Digital modeling method for X-ray chromatography defect detection of solid rocket engine

Abstract

The invention provides a digital modeling method for X-ray chromatography defect detection of a solid rocket engine, and belongs to the technical field of digital modeling and X-ray chromatography. Comprising the following steps: 1, constructing a solid rocket engine and defect digital model database; 2, integrating the solid rocket engine and the defect digital model; 3, performing X-ray chromatography simulation on the integrated digital model by using a computer simulation technology; and 4, matching the X-ray chromatography data with the digital model. According to the method, a digital model database of the solid rocket engine and the defects of the solid rocket engine is established, a real physical model is replaced by a digital model, and an actual X-ray chromatography detection process is replaced by X-ray chromatography computer analogue simulation. According to the method, the cost can be reduced, the safety can be improved, the testing efficiency and flexibility can be improved, and a new solution is provided for the solid rocket engine.

Description

Technical Field

[0001] The invention belongs to the technical field of digital modeling and X-ray tomography, and in particular relates to a digital modeling method for X-ray tomography defect detection of solid rocket engines. Background Art

[0002] Solid rocket engines are core equipment in the aerospace field and have broad application value in national defense and civil aviation. Their performance and safety are crucial to the success of the mission. Due to the complex internal structure of the engine, common defects will have a significant impact on its stability and reliability. X-ray tomography technology, as a non-destructive detection method, can perform high-precision grayscale reconstruction of the internal structure of solid rocket engines and intuitively display the distribution and characteristics of internal defects. The application of this technology has significantly improved the ability to discover and characterize defects, providing strong technical support for optimizing the charging process, improving the manufacturing process, and improving the overall quality of solid rocket engines. It has important engineering application value.

[0003] However, there is no unified standard process for X-ray tomography defect detection of solid rocket engines. To solve this problem, the traditional method usually designs and manufactures standard test pieces for detection and verification. The solid rocket engine standard test piece is a device that simulates the structure and density distribution of the real product, in which simulated defects of various specifications are preset to test and verify the performance of the X-ray tomography system. However, this method has the following problems:

[0004] High cost: The production of standard engines requires a lot of materials and human resources, especially for test pieces with complex structures or special materials, the cost is even greater.

[0005] Complex operation: The design, production and subsequent maintenance of standard test pieces are cumbersome and require highly specialized technical support, and require high skills of operators.

[0006] Safety issues: Using real or simulated solid rocket motor test pieces during testing may pose potential safety risks, especially in the production and testing of propellant test pieces.

[0007] Inefficiency: The cycle from specimen production to test verification is long, which makes it difficult to meet the needs of rapid response testing and is not conducive to product process optimization and rapid performance improvement. Summary of the invention

[0008] To solve the above problems, the present invention proposes a digital modeling method for X-ray tomography defect detection of solid rocket engines. This method establishes a digital model database of solid rocket engines and their defects, uses digital models to replace real physical models, and uses X-ray tomography computer simulation to replace the actual X-ray tomography detection process. This method can not only reduce costs and improve safety, but also improve the efficiency and flexibility of testing, providing a new solution for solid rocket engines.

[0009] The specific technical solution is as follows: A digital modeling method for X-ray tomography defect detection of solid rocket engines, comprising the following steps:

[0010] First step, construct a digital model database of solid rocket engines and defects;

[0011] Second step, integrate the digital models of solid rocket engines and defects;

[0012] Third step, use computer simulation technology to perform X-ray tomography simulation on the integrated digital model;

[0013] Fourth step, match the X-ray tomography data with the digital model.

[0014] The present invention has the following beneficial effects:

[0015] 1. Greatly reduce the production cost of test pieces: Completely replace the production of physical standard sample engines through digital modeling technology, save the consumption of expensive materials and the cost of repeated processing. The digital model can be reused infinitely, eliminating the customized production cost of test pieces with complex structures.

[0016] 2. Simplify the operation process and technical dependence: Built-in standardized defect model library and parametric modeling tools, no need to manually design the structure of test pieces, and the automated simulation process reduces the dependence on professional skills of X-ray detection. Ordinary technicians can operate after short-term training.

[0017] 3. Achieve low-risk detection throughout the process: Virtual simulation completely avoids the explosion and leakage risks of test pieces during physical charging, transportation, and detection. There is no contact with physical test pieces, which is especially suitable for quality inspection of hazardous materials.

[0018] 4. Build an efficient and agile detection system: Digital models can be generated and iterated immediately, support batch simulation of multi-parameter combinations, and accelerate the iteration speed of process optimization. Description of the Drawings

[0019] Figure 1 It is a flow chart of a digital modeling method for X-ray tomography defect detection of solid rocket engines;

[0020] Figure 2Schematic diagram of the X-ray tomography simulation imaging principle for a solid rocket motor model with defects. Specific implementation manners

[0021] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other. To achieve the above objectives, the present invention adopts the following technical solutions.

[0022] The present invention will be further described below in conjunction with the drawings and examples.

[0023] As Figure 1 shown, the present invention provides a digital modeling method for X-ray tomography defect detection of a solid rocket motor, which is divided into the following four steps: First step, constructing a digital model database of the solid rocket motor and defects; Second step, integrating the digital models of the solid rocket motor and defects; Third step, using computer simulation technology to perform X-ray tomography simulation on the integrated digital model; Fourth step, matching the X-ray tomography data with the digital model.

[0024] First step, constructing a digital model database of the solid rocket motor and defects. It includes: The digital model includes two major parts: a geometric model and a material model. The geometric model is a three-dimensional shape description of the real physical model, and it is necessary to use CAD software to separately model the solid rocket motor and the defects. The material model is used to describe the material properties, especially the key attributes required for X-ray tomography detection, including material composition, material density, and linear attenuation coefficient.

[0025] The main components of the solid rocket motor from the outside to the inside are the casing, the insulation layer, the liner, and the propellant grain. The casing is the external structure of the solid rocket motor, which is used to provide necessary mechanical support and sealing, withstand internal pressure and the action of the external environment, and is usually made of high-strength metal or composite materials. The insulation layer is a layer of material located between the casing and the liner, which is used for heat insulation and preventing direct damage to the casing by high-temperature gas flow, and is usually made of rubber-based or composite insulation materials. The liner is a layer of material covering the insulation layer, which plays a role in sealing and bonding, and is usually made of highly elastic and heat-resistant polymer materials. The propellant grain has cylindrical or star-shaped grooves in the middle to control the burning rate and thrust curve, and is composed of solid propellant, which usually includes oxidizer, reducing agent, binder, and additive.

[0026] Defects in solid rocket motors mainly include pores, inclusions, cracks, and debonds. Pores are cavities or bubbles formed during the manufacturing process of materials. Inclusions are defects formed by foreign particles mixing into the materials. Cracks are separations of materials caused by stress concentration or thermal shock. Debonding is manifested as the separation of the interface layer, usually in the form of gaps along the bonding interface. Pores, cracks, and debonds are all gases, while inclusions are materials with a density different from that of the matrix material.

[0027] In the second step, integrate the digital models of the solid rocket motor and the defects. Integrate the digital models of the solid rocket motor and the defects to form a complete digital model containing typical defects. This process uses a rule-based random distribution method to introduce different types of defects into the engine model according to specific rules and distribution patterns, so as to simulate the defect distribution in a real engine.

[0028] The rule-based random distribution method is used to distribute defects (pores, inclusions, cracks, and debonds) into different parts (shell, insulation layer, liner, and grain) of the solid rocket motor. The defects are reasonably arranged according to the following two rules:

[0029] Distribution area rule: According to the functions and manufacturing processes of each part of the engine, determine the possible distribution ranges of each type of defect in different locations. Pores and inclusions usually appear in the grain and liner, while cracks and debonds usually appear at the interfaces of the shell, liner, and grain.

[0030] Size and shape rule: The size of each defect needs to meet certain engineering design standards. The selection of the defect shape can also be randomly distributed according to its geometric characteristics in practice. Pores generally appear as spherical or irregular elliptical shapes, the shapes of inclusions are usually irregular, and may be spherical, cubic, or other geometric shapes. Cracks are usually linear defects, and their shapes can be straight, curved, or reticular. The shape of debonding usually appears as a thin layer and is distributed along the material interface.

[0031] Under the condition of following the above rules, randomly distribute defects in the solid rocket motor.

[0032] Randomly generate defect positions: According to the defect distribution area rule, randomly generate the positions of defects in each component of the engine. Defect size and shape assignment: According to the size and shape rules, randomly assign the specific parameters of the defects at each defect position.

[0033] The integrated digital model will include the complete structure of the solid rocket motor and all the introduced defects. This model not only has high-precision geometric information but also can accurately reflect the distribution state of defects in the actual engine.

[0034] In the third step, computer simulation technology is used to perform X-ray tomography simulation on the integrated digital model. Due to the characteristic that X-rays attenuate to different degrees for different materials, the integrated model cannot be a simple superposition of the solid rocket engine model and the defect model. Traditional X-ray tomography simulation methods usually require modifying the model. For example, for a solid rocket engine model with defects, the defect model needs to be removed from the solid rocket engine model first, separating the defect and the basic structure, and then separately simulating the X-ray tomography data of the solid rocket engine model after removing the defect and the removed defect model, and then synthesizing them. This method is relatively cumbersome, requires multiple operations, and the reusability of the model after removing the defect is poor.

[0035] The present invention proposes a new method. Based on the penetration attenuation principle of X-rays, without any modification to the original model, directly inputting the solid rocket engine model and the defect model can generate X-ray tomography data. This method not only simplifies the simulation process but also improves the reusability of the model.

[0036] As Figure 2 shown, it is a schematic diagram of the principle of X-ray tomography simulation imaging for a solid rocket engine model with defects. Let the basic model be A and the defect model be B, and the basic model is a solid rocket engine model without defects. Taking two rays L1 and L2 as examples, ray L1 passes through the defect, and ray L2 does not pass through the defect. The incident light intensities of both rays are I0. According to the Beer-Lambert law, the transmitted light intensities 、 of the two rays after attenuation are respectively:

[0037] ,

[0038] ,

[0039] In the formula, 、 are the linear attenuation coefficients of the basic model A and the defect model B respectively, are the penetration distances of the rays as Figure 2 shown respectively.

[0040] The attenuation of the ray has a negative exponential relationship with the sum of the products of the linear attenuation coefficients of each material and the penetration distance. This relationship can be utilized to get rid of the limitation of modifying the basic model A in the traditional method. Even if there is an overlapping part between the basic model A and the defect model B, it does not affect the simulation result. The new calculation method is as follows. Ray L1 passes through the defect, and the calculation formula for the transmitted light intensity is:

[0041] ,

[0042] Ray L2 does not pass through the defect, but ray L2 can be considered a special case of ray L1, that is, by setting the outgoing light intensity of ray L1 in the calculation formula the outgoing light intensity of ray L2 can be obtained The calculation formula of

[0043] ,

[0044] The new calculation method simplifies to the same as the original one, but its core advantage is that there is no need to perform a separation operation on the basic model A. Instead, the basic model A and the defect model B are regarded as independent wholes respectively, so as to realize the simulation of X-ray penetration.

[0045] Step 4: Match the X-ray tomography data with the digital model. Match the generated X-ray tomography data with the digital model of the solid rocket motor for further analysis and evaluation of the defects.

[0046] By comparing the defect information in the X-ray image with the defects in the digital model, the specific location of the defect can be accurately located, and its shape, size and depth can be determined. Through comparative analysis, the quality of the X-ray tomography image can be evaluated, and possible artifacts and noises can be identified, thus improving the accuracy of image analysis. Different types of defects have different manifestations in the X-ray tomography image. By matching with the digital model, defects can be further identified and classified to provide support for subsequent decision-making.

[0047] The matching results not only provide a basis for defect location and classification, but also support for subsequent engineering analysis and decision-making. Specific applications include:

[0048] Defect assessment: Through the matched data, the potential impact of each defect on the performance of the solid rocket motor can be evaluated. For example, pores may affect the sealing performance of the engine, cracks may lead to a decrease in structural strength, and inclusions may affect the combustion efficiency, etc. According to the location and severity of the defects, their impact on the overall performance of the engine can be evaluated to further guide design optimization.

[0049] Manufacturing process improvement: By analyzing the location and distribution law of the defects, potential problems in the manufacturing process can be found, and suggestions for process improvement can be put forward. For example, defects may be related to certain production links (such as casting, welding or heat treatment), and optimizing these links can effectively reduce the generation of defects.

[0050] Quality control and inspection standards: By matching with the digital model, more accurate quality control standards can be formulated to ensure the defect detection rate and repair efficiency in actual production. For example, the allowable defect size, type and their distribution range can be set to provide clear guidance for subsequent production and detection.

[0051] Optimization Design and Verification: Using the simulation results and matching data, designers can optimize the structure of solid rocket motors, avoid serious defects in critical parts, and improve the overall reliability of the motors.

[0052] In summary, by combining the digital models of solid rocket motors and defects, the present invention provides a novel X-ray tomography defect identification method. This method uses computer simulation technology to replace traditional physical models and actual X-ray tomography, greatly reducing costs, risks, and improving the flexibility and repeatability of testing, providing a more efficient, safer, and more economical solution for equipment manufacturing in fields such as national defense and civil aviation.

Claims

1. A digital modeling method for X-ray tomography defect detection of solid rocket motors, characterized in that It includes the following steps: The first step is to construct a digital model database of solid rocket engines and defects; The second step is to integrate the digital models of solid rocket engines and defects; The third step is to use computer simulation technology to perform X-ray tomography simulation on the integrated digital model; The fourth step is to match the X-ray tomography data with the digital model.

2. A digital modeling method for X-ray tomography defect detection of a solid rocket motor according to claim 1, characterized in that, In the first step, the digital model includes a geometric model and a material model; the geometric model is a three-dimensional shape description of the real physical model, and the solid rocket engine and defects are respectively modeled using CAD software; the material model is used to describe the material properties, including the key attributes required for X-ray tomography detection, specifically including material composition, material density, and linear attenuation coefficient.

3. A digital modeling method for X-ray tomography defect detection of a solid rocket motor according to claim 2, characterized in that, In the first step, the components of the solid rocket engine from the outside to the inside are the shell, insulation layer, liner, and propellant grain; the shell is the external structure of the solid rocket engine, used to provide necessary mechanical support and sealing, withstand internal pressure and the forces of the external environment, and is made of high-strength metal or composite materials; the insulation layer is a layer of material located between the shell and the liner, used for heat insulation and preventing direct damage to the shell by high-temperature gas flow, and is made of rubber-based or composite insulation materials; the liner is a layer of material covering the insulation layer, playing a role in sealing and bonding, and is made of highly elastic and heat-resistant polymer materials; the propellant grain has cylindrical or star-shaped grooves in the middle to control the burning rate and thrust curve, and is composed of solid propellant, including oxidizer, reducer, binder, and additive.

4. A digital modeling method for X-ray tomography defect detection of a solid rocket motor according to claim 3, characterized in that, In the first step, the defects in the solid rocket engine include pores, inclusions, cracks, and debonding; pores, cracks, and debonding are all gases, and inclusions are materials with different densities from the matrix material.

5. A digital modeling method for X-ray tomography defect detection of a solid rocket motor according to claim 1, characterized in that, In the second step, the digital models of the solid rocket engine and the defects are integrated to form a digital model containing defects. The rule-based random distribution method is used to introduce different types of defects into the engine model according to specific rules and distribution methods, so as to simulate the defect distribution in the real engine.

6. A digital modeling method for X-ray tomography defect detection of a solid rocket motor according to claim 5, characterized in that The rule-based random distribution method is used to distribute the defects to different parts of the solid rocket engine, and the following two rules are used to reasonably layout the defects: Distribution area rule: According to the functions and manufacturing processes of each part of the engine, determine the distribution range of each type of defect in different parts; Size and shape rule: The size of each defect meets the engineering design standards, and the selection of the defect shape is also randomly distributed according to its geometric characteristics in practice.

7. A digital modeling method for X-ray tomography defect detection of a solid rocket motor according to claim 6, characterized in that, In the distribution area rule, pores and inclusions appear in the propellant grain and the liner, and cracks and debonding appear at the interfaces of the shell, liner, and propellant grain.

8. A digital modeling method for X-ray tomography defect detection of a solid rocket motor according to claim 6, characterized in that, In the size and shape rule, pores are spherical or irregular elliptical, the shape of inclusions is irregular, spherical, cubic, or other geometric shapes, cracks are linear defects, with shapes of straight lines, bends, or meshes, and the shape of debonding is lamellar, distributed along the material interface.

9. A digital modeling method for X-ray tomography defect detection of a solid rocket motor according to claim 1, characterized in that, In the third step, let the basic model be A and the defect model be B. The basic model is a solid rocket engine model without defects. There are two rays, L1 and L2. Ray L1 passes through the defect, and ray L2 does not pass through the defect. The incident light intensity of both rays is I0, and the transmitted light intensity after attenuation of the two rays and are calculated as follows: ， ， Wherein, and are respectively the linear attenuation coefficients of the base model A and the defect model B, are respectively the penetration distances of the rays.

10. A digital modeling method for X-ray tomography defect detection of a solid rocket motor according to claim 1, characterized in that, In the fourth step, the generated X-ray tomography data is matched with the digital model of the solid rocket motor for further analysis and evaluation of defects; by comparing the defect information in the X-ray images with the defects in the digital model, the specific location of the defect is located, and its shape, size and depth are determined. Through comparative analysis, the quality of the X-ray tomography images is evaluated, artifacts and noise are identified, and defects are further identified and classified.

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