System and method for detecting and analyzing components of high-carbon ferrochrome production slag

Abstract

The invention belongs to the technical field of slag component detection, and particularly relates to a high-carbon ferrochrome production slag component detection and analysis system and method, multi-point temperature acquisition is implemented on a slag discharge flow path, and then a slag sampling strategy is optimized based on temperature distribution uniformity, so that accurate sampling aiming at different areas is realized, and the detection accuracy is improved. The sampling flexibility and representativeness are greatly improved, so that the accuracy and reliability of subsequent component detection are remarkably improved, meanwhile, after furnace slag stratified sampling, stratified component detection is carried out firstly, quantitative analysis of furnace slag component distribution is achieved, and the selection proportion of each stratified sample is dynamically adjusted based on the analysis result; the mixed sample is prepared and subjected to component detection, the global analysis capacity of the whole mixed slag is fully reflected, it is ensured that the mixed sample can comprehensively reflect the overall component characteristics of the slag, and the accuracy and reliability of the final detection result are improved to the maximum extent.

Description

Technical Field

[0001] The invention belongs to the technical field of slag composition detection, and in particular relates to a system and method for detecting and analyzing the composition of slag in high-carbon ferrochrome production. Background Art

[0002] High carbon ferrochrome is an iron alloy mainly containing chromium and 4%-8% carbon. It is made by high-temperature smelting of chromium ore and reducing agent and is widely used in the steel industry. During production, chromium oxide is reduced to metallic chromium and a large amount of slag is produced. In order to meet the product performance requirements, slag-forming agents need to be added to regulate the slag composition and performance. Since the slag composition directly affects the smelting stability and product quality, it is very important to frequently analyze the slag composition to adjust the type and amount of slag-forming agents. Therefore, accurate slag composition analysis is the core link of process control.

[0003] There are some technical solutions for slag composition detection in the prior art. For example, the Chinese invention patent with publication number CN114910467B proposes an online monitoring and analysis method and system for metallurgical slag. The method first completes the debugging preparation of the detection device by establishing a standard working curve of the element to be analyzed, and then uses a normal temperature digestion method or a high temperature melting digestion method to digest the metallurgical slag to generate a slag digestion solution. Finally, at least one method of ICP spectroscopy, electrode method or titration analysis is used to detect the element content in the slag digestion solution, aiming to take into account both timeliness and accuracy and meet the needs of real-time monitoring of slag composition during the smelting process.

[0004] In addition, the Chinese invention patent with publication number CN109507172A proposes an online detection and analysis device for the composition of high-temperature liquid slag in steelmaking. The device consists of a slag composition rapid analyzer and an optical probe. During detection, the optical probe is inserted into the liquid slag, and efficient detection is achieved through the slag composition rapid analyzer.

[0005] Although the above two technical solutions have improved the efficiency of slag composition analysis to a certain extent, there are still deficiencies in analysis accuracy, which are specifically manifested in the following aspects: 1. The first solution does not fully consider the differences in component distribution caused by uneven temperature distribution when the slag is discharged, and thus lacks the optimization setting for sampling uniformity. During the slag discharge process, the existence of temperature gradients may lead to component stratification: the slag in the high-temperature area has stronger fluidity and more uniform component distribution, while the slag in the low-temperature area may show local enrichment or depletion due to increased viscosity. If the sampling method is too fixed and the sampling strategy is not dynamically adjusted according to the characteristics of different temperature zones, it may lead to insufficient representativeness of the collected samples, thereby affecting the accuracy of the final test results.

[0006] 2. Although the second scheme recognizes that slag is a molten mixture between solid and liquid, and inserts an optical probe into the liquid slag to obtain data (based on the judgment that the composition of liquid slag is relatively more uniform), this judgment is subjective and does not use rational data to analyze the actual distribution characteristics of the slag composition, which will weaken the reliability of the test results; in addition, the detection method of the optical probe is essentially limited to the local area of ​​the slag, and it is impossible to achieve a global analysis of the overall mixed slag. This locality may cause the information of certain key components to be omitted, especially when there is spatial heterogeneity or local enrichment in the slag, the comprehensiveness and accuracy of the test results will be significantly affected. Summary of the invention

[0007] The present invention aims to overcome the deficiencies in the prior art and proposes a system and method for detecting and analyzing the composition of high-carbon ferrochrome production slag, which achieves high-precision and global detection of the slag composition by optimizing the sampling method and composition distribution analysis strategy during the high-carbon ferrochrome slag composition detection process.

[0008] The purpose of the present invention can be achieved through the following technical solutions: The first aspect of the present invention provides a high-carbon ferrochrome production slag composition detection and analysis system, including the following modules: Temperature distribution acquisition module: multiple temperature measuring points are arranged on the layer area divided by the flow path of the slag discharge port to collect slag temperature data and evaluate the uniformity of temperature distribution.

[0009] Slag sampling module: When the temperature distribution is assessed to be uniform, single-point sampling is started and component detection is performed directly; otherwise, stratified sampling is started.

[0010] Sampling stratification processing module: take part of the stratified sampling slag sample as the test sample.

[0011] Layered component detection module: Conduct component detection on each layer of test samples to obtain data on the content of each component, and use this to evaluate the uniformity of slag component distribution.

[0012] Preliminary mixing ratio determination module: Determine the preliminary mixing ratio of the remaining slag samples in each layer according to the uniformity of the slag composition distribution, and extract samples in proportion and then perform homogenization treatment to obtain preliminary mixed samples.

[0013] Mixing ratio dynamic adjustment module: performs component detection on the preliminary mixed sample and dynamically adjusts the preliminary mixing ratio based on the deviation of the component detection to complete the mixed sample component detection.

[0014] The second aspect of the present invention proposes a method for detecting and analyzing the composition of high carbon ferrochrome production slag, comprising the following steps: S1: arranging multiple temperature measuring points on the layer area divided by the flow path of the slag discharge outlet to collect slag temperature data and evaluate the uniformity of temperature distribution.

[0015] S2: When the temperature distribution is evaluated to be uniform, single-point sampling is started and S3 is executed; otherwise, stratified sampling is started and S4-S7 are executed.

[0016] S3: Conduct composition testing on the slag samples sampled at a single point.

[0017] S4: Take part of the stratified sampling slag sample as the test sample.

[0018] S5: Conduct component testing on each layer of test samples to obtain data on the content of each component, and use this data to evaluate the uniformity of slag component distribution.

[0019] S6: Determine the preliminary mixing ratio of the remaining slag samples in each layer according to the uniformity of the slag composition distribution, extract samples in proportion, and perform homogenization treatment to obtain preliminary mixed samples.

[0020] S7: Perform component detection on the preliminary mixed sample, and dynamically adjust the preliminary mixing ratio based on the deviation of the component detection to complete the component detection of the mixed sample.

[0021] Combining all the above technical solutions, the positive effects of the present invention are as follows: 1. The present invention implements multi-point temperature collection on the slag discharge flow path, and then optimizes the slag sampling strategy based on the uniformity of temperature distribution, so as to achieve accurate sampling in different areas, greatly improve the flexibility and representativeness of sampling, thereby significantly improving the accuracy and reliability of subsequent component detection, and providing a solid guarantee for the refined control of the high-carbon ferrochrome production process.

[0022] 2. The present invention realizes the quantitative analysis of the slag composition distribution by first performing stratified composition detection after stratified sampling of the slag, and dynamically adjusts the mixing ratio of each stratified sample based on the analysis result to prepare a mixed sample and conducts composition detection on it, which fully reflects the global analysis capability of the overall mixed slag, ensures that the mixed sample can comprehensively reflect the overall composition characteristics of the slag, and maximizes the accuracy and reliability of the final test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0024] Figure 1 A schematic diagram of the collaborative relationship between modules of a high-carbon ferrochrome production slag composition detection and analysis system provided in Example 1 of the present invention.

[0025] Figure 2 It is a schematic diagram of the composition of the slag sampling module in the present invention.

[0026] Figure 3A step diagram of a method for detecting and analyzing the composition of high-carbon ferrochrome production slag provided in Example 2 of the present invention.

[0027] Figure 4 A schematic diagram of the computer hardware structure provided for Example 3 of the present invention.

[0028] Reference numerals: 100 —bus, 101 —processor, 102 —memory, 103 —communication interface. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] Example 1

[0031] The invention provides a high carbon ferrochrome production slag composition detection and analysis system, comprising a temperature distribution acquisition module, a slag sampling module, a sampling layer processing module, a layer composition detection module, a preliminary mixing ratio determination module and a mixing ratio dynamic adjustment module.

[0032] like Figure 1 As shown, the overall collaborative relationship between the above modules is as follows: the temperature distribution acquisition module takes the starting point and guides the slag sampling strategy by evaluating the uniformity of temperature distribution.

[0033] Intermediate links: slag sampling module, sampling stratification processing module and stratification composition detection module complete sampling, stratification processing and composition detection in turn, and gradually refine the analysis.

[0034] Output end: The preliminary mixing ratio determination module and the mixing ratio dynamic adjustment module work together, and through multiple iterative optimizations, ultimately achieve global high-precision detection of the entire mixed slag.

[0035] The temperature distribution acquisition module is used to arrange multiple temperature measurement points on the hierarchical area divided by the flow path of the slag discharge outlet, collect temperature data of the slag when it is discharged in real time, and evaluate the uniformity of temperature distribution.

[0036] It is important to understand that slag is a high-temperature molten mixture with a certain viscosity and fluidity. Its flow behavior is affected by gravity, temperature distribution, and the structure of the discharge port, and a continuous flow path will naturally form during the discharge process. The slag discharge path is usually in a columnar or conical flow form with a certain height. This is because during the discharge process, the slag changes temperature due to contact with the external environment, the surface cools faster, and the fluidity decreases; while the internal temperature is higher, and the fluidity is stronger. This temperature gradient causes the slag to be layered along the flow path.

[0037] As a method for implementing the above scheme, multiple temperature measuring points are arranged on the hierarchical areas divided by the flow path of the slag discharge outlet. See the following process: the flow path is divided into a surface area, a middle area, and a bottom area according to the geometric height of the slag discharge path.

[0038] The above-mentioned mid-surface area is close to the air side, has a lower temperature, a faster cooling rate, and a higher viscosity, and may be enriched with low-melting-point substances.

[0039] The middle area has moderate temperature and good fluidity, and is the main flow area of ​​the slag.

[0040] The bottom area is close to the high-temperature heat source or the molten steel side, has the highest temperature and the strongest fluidity, and may be enriched with high-melting-point substances.

[0041] The above division of the surface, middle and bottom layers according to the geometric shape of the flow path is to better reflect the stratified characteristics of the slag caused by the temperature gradient and uneven distribution of components. This division method not only helps with accurate sampling, but also provides basic support for achieving high-precision global detection.

[0042] After the area is divided, temperature measuring points are usually arranged on the surface, middle and bottom layers respectively to cover the entire slag flow area.

[0043] When arranging specific temperature measurement points, the flow rate and flow velocity of slag discharge can be collected, and the total number of temperature measurement points can be estimated using empirical formulas. ,in Indicates the total number of temperature measurement points. Indicates the slag capacity, represents the slag flow path length, represents the slag flow velocity, Indicates the correction factor, which is determined based on actual equipment and process conditions.

[0044] It should be emphasized that although the flow rate, flow velocity and flow path length of slag discharge have different dimensions in the above empirical formula, the final result can be explained by physical meaning and applied to the layout of temperature measurement points.

[0045] In the above example, suppose , , , , substituting into the above empirical formula, the total number of temperature measurement points estimated is 20.

[0046] It should be added that when arranging the temperature measuring points, the number of temperature measuring points needs to be determined first, which should be determined according to factors such as slag flow rate and flow velocity. This is because the slag flow rate and flow velocity directly affect the residence time, temperature distribution and component stratification of the slag on the flow path of the discharge outlet. A larger flow rate or a faster flow velocity will cause the slag to cool rapidly during the discharge process, forming a significant temperature gradient. Therefore, it is necessary to reasonably arrange the temperature measuring points according to these parameters. Specifically, if the slag flow rate is large, the flow path is long and the component distribution is complex, the number of temperature measuring points needs to be increased to capture more details. If the slag flow rate is small, the flow path is short and the component distribution is relatively uniform, the number of temperature measuring points can be reduced. In the present invention, the number of temperature measuring points on the slag flow path is determined according to the empirical formula because the empirical formula is usually based on a large amount of experimental data and practical application summary, and the number of temperature measuring points that need to be arranged can be estimated more accurately to ensure that the temperature distribution on the entire flow path is fully covered. In addition, limited resources (such as sensors, data acquisition equipment, etc.) can be reasonably allocated under the premise of ensuring detection accuracy, avoiding the cost increase caused by over-configuration, while ensuring that key areas are adequately monitored.

[0047] According to the estimated total number of temperature measuring points, the temperature measuring points are arranged at equal intervals in the divided surface area, middle area and bottom area.

[0048] In the specific implementation of the above scheme, the temperature measuring points in each layer are arranged at equal intervals in proportion to each other, taking into account the different temperature distribution states in each layer, so as to determine the proportion of temperature measuring points in each layer. The surface area has a thinner thickness and a faster cooling rate, so the number of temperature measuring points can be less, but it is necessary to ensure that the entire surface is covered. The middle layer is the main flow area, and the number of temperature measuring points should account for a larger proportion to fully reflect the temperature distribution. The bottom layer has the highest temperature and complex composition, so the number of temperature measuring points should also be more to capture local temperature changes.

[0049] As an example operation, the number of temperature measurement points in each layer area can be allocated according to the empirical allocation ratio (such as 20% for the surface layer, 50% for the middle layer, and 30% for the bottom layer).

[0050] Furthermore, when arranging the temperature measuring points in each layer area, an equal interval method is adopted to ensure the average arrangement of the temperature measuring points in each layer area.

[0051] It should be noted that when selecting temperature measuring equipment, it must have good high temperature resistance and adapt to the extreme environment during slag discharge. For example, high-precision thermocouples can be selected because of their fast response speed, high accuracy, and high temperature resistance. At the same time, it is also necessary to ensure that the data collection time of all temperature measurement points is consistent to avoid errors caused by time deviation.

[0052] As a further implementation of the above scheme, the temperature distribution uniformity is evaluated as follows: the average temperature and the temperature standard deviation of the slag temperature at each temperature measuring point on each layer area on the flow path of the slag discharge outlet are calculated.

[0053] Define the temperature distribution uniformity formula ,in represents the temperature distribution uniformity index, represents the temperature standard deviation, Indicates the average temperature.

[0054] It should be understood that in the above temperature distribution uniformity formula It reflects the temperature variation coefficient, which is used to measure the relative discreteness of temperature distribution. The temperature distribution uniformity index is defined by subtracting the temperature variation coefficient from 1. When the temperature variation is greater, the temperature distribution uniformity is smaller. The closer the temperature distribution uniformity index is to 1, the more uniform the temperature distribution is.

[0055] The above expression formula for temperature distribution uniformity is easy to explain and apply in practice. In addition, in the field of engineering optimization, high uniformity of temperature distribution is usually pursued to ensure process stability and product quality. Compared with directly minimizing the temperature variation coefficient, by defining the value 1 minus the temperature variation coefficient as the temperature distribution uniformity index and maximizing this index as the objective function, the optimization goal can be more clearly reflected, that is, the pursuit of maximum uniformity of temperature distribution. This expression not only simplifies the mathematical expression of the optimization problem, but also improves its operability in engineering practice.

[0056] Substitute the average temperature and temperature standard deviation calculated for each layer into the temperature distribution uniformity formula to obtain the temperature distribution uniformity index for each region.

[0057] The temperature data of all temperature measuring points in all layer areas are combined to calculate the overall average temperature and temperature standard deviation and then imported into the temperature distribution uniformity formula to obtain the overall temperature distribution uniformity index.

[0058] As an example of the data for the above temperature distribution uniformity analysis, assume that we have three layer regions (surface layer, middle layer, bottom layer), and the slag temperature data at the temperature measurement points are shown in Table 1 (unit: °C).

[0059] Table 1: Slag temperature data at some temperature measurement points in the layer area

[0060]

[0061] The average temperature and standard deviation of each layer are calculated by using the data in the above table and substituted into the temperature distribution uniformity formula to obtain , , .

[0062] Combine the slag temperatures at all temperature measurement points to get the overall average temperature and temperature standard deviation , substituting into the temperature distribution uniformity formula, we get .

[0063] The temperature distribution uniformity index of each layer area and the total temperature distribution uniformity index are compared with the set threshold value. If both reach the set threshold value, it is evaluated that the slag temperature distribution on the flow path of the slag discharge outlet is uniform; otherwise, it is evaluated that the temperature distribution is uneven.

[0064] Continuing to apply the above example, assuming that the set threshold value of the temperature distribution uniformity index is 0.98, under the above example, the temperature distribution uniformity index of all layer areas and the total temperature distribution uniformity index are both greater than 0.98, and the slag temperature distribution on the flow path of the slag discharge outlet is evaluated to be uniform.

[0065] The above-mentioned temperature distribution uniformity analysis based on the slag temperature at different temperature measuring points in each layer of the slag flow path not only analyzes the temperature distribution uniformity of each area, but also comprehensively considers the overall situation of all temperature measuring points. This "local + global" analysis method can more comprehensively reflect the slag temperature distribution characteristics.

[0066] The slag sampling module starts single-point sampling and directly performs component detection when it is assessed that the temperature distribution is uniform, otherwise it starts stratified sampling.

[0067] It should be explained that when the temperature distribution along the slag flow path has been well studied or is expected to be very uniform, the results of a single point sampling can represent the overall situation. In this case, there is no need to conduct a comprehensive sampling to save time and resources.

[0068] It should be added that in the single-point sampling mode, since only one slag sample is collected, this sample will be directly used for the final composition analysis when the composition is tested. However, in practical applications, it is an overly idealized condition to assume that the temperature distribution on the slag flow path is completely uniform. In fact, the temperature distribution of slag is usually uneven due to various factors during the flow process. This unevenness may have a significant impact on the physical and chemical properties of the slag composition, thereby affecting the accuracy of the test results. Therefore, in the actual sampling process, in order to more comprehensively reflect the overall characteristics of the slag and its spatial heterogeneity, the stratified sampling method is widely used to ensure that the collected samples are more representative and reliable.

[0069] In the improved operation of the above scheme, the single-point sampling is implemented as follows: the deviation between the slag temperature of each temperature measuring point in all layer areas and the overall average temperature is calculated, and then the temperature measuring point with the minimum deviation is taken as the single-point sampling position. This ensures that the single-point sampling position can accurately reflect the overall characteristics of the slag, thereby improving the detection efficiency and the reliability of the results.

[0070] In a further improved operation of the above scheme, the stratified sampling is implemented as follows: the temperature distribution uniformity index of each layer area is compared with the set threshold.

[0071] For the layer area where the temperature distribution uniformity index reaches the set threshold, the deviation between the slag temperature of each temperature measuring point in the area and the average temperature of the area is calculated, and the temperature measuring point with the smallest deviation is selected as the sampling position of the area.

[0072] In the above stratified sampling, for the layer area whose temperature distribution uniformity index reaches the set threshold, it means that the temperature distribution of this layer area is relatively uniform, and the setting of its sampling point is equivalent to the above-mentioned single-point sampling.

[0073] For the layer area where the temperature distribution uniformity index does not reach the set threshold, the temperature measurement points corresponding to the highest and lowest temperatures in the area are selected as the sampling positions of the area. At the same time, the temperature gradients of adjacent temperature measurement points are calculated for the temperature measurement points arranged in sequence according to the positions in the area. Specifically, ,in Indicates two adjacent temperature measurement points and The temperature gradient, and All represent the temperature measurement point number. , Respectively represent two adjacent temperature measurement points and Temperature difference and distance.

[0074] By calculating the temperature gradient of two adjacent temperature measuring points and comparing it with the configured critical value, if the temperature gradient of two adjacent temperature measuring points is greater than the critical value, an auxiliary sampling point is added in the middle of the two adjacent temperature measuring points.

[0075] It is important to know that the temperature measurement points corresponding to the highest and lowest temperatures can reflect the extremes of the temperature distribution in the area. Temperature gradient calculation is used to assess the severity of temperature changes. If the gradient is too large, it indicates that there may be significant heat flow or temperature anomalies in the area, and additional sampling points are needed to capture these changes. The addition of auxiliary sampling points can more fully reflect the details of the temperature distribution and avoid missing important information.

[0076] In the example implementation of the above operation, it is assumed that the slag temperature data at the temperature measuring point in a certain layer area on the slag flow path are as shown in Table 2.

[0077] Table 2: Slag temperature data at temperature measurement points

[0078]

[0079] The temperature distribution uniformity index of this layer is calculated from the data in the table to be 0.97, which does not reach the threshold of 0.98. At this time, the temperature measurement points corresponding to the highest temperature (1250) and the lowest temperature (1150) are selected as sampling positions, and the temperature gradient of adjacent temperature measurement points is calculated. , , , , when compared with the critical value of the temperature gradient, assuming and If it is greater than the critical value, an auxiliary sampling point is added between the corresponding temperature measurement points.

[0080] The present invention effectively reduces the number of redundant sampling points and significantly improves the sampling efficiency by selecting the temperature measurement point with the smallest deviation from the average temperature in the area with uniform temperature distribution as the sampling position. In the area with uneven temperature distribution, the density of sampling points is increased in a targeted manner by screening extreme temperature points and calculating the temperature gradient, thus avoiding the waste of resources caused by global intensive sampling. This method comprehensively considers local characteristics and global characteristics, and flexibly adjusts the sampling strategy according to the temperature distribution characteristics of different regions, so that representative slag samples can be obtained more accurately.

[0081] In a supplementary implementation of the above scheme, the slag sampling module also includes a sampling device consisting of a sampling terminal, a data interface, a positioning unit, and a control unit.

[0082] The sampling terminal mentioned above is the part that comes into direct contact with the slag and is responsible for performing specific sampling operations. Different sampling terminals (such as drill type, scraper type or straw type) can be selected according to the state of the slag. The drill type is suitable for harder or solidified slag, the scraper type is suitable for slag with a smoother surface or semi-solid state, and the straw type is suitable for liquid or highly fluid slag.

[0083] The above data interface receives the temperature data of the temperature measurement point in real time and feeds back the sampling results to the control unit, realizing data collection, transmission and feedback, and providing support for subsequent analysis and control.

[0084] The above-mentioned positioning unit is used to locate the specific position of the sampling terminal on the slag flow path to ensure the accuracy and repeatability of the sampling point.

[0085] The control unit generates sampling instructions based on the temperature distribution data and other input information (such as process parameters, historical data, etc.) to control the action of the sampling terminal.

[0086] The connections between the above components are as follows Figure 2 shown.

[0087] It should be noted that in Figure 2 The sampling terminal is fixed on the positioning unit through a mechanical connection, so that the sampling terminal can be driven by the positioning unit to move to a specified position.

[0088] It is worth noting that the sampling equipment needs to rely on a positioning unit to accurately determine the sampling location. In the specific positioning implementation, optical positioning can be used as an example, such as arranging optical marking points or reflectors on the slag flow path, and measuring the relative position of the sampling terminal and the marking point by a laser scanner. The advantage of using this positioning method is non-contact measurement, which is suitable for high temperature environments, but the limitation is that it is greatly interfered by smoke and light.

[0089] Another example is to use laser radar to implement positioning, by emitting laser and receiving reflected signals, calculating the distance and angle between the sampling terminal and the target point. The advantages of this positioning operation are high precision and strong anti-interference ability, but the limitation is the high equipment cost.

[0090] Another example is electromagnetic positioning, where electromagnetic sensors are arranged near the slag flow path and positioning is performed by detecting the electromagnetic signal generated by the sampling head. This has the advantage of not being affected by light or smoke, but the limitation is that additional electromagnetic sensors need to be arranged, which increases system complexity and hardware requirements.

[0091] In actual positioning operations, the appropriate positioning method can be selected according to specific needs (such as environmental conditions, accuracy requirements, cost constraints, etc.) to ensure that the positioning function of the sampling equipment operates efficiently and reliably.

[0092] The sampling and stratification processing module takes part of the stratified sampling slag sample as a test sample.

[0093] It should be noted that the above-mentioned selection of part of the slag sample for stratified sampling as the test sample is to select a part of the slag sample collected from each sampling point during the stratified sampling process to form the test sample of the corresponding sampling point. This means that the test sample of each sampling point is extracted independently, ensuring the representativeness of each layer and each point.

[0094] The layered component detection module performs component detection on each layer of detection samples to obtain content data of each component, thereby evaluating the uniformity of slag component distribution.

[0095] As a preferred embodiment, the components of the test samples of each layer may be tested by X-ray fluorescence spectroscopy, atomic absorption spectroscopy, etc.

[0096] The specific implementation of evaluating the uniformity of slag composition distribution in the above scheme is as follows: the component content data of each layer of test samples are used to calculate the average content and content standard deviation of the same component in all layer areas.

[0097] The ingredient content data mentioned above can be understood as the ingredient ratio.

[0098] It should be noted that the component content data of the test samples of each layer mentioned above refers to the average value of the content of each component at each sampling point obtained by analyzing the test samples of each sampling point in each layer. Specifically, this data is calculated based on the statistical average content of each component in the test samples of all sampling points in each layer, aiming to quantify and characterize the composition characteristics of each layer of slag.

[0099] The coefficient of variation of the content distribution of each component was calculated using the average content and standard deviation of each component in all layer areas.

[0100] The coefficient of variation of the content distribution of various components is compared with the preset allowable threshold, wherein the allowable threshold can be preset according to the requirements of the production process for the slag composition distribution. If the coefficient of variation of the content distribution of all components meets the allowable threshold, the slag composition distribution is evaluated to be uniform, otherwise the slag composition distribution is evaluated to be uneven.

[0101] It should be pointed out that the above analysis of the uniformity of slag composition distribution based on the component content data of the test samples in each layer adopts statistical methods to transform qualitative problems into quantitative analysis, making the evaluation results more scientific and objective.

[0102] The preliminary mixing ratio determination module determines the preliminary mixing ratio of each layer of residual slag samples according to the uniformity of slag component distribution, and extracts samples in proportion and then performs homogenization treatment to obtain preliminary mixed samples.

[0103] It should be noted that the homogenization treatment mentioned above refers to the process of fully mixing and homogenizing the slag samples extracted from various layers through physical or chemical means to reduce the composition differences between the samples and ensure that the final mixed sample can accurately reflect the characteristics of the entire slag. In the specific operation, stirring and mixing is often used.

[0104] The preliminary mixing ratio of each layer of residual slag samples is determined according to the uniformity of the slag composition distribution mentioned above, and the following process is referred to: when the uniformity of the slag composition distribution is evaluated, the mixing ratio of each layer of residual slag samples is determined to be the same ratio.

[0105] As an explanation for the above operation, when the slag composition is evenly distributed, it means that there is no significant difference in the composition content between the layers. In this case, the contribution of each layer to the overall characteristics is equivalent, so there is no need to specially distinguish or adjust the mixing ratio. Selecting samples in the same proportion can fully reflect the characteristics of the entire slag system.

[0106] When evaluating the uneven distribution of slag components, the content of each component in each layer area is combined with the volume of each layer area to calculate the theoretical proportion of each component in the overall slag. , where Indicates The ingredient in The content of the layer area, Indicates the slag composition number, , represents the number of layers, , in the present invention, the number of layers is 3, wherein Indicates the bottom layer, Represents the middle layer, Indicates the surface, Indicates The volume of the layer area.

[0107] It should be noted that the core idea of ​​the above theoretical proportion calculation is to quantify the relative contribution of each component in the entire slag system by the volume-weighted average of each layer. This ratio reflects the absolute contribution of each component based on its content and volume distribution, rather than the normalized proportion directly presented in percentage form. Therefore, without normalization, the calculated cumulative value of each component proportion may not be equal to 100%. If you need to ensure that the sum of all component proportions is exactly 100%, you can adjust the original proportion of each component through the normalization method, where the normalization formula is , Represents the normalized This process can ensure that the final result meets the normalization requirements of probability statistics and accurately reflects the actual distribution characteristics of each component in the overall slag system.

[0108] As an example of the above theoretical proportion data, assume that there are three layers of slag samples (bottom layer, middle layer, and surface layer), and there are three components (component 1, component 2, and component 3), where the content data of each component in each layer area are shown in Table 3.

[0109] Table 3: Content data of each component in each layer area

[0110]

[0111] The volumes of the bottom layer, middle layer, and surface layer are 100 cubic meters, 150 cubic meters, and 200 cubic meters, respectively. Substituting the data in the table into the theoretical proportion calculation, the normalized result of the theoretical proportion of each component in the overall slag is: , , .

[0112] Using the formula Determine the preliminary mixing ratio of each layer of residual slag samples .

[0113] In the above formula reflects the total volume-weighted content of each layer in the slag flow path, It reflects the relative weight of each layer and represents the importance of each layer area. The layer area with a larger weight has a larger initial mixing ratio.

[0114] Continuing to apply the sample data in Table 3 above, the preliminary mixing ratio of the residual slag samples in each layer is: , , .

[0115] The mixing ratio dynamic adjustment module performs component detection on the preliminary mixed sample, and dynamically adjusts the preliminary mixing ratio based on the deviation of the component detection to complete the component detection of the mixed sample.

[0116] In the preferred implementation of the above scheme, the process of dynamically adjusting the preliminary mixing ratio based on the deviation of component detection is as follows: the preliminary mixed sample is subjected to component detection, and the deviation between the detection result and the theoretical proportion of each component in the overall slag is analyzed; if there is a deviation in the analysis, the preliminary mixing ratio of each layer is adjusted based on the component deviation.

[0117] In the improved implementation of the above scheme, the deviation analysis can calculate the deviation between the component test results of the preliminary mixed sample and the theoretical proportion of each component in the overall slag, that is, make a difference, and compare the difference result with the preset allowable deviation. If the deviation of a certain component is greater than the allowable deviation, there is a deviation in the analysis.

[0118] In a further improved implementation of the above scheme, the process of adjusting the initial mixing ratio of each layer based on the component deviation is as follows: define the deviation correction factor of each component , , Indicates The deviation of a component is obtained by subtracting the theoretical proportion from the detected proportion of the component in the preliminary mixed sample.

[0119] Based on the bias correction factor for each component and its content in each layer area Calculate the adjusted mixing ratio of each layer .

[0120] As an example of the above implementation, the theoretical proportions of components 1, 2, and 3 and the detected proportions in the preliminary mixed sample are shown in Table 4.

[0121] Table 4: Comparative data of slag composition

[0122]

[0123] Calculate the bias correction factor for each component based on the data in the table , , , and the adjusted mixing ratio of each layer is calculated as , , .

[0124] Re-prepare the mixed sample according to the adjusted mixing ratio of each layer and conduct component detection. If the test result still deviates from the theoretical value, repeat the above steps to further optimize the mixing ratio until the composition of the mixed sample meets the theoretical value.

[0125] The present invention prepares mixed samples by using different proportions of the remaining slag samples in each layer when evaluating the uneven distribution of slag components. The core reason is that when the slag component distribution is uneven, certain specific layers may contain more key information. By reasonably adjusting the mixing ratio, the layers with significant composition differences can be effectively highlighted, so as to more accurately capture the characteristics of these key areas. This method can avoid the dilution of important information caused by selecting the same proportion, which is conducive to improving the representativeness of the mixed sample for the overall slag characteristics.

[0126] Furthermore, under the condition of uneven distribution of slag composition, based on the deviation between the composition detection results of the preliminary mixed sample and the theoretical data, and combined with the importance of each layer of area, the mixing ratio of the remaining slag samples in each layer is dynamically adjusted. The mixed sample thus obtained can more accurately and comprehensively reflect the overall composition distribution characteristics of the slag and its spatial heterogeneity, thereby significantly improving the quality of the mixed sample and the reliability of the analysis results.

[0127] It should be emphasized that in the present invention, whether it is the component detection of stratified sampling samples or the component detection of mixed samples, it is assumed that the detection equipment has a high degree of accuracy and is operated under an ideal detection environment. Therefore, the detection results are not affected by fluctuations in the performance of the detection equipment, changes in the detection environment or other external factors, ensuring that the obtained data fully reflects the true component characteristics of the sample.

[0128] Example 2

[0129] See also Figure 3 As shown, the present invention proposes a method for detecting and analyzing the composition of high-carbon ferrochrome production slag, comprising the following steps: S1: arranging multiple temperature measuring points on the layer area divided by the flow path of the slag discharge outlet to collect slag temperature data and evaluate the uniformity of temperature distribution.

[0130] S2: When the temperature distribution is evaluated to be uniform, single-point sampling is started and S3 is executed; otherwise, stratified sampling is started and S4-S7 are executed.

[0131] S3: Conduct composition testing on the slag samples sampled at a single point.

[0132] S4: Take part of the stratified sampling slag sample as the test sample.

[0133] S5: Conduct component tests on the test samples of each layer to obtain the content data of each component, and evaluate the uniformity of slag composition distribution based on this.

[0134] S6: Determine the preliminary mixing ratio of the remaining slag samples in each layer according to the uniformity of the slag composition distribution, extract samples in proportion, and perform homogenization treatment to obtain preliminary mixed samples.

[0135] S7: Perform component detection on the preliminary mixed sample, and dynamically adjust the preliminary mixing ratio based on the deviation of the component detection to complete the component detection of the mixed sample.

[0136] The temperature measuring equipment of the present invention adopts a high-precision thermocouple with a millisecond response speed (<10ms), which can capture temperature distribution data in real time during the slag flow process. At the same time, the flow velocity of the slag is usually low (for example, the flow velocity range is about 0.1-1.0m / s), and the slag displacement is extremely small under the millisecond detection time (for example, when the flow velocity is 1m / s, the displacement within 10ms is only 1cm). Therefore, the temperature data and the sampling position can still maintain a high degree of correspondence, and the influence of hysteresis on the representativeness of the sampling can be ignored. In addition, the present invention adopts a multi-sampling point coverage strategy in the layer area with uneven temperature distribution, and performs independent component detection on the samples of different sampling points of each layer, and then takes the average value to obtain the component content data of each layer. This method effectively offsets the local deviation that may exist in single-point sampling through spatial redundant sampling. Even if individual sampling points have a slight offset due to flow displacement, the overall accuracy of the hierarchical regional component data can be ensured through the equalization of multiple data points.

[0137] Example 3

[0138] like Figure 4As shown, an embodiment of the present invention provides the following technical solution: a computer includes a memory 102, a processor 101, and a computer program stored in the memory 102 and executable on the processor 101, wherein the processor 101 implements the above-mentioned high-carbon ferrochrome production slag composition detection and analysis system when executing the computer program.

[0139] Specifically, the processor 101 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0140] Among them, the memory 102 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 102 may include a hard disk drive (HDD), a floppy disk drive, a solid state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 102 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 102 may be inside or outside the data processing device. In a specific embodiment, the memory 102 is a non-volatile memory. In a specific embodiment, the memory 102 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically alterable ROM (EAROM) or a flash memory (FLASH), or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0141] The memory 102 may be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 101 .

[0142] The processor 101 implements the above-mentioned high-carbon ferrochrome production slag composition detection and analysis system by reading and executing the computer program instructions stored in the memory 102.

[0143] In some embodiments, the computer may further include a communication interface 103 and a bus 100. Figure 4 As shown, the processor 101, the memory 102, and the communication interface 103 are connected via a bus 100 and communicate with each other.

[0144] The communication interface 103 is used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0145] The bus 100 includes hardware, software or both, and couples the components of the computer to each other. The bus 100 includes but is not limited to at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 100 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, bus 100 may include one or more buses. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.

[0146] Example 4

[0147] In combination with the above-mentioned high-carbon ferrochrome production slag composition detection and analysis system, an embodiment of the present invention provides the following technical solution: a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned high-carbon ferrochrome production slag composition detection and analysis system is implemented.

[0148] Those skilled in the art will appreciate that the logic and / or steps described in the flowchart as data or in other ways herein, for example, can be considered as a sequenced data table of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses.

[0149] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0150] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0151] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A high carbon ferrochrome production slag composition detection and analysis system, characterized in that: Includes the following modules: Temperature distribution acquisition module: multiple temperature measurement points are arranged on the layer area divided by the flow path of the slag discharge outlet to collect slag temperature data and evaluate the uniformity of temperature distribution; Slag sampling module: when the temperature distribution is uniform, single-point sampling is started and the composition test is carried out directly; otherwise, stratified sampling is started; Sampling stratification processing module: taking part of the stratified sampling slag sample as the test sample; Layered component detection module: perform component detection on each layer of test samples, obtain the content data of each component, and evaluate the uniformity of slag component distribution based on this; Preliminary mixing ratio determination module: determines the preliminary mixing ratio of each layer of residual slag samples according to the uniformity of slag component distribution, and extracts samples according to the ratio and then performs homogenization treatment to obtain preliminary mixed samples; Mixing ratio dynamic adjustment module: performs component detection on the preliminary mixed sample and dynamically adjusts the preliminary mixing ratio based on the deviation of the component detection to complete the mixed sample component detection.

2. A high carbon ferrochrome production slag composition detection and analysis system as claimed in claim 1, characterized in that: The process of arranging a plurality of temperature measuring points on the layer area divided by the flow path of the slag discharge port is as follows: The flow path is divided into a surface area, a middle area, and a bottom area according to the geometric shape of the slag discharge path; Collect the flow rate and flow velocity of slag during discharge and use the empirical formula to estimate the total number of temperature measurement points ,in Indicates the total number of temperature measurement points. Indicates the slag capacity, represents the slag flow path length, represents the slag flow velocity, Indicates the correction factor, which is determined according to the actual equipment and process conditions; According to the estimated total number of temperature measuring points, the temperature measuring points are arranged at equal intervals in the divided surface area, middle area and bottom area.

3. A high carbon ferrochrome production slag composition detection and analysis system as claimed in claim 1, characterized in that: The process of evaluating the uniformity of temperature distribution is as follows: The average temperature and the temperature standard deviation of the slag temperature at each temperature measuring point in each layer area on the flow path of the slag discharge outlet are calculated; Define the temperature distribution uniformity formula ,in represents the temperature distribution uniformity index, represents the temperature standard deviation, represents the average temperature; Substitute the average temperature and temperature standard deviation calculated for each layer into the temperature distribution uniformity formula to obtain the temperature distribution uniformity index for each region; The temperature data of all temperature measuring points in all layer areas are combined to calculate the overall average temperature and temperature standard deviation and then introduced into the temperature distribution uniformity formula to obtain the overall temperature distribution uniformity index; The temperature distribution uniformity index of each layer area and the total temperature distribution uniformity index are compared with the set threshold value. If both reach the set threshold value, it is evaluated that the slag temperature distribution on the flow path of the slag discharge outlet is uniform; otherwise, it is evaluated that the temperature distribution is uneven.

4. A high carbon ferrochrome production slag composition detection and analysis system as claimed in claim 3, characterized in that: The single point sampling is implemented as follows: The deviation between the slag temperature at each temperature measuring point in all layer areas and the overall average temperature is calculated, and then the temperature measuring point with the minimum deviation is taken as the single-point sampling position.

5. A high carbon ferrochrome production slag composition detection and analysis system as claimed in claim 3, characterized in that: The stratified sampling is implemented as follows: Compare the temperature distribution uniformity index of each layer area with the set threshold; For the layer area where the temperature distribution uniformity index reaches the set threshold, the deviation between the slag temperature of each temperature measuring point in the area and the average temperature of the area is calculated, and the temperature measuring point with the smallest deviation is selected as the sampling position of the area; For the layer area where the temperature distribution uniformity index does not reach the set threshold, the temperature measuring points corresponding to the highest and lowest temperatures in the area are selected as the sampling positions of the area, and the temperature gradients of adjacent temperature measuring points are calculated for the temperature measuring points arranged in sequence according to the positions in the area; The temperature gradient of two adjacent temperature measuring points is compared with the configured critical value. If the temperature gradient of two adjacent temperature measuring points is greater than the critical value, an auxiliary sampling point is added in the middle of the two adjacent temperature measuring points.

6. A high carbon ferrochrome production slag composition detection and analysis system as claimed in claim 1, characterized in that: The slag sampling module also includes a sampling device consisting of a sampling terminal, a data interface, a positioning unit, and a control unit; The sampling terminal is the part that is in direct contact with the slag and is responsible for executing the sampling instructions issued by the control unit; The data interface receives the temperature data of the temperature measurement point in real time and feeds back the sampling result to the control unit; The positioning unit is used to locate the specific position of the sampling terminal on the slag flow path; The control unit generates a sampling instruction according to the temperature distribution data and other input information.

7. A high carbon ferrochrome production slag composition detection and analysis system as claimed in claim 1, characterized in that: The evaluation of the uniformity of slag composition distribution is specifically implemented as follows: The component data of the test samples in each layer are used to calculate the average content and standard deviation of the same component in all layer areas; The coefficient of variation of the content distribution of each component is calculated using the average content and standard deviation of each component in all layer areas; The content distribution variation coefficients of various components are compared with the preset allowable thresholds. If the content distribution variation coefficients of all components meet the allowable thresholds, the slag composition is evaluated to be uniformly distributed; otherwise, the slag composition is evaluated to be unevenly distributed.

8. A high carbon ferrochrome production slag composition detection and analysis system as claimed in claim 1, characterized in that: The preliminary mixing ratio of each layer of residual slag samples is determined according to the uniformity of slag composition distribution, as shown in the following process: When evaluating the uniform distribution of slag composition, it is determined that the mixing ratio of the remaining slag samples in each layer is equal; When evaluating the uneven distribution of slag components, the content of each component in each layer area is combined with the volume of each layer area to calculate the theoretical proportion of each component in the overall slag. , where Indicates The ingredient in The content of the layer area, Indicates the slag composition number, , represents the number of layers, , Indicates The volume of the layer area; Using the formula Determine the preliminary mixing ratio of each layer of residual slag samples .

9. A high carbon ferrochrome production slag composition detection and analysis system as claimed in claim 8, characterized in that: The initial mixing ratio is adjusted dynamically based on the deviation of component detection, as shown in the following process: Conduct component testing on the preliminary mixed sample, and conduct deviation analysis between the test results and the theoretical proportion of each component in the whole slag. If there is a deviation in the analysis, adjust the preliminary mixing ratio of each layer based on the component deviation; Re-prepare the mixed sample according to the adjusted mixing ratio of each layer and conduct component testing. If the test result still deviates from the theoretical value, repeat the above steps to further optimize the mixing ratio until the composition of the mixed sample meets the theoretical value.

10. A method for detecting and analyzing the composition of high carbon ferrochrome production slag, characterized in that: The steps include: S1: Multiple temperature measuring points are arranged on the layer area divided by the flow path of the slag discharge outlet to collect slag temperature data and evaluate the uniformity of temperature distribution; S2: When the temperature distribution is uniform, start single-point sampling and execute S3; otherwise, start stratified sampling and execute S4-S7; S3: Conduct composition test on the slag sample taken at a single point; S4: taking part of the stratified sampling slag sample as a test sample; S5: Conduct component testing on each layer of test samples to obtain the content data of each component, and evaluate the uniformity of slag component distribution based on this; S6: determining the preliminary mixing ratio of the remaining slag samples in each layer according to the uniformity of the slag composition distribution, and extracting samples according to the ratio and performing homogenization treatment to obtain preliminary mixed samples; S7: Perform component detection on the preliminary mixed sample, and dynamically adjust the preliminary mixing ratio based on the deviation of the component detection to complete the component detection of the mixed sample.

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