Smelting equipment monitoring method and system based on operation data analysis

Abstract

The invention discloses a smelting equipment monitoring method and system based on operation data analysis, and relates to the technical field of smelting equipment monitoring, and the method comprises the steps: determining a smelting process according to a smelting process task, so as to determine a process sequence, a series-parallel connection relation and related content of the process task between smelting equipment; and a reliable basis is provided for setting a dynamic monitoring base line of subsequent smelting equipment. The fluctuation degree of the smelting equipment is defined, the raw material output quality of the smelting equipment is evaluated, and the fluctuation condition of each piece of operation state information of the equipment and the raw material output condition of the equipment are considered, so that the dynamic monitoring base line of the operation state information of the smelting equipment is set, and the adaptability and accuracy of the monitoring base line are improved; working safety and efficient production of smelting equipment are guaranteed, and an excellent production basis is provided for smelting production.

Description

Technical Field

[0001] The present invention relates to the technical field of smelting equipment monitoring, and in particular to a smelting equipment monitoring method and system based on operation data analysis. Background Art

[0002] Due to the continuous pursuit of production efficiency, product quality and resource utilization efficiency in the modern smelting industry, with the expansion of smelting production scale and the intensification of market competition, traditional manual monitoring methods can no longer meet the needs of efficient and accurate management. Therefore, it has become an inevitable trend to use advanced sensor technology, data acquisition and transmission technology, and data analysis technology to conduct real-time monitoring and data analysis of smelting equipment. These technologies can monitor the operating status, process parameters and other key information of smelting equipment in real time, and timely discover equipment failures, optimize production processes, improve product quality and reduce energy consumption through data analysis. The smelting equipment monitoring solution based on operation data analysis is proposed based on this background technology, aiming to enhance the overall competitiveness and sustainable development capabilities of the smelting industry through intelligent means.

[0003] In the prior art, the monitoring of smelting equipment is often achieved through fixed thresholds of operating parameters, but does not take into account the changing and fluctuating operating conditions of the smelting equipment and the impact of the raw material conditions of each equipment in the smelting process, resulting in poor accuracy and adaptability of smelting equipment monitoring and failure to ensure the production safety of the smelting equipment.

[0004] Therefore, how to improve the accuracy and adaptability of smelting equipment monitoring is a technical problem that needs to be solved. Summary of the invention

[0005] The purpose of the present invention is to solve the problem of poor accuracy and adaptability of smelting equipment monitoring in the prior art due to the failure to consider the changing and fluctuating working conditions of the smelting equipment and the influence of the raw material conditions of each equipment in the smelting process, and to propose a smelting equipment monitoring method based on operation data analysis, which includes: Collect smelting process tasks, and determine the smelting process according to the smelting process tasks. The smelting process includes multiple smelting equipment and the series-parallel relationship between the multiple smelting equipment; Obtain the operating status information and smelting process information of each smelting equipment, define the fluctuation degree of the smelting equipment, and evaluate the raw material output quality of the smelting equipment; The dynamic monitoring baseline of the operation status information of the smelting equipment is set according to the series-parallel relationship between multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment; The monitoring of the smelting equipment is achieved by relying on the relationship between the actual value of the operating status information of the smelting equipment and the dynamic monitoring baseline.

[0006] In some embodiments of the present application, the smelting process is determined according to the smelting process task, including: The smelting process tasks include the smelting process content and the smelting task content. The smelting task content includes the smelting product information, smelting raw material information and process requirement information; Identify the basic information of all smelting equipment in the smelting process content, divide the smelting process content into multiple process steps based on the smelting equipment, and formulate the target parameter range of both the operating status information and the smelting process information involved in each process step according to the smelting product information, smelting raw material information and process requirement information; The series and parallel relationships between the process steps are identified through the process steps, and corresponding flow charts are drawn to reflect the process steps and the series and parallel relationships between the process steps, so as to form and determine the smelting process.

[0007] In some embodiments of the present application, the fluctuation degree of the smelting equipment is defined, including: Classify the operation status information of each smelting equipment, construct a numerical dot matrix of each type of operation status information, identify abnormal points and non-abnormal points on the numerical dot matrix, connect the abnormal points and non-abnormal points respectively, and perform smoothing to obtain abnormal curves and non-abnormal curves, and mark abnormal points and non-abnormal points on the abnormal curves and non-abnormal curves respectively; The abnormal curve and the non-abnormal curve are evenly divided into multiple sub-curves according to their respective lengths, the average slope of each sub-curve is calculated, and the average slope of all sub-curves is integrated to obtain the average slope of the abnormal curve and the non-abnormal curve; Calculate the continuity between the numerical points of the abnormal curve and the non-abnormal curve respectively, determine the fluctuation index of the abnormal curve and the non-abnormal curve based on the continuity and the average slope, and calculate the coefficient of variation of each type of operation status information through the numerical dot matrix; The fluctuation indexes of the abnormal curve and the non-abnormal curve as well as the coefficient of variation of the numerical dot plot are combined to define the fluctuation degree of each type of operating status information of the smelting equipment. The fluctuation degree of the smelting equipment is described by the fluctuation degree of all the operating status information of the smelting equipment.

[0008] In some embodiments of the present application, the fluctuation index of each abnormal curve and the non-abnormal curve and the coefficient of variation of the numerical dot plot are combined to define the fluctuation degree of each type of operating status information of the smelting equipment, including: ; in, is the fluctuation degree of the i-th type of operating status information, , They are the combined weights of abnormal and non-abnormal curves, , They are the volatility indicators of abnormal curves and non-abnormal curves respectively. is the coefficient of variation of the i-th type of operating status information, is the constant corresponding to the i-th type of running status information.

[0009] In some embodiments of the present application, evaluating the quality of raw material output from a smelting device includes: Monitor the actual values ​​of the operation status information and smelting process information of each smelting equipment in real time, and compare the actual values ​​of the operation status information and smelting process information with the target parameter ranges of the operation status information and smelting process information to determine the deviation degree of each type of operation status information and each type of smelting process information; Quantify the raw material output quality of each smelting equipment, and construct a reference series based on the raw material output quality, construct a comparison series based on the operating status information and smelting process information, calculate the absolute difference between the comparison series and the reference series, generate a difference series, determine the discrete degree of the difference series, determine the resolution coefficient based on the discrete degree, and calculate the grey correlation degree between each comparison series and the reference series through the resolution coefficient; The raw material output quality of each smelting equipment is comprehensively evaluated based on the grey correlation degree, each type of operating status information and each type of smelting process information deviation.

[0010] In some embodiments of the present application, a dynamic monitoring baseline of the operation status information of the smelting equipment is set according to the series-parallel relationship between multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment, including: The series-parallel relationship between multiple smelting equipment includes a series relationship and a parallel relationship; For multiple smelting equipment in parallel, the smelting task volume is allocated according to the characteristics of each smelting equipment. The operating status information of the smelting equipment is predicted through the historical data of the smelting task volume, fluctuation degree and operating status information, so as to set the dynamic monitoring baseline of the operating status information of the smelting equipment.

[0011] In some embodiments of the present application, a dynamic monitoring baseline of the operation status information of the smelting equipment is set according to the series-parallel relationship between multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment, and further includes: For multiple smelting equipment in a series relationship, determine the original monitoring baseline of the operating status information of the smelting equipment, determine the process sequence between the multiple smelting equipment according to the series relationship, and determine the adjustment coefficient based on the process sequence, the fluctuation degree of the operating status information of the smelting equipment and the raw material output quality; ; in, For the The first smelting equipment The adjustment factor of the operating status information, For the The number of operating status information of smelting equipment, For the The first smelting equipment The combined weight of the running status information, For the The first smelting equipment The fluctuation degree of the running status information, For the The first smelting equipment The fluctuation degree of the running status information, Indicates The mapping relationship corresponding to the running status information is: For the The first smelting equipment The adjustment constant of the operating status information, For the The raw material output quality of each smelting equipment, For the The corresponding constants of each smelting equipment; The original monitoring baseline of the operating status information is adjusted according to the adjustment coefficient, so as to set the dynamic monitoring baseline of the operating status information of the smelting equipment.

[0012] In some embodiments of the present application, the monitoring of the smelting equipment is achieved by relying on the relationship between the actual value of the operating status information of the smelting equipment and the dynamic monitoring baseline, including: According to the monitoring cycle of each smelting equipment, the actual value of the operating status information is regularly collected and the dynamic monitoring baseline of the operating status information is calculated, and the timestamps of the actual value of the operating status information and the dynamic monitoring baseline are determined. The actual value of the operating status information and the dynamic monitoring baseline are time-aligned, and the part of the actual value of the operating status information that deviates from the dynamic monitoring baseline and the part of the actual value of the operating status information that is subordinate to the dynamic monitoring baseline are compared, and the operating status of the smelting equipment is monitored by combining the two parts.

[0013] Correspondingly, the present application also provides a smelting equipment monitoring system based on operation data analysis, including: A determination module is used to collect smelting process tasks and determine the smelting process according to the smelting process tasks. The smelting process includes multiple smelting equipment and the series-parallel relationship between the multiple smelting equipment; The evaluation module is used to obtain the operating status information and smelting process information of each smelting equipment, define the fluctuation degree of the smelting equipment, and evaluate the raw material output quality of the smelting equipment; A setting module, used to set a dynamic monitoring baseline of the operation status information of the smelting equipment according to the series-parallel relationship between the multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment; The monitoring module is used to monitor the smelting equipment by relying on the relationship between the actual value of the operating status information of the smelting equipment and the dynamic monitoring baseline.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. Determine the smelting process according to the smelting process tasks, so as to determine the process sequence, series-parallel relationship and process task-related content between the smelting equipment, and provide a reliable basis for setting the dynamic monitoring baseline of the subsequent smelting equipment.

[0015] 2. Define the fluctuation degree of smelting equipment, evaluate the raw material output quality of smelting equipment, consider the fluctuation of each operating status information of the equipment and the raw material output of the equipment, so as to set the dynamic monitoring baseline of the operating status information of the smelting equipment, improve the adaptability and accuracy of the monitoring baseline, ensure the working safety and efficient production of the smelting equipment, and provide an excellent production foundation for smelting production. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of a smelting equipment monitoring method based on operation data analysis proposed by the present invention; Figure 2 This is a schematic diagram of the structure of the smelting equipment monitoring system based on operation data analysis proposed by the present invention. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0018] Reference Figure 1 , a smelting equipment monitoring method and system based on operation data analysis, comprising the following steps, Step S101, collecting smelting process tasks, and determining the smelting process according to the smelting process tasks, wherein the smelting process includes a plurality of smelting equipment and a series-parallel relationship between the plurality of smelting equipment.

[0019] In this embodiment, the smelting process tasks usually come from production plans, customer orders or R&D projects. These tasks clarify key information such as the target product, required raw materials, and process requirements of the smelting. In a series relationship, the equipment is connected in a specific order to form a linear production process. In a parallel relationship, multiple devices work at the same time, share the same production task, and are independent of each other.

[0020] In some embodiments of the present application, the smelting process is determined according to the smelting process task, including: The smelting process tasks include the smelting process content and the smelting task content. The smelting task content includes the smelting product information, smelting raw material information and process requirement information; Identify the basic information of all smelting equipment in the smelting process content, divide the smelting process content into multiple process steps based on the smelting equipment, and formulate the target parameter range of both the operating status information and the smelting process information involved in each process step according to the smelting product information, smelting raw material information and process requirement information; The series and parallel relationships between the process steps are identified through the process steps, and corresponding flow charts are drawn to reflect the process steps and the series and parallel relationships between the process steps, so as to form and determine the smelting process.

[0021] In this embodiment, the basic information of smelting equipment includes but is not limited to blast furnace, converter, electric furnace, refining furnace, continuous casting machine, etc., as well as auxiliary equipment such as fans, pumps, cranes, etc. Equipment type, model, parameters, etc., the smelting process is divided into multiple process steps according to the order and function of the equipment, such as raw material preparation step, melting step, refining step, casting step, etc. Each process step is described in detail, including the operation sequence, key operation points, required time, etc. The target parameter range is the parameter range under the condition of meeting the requirements of the smelting process and the efficient and normal operation of the smelting equipment. The operating status information includes the temperature, power, voltage, pressure, flow rate, etc. of the equipment, and the smelting process information includes process parameters such as raw material addition amount, additive amount, reaction temperature, etc. The smelting product information includes the chemical composition, physical properties, size specifications, etc. of the product. The smelting raw material information includes the chemical composition, particle size, moisture, etc. of the raw material. The process requirement information is the requirements of the smelting product.

[0022] In this embodiment, each process step involves a smelting equipment, a series relationship, a relationship in which one process step must be completed before the next process step can be started. A parallel relationship, a relationship in which multiple process steps can be carried out simultaneously. Use flowchart software or hand-drawn to graphically display the process steps and their series and parallel relationships. Mark the name, equipment, key parameters, operation sequence, and other information of each process step on the flowchart.

[0023] Step S102, obtaining the operating status information and smelting process information of each smelting equipment, defining the fluctuation degree of the smelting equipment, and evaluating the raw material output quality of the smelting equipment.

[0024] In this embodiment, the operating status information includes the temperature, power, voltage, pressure, flow rate, etc. of the equipment, and the smelting process information includes process parameters such as the amount of raw material added, the amount of additives, and the reaction temperature. Defining the fluctuation degree of the smelting equipment means analyzing the operating data of the previous equipment to determine the degree of change of each type of operating status information. The raw material output quality of the smelting equipment is determined by both the state of the smelting equipment and the smelting process parameters. The raw material output quality is evaluated by analyzing the matching of the parameters of the two.

[0025] It is understandable that, because in the smelting process, the quality of the raw materials output by each smelting equipment is difficult to detect or experiment in real time, the raw material output quality is evaluated here by matching the status of the smelting equipment and the smelting process parameters with the target parameter range.

[0026] In some embodiments of the present application, the fluctuation degree of the smelting equipment is defined, including: Classify the operation status information of each smelting equipment, construct a numerical dot matrix of each type of operation status information, identify abnormal points and non-abnormal points on the numerical dot matrix, connect the abnormal points and non-abnormal points respectively, and perform smoothing to obtain abnormal curves and non-abnormal curves, and mark abnormal points and non-abnormal points on the abnormal curves and non-abnormal curves respectively; The abnormal curve and the non-abnormal curve are evenly divided into multiple sub-curves according to their respective lengths, the average slope of each sub-curve is calculated, and the average slope of all sub-curves is integrated to obtain the average slope of the abnormal curve and the non-abnormal curve; Calculate the continuity between the numerical points of the abnormal curve and the non-abnormal curve respectively, determine the fluctuation index of the abnormal curve and the non-abnormal curve based on the continuity and the average slope, and calculate the coefficient of variation of each type of operation status information through the numerical dot matrix; The fluctuation indexes of the abnormal curve and the non-abnormal curve as well as the coefficient of variation of the numerical dot plot are combined to define the fluctuation degree of each type of operating status information of the smelting equipment. The fluctuation degree of the smelting equipment is described by the fluctuation degree of all the operating status information of the smelting equipment.

[0027] In this embodiment, the numerical dot plot is a scatter plot, which is arranged in chronological order. The abnormal points and non-abnormal points are connected respectively to obtain two curves. The fluctuation of the operating status information is composed of the fluctuations of the two curves. The change of each curve is described by the average slope of the sub-curve. Finally, the sub-curve is integrated to obtain the change of each abnormal curve and the non-abnormal curve. The degree of continuity between the numerical points on the curve refers to the time distance between the points. For example, the abnormal points may not appear continuously, so the abnormal curve may show discontinuous or discontinuous characteristics. The abnormal curve may show obvious trend changes, such as gradual rise or fall. Non-abnormal points usually appear continuously, so the non-abnormal curve shows continuous and smooth characteristics, reflecting the stability of the equipment under normal operating conditions. The fluctuation index of each curve is determined by combining the degree of continuity and the average slope, and the coefficient of variation (the ratio of the standard deviation to the average value) is used to reflect the fluctuation of the overall data, which includes both abnormal points and non-abnormal points. The changes in different operating status information of the smelting equipment are different.

[0028] In some embodiments of the present application, the fluctuation index of each abnormal curve and the non-abnormal curve and the coefficient of variation of the numerical dot plot are combined to define the fluctuation degree of each type of operating status information of the smelting equipment, including: ; in, is the fluctuation degree of the i-th type of operating status information, , They are the combined weights of abnormal and non-abnormal curves, , They are the volatility indicators of abnormal curves and non-abnormal curves respectively. is the coefficient of variation of the i-th type of operating status information, is the constant corresponding to the i-th type of running status information.

[0029] In this embodiment, It means that the coefficient of variation (the overall fluctuation of abnormal and non-abnormal points) is used to correct the sum of the fluctuations of the abnormal curve and the non-abnormal curve. It is a constant designed to balance the size of the correction function.

[0030] In some embodiments of the present application, evaluating the quality of raw material output from a smelting device includes: Monitor the actual values ​​of the operation status information and smelting process information of each smelting equipment in real time, and compare the actual values ​​of the operation status information and smelting process information with the target parameter ranges of the operation status information and smelting process information to determine the deviation degree of each type of operation status information and each type of smelting process information; Quantify the raw material output quality of each smelting equipment, and construct a reference series based on the raw material output quality, construct a comparison series based on the operating status information and smelting process information, calculate the absolute difference between the comparison series and the reference series, generate a difference series, determine the discrete degree of the difference series, determine the resolution coefficient based on the discrete degree, and calculate the grey correlation degree between each comparison series and the reference series through the resolution coefficient; The raw material output quality of each smelting equipment is comprehensively evaluated based on the grey correlation degree, each type of operating status information and each type of smelting process information deviation.

[0031] In this embodiment, the raw material output quality is jointly determined by the operating status of the equipment and the smelting process conditions. Here, the raw material output quality is indirectly evaluated by the data of the two, and the specific relationship between the calculation influencing factors (operating status information and smelting process information) and the system output (raw material output quality) is realized by grey correlation analysis. Determine the reference sequence (i.e., ideal value or standard value) of the raw material output quality. This sequence represents the change of the expected raw material output quality level over time or batch. For each specific factor (such as temperature, pressure, raw material quantity, etc.), collect its numerical sequence that changes over time or batch to form multiple comparison sequences. Each comparison sequence represents the deviation of the factor from the expected value at different time points or batches. For each comparison sequence, calculate its absolute difference with the reference sequence at the same time point or batch to form an absolute difference sequence (difference sequence).

[0032] In this embodiment, the degree of discreteness of the difference sequence is determined. If the degree of data discreteness between the comparison sequence and the reference sequence is large, that is, the fluctuation between the data points is large, in order to more accurately reflect the subtle differences between the data, the value of ρ (resolution coefficient) can be appropriately reduced. A smaller ρ value will make the difference between the correlation coefficients more significant, thereby improving the accuracy of the analysis. After the resolution coefficient is determined, the correlation coefficient is obtained, and then the gray correlation calculation formula is obtained, so as to accurately calculate the gray correlation (between the factor and the raw material output quality). The gray correlation calculation formula and the correlation coefficient formula here are conventional means in this field and are not given again.

[0033] In this embodiment, the grey correlation degree shows the strength of the correlation between a certain factor and the output, and the raw material output quality of each smelting equipment is comprehensively evaluated by combining the deviation degree of each type of operating status information and each type of smelting process information.

[0034] Step S103, setting a dynamic monitoring baseline for the operation status information of the smelting equipment according to the series-parallel relationship between the plurality of smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment.

[0035] In this embodiment, for multiple smelting equipment in series, the raw material output quality of the previous smelting equipment in the smelting process is processed by the next smelting equipment. The raw material output quality will affect the operating status of the next smelting equipment. The dynamic monitoring baseline of the operating status information is a dynamic threshold line of the operating status information. Within the threshold line, it means that the operating status is relatively stable and safe.

[0036] In some embodiments of the present application, a dynamic monitoring baseline of the operation status information of the smelting equipment is set according to the series-parallel relationship between multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment, including: The series-parallel relationship between multiple smelting equipment includes a series relationship and a parallel relationship; For multiple smelting equipment in parallel, the smelting task volume is allocated according to the characteristics of each smelting equipment. The operating status information of the smelting equipment is predicted through the historical data of the smelting task volume, fluctuation degree and operating status information, so as to set the dynamic monitoring baseline of the operating status information of the smelting equipment.

[0037] In this embodiment, the smelting task volume is allocated according to the characteristics of each smelting equipment, the load balance of each smelting equipment is ensured as much as possible, and the operating status information of the smelting equipment is predicted. The prediction can be achieved through time series models such as ARIMA model and SARIMA model to set the monitoring baseline.

[0038] In some embodiments of the present application, a dynamic monitoring baseline of the operation status information of the smelting equipment is set according to the series-parallel relationship between multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment, and further includes: For multiple smelting equipment in a series relationship, determine the original monitoring baseline of the operating status information of the smelting equipment, determine the process sequence between the multiple smelting equipment according to the series relationship, and determine the adjustment coefficient based on the process sequence, the fluctuation degree of the operating status information of the smelting equipment and the raw material output quality; ; in, For the The first smelting equipment The adjustment factor of the operating status information, For the The number of operating status information of smelting equipment, For the The first smelting equipment The combined weight of the running status information, For the The first smelting equipment The fluctuation degree of the running status information, For the The first smelting equipment The fluctuation degree of the running status information, Indicates The mapping relationship corresponding to the running status information is: For the The first smelting equipment The adjustment constant of the operating status information, For the The raw material output quality of each smelting equipment, For the The corresponding constants of each smelting equipment; The original monitoring baseline of the operating status information is adjusted according to the adjustment coefficient, so as to set the dynamic monitoring baseline of the operating status information of the smelting equipment.

[0039] In this embodiment, for multiple smelting equipment in a series relationship, the fluctuation degree of the raw material output quality and operating status information of the previous smelting equipment will affect the operating status of the next smelting equipment, so the above factors are considered to determine the adjustment coefficient for the original monitoring baseline. This original monitoring baseline can be the initial threshold determined jointly by the equipment conditions and process conditions. Indicates the correction of the adjustment constant of the raw material output quality of the previous smelting equipment to the sum of all the operating status information of the previous smelting equipment and a certain operating status information of the next smelting equipment. The sum of all the operating status information of the previous smelting equipment and a certain operating status information of the next smelting equipment is mapped with an adjustment constant. It is a constant to balance the size of the correction function. The original monitoring baseline of the running status information is adjusted according to the adjustment coefficient. The adjustment method can be the adjustment coefficient * original monitoring baseline.

[0040] Step S104, monitoring of the smelting equipment is achieved by relying on the relationship between the actual value of the operating status information of the smelting equipment and the dynamic monitoring baseline.

[0041] In this embodiment, actual values ​​are compared according to a preset period, and a dynamic monitoring baseline is set. By comparing the deviation between the two, the status of the smelting equipment is monitored.

[0042] In some embodiments of the present application, the monitoring of the smelting equipment is achieved by relying on the relationship between the actual value of the operating status information of the smelting equipment and the dynamic monitoring baseline, including: According to the monitoring cycle of each smelting equipment, the actual value of the operating status information is regularly collected and the dynamic monitoring baseline of the operating status information is calculated, and the timestamps of the actual value of the operating status information and the dynamic monitoring baseline are determined. The actual value of the operating status information and the dynamic monitoring baseline are time-aligned, and the part of the actual value of the operating status information that deviates from the dynamic monitoring baseline and the part of the actual value of the operating status information that is subordinate to the dynamic monitoring baseline are compared, and the operating status of the smelting equipment is monitored by combining the two parts.

[0043] In this embodiment, the operating status of the smelting equipment is monitored by combining the portion of the actual value that deviates from the dynamic monitoring baseline (the irrational operation portion) and the portion of the actual value that is within the dynamic monitoring baseline (the reasonable operation portion).

[0044] Correspondingly, the present application also provides a smelting equipment monitoring system based on operation data analysis, such as Figure 2 As shown, including, A determination module is used to collect smelting process tasks and determine the smelting process according to the smelting process tasks. The smelting process includes multiple smelting equipment and the series-parallel relationship between the multiple smelting equipment; The evaluation module is used to obtain the operating status information and smelting process information of each smelting equipment, define the fluctuation degree of the smelting equipment, and evaluate the raw material output quality of the smelting equipment; A setting module, used to set a dynamic monitoring baseline of the operation status information of the smelting equipment according to the series-parallel relationship between the multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment; The monitoring module is used to monitor the smelting equipment by relying on the relationship between the actual value of the operating status information of the smelting equipment and the dynamic monitoring baseline.

[0045] Compared with the prior art, the present invention has the following beneficial effects: 1. Determine the smelting process according to the smelting process tasks, so as to determine the process sequence, series-parallel relationship and process task-related content between the smelting equipment, and provide a reliable basis for setting the dynamic monitoring baseline of the subsequent smelting equipment.

[0046] 2. Define the fluctuation degree of smelting equipment, evaluate the raw material output quality of smelting equipment, consider the fluctuation of each operating status information of the equipment and the raw material output of the equipment, so as to set the dynamic monitoring baseline of the operating status information of the smelting equipment, improve the adaptability and accuracy of the monitoring baseline, ensure the working safety and efficient production of the smelting equipment, and provide an excellent production foundation for smelting production.

[0047] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0048] Those skilled in the art will appreciate that the accompanying drawings are merely schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily required for implementing the present invention.

[0049] Those skilled in the art will appreciate that the modules in the system in the implementation scenario can be distributed in the system of the implementation scenario according to the implementation scenario description, or can be changed accordingly and located in one or more systems different from the implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple submodules.

[0050] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A smelting equipment monitoring method based on operation data analysis, characterized in that: include, Collect smelting process tasks, and determine the smelting process according to the smelting process tasks. The smelting process includes multiple smelting equipment and the series-parallel relationship between the multiple smelting equipment; Obtain the operating status information and smelting process information of each smelting equipment, define the fluctuation degree of the smelting equipment, and evaluate the raw material output quality of the smelting equipment; The dynamic monitoring baseline of the operation status information of the smelting equipment is set according to the series-parallel relationship between multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment; The monitoring of smelting equipment is realized by relying on the relationship between the actual value of the operating status information of the smelting equipment and the dynamic monitoring baseline; in, Define the fluctuation level of the smelting equipment, including, Classify the operation status information of each smelting equipment, construct a numerical dot matrix of each type of operation status information, identify abnormal points and non-abnormal points on the numerical dot matrix, connect the abnormal points and non-abnormal points respectively, and perform smoothing to obtain abnormal curves and non-abnormal curves, and mark abnormal points and non-abnormal points on the abnormal curves and non-abnormal curves respectively; The abnormal curve and the non-abnormal curve are evenly divided into multiple sub-curves according to their respective lengths, the average slope of each sub-curve is calculated, and the average slope of all sub-curves is integrated to obtain the average slope of the abnormal curve and the non-abnormal curve; Calculate the continuity between the numerical points of the abnormal curve and the non-abnormal curve respectively, determine the fluctuation index of the abnormal curve and the non-abnormal curve based on the continuity and the average slope, and calculate the coefficient of variation of each type of operation status information through the numerical dot matrix; The fluctuation indexes of the abnormal curve and the non-abnormal curve as well as the coefficient of variation of the numerical dot plot are combined to define the fluctuation degree of each type of operating status information of the smelting equipment. The fluctuation degree of the smelting equipment is described by the fluctuation degree of all the operating status information of the smelting equipment.

2. The smelting equipment monitoring method based on operation data analysis according to claim 1 is characterized in that: Determine the smelting process according to the smelting process tasks. include, The smelting process tasks include the smelting process content and the smelting task content. The smelting task content includes the smelting product information, smelting raw material information and process requirement information; Identify the basic information of all smelting equipment in the smelting process content, divide the smelting process content into multiple process steps based on the smelting equipment, and formulate the target parameter range of both the operating status information and the smelting process information involved in each process step according to the smelting product information, smelting raw material information and process requirement information; The series and parallel relationships between the process steps are identified through the process steps, and corresponding flow charts are drawn to reflect the process steps and the series and parallel relationships between the process steps, so as to form and determine the smelting process.

3. The smelting equipment monitoring method based on operation data analysis according to claim 1 is characterized in that: The fluctuation index of abnormal curve and non-abnormal curve and the coefficient of variation of numerical dot plot are combined to define the fluctuation degree of each type of operation status information of smelting equipment, including: ； in, is the fluctuation degree of the i-th type of operating status information, , They are the combined weights of abnormal and non-abnormal curves, , They are the volatility indicators of abnormal curves and non-abnormal curves respectively. is the coefficient of variation of the i-th type of operating status information, is the constant corresponding to the i-th type of running status information.

4. The smelting equipment monitoring method based on operation data analysis according to claim 2 is characterized in that: Evaluate the quality of raw material output from smelting equipment, include, Monitor the actual values ​​of the operation status information and smelting process information of each smelting equipment in real time, and compare the actual values ​​of the operation status information and smelting process information with the target parameter ranges of the operation status information and smelting process information to determine the deviation degree of each type of operation status information and each type of smelting process information; Quantify the raw material output quality of each smelting equipment, and construct a reference series based on the raw material output quality, construct a comparison series based on the operating status information and smelting process information, calculate the absolute difference between the comparison series and the reference series, generate a difference series, determine the discrete degree of the difference series, determine the resolution coefficient based on the discrete degree, and calculate the grey correlation degree between each comparison series and the reference series through the resolution coefficient; The raw material output quality of each smelting equipment is comprehensively evaluated based on the grey correlation degree, each type of operating status information and each type of smelting process information deviation.

5. The smelting equipment monitoring method based on operation data analysis according to claim 2 is characterized in that: The dynamic monitoring baseline of the operation status information of the smelting equipment is set according to the series and parallel relationship between multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment, including: The series-parallel relationship between multiple smelting equipment includes a series relationship and a parallel relationship; For multiple smelting equipment in parallel, the smelting task volume is allocated according to the characteristics of each smelting equipment. The operating status information of the smelting equipment is predicted through the historical data of the smelting task volume, fluctuation degree and operating status information, so as to set the dynamic monitoring baseline of the operating status information of the smelting equipment.

6. The smelting equipment monitoring method based on operation data analysis according to claim 5 is characterized in that: The dynamic monitoring baseline of the operation status information of the smelting equipment is set according to the series-parallel relationship between multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment, and also includes: For multiple smelting equipment in a series relationship, determine the original monitoring baseline of the operating status information of the smelting equipment, determine the process sequence between the multiple smelting equipment according to the series relationship, and determine the adjustment coefficient based on the process sequence, the fluctuation degree of the operating status information of the smelting equipment and the raw material output quality; ； in, For the The first smelting equipment The adjustment factor of the operating status information, For the The number of operating status information of smelting equipment, For the The first smelting equipment The combined weight of the running status information, For the The first smelting equipment The fluctuation degree of the running status information, For the The first smelting equipment The fluctuation degree of the running status information, Indicates The mapping relationship corresponding to the running status information is: For the The first smelting equipment The adjustment constant of the operating status information, For the The raw material output quality of each smelting equipment, For the The corresponding constants of each smelting equipment; The original monitoring baseline of the operating status information is adjusted according to the adjustment coefficient, so as to set the dynamic monitoring baseline of the operating status information of the smelting equipment.

7. The smelting equipment monitoring method based on operation data analysis according to claim 1 is characterized in that: The monitoring of smelting equipment is achieved by relying on the relationship between the actual value of the operating status information of the smelting equipment and the dynamic monitoring baseline, including: According to the monitoring cycle of each smelting equipment, the actual value of the operating status information is regularly collected and the dynamic monitoring baseline of the operating status information is calculated, and the timestamps of the actual value of the operating status information and the dynamic monitoring baseline are determined. The actual value of the operating status information and the dynamic monitoring baseline are time-aligned, and the part of the actual value of the operating status information that deviates from the dynamic monitoring baseline and the part of the actual value of the operating status information that is subordinate to the dynamic monitoring baseline are compared, and the operating status of the smelting equipment is monitored by combining the two parts.

8. The smelting equipment monitoring system based on operation data analysis is characterized by: The system is used to implement the smelting equipment monitoring method based on operation data analysis as described in any one of claims 1 to 7, wherein the system comprises: A determination module is used to collect smelting process tasks and determine the smelting process according to the smelting process tasks. The smelting process includes multiple smelting equipment and the series-parallel relationship between the multiple smelting equipment; The evaluation module is used to obtain the operating status information and smelting process information of each smelting equipment, define the fluctuation degree of the smelting equipment, and evaluate the raw material output quality of the smelting equipment; A setting module, used to set a dynamic monitoring baseline of the operation status information of the smelting equipment according to the series-parallel relationship between the multiple smelting equipment, the fluctuation degree of the smelting equipment and the raw material output quality of the smelting equipment; The monitoring module is used to monitor the smelting equipment by relying on the relationship between the actual value of the operating status information of the smelting equipment and the dynamic monitoring baseline.

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