A negative electrode material production equipment operation control system based on data analysis

Abstract

The present invention discloses a negative electrode material production equipment operation control system based on data analysis. The data analysis negative electrode material production equipment operation control system includes: a data acquisition and transmission module; a data analysis module; a production process monitoring module; an equipment optimization module; and an optimization adjustment module. The present invention collects the operation data of the negative electrode material production equipment in a preset time period in real time and performs data analysis to extract the operation information data, and then monitors the process operation status of the negative electrode material production equipment in a preset time period in real time in combination with the production alarm threshold, and constructs a product index prediction model based on the results of real-time monitoring to optimize the negative electrode material production equipment, and finally adjusts the operation parameters of the negative electrode material production equipment in the preset time period according to the production equipment compliance coefficient and the preset production task, thereby achieving an improvement in the production efficiency during the operation of the equipment, and solving the problem of low production efficiency during the operation of the equipment in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of operation control, and in particular to an operation control system for negative electrode material production equipment based on data analysis. Background Art

[0002] With the rapid development of my country's new energy industry, big data, artificial intelligence and other technologies, the equipment operation control system based on data analysis has gradually become a research hotspot. The downstream process of the negative electrode has higher and higher requirements for powder materials. Through the operation control system, the impact of the production indicators of the previous process on the production indicators of the subsequent process is analyzed. The process requirements have higher and higher requirements for the product indicators of each process of the equipment distribution such as crushing and drying, gas conveying, grinding, grading and shaping of the pre-treatment of negative electrode materials. However, the traditional operation control method of negative electrode material production equipment often relies on manual experience and regular maintenance. This method is not only inefficient, but also easily affected by human factors, resulting in unstable equipment operation status and difficult to guarantee product quality. Therefore, the development of an operation control system for negative electrode material production equipment based on data analysis has important practical significance and application value.

[0003] The existing equipment operation control system based on data analysis can realize real-time monitoring, prediction and early warning of equipment status by collecting, analyzing and mining equipment operation data, and optimize the production process according to preset product indicator data to formulate improvement measures.

[0004] For example, the patent application with publication number: CN116294584A discloses a high-efficiency and energy-saving lithium battery negative electrode material carbonization furnace production line, which includes: a large amount of combustible volatiles appear in the initial carbonization of the lithium battery negative electrode raw materials, and a volatile extraction device is used for auxiliary heating; a carbonization cooling section is equipped with a graded cooling device and an advanced control system by an automatic control device to timely and accurately meet the carbonization process and atmosphere requirements; a waste treatment device is used for heat exchange and exhaust gas filtration.

[0005] For example, the patent application with publication number: CN116182561A discloses a mechanized loading and unloading system for the graphitization purification process of negative electrode materials, including: a conveying device, a raw material feeding device, a raw material suction and unloading device, a graphitization furnace chamber, a clinker suction and unloading device and a clinker discharging device; a raw material lifting mechanism for lifting or releasing the raw material suction and unloading device through a walking device; extracting raw material from a raw material bag according to the raw material feeding device, and conveying it to the raw material suction and unloading device; conveying the raw material suction and unloading device to the graphitization furnace chamber through the raw material lifting mechanism; conveying the clinker suction and unloading device from the graphitization furnace chamber to the clinker discharging device and discharging the clinker into the clinker bag.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the prior art, with the expansion of production scale and the increase of equipment complexity, the equipment operation status becomes unstable, product quality is difficult to ensure, and there is a problem of low production efficiency during equipment operation. Summary of the invention

[0008] The embodiment of the present application solves the problem of low production efficiency during equipment operation in the prior art by providing a negative electrode material production equipment operation control system based on data analysis, thereby achieving improved production efficiency during equipment operation.

[0009] The embodiment of the present application provides a negative electrode material production equipment operation control system based on data analysis, including: a data acquisition and transmission module, a data analysis module, a production process monitoring module, an equipment optimization module and an optimization adjustment module; wherein the data acquisition and transmission module is used to collect in real time the operation data of the negative electrode material production equipment within a preset time period and store and manage it, and the operation data includes environmental data, temperature data, pressure data, speed data, input and output data and material moisture content data; the data analysis module is used to perform data analysis on the operation data to extract operation information data and perform modeling analysis, and the operation information data is used to describe the operation performance of the negative electrode material production equipment within a preset time period; the production process monitoring module is used to analyze the operation data according to the results of the modeling analysis and in combination with the production The production alarm threshold monitors the process operation status of the negative electrode material production equipment within a preset time period in real time. The production alarm threshold is the alarm indicator when the process operation status of the negative electrode material production equipment and the corresponding product indicators of the production exceed the normal range; the equipment optimization module is used to construct a product indicator prediction model according to the results of real-time monitoring, and optimize the negative electrode material production equipment. The product indicator prediction model is used to predict the product indicators of the production products corresponding to the negative electrode material production equipment; the optimization adjustment module is used to adjust the operating parameters of the negative electrode material production equipment within a preset time period according to the results of equipment optimization and in combination with the production equipment compliance coefficient and the preset production tasks. The production equipment compliance coefficient is the degree of matching between the actual production tasks of the negative electrode material production equipment and the preset production tasks.

[0010] Furthermore, the data analysis module includes a data preprocessing unit, a feature extraction unit, a model building unit, a modeling analysis unit and a visualization analysis unit; the data preprocessing unit is used to preprocess the operation data, and the preprocessing includes removing outliers, filling missing values ​​and converting data formats; the feature extraction unit is used to extract operation information data from the operation data according to the result of the preprocessing and in combination with a preset analysis algorithm; the model building unit is used to build an information classification model according to the operation information data and in combination with the process operation status of the negative electrode material production equipment, and the information classification model is used to visualize the change trend and fluctuation range of the process operation status corresponding to the negative electrode material production equipment; the modeling analysis unit is used to analyze the information classification model in combination with the process operation status of the negative electrode material production equipment; the visualization analysis unit is used to visualize the results of the data analysis in the form of a chart according to the information classification model and in combination with the results of the modeling analysis.

[0011] Furthermore, the specific extraction steps of the operation information data include: analyzing the preprocessed operation data, determining the characteristic data target according to the analysis results, and the characteristic data target is used to reflect the process operation status and performance changes of the negative electrode material production equipment; obtaining the characteristic values ​​of the characteristic data according to the determined characteristic data target and in combination with the preset analysis algorithm, and the characteristic values ​​include the mean value, the maximum value, the standard deviation and the volatility; performing feature screening on the calculated characteristic values ​​to obtain the characteristic operation information data and storing it in the characteristic database, and outputting it in a preset format, and the characteristic database is used to classify and store the characteristic operation information data.

[0012] Furthermore, the production process monitoring module includes a production alarm threshold setting unit, a real-time status monitoring unit, an alarm triggering unit and an alarm record analysis unit; the production alarm threshold setting unit is used to set the production alarm threshold according to the results of the modeling analysis and in combination with the preset process requirements; the real-time status monitoring unit is used to monitor the process operation status of the negative electrode material production equipment in real time within a preset time period and identify abnormal operation status in combination with the set production alarm threshold; the alarm triggering unit is used to determine whether the production alarm index meets the set production alarm threshold, if so, generate alarm information and communicate, otherwise continue real-time monitoring, the production alarm index is used to measure whether the normal operation status of the negative electrode material production equipment meets the accuracy index of the alarm trigger condition, and the alarm information includes alarm time, equipment name, alarm level and abnormal operation status type; the alarm record analysis unit is used to record alarm information and analyze the abnormal operation status according to the alarm information.

[0013] Furthermore, the specific method for obtaining the production alarm index is as follows: obtaining an equipment environment index based on the operating data of the negative electrode material production equipment within a preset time period, and the equipment environment index is used to describe the degree of deviation between the operating environment of the negative electrode material production equipment and the preset operating environment of the equipment; obtaining an abnormal operation index based on the process operation status of the negative electrode material production equipment within a preset time period and in combination with the preset production task, and the abnormal operation index is used to numerically describe the degree of abnormality of the negative electrode material production equipment; calculating the production alarm index of the negative electrode material production equipment within the preset time period based on the acquired equipment environment index and the abnormal operation index, and the production alarm index is calculated by the following formula: , where is the number of the preset time period, , is the total number of preset time periods, Indicates The production alarm index of negative electrode material production equipment within a preset time period, is a natural constant, Indicates The abnormal operation index of negative electrode material production equipment within a preset time period, Indicates the abnormal operation reference index, Indicates the reference deviation of abnormal operation index, Indicates The equipment environment index of negative electrode material production equipment within a preset time period, Indicates the device environment reference index, Indicates the reference deviation of the device environment index.

[0014] Furthermore, the specific process of constructing the product index prediction model is as follows: obtaining first operating data based on the operating data of the negative electrode material production equipment and in combination with the results of real-time monitoring, the first operating data including equipment status parameters, process flow parameters and environmental parameters; collecting corresponding product index data based on product preset indicators and in combination with product preset indicator coefficients to perform data standardization and data normalization processing, the product index data including product quality data, product flow data and product consumption data; analyzing the correlation between the first operating data and the product index data to obtain correlation characteristic data, the correlation characteristic data is used to reflect the correlation characteristics of the operating status and process flow of the negative electrode material production equipment; constructing a product index prediction model based on the correlation characteristic data and optimizing the product index prediction model according to the cross-validation method.

[0015] Furthermore, the product preset index coefficient is calculated by the following formula: , where is the number of the preset time period, , is the total number of the preset time period, Indicates negative electrode material production equipment The product preset index coefficient within a preset time period, is a natural constant, It indicates the weight of the average relative deviation of product quality data relative to the preset index coefficient of the product. Indicates the reference deviation of product quality data. Indicates negative electrode material production equipment Product quality data within a preset time period, Indicates product quality reference data, Indicates the weight of the average relative deviation of product flow data relative to the preset index coefficient of the product. Indicates the reference deviation of product flow data. Indicates Product flow data of negative electrode material production equipment within a preset time period, Indicates product flow reference data, Indicates the weight of the average relative deviation of product loss data relative to the preset index coefficient of the product. Indicates the reference deviation of product consumption data. Indicates Product consumption data of negative electrode material production equipment within a preset time period, Indicates product consumption reference data.

[0016] Further, the optimization and adjustment module includes an operation parameter optimization unit, a production equipment compliance coefficient evaluation unit and an operation parameter adjustment unit; the operation parameter optimization unit is used to optimize the operation parameters of the negative electrode material production equipment according to the result of the equipment optimization and in combination with the preset product index data; the production equipment compliance coefficient evaluation unit is used to evaluate the production equipment compliance coefficient according to the result of the operation parameter optimization and in combination with the preset production equipment compliance coefficient to obtain a production equipment evaluation index, and the production equipment evaluation index is an accuracy index of the negative electrode material production equipment to complete the preset production task;

[0017] The operating parameter adjustment unit is used to adjust the operating parameters once according to the production equipment evaluation index to meet the requirements of the preset production task.

[0018] Furthermore, the specific method for obtaining the compliance coefficient of the production equipment is as follows: obtaining the energy consumption compliance coefficient and the precision compliance coefficient of the negative electrode material production equipment within a preset time period, and obtaining the corresponding reference value and reference deviation to obtain the relative deviation of the energy consumption compliance coefficient and the relative deviation of the precision compliance coefficient, wherein the energy consumption compliance coefficient is the efficiency of the negative electrode material production equipment in terms of energy consumption, and the precision compliance coefficient is the degree of compliance between the precision of the products produced by the negative electrode material production equipment within the preset time period and the preset precision standard;

[0019] The matching degree between the actual production task of the negative electrode material production equipment within the preset time period and the preset production task is analyzed by combining the equipment environment index of the negative electrode material production equipment within the preset time period and the corresponding reference value and reference deviation to obtain the corresponding production equipment compliance coefficient.

[0020] Furthermore, the specific steps of optimizing the operating parameters of the negative electrode material production equipment include: determining the operating parameters to be optimized based on the results of equipment optimization, and setting product optimization goals for trial production, wherein the product optimization goals include maximizing product quality, maximizing product flow, minimizing energy consumption and generating efficiency indicators; determining an operating parameter optimization plan based on the results of the trial production and establishing a continuous monitoring mechanism to regularly collect and analyze production data; and further adjusting the operating parameters of the negative electrode material production equipment based on the monitoring results and in combination with changes in raw materials and production demand.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. By preprocessing the operation data and combining it with a preset analysis algorithm, the operation information data in the operation data is extracted, and then an information classification model is constructed in combination with the process operation status of the negative electrode material production equipment and analyzed to predict product indicators. Finally, according to the information classification model and combined with the results of the modeling analysis, the results of the data analysis are visualized in the form of a chart, thereby achieving a more accurate analysis of the operation data, and then achieving an improvement in the production efficiency during the operation of the equipment, effectively solving the problem of low production efficiency during the operation of the equipment in the prior art.

[0023] 2. Analyze the preprocessed operation data to determine the characteristic data target, then obtain the characteristic value of the characteristic data based on the determined characteristic data target and combined with the preset analysis algorithm, and finally perform feature screening on the calculated characteristic value to obtain the characteristic operation information data and store it in the characteristic database, and output it in a preset format, thereby achieving accurate extraction of the operation information data and more precise acquisition of the operation information data.

[0024] 3. Set the production alarm threshold based on the results of modeling analysis and combined with the preset process requirements, and then determine whether the production alarm index meets the set production alarm threshold. If it does, generate alarm information and communicate, otherwise continue real-time monitoring, and finally record the alarm information and analyze the abnormal operating status based on the alarm information, thereby achieving accurate analysis of the abnormal operating status and improving the operating efficiency of the negative electrode material production equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic diagram of the structure of a negative electrode material production equipment operation control system based on data analysis provided in an embodiment of the present application;

[0026] Figure 2 A structural schematic diagram of a data analysis module in a negative electrode material production equipment operation control system based on data analysis provided in an embodiment of the present application;

[0027] Figure 3 A flowchart for extracting operation information data provided in an embodiment of the present application;

[0028] Figure 4 A schematic diagram of the structure of a production process monitoring module in a negative electrode material production equipment operation control system based on data analysis provided in an embodiment of the present application;

[0029] Figure 5 A flowchart for constructing a product indicator prediction model provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The embodiment of the present application solves the problem of low production efficiency in the operation process of the equipment in the prior art by providing a negative electrode material production equipment operation control system based on data analysis. The environmental data, temperature data, pressure data, speed data, input and output data and material moisture content data of the negative electrode material production equipment within a preset time period are collected in real time through the data acquisition and transmission module and stored and managed. Secondly, the operation data is analyzed by the data analysis module and combined with the preset analysis algorithm to extract the operation performance of the negative electrode material production equipment within the preset time period. Then, the production process monitoring module is combined with the production alarm threshold to monitor the process operation status of the negative electrode material production equipment within the preset time period in real time. Then, the equipment optimization module is used to obtain the first operation data according to the operation data of the negative electrode material production equipment and the result of real-time monitoring, and the correlation between the first operation data and the product index data is analyzed to obtain the correlation characteristic data. Then, the information classification model is analyzed and the product index is predicted in combination with the process operation status of the negative electrode material production equipment. At the same time, the negative electrode material production equipment is optimized. Finally, the optimization adjustment module is used to adjust the operation parameters of the negative electrode material production equipment within the preset time period according to the production equipment compliance coefficient and the preset production task, so as to improve the production efficiency during the operation of the equipment.

[0031] The technical solution in the embodiment of the present application is to solve the problem of low production efficiency during the operation of the above-mentioned equipment, and the overall idea is as follows:

[0032] The operation data of the negative electrode material production equipment within a preset time period is collected in real time and analyzed to obtain the operation information data. Then, the process operation status of the negative electrode material production equipment within the preset time period is monitored in real time in combination with the production alarm threshold. A product indicator prediction model is constructed based on the results of real-time monitoring. Finally, the operation parameters of the negative electrode material production equipment within the preset time period are adjusted according to the production equipment compliance coefficient and the preset production tasks, thereby achieving the effect of improving production efficiency during equipment operation.

[0033] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0034] like Figure 1As shown, it is a structural schematic diagram of a negative electrode material production equipment operation control system based on data analysis provided in an embodiment of the present application. The negative electrode material production equipment operation control system based on data analysis provided in an embodiment of the present application includes: a data acquisition and transmission module, a data analysis module, a production process monitoring module, an equipment optimization module and an optimization adjustment module; wherein the data acquisition and transmission module is used to collect the operation data of the negative electrode material production equipment within a preset time period in real time and store and manage it, and the operation data includes environmental data, temperature data, pressure data, speed data, input and output data and material moisture content data; the data analysis module is used to perform data analysis on the operation data to extract operation information data and perform modeling analysis, and the operation information data is used to describe the operation performance of the negative electrode material production equipment within a preset time period; the production process monitoring module is used to monitor the process operation status of the negative electrode material production equipment within a preset time period in real time according to the results of the modeling analysis and in combination with the production alarm threshold, wherein the process operation status is usually It includes equipment operation status (such as whether the production equipment has stopped, failed or encountered abnormal conditions), process flow parameter status (such as temperature, pressure, flow rate and flow velocity in the production process of negative electrode materials), production efficiency status (such as product quality and production speed) and product quality status (such as product qualification rate), which can be adjusted according to actual conditions; the production alarm threshold is the alarm indicator when the process operation status of the negative electrode material production equipment and the corresponding product indicators of the production exceed the normal range; the equipment optimization module is used to construct a product indicator prediction model based on the results of real-time monitoring, and optimize the negative electrode material production equipment. The product indicator prediction model is used to predict the product indicators of the production products corresponding to the negative electrode material production equipment; the optimization adjustment module is used to adjust the operation parameters of the negative electrode material production equipment within a preset time period according to the results of equipment optimization and in combination with the production equipment compliance coefficient and the preset production tasks. The production equipment compliance coefficient is the degree of match between the actual production tasks of the negative electrode material production equipment and the preset production tasks.

[0035] In this embodiment, the negative electrode material production equipment includes a crusher, a dryer, a gas delivery device, a grinder, a classifier and a shaping machine, and the corresponding process flow of the negative electrode material production equipment includes crushing, drying, gas delivery, grinding, grading and shaping; the data acquisition and transmission module is responsible for real-time collection of various types of data during the operation of the negative electrode material production equipment within a preset time period. These data are effectively stored and managed, providing a basis for subsequent data analysis. By modeling and analyzing the operation information data, the operating performance of the equipment within the preset time period can be clearly understood; after building a product index prediction model, equipment optimization and real-time monitoring are carried out, wherein the product index prediction model is used to predict the negative electrode material according to the real-time monitored data. The product indicators of the products corresponding to the negative electrode material production equipment are predicted. These product indicators usually include the purity, particle size distribution, specific capacity, and cycle performance of the negative electrode material. The changing trend of the product indicators can be predicted in advance, so as to adjust the equipment parameters and process conditions in time to optimize the product quality; equipment optimization is used to carry out targeted optimization of the negative electrode material production equipment according to the results of product indicator prediction, which usually involves adjusting and improving the structure and parameters of the negative electrode material production equipment. The optimized equipment can better adapt to production needs, improve product quality and reduce production costs, which is helpful for the comprehensive control of the process flow of the negative electrode material production equipment and realizes the improvement of production efficiency during the operation of the equipment.

[0036] Further, such as Figure 2 As shown, it is a structural schematic diagram of a data analysis module in a data analysis-based negative electrode material production equipment operation control system provided in an embodiment of the present application, the data analysis module includes a data preprocessing unit, a feature extraction unit, a model building unit, a modeling analysis unit and a visualization analysis unit; data preprocessing unit: used to preprocess the operation data, the preprocessing includes removing outliers, filling missing values ​​and data format conversion; feature extraction unit: used to extract operation information data in the operation data according to the result of preprocessing and in combination with a preset analysis algorithm; model building unit: used to build an information classification model according to the operation information data and in combination with the process operation status of the negative electrode material production equipment, the information classification model is used to visualize the change trend and fluctuation range of the process operation status corresponding to the negative electrode material production equipment; modeling analysis unit: used to analyze the information classification model in combination with the process operation status of the negative electrode material production equipment; visualization analysis unit: used to visualize the results of the data analysis in the form of a chart according to the information classification model and in combination with the results of the modeling analysis.

[0037] In this embodiment, in the data preprocessing unit, abnormal values ​​are usually caused by sensor failure and data transmission errors. The missing values ​​in the data can be processed by interpolation and mean filling methods; the preset analysis algorithms in the feature extraction unit include statistical algorithms and machine learning algorithms. In actual application, the appropriate algorithm is selected according to the operation process of the negative electrode material production equipment within a preset time period, and the extracted key operation information data includes the operation status of the equipment, generation efficiency and fault warning signals; the information classification model in the model construction unit converts the process operation status corresponding to the negative electrode material production equipment into an intuitive chart form, so as to more clearly display the change trend and fluctuation range of the process operation status, among which the change trend of the process operation status usually includes stability trend and fault warning trend; the stability trend is mainly reflected in whether the parameters of each process of the negative electrode material production equipment are kept within a relatively stable range during the long-term operation. If the parameter fluctuation is small , indicating that the equipment is running stably, otherwise, it means that there are unstable factors in the equipment and it needs to be checked and adjusted; the fault warning trend is mainly manifested in abnormal fluctuations in process parameters and exceeding the preset range. By timely discovering these trends, fault warnings can be given in advance to avoid production interruptions and equipment damage; the fluctuation range of process operation status usually includes energy consumption fluctuations and product quality fluctuations; the fluctuation range of energy consumption mainly reflects the changes in energy consumption of production equipment under different process operation conditions. Abnormal energy consumption fluctuations mean that the production equipment has problems of unreasonable energy utilization and energy waste; the fluctuation range of product quality includes changes in product performance, appearance and size. If the product quality fluctuates significantly, it means that there are unstable factors in the negative electrode material during the production process, and targeted adjustments and optimizations are needed; the visualization content in the visualization analysis unit usually includes real-time charts of equipment operation status, display of warning signals and prediction curves of product indicators, realizing more accurate analysis of operation data.

[0038] Further, such as Figure 3 As shown, it is a flow chart for extracting the operation information data provided in an embodiment of the present application, and the specific steps for extracting the operation information data include: analyzing the preprocessed operation data, and determining the characteristic data target according to the analysis result, and the characteristic data target is used to reflect the process operation status and performance changes of the negative electrode material production equipment; according to the determined characteristic data target and in combination with the preset analysis algorithm, the characteristic values ​​of the characteristic data are obtained, and the characteristic values ​​include the mean value, the maximum value, the standard deviation and the volatility; the calculated characteristic values ​​are subjected to feature screening to obtain characteristic operation information data and store them in the characteristic database for storage, and output them in a preset format at the same time, and the characteristic database is used to classify and store the characteristic operation information data.

[0039] In this embodiment, the equipment status parameters generally include the temperature, pressure and rotation speed of the equipment. The process flow parameters in actual applications also involve the parameters of each stage in the production process, such as reaction time and mixing ratio. The environmental parameters generally include the temperature, humidity and cleanliness of the production environment. After collecting the first operating data and product index data, the negative electrode material production equipment management and control system will automatically perform data analysis to find the correlation between the two. This correlation may be manifested as changes in certain operating parameters directly affecting changes in product indicators. For example, inappropriate adjustment of a key parameter of the equipment may lead to a decline in product quality or an increase in product loss. This is conducive to adapting to various operating conditions and production environments, and achieving improved product quality and production efficiency.

[0040] Further, such as Figure 4 As shown, it is a structural schematic diagram of a production process monitoring module in a negative electrode material production equipment operation control system based on data analysis provided in an embodiment of the present application, the production process monitoring module includes a production alarm threshold setting unit, a real-time status monitoring unit, an alarm triggering unit and an alarm record analysis unit; the production alarm threshold setting unit: is used to set the production alarm threshold according to the results of the modeling analysis and in combination with the preset process requirements; the real-time status monitoring unit: is used to monitor the process operation status of the negative electrode material production equipment in a preset time period in real time and identify the abnormal operation status in combination with the set production alarm threshold; the alarm triggering unit: is used to determine whether the production alarm index meets the set production alarm threshold, if so, an alarm message is generated and communication is performed, otherwise real-time monitoring is continued, the production alarm index is used to measure whether the normal operating status of the negative electrode material production equipment meets the accuracy index of the alarm trigger condition, and the alarm information includes the alarm time, equipment name, alarm level and abnormal operation status type; the alarm record analysis unit: is used to record the alarm information and analyze the abnormal operation status according to the alarm information.

[0041] In this embodiment, the core function of the production alarm threshold is to set the production alarm threshold based on the results of modeling analysis and preset process requirements. The preset process requirements generally include process requirements, equipment performance and product indicators. This means that the system can not only consider the performance limitations of the equipment itself, but also set appropriate alarm thresholds based on process requirements and product requirements to ensure that the production process is both safe and efficient. After the alarm is triggered, the alarm recording and analysis unit will record the alarm information and conduct secondary analysis, which not only helps to understand the causes and trends of equipment failures, but also provides valuable data support for equipment optimization, thereby achieving more accurate monitoring and control of negative electrode material production equipment.

[0042] Furthermore, the specific method for obtaining the production alarm index is as follows: obtaining the equipment environment index according to the operation data of the negative electrode material production equipment within a preset time period, and the equipment environment index is used to describe the degree of deviation between the operating environment of the negative electrode material production equipment and the preset operating environment of the equipment; obtaining the abnormal operation index according to the process operation status of the negative electrode material production equipment within the preset time period and in combination with the preset production task, and the abnormal operation index is used to numerically describe the abnormal degree of the negative electrode material production equipment; calculating the production alarm index of the negative electrode material production equipment within the preset time period according to the obtained equipment environment index and abnormal operation index. In addition to being obtained by using a statistical algorithm to perform a weighted summation of the equipment environment index and the abnormal operation index and combining the corresponding weighting factor, the production alarm index can also be calculated by the following formula: ,

[0043] In the formula, is the number of the preset time period, , is the total number of preset time periods, Indicates The production alarm index of negative electrode material production equipment within a preset time period, is a natural constant, Indicates The abnormal operation index of negative electrode material production equipment within a preset time period, Indicates the abnormal operation reference index, Indicates the reference deviation of abnormal operation index, Indicates The equipment environment index of negative electrode material production equipment within a preset time period, Indicates the device environment reference index, Indicates the reference deviation of the device environment index.

[0044] In this embodiment, before calculating the production alarm index, the accuracy index of measuring the environmental conditions on the negative electrode material production equipment and the accuracy index of abnormal conditions occurring during the operation of the negative electrode material production equipment are determined according to the operation data of the negative electrode material production equipment within a preset time period. The preset time period in the formula refers to a specific time period set according to the operation characteristics and requirements of the production equipment for segmented analysis of the equipment operation data; the specific acquisition step of the equipment environment index also includes: collecting and statistically analyzing the environmental parameters of the negative electrode material production equipment within the preset time period, wherein the environmental parameters include temperature, humidity and air pressure, and then analyzing the change trend of the environmental parameters according to the statistical results and judging whether the environmental parameters are within the preset normal range and whether they have an impact on the production equipment, and finally determining the weight distribution of the equipment environment index in combination with the production requirements of the negative electrode material production equipment, and weighted summing the statistics and change trends of the environmental parameters to obtain the equipment environment index; the specific calculation formula of the equipment environment index is: , where Indicates The temperature of the negative electrode material production equipment within a preset time period, represents the reference temperature, represents the temperature reference deviation, Indicates The humidity of the negative electrode material production equipment within a preset time period, Indicates the reference humidity, Indicates the humidity reference deviation, Indicates The gas pressure of the negative electrode material production equipment within a preset time period, Indicates the reference air pressure, Indicates the pressure reference deviation. In practical applications, the abnormal operation index is usually calculated based on the weight of the abnormal degree, the frequency and duration of the abnormal situation. Specific influencing factors also include failure rate, downtime and reduced production efficiency, so as to evaluate whether the operating status of the equipment is stable and whether there are potential risks. The specific calculation formula of the abnormal operation index is: , where The weight representing the degree of abnormality, Indicates The frequency of abnormal conditions in the negative electrode material production equipment within a preset time period, Indicates the abnormal reference frequency, Indicates abnormal frequency reference deviation, Indicates The duration of abnormal conditions in negative electrode material production equipment within a preset time period, A reference deviation indicating the duration of an abnormal situation; achieving improved operational stability of negative electrode material production equipment.

[0045] Further, such as Figure 5 As shown, it is a flow chart for constructing a product index prediction model provided in an embodiment of the present application. The specific process of constructing the product index prediction model is: according to the operating data of the negative electrode material production equipment and in combination with the results of real-time monitoring, first operating data is obtained, and the first operating data includes equipment status parameters, process flow parameters and environmental parameters; according to the product preset indicators and in combination with the product preset indicator coefficients, the corresponding product index data is collected to perform data standardization and data normalization processing, and the product index data includes product quality data, product flow data and product loss data; the correlation between the first operating data and the product index data is analyzed to obtain correlation feature data, and the correlation feature data is used to reflect the correlation characteristics of the operating status and process flow of the negative electrode material production equipment; according to the correlation feature data, a product index prediction model is constructed and the product index prediction model is optimized according to the cross-validation method.

[0046] In this embodiment, the negative electrode material production equipment management and control system performs feature screening on the calculated eigenvalues, removes redundant feature data related to the operation management and control of the negative electrode material production equipment, and retains key information related to the management and control decision. Feature screening is helpful to reduce the dimension and complexity of the data and improve the efficiency of subsequent analysis and processing. In addition, the feature database is not only used to store data, but also has the function of automatic classification. It can automatically classify and organize the data according to its characteristics and attributes, which is convenient for querying, analyzing and utilizing the data. The obtained operation information data can be directly used for subsequent management and control decisions, fault diagnosis and performance optimization, realizing in-depth analysis and accurate evaluation of the equipment operation status.

[0047] Furthermore, the product preset index coefficient can be obtained by filtering the first operation data and combining the linear regression method in the machine learning algorithm according to the key data features and the corresponding weights after filtering, or by calculating the coefficient using the following formula: , where is the number of the preset time period, , is the total number of the preset time period, Indicates negative electrode material production equipment The product preset index coefficient within a preset time period, is a natural constant, It indicates the weight of the average relative deviation of product quality data relative to the preset index coefficient of the product. Indicates the reference deviation of product quality data. Indicates negative electrode material production equipment Product quality data within a preset time period, Indicates product quality reference data, Indicates the weight of the average relative deviation of product flow data relative to the preset index coefficient of the product. Indicates the reference deviation of product flow data. Indicates Product flow data of negative electrode material production equipment within a preset time period, Indicates product flow reference data, Indicates the weight of the average relative deviation of product loss data relative to the preset index coefficient of the product. Indicates the reference deviation of product consumption data. Indicates Product consumption data of negative electrode material production equipment within a preset time period, Indicates product consumption reference data.

[0048] In this embodiment, when calculating the product preset indicator coefficient, the average relative deviation and reference deviation of each coefficient are also considered. The average relative deviation reflects the degree of deviation between the actual monitoring value and the reference value, and the reference deviation is a standard deviation value set based on historical data and experience. By introducing these deviation values, the real-time monitoring data can be standardized so that data between different time periods and different monitoring times are comparable. The set weights are used to adjust the relative importance of each coefficient in calculating the product preset indicator coefficient, and are adjusted according to actual needs, which is conducive to ensuring the stability of the production process and the consistency of product quality, and realizing precise control and optimization of production equipment.

[0049] Furthermore, the optimization and adjustment module includes an operating parameter optimization unit, a production equipment compliance coefficient evaluation unit and an operating parameter adjustment unit; the operating parameter optimization unit is used to optimize the operating parameters of the negative electrode material production equipment according to the results of the equipment optimization and in combination with the preset product index data; the production equipment compliance coefficient evaluation unit is used to evaluate the production equipment compliance coefficient according to the results of the operating parameter optimization and in combination with the preset production equipment compliance coefficient to obtain a production equipment evaluation index, and the production equipment evaluation index is an accuracy index for the negative electrode material production equipment to complete the preset production task; the operating parameter adjustment unit is used to adjust the operating parameters once according to the production equipment evaluation index to meet the requirements of the preset production task.

[0050] In this embodiment, the operating parameter optimization unit uses data analysis technology and combines the historical operating data and product index data of the equipment to make an adjustment to find the best operating parameter combination to improve the operating efficiency and product quality of the equipment, wherein one adjustment represents the adjustment of the temperature, pressure, speed, input and output volume and material moisture content of the negative electrode material production equipment; the optimization and adjustment module also includes an adjustment effect monitoring unit, wherein the adjustment effect monitoring unit timely discovers problems in the equipment operation process through real-time monitoring and data analysis, and evaluates the adjustment effect input and output volume. If the adjustment effect is not good, the negative electrode material production equipment management and control system can automatically make a secondary adjustment and issue an early warning reminder to ensure that the equipment is always operating in the best condition, thereby reducing production costs and failure rates.

[0051] Furthermore, the specific method for obtaining the production equipment compliance coefficient is as follows: obtain the energy consumption compliance coefficient and the precision compliance coefficient of the negative electrode material production equipment within the preset time period, and obtain the corresponding reference value and reference deviation to obtain the relative deviation of the energy consumption compliance coefficient and the relative deviation of the precision compliance coefficient. The energy consumption compliance coefficient is the efficiency of the negative electrode material production equipment in terms of energy consumption, and the precision compliance coefficient is the degree of compliance between the precision of the products produced by the negative electrode material production equipment within the preset time period and the preset precision standard; combine the equipment environment index of the negative electrode material production equipment within the preset time period and the corresponding reference value and reference deviation to analyze the degree of match between the actual production task of the negative electrode material production equipment within the preset time period and the preset production task, and obtain the corresponding production equipment compliance coefficient

[0052] In this embodiment, a machine learning model can be established through the operation data of the negative electrode material production equipment within a preset time period and the compliance data of the preset production task, and the operation status and performance of the production equipment under specific conditions are predicted and a comprehensive evaluation index system is established. Then, the corresponding proportion weights are combined for weighted summation to obtain the production equipment compliance coefficient. In addition to obtaining the production equipment compliance coefficient by this method, it can also be calculated by the following formula: , where Indicates The production equipment compliance coefficient of negative electrode material production equipment within a preset time period, The correction factor representing the relative deviation of the equipment environment index, Indicates the relative deviation correction factor of energy consumption compliance coefficient, Indicates The energy consumption of negative electrode material production equipment meets the coefficient within a preset time period. Indicates that the energy consumption meets the reference coefficient, Indicates that the energy consumption complies with the coefficient reference deviation, Indicates the relative deviation correction factor of the accuracy compliance coefficient, Indicates The accuracy compliance coefficient of negative electrode material production equipment within a preset time period, Indicates that the accuracy meets the reference coefficient, It indicates the reference deviation of the accuracy compliance coefficient. By combining the coefficients of various influencing factors to obtain the compliance coefficient of the production equipment, the negative electrode material production equipment management and control system automatically conducts an evaluation, which helps to have a more comprehensive understanding of the operating status of the production equipment, discover potential problems in time and take corresponding measures to adjust and optimize, thereby achieving improved operating stability of the production equipment and production efficiency.

[0053] Furthermore, the specific steps for optimizing the operating parameters of the negative electrode material production equipment include: determining the operating parameters to be optimized based on the results of equipment optimization, and setting product optimization goals for trial production, the product optimization goals include maximizing product quality, maximizing product flow, minimizing energy consumption and generating efficiency indicators; determining the operating parameter optimization plan based on the results of the trial production and establishing a continuous monitoring mechanism to regularly collect and analyze production data; further adjusting the operating parameters of the negative electrode material production equipment based on the monitoring results and in combination with changes in raw materials and changes in production demand.

[0054] In this embodiment, during the test production process, product performance is monitored in real time and relevant test data is collected. By comparing with the preset product index data, the negative electrode material production equipment operation control system can evaluate the production effect, understand which operating parameter adjustments have a positive impact on improving product quality and production efficiency, and which may have a negative impact and be removed. Based on the evaluation results of the test effects, the optimized operating parameter plan is determined, and then the operating parameters of the negative electrode material production equipment are further adjusted according to the monitoring results and combined with the changes in raw materials and production demand changes to ensure the stable progress of the production process and achieve more accurate optimization of the operating parameters of the negative electrode material production equipment.

[0055] The technical scheme in the above-mentioned embodiment of the present application has at least the following technical effects or advantages: relative to a high-efficiency and energy-saving lithium battery negative electrode material carbonization furnace production line disclosed in the patent application with publication number: CN116294584A, the embodiment of the present application analyzes the pre-processed operation data to determine the characteristic data target, and then obtains the characteristic value of the characteristic data according to the determined characteristic data target and in combination with the preset analysis algorithm, and finally performs feature screening on the calculated characteristic value to obtain characteristic operation information data and stores it in the characteristic database for storage, and outputs it in a preset format, thereby realizing accurate extraction of operation information data, and then realizing more accurate acquisition of operation information data; relative to a mechanized loading and unloading furnace system for a graphitization purification process of a negative electrode material disclosed in the patent application with publication number: CN116182561A, the embodiment of the present application sets a production alarm threshold through the results of modeling analysis and in combination with preset process requirements, and then determines whether the production alarm index meets the set production alarm threshold. If it meets, an alarm message is generated and communicated, otherwise real-time monitoring is continued, and finally the alarm message is recorded and the abnormal operation state is analyzed according to the alarm message, thereby realizing accurate analysis of the abnormal operation state, and then realizing the improvement of the operation efficiency of the negative electrode material production equipment.

[0056] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0057] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0058] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0059] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0060] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0061] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A negative electrode material production equipment operation control system based on data analysis, characterized in that: It includes data acquisition and transmission module, data analysis module, production process monitoring module, equipment optimization module and optimization adjustment module; The data acquisition and transmission module is used to collect and store the operating data of the negative electrode material production equipment in a preset time period in real time, and the operating data includes environmental data, temperature data, pressure data, speed data, input and output data, and material moisture content data; The data analysis module is used to perform data analysis on the operation data to extract operation information data and perform modeling analysis, wherein the operation information data is used to describe the operation performance of the negative electrode material production equipment within a preset time period; The production process monitoring module is used to monitor the process operation status of the negative electrode material production equipment in real time within a preset time period according to the results of the modeling analysis and in combination with the production alarm threshold, wherein the production alarm threshold is the alarm indicator when the process operation status of the negative electrode material production equipment and the corresponding product indicators of the production exceed the normal range; The equipment optimization module is used to construct a product index prediction model according to the results of real-time monitoring, and optimize the negative electrode material production equipment. The product index prediction model is used to predict the product index of the production product corresponding to the negative electrode material production equipment; The optimization and adjustment module is used to adjust the operating parameters of the negative electrode material production equipment within a preset time period according to the equipment optimization results and in combination with the production equipment compliance coefficient and the preset production task, wherein the production equipment compliance coefficient is the matching degree between the actual production task of the negative electrode material production equipment and the preset production task; The production process monitoring module includes a production alarm threshold setting unit, a real-time status monitoring unit, an alarm triggering unit and an alarm record analysis unit; The production alarm threshold setting unit is used to set the production alarm threshold according to the results of the modeling analysis and in combination with the preset process requirements; The real-time status monitoring unit is used to monitor the process operation status of the negative electrode material production equipment in real time within a preset time period and identify abnormal operation status in combination with the set production alarm threshold; The alarm trigger unit is used to determine whether the production alarm index meets the set production alarm threshold. If so, an alarm message is generated and communication is performed; otherwise, real-time monitoring is continued. The production alarm index is used to measure the accuracy index of whether the normal operating state of the negative electrode material production equipment meets the alarm trigger condition. The alarm information includes the alarm time, equipment name, alarm level and abnormal operating state type; The alarm recording and analyzing unit is used to record the alarm information and analyze the abnormal operation status according to the alarm information; The specific method for obtaining the production alarm index is as follows: Acquire an equipment environment index according to the operating data of the negative electrode material production equipment within a preset time period, wherein the equipment environment index is used to describe the degree of deviation between the operating environment of the negative electrode material production equipment and the preset operating environment of the equipment; Obtaining an abnormal operation index according to the process operation status of the negative electrode material production equipment within a preset time period and in combination with a preset production task, wherein the abnormal operation index is used to numerically describe the abnormality degree of the negative electrode material production equipment; The production alarm index of the negative electrode material production equipment within a preset time period is calculated according to the acquired equipment environment index and abnormal operation index. The production alarm index is calculated by the following formula: ， In the formula, is the number of the preset time period, , is the total number of preset time periods, Indicates The production alarm index of negative electrode material production equipment within a preset time period, is a natural constant, Indicates The abnormal operation index of negative electrode material production equipment within a preset time period, Indicates the abnormal operation reference index, Indicates the reference deviation of abnormal operation index, Indicates The equipment environment index of negative electrode material production equipment within a preset time period, Indicates the device environment reference index, Indicates the reference deviation of the device environment index.

2. The negative electrode material production equipment operation control system based on data analysis as claimed in claim 1, characterized in that: The data analysis module includes a data preprocessing unit, a feature extraction unit, a model building unit, a modeling analysis unit and a visualization analysis unit; The data preprocessing unit is used to preprocess the running data, and the preprocessing includes removing outliers, filling missing values ​​and converting data formats; The feature extraction unit is used to extract the operation information data from the operation data according to the preprocessing result and in combination with the preset analysis algorithm; The model building unit is used to build an information classification model based on the operation information data and in combination with the process operation status of the negative electrode material production equipment, and the information classification model is used to visualize the change trend and fluctuation range of the process operation status corresponding to the negative electrode material production equipment; The modeling and analysis unit is used to analyze the information classification model in combination with the process operation status of the negative electrode material production equipment; The visualization analysis unit is used to visualize the results of data analysis in the form of charts based on the information classification model and in combination with the results of modeling analysis.

3. A negative electrode material production equipment operation control system based on data analysis as claimed in claim 2, characterized in that: The specific steps of extracting the operation information data include: Analyze the pre-processed operation data, and determine characteristic data targets according to the analysis results, wherein the characteristic data targets are used to reflect the process operation status and performance changes of the negative electrode material production equipment; According to the determined characteristic data target and in combination with the preset analysis algorithm, characteristic values ​​of the characteristic data are obtained, wherein the characteristic values ​​include the average value, the maximum value, the standard deviation and the volatility; The calculated characteristic values ​​are subjected to characteristic screening to obtain characteristic operation information data and stored in a characteristic database for storage, and output in a preset format at the same time. The characteristic database is used to classify and store the characteristic operation information data.

4. The negative electrode material production equipment operation control system based on data analysis as claimed in claim 1, characterized in that: The specific process of constructing the product index prediction model is as follows: Acquire first operating data according to the operating data of the negative electrode material production equipment and in combination with the result of real-time monitoring, wherein the first operating data includes equipment status parameters, process flow parameters and environmental parameters; According to the preset product indicators and in combination with the preset product indicator coefficients, corresponding product indicator data are collected to perform data standardization and data normalization processing, wherein the product indicator data includes product quality data, product flow data and product loss data; Analyzing the correlation between the first operation data and the product index data to obtain correlation characteristic data, wherein the correlation characteristic data is used to reflect the correlation characteristics of the operation status and process flow of the negative electrode material production equipment; A product indicator prediction model is constructed based on the correlation feature data and the product indicator prediction model is optimized using the cross-validation method.

5. A negative electrode material production equipment operation control system based on data analysis as claimed in claim 4, characterized in that: The product preset index coefficient is calculated by the following formula: ， In the formula, is the number of the preset time period, , is the total number of the preset time period, Indicates negative electrode material production equipment The product preset index coefficient within a preset time period, is a natural constant, It indicates the weight of the average relative deviation of product quality data relative to the preset index coefficient of the product. Indicates the reference deviation of product quality data. Indicates negative electrode material production equipment Product quality data within a preset time period, Indicates product quality reference data, Indicates the weight of the average relative deviation of product flow data relative to the preset index coefficient of the product. Indicates the reference deviation of product flow data. Indicates Product flow data of negative electrode material production equipment within a preset time period, Indicates product flow reference data, Indicates the weight of the average relative deviation of product loss data relative to the preset index coefficient of the product. Indicates the reference deviation of product consumption data. Indicates Product consumption data of negative electrode material production equipment within a preset time period, Indicates product consumption reference data.

6. The negative electrode material production equipment operation control system based on data analysis according to claim 1, characterized in that: The optimization and adjustment module includes an operation parameter optimization unit, a production equipment compliance coefficient evaluation unit and an operation parameter adjustment unit; The operating parameter optimization unit is used to optimize the operating parameters of the negative electrode material production equipment according to the equipment optimization results and in combination with the preset product index data; The production equipment compliance coefficient evaluation unit is used to evaluate the production equipment compliance coefficient according to the result of the operation parameter optimization and in combination with the preset production equipment compliance coefficient to obtain a production equipment evaluation index, wherein the production equipment evaluation index is an accuracy index of the negative electrode material production equipment in completing the preset production task; The operating parameter adjustment unit is used to adjust the operating parameters once according to the production equipment evaluation index to meet the requirements of the preset production task.

7. A negative electrode material production equipment operation control system based on data analysis as claimed in claim 6, characterized in that: The specific method for obtaining the production equipment compliance coefficient is as follows: Obtaining the energy consumption compliance coefficient and the precision compliance coefficient of the negative electrode material production equipment within a preset time period, and obtaining the corresponding reference value and reference deviation to obtain the relative deviation of the energy consumption compliance coefficient and the relative deviation of the precision compliance coefficient, wherein the energy consumption compliance coefficient is the efficiency of the negative electrode material production equipment in terms of energy consumption, and the precision compliance coefficient is the degree of compliance between the precision of the products produced by the negative electrode material production equipment within the preset time period and the preset precision standard; The matching degree between the actual production task of the negative electrode material production equipment within the preset time period and the preset production task is analyzed by combining the equipment environment index of the negative electrode material production equipment within the preset time period and the corresponding reference value and reference deviation to obtain the corresponding production equipment compliance coefficient.

8. A negative electrode material production equipment operation control system based on data analysis as claimed in claim 6, characterized in that: The specific steps of optimizing the operating parameters of the negative electrode material production equipment include: Determine the operating parameters to be optimized based on the results of equipment optimization, and set product optimization goals for trial production, wherein the product optimization goals include maximizing product quality, maximizing product flow, minimizing energy consumption and generating efficiency indicators; Determine the optimization plan for operating parameters based on the results of the trial production and establish a continuous monitoring mechanism to regularly collect and analyze production data; Based on the monitoring results and in combination with changes in raw materials and production demand, the operating parameters of the negative electrode material production equipment are further adjusted.

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