A method and system for measuring explosion-proof performance of barrier explosion-proof materials

Abstract

The present invention discloses a method and system for measuring the explosion-proof performance of a barrier explosion-proof material, and relates to the technical field of measuring the performance of barrier explosion-proof materials. The method for measuring the explosion-proof performance includes the following steps: building a material preparation platform based on the manufacturing process of barrier explosion-proof materials, and using the material preparation platform to simulate the production of barrier explosion-proof materials under different production ratios; using three-dimensional simulation analysis technology to build an application equipment model, adding barrier explosion-proof materials to the application equipment model, and triggering a preset detonation mechanism; using monitoring equipment to collect image data of the application equipment before and after detonation, and analyzing the integrity of the application equipment based on comparison technology; judging the explosion-proof performance of barrier explosion-proof materials under different production ratios according to the integrity analysis results to generate performance measurement criteria. The present invention can judge the explosion-proof performance of different production ratios, thereby selecting the optimal material production ratio and improving the performance of the final product.

Description

Technical Field

[0001] The present invention relates to the technical field of barrier and explosion-proof material performance measurement, and in particular to a barrier and explosion-proof material explosion-proof performance measurement method and system. Background Art

[0002] Barrier explosion-proof materials are materials used to prevent or mitigate explosion accidents. They are usually used in containers or equipment that store or transport flammable and explosive substances. The purpose of this type of material is to form one or more barrier layers inside the container to reduce or prevent the spread of flames and explosion waves, thereby protecting the container and its surrounding environment from damage. Barrier explosion-proof materials can usually inhibit the spread of flames and reduce the possibility of combustion. At the same time, they can withstand a certain degree of mechanical impact and maintain structural integrity.

[0003] In order to ensure that the explosion-proof performance of barrier explosion-proof materials can meet the requirements, explosion-proof performance tests will be carried out after their preparation to ensure that they meet specific safety standards and regulatory requirements and whether they can effectively prevent the spread of flames and pressure waves. The determination of the explosion-proof performance of barrier explosion-proof materials is not only a basic requirement for material performance, but also an important means to ensure public safety and promote technological progress.

[0004] However, most explosion-proof performance tests in the prior art are practical explosion measurements, which evaluate the explosion-proof performance of materials by simulating explosions under actual conditions. Although the practical method provides an intuitive way to evaluate the performance of materials in actual applications, the practical explosion measurement involves actual explosion processes, which may cause damage to test facilities, equipment and personnel, and there is a high safety risk. In addition, practical explosion measurements usually cause damage to test samples, which means that samples need to be re-prepared after each test, increasing the cost and time of the test.

[0005] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0006] In order to solve the above problems, the present invention proposes a method and system for measuring the explosion-proof performance of barrier explosion-proof materials, so as to achieve the purpose of predicting the performance of application equipment during the detonation process without actual detonation by using three-dimensional simulation analysis technology.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides a method for measuring the explosion-proof performance of an explosion-proof barrier material, the method comprising the following steps:

[0009] S1. Build a material preparation platform based on the manufacturing process of barrier explosion-proof materials, and use the material preparation platform to simulate the production of barrier explosion-proof materials under different production ratios;

[0010] S2. Use three-dimensional simulation analysis technology to build an application equipment model, add barrier and explosion-proof materials under different production ratios into the application equipment model, and trigger the preset detonation mechanism;

[0011] S3. Use monitoring equipment to collect image data of the application equipment before and after detonation, and analyze the integrity of the application equipment based on comparison technology;

[0012] S4. Determine the explosion-proof performance of barrier explosion-proof materials under different production ratios based on the completeness analysis results, generate performance measurement criteria, and select the optimal material production ratio based on the explosion-proof performance results.

[0013] Furthermore, the application equipment model is built by using three-dimensional simulation analysis technology, barrier explosion-proof materials under different production ratios are added to the application equipment model, and the preset detonation mechanism is triggered, including the following steps:

[0014] S21. Use laser scanning equipment to collect the original point cloud data of the application equipment, and use point cloud processing technology to perform registration, splicing, merging and noise reduction on the original point cloud data to obtain entity point cloud data;

[0015] S22, using the entity point cloud data as basic data for layered slicing processing, extracting the contour line of the application equipment, and using 3D modeling software to model the contour line to obtain an application equipment model;

[0016] S23, generating a single image based on the application device image collected by the entity, constructing the relative relationship between the entity point cloud data and each image, and converting the image into a texture space and adding it to the application device model;

[0017] S24. Add barrier explosion-proof materials with different production ratios produced by the material preparation platform to the application equipment model, and combine the preset detonation mechanism with the application equipment model to perform explosion simulation operations.

[0018] Furthermore, using monitoring equipment to collect image data of the application equipment before and after detonation, and analyzing the integrity of the application equipment based on comparison technology includes the following steps:

[0019] S31, adding an image acquisition device to the application device model to obtain image data of the application device before and after detonation, and using image processing technology to filter out image data that meets preset standards;

[0020] S32, using an equidistant division technique to divide the image data before and after detonation into a preset number of comparison areas, and making one-to-one correspondence between the comparison areas before and after detonation;

[0021] S33. Use recognition processing technology to find feature points in the comparison area respectively, and use similarity to quantify the similarity between the feature points to determine the integrity of the application equipment after the explosion.

[0022] Furthermore, using recognition processing technology to find feature points in the comparison area respectively, and using similarity quantification to quantify the similarity between the feature points to determine the integrity of the application device after the explosion includes the following steps:

[0023] S331, using recognition processing technology to search for the contour of the application device in the comparison area before and after detonation, and selecting the contour area with the largest area of ​​the application device as the feature judgment area;

[0024] S332, respectively, using the upper right vertices of the feature judgment areas before and after detonation as the origin to establish a two-dimensional coordinate system to determine the width and height of the application device, and using the midpoint of the width as the projection origin to scan the pixels of the contour area from right to left using the projection method;

[0025] S333, based on the projection result, two coordinates with the initial and final pixels being zero are selected to obtain the boundary conditions in the longitudinal direction of the feature judgment area, and two straight lines parallel to the longitudinal coordinate axis are fitted through the two coordinates;

[0026] S334, searching for the columns of the boundary coordinates of the vertical axis direction of the feature judgment area before and after detonation respectively, and selecting two coordinate positions at the bottom edge of the feature judgment area, connecting the coordinate positions with a straight line to obtain a rectangular area;

[0027] S335, applying the projection method to the rectangular area to count the number of pixels and the grayscale values ​​of each column from left to right, and determining the average grayscale value of each column of pixels and the number of pixels with zero grayscale values ​​to obtain feature points;

[0028] S336. Quantify the similarity between the feature points before and after detonation using similarity judgment technology to judge the integrity of the application equipment after the explosion.

[0029] Furthermore, the similarity between the feature points before and after the detonation is quantified using the similarity judgment technology, and the integrity of the application device after the explosion is judged, including the following steps:

[0030] S3361, plotting the coordinate values ​​corresponding to the feature points before and after detonation into the vector space, and assigning weights to the feature points before and after detonation according to the weight analysis technology;

[0031] S3362, obtaining the angle between the vectors based on the weight value distribution result and calculating the corresponding angle value, and judging the similarity between the feature points before and after detonation according to the angle value result;

[0032] S3363. Compare the similarity with a preset similarity threshold. If the similarity is higher than the threshold, it is considered that the integrity of the application device after the detonation is high; if the similarity is lower than the threshold, it is considered that the damage to the application device after the detonation is serious.

[0033] Furthermore, the similarity calculation formula is:

[0034]

[0035] In the formula, S similarity (S 1 ,S 2 ) represents the feature point S 1 With feature point S 2 The similarity between them; n represents the total number of feature points; υ j represents the weight value corresponding to the jth feature point before detonation; σ j Represents the weight value corresponding to the jth feature point after detonation.

[0036] Further, judging the explosion-proof performance of the barrier explosion-proof material under different production ratios according to the completeness analysis results to generate a performance determination criterion, and selecting the optimal material production ratio based on the explosion-proof performance results includes the following steps:

[0037] S41. Collect the completeness analysis results of the application equipment in the application of barrier explosion-proof materials with different production ratios, and set mechanical strength and flame retardancy as the performance evaluation indicators of barrier explosion-proof materials;

[0038] S42. Combine the performance evaluation index with the integrity analysis result, use the intelligent evaluation algorithm to evaluate the barrier explosion-proof material, summarize the evaluation conclusion to obtain the damage index of the barrier explosion-proof material;

[0039] S43. Evaluate the explosion-proof performance of barrier explosion-proof materials under different production ratios according to the damage index, and generate measurement criteria based on the explosion-proof performance results;

[0040] S44. Use automatic sorting technology to sort the explosion-proof performance results of barrier explosion-proof materials with different production ratios from high to low, and select the production ratio corresponding to the barrier explosion-proof material with the highest explosion-proof performance as the optimal material production ratio.

[0041] Furthermore, the performance evaluation index is combined with the integrity analysis results, and the barrier explosion-proof material is evaluated using the intelligent evaluation algorithm. The damage index of the barrier explosion-proof material is obtained by summarizing the evaluation conclusions, including the following steps:

[0042] S421. Based on the integrity analysis results, the mechanical strength and flame retardancy performance evaluation of the barrier explosion-proof material is graded, and damage assessment parameters are set according to the integrity analysis results;

[0043] S422. Describe the relationship vectors between the integrity of the application equipment and the mechanical strength and flame retardancy based on the damage assessment index;

[0044] S423. Based on the relationship vector, a relationship matrix is ​​constructed to represent the damage index of the barrier explosion-proof material, and the evaluation conclusions of the mechanical strength and flame retardancy are summarized to obtain the total damage index of the barrier explosion-proof material.

[0045] Furthermore, the explosion-proof performance results of barrier explosion-proof materials with different production ratios are sorted from high to low using automatic sorting technology, and the production ratio corresponding to the barrier explosion-proof material with the highest explosion-proof performance is selected as the optimal material production ratio, including the following steps:

[0046] S441. Standardize the explosion-proof performance results of barrier explosion-proof materials with different production ratios, and use the topological sorting algorithm to generate an initial sequence plan;

[0047] S442, introducing a greedy algorithm based on the initial sequence scheme to set a sorting rule from high to low, and using the crossover and mutation operations of the greedy algorithm to obtain a sorting result of the explosion-proof performance results;

[0048] S443. Select the explosion-proof performance result with the highest ranking from the ranking results, search for the production ratio parameters of the corresponding barrier explosion-proof material, and use the production ratio parameters as the optimal production ratio parameters.

[0049] In a second aspect, the present invention further provides a barrier explosion-proof material explosion-proof performance measurement system, the barrier explosion-proof material explosion-proof performance measurement system includes an explosion-proof material production simulation module, an explosion-proof material detonation simulation module, an equipment integrity analysis module and a material production ratio selection module;

[0050] The explosion-proof material production simulation module, the explosion-proof material detonation simulation module, the equipment integrity analysis module and the material production ratio selection module are connected in sequence;

[0051] The explosion-proof material production simulation module is used to build a material preparation platform based on the manufacturing process of barrier explosion-proof materials, and use the material preparation platform to simulate the production of barrier explosion-proof materials under different production ratios;

[0052] The explosion-proof material detonation simulation module is used to build an application equipment model using three-dimensional simulation analysis technology, add barrier explosion-proof materials under different production ratios to the application equipment model, and trigger the preset detonation mechanism;

[0053] The equipment integrity analysis module is used to collect image data of the application equipment before and after detonation using monitoring equipment, and analyze the integrity of the application equipment based on comparison technology;

[0054] The material production ratio selection module is used to determine the explosion-proof performance of barrier explosion-proof materials under different production ratios according to the completeness analysis results, generate performance measurement criteria, and select the optimal material production ratio based on the explosion-proof performance results.

[0055] The present invention has the following technical effects or advantages:

[0056] 1. The present invention can simulate the material preparation process under different production ratios by building a material preparation platform. The application of three-dimensional simulation analysis technology can predict the performance of application equipment during the detonation process without actual detonation. Compared with the actual multiple detonation tests, the simulation analysis can greatly reduce the cost and ensure the safety of the explosion-proof performance test of barrier explosion-proof materials. At the same time, the image data collected by the monitoring equipment can be used to obtain the information on the integrity of the application equipment. Based on the integrity analysis results, the explosion-proof performance of different production ratios can be judged, thereby selecting the optimal material production ratio to improve the performance of the final product.

[0057] 2. The present invention uses the original point cloud data obtained by laser scanning equipment, combined with point cloud processing technology, to create a high-precision application equipment model, which helps to improve the accuracy of simulation analysis. By constructing the relative relationship between the entity point cloud data and the image, visual factors such as lighting and texture can be considered in the simulation, so as to more comprehensively evaluate the material performance. Furthermore, without actual detonation, the performance of barrier and explosion-proof materials under different production ratios can be comprehensively evaluated, providing strong technical support for safety assessment.

[0058] 3. By adding an image acquisition device, the present invention can monitor the status of the application equipment before and after detonation in real time, and use image processing technology to screen out image data that meets preset standards, thereby eliminating noise and irrelevant information. By using recognition processing technology to find feature points in the comparison area, the damage of the application equipment after the explosion can be more accurately located. Finally, the similarity between the feature points is quantified using similarity metrics, which can objectively evaluate the integrity of the application equipment and reduce errors in subjective judgment. Compared with traditional destructive testing, this method has significant advantages in cost and time.

[0059] 4. The present invention collects and analyzes the results of integrity analysis, scientifically evaluates the mechanical strength and flame retardancy of barrier explosion-proof materials under different production ratios, ensures the objectivity and accuracy of the evaluation, uses intelligent evaluation algorithms to process large amounts of data, quickly summarizes evaluation conclusions, obtains damage indexes, and improves evaluation efficiency. It also sorts the explosion-proof performance results through automatic sorting technology, intuitively compares the performance under different ratios, and thus selects the optimal material production ratio. Based on performance measurement criteria and the selection of the optimal ratio, the production process and performance of the material are continuously improved, which helps to improve the safety and market competitiveness of explosion-proof materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0061] Figure 1 is a flow chart of a method for determining explosion-proof performance of an isolation and explosion-proof material according to an embodiment of the present invention;

[0062] Figure 2 The invention is a block diagram of a system for measuring explosion-proof performance of explosion-proof barrier materials according to an embodiment of the invention.

[0063] In the figure:

[0064] 1. Explosion-proof material production simulation module; 2. Explosion-proof material detonation simulation module; 3. Equipment integrity analysis module; 4. Material production ratio selection module. DETAILED DESCRIPTION

[0065] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0066] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0067] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that the terms "include" and "have" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0068] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0069] See also Figure 1 The present invention provides a method for measuring the explosion-proof performance of an explosion-proof barrier material, and the method comprises the following steps:

[0070] S1. Build a material preparation platform based on the manufacturing process of barrier explosion-proof materials, and use the material preparation platform to simulate the production of barrier explosion-proof materials under different production ratios.

[0071] In this embodiment, a material preparation platform is built based on the manufacturing process of barrier explosion-proof materials, and the material preparation platform is used to simulate the production of barrier explosion-proof materials under different production ratios, including:

[0072] The material preparation platform is built by developing a dynamic web interface using React or Vue.js technology. The model equipment required for the manufacture of barrier and explosion-proof materials is introduced into the interface, including mixers, extruders, calenders, etc. It also uses the principles of computational chemistry and materials science to provide material design and performance prediction functions, and integrates a material preparation simulation platform.

[0073] Define the performance standards of the required barrier and explosion-proof materials, including mechanical strength and flame retardant properties, select silicone, flame retardants, and reinforcing fillers as preparation raw materials, configure equipment in the material preparation platform to adapt to different material processing requirements and production scales, set the composition ratio based on the predetermined preparation raw materials, simulate the entire production process on the material preparation platform, and obtain barrier and explosion-proof materials under different production ratios from the input of raw materials to the output of finished products.

[0074] Specifically, barrier and explosion-proof material samples with different ratios can be prepared according to research needs, ensuring that each ratio is accurately mixed according to the predetermined proportion, and using standardized production processes to manufacture material specimens with high uniformity and consistency, such as plates or cylinders, to be suitable for subsequent testing.

[0075] At the same time, a universal material testing machine is introduced into the material preparation platform to carry out compression, tension and bending tests, record the elastic modulus, compressive strength and tensile strength of the material, and record all test data in detail, including the stress-strain curve.

[0076] S2. Use three-dimensional simulation analysis technology to build an application equipment model, add barrier and explosion-proof materials under different production ratios into the application equipment model, and trigger the preset detonation mechanism.

[0077] In this embodiment, the application equipment model is built by using three-dimensional simulation analysis technology, barrier explosion-proof materials under different production ratios are added to the application equipment model, and the preset detonation mechanism is triggered, including the following steps:

[0078] S21. Use laser scanning equipment to collect the original point cloud data of the application equipment, and use point cloud processing technology to perform registration, splicing, merging and noise reduction on the original point cloud data to obtain entity point cloud data.

[0079] Specifically, using laser scanning equipment to collect the original point cloud data of the application equipment, and using point cloud processing technology to perform registration, splicing, merging and noise reduction on the original point cloud data to obtain entity point cloud data includes the following steps:

[0080] Configure the scanning range and accuracy of the laser scanning device according to the size and shape of the application equipment that needs to be scanned, perform multi-angle scanning to ensure that all visible surfaces are covered, and collect raw point cloud data.

[0081] The collected raw point cloud data is initially cleaned to remove outliers and obvious noise, and the iterative closest point (ICP) algorithm is used to spatially align the point cloud data from different perspectives, and the aligned multiple point cloud data sets are merged into a single, continuous point cloud model.

[0082] Apply Gaussian filter, median filter or other suitable filtering technology to reduce the noise in the point cloud. At the same time, improve the uniformity and quality of point cloud data through point cloud density homogenization or sampling optimization technology, and merge multiple point cloud data that have undergone noise reduction to obtain physical point cloud data.

[0083] S22. The entity point cloud data is used as basic data for layered slicing, the contour line of the application equipment is extracted, and the contour line is modeled using three-dimensional modeling software to obtain the application equipment model.

[0084] Specifically, the entity point cloud data is used as basic data for layered slicing processing, the contour line of the application equipment is extracted, and the contour line is modeled by using 3D modeling software to obtain the application equipment model, which includes the following steps:

[0085] According to the size of the application equipment and the required model accuracy, set the appropriate slice thickness, slice the entire point cloud data in layers, and each slice represents a layer of cross-sectional point cloud data. In each slice, use Canny edge detection to identify clear contour lines and remove irregular edges and isolated points caused by scanning errors or point cloud noise.

[0086] The extracted contour lines are smoothed and the breakpoints are connected to ensure the continuity and accuracy of the contour lines. Autodesk Fusion360 is selected as the 3D modeling software, and the processed contour lines are imported into the modeling software. The modeling tools of the software are used to generate a 3D solid model according to the contour lines. The dimensions and shapes of the model are adjusted as needed, and possible model errors are corrected to obtain the application equipment model.

[0087] S23. Generate a single image based on the application device image collected by the entity, build a relative relationship between the entity point cloud data and each image, and convert the image into texture space and add it to the application device model.

[0088] Specifically, generating a single image based on the application device image collected by the entity, constructing the relative relationship between the entity point cloud data and each image, and converting the image into a texture space and adding it to the application device model includes the following steps:

[0089] Select the photographic equipment and configure the corresponding photographic parameters according to the size and details of the application equipment, pre-process the collected images, including cropping, correction and color balance, and use pixel-to-point cloud registration technology to establish the relative position relationship between point cloud data and images.

[0090] According to the registration relationship between the point cloud and the image, the image is mapped to the corresponding 3D point cloud, the processed image is converted into a texture file and the coordinates of the texture mapping are adjusted to match the surface of the 3D model, the texture file is imported into the 3D modeling software, and applied to the corresponding 3D model surface.

[0091] Adjust the size, position and direction of the texture to ensure natural transition and seamless splicing of the texture, and perform visual inspection on the textured model to ensure the accuracy and beauty of the texture.

[0092] S24. Add barrier explosion-proof materials with different production ratios produced by the material preparation platform to the application equipment model, and combine the preset detonation mechanism with the application equipment model to perform explosion simulation operations.

[0093] Specifically, adding barrier explosion-proof materials with different production ratios produced by the material preparation platform to the application equipment model, and combining the preset detonation mechanism with the application equipment model to perform the explosion simulation operation includes the following steps:

[0094] Set physical and chemical properties for barrier and explosion-proof materials with different production ratios, such as density, elastic modulus, thermal expansion coefficient, burning rate, etc., input these property parameters into the material database for calling in simulation, and import the application equipment model in the 3D modeling software into the simulation software platform.

[0095] Set one or more detonation points in the model. Select the location and number of detonation points, set detonation temperature, pressure, chemical reaction rate and other parameters, ensure that the detonation conditions meet the expected test standards, and configure the simulated environmental parameters.

[0096] Start the simulation, observe and record the material's response to the explosion impact and the structural integrity of the equipment, and collect post-explosion data, including material damage, blast wave propagation, temperature and pressure changes, etc.

[0097] In order to facilitate understanding of the technical solution of the present invention, in this embodiment, the fuel tank is set as an application simulation device to perform a detonation simulation operation, which is as follows:

[0098] Step 1: point cloud data collection and processing;

[0099] (1) Laser scanning equipment settings: Select the Faro Focus3D X 330 model, set the scanning resolution to 1 dot per millimeter, and the scanning range to cover the entire fuel tank. Perform a 360-degree full-range scan to obtain point cloud data.

[0100] (2) Point cloud processing: Use Leica Cyclone REGISTER software to perform point cloud registration on the point cloud data, integrate the data obtained from scanning at different angles, and apply the Statistical Outlier Removal filter to remove noise and retain the core data set.

[0101] Step 2: Layered slicing and modeling;

[0102] Slicing: Set the slice thickness to 2 mm per layer, use Autodesk ReCap for layering, and use 3D modeling software to extract contours and draw a 3D model of the fuel tank.

[0103] Step 3: texture mapping;

[0104] (1) Image acquisition: A Canon EOS 5D Mark IV was used with a resolution of 6720 × 4480 pixels. Images were taken from at least 10 different angles to ensure full coverage.

[0105] (2) Image-to-texture conversion: Use Photoshop for color correction and cropping, and use Pix4Dmapper software to map the image onto the 3D model to generate texture.

[0106] Step 4: Material addition and explosion simulation;

[0107] (1) Material parameter setting: Set the density of the physical properties of the barrier explosion-proof material to 1.2 g / cm 3 , tensile strength 250MPa.

[0108] (2) Explosion simulation: Detonation mechanism: The detonation temperature was set to 300°C and the detonation pressure was set to 5 MPa. ANSYS AUTODYN was used to perform explosion simulation, and the simulation environment temperature was set to 20°C and the pressure was set to 1 atm.

[0109] (3) Simulation operation and data collection: Track the propagation of explosion waves and collect image data of the tank structure response and material damage data.

[0110] Therefore, the original point cloud data obtained by laser scanning equipment is combined with point cloud processing technology to create a high-precision application equipment model, which helps to improve the accuracy of simulation analysis. By constructing the relative relationship between the physical point cloud data and the image, visual factors such as lighting and texture can be considered in the simulation, so as to more comprehensively evaluate the material performance. In addition, the performance of barrier and explosion-proof materials under different production ratios can be comprehensively evaluated without actual detonation, providing strong technical support for safety assessment.

[0111] S3. Use monitoring equipment to collect image data of the application equipment before and after detonation, and analyze the integrity of the application equipment based on comparison technology.

[0112] In this embodiment, using a monitoring device to collect image data of the application device before and after detonation, and analyzing the integrity of the application device based on a comparison technique includes the following steps:

[0113] S31. Add an image acquisition device to the application device model to obtain image data of the application device before and after detonation, and use image processing technology to filter out image data that meets preset standards.

[0114] Specifically, adding an image acquisition device to the application device model to obtain image data of the application device before and after detonation, and using image processing technology to filter out image data that meets preset standards includes the following steps:

[0115] During the simulation, a high-speed camera was selected, and the camera resolution and frame rate were adjusted to adapt to the rapid changes of the explosion event to collect images of the application equipment before and after detonation.

[0116] Pre-process a large number of images, including cropping, rotation, and brightness / contrast adjustment, to improve image usability. Perform image quality assessment based on preset image quality and feature recognition standards, such as clarity, key feature identifiability, etc., and sort out image data that meet the standards for further detailed analysis and reporting.

[0117] S32, using an equidistant division technique to divide the image data before and after detonation into a preset number of comparison areas, and making one-to-one correspondence between the comparison areas before and after detonation.

[0118] Specifically, using the equidistant division technology to divide the image data before and after detonation into a preset number of comparison areas, and making one-to-one correspondence between the comparison areas before and after detonation includes the following steps:

[0119] Ensure that all pre- and post-detonation images have sufficient clarity and resolution. Normalize the images to ensure that the brightness and contrast of the images before and after detonation are consistent to facilitate effective comparison. Determine the size and shape of the comparison area (such as square, circle, etc.) based on the image content and analysis requirements, and determine the number of areas to be divided.

[0120] The equidistant division technique is applied to the image to divide the pre-detonation image into a preset number of regions. Each region has clear coordinates and sizes, and the pre-detonation division scheme is accurately copied to the post-detonation image to ensure that each comparison area can completely correspond in both states.

[0121] S33. Use recognition processing technology to find feature points in the comparison area respectively, and use similarity to quantify the similarity between the feature points to determine the integrity of the application equipment after the explosion.

[0122] Specifically, using recognition processing technology to find feature points in the comparison area respectively, and using similarity quantification to determine the integrity of the application equipment after the explosion, the following steps are included:

[0123] S331, using recognition processing technology to search for the contour of the application device in the comparison area before and after detonation, and selecting the contour area with the largest area of ​​the application device as the feature judgment area;

[0124] S332, respectively, using the upper right vertices of the feature judgment areas before and after detonation as the origin to establish a two-dimensional coordinate system to determine the width and height of the application device, and using the midpoint of the width as the projection origin to scan the pixels of the contour area from right to left using the projection method;

[0125] S333, based on the projection result, two coordinates with the initial and final pixels being zero are selected to obtain the boundary conditions in the longitudinal direction of the feature judgment area, and two straight lines parallel to the longitudinal coordinate axis are fitted through the two coordinates;

[0126] S334, searching for the columns of the boundary coordinates of the vertical axis direction of the feature judgment area before and after detonation respectively, and selecting two coordinate positions at the bottom edge of the feature judgment area, connecting the coordinate positions with a straight line to obtain a rectangular area;

[0127] S335, applying the projection method to the rectangular area to count the number of pixels and the grayscale values ​​of each column from left to right, and determining the average grayscale value of each column of pixels and the number of pixels with zero grayscale values ​​to obtain feature points;

[0128] S336. Quantify the similarity between the feature points before and after detonation using similarity judgment technology to judge the integrity of the application equipment after the explosion.

[0129] Among them, using similarity judgment technology to quantify the similarity between the feature points before and after detonation, and judging the integrity of the application equipment after the explosion includes the following steps:

[0130] S3361, plotting the coordinate values ​​corresponding to the feature points before and after detonation into the vector space, and assigning weights to the feature points before and after detonation according to the weight analysis technology;

[0131] S3362, obtaining the angle between the vectors based on the weight value distribution result and calculating the corresponding angle value, and judging the similarity between the feature points before and after detonation according to the angle value result;

[0132] S3363. Compare the similarity with a preset similarity threshold. If the similarity is higher than the threshold, it is considered that the integrity of the application device after the detonation is high; if the similarity is lower than the threshold, it is considered that the damage to the application device after the detonation is serious.

[0133] Specifically, the similarity calculation formula is:

[0134]

[0135] In the formula, S similarity (S 1 ,S 2 ) represents the feature point S 1 With feature point S 2 The similarity between them; n represents the total number of feature points; υ j represents the weight value corresponding to the jth feature point before detonation; σ j Represents the weight value corresponding to the jth feature point after detonation.

[0136] Therefore, by adding image acquisition equipment, the status of the application equipment before and after detonation can be monitored in real time, and image processing technology can be used to screen out image data that meets the preset standards, thereby eliminating noise and irrelevant information. Recognition processing technology can be used to find feature points in the comparison area, which can more accurately locate the damage of the application equipment after the explosion. Finally, similarity is used to quantify the similarity between feature points, which can objectively evaluate the integrity of the application equipment and reduce errors in subjective judgment. Compared with traditional destructive testing, this method has significant advantages in cost and time.

[0137] S4. Determine the explosion-proof performance of barrier explosion-proof materials under different production ratios based on the completeness analysis results, generate performance measurement criteria, and select the optimal material production ratio based on the explosion-proof performance results.

[0138] In this embodiment, judging the explosion-proof performance of barrier explosion-proof materials under different production ratios according to the integrity analysis results to generate performance measurement criteria, and selecting the optimal material production ratio based on the explosion-proof performance results includes the following steps:

[0139] S41. Collect the integrity analysis results of the application equipment when using barrier and explosion-proof materials with different production ratios, and set mechanical strength and flame retardancy as performance evaluation indicators of barrier and explosion-proof materials.

[0140] S42. Combine the performance evaluation index with the integrity analysis results, use the intelligent evaluation algorithm to evaluate the barrier explosion-proof materials, and summarize the evaluation conclusions to obtain the damage index of the barrier explosion-proof materials.

[0141] Specifically, the performance evaluation index is combined with the integrity analysis results, and the intelligent evaluation algorithm is used to evaluate the barrier explosion-proof material. The evaluation conclusion is summarized to obtain the damage index of the barrier explosion-proof material, which includes the following steps:

[0142] S421. Based on the integrity analysis results, the mechanical strength and flame retardancy performance evaluation of the barrier explosion-proof material is graded, and damage assessment parameters are set according to the integrity analysis results;

[0143] S422. Describe the relationship vectors between the integrity of the application equipment and the mechanical strength and flame retardancy based on the damage assessment index;

[0144] S423. Based on the relationship vector, a relationship matrix is ​​constructed to represent the damage index of the barrier explosion-proof material, and the evaluation conclusions of the mechanical strength and flame retardancy are summarized to obtain the total damage index of the barrier explosion-proof material.

[0145] S43. Evaluate the explosion-proof performance of barrier explosion-proof materials under different production ratios according to the damage index, and generate measurement criteria based on the explosion-proof performance results.

[0146] Specifically, the explosion-proof performance of barrier explosion-proof materials under different production ratios is evaluated according to the damage index, and the determination criteria are generated based on the explosion-proof performance results, including the following steps:

[0147] Collect damage index data of barrier explosion-proof materials with various proportions. These data should include the degree of damage of the materials under actual or simulated explosion conditions obtained from the intelligent evaluation algorithm. Analyze the damage index and determine the explosion-proof performance of materials with different proportions. A high damage index indicates poor explosion-proof performance, while a low damage index indicates better explosion-proof performance.

[0148] The explosion-proof performance of barrier explosion-proof materials is graded according to the damage index. For example, the damage index is divided into three levels: high, medium and low. The specific standards are formulated based on the evaluation results of the explosion-proof performance and the measurement criteria are formulated.

[0149] S44. Use automatic sorting technology to sort the explosion-proof performance results of barrier explosion-proof materials with different production ratios from high to low, and select the production ratio corresponding to the barrier explosion-proof material with the highest explosion-proof performance as the optimal material production ratio.

[0150] Specifically, the explosion-proof performance results of barrier explosion-proof materials with different production ratios are sorted from high to low using automatic sorting technology, and the production ratio corresponding to the barrier explosion-proof material with the highest explosion-proof performance is selected as the optimal material production ratio, which includes the following steps:

[0151] S441. Standardize the explosion-proof performance results of barrier explosion-proof materials with different production ratios, and use the topological sorting algorithm to generate an initial sequence plan;

[0152] S442, introducing a greedy algorithm based on the initial sequence scheme to set a sorting rule from high to low, and using the crossover and mutation operations of the greedy algorithm to obtain a sorting result of the explosion-proof performance results;

[0153] S443. Select the explosion-proof performance result with the highest ranking from the ranking results, search for the production ratio parameters of the corresponding barrier explosion-proof material, and use the production ratio parameters as the optimal production ratio parameters.

[0154] The specific process of the present invention is embodied as follows:

[0155] Step 1: image acquisition and processing;

[0156] (1) Image equipment configuration: Use a high-speed camera, such as Phantom v2640, with a resolution of 2048*1952 pixels and a frame rate of 5000 frames per second to record the rapid dynamic changes before and after the explosion. Adjust the image according to the position of the fuel tank in the image to ensure that the focus is on the key area, and use image processing software to adjust the recognition and image clarity to meet the minimum threshold.

[0157] (2) Feature point identification and integrity analysis: Use image recognition software to perform edge detection and feature point identification. Select the contour area with the largest area of ​​the fuel tank as the feature judgment area, and apply mathematical methods to fit the contour boundary to ensure accurate identification of boundary changes. Quantify the feature point changes through image analysis methods (such as pixel projection method). Finally, use a similarity algorithm (cosine similarity) to calculate the similarity of the feature points before and after detonation.

[0158] Step 2: Performance measurement and optimal ratio selection;

[0159] Calculation of damage index and grading of explosion-proof performance: The explosion-proof performance of barrier explosion-proof materials is classified into three levels: high, medium and low according to the damage index.

[0160] Specifically, the expression of the damage index is:

[0161] D=μ 1 ·P+μ 2 ·S+μ 3 T;

[0162] Where D represents the damage index of the barrier explosion-proof material, μ 1 , μ 2 and μ 3 It represents the weight coefficient, P represents the mechanical strength of the barrier explosion-proof material, S represents the integrity result of the application equipment, and T represents the flame retardancy of the barrier explosion-proof material.

[0163] Specific explosion-proof performance results generation criteria include:

[0164] If D≤0.2, it is defined as high-level explosion-proof performance, indicating that the barrier explosion-proof material still maintains a high degree of integrity and functionality under extreme conditions;

[0165] If 0.2<D≤0.5, it is defined as intermediate explosion-proof performance, indicating that the barrier explosion-proof material can withstand a certain impact without complete failure under extreme conditions;

[0166] If D>0.5, it is defined as low-level explosion-proof performance, indicating that the barrier explosion-proof material will be severely damaged or fail to function under extreme conditions.

[0167] Step 3: Selection of optimal production ratio;

[0168] The ratio with the highest explosion-proof performance is selected through data analysis and sorting technology (such as sorting algorithm), and an example of the optimal ratio is determined, such as 70% silicone, 20% melamine flame retardant, and 10% carbon nanotubes.

[0169] Therefore, by collecting and analyzing the results of the completeness analysis, scientifically evaluating the mechanical strength and flame retardancy of barrier explosion-proof materials under different production ratios, ensuring the objectivity and accuracy of the evaluation, using intelligent evaluation algorithms to process large amounts of data, quickly summarizing the evaluation conclusions, obtaining the damage index, and improving the evaluation efficiency, the explosion-proof performance results are sorted through automatic sorting technology, and the performance under different ratios is intuitively compared, so as to select the optimal material production ratio. Based on the performance measurement criteria and the selection of the optimal ratio, the production process and performance of the material are continuously improved, which helps to improve the safety and market competitiveness of explosion-proof materials.

[0170] In a second aspect, the present invention further provides a barrier explosion-proof material explosion-proof performance determination system, the barrier explosion-proof material explosion-proof performance determination system comprises an explosion-proof material production simulation module 1, an explosion-proof material detonation simulation module 2, an equipment integrity analysis module 3 and a material production ratio selection module 4;

[0171] The explosion-proof material production simulation module 1, the explosion-proof material detonation simulation module 2, the equipment integrity analysis module 3 and the material production ratio selection module 4 are connected in sequence;

[0172] Explosion-proof material production simulation module 1 is used to build a material preparation platform based on the manufacturing process of barrier explosion-proof materials, and use the material preparation platform to simulate the production of barrier explosion-proof materials under different production ratios;

[0173] Explosion-proof material detonation simulation module 2 is used to build an application equipment model using three-dimensional simulation analysis technology, add barrier explosion-proof materials under different production ratios to the application equipment model, and trigger a preset detonation mechanism;

[0174] The device integrity analysis module 3 is used to collect image data of the application device before and after detonation using the monitoring device, and analyze the integrity of the application device based on the comparison technology;

[0175] The material production ratio selection module 4 is used to determine the explosion-proof performance of the barrier explosion-proof material under different production ratios according to the completeness analysis results, generate performance measurement criteria, and select the optimal material production ratio based on the explosion-proof performance results.

[0176] In summary, with the help of the above technical scheme of the present invention, the present invention can simulate the material preparation process under different production ratios by building a material preparation platform. The application of three-dimensional simulation analysis technology can predict the performance of the application equipment during the detonation process without actual detonation. Compared with the actual multiple detonation tests, the simulation analysis can greatly reduce the cost and ensure the safety of the explosion-proof performance test of the barrier explosion-proof material. At the same time, the image data collected by the monitoring device can be used to obtain the information on the integrity of the application equipment. Based on the integrity analysis results, the explosion-proof performance of different production ratios can be judged, so as to select the optimal material production ratio and improve the performance of the final product. The present invention creates a high-precision application equipment model by combining the original point cloud data obtained by the laser scanning device with the point cloud processing technology, which helps to improve the accuracy of the simulation analysis. By constructing the relative relationship between the entity point cloud data and the image, visual factors such as illumination and texture can be considered in the simulation, so as to more comprehensively evaluate the material performance, and then the performance of the barrier explosion-proof material under different production ratios can be comprehensively evaluated without actual detonation, providing strong technical support for safety assessment.

[0177] The present invention can monitor the state of the application equipment before and after detonation in real time by adding an image acquisition device, and use image processing technology to filter out image data that meets the preset standards, exclude noise and irrelevant information, use recognition processing technology to find feature points at the comparison area, and more accurately locate the damage of the application equipment after the explosion. Finally, the similarity between the feature points is quantified by similarity, and the integrity of the application equipment can be objectively evaluated, reducing the error of subjective judgment. Compared with traditional destructive testing, this method has significant advantages in cost and time. The present invention collects and analyzes the results of integrity analysis, scientifically evaluates the mechanical strength and flame retardancy of barrier explosion-proof materials under different production ratios, ensures the objectivity and accuracy of the evaluation, uses intelligent evaluation algorithms to process a large amount of data, quickly summarizes the evaluation conclusions, obtains the damage index, improves the evaluation efficiency, and sorts the explosion-proof performance results through automatic sorting technology, intuitively compares the performance under different ratios, thereby selecting the optimal material production ratio, based on the performance measurement criteria and the selection of the optimal ratio, continuously improves the production process and performance of the material, and helps to improve the safety and market competitiveness of explosion-proof materials.

[0178] Those skilled in the art will appreciate that the units, i.e., algorithm steps, of the various examples described in conjunction with this embodiment can be implemented in electronic hardware or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0179] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A method for measuring explosion-proof performance of barrier explosion-proof materials, characterized in that: The explosion-proof performance determination method comprises the following steps: S1. Build a material preparation platform based on the manufacturing process of barrier explosion-proof materials, and use the material preparation platform to simulate the production of barrier explosion-proof materials under different production ratios; S2. Use three-dimensional simulation analysis technology to build an application equipment model, add barrier and explosion-proof materials under different production ratios into the application equipment model, and trigger the preset detonation mechanism; S3. Use monitoring equipment to collect image data of the application equipment before and after detonation, and analyze the integrity of the application equipment based on comparison technology; S4. Determine the explosion-proof performance of barrier explosion-proof materials under different production ratios according to the results of the integrity analysis, generate performance measurement criteria, and select the optimal material production ratio based on the explosion-proof performance results; The method of collecting image data of the application device before and after detonation by using the monitoring device and analyzing the integrity of the application device based on the comparison technology includes the following steps: S31, adding an image acquisition device to the application device model to obtain image data of the application device before and after detonation, and using image processing technology to filter out image data that meets preset standards; S32, using an equidistant division technique to divide the image data before and after detonation into a preset number of comparison areas, and making one-to-one correspondence between the comparison areas before and after detonation; S33, using recognition processing technology to find feature points in the comparison area respectively, and using similarity quantification to quantify the similarity between the feature points to determine the integrity of the application equipment after the explosion; The method of using the recognition processing technology to find the feature points at the comparison area respectively and using the similarity quantification to determine the integrity of the application equipment after the explosion includes the following steps: S331, using recognition processing technology to search for the contour of the application device in the comparison area before and after detonation, and selecting the contour area with the largest area of ​​the application device as the feature judgment area; S332, respectively, using the upper right vertices of the feature judgment areas before and after detonation as the origin to establish a two-dimensional coordinate system to determine the width and height of the application device, and using the midpoint of the width as the projection origin to scan the pixels of the contour area from right to left using the projection method; S333, based on the projection result, two coordinates with the initial and final pixels being zero are selected to obtain the boundary conditions in the longitudinal direction of the feature judgment area, and two straight lines parallel to the longitudinal coordinate axis are fitted through the two coordinates; S334, searching for the columns of the boundary coordinates of the vertical axis direction of the feature judgment area before and after detonation respectively, and selecting two coordinate positions at the bottom edge of the feature judgment area, connecting the coordinate positions with a straight line to obtain a rectangular area; S335, applying the projection method to the rectangular area to count the number of pixels and the grayscale values ​​of each column from left to right, and determining the average grayscale value of each column of pixels and the number of pixels with zero grayscale values ​​to obtain feature points; S336, using similarity judgment technology to quantify the similarity between the feature points before and after detonation, and judging the integrity of the application device after the explosion; The similarity determination technology is used to quantify the similarity between the feature points before and after the detonation, and the integrity of the application device after the detonation is determined, including the following steps: S3361, plotting the coordinate values ​​corresponding to the feature points before and after detonation into the vector space, and assigning weights to the feature points before and after detonation according to the weight analysis technology; S3362, obtaining the angle between the vectors based on the weight value distribution result and calculating the corresponding angle value, and judging the similarity between the feature points before and after detonation according to the angle value result; S3363. Compare the similarity with a pre-set similarity threshold. If the similarity is higher than the threshold, it is considered that the integrity of the application device after the detonation is high; if the similarity is lower than the threshold, it is considered that the damage to the application device after the detonation is serious.

2. The method for determining explosion-proof performance of barrier explosion-proof materials according to claim 1, characterized in that: The method of using the three-dimensional simulation analysis technology to build an application equipment model, adding barrier explosion-proof materials under different production ratios into the application equipment model, and triggering a preset detonation mechanism includes the following steps: S21. Use laser scanning equipment to collect the original point cloud data of the application equipment, and use point cloud processing technology to perform registration, splicing, merging and noise reduction on the original point cloud data to obtain entity point cloud data; S22, using the entity point cloud data as basic data for layered slicing processing, extracting the contour line of the application equipment, and using 3D modeling software to model the contour line to obtain an application equipment model; S23, generating a single image based on the application device image collected by the entity, constructing the relative relationship between the entity point cloud data and each image, and converting the image into a texture space and adding it to the application device model; S24. Add barrier explosion-proof materials with different production ratios produced by the material preparation platform to the application equipment model, and combine the preset detonation mechanism with the application equipment model to perform explosion simulation operations.

3. The method for determining explosion-proof performance of barrier explosion-proof materials according to claim 1, characterized in that: The calculation formula of the similarity is: ； In the formula, S similarity ( S 1, S 2) Representing feature points S 1 and feature points S The similarity between 2, n Represents the total number of feature points, υ j Indicates the first j The weight value corresponding to the feature point is σ j Indicates that after detonation j The weight value corresponding to each feature point.

4. The method for determining explosion-proof performance of barrier explosion-proof materials according to claim 1, characterized in that: The method of determining the explosion-proof performance of the barrier explosion-proof material under different production ratios according to the completeness analysis results to generate a performance determination criterion, and selecting the optimal material production ratio based on the explosion-proof performance results includes the following steps: S41. Collect the completeness analysis results of the application equipment in the application of barrier explosion-proof materials with different production ratios, and set mechanical strength and flame retardancy as the performance evaluation indicators of barrier explosion-proof materials; S42. Combine the performance evaluation index with the integrity analysis result, use the intelligent evaluation algorithm to evaluate the barrier explosion-proof material, summarize the evaluation conclusion to obtain the damage index of the barrier explosion-proof material; S43. Evaluate the explosion-proof performance of barrier explosion-proof materials under different production ratios according to the damage index, and generate measurement criteria based on the explosion-proof performance results; S44. Use automatic sorting technology to sort the explosion-proof performance results of barrier explosion-proof materials with different production ratios from high to low, and select the production ratio corresponding to the barrier explosion-proof material with the highest explosion-proof performance as the optimal material production ratio.

5. A method for measuring explosion-proof performance of barrier explosion-proof materials according to claim 4, characterized in that: The method of combining the performance evaluation index with the integrity analysis result, using the intelligent evaluation algorithm to evaluate the barrier explosion-proof material, and summarizing the evaluation conclusion to obtain the damage index of the barrier explosion-proof material includes the following steps: S421. Based on the integrity analysis results, the mechanical strength and flame retardancy performance evaluation of the barrier explosion-proof material is graded, and damage assessment parameters are set according to the integrity analysis results; S422. Describe the relationship vectors between the integrity of the application equipment and the mechanical strength and flame retardancy based on the damage assessment index; S423. Based on the relationship vector, a relationship matrix is ​​constructed to represent the damage index of the barrier explosion-proof material, and the evaluation conclusions of the mechanical strength and flame retardancy are summarized to obtain the total damage index of the barrier explosion-proof material.

6. A method for measuring explosion-proof performance of barrier explosion-proof materials according to claim 5, characterized in that: The method of using the automatic sorting technology to sort the explosion-proof performance results of barrier explosion-proof materials with different production ratios from high to low, and selecting the production ratio corresponding to the barrier explosion-proof material with the highest explosion-proof performance as the optimal material production ratio includes the following steps: S441. Standardize the explosion-proof performance results of barrier explosion-proof materials with different production ratios, and use the topological sorting algorithm to generate an initial sequence plan; S442, introducing a greedy algorithm based on the initial sequence scheme to set a sorting rule from high to low, and using the crossover and mutation operations of the greedy algorithm to obtain a sorting result of the explosion-proof performance results; S443. Select the explosion-proof performance result with the highest ranking from the ranking results, search for the production ratio parameters of the corresponding barrier explosion-proof material, and use the production ratio parameters as the optimal production ratio parameters.

7. A system for measuring explosion-proof performance of barrier explosion-proof materials, used to implement the method for measuring explosion-proof performance of barrier explosion-proof materials according to any one of claims 1 to 6, characterized in that: The explosion-proof performance determination system of barrier explosion-proof materials includes an explosion-proof material production simulation module, an explosion-proof material detonation simulation module, an equipment integrity analysis module and a material production ratio selection module; The explosion-proof material production simulation module, the explosion-proof material detonation simulation module, the equipment integrity analysis module and the material production ratio selection module are connected in sequence; The explosion-proof material production simulation module is used to build a material preparation platform based on the barrier explosion-proof material manufacturing process, and use the material preparation platform to simulate the production of barrier explosion-proof materials under different production ratios; The explosion-proof material detonation simulation module is used to build an application equipment model using three-dimensional simulation analysis technology, add barrier explosion-proof materials under different production ratios into the application equipment model, and trigger a preset detonation mechanism; The device integrity analysis module is used to collect image data of the application device before and after detonation using the monitoring device, and analyze the integrity of the application device based on the comparison technology; The material production ratio selection module is used to determine the explosion-proof performance of barrier explosion-proof materials under different production ratios according to the completeness analysis results, generate performance measurement criteria, and select the optimal material production ratio based on the explosion-proof performance results.

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