A method and system for controlling the purity of high-carbon ferrochrome

Abstract

The present application relates to the technical field of high-carbon ferrochrome preparation, and discloses a preparation method and system for controlling the purity of high-carbon ferrochrome, which comprises the following steps: obtaining a preparation batch of high-carbon ferrochrome to be controlled for purity and corresponding raw material categories and preparation equipment, querying operation and maintenance technical requirements of the raw material categories and the preparation equipment to determine purity influencing elements of the preparation batch; analyzing a reaction operation state of a production process to calculate purity fluctuation entropy corresponding to the purity influencing elements and analyze purity deviation of the preparation batch; analyzing reaction activity characteristics of the raw material categories to calculate a purity guarantee rate of the preparation batch; analyzing purity interference factors during production of the preparation equipment to determine a purity contribution rate of the production process of the preparation equipment; and performing purity control processing of the raw material categories in the preparation equipment to obtain a purity control result. The present application can improve the preparation efficiency of high-carbon ferrochrome purity.

Description

Technical Field

[0001] This invention relates to a method and system for controlling the purity of high-carbon ferrochrome, belonging to the field of high-carbon ferrochrome preparation technology. Background Technology

[0002] As a core raw material for stainless steel production, the purity of high-carbon ferrochrome directly determines the mechanical properties and corrosion resistance of downstream stainless steel products. It is a key prerequisite for the metallurgical industry to achieve high-quality production. With the continuous growth of global stainless steel market demand for high-end products, the purity control requirements for high-carbon ferrochrome are becoming increasingly stringent. However, the current purity control methods in the industry still have significant limitations and are difficult to meet production needs.

[0003] Currently, the purity control of high-carbon ferrochrome relies heavily on traditional experience-based operations and post-production testing. Operators typically adjust raw material ratios based on past production experience, and purity testing is usually conducted after each batch is completed, using chemical analysis for sampling verification. However, this method lacks systematic consideration and fails to take into account key factors such as the reactivity of the raw materials and the operating status of the preparation equipment. It often causes batch purity fluctuations due to problems such as "poor raw material compatibility leading to incomplete reaction" and "abnormal equipment components introducing non-metallic impurities." Furthermore, it lacks real-time capability, as post-production testing cannot capture the causes of purity fluctuations in real time during production. Once the purity is found to be substandard, the entire batch of raw materials must be reworked, which not only wastes raw materials and energy but also disrupts the continuity of subsequent stainless steel production. In addition, the traditional method does not establish a correlation control logic between "raw materials-equipment-reaction process," making it difficult to quantify the degree of influence of each factor on purity, resulting in low efficiency in the preparation of high-carbon ferrochrome. Summary of the Invention

[0004] This invention provides a method and system for controlling the purity of high-carbon ferrochrome, the main purpose of which is to improve the preparation efficiency of high-carbon ferrochrome.

[0005] To achieve the above objectives, the present invention provides a method for controlling the purity of high-carbon ferrochrome, comprising:

[0006] Obtain the batches of high-carbon ferrochrome to be purified, along with the corresponding raw material categories and preparation equipment. Query the operation and maintenance technical requirements of the raw material categories and preparation equipment to determine the factors affecting the purity of the batches.

[0007] The reaction operation status of the production process is analyzed to calculate the purity fluctuation entropy corresponding to the purity influencing factors. Based on the purity fluctuation entropy, the purity deviation of the preparation batch is analyzed.

[0008] The reactivity characteristics of the raw materials are analyzed, a set of reaction coupling parameters for the production process is constructed, and the purity assurance rate of the preparation batch is calculated by combining the reactivity characteristics with the set of reaction coupling parameters.

[0009] Analyze the purity interference factor during the production process of the preparation equipment to determine the purity contribution rate of the production process of the preparation equipment;

[0010] Based on the purity deviation, the purity assurance rate, and the purity contribution rate, the purity control process of the raw material category in the preparation equipment is performed to obtain the purity control result.

[0011] Optionally, the step of querying the operation and maintenance technical requirements of the raw material category and the preparation equipment to determine the factors affecting the purity of the preparation batch includes:

[0012] Collect production process information of the raw material categories and preparation equipment, and calculate the production variation rate corresponding to the production process information;

[0013] Based on the production variation rate, key production information is extracted from the production process information;

[0014] Query the process operation standards corresponding to the raw material categories and preparation equipment, and calculate the standard conformity between the key production information and the process operation standards;

[0015] Based on the standard conformity and the key production information, the factors affecting the purity of the preparation batch are determined.

[0016] Optionally, calculating the standard conformity between the key production information and the process operation standard includes:

[0017] Extract the core descriptive content from the key production information and the process operation standards to obtain the core content of the production information and the core content of the process standards.

[0018] The content semantics corresponding to the core content of the production information and the core content of the process standard are analyzed to obtain the first core semantics and the second core semantics.

[0019] The first core semantic and the second core semantic are digitally vectorized to obtain the first core vector and the second core vector.

[0020] By combining the first core vector and the second core vector, the standard conformity between the key production information and the process operation standard is calculated.

[0021] Optionally, the analysis of the reaction operation status of the production process includes:

[0022] Collect operational data corresponding to the reaction stages during the production process to obtain initial reaction data;

[0023] The initial reaction data is effectively filtered to obtain valid reaction data;

[0024] Key features of the core state of the reaction are extracted from the effective reaction data to obtain key reaction features;

[0025] Trend analysis was performed on the key characteristics of the reaction to obtain the characteristic change trends;

[0026] Based on the aforementioned characteristic change trends, the reaction and operation status of the production process is analyzed.

[0027] Optionally, the step of analyzing the reaction operation status of the production process to calculate the purity fluctuation entropy corresponding to the purity influencing factors includes:

[0028] Based on the purity-influencing factors, the reaction operation status is screened to obtain the associated operation status;

[0029] Collect production status data corresponding to the associated operating status, including status parameter data and production raw material data;

[0030] Based on the state parameter data, calculate the state stability corresponding to the associated operating state;

[0031] Based on the production raw material data, determine whether there are any abnormalities in the raw material composition of the production system;

[0032] If there are no abnormalities in the raw material composition, then based on the state stability, calculate the purity fluctuation entropy corresponding to the purity influencing factor.

[0033] If there are abnormalities in the raw material composition, the abnormal composition characteristics of the raw material composition are extracted from the production raw material data.

[0034] Based on the aforementioned abnormal component characteristics, the component influence degree corresponding to the raw material component is calculated;

[0035] By combining the influence of the components and the stability of the state, the purity fluctuation entropy corresponding to the purity influencing factor is calculated.

[0036] Optionally, calculating the component influence degree corresponding to the raw material component based on the component anomaly characteristics includes:

[0037] Extract the records of elements exceeding limits, the periodicity of component fluctuations, and the locations of abnormal components from the abnormal component features;

[0038] Based on the records of element exceedances, the abnormality level of the raw material components is assessed.

[0039] Based on the component fluctuation cycle, determine the abnormal duration of the raw material component.

[0040] Based on the location of the abnormal component, the process isolation degree between the abnormal component and the core reaction area is calculated;

[0041] By combining the process isolation degree, the duration of the abnormality, and the level of the component abnormality, the component influence degree corresponding to the raw material component is calculated.

[0042] Optionally, the analysis of the reactivity characteristics of the raw material category includes:

[0043] Obtain the material composition information of the raw material category, perform phase structure analysis on the material composition information, and obtain the crystal configuration characteristics of the raw material;

[0044] Based on the crystal structure characteristics, the enthalpy change curves of the raw materials of the aforementioned raw material category during the heating process are constructed;

[0045] Based on the enthalpy change curve, the phase transition behavior of the raw materials of the raw material category in different temperature ranges is identified;

[0046] Extract the activation energy threshold corresponding to the phase transition behavior, and analyze the reactivity characteristics of the raw material category based on the activation energy threshold.

[0047] Optionally, constructing the enthalpy change curve of the raw material category during the heating process based on the crystal structure characteristics includes:

[0048] The structural integrity of the crystal form configuration features is verified to obtain the effective crystal form features;

[0049] Extract the crystal structure parameters of the effective crystal form characteristics, perform thermodynamic correlation processing on the crystal structure parameters, and obtain the standard thermodynamic characteristics;

[0050] Thermal response features are extracted from the standard thermodynamic features to obtain the dominant thermal response features;

[0051] The dominant thermal response characteristics are divided into phase transition stages to obtain segmented thermal response characteristics;

[0052] The enthalpy change characteristics are fitted to the segmented thermal response characteristics to obtain the enthalpy change characteristics;

[0053] Based on the aforementioned enthalpy change characteristics, enthalpy change curves of the raw materials of the aforementioned raw material category during the heating process are constructed.

[0054] Optionally, the construction of the reaction coupling parameter set for the production process includes:

[0055] Images of the reaction zone inside the furnace during the production process are acquired, and image enhancement processing is performed on the images of the reaction zone inside the furnace to obtain clear reaction images;

[0056] Thermal response features are extracted from the clear reaction image to obtain a thermal response feature map;

[0057] Identify the temperature distribution region in the thermal response feature map, and calculate the temperature gradient change rate of the production process based on the temperature distribution region;

[0058] Extract the material distribution information corresponding to the thermal response feature map, and calculate the material mixing uniformity of the production process based on the material distribution information;

[0059] Based on the temperature gradient change rate and the material mixing uniformity, a set of reaction coupling parameters for the production process is generated.

[0060] To address the aforementioned problems, the present invention also provides a preparation system for controlling the purity of high-carbon ferrochrome, the system comprising:

[0061] The purity factor determination module is used to obtain the high-carbon ferrochrome preparation batch to be purified and the corresponding raw material categories and preparation equipment, query the operation and maintenance technical requirements of the raw material categories and preparation equipment, and determine the purity influencing factors of the preparation batch.

[0062] The purity deviation analysis module is used to analyze the reaction operation status of the production process to calculate the purity fluctuation entropy corresponding to the purity influencing factors, and to analyze the purity deviation of the preparation batch based on the purity fluctuation entropy.

[0063] The purity assurance rate calculation module is used to analyze the reactivity characteristics of the raw material category, construct a set of reaction coupling parameters for the production process, and calculate the purity assurance rate of the preparation batch by combining the reactivity characteristics with the set of reaction coupling parameters.

[0064] The purity contribution rate determination module is used to analyze the purity interference factors during the production of the preparation equipment in order to determine the purity contribution rate of the production process of the preparation equipment.

[0065] The purity control execution module is used to perform purity control processing on the raw material category in the preparation equipment based on the purity deviation, the purity assurance rate, and the purity contribution rate, to obtain the purity control result.

[0066] Compared to the problems described in the background art, this invention, by querying the operational and maintenance technical requirements of the raw material categories and preparation equipment, determines the factors affecting the purity of the preparation batch. This allows for understanding the intrinsic relationship between the raw material categories, the operation of the preparation equipment, and the purity of high-carbon ferrochrome, providing a basis for assessing purity control. Furthermore, by analyzing the reaction operation status of the production process, this invention can understand the actual operation of key reaction stages in high-carbon ferrochrome preparation, capturing potential changes that may cause purity fluctuations. This provides real-time and reliable status data for subsequent calculations of purity fluctuation entropy. Moreover, by analyzing the reactivity characteristics of the raw material categories, this invention can accurately identify the differences in reaction efficiency and compatibility conditions of different raw materials during high-temperature preparation, avoiding issues caused by raw material reactivity. The problem of insufficient or excessive reaction caused by sex mismatch provides a core basis for constructing the reaction coupling parameter set of subsequent production processes. This invention analyzes the purity interference factors during the production of the preparation equipment and determines the purity contribution rate of the preparation equipment process. This allows for the identification of key factors and their proportion of influence at the equipment level that cause purity fluctuations, avoiding the one-sidedness of analyzing purity issues solely from the perspective of raw materials or processes. This provides a strong basis for targeted operation and maintenance and purity control of the preparation equipment. Finally, this invention performs purity control processing on the raw material categories in the preparation equipment based on the purity deviation, purity assurance rate, and purity contribution rate, obtaining purity control results, thereby improving the accuracy of purity control and ultimately improving preparation efficiency. Therefore, the preparation method and system for controlling the purity of high-carbon ferrochrome provided by this invention can improve the preparation efficiency of high-carbon ferrochrome purity. Attached Figure Description

[0067] Figure 1 This is a schematic flowchart illustrating a method for controlling the purity of high-carbon ferrochrome according to an embodiment of the present invention.

[0068] Figure 2 This is a flowchart of the purity control process in a method for preparing high-carbon ferrochrome provided by the present invention.

[0069] Figure 3 This is a schematic diagram of a module for implementing a preparation system for controlling the purity of high-carbon ferrochrome, provided in an embodiment of the present invention.

[0070] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0071] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0072] This application provides a method for controlling the purity of high-carbon ferrochrome. The execution subject of this method includes, but is not limited to, at least one electronic device configured to execute the method provided in this application, such as a server or a terminal. In other words, the method for controlling the purity of high-carbon ferrochrome can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0073] Reference Figure 1 The diagram shown is a flowchart illustrating a method for controlling the purity of high-carbon ferrochrome according to an embodiment of the present invention. In this embodiment, the method for controlling the purity of high-carbon ferrochrome includes:

[0074] S1. Obtain the batch of high-carbon ferrochrome to be prepared and the corresponding raw material categories and preparation equipment, and query the operation and maintenance technical requirements of the raw material categories and preparation equipment to determine the factors affecting the purity of the batch.

[0075] This invention determines the factors affecting the purity of the prepared batch by querying the operation and maintenance technical requirements of the raw material types and preparation equipment. It can grasp the intrinsic relationship between the raw material types, the operation of the preparation equipment and the purity of high carbon ferrochrome, and provide a basis for evaluating the purity control status.

[0076] It should be explained that the high-carbon ferrochrome production batches requiring purity control refer to production batches where purity control is difficult due to fluctuations in raw material composition, changes in equipment status, adjustments to process conditions, etc.; the raw material categories include, but are not limited to, chromite, coke, silica, etc.; the production equipment includes, but is not limited to, electric furnaces, refining furnaces, casting equipment, etc.; the operation and maintenance technical requirements refer to the operating and maintenance specifications and requirements formulated to ensure the normal use of raw materials and equipment; the purity influencing factors are various key indicators used to measure the purity control level of the production batch; furthermore, the operation and maintenance technical requirements for the raw material categories and production equipment can be found by consulting the metallurgical industry smelting job training manual, raw material technical standards, and equipment manufacturer operation and maintenance documents.

[0077] In detail, the process of querying the operation and maintenance technical requirements of the raw material categories and preparation equipment to determine the factors affecting the purity of the preparation batch includes:

[0078] Collect production process information of the raw material categories and preparation equipment, and calculate the production variation rate corresponding to the production process information;

[0079] Based on the production variation rate, key production information is extracted from the production process information;

[0080] Query the process operation standards corresponding to the raw material categories and preparation equipment, and calculate the standard conformity between the key production information and the process operation standards;

[0081] Based on the standard conformity and the key production information, the factors affecting the purity of the preparation batch are determined.

[0082] Among them, the production process information includes multi-dimensional production status and operating status information such as the raw material categories and feeding records of the preparation equipment, composition data, running time, temperature records, maintenance logs, and fault history; the production variation rate is a quantitative indicator used to measure the stability or variability of the production process information; the key production information is information from the production process information that has a significant impact on the purity of high-carbon ferrochrome and contains more key content; the process operation standards are operation and maintenance requirements formulated by metallurgical experts for different types of raw materials and equipment, with reference to advanced industry standards and combined with actual production; and the standard conformity indicates the level of consistency between the key production information and the various characteristics in the process operation standards.

[0083] Furthermore, production process information of the raw material categories and preparation equipment can be collected through a production data acquisition system compiled by a scripting language. The production variation rate corresponding to the production process information can be calculated using a standard deviation algorithm. The production variation rate is compared with a preset threshold. When the production variation rate is greater than the preset threshold, key production information in the production process information is extracted. The process operation standards corresponding to the raw material categories and preparation equipment can be queried through an enterprise standard document library, such as a high-carbon ferrochrome production process standard document library. Based on the standard conformity and the key production information, by cross-comparing key production information with high standard conformity with process operation standards, combined with expert experience, targeted analysis is performed on unique or abnormal data in the key production information, and successful control cases of similar production batches in the past are referenced to finally determine the purity influencing factors of the preparation batch.

[0084] Furthermore, as an optional embodiment of the present invention, calculating the standard conformity between the key production information and the process operation standard includes:

[0085] Extract the core descriptive content from the key production information and the process operation standards to obtain the core content of the production information and the core content of the process standards.

[0086] The content semantics corresponding to the core content of the production information and the core content of the process standard are analyzed to obtain the first core semantics and the second core semantics.

[0087] The first core semantic and the second core semantic are digitally vectorized to obtain the first core vector and the second core vector.

[0088] By combining the first core vector and the second core vector, the standard conformity between the key production information and the process operation standard is calculated.

[0089] The core content of the production information and the core content of the process standard are respectively sets of textual descriptions in the key production information and the process operation standards used to reflect the key production status and core process requirements. These contents are core descriptions that have a direct impact on purity extracted from the key production information and process operation standards. The first core semantics and the second core semantics are semantic interpretations corresponding to the core content of the production information and the core content of the process standard, that is, interpretations of the production significance and process intent carried by these core descriptions. The first core vector and the second core vector are digital vector forms corresponding to the first core semantics and the second core semantics. By mathematically transforming the semantics into vectors, the core semantics become computable, thereby providing a data foundation for the subsequent calculation of standard conformity.

[0090] Furthermore, the core descriptive content in the key production information and the process operation standards can be extracted using the TF-IDF algorithm to obtain the core content of the production information and the core content of the process standards; the core content of the production information and the core content of the process standards can be processed by natural language understanding technology to obtain the first core semantics and the second core semantics; the first core semantics and the second core semantics can be converted into digital vectors using the Doc2Vec model to obtain the first core vector and the second core vector.

[0091] Furthermore, as another embodiment of the present invention, the standard conformity between the key production information and the process operation standard is calculated by combining the first core vector and the second core vector:

[0092]

[0093] in, This represents the m-th vector in the first core vector. This represents the nth vector in the second core vector. and Let these represent the magnitudes of the m-th vector in the first core vector and the n-th vector in the second core vector, respectively. This indicates selecting the larger value between the m-th vector in the first core vector and the n-th vector in the second core vector, where m and n represent the sequence numbers corresponding to the first and second core vectors, respectively, and x and y represent the quantities corresponding to the first and second core vectors, respectively.

[0094] S2. Analyze the reaction operation status of the production process to calculate the purity fluctuation entropy corresponding to the purity influencing factors, and analyze the purity deviation of the preparation batch based on the purity fluctuation entropy.

[0095] This invention analyzes the reaction operation status of the production process to understand the actual operation of key reaction links in the preparation of high-carbon ferrochrome, and can capture potential changes that may cause purity fluctuations, providing real-time and reliable state basis for subsequent calculation of purity fluctuation entropy.

[0096] It should be explained that the reaction operation status refers to the real-time operation of core links such as smelting reaction and raw material reaction in the high carbon ferrochrome production process, covering key status information such as temperature in the smelting furnace, pressure in the reaction zone, uniformity of raw material mixing, and reaction duration.

[0097] In detail, the analysis of the reaction operation status of the production process includes:

[0098] Collect operational data corresponding to the reaction stages during the production process to obtain initial reaction data;

[0099] The initial reaction data is effectively filtered to obtain valid reaction data;

[0100] Key features of the core state of the reaction are extracted from the effective reaction data to obtain key reaction features;

[0101] Trend analysis was performed on the key characteristics of the reaction to obtain the characteristic change trends;

[0102] Based on the aforementioned characteristic change trends, the reaction and operation status of the production process is analyzed.

[0103] It should be explained that the initial reaction data is the raw data of the production reaction process collected by sensors, covering the operating parameters of the reaction equipment, the parameters of the reaction medium, and the parameters of the raw material supply. It may include invalid values ​​caused by sensor noise and transient interference. The effective reaction data is the usable data that matches the normal reaction process after removing abnormal jump values, data during equipment failure periods, and data with missing signals from the initial reaction data, ensuring the authenticity and relevance of the data. The key reaction characteristics are indicators extracted from the effective reaction data that directly reflect the core state of the reaction, such as the stable range of furnace temperature, the peak value of CO reducing gas concentration, and the fluctuation range of electrode current. These characteristics are directly related to reaction efficiency and product quality. The trend of characteristic change is the dynamic change law of key reaction characteristics with production time, such as the trend of furnace temperature rising-holding-falling with the reaction stage, and the trend of reducing gas concentration rising-stabilizing-falling, which can reflect the rationality of the reaction process.

[0104] Furthermore, initial reaction data can be collected using a distributed industrial sensor array. High-precision sensors are deployed at key locations in the reaction equipment to collect data in real time, ensuring coverage of the entire reaction process. The initial reaction data is processed using a "3σ criterion + process threshold dual screening method": first, outliers exceeding ±3 times the standard deviation of the data mean are removed using the 3σ criterion; then, invalid data is eliminated by combining this with production process thresholds, resulting in valid reaction data. Key reaction features are extracted using "time-series feature extraction + domain feature mapping": first, the valid reaction data is segmented into time sequences, and the mean furnace temperature, CO concentration fluctuation variance, and electrode current stability value within each segment are calculated; then, combined with the requirements of the high-carbon ferrochrome reduction process, these time-series features are mapped to "reaction activity characteristics" and "equipment stability characteristics," yielding the reaction... Key characteristics; trend analysis is performed on key reaction characteristics using "sliding window fitting + trend slope analysis": a 20-minute sliding window is used to perform linear fitting on key characteristics and calculate the trend slope. For example, if the furnace temperature trend slope is 0.5℃ / h during the reduction stage, it indicates that the reaction activity is slowly increasing, which meets the process requirements. When analyzing the reaction operation status based on the characteristic change trend, the process stage requirements are first compared to determine whether the characteristic trends match: if the furnace temperature trend slope increases and the CO concentration trend is stable, the reaction operation is determined to be stable; if the furnace temperature trend slope decreases and the CO concentration decreases simultaneously, the equipment log is checked to see if there is a cooling system failure, and the reaction operation is determined to be abnormal; at the same time, multiple characteristic trends are correlated to locate the cause of the abnormality and finally clarify the specific type of reaction operation status and the optimization direction.

[0105] This invention analyzes the reaction operation status of the production process to calculate the purity fluctuation entropy corresponding to the purity influencing factors. This allows for a quantitative assessment of the degree of disturbance of the purity influencing factors on the purity of the final product, providing a key indicator for accurately analyzing the purity deviation of the preparation batch. It should be explained that the purity fluctuation entropy is a quantitative indicator used to represent the degree to which each purity influencing factor causes random fluctuations in product purity. The larger the value, the higher the purity uncertainty caused by that factor.

[0106] In detail, the analysis of the reaction operation status of the production process to calculate the purity fluctuation entropy corresponding to the purity influencing factors includes:

[0107] Based on the purity-influencing factors, the reaction operation status is screened to obtain the associated operation status;

[0108] Collect production status data corresponding to the associated operating status, including status parameter data and production raw material data;

[0109] Based on the state parameter data, calculate the state stability corresponding to the associated operating state;

[0110] Based on the production raw material data, determine whether there are any abnormalities in the raw material composition of the production system;

[0111] If there are no abnormalities in the raw material composition, then based on the state stability, calculate the purity fluctuation entropy corresponding to the purity influencing factor.

[0112] If there are abnormalities in the raw material composition, the abnormal composition characteristics of the raw material composition are extracted from the production raw material data.

[0113] Based on the aforementioned abnormal component characteristics, the component influence degree corresponding to the raw material component is calculated;

[0114] By combining the influence of the components and the stability of the state, the purity fluctuation entropy corresponding to the purity influencing factor is calculated.

[0115] It should be explained that the purity-influencing factors refer to key factors affecting the purity of high-carbon ferrochrome, such as reactor temperature, raw material sulfur and phosphorus content, and reducing gas concentration; the associated operating states are operating states directly related to the purity-influencing factors, selected from the reaction operating states; the state parameter data are the operating parameter data of the reaction equipment, and the production raw material data are the component content, feed rate, and other data of the raw materials; the state stability is an indicator of whether the parameters in the associated operating states are stable; the raw material component anomaly is when the content of harmful elements in the raw material exceeds the process standard; the component anomaly characteristics are the specific data of the raw material component anomaly; and the component influence degree is the degree of influence of the raw material anomaly on the purity.

[0116] Furthermore, the associated operating status can be filtered through the "Purity Influence Factors - Operating Status Mapping Table". For example, if the factor is "reducing gas concentration", then the operating status of the gas supply link can be filtered. When collecting production status data, thermocouples are used to measure furnace temperature, gas sensors are used to measure reducing gas concentration, and component analyzers are used to measure raw material composition. The stability of the status is calculated using the "parameter standard deviation method". For example, the smaller the standard deviation of the furnace temperature data, the higher the stability. When raw material composition is abnormal, it can be achieved by comparing it with the process standard threshold. The abnormal composition characteristics can be extracted by capturing the composition data during the abnormal period and recording the excess amount and duration.

[0117] Furthermore, as an optional embodiment of the present invention, calculating the component influence degree corresponding to the raw material component based on the component anomaly characteristics includes:

[0118] Extract the records of elements exceeding limits, the periodicity of component fluctuations, and the locations of abnormal components from the abnormal component features;

[0119] Based on the records of element exceedances, the abnormality level of the raw material components is assessed.

[0120] Based on the component fluctuation cycle, determine the abnormal duration of the raw material component.

[0121] Based on the location of the abnormal component, the process isolation degree between the abnormal component and the core reaction area is calculated;

[0122] By combining the process isolation degree, the duration of the abnormality, and the level of the component abnormality, the component influence degree corresponding to the raw material component is calculated.

[0123] It should be explained that the element exceeding the limit record is the specific data record in the component anomaly characteristics regarding the content of a specific element exceeding the process allowable range; the component fluctuation period is the time span experienced from the first detection of the component anomaly to its content falling back to the normal range in the component anomaly characteristics; the abnormal component location refers to the specific physical location or process link in the raw material storage or transportation process where the component anomaly is detected; the component anomaly level indicates the severity level classified according to the extent of the element exceeding the limit, the types of harmful elements involved, and their potential harm to the quality of the final product; the process isolation degree is a comprehensive measure that reflects the ability of the existing process layout and process design to dilute, neutralize, or physically isolate the abnormal component from the abnormal component location to the core reaction area; the anomaly persistence duration directly reflects the persistence of the abnormal component in the preparation system.

[0124] Furthermore, the abnormal component characteristics can be extracted using an extraction function compiled in Java. Based on the element exceeding limit records, referring to the permissible upper limit threshold of hazardous elements in the raw material process standard, the ratio of the actual exceeding value to the threshold is calculated, and combined with the toxicity weight of the hazardous elements involved, a graded scoring method is used to assess the abnormal component level of the raw material component. Based on the component fluctuation cycle, by locating the time node of the first detection of the abnormal component and the time node of the content stabilizing and falling back to the process permissible range, the time difference between the two is calculated, and the residence time correction value of the raw material in the transportation or storage stage is added to determine the abnormal existence duration of the raw material component. Combined with the abnormal component location, according to the process stage where the abnormal component location is located, and combined with the number and efficiency parameters of the isolation equipment from the core reaction area, the theoretical attenuation coefficient of the abnormal component concentration is calculated, thereby calculating the process isolation degree between the abnormal component and the core reaction area.

[0125] Furthermore, as another embodiment of the present invention, the component influence degree corresponding to the raw material component is calculated using the following formula, combining the process isolation degree, the duration of the abnormality, and the component abnormality level:

[0126]

[0127] Where I represents the component influence degree corresponding to the raw material component. Indicates the level of abnormality of the ingredients. G represents the duration of the abnormality, and G represents the process isolation degree.

[0128] This invention analyzes the purity deviation of a preparation batch based on the purity fluctuation entropy, enabling early prediction of the risk of inaccurate final product composition from the perspective of the inherent reaction process. It should be explained that the purity deviation is a predictive description of the degree and range to which the key chemical components of the final product of the preparation batch may deviate from the preset quality target, comprehensively reflecting the cumulative impact of abnormalities in each reaction step on component stability. Furthermore, analyzing the purity deviation of the preparation batch based on the purity fluctuation entropy establishes an intrinsic correlation between entropy value and component deviation, quantifying the disorder of the process into an estimate of the result deviation. The higher the entropy value, the more disordered the reaction process, the greater the possibility of the preparation batch having excessive or unqualified components, and the more significant the corresponding purity deviation.

[0129] S3. Analyze the reactivity characteristics of the raw materials, construct a set of reaction coupling parameters for the production process, and calculate the purity assurance rate of the preparation batch by combining the reactivity characteristics with the set of reaction coupling parameters.

[0130] This invention, by analyzing the reactivity characteristics of the raw material categories, can accurately identify the differences in reaction efficiency and compatibility conditions of different raw materials during high-temperature preparation, avoiding problems of insufficient or excessive reaction caused by mismatch of raw material reactivity, and providing a core basis for the construction of reaction coupling parameter sets in subsequent production processes.

[0131] It should be explained that the reactivity characteristics reflect the tendency and ability of raw materials to participate in chemical reactions during high-temperature smelting, including their redox properties, interfacial wetting behavior, and element migration rates.

[0132] In detail, the analysis of the reactivity characteristics of the raw material category includes:

[0133] Obtain the material composition information of the raw material category, perform phase structure analysis on the material composition information, and obtain the crystal configuration characteristics of the raw material;

[0134] Based on the crystal structure characteristics, the enthalpy change curves of the raw materials of the aforementioned raw material category during the heating process are constructed;

[0135] Based on the enthalpy change curve, the phase transition behavior of the raw materials of the raw material category in different temperature ranges is identified;

[0136] Extract the activation energy threshold corresponding to the phase transition behavior, and analyze the reactivity characteristics of the raw material category based on the activation energy threshold.

[0137] It should be explained that the material composition information is the content data of each chemical element in the raw material obtained by equipment such as X-ray fluorescence spectrometer; the crystal structure characteristics reflect the structural characteristics of the mineral phase in the raw material, such as the degree of crystallization, cell size and defect density; the enthalpy change curve records the continuous data of heat absorbed or released by the raw material under programmed temperature conditions; the phase transformation behavior describes the phase transformation process that occurs in the raw material under specific temperature conditions; and the activation energy threshold is the minimum energy boundary required to initiate a significant chemical reaction in the raw material.

[0138] Furthermore, the material composition information of the raw materials can be obtained through inductively coupled plasma atomic emission spectrometry (ICP-AES) or gas chromatography-mass spectrometry (GC-MS). X-ray diffraction (XRD) can be used to analyze the phase structure of the material composition information to obtain the crystal structure characteristics of the raw materials. Based on the crystal structure characteristics, differential scanning calorimetry (DSC) is used to construct the enthalpy change curve of the raw materials during the heating process. Based on the enthalpy change curve, the phase transition behavior of the raw materials in different temperature ranges is identified by analyzing the position and intensity changes of the endothermic / exothermic characteristic peaks in the curve. The activation energy threshold corresponding to the phase transition behavior can be extracted using the Kissinger method combined with multi-heating rate experimental data. Based on the activation energy threshold, the reactivity characteristics of the raw materials are analyzed by determining the reaction energy barrier.

[0139] Furthermore, as an optional embodiment of the present invention, constructing the enthalpy change curve of the raw material category during the heating process based on the crystal structure characteristics includes:

[0140] The structural integrity of the crystal form configuration features is verified to obtain the effective crystal form features;

[0141] Extract the crystal structure parameters of the effective crystal form characteristics, perform thermodynamic correlation processing on the crystal structure parameters, and obtain the standard thermodynamic characteristics;

[0142] Thermal response features are extracted from the standard thermodynamic features to obtain the dominant thermal response features;

[0143] The dominant thermal response characteristics are divided into phase transition stages to obtain segmented thermal response characteristics;

[0144] The enthalpy change characteristics are fitted to the segmented thermal response characteristics to obtain the enthalpy change characteristics;

[0145] Based on the aforementioned enthalpy change characteristics, enthalpy change curves of the raw materials of the aforementioned raw material category during the heating process are constructed.

[0146] It should be explained that the effective crystal form characteristics are crystal form characteristic data that have been verified and can be used for thermodynamic analysis; the crystal structure parameters are specific indicators describing the microstructure of the crystal, including lattice constants, bond lengths, bond angles, etc.; the standard thermodynamic characteristics are thermodynamic parameters with clear physical meaning after thermodynamic correlation processing; the dominant thermal response characteristics are thermal response characteristics that play a major role in the heating process; the segmented thermal response characteristics are thermal response data divided into different stages according to the phase transition process; and the enthalpy change characteristics are regular data of enthalpy change with temperature obtained through fitting.

[0147] Furthermore, the structural integrity of the crystal form configuration features can be verified by peak shape integrity analysis of X-ray diffraction patterns, eliminating crystal form data with obvious defects to obtain effective crystal form features; crystal structure parameters of the effective crystal form features, including interplanar spacing and unit cell volume, can be extracted using lattice analysis algorithms; thermodynamic correlation processing of the crystal structure parameters is performed using the thermodynamic equation of state to convert the structural parameters into thermodynamic quantities such as heat capacity and entropy, obtaining standard thermodynamic features; thermal response features of the standard thermodynamic features are extracted using differential scanning calorimetry data analysis methods to identify the effects of temperature rise. The main thermal effect characteristics during the heating process are identified to obtain the dominant thermal response characteristics. Based on the start and end points of the thermal effect peak, the dominant thermal response characteristics are divided into phase transition stages, dividing the heating process into a crystal stability region, a phase transition transition region, and a crystal transformation region, resulting in segmented thermal response characteristics. A polynomial fitting method is used to fit the enthalpy change of the segmented thermal response characteristics to establish enthalpy change equations for each temperature range, thus obtaining enthalpy change characteristics. Based on the enthalpy change characteristics, the enthalpy change equations for each temperature range are smoothly connected using a curve connection algorithm to construct a continuous enthalpy change curve for the raw material during the heating process.

[0148] This invention constructs a set of reaction coupling parameters for the production process, which can comprehensively characterize the synergistic state of the production process, avoiding the one-sided characterization of the reaction process caused by single parameter analysis. Furthermore, by combining the reactivity characteristics with the set of reaction coupling parameters, the purity assurance rate of the preparation batch can be calculated, which can quantify the degree of matching between the reactivity of the raw materials and the actual reaction coupling conditions, understand the probability that the preparation batch meets the target purity requirements, and provide data support for subsequent raw material ratio adjustment and equipment operation and maintenance optimization.

[0149] It should be explained that the reaction coupling parameter set is a set of quantitative indicators reflecting the synergistic relationship of multiple reaction parameters in the production process. It covers the operating parameters of the reaction equipment, the parameters of the reaction medium, and the parameters of the raw material supply. It also includes the coupling correlation data between the parameters, which can avoid the limitation that single parameter analysis cannot characterize the overall state of the reaction system. The purity assurance rate is a quantitative indicator of the probability that the batch meets the target purity requirements based on the degree of fit between the reactivity characteristics of the raw materials and the reaction coupling parameter set. The higher the value, the higher the probability of the batch meeting the purity standard. It can directly provide a quantitative decision basis for raw material ratio optimization and equipment parameter calibration.

[0150] Furthermore, the steps for calculating the purity assurance rate of the preparation batch, combining the reactivity characteristics and the reaction coupling parameter set, are as follows: First, determine the standard threshold of the reactivity characteristics and the current detection value of the reactivity characteristics, and calculate the reactivity deviation using "(current value - standard threshold) / standard threshold × 100%"; simultaneously, extract the standard synergistic state of the reaction coupling parameter set and the actual value of the coupling parameter in the current production, and calculate the coupling parameter adaptation deviation using "1 - Euclidean distance between the actual value of the coupling parameter and the standard synergistic state / standard synergistic state range"; then, assign weights according to the preparation process characteristics; finally, multiply the reactivity deviation and the coupling parameter adaptation deviation by their corresponding weights, and calculate the purity assurance rate using "100% - (absolute value of the sum of the two products)".

[0151] Specifically, the construction of the reaction coupling parameter set for the production process includes:

[0152] Images of the reaction zone inside the furnace during the production process are acquired, and image enhancement processing is performed on the images of the reaction zone inside the furnace to obtain clear reaction images;

[0153] Thermal response features are extracted from the clear reaction image to obtain a thermal response feature map;

[0154] Identify the temperature distribution region in the thermal response feature map, and calculate the temperature gradient change rate of the production process based on the temperature distribution region;

[0155] Extract the material distribution information corresponding to the thermal response feature map, and calculate the material mixing uniformity of the production process based on the material distribution information;

[0156] Based on the temperature gradient change rate and the material mixing uniformity, a set of reaction coupling parameters for the production process is generated.

[0157] It should be explained that the clear reaction image is image data that has been enhanced to clearly display the details of the reaction; the thermal response feature map is an image reflecting the heat distribution and transfer characteristics during the reaction process; the temperature distribution area is the spatial distribution range of different temperature intervals within the reaction area; the temperature gradient change rate is a quantitative indicator characterizing the degree of temperature change during the reaction process; the material distribution information is data reflecting the spatial distribution state of the reactants in the furnace; and the material mixing uniformity is a parameter that measures the degree of mixing of different materials during the reaction process.

[0158] Furthermore, the image of the reaction area inside the furnace can be enhanced using the multi-scale Retinex algorithm to improve image contrast and clarity, resulting in a clear reaction image. Infrared thermal imaging analysis is then used to extract thermal response features from the clear reaction image, identifying hot spots and heat flow paths during the reaction process to obtain a thermal response feature map. A region growing algorithm is used to identify temperature distribution regions within the thermal response feature map, and the rate of temperature change is calculated based on the temperature difference and distance between adjacent temperature regions, yielding the temperature gradient change rate. Image segmentation techniques are used to extract material distribution information corresponding to the thermal response feature map, and the material mixing uniformity is calculated by statistically analyzing the pixel distribution dispersion of different materials. The temperature gradient change rate and the material mixing uniformity are then normalized, and a weighted fusion algorithm is used to generate a reaction coupling parameter set containing multiple key parameters.

[0159] S4. Analyze the purity interference factor during the production of the preparation equipment to determine the purity contribution rate of the production process of the preparation equipment.

[0160] This invention analyzes the purity interference factors during the production of the preparation equipment and determines the purity contribution rate of the production process of the preparation equipment. It can locate the key factors and their impact ratios at the equipment level that cause purity fluctuations, avoid the one-sidedness of analyzing purity issues only from the perspective of raw materials or processes, and provide a strong basis for targeted operation and maintenance and purity control of the preparation equipment.

[0161] It should be explained that the purity interference factors are specific factors that may lead to insufficient reaction of raw materials or the introduction of impurities during the operation of the preparation equipment, thereby causing purity fluctuations. These include non-metallic impurities introduced by local erosion and flaking of the furnace lining, uneven local temperature inside the furnace caused by electrode misalignment, and raw material imbalance caused by leakage from the conveying device. The purity contribution rate is the percentage of influence of each purity interference factor of the preparation equipment on the purity deviation of a certain batch, i.e., the percentage of purity deviation caused by that factor relative to the total purity deviation, used to clarify the primary and secondary relationships of the influence of each equipment factor on purity. Furthermore, the purity interference factors during the production of the preparation equipment can be identified by analyzing the correlation between equipment operating parameters and quality data. For example, by analyzing the correlation between reaction temperature fluctuations and product impurity content, temperature control accuracy can be identified as a key interference factor. Based on the identified interference factors, a contribution evaluation system is established to determine the purity contribution rate of the preparation equipment during the production process. For example, different weights are assigned according to the degree of influence of each interference factor on purity, and the contribution ratio of the equipment in overall purity control is obtained through weighted calculation.

[0162] S5. Based on the purity deviation, the purity assurance rate, and the purity contribution rate, perform purity control processing on the raw material category in the preparation equipment to obtain the purity control result.

[0163] This invention performs purity control processing on the raw material category in the preparation equipment based on the purity deviation, the purity assurance rate, and the purity contribution rate, thereby obtaining purity control results, improving the accuracy of purity control, and ultimately improving preparation efficiency.

[0164] Furthermore, based on the purity deviation, the purity assurance rate, and the purity contribution rate, purity control processing is performed on the raw material category in the preparation equipment to obtain the purity control result. This step involves: first, determining the level of difference between the current purity and the target value based on the purity deviation; evaluating the effectiveness of the existing assurance mechanism based on the purity assurance rate; then, identifying the primary and secondary factors affecting purity based on the purity contribution rate; formulating control measures for the primary influencing factors—adjusting the raw material ratio if the issue is caused by the raw material, and repairing the corresponding components if the issue is caused by the equipment; monitoring purity changes in real time after implementing the measures until the purity deviation drops to the process-permissible range, thus obtaining the final purity control result. For a more detailed understanding of the purity control processing flow, please refer to the following... Figure 2 The purity control process flow chart.

[0165] Compared to the problems described in the background art, this invention, by querying the operational and maintenance technical requirements of the raw material categories and preparation equipment, determines the factors affecting the purity of the preparation batch. This allows for understanding the intrinsic relationship between the raw material categories, the operation of the preparation equipment, and the purity of high-carbon ferrochrome, providing a basis for assessing purity control. Furthermore, by analyzing the reaction operation status of the production process, this invention can understand the actual operation of key reaction stages in high-carbon ferrochrome preparation, capturing potential changes that may cause purity fluctuations. This provides real-time and reliable status data for subsequent calculations of purity fluctuation entropy. Moreover, by analyzing the reactivity characteristics of the raw material categories, this invention can accurately identify the differences in reaction efficiency and compatibility conditions of different raw materials during high-temperature preparation, avoiding issues caused by raw material reactivity. The problem of insufficient or excessive reaction caused by sex mismatch provides a core basis for constructing the reaction coupling parameter set of subsequent production processes. This invention analyzes the purity interference factors during the production of the preparation equipment and determines the purity contribution rate of the preparation equipment process. This allows for the identification of key factors and their proportion of influence at the equipment level that cause purity fluctuations, avoiding the one-sidedness of analyzing purity issues solely from the perspective of raw materials or processes. This provides a strong basis for targeted operation and maintenance and purity control of the preparation equipment. Finally, this invention performs purity control processing on the raw material categories in the preparation equipment based on the purity deviation, purity assurance rate, and purity contribution rate, obtaining purity control results, thereby improving the accuracy of purity control and ultimately improving preparation efficiency. Therefore, the preparation method and system for controlling the purity of high-carbon ferrochrome provided by this invention can improve the preparation efficiency of high-carbon ferrochrome purity.

[0166] like Figure 3 The diagram shown is a functional block diagram of a preparation system for controlling the purity of high-carbon ferrochrome according to the present invention.

[0167] The preparation system 300 for controlling the purity of high-carbon ferrochrome described in this invention can be installed in an electronic device. Depending on the functions implemented, the preparation system for controlling the purity of high-carbon ferrochrome may include a purity element determination module 301, a purity deviation analysis module 302, a purity assurance rate calculation module 303, a purity contribution rate determination module 304, and a purity control execution module 305. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and is stored in the memory of the electronic device.

[0168] In this embodiment of the invention, the functions of each module / unit are as follows:

[0169] The purity factor determination module 301 is used to obtain the high carbon ferrochrome preparation batch to be purified and the corresponding raw material categories and preparation equipment, query the operation and maintenance technical requirements of the raw material categories and preparation equipment, so as to determine the purity influencing factors of the preparation batch.

[0170] The purity deviation analysis module 302 is used to analyze the reaction operation status of the production process, calculate the purity fluctuation entropy corresponding to the purity influencing factors, and analyze the purity deviation of the preparation batch based on the purity fluctuation entropy.

[0171] The purity assurance rate calculation module 303 is used to analyze the reactivity characteristics of the raw material category, construct a set of reaction coupling parameters for the production process, and calculate the purity assurance rate of the preparation batch by combining the reactivity characteristics with the set of reaction coupling parameters.

[0172] The purity contribution rate determination module 304 is used to analyze the purity interference factors during the production of the preparation equipment in order to determine the purity contribution rate of the production process of the preparation equipment.

[0173] The purity control execution module 305 is used to perform purity control processing on the raw material category in the preparation equipment based on the purity deviation, the purity assurance rate, and the purity contribution rate, to obtain the purity control result.

[0174] In detail, the modules in the preparation system 300 for controlling the purity of high-carbon ferrochrome described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The method described herein is the same as the preparation method for controlling the purity of high-carbon ferrochrome, and can produce the same technical effect, so it will not be repeated here.

[0175] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0176] Finally, it should be noted that in the above embodiments, each embodiment can be combined with each other or independent. Deleting any one of them will not affect the technical implementation of other embodiments. The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for controlling the purity of high-carbon ferrochrome, characterized in that, The method includes: Obtain the batches of high-carbon ferrochrome to be purified, along with the corresponding raw material categories and preparation equipment. Query the operation and maintenance technical requirements of the raw material categories and preparation equipment to determine the factors affecting the purity of the batches. The reaction operation status of the production process is analyzed to calculate the purity fluctuation entropy corresponding to the purity influencing factors. Based on the purity fluctuation entropy, the purity deviation of the preparation batch is analyzed. The reactivity characteristics of the raw materials are analyzed, a set of reaction coupling parameters for the production process is constructed, and the purity assurance rate of the preparation batch is calculated by combining the reactivity characteristics with the set of reaction coupling parameters. Analyze the purity interference factor during the production process of the preparation equipment to determine the purity contribution rate of the production process of the preparation equipment; Based on the purity deviation, the purity assurance rate, and the purity contribution rate, the purity control process of the raw material category in the preparation equipment is performed to obtain the purity control result.

2. The preparation method for controlling the purity of high-carbon ferrochrome as described in claim 1, characterized in that, The process of querying the operation and maintenance technical requirements of the raw material categories and preparation equipment to determine the factors affecting the purity of the preparation batch includes: Collect production process information of the raw material categories and preparation equipment, and calculate the production variation rate corresponding to the production process information; Based on the production variation rate, key production information is extracted from the production process information; Query the process operation standards corresponding to the raw material categories and preparation equipment, and calculate the standard conformity between the key production information and the process operation standards; Based on the standard conformity and the key production information, the factors affecting the purity of the preparation batch are determined.

3. The preparation method for controlling the purity of high-carbon ferrochrome as described in claim 2, characterized in that, The calculation of the standard conformity between the key production information and the process operation standards includes: Extract the core descriptive content from the key production information and the process operation standards to obtain the core content of the production information and the core content of the process standards. The content semantics corresponding to the core content of the production information and the core content of the process standard are analyzed to obtain the first core semantics and the second core semantics. The first core semantic and the second core semantic are digitally vectorized to obtain the first core vector and the second core vector. By combining the first core vector and the second core vector, the standard conformity between the key production information and the process operation standard is calculated.

4. The preparation method for controlling the purity of high-carbon ferrochrome as described in claim 1, characterized in that, The analysis of the reaction operation status of the production process includes: Collect operational data corresponding to the reaction stages during the production process to obtain initial reaction data; The initial reaction data is effectively filtered to obtain valid reaction data; Key features of the core state of the reaction are extracted from the effective reaction data to obtain key reaction features; Trend analysis was performed on the key characteristics of the reaction to obtain the characteristic change trends; Based on the aforementioned characteristic change trends, the reaction and operation status of the production process is analyzed.

5. The preparation method for controlling the purity of high-carbon ferrochrome as described in claim 1, characterized in that, The analysis of the reaction operation status of the production process to calculate the purity fluctuation entropy corresponding to the purity influencing factors includes: Based on the purity-influencing factors, the reaction operation status is screened to obtain the associated operation status; Collect production status data corresponding to the associated operating status, including status parameter data and production raw material data; Based on the state parameter data, calculate the state stability corresponding to the associated operating state; Based on the production raw material data, determine whether there are any abnormalities in the raw material composition of the production system; If there are no abnormalities in the raw material composition, then based on the state stability, calculate the purity fluctuation entropy corresponding to the purity influencing factor. If there are abnormalities in the raw material composition, the abnormal composition characteristics of the raw material composition are extracted from the production raw material data. Based on the aforementioned abnormal component characteristics, the component influence degree corresponding to the raw material component is calculated; By combining the influence of the components and the stability of the state, the purity fluctuation entropy corresponding to the purity influencing factor is calculated.

6. The preparation method for controlling the purity of high-carbon ferrochrome as described in claim 5, characterized in that, The calculation of the component influence degree corresponding to the raw material component based on the component anomaly characteristics includes: Extract the records of elements exceeding limits, the periodicity of component fluctuations, and the locations of abnormal components from the abnormal component features; Based on the records of element exceedances, the abnormality level of the raw material components is assessed. Based on the component fluctuation cycle, determine the abnormal duration of the raw material component. Based on the location of the abnormal component, the process isolation degree between the abnormal component and the core reaction area is calculated; By combining the process isolation degree, the duration of the abnormality, and the level of the component abnormality, the component influence degree corresponding to the raw material component is calculated.

7. The preparation method for controlling the purity of high-carbon ferrochrome as described in claim 1, characterized in that, The analysis of the reactivity characteristics of the raw material category includes: Obtain the material composition information of the raw material category, perform phase structure analysis on the material composition information, and obtain the crystal configuration characteristics of the raw material; Based on the crystal structure characteristics, the enthalpy change curves of the raw materials of the aforementioned raw material category during the heating process are constructed; Based on the enthalpy change curve, the phase transition behavior of the raw materials of the raw material category in different temperature ranges is identified; Extract the activation energy threshold corresponding to the phase transition behavior, and analyze the reactivity characteristics of the raw material category based on the activation energy threshold.

8. The preparation method for controlling the purity of high-carbon ferrochrome as described in claim 7, characterized in that, The construction of the enthalpy change curve of the raw material category during the heating process based on the crystal structure characteristics includes: The structural integrity of the crystal form configuration features is verified to obtain the effective crystal form features; Extract the crystal structure parameters of the effective crystal form characteristics, perform thermodynamic correlation processing on the crystal structure parameters, and obtain the standard thermodynamic characteristics; Thermal response features are extracted from the standard thermodynamic features to obtain the dominant thermal response features; The dominant thermal response characteristics are divided into phase transition stages to obtain segmented thermal response characteristics; The enthalpy change characteristics are fitted to the segmented thermal response characteristics to obtain the enthalpy change characteristics; Based on the aforementioned enthalpy change characteristics, enthalpy change curves of the raw materials of the aforementioned raw material category during the heating process are constructed.

9. The preparation method for controlling the purity of high-carbon ferrochrome as described in claim 1, characterized in that, The set of reaction coupling parameters for constructing the production process includes: Images of the reaction zone inside the furnace during the production process are acquired, and image enhancement processing is performed on the images of the reaction zone inside the furnace to obtain clear reaction images; Thermal response features are extracted from the clear reaction image to obtain a thermal response feature map; Identify the temperature distribution region in the thermal response feature map, and calculate the temperature gradient change rate of the production process based on the temperature distribution region; Extract the material distribution information corresponding to the thermal response feature map, and calculate the material mixing uniformity of the production process based on the material distribution information; Based on the temperature gradient change rate and the material mixing uniformity, a set of reaction coupling parameters for the production process is generated.

10. A preparation system for controlling the purity of high-carbon ferrochrome, characterized in that, The system includes: The purity factor determination module is used to obtain the high-carbon ferrochrome preparation batch to be purified and the corresponding raw material categories and preparation equipment, query the operation and maintenance technical requirements of the raw material categories and preparation equipment, and determine the purity influencing factors of the preparation batch. The purity deviation analysis module is used to analyze the reaction operation status of the production process to calculate the purity fluctuation entropy corresponding to the purity influencing factors, and to analyze the purity deviation of the preparation batch based on the purity fluctuation entropy. The purity assurance rate calculation module is used to analyze the reactivity characteristics of the raw material category, construct a set of reaction coupling parameters for the production process, and calculate the purity assurance rate of the preparation batch by combining the reactivity characteristics with the set of reaction coupling parameters. The purity contribution rate determination module is used to analyze the purity interference factors during the production of the preparation equipment in order to determine the purity contribution rate of the production process of the preparation equipment. The purity control execution module is used to perform purity control processing on the raw material category in the preparation equipment based on the purity deviation, the purity assurance rate, and the purity contribution rate, to obtain the purity control result.

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