Method for detecting density uniformity of preform

Abstract

The invention provides a method for detecting the density uniformity of a preform, which comprises the following steps of: (1) carrying out computerized tomography on the preform to be detected to obtain a CT (Computed Tomography) scanning model; (2) performing grid division on the CT scanning model in the step (1) to obtain a plurality of subdivision unit models; and (3) carrying out first data processing on the subdivision unit models in the step (2) to obtain gray values of the subdivision unit models, and carrying out second data processing on the gray values of the plurality of subdivision unit models to obtain a gray value variation coefficient of the to-be-measured preform so as to represent the density uniformity of the preform. According to the method, the internal density uniformity of the prefabricated body can be detected and analyzed under the condition that the main body structure of the prefabricated body is not damaged, and the application prospect is wide.

Description

Technical Field

[0001] The present invention relates to the technical field of preform detection, and in particular to a method for detecting density uniformity of a preform. Background Art

[0002] The most commonly used method for measuring the coefficient of variation of the volume density of preforms is the weighing method, which is to cut the preform into several preform blocks of the same size, calculate the volume density of each preform block by measuring its outer dimensions and weight, and then use the coefficient of variation calculation formula to calculate the coefficient of variation of the volume density of the preform. This method not only requires destroying the integrity of the preform, but also has errors in the measurement and calculation process. It can only be applied to the random inspection of large quantities of preforms, and cannot efficiently and quickly detect the coefficient of variation of the volume density of each preform.

[0003] CN112630096A discloses a device and method for detecting uniformity of bulk density, which specifically discloses that a large number of preforms are first taken, and the bulk density of each preform is calculated. After heating for a certain period of time by a device, the surface temperature of each preform is measured, and then a linear equation of bulk density and surface temperature is calculated. Then, the preform to be measured is heated, and the surface temperature of each area is measured, which is substituted into the linear equation to calculate the bulk density of each area, and then the coefficient of variation of the bulk density of the preform to be measured is calculated; the device includes a thermal sensing device, a preform heating box, an asbestos net, an electric heating tube, thermal insulation cotton, a windproof shell, an oil bath shaker, and an image processing device.

[0004] However, this method can only characterize the uniformity of density through surface temperature, that is, it can only involve the uniformity of the volume divided by the surface, and cannot detect the uniformity of the density inside the preform.

[0005] CN115326636A discloses a device and method for detecting uniformity of a preform, the device comprising a cone needle, a normal gasket, a directional spring, a limit rod, a measuring scale, a cone needle limit ring, a cone needle baffle, a pressure sensor, a sensor fixing ring, a handle, a mechanical cylinder and a servo motor. The method first performs multiple cone punctures on the test preform to obtain a linear relationship between its volume density and pressure, then performs multiple cone punctures on the preform to be tested to obtain the pressure value of each cone puncture, and substitutes it into the above linear equation to obtain the volume density of the preform to be tested; and the number of unit layers and the number of material layers are obtained by the repeated changes in the pressure curve when the cone needle is pulled out; finally, the thickness of the preform is obtained by the scale marked on the device.

[0006] However, the cone piercing process of this method will damage the preform, making it difficult to detect the preform that is actually needed.

[0007] Therefore, it is necessary to develop a new method for detecting the uniformity of the preform so as to obtain the uniformity data of the preform without negatively affecting the preform, which is of great significance for the production and application of the preform. Summary of the invention

[0008] In order to solve the above technical problems, the present invention provides a method for detecting the density uniformity of a preform. By adopting electronic computed tomography combined with grid division and grayscale value calculation methods, it is possible to effectively detect the density uniformity of the preform without destroying the preform to be tested, and can quantitatively analyze the uniformity of the internal density of the preform.

[0009] To achieve this object, the present invention adopts the following technical solutions:

[0010] The present invention provides a method for detecting the uniformity of density of a preform, the method comprising the following steps:

[0011] (1) performing electronic computer tomography scanning on the preform to be tested to obtain a CT scanning model;

[0012] (2) meshing the CT scan model in step (1) to obtain a plurality of subdivided unit models;

[0013] (3) performing a first data processing on the subdivided unit model described in step (2) to obtain a grayscale value of the subdivided unit model, and performing a second data processing on the grayscale values ​​of a plurality of subdivided unit models to obtain a grayscale value variation coefficient of the preform to be tested, so as to characterize the density uniformity of the preform.

[0014] The present invention first performs electronic computer tomography scanning, then performs grid division, gray value calculation, and calculates the gray value variation coefficient, which can not only quantify the uniformity of the density of the preform; but also can evaluate whether the density uniformity inside the preform is uniform. Through the gray value data graph inside each subdivided unit model, the density non-uniform area inside the preform to be tested can be clearly found, and there is no need to damage the sample during the entire sampling process. The preforms used in the market can be directly tested without the need to reserve or set up the preform to be tested separately for testing; the entire testing method is convenient and easy to operate, and has high detection accuracy and broad application prospects.

[0015] The CT scanning in the present invention can utilize the different absorption and transmittance of rays by each part to collect penetration images at each angle, and then reconstruct the entity image of the object to be measured by computer calculation.

[0016] The model in the present invention is generated by calculating the ray projection data at different angles of the preform, and can truly reflect the three-dimensional internal structure of the preform.

[0017] Preferably, the subdivided unit model in step (2) is in the shape of a cube.

[0018] The present invention preferably divides the shape of the subdivided unit model into cubes, so that the thickness of the subdivided unit model observed from each dimension of the three-dimensional angle is the same, which can avoid the calculation difference of the grayscale value caused by the thickness difference at different observation angles when the three-dimensional side lengths are inconsistent, that is, the use of a cube grid can more accurately predict the uniformity of the preform density.

[0019] Preferably, the side length of the subdivided unit model in step (2) is equivalent to the thickness of the internal structural unit layer of the preform to be tested.

[0020] The internal structural unit layer of the preform to be tested of the present invention refers to the preform to be tested that uses different structural units to form unit layers during the preparation process, such as fiber cloth / fiber mesh, fiber cloth / fiber grid / fiber mesh. It is preferred that the side length of the subdivided unit model is equivalent to the thickness of the internal structural unit layer of the preform to be tested, which can better match the structure of the preform to be tested itself, and avoid the grid structure spanning more than two structural unit layers, resulting in a large density difference within the same subdivided unit model, but it is counted as one gray value, which ultimately leads to a decrease in the accuracy of the prediction.

[0021] Preferably, the side length of the subdivided unit model in step (2) is 0.1-1.5 mm, for example, it can be 0.1 mm, 0.2 mm, 0.3 mm, 0.4 mm, 0.5 mm, 0.6 mm, 0.7 mm, 0.8 mm, 1.0 mm, 1.1 mm, 1.2 mm, 1.3 mm, 1.4 mm or 1.5 mm, etc.

[0022] Preferably, in step (3), the first data processing is to calculate the grayscale value of the subdivided unit model using data processing software.

[0023] As a preferred technical solution of the present invention, the data processing software includes any one of VG Studio, Amira, Avizo, Dragonfly or Mimics, or a combination of at least two of them, wherein typical but non-limiting combinations are a combination of VGStudio and Amira, a combination of Avizo and Amira, a combination of Dragonfly and Amira, and a combination of Dragonfly and Mimics.

[0024] The present invention preferably uses the above-mentioned model and data processing software to predict and process the grayscale value, which can better correspond the grayscale value to the density of the preform.

[0025] Preferably, the second data processing in step (3) includes: calculating the average value and standard deviation of the grayscale values ​​of a plurality of subdivided unit models, and calculating the grayscale value variation coefficient of the preform to be tested based on the average value and the standard deviation.

[0026] Preferably, the calculation formula of the gray value variation coefficient in step (3) is:

[0027] C v =σ / μ Formula (1)

[0028] In formula (1): C v , gray value variation coefficient, %. σ, gray value standard deviation; μ, gray value mean.

[0029] Preferably, the grayscale value of the preform to be tested corresponding to the subdivided unit model in step (3) increases with the increase of density.

[0030] Preferably, the detection method comprises the following steps:

[0031] (1) performing electronic computer tomography scanning on the preform to be tested to obtain a CT scanning model;

[0032] (2) meshing the CT scan model of step (1) to obtain a plurality of cubic unit models with a side length of 0.1 to 1.5 mm, wherein the side length of the subdivided unit model is equivalent to the thickness of the internal structural unit layer of the preform to be tested;

[0033] (3) using data processing software to calculate the grayscale value of the subdivided unit model, wherein the data processing software includes any one of VG Studio, Amira, Avizo, Dragonfly or Mimics or a combination of at least two thereof, to obtain the grayscale value of the subdivided unit model;

[0034] Calculating the average value and standard deviation of the grayscale values ​​of several subdivided unit models, and calculating the grayscale value variation coefficient of the preform to be tested based on the average value and the standard deviation to characterize the density uniformity of the preform;

[0035] The calculation formula of the gray value variation coefficient is:

[0036] C v =σ / μ Formula (1)

[0037] In formula (1): C v , gray value variation coefficient, %; σ, gray value standard deviation; μ, gray value mean.

[0038] Compared with the prior art, the present invention has at least the following beneficial effects:

[0039] (1) Compared with the traditional X-ray detection, the method for detecting the uniformity of density of the preform provided by the present invention can realize high-precision three-dimensional imaging, fully display the internal structure of the preform, detect the uniformity of density inside the preform, and thus detect the defects inside the preform;

[0040] (2) The method for detecting the uniformity of density of a preform provided by the present invention does not need to destroy the preform to be detected, and can ensure the integrity of the product. Therefore, there is no need to set up a separate preform for detection, and the preform used in production can be directly detected, which is closer to industrial production.

[0041] (3) The method for detecting the uniformity of density of a preform provided by the present invention can fully quantify the uniformity of density, so that the uniformity of density of the preform can be compared horizontally between different products and between different batches of the same product, which makes the analysis of the product more complete;

[0042] (4) The method for detecting the density uniformity of the preform provided by the present invention does not need to measure the true density of the preform, and can also omit the process of establishing the correlation model between the true density and the grayscale value. The grayscale value can be directly used to characterize the density uniformity of the preform, and the modeling and calculation are simpler and more practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a CT model diagram of the preform provided in Example 1 of the present invention.

[0044] Figure 2 This is a CT model grid division diagram provided in Example 1 of the present invention.

[0045] Figure 3 This is a grayscale value calculation diagram of the CT model provided in Example 1 of the present invention.

[0046] Among them, a, b, c represent the front view, top view and side view of the CT model image respectively, and d is the three-dimensional model image. DETAILED DESCRIPTION

[0047] For the convenience of understanding the present invention, the present invention lists the following embodiments. It should be understood by those skilled in the art that the embodiments are only to help understand the present invention and should not be regarded as specific limitations of the present invention.

[0048] It should be understood that, in the description of the present invention, the terms "first", "second", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0049] The preform categories targeted in this specific embodiment include, but are not limited to, any one of or a combination of at least two of a carbon fiber preform, a quartz fiber preform, a silicon nitride fiber preform, an alumina fiber preform, a silicon carbide fiber preform, a carbon fiber / quartz fiber preform or a carbon fiber / silicon carbide fiber preform.

[0050] This specific embodiment provides a method for detecting the uniformity of density of a preform, and the detection method comprises the following steps:

[0051] (1) performing electronic computer tomography scanning on the preform to be tested to obtain a CT scanning model;

[0052] (2) meshing the CT scan model of step (1) to obtain a plurality of cubic unit models with a side length of 0.1 to 1.5 mm, wherein the side length of the subdivided unit model is equivalent to the thickness of the internal structural unit layer of the preform to be tested;

[0053] (3) using data processing software to calculate the grayscale value of the subdivided unit model, wherein the data processing software includes any one of VG Studio, Amira, Avizo, Dragonfly or Mimics or a combination of at least two thereof, to obtain the grayscale value of the subdivided unit model;

[0054] Calculating the average value and standard deviation of the grayscale values ​​of several subdivided unit models, and calculating the grayscale value variation coefficient of the preform to be tested based on the average value and the standard deviation to characterize the density uniformity of the preform;

[0055] The calculation formula of the gray value variation coefficient is:

[0056] C v =σ / μ........................Formula (1)

[0057] In formula (1): C v , gray value variation coefficient, %; σ, gray value standard deviation; μ, gray value mean.

[0058] Examples 1 to 8

[0059] Embodiments 1 to 8 respectively provide a method for detecting the density uniformity of a preform, wherein the method performs density uniformity detection on a preform, and the thickness of the internal structural unit layer of all preforms to be detected is 0.5 mm.

[0060] Among them, Examples 1 to 4 use different types of preforms to perform tests under the same conditions.

[0061] Examples 5 and 6 use the preform of Example 1 to divide the preform into different grid sizes.

[0062] Examples 7 and 8 use the preform of Example 1 and process it through different data processing software.

[0063] The specific grid division and data processing methods of Examples 1 to 8 are shown in Table 1.

[0064] Table 1

[0065]

[0066]

[0067] like Figures 1 to 3 The CT model diagram, mesh division diagram and gray value calculation diagram of the preform of Example 1 are shown. The other embodiments are tested in the same way and will not be shown here.

[0068] It can be seen from Examples 1 to 4 that the method for detecting the uniformity of density of a preform provided by the present invention can achieve high-precision three-dimensional imaging, fully display the internal structure of the preform, and detect the uniformity of density inside the preform, thereby being able to detect defects inside the preform; and the coefficient of variation of the gray value can be used to characterize the uniformity of density inside the preform without destroying the structure of the preform, and the application prospect is broad.

[0069] By comparing Example 1 with Examples 5 to 6, it can be seen that the grid size division in Examples 5 to 6 is not performed according to the thickness of the internal structural unit layer of the preform, resulting in the coefficient of variation of the final detection density reaching 6.53% and 6.76%. This shows that the present invention can more accurately evaluate the density uniformity of the preform by preferably dividing the grid size according to the internal structural unit layer of the preform.

[0070] By comparing Example 1 with Examples 7 to 8, it can be seen that after the data processing software is replaced, the accuracy of grayscale value division decreases, which ultimately leads to an increase in the grayscale value variation coefficient compared to Example 1. This shows that the present invention preferably uses VG Studio to process the image data, which can more accurately evaluate the density uniformity of the preform.

[0071] Comparative Example 1

[0072] This comparative example provides a method for detecting the uniformity of density of a preform, and the detection method adopts X-ray scanning.

[0073] This comparative example can only qualitatively analyze the macroscopic density of the preform surface, and cannot understand the size and shape of the defects inside the workpiece.

[0074] The preforms used in Examples 1 to 4 were disassembled into 5 mm × 5 mm sizes, and the preform density of each disassembled unit was calculated by weight and volume detection methods. Then, the density variation coefficient of the entire preform was calculated and compared with the gray value variation coefficient obtained by the detection method in Examples 1 to 4.

[0075] The specific results are shown in Table 2 below.

[0076] Table 2

[0077] Example Group <![CDATA[Gray value C v (%)]]> <![CDATA[Density C v (%)]]> Example 1 3.04 7.16 Example 2 3.44 8.17 Example 3 3.97 8.59 Example 4 4.26 9.67

[0078] From Table 2 we can see that:

[0079] The method for detecting the uniformity of density of a preform provided by the present invention not only does not require the destruction of the preform, but also does not require the understanding of the true density of each part of the preform, and also does not require the establishment of a model relationship between the true density and the grayscale value. The difference between the densities can be directly characterized by the grayscale values ​​of each part, and the application prospect is broad. However, due to the particularity of the preform material, the disassembly method is prone to fiber damage and material falling during the disassembly process, the density difference detected is greater, and the accuracy of the detection is reduced.

[0080] The present invention illustrates the detailed features of the present invention through the above embodiments, but the present invention is not limited to the above detailed features, that is, it does not mean that the present invention must rely on the above detailed features to be implemented. Those skilled in the art should understand that any improvement to the present invention, equivalent replacement of the technical features selected by the present invention, addition of auxiliary technical features, selection of specific methods, etc., all fall within the protection scope and disclosure scope of the present invention.

Claims

1. A method for detecting the uniformity of density of a preform, characterized in that: The detection method comprises the following steps: (1) performing electronic computer tomography scanning on the preform to be tested to obtain a CT scanning model; (2) meshing the CT scan model in step (1) to obtain a plurality of subdivided unit models; (3) performing a first data processing on the subdivided unit model described in step (2) to obtain a grayscale value of the subdivided unit model, and performing a second data processing on the grayscale values ​​of a plurality of subdivided unit models to obtain a grayscale value variation coefficient of the preform to be tested, so as to characterize the density uniformity of the preform.

2. The detection method according to claim 1, characterized in that: The shape of the subdivision unit model in step (2) is a cube.

3. The detection method according to claim 2, characterized in that: The side length of the subdivided unit model in step (2) is equivalent to the thickness of the internal structural unit layer of the preform to be tested.

4. The detection method according to claim 2 or 3, characterized in that: The side length of the subdivided unit model in step (2) is 0.1 to 1.5 mm.

5. The detection method according to claim 1, characterized in that: In step (3), the first data processing is to calculate the gray value of the subdivided unit model using data processing software.

6. The detection method according to claim 5, characterized in that: The data processing software includes any one of VG Studio, Amira, Avizo, Dragonfly or Mimics, or a combination of at least two of them.

7. The detection method according to claim 1, characterized in that: The second data processing in step (3) includes: calculating the average value and standard deviation of the grayscale values ​​of a plurality of subdivided unit models, and calculating the grayscale value variation coefficient of the preform to be tested based on the average value and the standard deviation.

8. The detection method according to claim 7, characterized in that: The calculation formula of the gray value variation coefficient in step (3) is: v =σ / μ Formula (1) In formula (1): C v , gray value variation coefficient, %; σ, gray value standard deviation; μ, gray value mean.

9. The detection method according to claim 1, characterized in that: The grayscale value of the preform to be tested corresponding to the subdivided unit model in step (3) increases with the increase of density.

10. The detection method according to claim 1, characterized in that: The detection method comprises the following steps: (1) performing electronic computer tomography scanning on the preform to be tested to obtain a CT scanning model; (2) meshing the CT scan model of step (1) to obtain a plurality of cubic unit models with a side length of 0.1 to 1.5 mm, wherein the side length of the subdivided unit model is equivalent to the thickness of the internal structural unit layer of the preform to be tested; (3) using data processing software to calculate the grayscale value of the subdivided unit model, wherein the data processing software includes any one of VGStudio, Amira, Avizo, Dragonfly or Mimics or a combination of at least two thereof, to obtain the grayscale value of the subdivided unit model; Calculating the average value and standard deviation of the grayscale values ​​of several subdivided unit models, and calculating the grayscale value variation coefficient of the preform to be tested based on the average value and the standard deviation to characterize the density uniformity of the preform; The calculation formula of the gray value variation coefficient is: v =σ / μ Formula (1) In formula (1): C v , gray value variation coefficient, %; σ, gray value standard deviation; μ, gray value mean.

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