A non-destructive characterization method of explosive small component migration degree based on mu CT

Abstract

The application provides a nondestructive characterization method for migration degree of small components of explosives based on mu CT, comprising the following steps: step one, determining test conditions; step two, obtaining images of a propellant column by mu CT and distinguishing components; step three, calculating initial parameters before a thermal aging test; step four, calculating characteristic quantities in a thermal aging process; step five, confirming aging time when small component n migrates out of the propellant column; step six, calculating characteristic quantities at the end of migration; and step seven, establishing a migration degree characterization model. The method of the application takes mu CT as a technical means, takes gray values as a basis for distinguishing, combines porosity and proportion of characteristic components, calculates characteristic quantity values of the initial state of the propellant column, the thermal aging process and the end of migration, establishes a migration degree characterization model for the whole cycle of thermal aging of the propellant column, and can realize nondestructive characterization of the migration degree of small components in the propellant column.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of explosives and relates to small component migration in explosive grain, in particular to a nondestructive characterization method for small component migration degree of explosives based on μCT. BACKGROUND

[0002] Explosives are the energy source for killing and destroying warheads. In order to improve the performance of explosives, small components such as binders, plasticizers and desensitizers are added to the energetic components to improve the mechanical properties, process properties and safety performance. In the long-term storage process, the small molecular components with low melting point in the explosive formula will produce phase transition and dissolution due to temperature and aging effect, and will produce "surface-seeking" migration under the push of concentration difference or pressure difference, and crystallization and oil seepage may occur on the surface of the explosive grain. Due to the migration and seepage of small components of explosives, pores may be produced in the interior of the explosive grain, making the explosive locally loose and brittle, affecting the structural integrity and mechanical properties of the explosive grain, and the migration and seepage of desensitizer small components will also cause the sensitization of explosives and increase the sensitivity, increasing the use risk. The migration degree of small components in explosive grain is defined as migration degree, and the research on the characterization method of small component migration degree can provide technical support for safety failure analysis, formula design, safe and reliable use and the like of explosive charge.

[0003] Currently, the change amount is mostly used to represent the migration degree in the field of explosives, which can be divided into non-destructive representation and destructive representation. At present, the non-destructive representation mainly includes: 1. Taking the weight increase amount as the characteristic quantity, the substance migrated to the surface of the grain is wrapped with filter paper (or glassware is used to collect) outside the grain, and the weight change of the filter paper (or the ware) before and after the component migration is measured by using a precision electronic balance; 2. Taking the overall weight loss rate of the grain as the characteristic quantity, the weight change of the grain before and after the component migration is measured by using a precision electronic balance; 3. Taking the content of the characteristic element of the substance migrated to the surface of the grain as the characteristic quantity, the content change of the characteristic element (such as N element and F element) before and after the component migration is measured by using an X-ray photoelectron spectrometer (XPS); 4. Taking the content of the surface migration component as the characteristic quantity, the content change of the substance migrated to the surface of the grain is measured by using gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography (HPLC) or near infrared spectroscopy and other technical means; 5. Other auxiliary means: the surface morphology change of the grain is observed by using a scanning electron microscope (SEM). The current non-destructive representation method only studies the overall weight loss, the substance migrated to the surface of the grain and the morphology of the surface of the grain, and cannot analyze the migration degree of the small component in the grain. Since the distribution depth of the component in the grain is different, it is possible that there is only migration phenomenon in the grain at the initial stage of migration, and the phenomenon has not migrated to the surface of the grain, so it is urgent to develop a representation method which can comprehensively analyze the migration degree of the grain in the whole period of thermal aging. In view of the disadvantages of the non-destructive representation, the destructive representation cuts the grain into thin slices or turns it into powder according to a certain thickness under different migration degrees, and analyzes the content of each range by using HPLC and other technical means, which can detect the components in the grain, but cannot study the migration degree in the whole period of the same grain, and the cutting or turning has a certain thickness, which leads to a small number of measurement points and limits the representation accuracy of the migration degree. In addition, the non-destructive representation and the destructive representation both take the change amount of the component as the characteristic quantity, and cannot directly represent the degree of migration. SUMMARY

[0004] In view of the deficiencies in the prior art, the purpose of the present application is to provide a μCT-based non-destructive representation method for the migration degree of small components of explosives, so as to solve the technical problem that there is no non-destructive, whole period and intuitive small component migration representation method in the field of explosives in the prior art.

[0005] In order to solve the above technical problems, the present application adopts the following technical solutions:

[0006] A μCT-based non-destructive representation method for the migration degree of small components of explosives, which comprises the following steps:

[0007] Step 1, determine the test conditions;

[0008] Step 2, μCT obtains the grain image and separates the components;

[0009] Step three, calculate the initial parameters before the heat aging test:

[0010] Step four, calculate the characteristic quantity during the heat aging process;

[0011] Step five, confirm the aging time when the small group component n migrates out of the propellant column;

[0012] Step six, migration end characteristic quantity calculation;

[0013] Step seven, establish the migration degree representation model.

[0014] Compared with the prior art, the present application has the following technical effects:

[0015] (I) The method of the present application uses μCT as a technical means, uses gray value as a distinguishing basis, combines porosity and characteristic component proportion two characteristic quantities, calculates the characteristic quantity values of the initial state of the propellant column, the heat aging process and the migration end, and establishes a migration degree representation model of the whole cycle of the heat aging of the propellant column, so that the migration degree of the small group component in the propellant column can be realized.

[0016] (II) The method of the present application can realize intuitive and non-destructive representation.

[0017] (III) The method of the present application obtains 720 images by scanning the whole propellant column, which greatly improves the representation accuracy compared with the representation methods such as turning or slicing. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a schematic diagram of the state of the migration of the small group component of the propellant column at each stage.

[0019] Figure 2 is a schematic diagram of obtaining the volume of the pores, the volume of the small group component n and the total volume in the propellant column.

[0020] Figure 1 and Figure 2 The components in the above two formulas refer to the small group components.

[0021] The specific content of the present application will be further explained and described in detail in combination with the following embodiments. DETAILED DESCRIPTION

[0022] It should be noted that all the basic methods in the present application, if not specially stated, all use the known basic methods in the prior art.

[0023] Micro-CT (i.e. Micro-CT, μCT) is short for micro-focus industrial CT, which generally refers to X-ray CT with a focus size less than 100 microns, and can realize nondestructive testing of the internal porosity of a propellant column based on gray value. The principle is as follows: the sample is fixed on a sample table that can rotate by 360 degrees or 180 degrees, and is rotated and scanned at a set step angle; during scanning, the X-ray energy attenuates after passing through the test piece, and the attenuated signal is received by the detector and a projection image is obtained; then, according to the linear attenuation coefficient relationship of each point of the test piece, the CT gray image is converted in proportion, the image threshold segmentation method is used to divide the pixel set in the image according to the gray level, and each subset obtained forms a region corresponding to the real scene. μCT can not only obtain a truly isotropic volume image with a spatial resolution of several microns, but also has a relatively fast image acquisition speed, which can meet the requirements of modern high-precision and fast testing. At present, μCT is mainly used for porosity in the field of explosives and propellants to realize the characterization of the damage and the internal damage evolution law of the propellant, and there is no reported method for using μCT to characterize the migration degree of small components of explosives.

[0024] According to the above technical solution, the specific embodiments of the present application are given below. It should be noted that the present application is not limited to the following specific embodiments, and any equivalent transformation based on the technical solution of the present application falls within the scope of protection of the present application.

[0025] Embodiment:

[0026] The present embodiment gives a nondestructive characterization method for the migration degree of small components of explosives based on μCT, which comprises the following steps:

[0027] Step one, determine the test conditions:

[0028] The test conditions include the thermal aging test conditions, the μCT working conditions and the initial placement position of the propellant column.

[0029] Step two, μCT obtains the propellant column image and performs component division:

[0030] According to the working conditions of μCT determined in step one, the propellant column at the initial position is measured to obtain a three-dimensional gray image; the different small components and pores of explosives show different gray values on the μCT image, and different small components and pores are determined according to the gray value range, and the rest is the main body of the propellant column.

[0031] Step three, calculate the initial parameters before the thermal aging test:

[0032] Step 301, calculate the initial porosity:

[0033] According to the gray value range of the pores, the area occupied by the pores in each image is obtained, and the ratio of the sum of the areas of the pores in all the collected images to the sum of the areas of the main bodies of the drug columns in all the images is recorded as the initial porosity R Po .

[0034] Step 302, calculate the initial volume proportion of the component:

[0035] According to the gray value range of the different components, the area occupied by the migrated small component n in each image is obtained, the sum of the areas of the specific components in all the collected images is summed as the initial volume value, the sum of the areas of the main bodies of the drug columns in all the images is summed as the total volume of the drug column, and the ratio of the two is recorded as the initial volume proportion

[0036] Step four, calculate the characteristic quantity in the thermal aging process:

[0037] In the aging period T, at the aging time t, all the collected images are obtained, the porosity in the migration process and the volume of the component n in the migration process are calculated, and the porosity of the small component n in the migration process is obtained by comparing with the total volume of the drug column And the volume proportion

[0038] Step five, confirm the aging time when the small component n migrates out of the drug column:

[0039] The volume proportion of the small component n in the migration process is compared with the initial volume proportion If , it indicates that the component has not migrated out of the drug column; if , it indicates that the component has migrated out of the drug column, and the aging time t' at this time is recorded as the aging time when the small component n migrates out of the drug column.

[0040] Step six, migration end characteristic quantity calculation:

[0041] In the interval between the adjacent two aging times, the porosity and the volume proportion remain basically unchanged, which indicates the end of migration. The porosity and the characteristic component volume proportion

[0042] Step seven, establish a migration degree representation model:

[0043] Step 701, define the initial state of the drug column before the aging test as corresponding to a migration degree of 0%.

[0044] Step 702, define the migration end as corresponding to a migration degree of 100%.

[0045] Step 703, according to the initial migration degree, the end migration degree, the initial porosity and the porosity in the migration process, the porosity is taken as a characteristic quantity to represent the migration degree in the thermal aging process

[0046] Step 704, according to the initial migration degree, the end migration degree, the initial volume ratio and the volume ratio in the migration process, the volume ratio is taken as a characteristic quantity to represent the migration degree in the thermal aging process

[0047] Step 705, since the change in porosity may be caused by other components or reasons other than the characteristic small component n, the migration degree represented by the porosity characteristic quantity may be deviated, so it is necessary to verify whether the porosity method is deviated or not based on the volume ratio method, if there is deviation, the deviation factor AM is calculated and calibrated.

[0048] Further preferably, in step 705, the deviation factor is calculated according to the ratio R of the change in the end and initial porosity volume ΔP and the ratio R of the change in the volume of the specific component If R indicates that there is deviation, the deviation factor AM is calculated If R indicates that there is no deviation, there is no need to calculate the deviation factor, and the migration degree represented by the porosity is directly used.

[0049] Step 706, the migration degree represented by the porosity is combined with the deviation factor AM and the migration degree represented by the volume ratio to construct a representation model of the whole cycle migration degree M in the aging process of the drug column.

[0050] Further preferably, in step 706, the representation model of the whole cycle migration degree M in the aging process of the drug column is:

[0051]

[0052] When t is in (0, t'), that is, the small component n has not migrated out of the drug column, the migration degree M is represented by the porosity migration degree and the deviation factor; when t is in [t', T], that is, the small component n has migrated out of the drug column, the migration degree M is represented by the volume ratio migration degree.

[0053] Application example:

[0054] The application example gives a nondestructive representation method of the migration degree of the small component of the explosive based on the μCT based on the above-mentioned embodiment, specifically, the application example takes the migration degree representation of the small component n as an example, and the application is described in detail in combination with the drawings.

[0055] Since the small component n is located at a certain depth within the propellant column, in the early stages of migration, it may only move within the column, exhibiting changes in porosity but no change in its volume fraction. Therefore, volume fraction cannot be used to characterize component migration. Thus, before the small component n migrates out of the column, porosity is used as the characteristic quantity to represent component migration. However, since changes in porosity may be caused by other components or factors besides the small component n, this method of characterizing component migration using porosity as a characteristic quantity may be biased, requiring calibration. After the small component n has migrated out of the column, volume fraction, a more accurate characteristic quantity, is used to characterize component migration.

[0056] The method specifically includes the following steps:

[0057] Step 1: Determine the experimental conditions:

[0058] (1) The thermal aging temperature is 71℃, the aging humidity is 65% (RH), the total aging time is T days (the aging end time is when the specific component does not migrate), and the time interval is 5 days.

[0059] (2) The X-ray input voltage of μCT is 75kV and the current is 133μA; the detector is set to full resolution; 720 samples are taken at 360°.

[0060] (3) Fix the drug cartridge on the base and place it at the center of rotation, and make a straight line mark at the initial X-ray scanning position.

[0061] Among them, the test conditions in (1) and (2) can be optimized according to the measured samples.

[0062] Step 2: μCT acquires images of the drug column and distinguishes its components.

[0063] Before thermal aging, the intact drug column was scanned according to the μCT test conditions, and the results were as follows: Figure 1 The initial state of the explosive charge is shown in (a). Based on the N components in the explosive formulation... Figure 1 In the N=4) component, the characteristics of the components and different gray values ​​in the image are used to distinguish the components. The gray value range of the pores is defined as G. p [g p1 ,g p2 ](like Figure 1 (as shown in the white area in (b) of the image), g p1 and g p2 These represent the upper and lower limits of the pore grayscale, respectively; the grayscale range of sub-segment n is G. n [g n1 ,g n2 ], g n1 and g n2 These represent the upper and lower limits of the grayscale values ​​of the subgroup n; the rest are the main body of the drug column.

[0064] Step three, initial characteristic quantity calculation:

[0065] The analysis and calculation of the above component separation test results are as follows, wherein the volume of the pores, the volume of the small component n, and the total volume are obtained as shown in the following table. Figure 2

[0066] Step 301, calculation of initial porosity:

[0067] The sum of the pore areas in the 720 DR images with the gray value in the G p range is obtained, denoted as the initial volume of the pores V The sum of the main body areas in the 720 DR images is obtained, denoted as the total volume V, and then the initial porosity P

[0068]

[0069] Step 302, initial volume proportion of the small component n:

[0070] The sum of the areas of the small component n in the 720 DR images with the gray value in the G n range is obtained, denoted as the initial volume of the small component n V Then the initial volume proportion of the small component n is

[0071] Step four, calculation of characteristic quantities in the thermal aging process:

[0072] At the aging time t∈(0,T], the sum of the pore areas in the 720 DR images with the gray value in the G p range is obtained, denoted as the volume of the pores in the migration process V Then the porosity in the migration process is The sum of the areas in the 720 DR images with the gray value in the G n range is obtained, denoted as the volume of the small component n in the migration process V Then the volume proportion of the small component n in the migration process is

[0073] Step five, confirmation of the aging time when the small component n migrates out of the drug column:

[0074] The volume of the small component n in the migration process V is compared with the initial volume proportion If , it indicates that the component has not migrated out of the drug column; if , it indicates that the component has migrated out of the drug column, and the aging time t' at this time is recorded as the aging time when the small component n migrates out of the drug column.

[0075] Step six, calculation of characteristic quantities at the end of migration:

[0076] ​During the time interval between two consecutive aging cycles, the porosity and volume fraction remained essentially unchanged, indicating the migration was considered complete. At the end of the migration, the grayscale values ​​in 720 DR images were obtained at G... p The sum of the pore areas within the range is denoted as the pore migration termination volume. And calculate the porosity at the end of migration. Obtain the grayscale values ​​in G from 720 DR images n The sum of the areas within the range is denoted as the final volume of the migration of group n. And calculate the percentage of the final migration volume of group n.

[0077] Step 7: Establish a mobility representation model:

[0078] The migration of components is characterized by a combination of porosity and the volume fraction of small components (n).

[0079] Step 701: Define the migration degree corresponding to the initial state of the propellant column before the aging test as 0%, i.e., the porosity is 0%. migration during time Volume ratio migration during time

[0080] Step 702: Define the migration degree corresponding to the end of migration as 100%, i.e., the porosity is 100%. migration during time Volume ratio Mobility M VnE =100%.

[0081] Step 703, based on the two known points and Establish mobility M with porosity as a characteristic quantity Pt The representation model is as follows: Right now Where R Pt It was calculated in step five.

[0082] Step 704, based on the two known points and Establish mobility M with volume percentage as a characteristic quantity Vnt The representation model is as follows: Right now in It was calculated in step four.

[0083] Step 705, since the porosity change can be caused by other components or reasons other than the small component n, the migration degree characterization method characterized by porosity may be biased, but the volume fraction method is accurate, so first verify whether the porosity method is biased or not, if it is biased, then calibrate. That is, compare the change ratio of the porosity volume at the end of migration and the initial time and the volume change ratio of the small component n If indicates a deviation, then calculate the deviation factor If then it indicates no deviation, and there is no need to calculate the deviation factor, and the porosity characterization migration degree can be directly used.

[0084] Step 706, the full-cycle migration degree M characterization model during the thermal aging process of the drug column is as follows:

[0085]

[0086] When t∈(0,t′), that is, the small component n has not migrated out of the drug column, the migration degree M is characterized by the porosity migration degree and the deviation factor; when t∈[t′,T], that is, after the small component n migrates out of the drug column, the migration degree M is characterized by the volume fraction migration degree.

Claims

1. A method for non-destructive characterization of the migration degree of small components of explosives based on μCT, characterized in that, The method comprises the following steps: Step one, determine the test conditions: The test conditions include thermal aging test conditions, μCT working conditions and initial placement position of the propellant grain; Step two, μCT obtains the grain image and carries out component division: According to the working conditions of μCT determined in step one, the grain at the initial position is measured to obtain a three-dimensional gray scale image of the grain; different small groups and pores are determined according to the gray value range, and the rest is the main body of the grain; Step three, calculate the initial parameters before thermal aging test: Step 301, calculate the initial porosity: According to the gray value range of the pores, the area occupied by the pores in each image is obtained, and the ratio of the sum of the areas of the pores in all the images to the sum of the areas of the main bodies of the drug columns in all the images is recorded as the initial porosity Step 302, calculate the initial volume ratio of the component: According to the gray value range of different components, the area occupied by the migrated small component n is obtained in each image, the sum of the specific component areas of all collected images is taken as the initial volume value, the sum of the main body areas of all images is taken as the total volume of the drug column, and the ratio of the two is taken as the initial volume ratio Step four, calculate the characteristic quantity in the thermal aging process: At aging time t in aging period T, all the images collected are obtained, the porosity in the migration process and the volume of component n in the migration process are calculated, and the porosity of small component n in the migration process is obtained by comparing the total volume of the drug column and the volume ratio Step five, confirm the aging time when the small component n migrates out of the grain: Volume fraction of the small component n during migration Volume fraction of the initial If, in comparison, Indicates that the component has not migrated out of the pellet; if Indicates that the component has migrated out of the pellet, and the aging time t' at this time is recorded as the aging time when the small component n migrates out of the pellet; Step six, calculate the migration end characteristic quantity: If the porosity and volume percentage remain unchanged between two adjacent aging time intervals, the migration is over; record the porosity at this time and the characteristic component volume percentage Step seven, establish the migration degree representation model: Step 701, define the migration degree corresponding to the initial state of the grain before the aging test as 0%; Step 702, define the migration degree corresponding to the migration end as 100%; Step 703, according to the initial migration degree, the end migration degree, the initial porosity and the porosity in the migration process, taking the porosity as a characteristic quantity to represent the migration degree in the thermal aging process At step 704, according to the initial migration degree, the end migration degree, the initial volume ratio, and the volume ratio in the migration process, the migration degree in the heat aging process is represented by taking the volume ratio as a characteristic quantity Step 705, take the volume ratio method as the benchmark to verify whether the porosity method has deviation, if there is deviation, calculate the deviation factor ΔM and calibrate; Step 706, using the degree of migration characterized by porosity as a characteristic quantity The deviation factor AM and the degree of migration characterized by the volume ratio The characterization model of the degree of migration M in the whole cycle of the aging process of the pharmaceutical column is constructed comprehensively.

2. The non-destructive characterization of the migration of small components of explosives based on μCT according to claim 1, characterized in that, In step 705, the deviation factor is calculated according to the ratio R of the change of the final and initial pore volume ΔP and the ratio R of the change of the final and initial volume of the specific component If indicates deviation, the deviation factor is calculated If indicates no deviation, no deviation factor is calculated and the porosity is directly used to represent the migration degree.

3. The non-destructive characterization of the migration of small components of explosives based on μCT according to claim 1, characterized in that, In step 706, the representation model of the migration degree M in the whole cycle of the grain aging process is: When t ∈ (0, t ′ ), i.e. the small component n does not migrate out of the drug column, the migration degree M is represented by the porosity migration degree and the deviation factor; when t ∈ [t ′ , T], i.e. the small component n migrates out of the drug column, the migration degree M is represented by the volume proportion migration degree.

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