Preparation method of silicon carbide ceramic matrix composite material based on parameter optimization

Abstract

The present application relates to the technical field of silicon carbide ceramic material processing, and specifically to a method for preparing a silicon carbide ceramic-based composite material based on parameter optimization, comprising: preparing a silver-ammonia solution; adding carbon fibers to a sodium hydroxide solution and ultrasonically oscillating to obtain alkali-treated carbon fibers; adding the alkali-treated carbon fibers to the silver-ammonia solution and a glucose solution, heating the carbon fibers in a water bath, and then washing the treated carbon fibers until neutral to obtain pretreated carbon fibers; forming a titanium carbide layer by radio frequency magnetron sputtering, forming a silicon carbide layer by radio frequency magnetron sputtering, weaving the resulting carbon fiber cloth, obtaining a silicon carbide preform by depositing silicon carbide, and placing the silicon carbide preform in a vacuum reaction sintering furnace to prepare the silicon carbide ceramic-based composite material. The present application can optimize the temperature control of the sintering furnace and improve the mechanical properties of the silicon carbide ceramic-based composite material.

Description

Technical Field

[0001] The present application relates to the technical field of silicon carbide ceramic material processing, and in particular to a method for preparing a silicon carbide ceramic-based composite material based on parameter optimization. Background Art

[0002] Nowadays, in the preparation process of silicon carbide ceramic-based composites, temperature control affects the densification, hardness, toughness and other properties of the final prepared product. If the temperature is too high, the evaporation rate of silicon increases, resulting in the loss of silicon source, which will reduce the chance of carbon reaction between silicon and silicon carbide preform, thereby affecting the densification and uniformity of the silicon carbide ceramic-based composite material; if the temperature is too low, the reaction rate of silicon and carbon decreases, resulting in an increase in the densification treatment time, and even failure to achieve complete densification, resulting in pores in the prepared silicon carbide ceramic-based composite material, affecting the mechanical properties of the material. Therefore, too high or too low a temperature may affect the densification, hardness, toughness and other properties of the product.

[0003] Existing methods for optimizing temperature parameters in the preparation of silicon carbide ceramic-based composites include: reducing the sintering temperature by adding low-temperature sintering aids to improve the toughness and hardness of the product; and adjusting the precursor composition, densification cycles, and temperature to adapt the product to the needs of different environments. Therefore, effectively controlling the temperature parameters during the preparation of silicon carbide ceramic-based composites can improve the performance of the prepared composites.

[0004] In the process of preparing silicon carbide ceramic-based composite materials, due to the existing technologies such as additives or traditional feedback control methods to control the temperature during the preparation process, the judgment of temperature errors and the control of temperature changes in the vacuum reactor are poor, and thus the ideal temperature control effect cannot be achieved; among them, the effective control of the temperature during the melt silicon infiltration process in the preparation of silicon carbide ceramic-based composite materials will affect the evaporation rate of silicon, which may lead to the loss of silicon source and reduce the chance of carbon reaction between silicon and silicon carbide preform, thereby affecting the densification and uniformity of the silicon carbide ceramic-based composite materials and affecting the mechanical properties of the material. Summary of the Invention

[0005] In order to solve the above technical problems, the present application provides a preparation method of silicon carbide ceramic-based composite materials based on parameter optimization to solve the existing problems.

[0006] The method for preparing the silicon carbide ceramic matrix composite material based on parameter optimization of the present application adopts the following technical solution:

[0007] One embodiment of the present application provides a method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization, the method comprising the following steps:

[0008] Ammonia solution was added dropwise to the silver nitrate solution until the precipitate disappeared, 1-allyl-2,3-dimethylimidazolium tetrafluoroborate and ethyltriphenylphosphine tetrafluoroborate were added dropwise, and the mixture was stirred to obtain a silver ammonia solution;

[0009] The carbon fibers are added to a sodium hydroxide solution, subjected to ultrasonic vibration, and then rinsed with deionized water to obtain alkali-treated carbon fibers;

[0010] adding the alkali-treated carbon fiber to the silver ammonia solution, and adding the glucose solution, heating in a water bath, filtering out the solid, washing to neutrality, and drying to obtain the pretreated carbon fiber;

[0011] The pretreated carbon fibers are treated by radio frequency magnetron sputtering to form a titanium carbide layer, and the carbon fibers with the titanium carbide layer are treated again by radio frequency magnetron sputtering to form a silicon carbide layer, and the carbon fibers are woven to obtain a carbon fiber cloth.

[0012] Silicon carbide is deposited on carbon fiber cloth to obtain a silicon carbide preform. The silicon carbide preform is placed in a vacuum reaction sintering furnace using the melt siliconization method. The temperature difference characteristics of the local hot spot area of ​​each pixel point in the infrared image of the sintering furnace are analyzed to construct a local temperature difference value. The temperature change characteristics of the same hot spot area are analyzed based on the local temperature difference value to construct an evaporation superheat index. The cooling demand degree at each moment is analyzed based on the evaporation superheat index to construct a sintering cooling index. The temperature of the sintering furnace is controlled during the melt siliconization process. After the reaction is completed, a silicon carbide ceramic-based composite material is prepared.

[0013] In the above preparation method, the concentration of the silver nitrate solution is 0.12-0.2 mol / L, and the mass concentration of the ammonia solution is 2.2-3%.

[0014] In the above preparation method, the weight of the sodium hydroxide solution is 6.5 to 8 times the weight of the carbon fiber, the mass concentration of the sodium hydroxide solution is 20 to 30%, and the ultrasonic oscillation is performed at a power of 320 to 400 W for 1.5 to 2 hours.

[0015] In the above preparation method, the volume of the glucose solution is twice that of the silver ammonia solution, and the concentration is 0.6 to 1 times that of the silver ammonia solution. The water bath heating is performed at 52 to 60° C. for 95 to 100 minutes.

[0016] In the above preparation method, during the process of forming the titanium carbide layer, the vacuum degree before sputtering is Pa, the RF sputtering power is 850-1000 W, the deposition time is 105-120 minutes, the distance between the target and the pretreated carbon fiber is 65-80 mm, and the argon flow rate is 40-50 sccm.

[0017] In the above preparation method, during the process of forming the silicon carbide layer, the vacuum degree before sputtering is Pa, the RF sputtering power is 1100-1200 W, the deposition time is 55-70 minutes, the distance between the target and the pretreated carbon fiber is 65-80 mm, and the argon flow rate is 35-50 sccm.

[0018] In the above preparation method, the method for constructing the local temperature difference is:

[0019] Obtain infrared images at each acquisition moment in the sintering furnace;

[0020] Construct a hot spot monitoring window for each pixel in the infrared image with each pixel as the center;

[0021] Based on the grayscale difference between pixels within the hot spot monitoring window of each pixel, the local temperature difference value of each pixel is determined.

[0022] In the above preparation method, the method for constructing the evaporation superheat index is:

[0023] The local temperature difference and grayscale value of each pixel are combined as the temperature feature descriptor of each pixel. The temperature feature descriptors of all pixels in the infrared image are clustered. The cluster with the largest grayscale mean after clustering is taken as the thermal effect cluster, and each connected domain corresponding to the thermal effect cluster is recorded as the thermal effect area.

[0024] The evaporation superheat index of each heat effect zone is determined based on the local temperature difference and grayscale value of all pixels in each heat effect zone, wherein the evaporation superheat index is inversely correlated with the fluctuation of the local temperature difference of all pixels in the heat effect zone and is positively correlated with the grayscale value of the pixel.

[0025] In the above preparation method, the sintering temperature drop index is a positive fusion of the area of ​​each heat-affected zone in the infrared image at each acquisition moment and the evaporation overheating index.

[0026] In the above preparation method, the controlling of the temperature of the sintering furnace during the melt siliconizing process further comprises:

[0027] Preset the temperature range of the sintering furnace during the melt siliconizing process and calculate the interval length of the temperature range;

[0028] The product of the interval length and the normalized value of the sintering cooling index at each acquisition moment is analyzed and recorded as the temperature adjustment factor at each acquisition moment; the optimal temperature at each acquisition moment is the difference between the maximum value of the temperature range and the temperature adjustment factor.

[0029] This application has at least the following beneficial effects:

[0030] This application considers that during the reaction between the silicon carbide preform and the silicon particles, the evaporation process of silicon may cause hot spots. Therefore, a local window is constructed with each pixel point in the collected infrared thermal imaging image as the center, and the change characteristics of the pixel value within the local window where each pixel point is located are analyzed to obtain a local temperature difference value representing the temperature uniformity of the local area during the reaction process. The beneficial effect of this is that it can fully consider the temperature change characteristics of the hot spot boundary generated in the infrared thermal imaging image, and avoid the influence of the hot spot boundary area on the judgment of temperature uniformity during the reaction process.

[0031] Secondly, based on the pixel values ​​and corresponding local temperature difference values ​​in the infrared thermal imaging image, the pixels are clustered and analyzed. Based on the results of the cluster analysis, the heat-affected area with temperature values ​​similar to the temperature uniformity characteristics is obtained. The possibility of overheating in the local area is analyzed based on the temperature uniformity characteristics and temperature values ​​in the heat-affected area. The beneficial effect is that the comparison and analysis relationship between the temperature value and the temperature uniformity characteristics can accurately reflect the possibility of the generation of the hot spot area at the pixel location.

[0032] Secondly, based on the evaporation overheating index of the heat effect zone, the current overheating degree is analyzed to construct a sintering cooling index. The overheating situation in the vacuum reactor is reflected by the sintering cooling index. Its beneficial effect is that the evaporation overheating index of the heat effect zone and the pixel points in the heat effect zone can accurately obtain the formation of hot spots in the vacuum reactor, and then accurately judge the temperature control in the furnace, accurately control the temperature during the reaction process, solve the problem in the existing technology that the mechanical properties of the material are reduced due to silicon evaporation caused by excessive temperature, and improve the mechanical properties of the prepared silicon carbide ceramic-based composite materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0034] Figure 1 A flow chart of the steps of the method for preparing silicon carbide ceramic-based composite materials based on parameter optimization provided in this application;

[0035] Figure 2 Schematic diagram of infrared image acquisition of sintering furnace during melt siliconization process;

[0036] Figure 3 Schematic diagram of the sintering furnace temperature control process during the melt siliconizing process. DETAILED DESCRIPTION

[0037] To further illustrate the technical means and effects employed by this application to achieve the intended invention objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, details the method for preparing a silicon carbide ceramic-based composite material based on parameter optimization proposed in this application, including its specific implementation, structure, features, and effects. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0038] Unless otherwise defined, terms such as "comprises," "comprising," or any other variants thereof are intended to encompass non-exclusive inclusion, such that a circuit structure, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such article or device. In the absence of further restrictions, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the article or device comprising the element. In addition, the term "and\or" as used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application pertains.

[0039] The specific scheme of the preparation method of the silicon carbide ceramic-based composite material based on parameter optimization provided by the present application is described in detail below with reference to the accompanying drawings.

[0040] An embodiment of the present application provides a method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization. For details, please refer to Figure 1 , the method comprises the following steps:

[0041] : Prepare a silver ammonia solution. Add a 2.2-3% ammonia solution dropwise to a 0.12-0.2 mol / L silver nitrate solution. After a brown precipitate appears, continue to add the ammonia solution dropwise until the precipitate disappears. Then, add 1-allyl-2,3-dimethylimidazolium tetrafluoroborate in a molar amount of 2% based on the silver nitrate solution and ethyltriphenylphosphine tetrafluoroborate in a molar amount of 1% based on the silver nitrate solution, and stir evenly to obtain a silver ammonia solution. Preferably, in the three embodiments of the present application, the process parameters for preparing the silver ammonia solution are specifically set as follows:

[0042] In Example 1, the concentration of the silver nitrate solution was 0.12 mol / L, and the ammonia solution was 2.2%;

[0043] In Example 2, the concentration of the silver nitrate solution was 0.16 mol / L and the ammonia solution was 2.6%;

[0044] In Example 3, the concentration of the silver nitrate solution is 0.2 mol / L, and the ammonia solution is 3%.

[0045] Alkali-treated carbon fiber. The carbon fiber is added to a sodium hydroxide solution (6.5 to 8 times its weight and with a mass concentration of 20 to 30%), and oscillated in an ultrasonic oscillator at a power of 320 to 400 W for 1.5 to 2 hours. After filtering, the solution is rinsed multiple times with deionized water. The implementer can set the number of rinses according to actual conditions. In the embodiment of the present application, the number of rinses is 3 to obtain alkali-treated carbon fiber. Preferably, in the three embodiments of the present application, the relevant process parameters during the alkali-treated carbon fiber are specifically set as follows:

[0046] In Example 1, the carbon fiber was added to a sodium hydroxide solution with a mass concentration of 20% and a weight of 6.5 times the carbon fiber. The ultrasonic oscillator had an oscillation power of 320 W and an oscillation time of 1.5 h.

[0047] In Example 2, the carbon fiber was added to a sodium hydroxide solution with a mass concentration of 25% and a weight of 7 times the carbon fiber. The oscillation power of the ultrasonic oscillator was 360 W and the oscillation time was 1.7 h.

[0048] In Example 3, the carbon fiber was added to a sodium hydroxide solution with a mass concentration of 30% and a weight ratio of 8 times the carbon fiber. The oscillation power of the ultrasonic oscillator was 400 W, and the oscillation time was 2 h.

[0049] Pretreatment of carbon fiber. Add the alkali-treated carbon fiber obtained in step S2 to the silver ammonia solution obtained in step S1, add a glucose solution having a volume twice that of the silver ammonia solution and a concentration of 0.6 to 1 times that of the silver ammonia solution, heat in a water bath at 52 to 60°C for 95 to 100 minutes, filter out the solid, wash to neutrality, and dry to obtain pretreated carbon fiber. Preferably, in the three embodiments of the present application, the relevant process parameters during the pretreatment of the carbon fiber are specifically set as follows:

[0050] In Example 1, the concentration of the glucose solution was 0.6 times that of the silver ammonia solution, the water bath was heated at 52°C, and the heating time was 95 minutes;

[0051] In Example 2, the concentration of the glucose solution was 0.8 times that of the silver ammonia solution, the water bath was heated at 56°C, and the heating time was 97 minutes;

[0052] In Example 3, the concentration of the glucose solution is 1 times that of the silver ammonia solution, the water bath heating temperature is 60° C., and the heating time is 100 minutes.

[0053] : Weaving carbon fiber cloth. The pre-treated carbon fiber obtained in step S3 is treated by radio frequency magnetron sputtering in a radio frequency magnetron sputtering device to form a titanium carbide layer on the surface of the carbon fiber, wherein the vacuum degree before sputtering is Pa, RF sputtering power of 850-1000 W, deposition time of 105-120 min, the distance between the target and the pretreated carbon fiber of 65-80 mm, and argon flow rate of 40-50 sccm;

[0054] The carbon fiber with titanium carbide layer is treated by radio frequency magnetron sputtering in radio frequency magnetron sputtering equipment, so that silicon carbide layer is formed on the titanium carbide layer formed on the surface of carbon fiber. The vacuum degree before sputtering is Pa, RF sputtering power of 1100-1200 W, deposition time of 55-70 min, distance between target and pretreated carbon fiber of 65-80 mm, argon flow rate of 35-50 sccm;

[0055] The single layer of 0° non-woven fabric, tire net, 90° non-woven fabric, and tire net are stacked in sequence for several layers, and a relay needle punching method is used to weave a density of Preferably, in the three embodiments of the present application, the relevant process parameters for weaving the carbon fiber cloth are specifically set as follows:

[0056] In Example 1, when the pretreated carbon fiber obtained in step S1 is treated by radio frequency magnetron sputtering, the radio frequency sputtering power is 850 W, the deposition time is 105 minutes, the distance between the target and the pretreated carbon fiber is 65 mm, and the argon gas flow rate is 40 sccm;

[0057] When the carbon fiber forming the titanium carbide layer was treated by radio frequency magnetron sputtering, the radio frequency sputtering power was 1100 W, the deposition time was 55 minutes, the distance between the target and the pretreated carbon fiber was 65 mm, and the argon gas flow rate was 35 sccm;

[0058] In Example 2, when the pretreated carbon fiber obtained in step S1 was treated by radio frequency magnetron sputtering, the radio frequency sputtering power was 920 W, the deposition time was 110 minutes, the distance between the target and the pretreated carbon fiber was 73 mm, and the argon gas flow rate was 45 sccm;

[0059] When the carbon fiber forming the titanium carbide layer was treated by radio frequency magnetron sputtering, the radio frequency sputtering power was 1150 W, the deposition time was 65 minutes, the distance between the target and the pretreated carbon fiber was 73 mm, and the argon gas flow rate was 45 sccm;

[0060] In Example 3, when the pretreated carbon fiber obtained in step S1 is treated by radio frequency magnetron sputtering, the radio frequency sputtering power is 1000 W, the deposition time is 120 minutes, the distance between the target and the pretreated carbon fiber is 80 mm, and the argon gas flow rate is 50 sccm;

[0061] When the carbon fiber forming the titanium carbide layer is processed by radio frequency magnetron sputtering, the radio frequency sputtering power is 1200 W, the deposition time is 70 minutes, the distance between the target and the pretreated carbon fiber is 80 mm, and the argon gas flow rate is 50 sccm.

[0062] Preparation of a silicon carbide ceramic-based composite material. Silicon carbide is deposited on the carbon fiber cloth obtained in step S4 using chemical vapor deposition to obtain a silicon carbide preform. The silicon carbide preform is then placed in a vacuum reaction sintering furnace using a melt siliconization method. A density treatment is performed using an argon atmosphere to protect the bottom of the preform. This results in the preparation of a silicon carbide ceramic-based composite material.

[0063] In this embodiment, the specific process conditions of the chemical vapor deposition method are: temperature of 1100°C, atmosphere pressure of 3.5kPa, hydrogen flow rate of 300mL / min, argon flow rate of 320mL / min, trichloromethylsilane temperature of 40°C, and molar mass ratio of hydrogen to trichloromethylsilane of 9:1; as other implementation methods, the specific process conditions of the chemical vapor deposition method can be set by the implementer according to the actual application scenario, and this application does not impose any special restrictions on this.

[0064] In the process of placing the silicon carbide preform in a vacuum reaction sintering furnace for sintering reaction using the melt siliconizing method, the melt siliconizing temperature range is set to 1700-1800°C in this application. The melt siliconizing temperature is adjusted and controlled within this temperature range to ensure the preparation quality of the silicon carbide ceramic-based composite material. The optimization process of the optimal reaction temperature in the vacuum reaction sintering furnace is specifically as follows:

[0065] Step 1: Collect infrared images inside the vacuum reaction sintering furnace.

[0066] When the melt siliconization treatment is carried out in the vacuum reaction sintering furnace, the infrared image of the furnace is collected by a high-definition infrared thermal imager above the vacuum reaction sintering furnace in a sampling manner at equal time intervals. Since the temperature of the vacuum reaction sintering furnace is relatively high, the high-definition infrared thermal imager is a water-cooled and air-cooled dual-circulation ultra-high temperature resistant infrared thermal imager. The infrared image of the furnace obtained is a grayscale image. The grayscale value of each pixel in the image represents the thermal radiation intensity of the area in the furnace corresponding to the pixel, which can reflect the temperature. The larger the grayscale value, the higher the corresponding temperature. The time interval in this embodiment is 20s, and the collection result diagram is as follows: Figure 2 shown.

[0067] Step 2: Analyze the temperature difference characteristics of the local area of ​​each pixel in the infrared image in the sintering furnace to construct the local temperature difference value.

[0068] When the silicon carbide preform reacts with silicon particles in a vacuum reaction sintering furnace, if the temperature is too high, the evaporation rate of silicon will increase, resulting in the loss of silicon source. During the evaporation process of silicon, a large amount of heat from the surrounding will be absorbed, causing the temperature of the silicon evaporation area to rise, making the temperature of the silicon evaporation area higher than the surrounding temperature, forming a hot spot, such as Figure 2 In the white bright spot area, the larger the grayscale value, the higher the corresponding temperature. Since the temperature of the local hot spot area is higher and the temperature of other normal areas is lower than that of the hot spot area, the hot spot boundary position is affected by the temperature of the local hot spot and the normal area, resulting in a large difference in the temperature distribution within the local range of the hot spot boundary sampling point. Based on the above analysis, this application constructs a local temperature difference value to reflect the uniformity of the local temperature. The construction process of the local temperature difference value is as follows:

[0069] The window with pixel A as the center and side length L is recorded as the hot spot monitoring window of pixel A. In this embodiment, L is set to 5. Then the local temperature difference can be calculated as follows:

[0070] The local temperature difference is determined by the grayscale value differences within the hot spot monitoring window for pixel A. It should be noted that the more uniform the temperature of the vacuum reaction sintering furnace region corresponding to different pixels within the hot spot monitoring window, the less likely it is that the region is located at the boundary of the hot spot region, and therefore the larger the calculated local temperature difference.

[0071] The calculation method of the local temperature difference value provided in the embodiment of the present application is to take the sum of the reciprocal of the sum of the absolute value of the grayscale value difference between all two pixels in the hot spot monitoring window of pixel point A and 1 as the local temperature difference value of the pixel point.

[0072] It should be noted that the calculation of the local temperature difference value of each pixel is not limited to the method provided in the embodiment of the present application. For example, the difference between the ratio of the grayscale values ​​of any two pixels in the hot spot monitoring window and the value 1 is analyzed and recorded as the first difference. The larger the first difference, the greater the difference in the grayscale values ​​of the two pixels. The cumulative sum of all first differences in the hot spot monitoring window is taken as the inverse to evaluate the local temperature difference value of the central pixel of the hot spot monitoring window. For another example, the fluctuation of the grayscale value in the hot spot monitoring window is analyzed to characterize the local temperature difference value of the central pixel of the hot spot monitoring window. The result of the inverse proportional mapping of the discrete degree of the grayscale values ​​of all pixels in the hot spot monitoring window is used as the local temperature difference value of the central pixel of the hot spot monitoring window. The greater the fluctuation of the grayscale value in the hot spot monitoring window, the smaller the local temperature difference value of the central pixel of the hot spot monitoring window. The analysis of the local temperature difference value of the pixel is not limited to the method of the above example.

[0073] Step 3: Analyze the temperature change characteristics of the same hot spot area based on the local temperature difference to construct the evaporation superheat index.

[0074] The local temperature difference of each pixel in the infrared image of the vacuum reaction sintering furnace obtained through the above steps reflects the degree of difference in local temperature. For the area where the hot spot phenomenon occurs due to the evaporation of the same piece of silicon, since the density of silicon is small and the fluidity is strong after evaporation into gas, the temperature distribution in space is relatively uniform. Therefore, the grayscale values ​​corresponding to the pixels in the same hot spot area should be relatively close, so the boundaries of the same hot spot area should have relatively close temperature differences. Based on the above analysis, this application constructs an evaporation overheating index based on the local temperature difference to reflect the degree of overheating of the current hot spot area. The construction process of the evaporation overheating index is as follows:

[0075] The characteristic binary formed by the local temperature difference and grayscale value of a pixel is recorded as the temperature feature descriptor of the pixel, which is used to reflect the temperature distribution uniformity and temperature magnitude of the area in the vacuum reaction sintering furnace corresponding to the pixel. In this embodiment, the temperature feature descriptors of all pixels in the infrared image of the furnace at each acquisition moment are used as the input of the K-means clustering algorithm, and the output is the cluster corresponding to each acquisition moment. In this embodiment, the number of clusters, i.e., K, is 2, and the cluster with the largest grayscale mean within the cluster is regarded as the thermal effect cluster. It is understood that pixels belonging to the same class have similar temperature distribution uniformity and temperature. The K-means clustering algorithm is a well-known technology and will not be described in detail.

[0076] It should be noted that, in the process of clustering, the Euclidean distance between temperature feature descriptors can be used as the clustering metric distance, or the cosine similarity between temperature feature descriptors can be used as the clustering metric distance; in actual application, the implementer can use other clustering algorithms to perform the above clustering process, such as the DBSCAN clustering algorithm, etc., and this application does not impose any special restrictions on this.

[0077] Connected domain analysis is performed on the pixels of the thermal effect cluster. Since pixels belonging to the same cluster may be distributed in multiple locations, the number of regions formed by the pixels belonging to the same cluster obtained through connected domain analysis may be multiple. Each region obtained through connected domain analysis of the thermal effect cluster is recorded as the thermal effect area. Connected domain analysis is a well-known technique and will not be described in detail here.

[0078] Furthermore, the evaporation superheat index of each heat effect zone is analyzed based on the local temperature difference and grayscale value of the pixel points in each heat effect zone. The analysis process is as follows:

[0079] The evaporation superheat index of each heat-affected zone is determined based on the local temperature difference and grayscale values ​​of all pixels within the heat-affected zone. The evaporation superheat index is inversely correlated with the fluctuations in the local temperature difference across all pixels within the heat-affected zone, and positively correlated with the grayscale values ​​of the pixels. Specifically, the more uniform the temperature distribution within each heat-affected zone, the smaller the local temperature difference between pixels (i.e., the smaller the fluctuations), and the higher the temperature within the heat-affected zone (i.e., the larger the grayscale value), the more likely the heat-affected zone is to exhibit hot spots due to silicon evaporation, and the more likely it is to experience overheating. Consequently, the corresponding evaporation superheat index is higher.

[0080] The calculation method of the evaporation superheat index provided in this embodiment is:

[0081] For each thermal effect zone, the mean of the local temperature difference values ​​of all pixels in the thermal effect zone is analyzed, and the sum of the absolute value of the difference between the local temperature difference value of each pixel in the thermal effect zone and the obtained mean and 1 is used as the denominator to characterize the fluctuation of the local temperature difference value of the pixels in the thermal effect zone, that is, the degree of difference between the local temperature difference values ​​of each pixel. The larger the denominator, the greater the deviation of the local temperature difference value of each pixel in the thermal effect zone from the mean, that is, the higher the degree of fluctuation of the local temperature difference value of the pixels in the thermal effect zone;

[0082] The grayscale value of each pixel in the heat effect area is used as the numerator, the ratio of the numerator to the denominator is used as the overheating factor of each pixel, and the sum of the overheating factors of all pixels in the heat effect area is used as the evaporation overheating index of the heat effect area.

[0083] It should be noted that the analysis of fluctuations in the local temperature difference values ​​of all pixels within the thermal effect zone is not limited to the method of the above embodiment. For example, the coefficient of variation of the local temperature difference values ​​of all pixels within the thermal effect zone can be analyzed, and the cumulative sum of the ratios of the grayscale values ​​of each pixel within the thermal effect zone to the coefficient of variation can be used as the evaporation superheat index of the corresponding thermal effect zone. For another example, the evaporation superheat index within the thermal effect zone can also be analyzed by multiplying the grayscale values ​​of each pixel within the thermal effect zone by the local temperature difference values, and then accumulating the result as the evaporation superheat index of the thermal effect zone. That is, the larger the local temperature difference value of the pixels within the thermal effect zone, the more uniform the temperature distribution, and the higher the grayscale value within the thermal effect zone, the larger the evaporation superheat index of the corresponding thermal effect zone. The implementer can decide how to analyze and calculate the evaporation superheat index of the thermal effect zone based on the actual application scenario.

[0084] Step 4: Analyze the cooling demand at each moment based on the evaporation superheat index to construct the sintering cooling index.

[0085] In a vacuum reaction sintering furnace, the larger the area of ​​the hot spot area, the higher the temperature in the furnace, the greater the degree of silicon evaporation, and the lower the chance of silicon reacting with carbon in the silicon carbide preform, thereby affecting the densification and uniformity of the material. At this time, the vacuum reaction sintering furnace should be cooled. At the same time, the evaporation overheat index at each moment obtained in the above steps reflects the formation of the hot spot area in the vacuum reaction sintering furnace at each collection moment. Based on the evaporation overheat index, a sintering cooling index at each collection moment can be constructed to reflect the degree of cooling demand for the vacuum reaction sintering furnace at each collection moment. The calculation method of the sintering cooling index is as follows:

[0086] The sintering cooling index at each acquisition moment is determined by the evaporation superheat index and area of ​​all heat-affected zones (HAZs) in the infrared image of the vacuum reaction sintering furnace at that moment. The sintering cooling index at each acquisition moment is a forward fusion of the area of ​​each HZ in the infrared image at that moment and the evaporation superheat index. The more severe the overheating in the HZs at that moment, the greater the evaporation superheat index. Furthermore, the larger the area of ​​the HZs, the more overheating is occurring in the HZs, indicating a greater need for cooling to prevent degradation of product performance. Consequently, the sintering cooling index at that moment increases.

[0087] Preferably, the calculation method of the sintering cooling index provided in the embodiment of the present application is to use the number of all pixel points in each heat effect zone as the area of ​​each heat effect zone, and to use the cumulative result of the product of the area of ​​all heat effect zones in the infrared image of the furnace at each acquisition moment and the evaporation superheat index as the sintering cooling index at each acquisition moment.

[0088] It should be noted that the forward fusion of the area of ​​each heat-affected zone in the infrared image at each acquisition moment and the evaporation superheat index is not limited to the product of the area of ​​the heat-affected zone and the evaporation superheat index in the above embodiment. For example, the sum of the area of ​​the heat-affected zone and the evaporation superheat index can be used, and the average value of the sum of all the heat-affected zones in the infrared image can be used as the sintering cooling index at each acquisition moment. The specific calculation relationship is not particularly limited in this application.

[0089] Step 5: Control the temperature of the sintering furnace during the melt siliconizing process based on the sintering cooling index.

[0090] The sintering cooling index at each sampling moment obtained through the above steps reflects the degree of cooling requirement at each sampling moment. The sintering cooling index at each sampling moment is normalized using the Z-score method to obtain the normalized sintering cooling index. The Z-score normalization method is well known in the art and will not be described in detail here.

[0091] Furthermore, the optimal temperature at each collection moment is calculated. Taking the current collection moment as an example, the calculation formula is as follows: ;in, Indicates the optimal temperature at the current collection time. Indicates the maximum value of the temperature adjustment interval, Y indicates the length of the preset temperature range, and Z indicates the normalized sintering cooling index at the current acquisition moment. = is the temperature adjustment factor at the current acquisition moment. Since the preset temperature range for melt siliconization treatment in this application is 1700-1800°C, The temperature in the embodiment is 1800° C., and the temperature in the Y embodiment is 100° C. The temperature adjusted in this application is the temperature during the melt siliconization process, which ensures that the melting temperature at each sampling moment reaches the optimal value and improves the preparation quality of the silicon carbide ceramic matrix composite material.

[0092] The higher the cooling demand at the current acquisition moment, the more the vacuum reaction sintering furnace should be cooled to avoid excessive evaporation of silicon due to excessive temperature, which will cause the performance of silicon carbide ceramic-based composite materials to deteriorate. Therefore, the calculated optimal temperature is smaller.

[0093] The temperature of the vacuum reaction sintering furnace is controlled based on the optimal temperature at each moment obtained in the above steps. The specific control process is as follows: the initial parameters of the proportional term, integral term, and differential term in the PID control are set to 0.5, 0.45, and 0.55, respectively. The optimal temperature at each moment and the actual temperature at the previous moment are used as inputs, and a PID algorithm is used to output a control signal to control the temperature of the vacuum reaction sintering furnace. The PID algorithm is well known in the art and will not be described in detail in this application.

[0094] See also Figure 3 , Figure 3 Schematic diagram of the sintering furnace temperature control process during the melt siliconizing process.

[0095] The silicon carbide ceramic matrix composite materials prepared in Example 1, Example 2, and Example 3 were tested, and the test results are shown in Table 1 below. The test method is as follows:

[0096] Mechanical properties test: The compressive strength and fracture toughness of composite materials are tested using an electronic universal testing machine;

[0097] Electromagnetic shielding performance test: Refer to IEC / TR 62153-4-1:2007, test in the 2-15GHz frequency range to determine the maximum shielding performance;

[0098] High temperature resistance: The composite material was treated in a 2000°C environment for 30 minutes, and the mechanical properties and electromagnetic shielding performance were tested again.

[0099] Table 1: Performance test results of silicon carbide ceramic matrix composites

[0100] It is understood that references to "one embodiment" or "some embodiments" in the present specification mean that one or more embodiments of the present application include a particular feature, structure, or characteristic described in conjunction with that embodiment. Thus, if "in one embodiment," "in some embodiments," "in other embodiments," or "in other embodiments" appear in different places in this specification, they do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0101] It should be noted that the above-mentioned sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above description is of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-tasking and parallel processing are also possible or may be advantageous. At the same time, the size of the sequence number of each step in the embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments in this specification.

[0102] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization, characterized in that: The method comprises the following steps: Ammonia solution was added dropwise to the silver nitrate solution until the precipitate disappeared, 1-allyl-2,3-dimethylimidazolium tetrafluoroborate and ethyltriphenylphosphine tetrafluoroborate were added dropwise, and the mixture was stirred to obtain a silver ammonia solution; The carbon fibers are added to a sodium hydroxide solution, subjected to ultrasonic vibration, and then rinsed with deionized water to obtain alkali-treated carbon fibers; adding the alkali-treated carbon fiber to the silver ammonia solution, and adding the glucose solution, heating in a water bath, filtering out the solid, washing to neutrality, and drying to obtain the pretreated carbon fiber; The pretreated carbon fibers are treated by radio frequency magnetron sputtering to form a titanium carbide layer, and the carbon fibers with the titanium carbide layer are treated again by radio frequency magnetron sputtering to form a silicon carbide layer, and the carbon fibers are woven to obtain a carbon fiber cloth. Silicon carbide is deposited on carbon fiber cloth to obtain a silicon carbide preform. The silicon carbide preform is placed in a vacuum reaction sintering furnace using a melt siliconizing method. The temperature difference characteristics of the local hot spot area of ​​each pixel point in the infrared image of the sintering furnace are analyzed to construct a local temperature difference value. The temperature change characteristics of the same hot spot area are analyzed based on the local temperature difference value to construct an evaporation superheat index. The cooling demand at each moment is analyzed based on the evaporation superheat index to construct a sintering cooling index. The temperature of the sintering furnace is controlled during the melt siliconizing process. After the reaction, a silicon carbide ceramic matrix composite material is prepared. The evaporation superheat index of each heat-effect zone is determined based on the local temperature difference and grayscale value of all pixels in each heat-effect zone. The heat-effect zone is the connected domain corresponding to the heat-effect cluster. The heat-effect cluster is the cluster with the largest grayscale mean after clustering the temperature feature descriptors of all pixels in the infrared image. The temperature feature descriptor of the pixel point is the combination of the local temperature difference and grayscale value of the pixel point.

2. The method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization according to claim 1, characterized in that: The concentration of the silver nitrate solution is 0.12-0.2 mol / L, and the mass concentration of the ammonia solution is 2.2-3%.

3. The method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization according to claim 1, characterized in that: The weight of the sodium hydroxide solution is 6.5 to 8 times the weight of the carbon fiber, the mass concentration of the sodium hydroxide solution is 20 to 30%, and the ultrasonic oscillation is carried out at a power of 320 to 400 W for 1.5 to 2 hours.

4. The method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization according to claim 1, wherein: The volume of the glucose solution is 2 times that of the silver ammonia solution, and the concentration is 0.6 to 1 times that of the silver ammonia solution. The water bath heating is performed at 52 to 60° C. for 95 to 100 minutes.

5. The method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization according to claim 1, characterized in that: In the process of forming the titanium carbide layer, the vacuum degree before sputtering is 1.0×10 -3 Pa, the RF sputtering power is 850-1000 W, the deposition time is 105-120 minutes, the distance between the target and the pretreated carbon fiber is 65-80 mm, and the argon flow rate is 40-50 sccm.

6. The method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization according to claim 1, characterized in that: In the process of forming the silicon carbide layer, the vacuum degree before sputtering is 1.0×10 -3 Pa, the RF sputtering power is 1100-1200 W, the deposition time is 55-70 minutes, the distance between the target and the pretreated carbon fiber is 65-80 mm, and the argon flow rate is 35-50 sccm.

7. The method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization according to claim 1, characterized in that: The method for constructing the local temperature difference value is: Obtain infrared images at each acquisition moment in the sintering furnace; Construct a hot spot monitoring window for each pixel in the infrared image with each pixel as the center; Based on the grayscale difference between pixels within the hot spot monitoring window of each pixel, the local temperature difference value of each pixel is determined.

8. The method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization according to claim 1, characterized in that: The sintering temperature drop index is a positive fusion of the area of ​​each heat-affected zone in the infrared image at each acquisition moment and the evaporation overheating index.

9. The method for preparing a silicon carbide ceramic matrix composite material based on parameter optimization according to claim 8, characterized in that: The controlling of the temperature of the sintering furnace during the melt siliconizing process further comprises: Preset the temperature range of the sintering furnace during the melt siliconizing process and calculate the interval length of the temperature range; The product of the interval length and the normalized value of the sintering cooling index at each acquisition moment is analyzed and recorded as the temperature adjustment factor at each acquisition moment; the optimal temperature at each acquisition moment is the difference between the maximum value of the temperature range and the temperature adjustment factor.

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