A quality detection device for refractory material processing

Abstract

The application relates to the technical field of refractory material detection, and discloses a quality detection device for refractory material processing, which comprises a high-temperature furnace chamber, a protective gas gas path system and an atmosphere self-adaptive control system. The atmosphere self-adaptive control system obtains a material comprehensive demand coefficient by fusing material activity, surface area and apparent porosity through a material demand analysis module, obtains a furnace state coefficient by fusing oxygen partial pressure, temperature and a test stage through an in-furnace state monitoring module, obtains a gas supply efficiency coefficient by fusing inlet pressure, filter differential pressure and gas source dew point through a gas supply system health degree evaluation module, and calculates an atmosphere matching coefficient by combining real-time gas consumption rate and pollutant concentration through a dynamic matching calculation module. Finally, a flow decision and execution module adjusts the protective gas flow in real time according to a reference flow and the two coefficients. The application realizes multi-factor dynamic self-adaptive control of the protective gas flow, and takes into account the atmosphere maintenance effect and operation economy.

Description

Technical Field

[0001] This invention belongs to the field of refractory material testing technology, and in particular relates to a quality testing device for refractory material processing. Background Technology

[0002] Refractory materials are key basic materials in high-temperature industries such as steel, cement, and glass. Their high-temperature mechanical properties (such as high-temperature flexural strength, high-temperature compressive strength, and creep properties) are core indicators for evaluating their service life and reliability. High-temperature mechanical testing machines are commonly used in the industry to test refractory materials. These machines typically include a high-temperature furnace, a loading system, and a protective gas supply system. The protective gas supply system, as an important component of the high-temperature mechanical testing machine, is responsible for supplying inert or reducing protective gases to the furnace. Its function is to isolate the sample from residual oxygen or water vapor in the furnace during high-temperature loading, preventing oxidation, decarburization, and other chemical reactions in carbonaceous or non-oxide refractory materials. This ensures that the measured high-temperature mechanical property data accurately reflect the intrinsic service behavior of the material.

[0003] However, the protective gas path system in existing high-temperature mechanical testing machines has significant defects in its control method: On the one hand, when using a fixed flow rate mode, it cannot adapt to the dynamic changes in protective gas demand at different stages of the test (such as heating, holding, and loading), resulting in gas waste at low temperatures. Meanwhile, at high temperatures and critical loading stages, insufficient flow leads to increased oxygen partial pressure inside the furnace, causing oxidation reactions on the sample surface or inside, resulting in significantly lower and more dispersed high-temperature strength and deformation data. On the other hand, manual adjustment relies on the operator's experience and judgment, resulting in a delayed response, and differences in adjustment between different operators lead to poor repeatability and comparability of test results. These crude control methods not only increase operating costs but also introduce systematic errors, directly impairing the accuracy and reliability of the high-temperature mechanical testing machine's test data. Summary of the Invention

[0004] The purpose of this invention is to provide a quality inspection device for refractory material processing, which aims to solve the above-mentioned problems.

[0005] This invention is implemented as follows: a quality testing device for refractory material processing includes a high-temperature furnace and a protective gas supply system connected to the high-temperature furnace. The protective gas supply system supplies protective gas to the high-temperature furnace. The device also includes an atmosphere adaptive control system, which adjusts the protective gas flow rate of the protective gas supply system connected to the high-temperature furnace in real time. The atmosphere adaptive control system includes: a material demand analysis module, which calculates a comprehensive material demand coefficient based on the material activity coefficient, sample surface area, and sample apparent porosity; a furnace condition monitoring module, which calculates a furnace condition coefficient based on the furnace oxygen partial pressure, furnace absolute temperature, furnace temperature change rate, and test process stage; a gas supply system health assessment module, which calculates a gas supply efficiency coefficient based on the protective gas inlet pressure, filter differential pressure, and gas source dew point; a dynamic matching calculation module, which calculates an atmosphere matching coefficient based on the dynamic reaction gas consumption rate and contaminant gas concentration under the furnace condition coefficient and gas supply efficiency coefficient; and a flow rate decision and execution module, which calculates a target protective gas flow rate based on the baseline protective gas flow rate, the comprehensive material demand coefficient, and the atmosphere matching coefficient, and adjusts the current protective gas flow rate to the target protective gas flow rate.

[0006] A further technical solution involves the following steps for calculating and obtaining the target protective gas flow rate: obtaining the baseline protective gas flow rate, the comprehensive material requirement coefficient, and the atmosphere matching coefficient; determining the target protective gas flow rate through multiplication based on the baseline protective gas flow rate, the comprehensive material requirement coefficient, and the atmosphere matching coefficient, wherein the target protective gas flow rate is positively correlated with both the comprehensive material requirement coefficient and the atmosphere matching coefficient.

[0007] A further technical solution involves the following steps for calculating the comprehensive material demand coefficient: obtaining the material activity coefficient, sample surface area, and sample apparent porosity; performing maximum-minimum normalization on the sample surface area and sample apparent porosity to obtain the sample surface area index and sample apparent porosity index; and calculating the comprehensive material demand coefficient based on the material activity coefficient, sample surface area index, and sample apparent porosity index using a weighted geometric mean or an equivalent fusion algorithm. The comprehensive material demand coefficient is used to comprehensively reflect the sample's basic demand intensity for protective gas; a larger comprehensive material demand coefficient indicates a stronger demand, and its value is between 0 and 1.

[0008] A further technical solution involves calculating the atmosphere matching coefficient as follows: obtaining the furnace state coefficient, gas supply efficiency coefficient, dynamic reaction gas consumption rate, and pollutant gas concentration; comparing the current dynamic reaction gas consumption rate and pollutant gas concentration with the maximum possible reaction gas consumption rate and the maximum allowable pollutant concentration threshold, respectively, to obtain the dynamic reaction gas consumption rate index and the pollutant gas concentration index; and substituting the furnace state coefficient, gas supply efficiency coefficient, dynamic reaction gas consumption rate index, and pollutant gas concentration index into the formula. Obtain the atmosphere matching coefficient , , This indicates a need to increase traffic. This indicates a need to reduce traffic, among which, For system response coefficients, , Used to control the adjustment range. The gas consumption rate index is the dynamic reaction rate index. This refers to the pollutant gas concentration index. This is the furnace internal state coefficient. This is the gas supply efficiency coefficient.

[0009] A further technical solution involves the following steps for calculating the gas supply efficiency coefficient: obtaining the protective gas inlet pressure, filter differential pressure, and gas source dew point; comparing the current protective gas inlet pressure with the minimum inlet pressure required for the current target flow rate, and limiting the upper limit of the ratio to 1 using a min function to obtain the inlet pressure index; comparing the current filter differential pressure with the maximum allowable differential pressure, taking the complement of the ratio, and limiting the upper limit of the complement to 0 using a max function to obtain the filter passing index; comparing the difference between the current gas source dew point and the specified dew point with the allowable dew point exceedance limit, taking the complement of the ratio, and limiting the upper limit of the complement to 0 using a max function to obtain the gas source dryness index; and taking the minimum value among the inlet pressure index, filter passing index, and gas source dryness index as the gas supply efficiency coefficient. , , This indicates that the gas supply system is in excellent condition, with sufficient pressure, unobstructed pipelines, and dry gas source, which can fully support the required flow regulation.

[0010] A further technical solution involves the following steps for calculating and obtaining the furnace state coefficient: obtaining the furnace oxygen partial pressure, furnace absolute temperature, furnace temperature change rate, and test progress stage; comparing the absolute value of the difference between the current furnace oxygen partial pressure and the target oxygen partial pressure with the maximum allowable deviation tolerance, taking the complement of the ratio, and using the max function to limit the upper limit of the ratio to 0, thus obtaining the furnace oxygen partial pressure index; performing maximum-minimum normalization on the current furnace absolute temperature to obtain the furnace absolute temperature factor; and comparing the absolute value of the current furnace temperature change rate with the maximum heating rate to obtain the furnace temperature change factor. Rate factor; The furnace absolute temperature factor and the furnace temperature change rate factor are weighted and fused according to preset weights, and the fusion result is subjected to upper limit processing to obtain the temperature demand index; Among them, the weight of the weighted fusion is used to adjust the influence of temperature level and temperature change rate on protective gas demand, and the upper limit processing limits the temperature demand index within the preset upper limit value; The furnace oxygen partial pressure index, temperature demand index and test process stage coefficient are multiplied and fused to obtain the furnace state coefficient, which is used to comprehensively characterize the urgency of the current furnace operating conditions for protective gas regulation.

[0011] A further technical solution includes a protective gas path system comprising a high-purity gas source cylinder, a pressure reducing valve, a manual shut-off valve, a precision filter, a mass flow controller, and a furnace inlet, connected sequentially via pipelines; wherein the control signal input terminal of the mass flow controller is electrically connected to the output terminal of the atmosphere adaptive control system; differential pressure sensors are connected to both ends of the precision filter to obtain the filter pressure difference; a pressure sensor is installed on the pipeline between the pressure reducing valve and the manual shut-off valve to obtain the protective gas inlet pressure.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0013] 1. By capturing changes in material reaction consumption and furnace contamination levels in real time, the protective gas flow rate is dynamically adjusted to provide sufficient protection during critical stages such as high-temperature loading, avoiding sample oxidation or decarburization caused by atmospheric fluctuations, and significantly improving the authenticity and repeatability of test data.

[0014] 2. Based on the material's own characteristics and the testing process, the basic gas supply is intelligently adjusted. During non-sensitive stages such as low temperature or heat preservation, the flow rate is automatically reduced, realizing the "on-demand supply" of protective gas and effectively reducing gas consumption and operating costs.

[0015] 3. By incorporating the health status (pressure, blockage, dryness) of the gas supply system itself into the control logic, the flow regulation command can be effectively executed within the actual supply capacity, avoiding control failure due to equipment deterioration and enhancing the robustness of the system. Attached Figure Description

[0016] Figure 1 A schematic diagram of the structure of a quality inspection device for refractory material processing provided by the present invention;

[0017] Figure 2 A flowchart of the atmosphere adaptive control system provided by the present invention.

[0018] In the attached diagram: 1. High-purity gas cylinder; 2. Pressure reducing valve; 3. Manual shut-off valve; 4. Precision filter; 5. Mass flow controller; 6. Furnace inlet; 7. High-temperature furnace. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0020] In traditional high-temperature mechanical property testing of refractory materials, the control method of the protective gas path system has significant defects. Specifically, the fixed flow rate mode cannot dynamically match the real-time changes in the test conditions. Specifically, in the low-temperature stage, the constant flow rate leads to excessive supply of protective gas, resulting in resource waste; in the high-temperature and critical loading stages, insufficient flow rate causes fluctuations in the oxygen partial pressure inside the furnace, failing to effectively suppress oxidation and decarburization reactions on or inside the sample surface. Furthermore, the manual adjustment mechanism relies on the operator's experience and judgment, and the response process lags behind changes in the material's reaction rate. This introduces human operational bias, causing systematic distortion of the measured intrinsic mechanical property parameters such as high-temperature flexural strength and high-temperature compressive strength, severely impairing the accuracy of the test data and batch-to-batch comparability.

[0021] For example, when testing magnesia-carbon brick samples, during the furnace temperature rise to 1200°C and mechanical load is applied, the samples exhibit high apparent porosity and a large material activity coefficient, causing the oxygen partial pressure inside the furnace to rise rapidly due to oxidation. At this time, the fixed-flow protective gas system fails to compensate for the gas consumption in a timely manner, and the operator fails to adjust the flow rate synchronously, resulting in a thickening of the decarburized layer on the sample surface. Consequently, the measured flexural strength values ​​remain consistently low, and the data dispersion increases. Furthermore, the fluctuations in the protective gas inlet pressure and the pressure difference changes in precision filter 4 were not incorporated into the adjustment criteria, further exacerbating the instability of the furnace atmosphere and preventing the test results from accurately reflecting the mechanical behavior of the material in actual service environments.

[0022] If the above problems are not resolved, the systematic errors in the test data will continue to accumulate, leading to misjudgments of the service life of refractory materials and potentially causing safety hazards in high-temperature industrial kilns. At the same time, the repeatability defects in the test results will hinder the material research and development process, cause the quality control system to fail, and ultimately affect the reliability of kiln design and production efficiency in industries such as steel and cement.

[0023] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0024] like Figure 1 and Figure 2 As shown, an embodiment of the present invention provides a quality testing device for refractory material processing, including a high-temperature furnace 7 and a protective gas path system connected to the high-temperature furnace 7. The protective gas path system supplies protective gas to the high-temperature furnace 7, which is the core component of the testing device. It provides a controllable high-temperature environment for the refractory material sample to be tested. The temperature inside the furnace can be precisely controlled to simulate the temperature conditions that the refractory material may experience in actual kilns or industrial equipment. The protective gas path system is responsible for delivering protective gas into the high-temperature furnace 7. The protective gas is usually an inert gas or a reducing gas, and its function is to isolate the sample from the oxygen or water vapor that may be present in the furnace, thereby preventing the sample from undergoing chemical reactions such as oxidation and decarburization during high-temperature testing, and ensuring the accuracy of the test results. The device also includes an atmosphere adaptive control system, which is used to adjust the protective gas flow rate of the protective gas path system connected to the high-temperature furnace 7 in real time. The atmosphere adaptive control system includes:

[0025] The materials requirements analysis module calculates the comprehensive material requirements coefficient based on the material activity coefficient, sample surface area, and apparent porosity. This module is used to assess the intrinsic requirements of the refractory material under test for protective gas. The comprehensive material requirements coefficient reflects the material's potential tendency to react at high temperatures and the intensity of its basic requirements for protective gas.

[0026] The furnace condition monitoring module calculates and obtains the furnace condition coefficient based on the furnace oxygen partial pressure, furnace absolute temperature, furnace temperature change rate, and test progress stage. This module is responsible for acquiring the environmental parameters inside the high-temperature furnace in real time. The furnace condition coefficient comprehensively reflects the urgency of the furnace's internal environment's demand for protective gas flow.

[0027] The gas supply system health assessment module calculates the gas supply efficiency coefficient based on the protective gas inlet pressure, filter differential pressure, and gas source dew point. This module is used to evaluate the operating status of the protective gas supply system. The gas supply efficiency coefficient reflects the gas supply system's ability to stably and efficiently provide the required flow rate.

[0028] The dynamic matching calculation module calculates the atmosphere matching coefficient based on the dynamic reaction gas consumption rate and pollutant gas concentration under the furnace state coefficient and gas supply efficiency coefficient. The atmosphere matching coefficient is used to guide the flow rate decision, ensuring that the protective gas flow rate can dynamically adapt to the actual reaction consumption and pollutant removal needs in the furnace.

[0029] The flow rate decision and execution module calculates the target protective gas flow rate based on the baseline protective gas flow rate, the comprehensive material demand coefficient, and the atmosphere matching coefficient, and then adjusts the current protective gas flow rate to the target flow rate. This module is the execution unit of the atmosphere adaptive control system.

[0030] The fixed flow rate mode in existing technologies cannot adapt to the dynamic changes in factors such as material activity, furnace temperature, and reaction rate during the testing process, leading to gas waste or insufficient protection at different stages. For example, in the aforementioned creep test of magnesia-carbon bricks, a fixed flow rate may cause unnecessary consumption at low temperatures, while failing to provide sufficient protection at critical high-temperature stages. This embodiment, through the collaborative work of a material demand analysis module, a furnace condition monitoring module, a gas supply system health assessment module, and a dynamic matching calculation module, can comprehensively and in real time assess the furnace atmosphere demand and gas supply capacity, thereby calculating the precise target protective gas flow rate.

[0031] Furthermore, existing manual adjustment methods are not only slow to respond and unable to keep up with rapidly changing furnace environments, but also highly dependent on operator experience, resulting in poor repeatability and comparability of test results. The flow decision and execution module in this embodiment can automatically and quickly adjust the protective gas path system based on the calculated target protective gas flow rate, eliminating the uncertainty and lag caused by human intervention. This automated and precise control method ensures that the furnace interior remains under ideal protective atmosphere conditions throughout the entire testing cycle, thereby significantly improving the accuracy and reliability of high-temperature mechanical property test data.

[0032] Therefore, this embodiment not only effectively solves the problems of crude protective gas control, low efficiency, and distorted test results in the prior art, but also achieves optimized utilization of protective gas resources through comprehensive consideration of multi-dimensional parameters and intelligent decision-making, reduces operating costs, and provides a more accurate and stable testing platform for the research and development and quality control of refractory materials.

[0033] This application further proposes the following steps for calculating and obtaining the target protective gas flow rate:

[0034] The system acquires the baseline protective gas flow rate, the comprehensive material demand coefficient, and the atmosphere matching coefficient. The baseline protective gas flow rate is a preset initial or reference flow rate value based on the type, size, and testing stage of the refractory material. It can be obtained by user input on the control interface, querying a preset database, or automatically loading by the system according to the current testing stage. The comprehensive material demand coefficient reflects the intrinsic demand intensity of the tested refractory material for protective gas. This coefficient is calculated by the material demand analysis module, and its acquisition method is to directly receive the output value from this module. The atmosphere matching coefficient reflects the degree of matching between the current furnace atmosphere and the ideal state, as well as the health of the gas supply system. This coefficient is calculated by the dynamic matching calculation module, and its acquisition method is to directly receive the output value from this module.

[0035] The target protective gas flow rate is determined by multiplication based on the baseline protective gas flow rate, the comprehensive material requirement coefficient, and the atmosphere matching coefficient. The target protective gas flow rate is positively correlated with both the comprehensive material requirement coefficient and the atmosphere matching coefficient. Specifically, the calculation method involves substituting the baseline protective gas flow rate, the material requirement coefficient, and the atmosphere matching coefficient into the formula. Obtain the target protective gas flow rate ,in, As a reference for protective gas flow rate, This is the comprehensive material demand coefficient. The atmosphere matching coefficient is used as the basis for the formula. This formula uses a multiplicative operation to take the baseline flow rate as the foundation and employs the material comprehensive demand coefficient and atmosphere matching coefficient as correction factors to dynamically adjust the baseline flow rate. This multiplicative relationship allows the various coefficients to influence each other, jointly determining the final flow rate, ensuring the precision and adaptability of flow rate regulation. This calculation process can be executed by a processor in the atmosphere adaptive control system, for example, through control algorithms embedded in microcontrollers, programmable logic controllers (PLCs), or industrial computers.

[0036] The solution in this application introduces an explicit mathematical model, namely the formula. This allows for the precise integration of reference protective gas flow rate, material comprehensive requirement factor, and atmosphere matching factor. First, the system acquires the preset reference protective gas flow rate. This flow rate represents the basic gas volume required to maintain the furnace atmosphere under standard or ideal conditions. Next, the system obtains the comprehensive material requirement coefficient calculated by the material requirements analysis module. This coefficient, as the first correction factor for the baseline flow rate, quantifies the additional or reduced demand for protective gas by the tested refractory material due to its inherent characteristics (such as reactivity, surface area, and apparent porosity). For example, highly reactive materials will... The value is high, thus amplifying the baseline flow rate in the formula. Simultaneously, the system obtains the atmosphere matching coefficient calculated by the dynamic matching calculation module. This coefficient, as the second correction factor, comprehensively reflects the real-time state of the furnace atmosphere (such as oxygen partial pressure, temperature, and testing stage) and the health of the protective gas supply system (such as inlet pressure, filter differential pressure, and gas source dew point). When the furnace atmosphere deviates from the ideal state or there are problems with the gas supply system, The parameters will be adjusted accordingly to guide the increase or decrease of flow rate. Ultimately, these three parameters are combined through multiplication to generate the target protective gas flow rate. This multiplicative relationship ensures that the weights and influences of each factor can be dynamically superimposed and adjusted. For example, if the material demand is high ( (Large) and the atmosphere inside the furnace needs to be better protected. If the material demand is large, the target flow rate will increase significantly; conversely, if the material demand is low ( (Small) or the atmosphere inside the furnace has reached the standard ( If the target flow rate is small, the target flow rate will be reduced accordingly. This calculation method avoids the errors that may be caused by simple superposition or linear adjustment, enabling the flow decision and execution module to achieve fine-grained and adaptive adjustment of the protective gas flow rate based on multi-dimensional real-time data. This effectively solves the problem that it is difficult to accurately control the protective gas flow rate based on experience or a single factor, ensuring the stability and optimization of the atmosphere environment inside the furnace.

[0037] In one specific implementation, the flow decision and execution module can be configured with a microprocessor that pre-stores an algorithm for calculating the target protective gas flow rate. During the detection process, the microprocessor first obtains the current reference protective gas flow rate from system memory or a sensor interface. (For example, the current test phase is preset to 10L / min), material comprehensive demand coefficient (For example, calculated as 0.85 by the material requirements analysis module) and atmosphere matching coefficient (For example, calculated as 1.1 by the dynamic matching calculation module). The microprocessor then substitutes these values ​​into the formula. The calculated flow rate is 9.35 L / min, from which the target protective gas flow rate can be calculated. The target flow rate is 9.35 L / min. After the calculation is completed, the microprocessor sends this target flow rate value to the mass flow controller 5, which then performs the corresponding flow adjustment operation to adjust the actual protective gas flow rate to 9.35 L / min.

[0038] Through the aforementioned technical solution, the atmosphere adaptive control system can organically combine the baseline protective gas flow rate, the comprehensive material demand coefficient, and the atmosphere matching coefficient using a clear mathematical model, thereby accurately calculating the target protective gas flow rate. This flow decision mechanism based on multi-factor multiplication allows the system to fully consider the inherent requirements of the tested material, the real-time dynamics of the furnace atmosphere, and the operating status of the gas supply system, achieving refined and adaptive adjustment of the protective gas flow rate. This not only avoids the problems of excessive or insufficient flow rate that may exist in traditional control methods, but also significantly improves the accuracy and response speed of furnace atmosphere control, ensuring that the refractory material is always in the optimal protective atmosphere environment during the processing quality inspection process, thereby improving the reliability and consistency of the test results.

[0039] This application further proposes the following steps for calculating and obtaining the comprehensive material demand coefficient:

[0040] Obtaining the material activity coefficient, sample surface area, and apparent porosity is crucial. The material activity coefficient characterizes the chemical reactivity of the material itself; for example, some materials react more readily with residual oxygen in the furnace at high temperatures, thus requiring more protective gas. The sample surface area and apparent porosity reflect the size of the physical interface between the material and the furnace atmosphere, as well as the internal structural characteristics. A larger surface area or higher apparent porosity means a greater contact area with the protective gas or potentially harmful gases, potentially leading to faster reaction rates or higher gas consumption, thus increasing the demand for protective gas. Accurate acquisition of these parameters is a prerequisite for subsequent precise calculation of the material's overall demand coefficient.

[0041] Max-min normalization was performed on the sample surface area and apparent porosity to obtain the sample surface area index and apparent porosity index. The purpose was to transform the raw data with different dimensions and numerical ranges to a unified scale, facilitating comprehensive calculations and comparisons in subsequent mathematical models. Max-min normalization is a commonly used method that linearly maps data to a specified interval (e.g., 0 to 1), eliminating the influence of dimensions and allowing the contributions of different physical quantities to be evaluated under the same standard. Besides max-min normalization, data standardization can also be achieved using Z-score normalization (converting data to a distribution with a mean of 0 and a standard deviation of 1) or decimal scaling (scaling data to the range [-1, 1] by moving the decimal point) to ensure that the weights of each parameter in the calculation are reasonably and effectively allocated.

[0042] Based on the material activity coefficient, sample surface area index, and sample apparent porosity index, a comprehensive material demand coefficient is calculated using a weighted geometric mean or an equivalent fusion algorithm. This comprehensive material demand coefficient comprehensively reflects the sample's basic demand intensity for the protective gas; a higher coefficient indicates a stronger demand, and its value ranges from 0 to 1. The specific calculation method involves substituting the material activity coefficient, sample surface area index, and sample apparent porosity index into the formula... Obtain the comprehensive material demand coefficient , , A value close to 1 indicates that the sample has extremely high activity, large surface area, and high porosity, and therefore a very strong requirement for a protective gas. The material activity coefficient, These are preset scalar values ​​based on the material type. For example, ordinary clay bricks are set to 0.2, high-alumina bricks to 0.5, and magnesia-carbon bricks to 0.9. This is the sample surface area index. The apparent porosity index of the sample. , and All are weighting coefficients with values ​​ranging from 0 to 1, and Weighting coefficient , and The relative importance of different factors in material requirements assessment can be adjusted based on actual application scenarios and experience. For example, for certain materials sensitive to surface reactions, the importance of these factors can be appropriately increased. The weighting. This combination method can generate a comprehensive material demand coefficient between 0 and 1. This coefficient intuitively represents the overall demand intensity of the current material for protective gas, providing a quantitative basis for subsequent flow rate decisions. , and The specific value can also be derived from a large amount of historical test data through regression analysis or neural network training and calibration, and pre-stored in the system database to ensure the accuracy of the evaluation model under different materials and working conditions. This formula, through a weighted geometric average, comprehensively considers the combined effects of the material's intrinsic activity, external contact area, and internal pore structure on the protective gas requirement. Among these, the material activity coefficient... It directly reflects the inherent properties of the material, while the sample surface area index and the apparent porosity index of the sample This quantifies the physical structural characteristics of the material.

[0043] This application's solution improves the accuracy of atmosphere adaptive control systems in regulating protective gas flow by precisely quantifying the comprehensive requirements of refractory materials for protective gas. Specifically, it first obtains three key parameters of the refractory material to be tested: the material activity coefficient, sample surface area, and apparent porosity. The material activity coefficient characterizes the chemical reactivity tendency of the material itself, while the sample surface area and apparent porosity reflect the interface and internal structure between the material and the furnace atmosphere. To eliminate the influence of different physical dimensions and numerical ranges on the calculation results, the sample surface area and apparent porosity are subjected to maximum-minimum normalization, converting them into dimensionless sample surface area indices and sample apparent porosity indices, allowing these parameters to be compared and calculated on a uniform scale. Subsequently, the material activity coefficient, the normalized sample surface area index, and the sample apparent porosity index, along with preset weighting coefficients, are substituted into a specific weighted geometric mean formula. This formula cleverly integrates the intrinsic chemical properties and external physical structural characteristics of the material, and by adjusting the weighting coefficients, it can flexibly reflect the relative importance of different factors to the protective gas requirements. Finally, a comprehensive material demand coefficient between 0 and 1 was calculated. This coefficient It can comprehensively and quantitatively characterize the overall intensity of the current refractory materials' demand for protective gas, for example, The closer the value is to 1, the higher the material's activity, surface area, and porosity, indicating a very strong demand for protective gas. In this way, this scheme provides precise material requirement input for the atmosphere adaptive control system, enabling the system to calculate the target protective gas flow rate more intelligently and accurately based on the material's actual characteristics, avoiding the inaccurate flow rate adjustment problems caused by differences in material properties in traditional methods.

[0044] As a specific implementation method, suppose we need to conduct quality testing on a high-alumina brick. First, we obtain the material activity coefficient of the high-alumina brick by consulting a material database or conducting experimental measurements. For example, setting The value is 0.5. Simultaneously, the surface area of ​​the high-alumina brick sample was measured as A, and the apparent porosity was P. To incorporate these raw data into the calculation, the surface area needs to be... The apparent porosity P is then subjected to a maximum-minimum normalization process. For example, if the maximum surface area of ​​all possible samples is known to be... The minimum surface area is Then the sample surface area index It can be done through formula The calculation yielded the same result. Similarly, the apparent porosity index... It can also be calculated in a similar way. Assuming that after normalization, the sample surface area index is obtained... The apparent porosity index of the sample is 0.7. The value is 0.6. Next, weighting coefficients are set; for example, considering the influence of the activity and structure of high-alumina bricks on the protective gas requirement, a weighting coefficient can be set to... It is 0.4. It is 0.3. It is 0.3 and satisfies Substitute these parameters into the formula. Calculated It is 0.58. The value will be used as the comprehensive material demand coefficient. It is sent to the flow decision and execution module, and compared with the reference protective gas flow rate. Atmosphere matching coefficient Together they are used to calculate the final target protective gas flow rate. .

[0045] Through the above technical solution, this application overcomes the limitations of traditional methods in accurately assessing the protective gas requirements of refractory materials. By comprehensively considering the material activity coefficient, sample surface area, and apparent porosity, and employing normalization and a weighted geometric mean formula, this application generates an accurate and quantifiable comprehensive material requirement coefficient. This coefficient truly reflects the actual protective gas requirements of different refractory materials under different physical structures, thus providing more precise input parameters for the atmosphere adaptive control system. This enables the flow decision and execution module to more intelligently calculate the target protective gas flow rate based on the inherent properties and structural characteristics of the material, effectively avoiding resource waste caused by excessive protective gas supply or substandard testing environment due to insufficient supply. Ultimately, this improves the precision and adaptability of the quality testing device for refractory material processing in controlling the protective gas flow rate, ensuring the stability of the testing process and the reliability of the results.

[0046] This application further proposes the following steps for calculating and obtaining the atmosphere matching coefficient:

[0047] The process involves obtaining parameters such as the furnace state coefficient, gas supply efficiency coefficient, dynamic reaction gas consumption rate, and contaminant gas concentration. The furnace state coefficient reflects the ideality of the internal furnace environment and the urgency of the need for protective gas, obtained through parameters such as oxygen partial pressure and temperature monitored by sensors. The gas supply efficiency coefficient assesses the health and support capacity of the protective gas supply system, obtained through parameters such as inlet pressure, filter differential pressure, and gas source dew point. The dynamic reaction gas consumption rate refers to the rate at which protective gas is consumed during the test due to the reaction between the sample and the furnace atmosphere or other factors, and can be estimated through real-time monitoring of gas composition changes or a preset model. The contaminant gas concentration refers to the content of gaseous impurities that may be present in the furnace and are harmful to the test results or equipment operation, detected by a gas analyzer. Accurate acquisition of these parameters is a prerequisite for subsequent precise calculations and adjustments.

[0048] The dynamic reaction gas consumption rate and pollutant gas concentration are compared with the maximum possible reaction gas consumption rate and the maximum permissible pollutant concentration threshold, respectively, to obtain the dynamic reaction gas consumption rate index and the pollutant gas concentration index. This step aims to standardize the original dynamic reaction gas consumption rate and pollutant gas concentration data, transforming them into dimensionless indices for easier subsequent unified calculations and comparisons. The dynamic reaction gas consumption rate index reflects the proportion of current gas consumption relative to the system's maximum capacity; for example, it can be obtained by dividing the current gas consumption rate by the maximum gas consumption rate achievable under the most extreme reaction conditions. The pollutant gas concentration index represents the degree to which the current pollutant level is relative to the acceptable upper limit; for example, it can be obtained by dividing the current pollutant concentration by a preset maximum permissible pollutant concentration threshold. This ratioing process unifies physical quantities with different dimensions into a range of 0 to 1, thus providing standardized input for the comprehensive evaluation of the atmosphere matching coefficient.

[0049] Substituting the furnace state coefficient, gas supply efficiency coefficient, dynamic reaction gas consumption rate index, and pollutant gas concentration index into the formula Obtain the atmosphere matching coefficient , , This indicates a need to increase traffic. This indicates a need to reduce traffic, among which, For system response coefficients, , Used to control the adjustment range. The specific values ​​can be determined through experimental calibration based on the system's dynamic response speed and stability requirements, in order to balance the sensitivity of flow regulation with the stability of the control process; The gas consumption rate index is the dynamic reaction rate index. This refers to the pollutant gas concentration index. This is the furnace internal state coefficient. This step represents the gas supply efficiency coefficient. It is the core calculation process for the atmosphere matching coefficient. Through a comprehensive mathematical model, standardized parameters are weighted and nonlinearly processed to obtain an atmosphere matching coefficient between 0 and 1. This formula takes into account the dynamic reaction gas consumption rate exponent. Pollutant gas concentration index Furnace internal state coefficient and gas supply efficiency coefficient And the system response coefficient was introduced. This allows for the adjustment of the sensitivity of flow rate regulation. This calculation method comprehensively and dynamically assesses the actual demand for atmosphere within the furnace and the capacity of the supply system, thus providing an accurate basis for flow rate decisions. For example, the formula can be integrated into a microprocessor or dedicated computing chip within the atmosphere adaptive control system for real-time calculation, or implemented using a programmable logic controller (PLC).

[0050] This application introduces a refined method for calculating atmosphere matching coefficients, aiming to improve the accuracy and responsiveness of protective gas flow regulation in quality testing devices for refractory material processing. The method first comprehensively acquires key parameters affecting furnace atmosphere balance and gas supply, including furnace state coefficient, gas supply efficiency coefficient, dynamic reaction gas consumption rate, and contaminant gas concentration. These parameters quantitatively describe the current atmosphere condition from multiple dimensions, such as the ideality of the furnace environment, the health of the gas supply system, actual gas consumption, and the content of potential harmful impurities. To unify these heterogeneous data for calculation, this scheme standardizes the dynamic reaction gas consumption rate and contaminant gas concentration. Specifically, the current dynamic reaction gas consumption rate is compared with the maximum possible reaction gas consumption rate to obtain the dynamic reaction gas consumption rate index; simultaneously, the current contaminant gas concentration is compared with the maximum permissible contaminant concentration threshold to obtain the contaminant gas concentration index. This ratioing process maps the original data to a unified dimensionless interval, eliminating dimensional differences and enabling effective comprehensive evaluation of different parameters. Subsequently, these standardized indices, along with the furnace state coefficient and gas supply efficiency coefficient, are substituted into a preset comprehensive calculation formula. This formula cleverly combines the actual demand inside the furnace (reflected by the dynamic reaction gas consumption rate index and the pollutant gas concentration index) with the system supply capacity (reflected by the furnace state coefficient and the gas supply efficiency coefficient), and uses the system response coefficient as a reference. Adjust the sensitivity of the flow rate adjustment. Limit the calculation results using the min and max functions to ensure atmosphere matching. It remains between 0 and 1, thus providing a stable and meaningful regulation signal. When When this occurs, it indicates an increase in the demand for furnace atmosphere or insufficient supply capacity, requiring an increase in the protective gas flow rate; when When the atmosphere demand decreases or the supply is sufficient, the protective gas flow rate can be reduced. This calculation mechanism allows the dynamic matching calculation module to comprehensively consider multiple factors and generate a matching coefficient that accurately reflects the current atmosphere conditions and adjustment requirements. This atmosphere matching coefficient is then used by the flow decision and execution module to calculate the target protective gas flow rate and guide the protective gas path system to make corresponding flow adjustments. Compared to adjustment methods that rely solely on a single parameter or simple threshold judgment, this scheme, through comprehensive evaluation and refined calculation of multiple parameters, can more accurately capture the dynamic changes in the furnace atmosphere and the actual condition of the supply system, thereby achieving more intelligent and efficient adaptive control of the protective gas flow rate and effectively avoiding the problems of decreased detection accuracy or gas waste caused by improper flow adjustment.

[0051] For example, the dynamic matching calculation module in an atmosphere adaptive control system can be implemented by an embedded controller, such as a high-performance ARM Cortex-M series microcontroller. This microcontroller receives sensor signals such as furnace oxygen partial pressure and furnace absolute temperature from the furnace condition monitoring module via an analog input interface, and sensor signals such as protective gas inlet pressure and filter differential pressure from the gas supply system health assessment module. Simultaneously, it acquires dynamic reaction gas consumption rate and contaminant gas concentration data via a digital communication interface (such as Modbus or CAN bus). This data may be provided by a standalone online gas analyzer or a software module based on reaction kinetics models. After acquiring all the necessary parameters, the microcontroller first performs ratio processing. For example, it divides the current dynamic reaction gas consumption rate (in L / min) by a preset maximum possible reaction gas consumption rate (e.g., 10 L / min) to obtain the dynamic reaction gas consumption rate index. Similarly, the pollutant gas concentration index is obtained by dividing the current pollutant gas concentration (in ppm) by the maximum permissible pollutant concentration threshold (e.g., 50 ppm). Subsequently, the microcontroller processes these indices along with the obtained furnace state coefficients. and gas supply efficiency coefficient Substitute into the preset formula Calculations are performed. Among them, the system response coefficients... It can be preset to 0.8 to balance the sensitivity and stability of the adjustment. The calculated atmosphere matching coefficient... The data is sent to the flow decision and execution module via the microcontroller's digital output port. This module may be a standalone PID controller or a software algorithm integrated into the same microcontroller, used to further calculate the target protective gas flow rate and control the mass flow controller. The entire calculation process can be completed in milliseconds, ensuring the real-time performance and accuracy of the atmosphere matching coefficient.

[0052] Through the above technical solution, the atmosphere adaptive control system of the refractory material processing quality inspection device can overcome the problem of inaccurate assessment of furnace atmosphere demand and supply capacity in traditional flow regulation methods. By comprehensively considering multi-dimensional information such as furnace conditions, gas supply health, dynamic gas consumption rate, and contaminant concentration, and using a refined mathematical model for calculation, the obtained atmosphere matching coefficient can more accurately reflect the actual demand of the current furnace atmosphere and the support capacity of the supply system. This allows the flow decision and execution module to calculate the target protective gas flow rate based on more precise input, thereby achieving intelligent, dynamic, and high-precision regulation of the protective gas flow rate. This regulation method not only effectively maintains the stability and purity of the furnace atmosphere, ensuring the accuracy of refractory material quality inspection, but also avoids unnecessary waste of protective gas, significantly improving the efficiency and economy of the entire inspection process.

[0053] This application further proposes the following steps for calculating and obtaining the gas supply efficiency coefficient:

[0054] The protective gas inlet pressure, filter differential pressure, and gas source dew point are measured. The protective gas inlet pressure refers to the pressure of the protective gas before it enters the gas supply system or a specific control unit. Its function is to reflect the adequacy of the gas supply source pressure and is a fundamental parameter for assessing gas supply capacity. This pressure can be obtained in real time by installing a pressure sensor at the gas pipeline inlet; for example, a piezoresistive or capacitive pressure sensor can be used. The filter differential pressure refers to the pressure difference generated before and after the protective gas passes through the filter. Changes in this pressure difference can effectively indicate the degree of filter blockage; a larger differential pressure usually means more severe filter blockage and greater resistance to gas flow. The filter differential pressure can be obtained by installing pressure sensors on both sides of the filter inlet and outlet and calculating the difference between them; or by directly measuring it using a differential pressure sensor. The gas source dew point is an indicator of the water vapor content in the protective gas; a lower dew point indicates a drier gas. In refractory material processing quality testing, gas dryness is crucial to the purity of the furnace atmosphere. An excessively high dew point may cause water vapor to react with the material, affecting the test results. The dew point of the gas source can be monitored in real time using a dew point meter, such as a capacitive dew point sensor or an alumina dew point sensor.

[0055] The inlet pressure index is obtained by comparing the current protective gas inlet pressure with the minimum inlet pressure required for the current target flow rate, and then using a min function to limit the ratio to an upper limit of 1. By comparing the actual inlet pressure with the minimum pressure required to meet the current target flow rate, pressure adequacy can be assessed. After ratio processing, if the actual pressure is higher than the required minimum pressure, the index is 1 (indicating sufficient pressure); if it is lower than the required minimum pressure, the index is less than 1, reflecting the degree of pressure insufficiency. This ensures that the index will not exceed 1 when the pressure is too high, thus avoiding overestimation of supply capacity.

[0056] The filter throughput index is obtained by comparing the current filter differential pressure with the maximum allowable differential pressure, taking the complement of the ratio (i.e., 1 minus the ratio), and then using the max function to limit the upper limit of the ratio and the lower limit of the complement to 0. This process is used to assess the degree to which the filter impedes gas flow. The ratio of the filter differential pressure to the maximum allowable differential pressure reflects the severity of the blockage. Taking the complement of the ratio (1 minus the ratio) converts the degree of blockage into a throughput index; that is, the smaller the differential pressure (the lighter the blockage), the closer the throughput index is to 1; the larger the differential pressure (the heavier the blockage), the closer the throughput index is to 0. The max function limits the upper limit of the ratio and the lower limit of the complement to 0, ensuring that even if the differential pressure exceeds the maximum allowable value, the index will not be negative and will always remain within the range of 0 to 1.

[0057] The gas source dryness index is obtained by comparing the difference between the current gas source dew point and the specified dew point with the allowable dew point exceedance tolerance, taking the complement of the ratio (i.e., one minus the ratio), and then using a max function to limit the upper limit of the ratio and the lower limit of the complement to 0. This step aims to quantify the impact of gas source dryness on atmosphere purity. By comparing the difference between the actual dew point and the specified dew point, and combining this with the allowable exceedance tolerance, the dryness of the gas can be assessed to determine whether the requirements are met. The complement of the ratio converts the degree of dew point exceedance into a dryness index; the closer the dew point is to or below the specified requirement, the closer the index is to 1; the greater the dew point exceedance, the closer the index is to 0. The max function limit ensures that the index is not negative and remains within the range of 0 to 1.

[0058] The minimum value among the inlet pressure index, filter throughput index, and gas source dryness index is taken as the gas supply efficiency coefficient. , , This indicates that the gas supply system is in excellent condition, with sufficient pressure, unobstructed pipelines, and dry gas source, fully capable of supporting the required flow regulation. This step comprehensively assesses the overall health of the gas supply system by taking the minimum value of each index. This means that the efficiency of the gas supply system is limited by its weakest link. For example, even if the inlet pressure and gas source dryness are good, if the filter is severely clogged, the supply efficiency of the entire system will be reduced. This "weakest link effect" assessment method accurately reflects the actual supply capacity of the system.

[0059] This application introduces a gas supply efficiency coefficient. This method quantifies the health status of the protective gas supply system to ensure that the atmosphere adaptive control system in the refractory material processing quality inspection device can accurately and effectively regulate the protective gas flow rate. The coefficient is calculated first by real-time monitoring of three key parameters: protective gas inlet pressure, filter differential pressure, and gas source dew point. Inlet pressure reflects the gas supply capacity, filter differential pressure indicates pipeline patency, and gas source dew point represents gas purity. The system then transforms this raw monitoring data into standardized indices. Specifically, the inlet pressure is compared to the minimum pressure required for the current target flow rate to generate an inlet pressure index, with an upper limit limited to 1 to ensure that sufficient pressure is not overestimated. The filter differential pressure is compared to the maximum allowable differential pressure and rounded to generate a filter throughput index, with a lower limit limited to 0 to reflect the impact of blockage on throughput. Similarly, the gas source dew point is compared to the difference between the specified dew point and the allowable over-limit and rounded to generate a gas source dryness index, also with a lower limit limited to 0 to assess gas purity. Finally, the gas supply efficiency coefficient is calculated. It was determined to be the minimum of the three standardized indices. This method of taking the minimum ensures that the efficiency assessment of the entire gas supply system is not masked by any single well-performing component, but is determined by its weakest link. For example, even if the inlet pressure is sufficient and the gas is dry, if the filter is severely clogged, the gas supply efficiency coefficient will be low. The gas supply efficiency coefficient will be lowered due to the lower filter pass rate. It was then used by the dynamic matching calculation module to calculate the atmosphere matching coefficient. This, in turn, affects the flow decision and execution module's calculation of the target protective gas flow rate. In this way, the atmosphere adaptive control system, when making flow adjustment decisions, not only considers the furnace conditions and material requirements but also fully takes into account the actual capacity of the gas supply system itself. This avoids control failures or poor performance due to insufficient supply capacity, making the adjustment of the protective gas flow rate more precise and reliable.

[0060] The following is a specific example to illustrate this. In a quality inspection device for refractory material processing, the gas supply efficiency coefficient can be calculated using the following method. First, the inlet pressure of the protective gas is obtained through a pressure sensor installed in the protective gas circuit system, for example, a pressure sensor is installed on the pipeline between the pressure reducing valve 2 and the manual shut-off valve 3. Simultaneously, differential pressure sensors are connected to both ends of the precision filter 4 to obtain the filter differential pressure in real time. Furthermore, a dew point meter is installed at the gas source outlet or before entering the furnace to obtain the gas source dew point. After obtaining this real-time data, the gas supply system health assessment module in the atmosphere adaptive control system can perform the following processing: Assuming the minimum inlet pressure required under the current target flow rate is 0.5 MPa, while the actual measured protective gas inlet pressure is 0.6 MPa, the inlet pressure index is min(0.6 / 0.5,1)=1. Assuming the maximum allowable filter differential pressure is 10 kPa, while the actual measured filter differential pressure is 3 kPa, the filter throughput index is max(1-(3 / 10),0)=0.7. Assuming the specification requires a dew point of -60℃ with an allowable exceedance of 5℃, and the actual measured dew point of the gas source is -58℃ (i.e., a difference of 2℃ from the specification requirement), then the gas source dryness index is max(1-(2 / 5),0)=0.6. Finally, the gas supply system health assessment module will calculate the gas supply efficiency coefficient. The minimum value is min(1, 0.7, 0.6) = 0.6. This calculation result will be used as the atmosphere matching coefficient. One of the inputs to the calculation guides subsequent decisions regarding the target protective gas flow rate.

[0061] Through the above technical solution, the atmosphere adaptive control system can fully consider the actual operating conditions of the protective gas supply system when adjusting the protective gas flow rate. By real-time monitoring of inlet pressure, filter differential pressure, and gas source dew point, and converting these into a comprehensive gas supply efficiency coefficient, the system can accurately assess whether the gas source is sufficient, the pipeline is unobstructed, and the gas purity meets the standards. This avoids the system blindly issuing high flow commands when the gas supply capacity is insufficient, resulting in a discrepancy between the actual flow rate and the target flow rate, which affects the precise control of the furnace atmosphere. When there are potential problems in the gas supply system (such as pressure drop, filter blockage, or gas moisture), this coefficient will decrease accordingly, prompting the atmosphere adaptive control system to be more conservative or make necessary adjustments when calculating the atmosphere matching coefficient and target protective gas flow rate to adapt to the current supply capacity. This ensures that even under less than ideal supply conditions, the relative stability and purity of the furnace atmosphere can be maintained, thereby guaranteeing the accuracy and reliability of refractory material quality testing.

[0062] This application further proposes the following steps for calculating and obtaining the furnace state coefficients:

[0063] Acquiring information on the partial pressure of oxygen inside the furnace, the absolute temperature of the furnace chamber, the rate of change of the furnace temperature, and the testing process stages is fundamental to comprehensively understanding the furnace environment. The partial pressure of oxygen inside the furnace directly reflects the redox state of the atmosphere and is crucial for maintaining a protective atmosphere. It can be monitored in real time using a zirconia oxygen sensor or an electrochemical oxygen sensor. The absolute temperature of the furnace chamber is a key factor affecting the reactivity of materials and the rate of gas consumption, and is typically measured using thermocouples or infrared thermometers. The rate of change of the furnace temperature reveals the dynamic trend of the furnace temperature, such as the rate of heating or cooling, which is instructive for predicting gas demand and adjusting the response speed. It can be obtained by differential calculation of continuous temperature measurement data. The testing process stages provide macroscopic time and process background information, such as purging, heating, holding, loading, or cooling. Different stages have different requirements and sensitivities to the atmosphere. This information can be automatically identified by the control system according to the preset process flow or manually entered by the operator.

[0064] The oxygen partial pressure index is obtained by comparing the absolute value of the difference between the current oxygen partial pressure and the target oxygen partial pressure with the maximum allowable deviation. The complement of this ratio (i.e., one minus the ratio) is then used, and the upper limit of the ratio and the lower limit of the complement are set to 0 using a max function. This step quantifies the degree to which the oxygen partial pressure deviates from the ideal state. This index directly reflects the accuracy of the current oxygen partial pressure control; the closer the oxygen partial pressure is to the target value, the higher the index, indicating better atmosphere control. For example, if the target oxygen partial pressure is 10 ppm, the maximum allowable deviation is 2 ppm, and the current oxygen partial pressure is 11 ppm, then the absolute value of the difference is 1 ppm, the ratio is 0.5, the complement is 0.5, and the oxygen partial pressure index is 0.5.

[0065] The current furnace absolute temperature is normalized to a maximum-minimum value to obtain the furnace absolute temperature factor. This step unifies the measured values ​​across different temperature ranges onto a dimensionless scale, facilitating comprehensive calculations with other parameters. For example, the lowest operating temperature of the furnace can be set as the minimum value, and the highest operating temperature as the maximum value, mapping the current temperature to a value between 0 and 1. This approach allows for standardized evaluation of the impact of temperature under different operating conditions.

[0066] The furnace temperature change rate factor is obtained by comparing the absolute value of the current furnace temperature change rate with the maximum heating rate. This factor is used to assess the drastic nature of temperature changes within the furnace. When the furnace temperature changes rapidly, such as with rapid heating, the reactivity of the material may increase significantly, and the demand for protective gas will also change accordingly. This factor reflects this dynamic demand; for example, if the maximum heating rate is 10°C / min and the current heating rate is 5°C / min, then the factor is 0.5.

[0067] The furnace absolute temperature factor and the furnace temperature change rate factor are weighted and fused according to preset weights, and the fusion result is then subjected to upper limit processing to obtain the temperature demand index. The weights in the weighted fusion are used to adjust the influence of temperature level and temperature change rate on the protective gas demand, and the upper limit processing restricts the temperature demand index within a preset upper limit value. The specific calculation method is as follows: substitute the furnace absolute temperature factor and the furnace temperature change rate factor into the formula... Obtain the temperature demand index ,in, Temperature weights are defined as values ​​ranging from 0 to 1. The absolute temperature factor of the furnace. Furnace temperature change rate factor; temperature demand index The combined impact of the current furnace temperature level and temperature change trend on the protective gas demand was comprehensively considered. Among these, As a temperature weighting factor, the system can adjust the relative importance of the current temperature level and the rate of temperature change in temperature requirement assessment based on actual process needs. For example, in some processes, maintaining a specific temperature is more critical than rapid heating; in this case, the weighting factor can be appropriately increased. The value, Specifically, values ​​can be assigned through preset strategies or dynamic algorithms.

[0068] The furnace internal oxygen partial pressure index, temperature demand index, and test process stage coefficient are multiplied and fused to obtain the furnace internal state coefficient. This coefficient comprehensively characterizes the urgency of the current furnace internal operating conditions' demand for protective gas regulation. Specifically, the calculation method involves substituting the furnace internal oxygen partial pressure index, furnace temperature change rate factor, and other parameters into the formula. Obtain the furnace state coefficient , , A value close to 1 indicates an ideal furnace environment (oxygen partial pressure precisely met, at a critical high-temperature stage, and normal pressure), with an urgent need to maintain or regulate the protective gas. This coefficient is a comprehensive indicator used to fully assess the ideality of the furnace atmosphere and the urgency of maintaining or regulating the protective gas. This refers to the oxygen partial pressure index inside the furnace. The furnace temperature change rate factor, This is the testing process phase. Based on preset values ​​for each stage, for example: 0.8 for the purging stage, 0.9 for the heating stage, 1.0 for the heat preservation and loading stage, and 0.6 for the cooling stage. Specific values ​​can be derived from a large amount of historical test data through regression analysis or neural network training and calibration, and are pre-stored in the system database to ensure the accuracy of the evaluation model under different materials and working conditions. This formula organically combines the accuracy of oxygen partial pressure, the dynamic requirements of temperature, and the macroscopic influences of the testing phase through multiplication operations, making... It can sensitively reflect subtle changes in the furnace environment. When When the value is close to 1, it indicates that the furnace condition is very ideal, such as the oxygen partial pressure is precisely within the target range, the furnace is in a critical high-temperature stage, and the pressure is normal. At this time, the need to maintain or regulate the protective gas is most urgent, and the system needs to maintain a high level of responsiveness.

[0069] The quality inspection device for refractory material processing disclosed in this application utilizes an atmosphere adaptive control system to achieve precise and dynamic adjustment of the protective gas flow rate within a high-temperature furnace. Specifically, the furnace condition monitoring module performs refined calculations of the furnace condition coefficients. This provides crucial feedback on the furnace environment for the entire control system. The calculation process first comprehensively acquires four core parameters: furnace oxygen partial pressure, furnace absolute temperature, furnace temperature change rate, and the testing process stage. These parameters characterize the real-time furnace environment from multiple dimensions, including atmosphere purity, thermodynamic conditions, and process flow. Specifically, the furnace oxygen partial pressure index... The calculation, by standardizing the deviation between the current oxygen partial pressure and the target value, and performing complementation and amplitude limiting operations, ensures that the index accurately reflects the degree to which the oxygen partial pressure meets the target, and that a higher value indicates more precise control. Simultaneously, the furnace absolute temperature factor... and furnace temperature change rate factor The temperature factors are obtained by processing the maximum-minimum normalization sum and the ratio to the maximum heating rate, transforming the static temperature level and dynamic trend into quantifiable dimensionless parameters. Subsequently, these two temperature factors are substituted into a weighted summation formula to generate the temperature demand index. This index comprehensively reflects the urgency of the demand for protective gas under furnace temperature conditions, with weighting coefficients... The introduction of this feature allows the system to flexibly adjust the emphasis on temperature stability and rate of change according to different process stages. Ultimately, the oxygen partial pressure index in the furnace... Temperature demand index and preset values ​​representing the test process stages. The furnace state coefficients are formed through multiplication operations. This multiplicative combination method ensures that protective gas is only used when all key factors are in ideal condition or when there is a strong demand for it. Only then can a higher value be achieved, thereby prompting the atmosphere adaptive control system to use the atmosphere matching coefficient in the flow decision and execution module. The calculations allow for more proactive adjustments to the protective gas flow rate. For example, when the oxygen partial pressure inside the furnace deviates significantly from the target value, when temperature changes drastically, or when the furnace is in a critical heat preservation loading phase, This will increase accordingly, thus affecting the atmosphere matching coefficient. This prompts the system to increase the protective gas flow rate to quickly correct the furnace atmosphere or provide more adequate protection during critical stages. This multi-dimensional, dynamically weighted evaluation mechanism enables the furnace state coefficient to... It can accurately capture subtle changes and potential risks in the furnace environment, thereby guiding the real-time and intelligent adjustment of protective gas flow. This significantly improves the response speed and accuracy of atmosphere control, effectively avoids material performance degradation or test result distortion caused by furnace atmosphere fluctuations, and ensures the reliability of refractory material processing quality testing.

[0070] As a specific implementation method, during the operation of the quality inspection device for refractory material processing, the furnace condition monitoring module in the atmosphere adaptive control system can calculate the furnace condition coefficient in the following manner. First, the oxygen partial pressure inside the furnace is acquired in real time using a zirconia oxygen sensor installed within the high-temperature furnace, for example, a current reading of 12 ppm. Simultaneously, the absolute temperature of the furnace is acquired via a K-type thermocouple array, for example, currently 1500℃. The furnace temperature change rate is calculated by sampling continuous temperature data, for example, currently +8℃ / min (indicating a temperature rise). Furthermore, the control system identifies the current "heating stage" according to a preset process program, corresponding to the test progress stage. The preset value is 0.9. Next, the various indices and factors are calculated. Assuming the target oxygen partial pressure is 10 ppm and the maximum allowable deviation is 2 ppm, the absolute value of the difference between the current oxygen partial pressure and the target value is |12-10| = 2 ppm. The ratio is 2 / 2 = 1. Taking the complement of the ratio, 1-1 = 0. Using the max function with a lower limit of 0, the in-furnace oxygen partial pressure index... The value is 0. This indicates that the oxygen partial pressure has reached the upper limit of the allowable deviation and requires attention. For the furnace absolute temperature, assuming the minimum operating temperature is 200℃ and the maximum operating temperature is 1600℃, the current furnace absolute temperature of 1500℃ is normalized to a maximum-min, resulting in a furnace absolute temperature factor of 0.9286. For the furnace temperature change rate, assuming the maximum heating rate is 10℃ / min, the current absolute value of the furnace temperature change rate is 8℃ / min. After ratio processing, the furnace temperature change rate factor is 0.8. Then, the temperature demand index is calculated. Assuming temperature weighting Set to 0.6. Calculation results The value is 0.87716. Finally, the oxygen partial pressure index in the furnace is... The calculation result is 0, temperature demand index. The calculation result is 0.87716 and the testing process stage. Substitute the value 0.9 into the formula The furnace state coefficient was calculated. The value is 0. In this example, although the furnace is in the heating stage and the temperature is high, the oxygen partial pressure inside the furnace has reached the upper limit of the allowable deviation, resulting in an oxygen partial pressure index of 0, which ultimately leads to a furnace state coefficient of 0. The value is 0. This indicates a serious problem with the current furnace atmosphere control, requiring immediate action. The value will be further passed to the dynamic matching calculation module, affecting the atmosphere matching coefficient. The calculation guides the flow decision and execution module to adjust the protective gas flow accordingly. For example, the system may determine that the protective gas flow needs to be increased significantly to reduce the oxygen partial pressure.

[0071] Through the above technical solution, the quality testing device for refractory material processing can achieve a refined and multi-dimensional assessment of the furnace's internal condition. This solution comprehensively considers the accuracy of the furnace's oxygen partial pressure, the absolute level of the furnace temperature and its dynamic trends, and incorporates process background information at each testing stage, thereby calculating a more comprehensive and accurate furnace condition coefficient. This comprehensive assessment mechanism overcomes the limitations of single-parameter or static assessments, enabling the atmosphere adaptive control system to more sensitively capture subtle changes and potential risks in the furnace environment. For example, when there are slight fluctuations in the furnace's oxygen partial pressure, or when the furnace temperature is at a critical high level or undergoing rapid heating, the furnace condition coefficient can promptly reflect the urgency of the protective gas requirement. This allows the flow decision and execution module to make more timely and appropriate adjustments to the protective gas flow rate based on more accurate furnace condition information, effectively avoiding material oxidation, performance degradation, or distorted test results caused by improper furnace atmosphere control. Ultimately, this solution significantly improved the response speed, accuracy, and stability of atmosphere control during the quality inspection process for refractory material processing, ensuring the reliability of test results and extending the service life of the furnace and related components.

[0072] like Figure 1 As shown, in a preferred embodiment of the present invention, the protective gas circuit system includes a high-purity gas source cylinder 1, a pressure reducing valve 2, a manual shut-off valve 3, a precision filter 4, a mass flow controller 5, and a furnace inlet 6, which are connected in sequence through pipelines; wherein, the control signal input terminal of the mass flow controller 5 is electrically connected to the output terminal of the atmosphere adaptive control system; differential pressure sensors are connected to both ends of the precision filter 4 to obtain the filter pressure difference; a pressure sensor is provided on the pipeline between the pressure reducing valve 2 and the manual shut-off valve 3 to obtain the protective gas inlet pressure.

[0073] High-purity gas cylinder 1 serves as the storage and supply source for protective gases, typically storing high-purity inert gases such as argon and nitrogen to ensure the purity of the atmosphere within the furnace. Pressure reducing valve 2 reduces the gas pressure in high-pressure gas cylinder 1 to the required operating pressure range of the system, ensuring the safe operation of downstream equipment and the stability of flow control. This can be achieved using diaphragm-type or piston-type pressure reducing valves, with the outlet pressure set by adjusting the spring preload. Manual shut-off valve 3 allows for manual shut-off or opening of the gas path when needed, facilitating system maintenance, repair, or emergency shutdown. It can be a ball valve, gate valve, or needle valve, and the gas path can be opened or closed manually. Precision filter 4 removes minute particulate impurities from the protective gas, preventing them from entering the furnace and contaminating samples or clogging downstream flow control equipment, ensuring gas purity. It can use sintered metal filter elements, polytetrafluoroethylene (PTFE) filter elements, or glass fiber filter elements, with different pore sizes selected based on filtration precision requirements. The mass flow controller 5 is the core component for achieving precise control of the protective gas flow rate. It can accurately adjust the flow rate of the protective gas through the gas path based on the control signal from the atmosphere adaptive control system. Its implementation can include thermal mass flow controllers, Coriolis mass flow controllers, etc., which regulate the flow rate by controlling the opening of internal valves via electrical signals. The furnace inlet 6 is the channel through which the protective gas enters the high-temperature furnace. It is typically designed with a diffusion structure to ensure that the protective gas is evenly distributed inside the furnace.

[0074] The control signal input terminal of the mass flow controller 5 is electrically connected to the output terminal of the atmosphere adaptive control system, enabling the atmosphere adaptive control system to send control commands to the mass flow controller 5 in real time based on its calculated target protective gas flow rate, thereby achieving precise and dynamic adjustment of the protective gas flow rate. Differential pressure sensors are connected to both ends of the precision filter 4. These sensors monitor the pressure difference before and after the filter 4 in real time. Changes in the pressure difference can determine the degree of clogging of the filter 4, providing crucial data for calculating the gas supply efficiency coefficient. The differential pressure sensor can be a differential pressure transmitter or similar device, converting the pressure difference into an electrical signal output. A pressure sensor is installed on the pipeline between the pressure reducing valve 2 and the manual shut-off valve 3. This sensor monitors the inlet pressure of the protective gas entering the gas path system in real time, providing another crucial parameter for calculating the gas supply efficiency coefficient. The pressure sensor can be a diffused silicon pressure sensor, a ceramic pressure sensor, or similar device, converting the pressure value into an electrical signal output.

[0075] This application's solution constructs a complete and controllable protective gas path system by sequentially connecting a high-purity gas source cylinder 1, a pressure reducing valve 2, a manual shut-off valve 3, a precision filter 4, a mass flow controller 5, and a furnace inlet 6 via pipelines. The control signal input of the mass flow controller 5 is electrically connected to the output of the atmosphere adaptive control system, enabling the system to directly control the flow rate of the protective gas. More importantly, by connecting differential pressure sensors to both ends of the precision filter 4 and installing pressure sensors on the pipeline between the pressure reducing valve 2 and the manual shut-off valve 3, this gas path system can acquire two key parameters in real time: the filter differential pressure and the protective gas inlet pressure. This real-time data is utilized by the gas supply system health assessment module in the atmosphere adaptive control system to calculate the gas supply efficiency coefficient. For example, excessively high filter differential pressure indicates filter blockage and decreased gas supply efficiency; insufficient protective gas inlet pressure also indicates a problem with the gas supply. Through the precise data provided by these sensors, the atmosphere adaptive control system can accurately assess the current health and efficiency of the gas supply system, thereby more accurately calculating the atmosphere matching coefficient and ultimately determining the most suitable target protective gas flow rate. This combination of precise physical-level monitoring and intelligent control algorithms enables the entire refractory material processing quality inspection device to achieve closed-loop, adaptive, and high-precision control of the furnace atmosphere.

[0076] In one specific implementation, the protective gas system can use a high-purity argon cylinder 1 as the gas source, with the pressure stabilized at 0.5 MPa by a high-precision diaphragm pressure reducing valve 2. Downstream of the pressure reducing valve 2, a stainless steel manual ball valve 3 is installed for daily operation and maintenance. Following this is a precision filter 4 with a 0.01-micron PTFE filter element, connected at both ends to a differential pressure transmitter with a range of 0-10 kPa via compression fittings for real-time monitoring of the filter differential pressure. A diffused silicon pressure sensor with a range of 0-1 MPa is installed on the pipeline between the pressure reducing valve 2 and the manual ball valve 3 to acquire the protective gas inlet pressure. The core flow control component can be a thermal mass flow controller 5, whose control signal input communicates with the output of the atmosphere adaptive control system via an RS485 bus, receiving the flow setpoint and precisely adjusting the argon flow rate. Finally, the adjusted argon gas enters the high-temperature furnace through a furnace inlet 6 with a porous diffuser plate.

[0077] Through the above technical solution, the quality inspection device for refractory material processing can acquire key operating parameters of the protective gas system in real time and accurately, such as the protective gas inlet pressure and filter differential pressure. This data provides reliable input to the gas supply system health assessment module in the atmosphere adaptive control system, enabling the system to accurately assess gas supply efficiency and thus more accurately calculate the atmosphere matching coefficient and target protective gas flow rate. This significantly improves the accuracy and reliability of the atmosphere adaptive control system in regulating the protective gas flow rate, effectively avoiding flow control deviations caused by abnormal gas system conditions, ensuring the stability and purity of the furnace atmosphere, and thereby improving the accuracy and consistency of refractory material quality inspection.

[0078] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A quality inspection device for refractory material processing, comprising a high-temperature furnace and a protective gas supply system connected to the high-temperature furnace, the protective gas supply system being used to supply protective gas to the high-temperature furnace, characterized in that, It also includes: an atmosphere adaptive control system, which is used to adjust the protective gas flow rate of the protective gas path system connected to the high-temperature furnace in real time, the atmosphere adaptive control system comprising: The material requirements analysis module calculates the comprehensive material requirements coefficient based on the material activity coefficient, sample surface area, and sample apparent porosity. The furnace condition monitoring module calculates and obtains the furnace condition coefficient based on the furnace oxygen partial pressure, furnace absolute temperature, furnace temperature change rate, and test process stage. The gas supply system health assessment module calculates and obtains the gas supply efficiency coefficient based on the protective gas inlet pressure, filter pressure difference, and gas source dew point. The dynamic matching calculation module calculates the atmosphere matching coefficient based on the dynamic reaction gas consumption rate and pollutant gas concentration under the furnace state coefficient and gas supply efficiency coefficient. The flow rate decision and execution module calculates the target protective gas flow rate based on the baseline protective gas flow rate, the material comprehensive demand coefficient, and the atmosphere matching coefficient, and adjusts the current protective gas flow rate to the target protective gas flow rate.

2. The quality inspection device for refractory material processing according to claim 1, characterized in that, The steps for calculating and obtaining the target protective gas flow rate are as follows: Obtain the baseline protective gas flow rate, material comprehensive demand coefficient, and atmosphere matching coefficient; The target protective gas flow rate is determined by multiplication based on the baseline protective gas flow rate, the comprehensive material requirement coefficient, and the atmosphere matching coefficient, wherein the target protective gas flow rate is positively correlated with both the comprehensive material requirement coefficient and the atmosphere matching coefficient.

3. The quality inspection device for refractory material processing according to claim 2, characterized in that, The steps for calculating and obtaining the comprehensive material demand coefficient are as follows: Obtain the material activity coefficient, sample surface area, and sample apparent porosity; The sample surface area and apparent porosity were subjected to maximum-minimum normalization to obtain the sample surface area index and the sample apparent porosity index. Based on the material activity coefficient, sample surface area index, and sample apparent porosity index, the comprehensive material demand coefficient is calculated using a weighted geometric average or an equivalent fusion algorithm. The material comprehensive demand coefficient is used to comprehensively reflect the basic demand intensity of the sample for protective gas. The larger the material comprehensive demand coefficient, the stronger the demand. Its value is between 0 and 1.

4. The quality inspection device for refractory material processing according to claim 2, characterized in that, The steps for calculating and obtaining the atmosphere matching coefficient are as follows: Obtain the furnace state coefficient, gas supply efficiency coefficient, dynamic reaction gas consumption rate, and pollutant gas concentration; The current dynamic reaction gas consumption rate and pollutant gas concentration are compared with the maximum possible reaction gas consumption rate and the maximum allowable pollutant concentration threshold, respectively, to obtain the dynamic reaction gas consumption rate index and the pollutant gas concentration index. Substituting the furnace state coefficient, gas supply efficiency coefficient, dynamic reaction gas consumption rate index, and pollutant gas concentration index into the formula Obtain the atmosphere matching coefficient , , This indicates a need to increase traffic. This indicates a need to reduce traffic, among which, For system response coefficients, , Used to control the adjustment range. The gas consumption rate index is the dynamic reaction rate index. This refers to the pollutant gas concentration index. This is the furnace internal state coefficient. This is the gas supply efficiency coefficient.

5. The quality inspection device for refractory material processing according to claim 4, characterized in that, The steps for calculating and obtaining the gas supply efficiency coefficient are as follows: Obtain the protective gas inlet pressure, filter differential pressure, and gas source dew point; The ratio of the current protective gas inlet pressure to the minimum inlet pressure required for the current target flow rate is processed, and the inlet pressure index is obtained by using the min function to limit the upper limit of the ratio to 1. The filter throughput index is obtained by comparing the current filter differential pressure with the maximum allowable differential pressure, taking the complement of the ratio, and using the max function to limit the upper limit of the ratio and the lower limit of the complement to 0. The difference between the current gas source dew point and the specified dew point is compared with the allowable dew point exceedance limit. The complement of the ratio is taken and the upper limit of the complement is limited to 0 using the max function to obtain the gas source dryness index. The minimum value among the inlet pressure index, filter throughput index, and gas source dryness index is taken as the gas supply efficiency coefficient. , , This indicates that the gas supply system is in excellent condition, with sufficient pressure, unobstructed pipelines, and dry gas source, which can fully support the required flow regulation.

6. The quality inspection device for refractory material processing according to claim 4, characterized in that, The steps for calculating and obtaining the furnace state coefficients are as follows: Acquire the partial pressure of oxygen in the furnace, the absolute temperature of the furnace, the rate of change of furnace temperature, and the testing process stages; The absolute value of the difference between the current oxygen partial pressure in the furnace and the target oxygen partial pressure is compared with the maximum allowable deviation limit. The complement of the ratio is taken, and the upper limit of the ratio complement is limited to 0 by the max function. Then, the oxygen partial pressure index in the furnace is obtained. The current furnace absolute temperature is processed by maximum-minimum normalization to obtain the furnace absolute temperature factor. The furnace temperature change rate factor is obtained by comparing the absolute value of the current furnace temperature change rate with the maximum heating rate. The furnace absolute temperature factor and the furnace temperature change rate factor are weighted and fused according to preset weights, and the fusion result is subjected to upper limit limiting processing to obtain the temperature demand index. The weights of the weighted fusion are used to adjust the degree of influence of temperature level and temperature change rate on the demand for protective gas, and the upper limit limiting processing restricts the temperature demand index to a preset upper limit value. The furnace internal oxygen partial pressure index, temperature demand index, and test process stage coefficient are multiplied and fused to obtain the furnace internal state coefficient. The furnace internal state coefficient is used to comprehensively characterize the urgency of the current furnace internal operating conditions for protective gas regulation.

7. The quality inspection device for refractory material processing according to claim 5, characterized in that, The protective gas path system includes a high-purity gas source cylinder, a pressure reducing valve, a manual shut-off valve, a precision filter, a mass flow controller, and a furnace inlet, which are connected in sequence via pipelines. The control signal input terminal of the mass flow controller is electrically connected to the output terminal of the atmosphere adaptive control system. Differential pressure sensors are connected to both ends of the precision filter to obtain the filter pressure difference. A pressure sensor is installed on the pipeline between the pressure reducing valve and the manual shut-off valve to obtain the protective gas inlet pressure.

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