Method and system for surface anti-carbon deposition treatment of silicon nitride ceramic heating element

Abstract

The application discloses a surface anti-carbon deposition treatment method and system of a silicon nitride ceramic electric heating element, relates to the technical field of electric heating element coating, and comprises the following steps: determining an anti-carbon deposition coating of the silicon nitride ceramic electric heating element, performing buffer coating matching, and determining a thermal expansion gradient buffer coating; constructing a surface spraying three-dimensional model of the silicon nitride ceramic electric heating element, performing local mask analysis of coating homogenization, and determining spraying parameters of each layer; performing powder flow defect analysis during spraying, determining ultrasonic dispersion pretreatment parameters before spraying, and performing spraying treatment of the anti-carbon deposition coating and the thermal expansion gradient buffer coating. The application solves the technical problems that the coating is prone to cracking due to differences in thermal expansion coefficients, the coating is non-uniform due to inaccurate spraying parameters, and powder flow defects affect the quality of the coating in the prior art, and achieves the technical effects of improving the quality and stability of the surface anti-carbon deposition coating of the silicon nitride ceramic electric heating element.

Description

Technical Field

[0001] This invention relates to the field of coating technology for electric heating elements, and specifically to a method and system for anti-carbon deposition treatment of the surface of silicon nitride ceramic electric heating elements. Background Technology

[0002] In modern industry, silicon nitride ceramic heating elements are widely used in metallurgy, chemical industry, electronics, and other sectors due to their excellent high-temperature resistance, oxidation resistance, and electrothermal properties. However, in actual use, their surfaces are prone to carbon buildup, which not only reduces the heating efficiency of the elements but may also cause localized overheating, affecting the lifespan and safety of the elements. Existing anti-carbon buildup treatment methods have many shortcomings. On the one hand, they do not fully consider the difference in thermal expansion coefficients between the substrate and the anti-carbon buildup coating, making the coating prone to cracking and peeling when the temperature changes. On the other hand, the spraying process lacks precise control, resulting in poor coating uniformity. Powder agglomeration, dispersion, and rebound occur during the spraying process, leading to low coating density and insufficient adhesion, which cannot effectively resist carbon buildup and seriously restricts the performance and application range of silicon nitride ceramic heating elements.

[0003] Existing technologies have technical problems such as coating cracking due to differences in thermal expansion coefficients, uneven coating due to inaccurate spraying parameters, and powder flow defects affecting coating quality. Summary of the Invention

[0004] This application provides a method and system for anti-carbon deposition treatment of silicon nitride ceramic heating elements, which is used to solve the technical problems in the prior art such as coating cracking due to differences in thermal expansion coefficients, uneven coating caused by inaccurate spraying parameters, and powder flow defects affecting coating quality.

[0005] In view of the above problems, this application provides a method and system for anti-carbon deposition treatment of silicon nitride ceramic heating elements.

[0006] A first aspect of this application provides a method for anti-carbon deposition treatment of the surface of a silicon nitride ceramic heating element, the method comprising:

[0007] An anti-carbon deposition coating for the silicon nitride ceramic heating element is determined, and a buffer coating is matched with the thermal expansion coefficient of the substrate and the thermal expansion coefficient of the anti-carbon deposition coating to determine a thermal expansion gradient buffer coating. A three-dimensional model of the surface spraying of the silicon nitride ceramic heating element is constructed, and local mask analysis for coating homogenization is performed on the anti-carbon deposition coating and the thermal expansion gradient buffer coating to determine the spraying parameters for each layer. Powder flow defect analysis is performed on the anti-carbon deposition coating and the thermal expansion gradient buffer coating during spraying to determine the ultrasonic dispersion pretreatment parameters before spraying. The spraying treatment of the anti-carbon deposition coating and the thermal expansion gradient buffer coating is performed using the spraying parameters for each layer and the ultrasonic dispersion pretreatment parameters.

[0008] A second aspect of this application provides a surface anti-carbon deposition treatment system for silicon nitride ceramic heating elements, the system comprising:

[0009] The module includes a buffer coating matching module for determining the anti-carbon deposition coating of the silicon nitride ceramic heating element and matching the buffer coating with the thermal expansion coefficient of the substrate to determine the thermal expansion gradient buffer coating. A spraying parameter determination module is used to construct a three-dimensional model of the surface spraying of the silicon nitride ceramic heating element, perform local mask analysis for coating homogenization on the anti-carbon deposition coating and the thermal expansion gradient buffer coating, and determine the spraying parameters for each layer. A defect analysis module is used to analyze powder flow defects during the spraying of the anti-carbon deposition coating and the thermal expansion gradient buffer coating, and determine the ultrasonic dispersion pretreatment parameters before spraying. A spraying treatment module is used to perform the spraying treatment of the anti-carbon deposition coating and the thermal expansion gradient buffer coating using the spraying parameters for each layer and the ultrasonic dispersion pretreatment parameters.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] A method was developed to determine the anti-carbon deposition coating for silicon nitride ceramic heating elements, perform buffer coating matching, and identify a thermal expansion gradient buffer coating. A three-dimensional model of the surface of the silicon nitride ceramic heating element was constructed, and local mask analysis for coating homogenization was performed to determine the spraying parameters for each layer. Powder flow defect analysis was conducted during spraying to determine the ultrasonic dispersion pretreatment parameters before spraying. The anti-carbon deposition coating and the thermal expansion gradient buffer coating were then sprayed using the specified spraying parameters and the ultrasonic dispersion pretreatment parameters. This method effectively improves the quality and stability of the anti-carbon deposition coating on the surface of the silicon nitride ceramic heating element. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of the process for anti-carbon deposition treatment of the surface of silicon nitride ceramic heating elements provided in the embodiments of this application;

[0014] Figure 2 This is a schematic diagram of the anti-carbon deposition treatment system for the surface of silicon nitride ceramic heating elements provided in the embodiments of this application.

[0015] Explanation of reference numerals in the attached diagram: Buffer coating matching module 10, spraying parameter determination module 20, defect analysis module 30, spraying treatment module 40. Detailed Implementation

[0016] This application provides a method and system for anti-carbon deposition treatment of silicon nitride ceramic heating elements, which addresses the technical problems in the prior art such as coating cracking due to differences in thermal expansion coefficients, uneven coating due to inaccurate spraying parameters, and powder flow defects affecting coating quality.

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0018] Example 1, as Figure 1 As shown, this application provides a method for anti-carbon deposition treatment of the surface of silicon nitride ceramic heating elements, the method comprising:

[0019] Step S100: Determine the anti-carbon deposition coating of the silicon nitride ceramic heating element, and combine the thermal expansion coefficient of the substrate with the thermal expansion coefficient of the anti-carbon deposition coating to match the buffer coating and determine the thermal expansion gradient buffer coating.

[0020] Specifically, the first step is to identify the anti-carbon deposition coating of the silicon nitride ceramic heating element. By determining the material information of this coating, the corresponding coefficient of thermal expansion is looked up to obtain the coefficient of thermal expansion of the anti-carbon deposition coating. Here, the coefficient of thermal expansion of the substrate is the coefficient of thermal expansion of the silicon nitride ceramic itself. This coefficient of thermal expansion is used to construct a thermal expansion buffer space with the coefficient of thermal expansion of the anti-carbon deposition coating. Within this space, a predetermined buffer adaptation gradient is used for step-by-step matching to determine the thermal expansion gradient buffer coating. The predetermined buffer adaptation gradient refers to the deviation of the coefficient of thermal expansion that makes the probability of coating cracking less than a predetermined probability threshold at a predetermined operating temperature. When determining the predetermined buffer adaptation gradient, the operating mode of the element needs to be collected and extreme operating conditions simulated to obtain the extreme heating range and extreme cooling range, thereby constructing the predetermined operating temperature. Then, using the thermal expansion buffer space as the starting point for optimization, under the fitting condition of the predetermined operating temperature, the deformation difference between adjacent coatings is analyzed to generate the first fitted coating cracking probability. If the probability is less than the preset probability threshold, the matching of the thermal expansion gradient buffer coating will no longer be performed, and the analysis and spraying of the relevant parameters of the anti-carbon deposit coating will proceed directly. If it is less than the preset probability threshold, the thermal expansion buffer space will be iterated by uniformly dividing the thermal expansion buffer gradient and analyzing the deformation difference according to the preset step size until the cracking probability of the generated fitted coating is less than the preset probability threshold. At this time, the corresponding thermal expansion coefficient deviation value is the predetermined buffer adaptation gradient, and the determination of the thermal expansion gradient buffer coating is completed. The difference between the thermal expansion coefficient of this coating and the thermal expansion coefficient of the anti-carbon deposit coating gradually decreases from the inside to the outside, which can effectively alleviate the risk of coating cracking caused by the difference in thermal expansion coefficient.

[0021] Step S200: Construct a three-dimensional model of the surface coating of the silicon nitride ceramic heating element, perform local mask analysis on the anti-carbon deposition coating and the thermal expansion gradient buffer coating to determine the coating parameters of each layer.

[0022] Specifically, the unit spraying parameters of the silicon nitride ceramic heating element surface spraying equipment are determined, and the first coating structure information, including coating thickness and material properties, is extracted from the anti-carbon deposition coating and the thermal expansion gradient buffer coating. Based on the acquired unit spraying parameters, the spraying of the constructed surface spraying 3D model is fitted with non-overlapping areas, targeting the first coating structure information. During this process, the spraying operation is simulated to determine the first round of spraying parameters, and areas missing from the first round of spraying—those not fully covered or with unsatisfactory coverage—are identified. For these missing areas, a collaborative analysis of local masking and spraying is performed, guided by the first coating structure information. Local masking is used to precisely control the spraying area and avoid affecting other already sprayed areas, while the collaborative analysis comprehensively considers various factors, such as spraying angle and speed, to generate second-round local collaborative spraying parameters. Finally, the first-round spraying parameters and the second-round local collaborative spraying parameters are integrated to form the complete spraying parameters for the first coating layer, and this is added to the set of spraying parameters for each layer. Through this analysis and calculation process, precise spraying parameters for each layer of the anti-carbon deposition coating and the thermal expansion gradient buffer coating can be determined, providing a strong guarantee for subsequent high-quality spraying operations and helping to improve the effect and quality of anti-carbon deposition treatment on the surface of silicon nitride ceramic heating elements.

[0023] Step S300: Analyze the powder flow defects during the spraying of the anti-carbon deposition coating and the thermal expansion gradient buffer coating, and determine the ultrasonic dispersion pretreatment parameters before spraying.

[0024] Specifically, for anti-carbon deposition coatings and thermal expansion gradient buffer coatings, due to the small particle size of certain functional powders (such as rare earth oxides), they exhibit characteristics such as easy agglomeration and dispersion, making it difficult to form a continuous and dense coating. Therefore, it is necessary to analyze the powder flow defects during spraying. First, based on the coating materials of each layer, twin fitting is performed on the determined spraying parameters of each layer. This fitting method identifies the target coating with powder flow defects and the specific flow defect characteristics, which cover one or more of the following: powder agglomeration, powder dispersion, or powder rebound. Then, based on the identified flow defect characteristics, the corresponding fluid dispersion requirements are determined. This requirement is input into a preset ultrasonic dispersion pretreatment database, and matching is performed in the database to generate corresponding ultrasonic dispersion pretreatment parameters. These parameters can effectively improve the flow state of the powder and reduce defects. Finally, the generated ultrasonic dispersion pretreatment parameters are mapped and identified with the corresponding target coatings so that the corresponding ultrasonic dispersion pretreatment parameters can be accurately applied to different target coatings in subsequent spraying processes. This ensures that the powder is properly pretreated before spraying, thereby improving the continuity and density of the coating and enhancing the overall effect of anti-carbon deposition treatment on the surface of silicon nitride ceramic heating elements.

[0025] Step S400: Perform the spraying treatment of the anti-carbon deposition coating and the thermal expansion gradient buffer coating with the spraying parameters of each layer and the ultrasonic dispersion pretreatment parameters.

[0026] Specifically, the spraying parameters for each layer and the ultrasonic dispersion pretreatment parameters are obtained from the determined information. The spraying parameters for each layer are determined through local masking analysis using a constructed 3D model of the surface of the silicon nitride ceramic heating element, encompassing key parameters such as speed, angle, and flow rate of the spraying equipment during different coating applications. The ultrasonic dispersion pretreatment parameters are obtained through analysis and matching with a pre-set database, targeting powder flow defects in anti-carbon deposition coatings and thermal expansion gradient buffer coatings. Next, according to the ultrasonic dispersion pretreatment parameters, the powder material used for spraying is pretreated. Ultrasonic dispersion equipment is used to improve the dispersion state of the powder (especially functional powders prone to agglomeration and dispersion, such as rare earth oxides), reducing agglomeration and dispersion, and improving powder flowability and uniformity. Then, based on the spraying parameters for each layer, the operating parameters of the spraying equipment are adjusted, setting the position, movement path, and spraying pressure of the spray gun to ensure a precise and stable spraying process. Once preparations are complete, the spraying equipment is started. First, a thermal expansion gradient buffer coating is sprayed. The difference in thermal expansion coefficient between this coating and the anti-carbon deposit coating gradually decreases from the inside out, effectively alleviating thermal stress. During the spraying process, all parameters are strictly monitored to ensure uniform coating thickness and complete coverage. After the buffer coating is applied and reaches the specified drying or curing conditions, the anti-carbon deposit coating is sprayed following the same operating procedures. This completes the anti-carbon deposit treatment of the entire silicon nitride ceramic heating element surface, thereby improving the element's anti-carbon deposit performance and service life.

[0027] In one possible implementation, step S100 further includes:

[0028] Step S110: The thermal expansion gradient buffer coating includes a multi-layer buffer coating in which the difference between the thermal expansion coefficient and the thermal expansion coefficient of the anti-carbon deposition coating gradually decreases from the inside to the outside, and the anti-carbon deposition coating is applied to the outermost layer of the multi-layer buffer coating.

[0029] Specifically, the thermal expansion gradient buffer coating is a special multi-layered coating structure where the difference between the thermal expansion coefficients of each layer from the inside to the outside and the thermal expansion coefficient of the anti-carbon deposition coating gradually decreases. This design addresses the stress issues arising from the different degrees of thermal expansion of different materials due to temperature changes during actual use. By setting up multiple buffer coatings, each layer can gradually buffer thermal stress, reducing the risk of coating cracking and peeling due to excessive differences in thermal expansion coefficients. After completing the construction of the thermal expansion gradient buffer coating, the anti-carbon deposition coating is applied on the outermost layer of the multi-layer buffer coating. As a key component directly resisting carbon deposition, the anti-carbon deposition coating, under the protection of the buffer coating, can better exert its anti-carbon deposition function, improving the performance and service life of the silicon nitride ceramic heating element and ensuring stable operation of the element under complex conditions.

[0030] In one possible implementation, step S100 further includes:

[0031] Step S120: Determine the coating material information of the anti-carbon deposit coating, query the coefficient of thermal expansion, and generate the coefficient of thermal expansion of the anti-carbon deposit coating.

[0032] Step S130: Construct a thermal expansion buffer space using the thermal expansion coefficient of the substrate and the thermal expansion coefficient of the anti-carbon deposition coating, wherein the thermal expansion coefficient of the substrate is the thermal expansion coefficient of silicon nitride ceramic.

[0033] Step S140: In the thermal expansion buffer space, a predetermined buffer adaptation gradient is invoked to match the gradient buffer coating step by step, thereby generating the thermal expansion gradient buffer coating.

[0034] Specifically, firstly, a comprehensive analysis of the materials used in the anti-carbon deposit coating is conducted, detailing its chemical composition, including the specific types and proportions of various compounds and additives, and gaining a thorough understanding of its microstructural characteristics, such as crystal structure and particle distribution. After mastering these material properties, a material thermal expansion coefficient lookup tool, such as a materials science database, is used to retrieve the key material information of the anti-carbon deposit coating. If the database lacks corresponding material data, thermal expansion coefficient data of similar materials is referenced. Through this method, the thermal expansion coefficient of the anti-carbon deposit coating under different temperature conditions is accurately obtained, generating complete thermal expansion coefficient data for the anti-carbon deposit coating.

[0035] After obtaining the thermal expansion coefficients of the silicon nitride ceramic matrix and the anti-carbon deposition coating, a thermal expansion buffer space was constructed using data analysis software (such as MATLAB). First, two variables were created in the software, inputting the precisely measured values ​​of the matrix thermal expansion coefficient and the anti-carbon deposition coating thermal expansion coefficient, respectively. Next, using the software's calculation function, an interval encompassing these two coefficient values ​​was defined, with the lower limit being the smaller of the two coefficients and the upper limit being the larger value, thus constructing the thermal expansion buffer space. For more intuitive visualization and subsequent analysis, a two-dimensional coordinate system was plotted in the software, with temperature as the x-axis and the thermal expansion coefficient as the y-axis. The matrix thermal expansion coefficient and the anti-carbon deposition coating thermal expansion coefficient were marked on the coordinate system, and the thermal expansion buffer space was presented as a shaded area. Simultaneously, to ensure data accuracy and the reliability of subsequent analysis, these two coefficient values ​​were measured multiple times and averaged. The measurement error range was considered when constructing the space, and this error range was incorporated into the boundary setting of the thermal expansion buffer space, ultimately forming an accurate thermal expansion buffer space that reflects actual thermal expansion differences.

[0036] The thermal expansion buffer space is a range determined by the thermal expansion coefficients of the substrate (silicon nitride ceramic) and the anti-carbon deposition coating, providing boundary conditions for matching the buffer coating. The predetermined buffer adaptation gradient is the thermal expansion coefficient deviation value that ensures the probability of coating cracking is less than a predetermined probability threshold at a preset operating temperature; this is the key basis for generating a thermal expansion gradient buffer coating. In practice, matching begins from the end of the thermal expansion buffer space closest to the substrate's thermal expansion coefficient. First, a buffer coating material is selected, and its thermal expansion coefficient is obtained from a material property database. It is ensured that the difference between the material's thermal expansion coefficient and the substrate's thermal expansion coefficient conforms to the predetermined buffer adaptation gradient, and this is used as the first layer of the thermal expansion gradient buffer coating. After determining the thickness, composition ratio, and other process parameters of the first layer, the second layer buffer coating material is selected again based on the predetermined buffer adaptation gradient, ensuring that the difference between the second layer's thermal expansion coefficient and the first layer is within the gradient range. Simultaneously, the thickness and composition ratio of the second layer are adjusted. This process is repeated for each buffer coating layer from the inside out. For each layer being matched, the difference in thermal expansion coefficient between that layer and the adjacent inner layer must be rigorously checked to ensure it conforms to the predetermined buffer adaptation gradient. Furthermore, the actual process conditions and material properties must be considered to ensure compatibility and stability between layers. During this process, the selected materials require appropriate treatment, such as adding additives and adjusting the firing temperature, to fine-tune their thermal expansion coefficients. When matching the outermost buffer coating, the difference in its thermal expansion coefficient with that of the anti-carbon deposition coating must also meet the predetermined buffer adaptation gradient. This completes the formation of the entire thermal expansion gradient buffer coating, effectively mitigating stress problems caused by differences in thermal expansion and improving the coating's reliability and service life.

[0037] In one possible implementation, step S140 further includes:

[0038] Step S141: The predetermined buffer adaptation gradient is the thermal expansion coefficient deviation value when the probability of coating cracking is less than a preset probability threshold at a preset operating temperature.

[0039] Specifically, the predetermined buffer adaptation gradient is defined as the deviation of the coefficient of thermal expansion (COP) from the predetermined probability threshold at a predetermined operating temperature, where the probability of coating cracking is less than the predetermined probability threshold. The predetermined operating temperature is determined by comprehensively considering the temperature variation range in the actual operating environment of the silicon nitride ceramic heating element. For example, if the element typically operates in the temperature range of 300℃-800℃, this range is used as the predetermined operating temperature. The predetermined probability threshold is set based on the requirements for coating quality and reliability. For instance, if the expected cracking probability of the coating within a certain service life does not exceed 5%, then 5% is the predetermined probability threshold. When determining the predetermined buffer adaptation gradient, the thermal expansion buffer space is first used as the starting point for optimization. The thermal expansion buffer space is the range constructed by the COP of the substrate and the COP of the anti-carbon deposition coating. Using the predetermined operating temperature as the fitting condition, the deformation differences of adjacent coatings during this temperature change process are analyzed to generate the first fitted coating cracking probability. If the first fitted coating cracking probability is less than the predetermined probability threshold, the thermal expansion buffer space is uniformly divided according to a predetermined step size using the thermal expansion buffer gradient, and the deformation difference analysis is performed again. This process is iterated until the generated fitted coating cracking probability is less than the predetermined probability threshold. The corresponding deviation in the coefficient of thermal expansion at this point is the predetermined buffer adaptation gradient. By calling this predetermined buffer adaptation gradient to match the gradient buffer coating layer by layer, it is possible to effectively ensure that the coefficient of thermal expansion of each layer of the thermal expansion gradient buffer coating is reasonably designed, reduce the risk of cracking during use, and improve the stability and reliability of the entire coating system.

[0040] In one possible implementation, step S141 further includes:

[0041] Step S1411: Collect the operating mode of the silicon nitride ceramic heating element, perform extreme working condition simulation, and determine the extreme heating range and extreme cooling range.

[0042] Step S1412: Construct the preset operating temperature using the extreme heating range and the extreme cooling range.

[0043] Step S1413: Using the thermal expansion buffer space as the starting point for optimization and the preset operating temperature as the fitting condition, perform deformation difference analysis of adjacent coatings to generate the first fitted coating cracking probability.

[0044] Step S1414: Determine whether the cracking probability of the first fitted coating is less than the preset probability threshold. If not, perform iterative thermal expansion buffer gradient uniform division and deformation difference analysis on the thermal expansion buffer space according to the preset step size until the cracking probability of the generated fitted coating is less than the preset probability threshold. Generate the predetermined buffer adaptation gradient with the thermal expansion coefficient deviation value corresponding to the thermal expansion buffer gradient division result at that time.

[0045] Specifically, a sensor monitoring system is used to comprehensively collect operating mode data of the silicon nitride ceramic heating element in the actual operating environment or simulated operating environment. This data covers the element's operating parameters under various conditions, including normal operation, load changes, and different ambient temperatures, such as real-time temperature, input power, operating time, and voltage and current fluctuations. After collecting sufficient operating data, simulation software (such as ANSYS, COMSOL, etc.) is used to simulate extreme operating conditions. During the simulation, based on the actual collected operating mode data, the maximum power input of the element during the heating phase is set, and conventional limiting factors such as heat dissipation are ignored. The temperature change curve of the element under the most severe heating conditions is simulated, thus determining the extreme heating range. This range clearly defines the initial temperature and maximum temperature of the element under extreme heating conditions. Similarly, during the simulated cooling phase, the maximum heat dissipation rate is set, and the temperature drop process of the element without external heating compensation is simulated, generating an extreme cooling curve, thereby determining the extreme cooling range. This range gives the initial temperature and minimum temperature of the element under extreme cooling conditions. Through this series of operations, the extreme heating range and extreme cooling range are determined.

[0046] The extreme heating range records the temperature change range of the element under extremely rapid heating, while the extreme cooling range records the temperature range under extremely rapid cooling. They represent the worst temperature changes the element may face. First, the common temperature fluctuation patterns of silicon nitride ceramic heating elements in practical applications are analyzed. For example, if the element is mainly used in an industrial heating device, its temperature change within a working cycle is usually within a certain range and frequency. Based on these practical usage scenarios, representative temperature values ​​and change processes are selected from the extreme heating and cooling ranges. Then, considering the thermal fatigue characteristics of the element material and long-term stability requirements, the selected temperature range is appropriately adjusted. If the element material is prone to performance degradation or structural changes near a certain temperature, the temperature dwell time near that temperature point will be appropriately increased or the temperature change amplitude adjusted when constructing the preset operating temperature. Finally, the selected and adjusted temperature values ​​and change processes are combined to form the preset operating temperature. This preset operating temperature includes both the extreme temperature changes the element may encounter and the actual working scenario and material properties, more realistically simulating the temperature environment faced by the element in actual use.

[0047] The thermal expansion buffer space was discretized into 500 uniformly distributed points, each representing a combination of thermal expansion coefficients. For a preset operating temperature, finite element method simulation was used to apply 100 temperature cycles to adjacent coatings under each thermal expansion coefficient combination. Displacement, stress, and strain data of adjacent coatings were recorded during each loading process, constructing a dataset of 1000 samples. The model was trained using the random forest regression algorithm from Python's Scikit-learn library: the number of decision trees was set to 100, the maximum depth to 8, and the minimum number of sample splits to 5. Thermal expansion coefficient, number of temperature cycles, displacement, stress, and strain were used as input features, and whether the coating cracked (cracked = 1, no cracked = 0) was used as the output label. The model parameters were optimized using 5-fold cross-validation, and the model learned the complex nonlinear relationship between input features and coating cracking. After training, predictions were made on the remaining 500 test samples, and the probability of coating cracking in the prediction results was calculated to obtain the first fitted coating cracking probability.

[0048] The cracking probability of the first fitted coating is compared with a preset probability threshold. Assuming the preset probability threshold is set to 5%, when the cracking probability of the first fitted coating is less than 5%, the thermal expansion buffer space is operated on according to a preset step size. The preset step size can be set to 0.001 × 10⁻⁶. -6 The thermal expansion buffer space is uniformly divided at a step size of / ℃ (this value can be adjusted according to actual conditions) to obtain a series of new combinations of thermal expansion coefficients. For each new combination of thermal expansion coefficients, deformation difference analysis is performed again. Using finite element simulation and other methods, the difference in thermal expansion between adjacent coatings at a preset operating temperature is calculated, and the resulting stress and strain are analyzed. Based on these analysis results, a fitted coating cracking probability is generated again. This process of uniformly dividing the thermal expansion buffer space, performing deformation difference analysis, and generating a fitted coating cracking probability is repeated until the obtained fitted coating cracking probability is less than a preset probability threshold of 5%. At this point, the thermal expansion coefficient deviation value corresponding to the last thermal expansion buffer gradient division result that meets the conditions is determined as the predetermined buffer adaptation gradient. This predetermined buffer adaptation gradient will be used to subsequently determine the thermal expansion gradient buffer coating to ensure that the coating system has a low cracking risk under actual operating conditions, thereby improving the reliability and stability of the surface coating of the silicon nitride ceramic heating element.

[0049] In one possible implementation, step S1414 further includes:

[0050] If the cracking probability of the first fitted coating is less than the preset probability threshold, the matching of the thermal expansion gradient buffer coating is not performed, and the spraying parameters and ultrasonic dispersion pretreatment parameters of the anti-carbon deposit coating are directly analyzed and sprayed.

[0051] Specifically, if the cracking probability of the first fitted coating is less than the preset probability threshold, this may be because the difference in thermal expansion coefficients between the anti-carbon deposition coating and the silicon nitride substrate is very small, and a buffer layer is not actually needed to adjust for the thermal expansion difference. Therefore, the matching operation of the thermal expansion gradient buffer coating is no longer performed at this time. Instead, the process proceeds directly to the subsequent processing stage. First, a three-dimensional model of the surface spraying of the silicon nitride ceramic heating element is constructed, and a local mask analysis for coating homogenization is performed on the anti-carbon deposition coating to determine the spraying parameters. Next, a defect analysis is performed on the powder flow of the anti-carbon deposition coating during spraying, and appropriate ultrasonic dispersion pretreatment parameters are matched in the preset ultrasonic dispersion pretreatment database based on the analysis results. Finally, according to the determined spraying parameters and ultrasonic dispersion pretreatment parameters, the anti-carbon deposition coating is directly sprayed, thus completing the key operation in the entire anti-carbon deposition treatment process.

[0052] In one possible implementation, step S200 further includes:

[0053] Step S210: Determine the unit spraying parameters of the surface spraying equipment for the silicon nitride ceramic heating element.

[0054] Step S220: Extract the first coating structure information from the anti-carbon deposition coating and the thermal expansion gradient buffer coating.

[0055] Step S230: Based on the unit spraying parameters, with the first coating structure information as the target, perform non-overlapping region spraying fitting on the surface spraying three-dimensional model to determine the first round of spraying parameters and the first round of missing regions.

[0056] Step S240: For the first round of missing areas, with the first coating structure information as the target, perform a collaborative analysis of local masking and spraying to generate second round of local collaborative spraying parameters.

[0057] Step S250: Generate the spraying parameters for the first coating layer using the first round of spraying parameters and the second round of local collaborative spraying parameters, and add them to the spraying parameters for each layer.

[0058] Specifically, the first step is to determine the model, specifications, and technical characteristics of the surface coating equipment currently in use. Then, prepare multiple silicon nitride ceramic samples of the same material, size, and surface condition. Turn on the coating equipment and set a set of basic coating parameters, such as fixed spray pressure, spray gun movement speed, and paint flow rate. Apply the coating to the samples using these parameters. After the coating dries and cures, measure the coating thickness using a thickness gauge and simultaneously calculate the area covered by each spray using an image acquisition device. To ensure data accuracy and reliability, the basic coating parameters will be adjusted multiple times under different time and environmental conditions, and the above operation will be repeated to obtain multiple sets of data on the unit spray area and thickness. Finally, these data will be organized, compared, and analyzed. Taking into account the equipment's stability, the characteristics of the paint, and actual production needs, the unit spray area and thickness of the equipment under the most suitable coating conditions will be determined.

[0059] The structural information of the first coating layer was extracted from the anti-carbon deposition coating and the thermal expansion gradient buffer coating. Firstly, scanning electron microscopy (SEM) was used to observe the internal microstructure of the coating, including key information such as grain size, arrangement, and the presence of porosity. X-ray diffraction (XRD) was used to analyze the crystal structure of the coating to determine its phase composition. Atomic force microscopy (AFM) was used to accurately measure the surface roughness of the coating. Simultaneously, relevant technical documents and research materials were consulted to obtain theoretical parameters for the coating design, such as the expected coating thickness and the proportions of each component. These information obtained through experimental measurements and literature review were summarized and integrated to comprehensively and accurately extract the structural information of the first coating layer for both the anti-carbon deposition coating and the thermal expansion gradient buffer coating.

[0060] Based on the established unit spraying parameters, and using the first coating structure information (such as target thickness 50-200 μm, porosity <3%) as the optimization objective, a non-overlapping region spraying fitting is performed on the 3D model of the surface spraying. First, the surface to be sprayed is discretized into 1000×1000 micro-elements, each corresponding to a spraying point. An improved particle swarm optimization (PSO) algorithm is used to optimize the spray gun trajectory: by defining a spraying efficiency function (considering material deposition rate and thickness uniformity) and constraints (spray gun angle ±45°, moving speed 300-500 mm / s), the optimal spray gun path is searched in 3D space. In curved areas, non-critical areas that can be skipped (such as acute angles with a curvature radius <0.5 mm) are automatically identified, prioritizing the spraying quality of flat surfaces and surfaces with large curvature. By iteratively calculating the material deposition amount at each landing point, the first round of non-overlapping spraying parameters (including spray gun trajectory, speed, angle, etc.) are finally generated. Meanwhile, areas with a deposition thickness less than 95% of the target value were marked and identified as the first round of missing areas (mainly concentrated at geometric abrupt changes), providing a basis for subsequent local optimization.

[0061] To generate second-round local collaborative spraying parameters for the first-round missing areas, a Convolutional Neural Network (CNN) algorithm was employed. First, the 3D model data of the first-round missing areas and the first coating structure information were used as input data. The convolutional layers in the CNN algorithm extracted features from the missing areas, analyzing key information such as their shape, location, and relationship with surrounding areas. Pooling layers were used to reduce the dimensionality of the extracted features, reducing the amount of data while retaining key features. Then, these feature data were compared and analyzed with the requirements for thickness, smoothness, etc., in the first coating structure information. A complex relationship model between local masking and spraying operations was constructed using fully connected layers, and multiple rounds of training and optimization were performed to continuously adjust the network parameters. During training, the goal was to minimize the difference between the actual spraying effect and the requirements of the first coating structure information, allowing the model to learn the optimal local masking strategy and spraying parameter combination for different missing area features. After training with a large amount of sample data, the CNN model output second-round local collaborative spraying parameters for the first-round missing areas, including the shape, size, and location of the mask, as well as corresponding parameters such as spraying pressure, speed, and paint flow rate, thereby achieving precise processing of the missing areas and ensuring the overall coating quality.

[0062] Data processing software (such as MATLAB or Python libraries) is used to generate the spraying parameters for the first coating layer from the first and second rounds of spraying parameters, and then add these parameters to the spraying parameters for each layer. First, the first-round spraying parameters and the second-round local collaborative spraying parameters are organized according to the region division of the component surface, forming a structured data format, such as a dictionary or array indexed by coordinate position. Each region of the component surface is traversed; for regions not missing from the first round, the corresponding data from the first-round spraying parameters is directly extracted; for regions missing from the first round, the second-round local collaborative spraying parameters are used. During data fusion, based on the requirements for coating uniformity and other aspects in the first coating structure information, necessary smoothing transition processing is performed on the two types of parameters. Linear interpolation is used to adjust the differences in parameters between adjacent regions, ensuring the spatial continuity and consistency of the spraying parameters for the entire first coating layer. After processing, a first coating parameter set containing complete component surface coating information is generated. This parameter set is then appended to a data file (such as a CSV file) or a database table that stores the coating parameters of each layer. This ensures that the coating equipment can accurately read and apply these parameters during actual coating operations, thereby guaranteeing the coating quality and process effect of each coating.

[0063] In one possible implementation, step S300 further includes:

[0064] Step S310: Perform twin fitting on the spraying parameters of each layer based on the coating material of each layer to determine the target coating and flow defect characteristics of each layer with powder flow defects.

[0065] Step S320: After determining the fluid dispersion requirements based on the flow defect characteristics, input the preset ultrasonic dispersion pretreatment database to match the ultrasonic dispersion pretreatment parameters, generate the ultrasonic dispersion pretreatment parameters, and map and identify them with the target coating.

[0066] Specifically, to determine the target coatings with powder flow defects and their characteristics, detailed information on each coating layer's materials is first collected, including composition, particle size distribution, density, and other properties. Simultaneously, the established spraying parameters for each layer are acquired, such as spraying pressure, spray gun movement speed, and powder feed rate. Then, a twin fitting technique, based on a deep learning twin neural network architecture, is employed. The characteristics of each coating layer's materials and the corresponding spraying parameters are used as two sets of input data for the network, allowing it to learn the complex relationship between them. The network is trained using a large amount of historical data, enabling it to identify potential powder flow defects under different combinations of materials and spraying parameters. After training, the current coating material and spraying parameters to be analyzed are input into the network, and the network outputs the probability of powder flow defects in each coating layer and the corresponding defect feature vector. The target coating with powder flow defects is selected based on probability screening. The defect feature vector is then analyzed and transformed into specific flow defect features, such as powder agglomeration features (manifested as powder particles agglomerating to form large particle clusters in a certain area), powder scattering features (powder particles deviating from the predetermined trajectory and scattering around during the spraying process), or powder rebound features (powder bounces away after hitting the substrate). This provides a basis for determining the ultrasonic dispersion pretreatment parameters.

[0067] Support Vector Machine Regression (SVR) algorithm is used to determine ultrasonic dispersion preprocessing parameters based on flow defect characteristics and map them to the target coating. The obtained flow defect characteristics, such as powder agglomeration degree, powder dispersion range, and powder rebound velocity, are standardized and transformed into feature vectors suitable for machine learning algorithms. These feature vectors serve as input data for the SVR model. Next, a large number of existing flow defect feature samples and their corresponding ultrasonic dispersion preprocessing parameters (such as ultrasonic power, ultrasonic frequency, and ultrasonic processing time) are extracted from a pre-defined ultrasonic dispersion preprocessing database to construct a training dataset. Radial Basis Function (RBF) is used as the kernel function of the SVR model. The penalty parameter C and kernel function parameter γ of the model are fine-tuned through cross-validation to find the optimal combination of model parameters, thereby training an SVR model that can accurately predict ultrasonic dispersion preprocessing parameters. Then, the current flow defect characteristics to be processed are input into the trained SVR model, and the model outputs the corresponding predicted values ​​of the ultrasonic dispersion preprocessing parameters. Finally, the generated ultrasonic dispersion pretreatment parameters are associated with the target coating exhibiting flow defects. By constructing a key-value pair mapping table, the identifier of the target coating is used as the key and the ultrasonic dispersion pretreatment parameters are used as the value, thus completing the mapping between the two. This facilitates the accurate recall of the corresponding pretreatment parameters during subsequent spraying processes, thereby resolving the powder flow defect problem.

[0068] In one possible implementation, step S310 further includes:

[0069] Step S311: The flow defect features include one or more of the following: powder agglomeration features, powder dispersion features, or powder rebound features.

[0070] Specifically, flow defect characteristics include one or more of the following: powder agglomeration, powder scattering, or powder rebound. Powder agglomeration occurs when initially dispersed powder particles aggregate into larger clumps due to van der Waals forces, electrostatic forces, etc. These clumps cannot be evenly dispersed during spraying, leading to uneven coating thickness, localized protrusions or holes, and affecting the coating's density and surface smoothness. Powder scattering refers to the phenomenon where, during spraying, some powder particles do not reach the substrate surface along the expected trajectory but instead scatter into the surrounding space. This may be caused by unstable airflow in the spray gun, excessively high powder feed rate, or unreasonable powder particle size distribution. Powder scattering not only wastes material but also pollutes the spraying environment, and the scattered powder may deposit in non-target areas, affecting the normal operation of other components. Powder rebound occurs when powder particles, upon impacting the substrate surface, are not effectively adsorbed and deposited but instead bounce away. This is mainly due to insufficient adhesion between the powder and the substrate, or poor pretreatment of the substrate surface, resulting in the powder failing to adhere well to the substrate. Powder rebound reduces coating deposition efficiency, increases the number of coats and costs, and also affects the coating's bonding strength and overall performance. These flow defects can occur individually or in combination, severely impacting the coating quality of anti-carbon deposit coatings and thermal expansion gradient buffer coatings.

[0071] Example 2, based on the same inventive concept as the surface anti-carbon deposition treatment method for silicon nitride ceramic heating elements in the foregoing examples, such as... Figure 2 As shown, this application provides a surface anti-carbon deposition treatment system for silicon nitride ceramic heating elements. The system and method embodiments in this application are based on the same inventive concept. The system includes:

[0072] The buffer coating matching module 10 is used to determine the anti-carbon deposition coating of the silicon nitride ceramic heating element, and to match the buffer coating by combining the thermal expansion coefficient of the substrate with the thermal expansion coefficient of the anti-carbon deposition coating, so as to determine the thermal expansion gradient buffer coating.

[0073] The spraying parameter determination module 20 is used to construct a three-dimensional model of the surface spraying of the silicon nitride ceramic heating element, perform local mask analysis on the anti-carbon deposition coating and the thermal expansion gradient buffer coating to homogenize the coating, and determine the spraying parameters of each layer.

[0074] The defect analysis module 30 is used to analyze the powder flow defects during the spraying of the anti-carbon deposition coating and the thermal expansion gradient buffer coating, and to determine the ultrasonic dispersion pretreatment parameters before spraying.

[0075] The spraying module 40 is used to perform the spraying treatment of the anti-carbon deposition coating and the thermal expansion gradient buffer coating with the spraying parameters of each layer and the ultrasonic dispersion pretreatment parameters.

[0076] Furthermore, the system is also used for the following functions:

[0077] The thermal expansion gradient buffer coating comprises a multi-layer buffer coating in which the difference between the thermal expansion coefficient and the thermal expansion coefficient of the anti-carbon deposit coating gradually decreases from the inside to the outside, and the anti-carbon deposit coating is applied on the outermost layer of the multi-layer buffer coating.

[0078] Furthermore, the system is also used for the following functions:

[0079] The coating material information of the anti-carbon deposition coating is determined, the coefficient of thermal expansion is queried, and the coefficient of thermal expansion of the anti-carbon deposition coating is generated; a thermal expansion buffer space is constructed using the coefficient of thermal expansion of the substrate and the coefficient of thermal expansion of the anti-carbon deposition coating, wherein the coefficient of thermal expansion of the substrate is the coefficient of thermal expansion of silicon nitride ceramic; in the thermal expansion buffer space, a predetermined buffer adaptation gradient is called to match the gradient buffer coating step by step, and the thermal expansion gradient buffer coating is generated.

[0080] Furthermore, the system is also used for the following functions:

[0081] The predetermined buffer adaptation gradient is the thermal expansion coefficient deviation value when the probability of coating cracking is less than a predetermined probability threshold at a predetermined operating temperature.

[0082] Furthermore, the system is also used for the following functions:

[0083] The operating mode of the silicon nitride ceramic heating element is collected, and extreme operating condition simulation is performed to determine the extreme heating range and extreme cooling range. A preset operating temperature is constructed based on the extreme heating range and the extreme cooling range. Using the thermal expansion buffer space as the starting point for optimization and the preset operating temperature as the fitting condition, deformation difference analysis of adjacent coatings is performed to generate a first fitted coating crack probability. It is determined whether the first fitted coating crack probability is less than the preset probability threshold. If not, the thermal expansion buffer space is iterated through uniform division of the thermal expansion buffer gradient and deformation difference analysis according to a preset step size until the generated fitted coating crack probability is less than the preset probability threshold. The predetermined buffer adaptation gradient is generated based on the thermal expansion coefficient deviation value corresponding to the thermal expansion buffer gradient division result at that time.

[0084] Furthermore, the system is also used for the following functions:

[0085] If the cracking probability of the first fitted coating is less than the preset probability threshold, the matching of the thermal expansion gradient buffer coating is not performed, and the spraying parameters and ultrasonic dispersion pretreatment parameters of the anti-carbon deposit coating are directly analyzed and sprayed.

[0086] Furthermore, the system is also used for the following functions:

[0087] The unit spraying parameters of the surface spraying equipment for the silicon nitride ceramic heating element are determined; the first coating structure information is extracted from the anti-carbon deposition coating and the thermal expansion gradient buffer coating; based on the unit spraying parameters, and with the first coating structure information as the target, a non-overlapping region spraying fitting is performed on the surface spraying three-dimensional model to determine the first round of spraying parameters and the first round of missing regions; for the first round of missing regions, with the first coating structure information as the target, a collaborative analysis of local masking and spraying is performed to generate the second round of local collaborative spraying parameters; the spraying parameters of the first coating layer are generated using the first round of spraying parameters and the second round of local collaborative spraying parameters, and added to the spraying parameters of each layer.

[0088] Furthermore, the system is also used for the following functions:

[0089] Based on the coating material of each layer, the spraying parameters of each layer are twinned to determine the target coating and flow defect characteristics of each layer with powder flow defects. After determining the fluid dispersion requirements based on the flow defect characteristics, the parameters are input into a preset ultrasonic dispersion pretreatment database for ultrasonic dispersion pretreatment parameter matching to generate the ultrasonic dispersion pretreatment parameters, and then mapped and identified with the target coating.

[0090] Furthermore, the system is also used for the following functions:

[0091] The flow defect features include one or more of the following: powder agglomeration features, powder dispersion features, or powder rebound features.

[0092] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0093] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0094] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for preventing carbon buildup on the surface of silicon nitride ceramic heating elements, characterized in that, include: The anti-carbon deposition coating of silicon nitride ceramic heating element was determined, and the thermal expansion gradient buffer coating was determined by matching the thermal expansion coefficient of the substrate with the thermal expansion coefficient of the anti-carbon deposition coating. A three-dimensional model of the surface spraying of the silicon nitride ceramic heating element was constructed, and a local mask analysis of coating homogenization was performed on the anti-carbon deposition coating and the thermal expansion gradient buffer coating to determine the spraying parameters of each layer. Analysis of powder flow defects during spraying of the anti-carbon deposition coating and the thermal expansion gradient buffer coating was conducted to determine the ultrasonic dispersion pretreatment parameters before spraying. The anti-carbon deposition coating and the thermal expansion gradient buffer coating are sprayed using the spraying parameters for each layer and the ultrasonic dispersion pretreatment parameters. The thermal expansion gradient buffer coating comprises a multi-layer buffer coating in which the difference between the thermal expansion coefficient and the thermal expansion coefficient of the anti-carbon deposition coating gradually decreases from the inside to the outside, and the anti-carbon deposition coating is applied to the outermost layer of the multi-layer buffer coating; The anti-carbon deposition coating for silicon nitride ceramic heating elements was determined, and a buffer coating was matched with the thermal expansion coefficient of the substrate and the thermal expansion coefficient of the anti-carbon deposition coating to determine the thermal expansion gradient buffer coating, including: Determine the coating material information of the anti-carbon deposit coating, query the coefficient of thermal expansion, and generate the coefficient of thermal expansion of the anti-carbon deposit coating; A thermal expansion buffer space is constructed using the thermal expansion coefficient of the substrate and the thermal expansion coefficient of the anti-carbon deposition coating, wherein the thermal expansion coefficient of the substrate is the thermal expansion coefficient of silicon nitride ceramic; In the thermal expansion buffer space, a predetermined buffer adaptation gradient is invoked to match the gradient buffer coating step by step, thereby generating the thermal expansion gradient buffer coating. A three-dimensional model of the surface coating of the silicon nitride ceramic heating element was constructed. Local masking analysis was performed on the anti-carbon deposition coating and the thermal expansion gradient buffer coating to determine the coating parameters for each layer, including: Determine the unit spraying parameters of the surface spraying equipment for the silicon nitride ceramic heating element; Extract the first coating structure information from the anti-carbon deposition coating and the thermal expansion gradient buffer coating; Based on the unit spraying parameters, with the first coating structure information as the target, the surface spraying three-dimensional model is subjected to non-overlapping region spraying fitting to determine the first round of spraying parameters and the first round of missing regions. For the first round of missing areas, taking the first coating structure information as the target, a collaborative analysis of local masking and spraying is performed to generate the second round of local collaborative spraying parameters; The spraying parameters for the first coating layer are generated using the first round of spraying parameters and the second round of local collaborative spraying parameters, and then added to the spraying parameters for each layer. Analysis of powder flow defects during spraying of the anti-carbon deposition coating and the thermal expansion gradient buffer coating was conducted to determine the ultrasonic dispersion pretreatment parameters before spraying, including: Based on the coating material of each layer, twin fitting is performed on the spraying parameters of each layer to determine the target coating and flow defect characteristics of each layer with powder flow defects. After determining the fluid dispersion requirements based on the flow defect characteristics, the parameters are input into a preset ultrasonic dispersion pretreatment database to match the ultrasonic dispersion pretreatment parameters, generate the ultrasonic dispersion pretreatment parameters, and map and identify them with the target coating. The predetermined buffer adaptation gradient is the thermal expansion coefficient deviation value when the probability of coating cracking is less than a preset probability threshold at a preset operating temperature. The method for determining the predetermined buffer adaptation gradient includes: The operating modes of the silicon nitride ceramic heating element are collected, extreme operating condition simulations are performed, and the extreme heating range and extreme cooling range are determined. The preset operating temperature is constructed using the extreme heating range and the extreme cooling range; Using the thermal expansion buffer space as the starting point for optimization and the preset operating temperature as the fitting condition, the deformation difference analysis of adjacent coatings is performed to generate the first fitted coating cracking probability. Determine whether the cracking probability of the first fitted coating is less than the preset probability threshold. If not, perform iterative thermal expansion buffer gradient uniform division and deformation difference analysis on the thermal expansion buffer space according to the preset step size until the cracking probability of the generated fitted coating is less than the preset probability threshold. Generate the predetermined buffer adaptation gradient with the thermal expansion coefficient deviation value corresponding to the thermal expansion buffer gradient division result at that time.

2. The method for preventing carbon buildup on the surface of silicon nitride ceramic heating elements as described in claim 1, characterized in that, If the cracking probability of the first fitted coating is less than the preset probability threshold, the matching of the thermal expansion gradient buffer coating is not performed, and the spraying parameters and ultrasonic dispersion pretreatment parameters of the anti-carbon deposit coating are directly analyzed and sprayed.

3. The method for preventing carbon buildup on the surface of silicon nitride ceramic heating elements as described in claim 1, characterized in that, The flow defect features include one or more of the following: powder agglomeration features, powder dispersion features, or powder rebound features.

4. A surface anti-carbon deposition treatment system for silicon nitride ceramic heating elements, characterized in that, The system is used to implement the surface anti-carbon deposition treatment method for silicon nitride ceramic heating elements according to any one of claims 1-3, the system comprising: The buffer coating matching module is used to determine the anti-carbon deposition coating of the silicon nitride ceramic heating element, and to match the buffer coating by combining the thermal expansion coefficient of the substrate and the thermal expansion coefficient of the anti-carbon deposition coating, so as to determine the thermal expansion gradient buffer coating. The spraying parameter determination module is used to construct a three-dimensional model of the surface spraying of the silicon nitride ceramic heating element, perform local mask analysis on the anti-carbon deposition coating and the thermal expansion gradient buffer coating to homogenize the coating, and determine the spraying parameters of each layer. The defect analysis module is used to analyze powder flow defects during the spraying of the anti-carbon deposition coating and the thermal expansion gradient buffer coating, and to determine the ultrasonic dispersion pretreatment parameters before spraying. A spraying module is used to perform the spraying of the anti-carbon deposit coating and the thermal expansion gradient buffer coating with the spraying parameters of each layer and the ultrasonic dispersion pretreatment parameters.

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