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0170] For each rusted part, a thickness gauge is used to collect rust layer thickness data at multiple collection points of the rusted part at preset distance intervals; the rust layer thickness data of the multiple collection points are all used as the rust layer thickness data of the rusted part.

[0171] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0172] Obtain the rust layer thickness data of the instrument under test in the test environment; take the product of the rust layer thickness data of the instrument under test in the test environment and the conversion coefficient as the rust layer thickness data of the instrument under test; wherein the conversion coefficient is determined according to the difference between the actual use environment of the instrument under test and the test environment.

[0173] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0174] Obtaining rust layer thickness data of the instrument to be tested;

[0175] The rust layer thickness data is integrated into the initial finite element model of the instrument to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads and connection relationships between internal components of the instrument to be tested;

[0176] According to the target finite element model, the bearing capacity of the instrument to be tested after rusting is determined.

[0177] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0178] According to the target finite element model, the remaining thickness data of the device to be tested is determined; according to the corresponding relationship between the candidate thickness data and the candidate bearing capacity, and the remaining thickness data, the bearing capacity of the device to be tested after rusting is determined.

[0179] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0180] According to the rust layer thickness data of the instrument to be tested, the rust layer simulation data of the instrument to be tested is determined; the rust layer simulation data is integrated into the initial finite element model of the instrument to be tested to obtain the target finite element model with the rust layer thickness data removed.

[0181] In one embodiment, the rust layer thickness data includes the rust layer thickness data of each rusted part of the instrument to be tested; when the computer program is executed by the processor, the following steps are also implemented:

[0182] Acquire an instrument image of the instrument to be tested; determine each rusted part in the instrument to be tested according to the instrument image; obtain pixel position information of each rusted part in the instrument image; correlate and fit the pixel position information of each rusted part with the corresponding rust layer thickness data to obtain rust layer simulation data of the instrument to be tested.

[0183] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0184] For each rusted part, a thickness gauge is used to collect rust layer thickness data at multiple collection points of the rusted part at preset distance intervals; the rust layer thickness data of the multiple collection points are all used as the rust layer thickness data of the rusted part.

[0185] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0186] Obtain the rust layer thickness data of the instrument under test in the test environment; take the product of the rust layer thickness data of the instrument under test in the test environment and the conversion coefficient as the rust layer thickness data of the instrument under test; wherein the conversion coefficient is determined according to the difference between the actual use environment of the instrument under test and the test environment.

[0187] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0188] Obtaining rust layer thickness data of the instrument to be tested;

[0189] The rust layer thickness data is integrated into the initial finite element model of the instrument to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads and connection relationships between internal components of the instrument to be tested;

[0190] According to the target finite element model, the bearing capacity of the instrument to be tested after rusting is determined.

[0191] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0192] According to the target finite element model, the remaining thickness data of the device to be tested is determined; according to the corresponding relationship between the candidate thickness data and the candidate bearing capacity, and the remaining thickness data, the bearing capacity of the device to be tested after rusting is determined.

[0193] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0194] According to the rust layer thickness data of the instrument to be tested, the rust layer simulation data of the instrument to be tested is determined; the rust layer simulation data is integrated into the initial finite element model of the instrument to be tested to obtain the target finite element model with the rust layer thickness data removed.

[0195] In one embodiment, the rust layer thickness data includes the rust layer thickness data of each rusted part of the instrument to be tested; when the computer program is executed by the processor, the following steps are also implemented:

[0196] Acquire an instrument image of the instrument to be tested; determine each rusted part in the instrument to be tested according to the instrument image; obtain pixel position information of each rusted part in the instrument image; correlate and fit the pixel position information of each rusted part with the corresponding rust layer thickness data to obtain rust layer simulation data of the instrument to be tested.

[0197] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0198] For each rusted part, a thickness gauge is used to collect rust layer thickness data at multiple collection points of the rusted part at preset distance intervals; the rust layer thickness data of the multiple collection points are all used as the rust layer thickness data of the rusted part.

[0199] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0200] Obtain the rust layer thickness data of the instrument under test in the test environment; take the product of the rust layer thickness data of the instrument under test in the test environment and the conversion coefficient as the rust layer thickness data of the instrument under test; wherein the conversion coefficient is determined according to the difference between the actual use environment of the instrument under test and the test environment.

[0201] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and 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-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0202] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0203] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for determining the bearing capacity of an appliance, characterized in that: The method comprises: Obtaining rust layer thickness data of the instrument to be tested; The rust layer thickness data is integrated into the initial finite element model of the device to be tested, so as to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads and connection relationships between internal components of the device to be tested; The bearing capacity of the device to be tested after corrosion is determined according to the target finite element model.

2. The method according to claim 1, characterized in that: Determining the bearing capacity of the device to be tested after corrosion according to the target finite element model includes: Determining the remaining thickness data of the device to be tested according to the target finite element model; The bearing capacity of the device to be tested after corrosion is determined based on the corresponding relationship between the candidate thickness data and the candidate bearing capacity, as well as the remaining thickness data.

3. The method according to claim 1, characterized in that The step of fusing the rust layer thickness data into the initial finite element model of the device to be tested to obtain a target finite element model without the rust layer thickness data comprises: Determining rust layer simulation data of the device to be tested according to the rust layer thickness data of the device to be tested; The rust layer simulation data is integrated into the initial finite element model of the device to be tested to obtain a target finite element model with the rust layer thickness data removed.

4. The method according to claim 3, characterized in that The rust layer thickness data includes the rust layer thickness data of each rusted part of the device to be tested; The step of determining the rust layer simulation data of the device to be tested according to the rust layer thickness data of the device to be tested comprises: acquiring an instrument image of the instrument to be tested; Determining various rusted locations in the tool to be tested according to the tool image; Obtain pixel position information of each rusted part in the tool image; The pixel position information of each rusted part and the corresponding rust layer thickness data are correlated and fitted to obtain the rust layer simulation data of the instrument to be tested.

5. The method according to claim 4, characterized in that The step of obtaining the rust layer thickness data of the device to be tested comprises: For each rusted part, a thickness gauge is used to collect rust layer thickness data at multiple collection points of the rusted part at preset distance intervals; The rust layer thickness data of the multiple collection points are all used as the rust layer thickness data of the rusted part.

6. The method according to claim 1, characterized in that The step of obtaining the rust layer thickness data of the device to be tested comprises: Obtaining rust layer thickness data of the device to be tested under a test environment; The product of the rust layer thickness data of the instrument to be tested under the test environment and the conversion coefficient is used as the rust layer thickness data of the instrument to be tested; wherein the conversion coefficient is determined according to the difference between the actual use environment of the instrument to be tested and the test environment.

7. A device for determining the bearing capacity of an appliance, characterized in that: The device comprises: An acquisition module is used to obtain the rust layer thickness data of the instrument to be tested; A fusion module, used for fusing the rust layer thickness data into the initial finite element model of the instrument to be tested, to obtain a target finite element model with the rust layer thickness data removed; wherein the initial finite element model at least includes geometric parameters, material properties, physical constraints, loads of the instrument to be tested, and connection relationships between internal components of the instrument to be tested; The determination module is used to determine the bearing capacity of the device to be tested after corrosion according to the target finite element model.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. 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 6 are implemented.

10. A computer program product, comprising a computer program, 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 6 are implemented.

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