Three-dimensional visualization reconstruction method and device for defects of high-temperature pressure-bearing equipment

Abstract

The application relates to a three-dimensional visualization reconstruction method and device for defects of high-temperature pressure-bearing equipment, wherein the method comprises the following steps: obtaining multi-source data of the high-temperature pressure-bearing equipment based on at least two detection combinations of phased array ultrasonic detection, digital ray detection and memory detection; unifying multi-source data coordinate systems by using a space coordinate conversion matrix based on the multi-source data, so as to obtain multi-source data after unification of the coordinate systems; determining a defect boundary of the high-temperature pressure-bearing equipment based on the multi-source data after unification of the coordinate systems, and performing three-dimensional visualization reconstruction on the defect boundary in a preset equipment model, so as to generate a three-dimensional visualization reconstruction result of the defects of the high-temperature pressure-bearing equipment. Therefore, the problems that related technologies cannot intuitively present the real appearance of the defects in the three-dimensional space of the equipment, lack a space coordinate unification mapping mechanism for fusing multi-source detection data, and result in a high error rate of safety evaluation are solved.

Description

Technical Field

[0001] This application relates to the field of non-destructive testing technology for power equipment, and in particular to a three-dimensional visualization reconstruction method and device for defects in high-temperature pressure equipment. Background Technology

[0002] Currently, high-temperature pressure equipment operates under harsh conditions such as high temperature, high pressure, and corrosive media, making it prone to defects such as cracks, lack of fusion, pitting corrosion, and stress corrosion, which seriously threaten equipment safety and stable unit operation. To ensure equipment integrity, the industry widely adopts non-destructive testing technology to identify and assess defects.

[0003] Among related technologies, defects can be detected through methods such as magnetic particle / penetrating electron microscopy, radiographic testing, conventional ultrasound, and phased array ultrasound.

[0004] However, among the related technologies, magnetic particle / penetrating inspection only shows a two-dimensional linear projection of surface cracks; radiographic inspection (RT) shows a two-dimensional superimposed projection of defects on film; conventional ultrasound (UT) relies on A-scan waveform amplitude to assess defect size; and phased array ultrasound (PAUT) can generate B / C / D scan views but is still a two-dimensional slice, which urgently needs improvement. Summary of the Invention

[0005] This application provides a three-dimensional visualization reconstruction method and device for defects in high-temperature pressure equipment, in order to solve the problems that related technologies cannot intuitively present the true shape of defects in the three-dimensional space of the equipment, lack a unified spatial coordinate mapping mechanism that integrates multi-source detection data, and thus lead to high error rates in safety assessment.

[0006] The first aspect of this application provides a three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment, comprising the following steps: acquiring multi-source data of the high-temperature pressure equipment based on at least two detection combinations among phased array ultrasound, digital X-ray, and memory detection; unifying the coordinate system of the multi-source data using a spatial coordinate transformation matrix based on the multi-source data to obtain multi-source data after unification; determining the defect boundary of the high-temperature pressure equipment based on the multi-source data after unification, and performing three-dimensional visualization reconstruction of the defect boundary in a preset equipment model to generate a three-dimensional visualization reconstruction result of the defects in the high-temperature pressure equipment.

[0007] Optionally, in one embodiment of this application, the step of performing three-dimensional visualization reconstruction of the defect boundary in a preset equipment model to generate a three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect includes: reconstructing the point cloud of the defect boundary into a triangular mesh to generate an initial defect triangular mesh model; optimizing the initial defect triangular mesh model to obtain an optimized defect triangular mesh; performing parametric surface reconstruction on the optimized defect triangular mesh to generate a three-dimensional defect model, and embedding the three-dimensional defect model into the preset equipment model to perform three-dimensional visualization reconstruction of the high-temperature pressure equipment defect and generate a three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect.

[0008] Optionally, in one embodiment of this application, the objective function for optimizing the spatial coordinate transformation matrix is:

[0009] in, For rotation matrix, It is a translation vector. For detection data points, For the corresponding point of the equipment model, It is the Euclidean norm.

[0010] Optionally, in one embodiment of this application, the step of unifying the multi-source data coordinate system using a spatial coordinate transformation matrix includes: establishing a spatial coordinate transformation matrix between the body coordinate system of the high-temperature pressure-bearing equipment and the coordinate systems of each testing device; and using the spatial coordinate transformation matrix to map the multi-source data collected by each testing device to the body coordinate system, so as to unify the multi-source data coordinate system.

[0011] Optionally, in one embodiment of this application, after generating the three-dimensional visualization result of the defect in the high-temperature pressure-bearing equipment, the method further includes: based on the three-dimensional visualization result of the defect in the high-temperature pressure-bearing equipment, calculating the stress intensity factor of the defect according to the three-dimensional morphology of the defect, wherein the stress intensity factor includes an open-type stress intensity factor. Sliding type stress intensity factor and tear-type stress intensity factor Integrate the above using a preset formula The above and stated The remaining lifespan of the high-temperature pressure-bearing equipment is predicted; the remaining lifespan of the high-temperature pressure-bearing equipment is classified into risk levels to generate risk assessment data for the high-temperature pressure-bearing equipment.

[0012] Optionally, in one embodiment of this application, the multi-parameter correction model for the remaining lifetime is:

[0013] in, Indicates the crack propagation rate. For material constants, The index is the Paris formula index. This represents the stress intensity factor amplitude. Temperature is a factor that affects the environment. It is an environmental corrosive agent.

[0014] Optionally, in one embodiment of this application, after generating the three-dimensional visualization reconstruction result of the defect of the high-temperature pressure equipment, the method further includes: superimposing the three-dimensional visualization reconstruction result of the defect of the high-temperature pressure equipment onto the real-world image of the equipment to generate a target view; and using the target view to perform a visual evaluation of the defect of the high-temperature pressure equipment to obtain an evaluation report of the high-temperature pressure equipment.

[0015] A second aspect of this application provides a three-dimensional visualization reconstruction device for defects in high-temperature pressure equipment, comprising: an acquisition module for acquiring multi-source data of the high-temperature pressure equipment based on at least two detection combinations among phased array ultrasound, digital X-ray, and memory detection; a unification module for unifying the coordinate system of the multi-source data using a spatial coordinate transformation matrix to obtain multi-source data after unification; and a reconstruction module for determining the defect boundary of the high-temperature pressure equipment based on the multi-source data after unification, and performing three-dimensional visualization reconstruction of the defect boundary in a preset equipment model to generate a three-dimensional visualization reconstruction result of the defects in the high-temperature pressure equipment.

[0016] Optionally, in one embodiment of this application, the reconstruction module includes: a reconstruction unit, configured to reconstruct the point cloud of the defect boundary into a triangular mesh to generate an initial defect triangular mesh model; optimize the initial defect triangular mesh model to obtain an optimized defect triangular mesh; and a reconstruction unit, configured to perform parametric surface reconstruction on the optimized defect triangular mesh to generate a three-dimensional defect model, and embed the three-dimensional defect model into the preset equipment model to perform three-dimensional visualization reconstruction of the high-temperature pressure equipment defect, thereby generating a three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect.

[0017] Optionally, in one embodiment of this application, the objective function for optimizing the spatial coordinate transformation matrix is:

[0018] in, For rotation matrix, It is a translation vector. For detection data points, For the corresponding point of the equipment model, It is the Euclidean norm.

[0019] Optionally, in one embodiment of this application, the unification module includes: an establishment unit, used to establish a spatial coordinate transformation matrix between the body coordinate system of the high-temperature pressure-bearing equipment and the coordinate systems of each detection device; and a unification unit, used to use the spatial coordinate transformation matrix to map the multi-source data collected by each detection device to the body coordinate system, so as to unify the multi-source data coordinate system.

[0020] Optionally, in one embodiment of this application, it further includes: a calculation module, used to calculate the stress intensity factor of the defect based on the three-dimensional visualization results of the defect in the high-temperature pressure equipment and according to the three-dimensional morphology of the defect, wherein the stress intensity factor includes an open-type stress intensity factor. Sliding type stress intensity factor and tear-type stress intensity factor The prediction module is used to integrate the above using a preset formula. The above and stated The system predicts the remaining lifespan of the high-temperature pressure-bearing equipment; the generation module is used to classify the remaining lifespan of the high-temperature pressure-bearing equipment into risk levels to generate risk assessment data for the high-temperature pressure-bearing equipment.

[0021] Optionally, in one embodiment of this application, the multi-parameter correction model for the remaining lifetime is:

[0022] in, Indicates the crack propagation rate. For material constants, The index is the Paris formula index. This represents the stress intensity factor amplitude. Temperature is a factor that affects the environment. It is an environmental corrosive agent.

[0023] Optionally, in one embodiment of this application, it further includes: an overlay module, used to overlay the three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect onto the real-world image of the equipment after generating the three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect to generate a target view; and an evaluation module, used to use the target view to perform a visual evaluation of the defect of the high-temperature pressure equipment to obtain an evaluation report of the high-temperature pressure equipment.

[0024] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment as described in the above embodiments.

[0025] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for three-dimensional visualization reconstruction of defects in high-temperature pressure equipment.

[0026] This application's embodiments can acquire equipment defect data through at least two non-destructive testing methods, establish a three-dimensional digital twin model of the equipment, unify the coordinate system of multi-source data using a spatial coordinate transformation matrix, determine the defect boundary based on an improved edge extraction algorithm, generate a three-dimensional defect model using NURBS (Non-Uniform Rational B-Spline Surface) surface reconstruction technology, and perform three-dimensional visualization rendering in the equipment model, thereby achieving accurate reconstruction of the defect's spatial morphology and safety assessment. This solves the problems of related technologies failing to intuitively present the true morphology of defects in the equipment's three-dimensional space, lacking a unified spatial coordinate mapping mechanism that integrates multi-source detection data, leading to high error rates in safety assessments.

[0027] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0028] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment according to an embodiment of this application. Figure 2 This is a detailed flowchart according to one embodiment of the present application; Figure 3 This is a flowchart illustrating the overall system workflow according to one embodiment of this application; Figure 4 This is a flowchart of a spatial coordinate unification algorithm according to an embodiment of this application; Figure 5 This is a flowchart of a three-dimensional reconstruction algorithm according to an embodiment of this application; Figure 6 This is a flowchart of a security assessment decision-making process according to one embodiment of this application; Figure 7 This is a flowchart illustrating an embodiment of online high-temperature detection according to this application. Figure 8This is a flowchart illustrating the multimodal data fusion verification process according to an embodiment of this application. Figure 9 This is a flowchart illustrating an AR / VR visualization interaction according to an embodiment of this application. Figure 10 This is a flowchart of a reconstruction algorithm according to an embodiment of this application; Figure 11 This is a schematic diagram of the structure of a three-dimensional visualization reconstruction device for defects in high-temperature pressure equipment provided in an embodiment of this application; Figure 12 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0029] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0030] The following describes a method and apparatus for three-dimensional visualization reconstruction of defects in high-temperature pressure equipment according to embodiments of this application, with reference to the accompanying drawings. Addressing the issues mentioned in the background art, such as the inability to intuitively present the true shape of defects in the three-dimensional space of the equipment and the lack of a unified spatial coordinate mapping mechanism integrating multi-source detection data, leading to high error rates in safety assessments, this application provides a method for three-dimensional visualization reconstruction of defects in high-temperature pressure equipment. In this method, equipment defect data is acquired through at least two non-destructive testing methods, a three-dimensional digital twin model of the equipment is established, a spatial coordinate transformation matrix is ​​used to unify the coordinate system of multi-source data, defect boundaries are determined based on an improved edge extraction algorithm, a three-dimensional defect model is generated using NURBS surface reconstruction technology, and three-dimensional visualization rendering is performed on the equipment model, thereby achieving accurate reconstruction of the defect's spatial shape and safety assessment. This solves the problems of related technologies failing to intuitively present the true shape of defects in the three-dimensional space of the equipment and lacking a unified spatial coordinate mapping mechanism integrating multi-source detection data, resulting in high error rates in safety assessments.

[0031] Specifically, Figure 1 This is a flowchart illustrating a three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment provided in an embodiment of this application.

[0032] like Figure 1 As shown, the three-dimensional visualization reconstruction method for defects in this high-temperature pressure equipment includes the following steps: In step S101, multi-source data of the high-temperature pressure equipment is acquired based on at least two of the following detection methods: phased array ultrasound, digital X-ray, and memory detection.

[0033] In this embodiment of the application, the multi-source data of the high-temperature pressure equipment corresponds to the equipment defect data, which can be obtained through at least two non-destructive testing methods.

[0034] In actual implementation, such as Figure 2 As shown, this application embodiment uses two or more combinations of non-destructive testing methods, including phased array ultrasound, digital X-ray, and magnetic memory testing, to acquire multi-source data from high-temperature pressure-bearing equipment, thereby providing support for subsequent data preprocessing and initiating a spatial coordinate unification process. The overall system workflow diagram of this application is shown below. Figure 3 As shown.

[0035] In step S102, based on the multi-source data, the coordinate system of the multi-source data is unified using a spatial coordinate transformation matrix to obtain the multi-source data after the coordinate system is unified.

[0036] In practical implementation, the embodiments of this application can establish a three-dimensional digital twin model of the equipment based on multi-source data, and use a spatial coordinate transformation matrix to unify the coordinate system of the multi-source data to obtain multi-source data with a unified coordinate system, which is beneficial for the accurate extraction of defect edges in the subsequent process. The flowchart of the spatial coordinate unification algorithm is as follows: Figure 4 As shown.

[0037] Optionally, in one embodiment of this application, a spatial coordinate transformation matrix is ​​used to unify the coordinate system of multi-source data, including: establishing a spatial coordinate transformation matrix between the body coordinate system of the high-temperature pressure equipment and the coordinate systems of each testing equipment; and using the spatial coordinate transformation matrix to map the multi-source data collected by each testing equipment to the body coordinate system, so as to unify the multi-source data coordinate system.

[0038] In actual implementation, the embodiments of this application can introduce a multimodal data fusion mechanism to establish a spatial coordinate transformation matrix between the body coordinate system (O-XYZ) of the high-temperature pressure-bearing equipment and the coordinate systems (O'-UVW) of each testing device: X,Y,Z] T = M·[U,V,W] T + T Where M is the rotation matrix and T is the translation vector.

[0039] This application can be used to develop adaptive weighted fusion algorithms: W i = k1·Accuracy i + k2·Resolution Among them, W i For the i-th sample, Accuracy is the overall score. i The accuracy (measure of prediction correctness) for the i-th sample is the Resolution. iLet k1 be the resolution of the i-th sample (a measure of prediction precision), and k2 be weighting coefficients used to balance the impact of accuracy and resolution.

[0040] Furthermore, embodiments of this application can utilize a spatial coordinate transformation matrix to map multi-source data collected by various detection devices to the body coordinate system, thereby unifying the multi-source data coordinate system, eliminating data misalignment caused by coordinate system differences between different detection methods, and achieving accurate alignment and association of multimodal data in the global space of the device.

[0041] In one embodiment of this application, the coordinate transformation matrix is ​​dynamically optimized using the Iterative Closest Point (ICP) algorithm, and the objective function for optimizing the spatial coordinate transformation matrix is:

[0042] in, For rotation matrix, It is a translation vector. For detection data points, For the corresponding points of the equipment model, It is the Euclidean norm.

[0043] Table 1 is the parameter definition table, as shown in Table 1: Table 1

[0044] In step S103, based on the multi-source data after unifying the coordinate system, the defect boundary of the high-temperature pressure equipment is determined, and the defect boundary is reconstructed in three dimensions in the preset equipment model to generate the three-dimensional visualization reconstruction result of the defect of the high-temperature pressure equipment.

[0045] In this embodiment, based on multi-source data in a unified coordinate system, the defect boundary of the high-temperature pressure-bearing equipment is determined using an improved edge extraction algorithm. A three-dimensional defect model is generated using NURBS surface reconstruction technology. Based on the three-dimensional defect model, the defect boundary is reconstructed or rendered in a preset equipment model to generate a three-dimensional visualization reconstruction result of the high-temperature pressure-bearing equipment defect. The flowchart of the three-dimensional reconstruction algorithm is shown below. Figure 5 As shown.

[0046] In extracting defect edges, this application uses wavelet packet transform (WPT) for noise reduction and an improved Canny operator for edge detection to obtain ultrasonic signals, and applies the U-Net deep learning segmentation network to detect ray images (the training dataset contains 100,000+ industrial defect samples).

[0047] Edge extraction employs an adaptive threshold segmentation algorithm, with the threshold calculated as follows: T = μ + k·σ Where μ is the image mean, σ is the standard deviation, and k is the defect type correlation factor.

[0048] Optionally, in one embodiment of this application, the defect boundary is reconstructed in three dimensions using a preset equipment model to generate a three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect. This includes: reconstructing the point cloud of the defect boundary into a triangular mesh to generate an initial defect triangular mesh model; optimizing the initial defect triangular mesh model to obtain an optimized defect triangular mesh; reconstructing the optimized defect triangular mesh into a parametric surface to generate a three-dimensional defect model; and embedding the three-dimensional defect model into the preset equipment model to perform a three-dimensional visualization reconstruction of the high-temperature pressure equipment defect and generate a three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect.

[0049] In this application, during triangular mesh reconstruction, algorithms such as Delaunay triangulation and Poisson reconstruction can be used to reconstruct the point cloud of the defect boundary into a triangular mesh, generating an initial defect triangular mesh model to generate a continuous triangular mesh surface from the discrete point cloud. During mesh optimization, the initial defect triangular mesh model can be optimized using methods such as Laplacian smoothing, mesh simplification, and mesh repair to obtain an optimized defect triangular mesh, thereby improving mesh quality and laying the foundation for subsequent processing. In parametric surface reconstruction, this application can perform surface reconstruction based on NURBS (Non-Uniform Rational B-Splines) surface fitting technology. The optimized triangular mesh is parameterized, and then the parameterized data is used to generate a smooth and continuous surface model through NURBS fitting. In other words, this application performs parametric surface reconstruction on the optimized defect triangular mesh to generate a three-dimensional defect model, which is then embedded into a preset equipment model to perform three-dimensional visualization reconstruction of the high-temperature pressure equipment defect, generating a three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect.

[0050] Optionally, in one embodiment of this application, after generating the three-dimensional visualization result of the high-temperature pressure-bearing equipment defect, the method further includes: based on the three-dimensional visualization result of the high-temperature pressure-bearing equipment defect, calculating the stress intensity factor of the defect according to the three-dimensional morphology of the defect, wherein the stress intensity factor includes the open-type stress intensity factor. Sliding type stress intensity factor and tear-type stress intensity factor Integration using preset formulas , and To predict the remaining lifespan of high-temperature pressure equipment; to classify the remaining lifespan of high-temperature pressure equipment into risk levels to generate risk assessment data for high-temperature pressure equipment.

[0051] Specifically, embodiments of this application can perform stress intensity factor calculation based on the three-dimensional morphology of the defect. , , The embodiments of this application can perform remaining lifetime prediction based on Paris formula integration. , , This allows for the prediction of the remaining lifespan of high-temperature pressure equipment. The embodiments of this application can perform risk assessments, classifying risks according to the API 579 standard to generate risk assessment data for high-temperature pressure equipment.

[0052] This application can integrate ASME B31G / API 579 standards for residual strength assessment and combine the Paris formula to predict crack propagation life: da / dN = C(ΔK) m Where ΔK is calculated using the three-dimensional stress intensity factor, da / dN is the crack propagation rate, representing the increment of crack length per load cycle, in meters per cycle; ΔK is the stress intensity factor amplitude, ΔK = K max -K min Unit: MPa / m; C and m are material constants, determined experimentally, reflecting the material's sensitivity to fatigue crack propagation.

[0053] In one embodiment of this application, the multi-parameter correction model for the remaining lifetime is as follows:

[0054] in, Indicates the crack propagation rate. For material constants, The index is the Paris formula index. This represents the stress intensity factor amplitude. Temperature is a factor that affects the environment. It is an environmental corrosive agent.

[0055] Table 2 shows the parameter definitions for the multi-parameter correction model. Table 2

[0056] Where f(T) is the temperature influence factor and g(Environment) is the environmental corrosion factor.

[0057] Optionally, in one embodiment of this application, after generating the three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect, the method further includes: superimposing the three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect onto the real-world image of the equipment to generate a target view; and using the target view to perform a visual evaluation of the high-temperature pressure equipment defect to obtain an evaluation report of the high-temperature pressure equipment.

[0058] The security assessment decision-making flowchart of this application is as follows: Figure 6 As shown, the application is applicable to the inspection of high-temperature pipelines in thermal power units and to the inspection of heat transfer tubes in nuclear power steam generators. The flowchart for the implementation of high-temperature online inspection is as follows. Figure 7 As shown, the multimodal data fusion verification flowchart is as follows. Figure 8 As shown.

[0059] In actual implementation, the AR / VR visual interaction flowchart is as follows: Figure 9 As shown, the embodiments of this application can use the AR glasses display module to overlay the three-dimensional model of the defect onto the real equipment image to generate a target view, and use the interactive sectioning module to support arbitrary plane sectioning to observe internal defects, and use the target view to perform a visual evaluation of the defects of the high-temperature pressure equipment to obtain an evaluation report of the high-temperature pressure equipment.

[0060] Specifically, the working principle of the three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment in this application is explained in detail with specific embodiments.

[0061] Example 1: Inspection of circumferential welds in main steam pipelines of power plants (1) Data acquisition: PAUT: 64-element probe (5MHz) with scanning step of 0.5mm; DR (digital radiography): double-wall double-image radiography with a focal length of 700mm. The object of inspection is a P91 steel φ508×50mm pipe.

[0062] (2) Data processing flow The system includes a coordinate unification module, laser scanning to acquire pipeline point clouds, establishing a global coordinate system, calculating transformation matrices, and data mapping.

[0063] (3) Three-dimensional reconstruction results: The unfused defect with a depth of 7.2 mm was successfully reconstructed (the traditional UT evaluation error is ±2 mm); the spatial orientation of the crack in the weld fusion zone was visualized (inclination angle 63°).

[0064] Example 2: Corrosion Detection of Boiler Water-Cooled Wall Tubes (1) Test object and environment: Equipment: TP347H stainless steel water-cooled wall tube of supercritical boiler (φ42×6.5mm); Service conditions: temperature 605℃ / pressure 28.5MPa, operation for 110,000 hours; Failure mode: pitting corrosion caused by high temperature sulfur corrosion (typical new energy biomass co-firing condition).

[0065] (2) Multimodal data acquisition, as shown in Table 3: Table 3

[0066] It should be noted that EMAT uses non-contact testing to solve the problem of online testing of high-temperature wall pipes (>200℃).

[0067] (3) Key steps in data processing 1. Unified spatial coordinates: Establish a global coordinate system: with the pipe end flange sealing surface as the reference plane (Z=0); Calculation of coordinate transformation matrix: Laser point cloud and EMAT data registration; Registration error: RMS≤0.15mm.

[0068] 2. Intelligent extraction of defect edges Surface corrosion profile: Image processing for penetration testing; Depth direction extraction: Employing the EMAT echo envelope integration method. Depth = (t_echo × V_sound) / 2 - k·σ_corr Where k is the material attenuation compensation coefficient, and k=0.33 is taken for TP347H.

[0069] (4) 3D reconstruction and visualization Point cloud fusion: Surface contour points: 11,850 (penetration detection + laser scanning); Depth point cloud: 8,240 (EMATC scan data).

[0070] The reconstruction algorithm flow includes: point cloud denoising, Poisson surface reconstruction, erosion pit region segmentation, local B-spline surface fitting, and adaptive mesh refinement. The reconstruction algorithm flowchart is shown below. Figure 10 As shown.

[0071] The reconstruction results are shown in Table 4: Table 4

[0072] (5) Safety assessment implementation 1. Residual strength analysis: Assessment based on API 579-1 / ASME FFS-1 Level 2: Ultimate load calculation, residual strength ratio RSF=0.92 (critical value 0.9).

[0073] 2. Corrosion propagation prediction Coupled high-temperature electrochemical model:

[0074] The parameter definition table is shown in Table 5: Table 5

[0075] Parameter calibration: A = 2.7 × 10 -4 mg / (mm²·h), Q=85 kJ / mol.

[0076] Predicted lifespan: 8,200 hours for depths up to 3mm (requires replacement within 6,000 hours). (6) Visual output AR display interface: 1. 3D model of erosion pits superimposed on the real pipe (implemented by HoloLens 2); 2. Risk level color coding: red (depth > 2mm): 3 locations; yellow (1-2mm): 17 locations.

[0077] Engineering Decision Support: Application Case: After application to a 350MW CFB boiler, unplanned downtime caused by corrosion-induced tube rupture was avoided (saving approximately ¥3.8 million in losses per instance).

[0078] This application features small corrosion depth measurement error, shorter assessment time, and high accuracy in remaining life prediction. It addresses unique challenges in the new energy sector: corrosion from molten alkali metal salts generated by biomass co-firing is easier to quantify and assess, and for the first time achieves high-temperature online detection and 3D reconstruction. This application utilizes penetrant testing with 2D contours and EMAT depth data to ensure accurate corrosion volume calculation (error <10%), more accurate corrosion propagation rate prediction, smaller defect size errors, higher assessment efficiency, and a lower missed detection rate. This prevents unplanned shutdowns of a 1000MW unit and extends equipment service life by more than 30%.

[0079] The three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment proposed in this application acquires equipment defect data through at least two non-destructive testing methods, establishes a three-dimensional digital twin model of the equipment, unifies the coordinate system of multi-source data using a spatial coordinate transformation matrix, determines the defect boundary based on an improved edge extraction algorithm, generates a three-dimensional defect model using NURBS surface reconstruction technology, and performs three-dimensional visualization rendering on the equipment model, thereby achieving accurate reconstruction of the defect spatial morphology and safety assessment. This solves the problems of related technologies failing to intuitively present the true morphology of defects in the three-dimensional space of the equipment and lacking a unified spatial coordinate mapping mechanism that integrates multi-source detection data, leading to a high error rate in safety assessment.

[0080] Next, referring to the accompanying drawings, a three-dimensional visualization reconstruction device for defects in high-temperature pressure equipment according to an embodiment of this application is described.

[0081] Figure 11 This is a schematic diagram of the structure of a three-dimensional visualization reconstruction device for defects in high-temperature pressure equipment according to an embodiment of this application.

[0082] like Figure 11 As shown, the three-dimensional visualization reconstruction device 10 for defects in high-temperature pressure equipment includes: an acquisition module 100, a unification module 200, and a reconstruction module 300.

[0083] Specifically, the acquisition module 100 is used to acquire multi-source data of high-temperature pressure equipment based on at least two of the following detection combinations: phased array ultrasound, digital X-ray, and memory detection.

[0084] The unified module 200 is used to unify the coordinate system of multi-source data based on multi-source data using a spatial coordinate transformation matrix, so as to obtain multi-source data after unifying the coordinate system.

[0085] The reconstruction module 300 is used to determine the defect boundary of the high-temperature pressure equipment based on multi-source data after unifying the coordinate system, and to perform three-dimensional visualization reconstruction of the defect boundary in the preset equipment model to generate the three-dimensional visualization reconstruction result of the defect of the high-temperature pressure equipment.

[0086] Optionally, in one embodiment of this application, the reconstruction module 300 includes a rebuilding unit and a reconstructing unit.

[0087] The reconstruction unit is used to reconstruct the point cloud of the defect boundary into a triangular mesh to generate an initial defect triangular mesh model; the initial defect triangular mesh model is then optimized to obtain an optimized defect triangular mesh.

[0088] The reconstruction unit is used to perform parametric surface reconstruction on the optimized defect triangular mesh, generate a 3D defect model, and embed the 3D defect model into a preset equipment model to perform 3D visualization reconstruction of the defects of high-temperature pressure equipment, and generate the 3D visualization reconstruction result of the defects of high-temperature pressure equipment.

[0089] Optionally, in one embodiment of this application, the objective function for optimizing the spatial coordinate transformation matrix is:

[0090] in, Let be a rotation matrix. It is a translation vector. For detection data points, For the corresponding point of the equipment model, It is the Euclidean norm.

[0091] Optionally, in one embodiment of this application, the unification module 200 includes: an establishment unit and a unification unit.

[0092] Among them, the establishment unit is used to establish the spatial coordinate transformation matrix between the body coordinate system of the high-temperature pressure-bearing equipment and the coordinate systems of each testing equipment.

[0093] A unified unit is used to map multi-source data collected by various detection devices to the body coordinate system using a spatial coordinate transformation matrix, so as to unify the multi-source data coordinate system.

[0094] Optionally, in one embodiment of this application, the three-dimensional visualization reconstruction device 10 for defects in high-temperature pressure equipment further includes: a calculation module, a prediction module, and a generation module.

[0095] The calculation module is used to calculate the stress intensity factor of the defect based on the three-dimensional visualization results of the defect in the high-temperature pressure equipment and the three-dimensional morphology of the defect. The stress intensity factor includes the open-type stress intensity factor. Sliding type stress intensity factor and tear-type stress intensity factor .

[0096] The prediction module is used to integrate preset formulas. , and This is to predict the remaining lifespan of high-temperature pressure equipment.

[0097] The generation module is used to classify the remaining lifespan of high-temperature pressure equipment into risk levels in order to generate risk assessment data for high-temperature pressure equipment.

[0098] Optionally, in one embodiment of this application, the multi-parameter correction model for remaining lifetime is:

[0099] in, Indicates the crack propagation rate. For material constants, The index is the Paris formula index. This represents the stress intensity factor amplitude. Temperature is a factor that affects the environment. It is an environmental corrosive agent.

[0100] Optionally, in one embodiment of this application, the three-dimensional visualization reconstruction device 10 for defects in high-temperature pressure equipment further includes: an overlay module and an evaluation module.

[0101] The overlay module is used to overlay the three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect onto the actual image of the equipment after generating the three-dimensional visualization reconstruction result of the high-temperature pressure equipment defect to generate the target view.

[0102] The evaluation module is used to visually evaluate the defects of high-temperature pressure equipment using target views, in order to obtain an evaluation report for the high-temperature pressure equipment.

[0103] It should be noted that the explanation of the aforementioned embodiment of the three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment also applies to the three-dimensional visualization reconstruction device for defects in high-temperature pressure equipment in this embodiment, and will not be repeated here.

[0104] The three-dimensional visualization reconstruction device for defects in high-temperature pressure equipment proposed in this application acquires equipment defect data through at least two non-destructive testing methods, establishes a three-dimensional digital twin model of the equipment, unifies the coordinate system of multi-source data using a spatial coordinate transformation matrix, determines the defect boundary based on an improved edge extraction algorithm, generates a three-dimensional defect model using NURBS surface reconstruction technology, and performs three-dimensional visualization rendering on the equipment model, thereby achieving accurate reconstruction of the spatial morphology of the defect and safety assessment. This solves the problems of related technologies failing to intuitively present the true morphology of defects in the three-dimensional space of the equipment and lacking a unified spatial coordinate mapping mechanism that integrates multi-source detection data, leading to a high error rate in safety assessment.

[0105] Figure 12 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 1201, the processor 1202, and the computer program stored on the memory 1201 and executable on the processor 1202.

[0106] When the processor 1202 executes the program, it implements the three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment provided in the above embodiments.

[0107] Furthermore, electronic devices also include: Communication interface 1203 is used for communication between memory 1201 and processor 1202.

[0108] The memory 1201 is used to store computer programs that can run on the processor 1202.

[0109] The memory 1201 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage.

[0110] If the memory 1201, processor 1202, and communication interface 1203 are implemented independently, then the communication interface 1203, memory 1201, and processor 1202 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 12 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0111] Optionally, in a specific implementation, if the memory 1201, processor 1202, and communication interface 1203 are integrated on a single chip, then the memory 1201, processor 1202, and communication interface 1203 can communicate with each other through an internal interface.

[0112] The processor 1202 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0113] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for three-dimensional visualization reconstruction of defects in high-temperature pressure equipment.

[0114] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0115] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0116] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0117] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0118] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0119] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0120] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0121] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment, characterized in that, Includes the following steps: Multi-source data of high-temperature pressure equipment is acquired by combining at least two of phased array ultrasound, digital X-ray and memory detection. Based on the aforementioned multi-source data, a spatial coordinate transformation matrix is ​​used to unify the coordinate system of the multi-source data to obtain multi-source data after unifying the coordinate system. Based on the multi-source data after the unified coordinate system, the defect boundary of the high-temperature pressure-bearing equipment is determined, and the defect boundary is reconstructed in three dimensions in the preset equipment model to generate the three-dimensional visualization reconstruction result of the defect of the high-temperature pressure-bearing equipment.

2. The method according to claim 1, characterized in that, The step of performing three-dimensional visualization reconstruction of the defect boundary in a preset equipment model to generate a three-dimensional visualization reconstruction result of the defect in the high-temperature pressure equipment includes: The point cloud of the defect boundary is reconstructed into a triangular mesh to generate an initial defect triangular mesh model; The initial defect triangular mesh model is optimized to obtain the optimized defect triangular mesh. The optimized defect triangular mesh is parametrically reconstructed to generate a three-dimensional defect model. The three-dimensional defect model is then embedded into the preset equipment model to perform three-dimensional visualization reconstruction of the defect in the high-temperature pressure equipment, generating a three-dimensional visualization reconstruction result of the defect in the high-temperature pressure equipment.

3. The method according to claim 1, characterized in that, The objective function for optimizing the spatial coordinate transformation matrix is: in, For rotation matrix, It is a translation vector. For detection data points, For the corresponding point of the equipment model, It is the Euclidean norm.

4. The method according to claim 1, characterized in that, The method of unifying the coordinate system of multi-source data using a spatial coordinate transformation matrix includes: Establish a spatial coordinate transformation matrix between the body coordinate system of the high-temperature pressure-bearing equipment and the coordinate systems of each testing device; Using the spatial coordinate transformation matrix, the multi-source data collected by each detection device is mapped to the body coordinate system to unify the multi-source data coordinate system.

5. The method according to claim 1, characterized in that, After generating the three-dimensional visualization results of the defects in the high-temperature pressure equipment, the following steps are also included: Based on the three-dimensional visualization results of the defects in the high-temperature pressure-bearing equipment, the stress intensity factor of the defects is calculated according to their three-dimensional morphology. The stress intensity factor includes an open-type stress intensity factor. Sliding type stress intensity factor and tear-type stress intensity factor ; Integrate the above using a preset formula The above and stated In order to predict the remaining lifespan of the high-temperature pressure-bearing equipment; The remaining lifespan of the high-temperature pressure-bearing equipment is classified into risk levels to generate risk assessment data for the high-temperature pressure-bearing equipment.

6. The method according to claim 5, characterized in that, The multi-parameter correction model for the remaining lifetime is as follows: in, Indicates the crack propagation rate. For material constants, The index is the Paris formula index. This represents the stress intensity factor amplitude. Temperature is a factor that affects the environment. It is an environmental corrosive agent.

7. The method according to claim 1, characterized in that, After generating the three-dimensional visualization reconstruction result of the defects in the high-temperature pressure equipment, the following steps are also included: The three-dimensional visualization reconstruction result of the defects of the high-temperature pressure equipment is superimposed on the real-scene image of the equipment to generate a target view; The defects of the high-temperature pressure-bearing equipment are visually evaluated using the target view to obtain an evaluation report for the high-temperature pressure-bearing equipment.

8. A three-dimensional visualization reconstruction device for defects in high-temperature pressure equipment, characterized in that, include: The acquisition module is used to acquire multi-source data of high-temperature pressure equipment based on at least two of the following detection combinations: phased array ultrasound, digital X-ray, and memory detection. A unified module is used to unify the coordinate system of the multi-source data based on the multi-source data using a spatial coordinate transformation matrix, so as to obtain the multi-source data after unifying the coordinate system; The reconstruction module is used to determine the defect boundary of the high-temperature pressure-bearing equipment based on the multi-source data after the unified coordinate system, and to perform three-dimensional visualization reconstruction of the defect boundary in the preset equipment model to generate a three-dimensional visualization reconstruction result of the defect of the high-temperature pressure-bearing equipment.

9. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the three-dimensional visualization reconstruction method for defects in high-temperature pressure equipment as described in any one of claims 1-7.

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