Smelting Equipment Monitoring Method and System Based on Operating Data Analysis

Abstract

The present invention discloses a smelting equipment monitoring method and system based on operation data analysis, which relates to the technical field of smelting equipment monitoring. It includes determining the smelting process according to the smelting process task, so as to determine the process sequence, series-parallel relationship and process task-related content among smelting equipment, providing a reliable basis for setting the dynamic monitoring baseline of subsequent smelting equipment. The degree of fluctuation of smelting equipment is defined, the raw material output quality of smelting equipment is evaluated, considering the fluctuation of each operation state information of the equipment and the raw material output of the equipment, thereby setting the dynamic monitoring baseline of the operation state information of smelting equipment, improving the adaptability and accuracy of the monitoring baseline, ensuring the work safety and efficient production of smelting equipment, and providing an excellent production basis for smelting production.

Description

Technical Field

[0001] The present invention relates to the technical field of smelting equipment monitoring, and particularly 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 are difficult to meet the requirements 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 on smelting equipment. These technologies can monitor key information such as the operating status and process parameters of smelting equipment in real time, and through data analysis, timely detect equipment failures, optimize production processes, improve product quality, and reduce energy consumption. The smelting equipment monitoring solution based on operation data analysis is proposed based on this background art, aiming to enhance the overall competitiveness and sustainable development ability 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 the changing and fluctuating operating conditions of smelting equipment and the influence of raw material conditions of each other's equipment in the smelting process flow are not considered, resulting in poor accuracy and adaptability of smelting equipment monitoring and unable to ensure the production safety of smelting equipment.

[0004] Therefore, how to improve the accuracy and adaptability of smelting equipment monitoring is a technical problem to be solved at present. 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 operating conditions of smelting equipment and the influence of raw material conditions of each other's equipment in the smelting process flow, and a smelting equipment monitoring method based on operation data analysis is proposed, which includes,

[0006] 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 multiple smelting equipment;

[0007] Obtain the operating status information and smelting process information of each smelting equipment, define the degree of fluctuation of the smelting equipment, and evaluate the raw material output quality of the smelting equipment;

[0008] Set a dynamic monitoring baseline for the operating status information of the smelting equipment according to the series-parallel relationship between multiple smelting equipment, the degree of fluctuation of the smelting equipment, and the raw material output quality of the smelting equipment;

[0009] The monitoring of the smelting equipment is realized based on the relationship between the actual value of the operation status information of the smelting equipment and the dynamic monitoring baseline.

[0010] In some embodiments of the present application, the smelting process is determined according to the smelting process task, including,

[0011] The smelting process task includes the smelting process content and the smelting task content. The smelting task content includes smelting product information, smelting raw material information, and process requirement information;

[0012] All the basic information of the smelting equipment in the smelting process content is identified. The smelting process content is divided into multiple process steps in units of smelting equipment, and the target parameter ranges of the operation status information and the smelting process information involved in each process step are formulated according to the smelting product information, the smelting raw material information, and the process requirement information;

[0013] The series-parallel relationship between the process steps is identified through the process steps, and the corresponding flow chart is drawn to reflect the process steps and the series-parallel relationship between the process steps, thereby forming and determining the smelting process.

[0014] In some embodiments of the present application, the fluctuation degree of the smelting equipment is defined, including,

[0015] The operation status information of each smelting equipment is classified, a numerical dot matrix diagram of each type of operation status information is constructed, abnormal points and non-abnormal points are identified on the numerical dot matrix diagram, the abnormal points and non-abnormal points are respectively connected and smoothed to obtain an abnormal curve and a non-abnormal curve, and the abnormal points and non-abnormal points are respectively marked on the abnormal curve and the non-abnormal curve;

[0016] The abnormal curve and the non-abnormal curve are evenly split into multiple sub-curves according to the lengths of the abnormal curve and the non-abnormal curve respectively, the average slope value of each sub-curve is calculated, and the average slope values of all the sub-curves are integrated to obtain the average slope values of the abnormal curve and the non-abnormal curve respectively;

[0017] The continuity between the numerical points of the abnormal curve and the non-abnormal curve is calculated respectively, the fluctuation indexes of the abnormal curve and the non-abnormal curve are determined based on the continuity and the average slope value, and the coefficient of variation of each type of operation status information is calculated through the numerical dot matrix diagram;

[0018] The fluctuation degree of each type of operation status information of the smelting equipment is defined by comprehensively considering the fluctuation indexes of the abnormal curve and the non-abnormal curve and the coefficient of variation of the numerical dot matrix diagram, and the fluctuation degree of the smelting equipment is described by virtue of the fluctuation degrees of all the operation status information of the smelting equipment.

[0019] In some embodiments of the present application, the fluctuation degree of each type of operating state information of the smelting equipment is defined by integrating the fluctuation indexes of the abnormal curve and the non-abnormal curve respectively and the coefficient of variation of the numerical dot matrix diagram, including,

[0020] ;

[0021] Among them, is the fluctuation degree of the i-th type of operating state information, 、 are the combination weights of the abnormal curve and the non-abnormal curve respectively, 、 are the fluctuation indexes of the abnormal curve and the non-abnormal curve respectively, is the coefficient of variation of the i-th type of operating state information, is the constant corresponding to the i-th type of operating state information.

[0022] In some embodiments of the present application, evaluating the raw material output quality of the smelting equipment includes,

[0023] Real-time monitoring the actual values of the operating state information and the smelting process information of each smelting equipment respectively, and comparing the actual values of the operating state information and the smelting process information with the target parameter ranges of the operating state information and the smelting process information to determine the deviation degrees of each type of operating state information and each type of smelting process information;

[0024] Quantify the raw material output quality of each smelting equipment, construct a reference sequence according to the raw material output quality, construct a comparison sequence according to the operating state information and the smelting process information, calculate the absolute difference between the comparison sequence and the reference sequence, generate a difference sequence, determine the dispersion degree of the difference sequence, determine the resolution coefficient based on the dispersion degree, and calculate the grey correlation degree between each comparison sequence and the reference sequence through the resolution coefficient;

[0025] Comprehensively evaluate the raw material output quality of each smelting equipment according to the grey correlation degree, the deviation degrees of each type of operating state information and each type of smelting process information.

[0026] In some embodiments of the present application, setting the dynamic monitoring baseline of the operating state information of the smelting equipment 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 includes,

[0027] The series-parallel relationship between multiple smelting equipment includes a series relationship and a parallel relationship;

[0028] For multiple smelting equipment under the parallel relationship, allocate the smelting task volume according to the characteristics of each smelting equipment, predict the operating state information of the smelting equipment through the historical data of the smelting task volume, the fluctuation degree and the operating state information, so as to set the dynamic monitoring baseline of the operating state information of the smelting equipment.

[0029] In some embodiments of the present application, according to the series-parallel relationship between multiple smelting devices, the fluctuation degree of the smelting devices, and the raw material output quality of the smelting devices, a dynamic monitoring baseline for the operating status information of the smelting devices is set. It also includes,

[0030] For multiple smelting devices in a series relationship, determine the original monitoring baseline of the operating status information of the smelting devices, determine the process sequence between the multiple smelting devices according to the series relationship, and determine the adjustment coefficient by synthesizing the process sequence, the fluctuation degree of the operating status information of the smelting devices, and the raw material output quality;

[0031] ;

[0032] Among them, is the adjustment coefficient of the th operating status information of the th smelting device, is the number of operating status information of the th smelting device, is the combination weight of the th operating status information of the th smelting device, is the fluctuation degree of the th operating status information of the th smelting device, is the fluctuation degree of the th operating status information of the th smelting device, represents the mapping relationship corresponding to the th operating status information, is the adjustment constant of the th operating status information of the th smelting device, is the raw material output quality of the th smelting device, is the corresponding constant of the th smelting device;

[0033] Adjust the original monitoring baseline of the operating status information according to the adjustment coefficient, so as to set the dynamic monitoring baseline of the operating status information of the smelting devices.

[0034] In some embodiments of the present application, the monitoring of the smelting devices is realized by virtue of the relationship between the actual value of the operating status information of the smelting devices and the dynamic monitoring baseline, including,

[0035] Regularly collect the actual values of the operating status information according to the monitoring cycle of each smelting device, calculate the dynamic monitoring baseline of the operating status information, and determine the timestamps of the actual values of the operating status information and the dynamic monitoring baseline respectively. Align the actual values of the operating status information and the dynamic monitoring baseline in terms of time, compare to obtain the part where the actual value of the operating status information deviates outside the dynamic monitoring baseline and the part where the actual value of the operating status information belongs within the dynamic monitoring baseline, and comprehensively monitor the operating status of the smelting device based on these two parts.

[0036] Correspondingly, the present application also provides a smelting device monitoring system based on operation data analysis, including,

[0037] A determination module, configured to collect smelting process tasks, determine the smelting process according to the smelting process tasks, where the smelting process includes multiple smelting devices and the series-parallel relationships between the multiple smelting devices;

[0038] An evaluation module, configured to obtain the operating status information and smelting process information of each smelting device, define the fluctuation degree of the smelting device, and evaluate the raw material output quality of the smelting device;

[0039] A setting module, configured to set the dynamic monitoring baseline of the operating status information of the smelting device according to the series-parallel relationships between the multiple smelting devices, the fluctuation degree of the smelting device, and the raw material output quality of the smelting device;

[0040] A monitoring module, configured to monitor the smelting device based on the relationship between the actual value of the operating status information of the smelting device and the dynamic monitoring baseline.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] 1. Determine the smelting process according to the smelting process tasks, so as to determine the process sequence, series-parallel relationships, and process task-related content between the smelting devices, providing a reliable basis for setting the dynamic monitoring baseline of the subsequent smelting devices.

[0043] 2. Define the fluctuation degree of the smelting device, evaluate the raw material output quality of the smelting device, consider the fluctuation of each operating status information of the device and the raw material output of the device, thereby setting the dynamic monitoring baseline of the operating status information of the smelting device, improving the adaptability and accuracy of the monitoring baseline, ensuring the work safety and efficient production of the smelting device, and providing an excellent production basis for smelting production. Description of the Drawings

[0044] Figure 1 It is a schematic flowchart of the smelting device monitoring method based on operation data analysis proposed by the present invention;

[0045] Figure 2Schematic diagram of the smelting equipment monitoring system based on operation data analysis proposed by the present invention. Specific embodiments

[0046] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0047] Referring to Figure 1 , the smelting equipment monitoring method and system based on operation data analysis include the following steps.

[0048] Step S101, collect smelting process tasks, determine the smelting process according to the smelting process tasks. The smelting process includes multiple smelting equipment and the series-parallel relationships between multiple smelting equipment.

[0049] 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 products of smelting, required raw materials, and process requirements. In a series relationship, the equipment is connected in a specific order in sequence to form a linear production process. In a parallel relationship, multiple equipment work simultaneously, jointly undertaking the same production task, and are independent of each other.

[0050] In some embodiments of the present application, determining the smelting process according to the smelting process tasks includes:

[0051] The smelting process tasks include smelting process content and smelting task content. The smelting task content includes smelting product information, smelting raw material information, and process requirement information;

[0052] Identify all the basic information of the smelting equipment in the smelting process content, divide the smelting process content into multiple process steps in units of smelting equipment, and formulate the target parameter ranges of both the operating state 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;

[0053] Identify the series-parallel relationships between the process steps through the process steps, and draw the corresponding flow chart to reflect the process steps and the series-parallel relationships between the process steps, thereby forming and determining the smelting process.

[0054] In this embodiment, the basic information of the smelting equipment includes, but is not limited to, blast furnaces, converters, electric furnaces, refining furnaces, continuous casting machines, etc., as well as auxiliary equipment such as fans, pumps, cranes, etc., including equipment types, models, parameters, etc. The smelting process is divided into multiple process steps according to the usage sequence and functions of the equipment, such as raw material preparation steps, melting steps, refining steps, casting steps, 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 state of the smelting equipment. The operation state information includes the temperature, power, voltage, pressure, flow rate, etc. of the equipment. The smelting process information includes process parameters such as raw material addition amount, additive dosage, reaction temperature, etc. The smelting product information includes the chemical composition, physical properties, dimensional specifications, etc. of the product. The smelting raw material information includes the chemical composition, particle size, moisture content, etc. of the raw materials. The process requirement information is the requirement for the smelting product.

[0055] In this embodiment, each process step involves a smelting equipment, a series relationship, that is, a relationship where the next process step can only start after one process step is completed. A parallel relationship, that is, a relationship where multiple process steps can be carried out simultaneously. Use flowchart software or draw by hand to graphically display the process steps and their series-parallel relationships. Mark information such as the name, equipment, key parameters, operation sequence, etc. of each process step on the flowchart.

[0056] Step S102, obtain the operation state 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.

[0057] In this embodiment, the operation state information includes the temperature, power, voltage, pressure, flow rate, etc. of the equipment. The smelting process information includes process parameters such as raw material addition amount, additive dosage, reaction temperature, etc. Defining the fluctuation degree of the smelting equipment means analyzing the operation data of the previous equipment to determine the change degree of each type of operation state information. The raw material output quality of the smelting equipment is jointly determined by the state of the smelting equipment and the smelting process parameters. Analyze the parameter matching situation of these two to evaluate the raw material output quality.

[0058] It can be understood that in the smelting process, it is difficult to detect or experiment on the raw material quality output by each smelting equipment in real time. Therefore, the raw material output quality is evaluated here through the matching situation of the state of the smelting equipment and the smelting process parameters with the target parameter range.

[0059] In some embodiments of the present application, defining the fluctuation degree of the smelting equipment includes,

[0060] Classify the operation status information of each smelting device, construct a numerical dot matrix diagram for each type of operation status information, identify abnormal points and non-abnormal points on the numerical dot matrix diagram, connect the abnormal points and non-abnormal points separately, and perform smoothing processing to obtain an abnormal curve and a non-abnormal curve, and mark the abnormal points and non-abnormal points on the abnormal curve and the non-abnormal curve respectively;

[0061] Uniformly split the abnormal curve and the non-abnormal curve into multiple sub-curves according to their respective lengths, calculate the average slope value of each sub-curve, and integrate the average slope values of all sub-curves to obtain the average slope values of the abnormal curve and the non-abnormal curve respectively;

[0062] Calculate the continuity degree between the numerical points of the abnormal curve and the non-abnormal curve respectively, determine the fluctuation indexes of the abnormal curve and the non-abnormal curve based on the continuity degree and the average slope value, and calculate the coefficient of variation of each type of operation status information through the numerical dot matrix diagram;

[0063] Comprehensively define the fluctuation degree of each type of operation status information of the smelting device based on the fluctuation indexes of the abnormal curve and the non-abnormal curve respectively and the coefficient of variation of the numerical dot matrix diagram, and describe the fluctuation degree of the smelting device by virtue of the fluctuation degrees of all the operation status information of the smelting device.

[0064] In this embodiment, the numerical dot matrix diagram is a scatter plot arranged in chronological order. Connect the abnormal points and non-abnormal points separately to obtain two curves. The fluctuation of the operation status information is jointly composed of the fluctuations of the two curves. The change of each curve is expressed by the average slope value of the sub-curve, and finally the synthesis of the sub-curves is carried out to obtain the change of the abnormal curve and the non-abnormal curve respectively. The continuity degree 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 non-continuous characteristics. The abnormal curve may show obvious trend changes, such as gradually rising or falling. The non-abnormal points usually appear continuously, so the non-abnormal curve shows continuous and smooth characteristics, reflecting the stability of the equipment in the normal operation state. The fluctuation indexes of the respective curves are determined by comprehensively considering the continuity degree and the average slope value, 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 change situations of different operation status information of the smelting device are different.

[0065] In some embodiments of the present application, comprehensively define the fluctuation degree of each type of operation status information of the smelting device based on the fluctuation indexes of the abnormal curve and the non-abnormal curve respectively and the coefficient of variation of the numerical dot matrix diagram, including,

[0066] ;

[0067] Among them, is the degree of fluctuation of the i-th type of operating state information, and are the combined weights of the abnormal curve and the non-abnormal curve respectively, and are the fluctuation indexes of the abnormal curve and the non-abnormal curve respectively, is the coefficient of variation of the i-th type of operating state information, is the constant corresponding to the i-th type of operating state information.

[0068] In this embodiment, represents the sum of the fluctuations of the abnormal curve and the non-abnormal curve corrected by the coefficient of variation (the overall fluctuation of abnormal and non-abnormal points), is a constant set to balance the size of the correction function.

[0069] In some embodiments of the present application, to evaluate the raw material output quality of a smelting device, it includes

[0070] monitoring in real time the actual values of the operating state information and the smelting process information of each smelting device, and comparing the actual values of the operating state information and the smelting process information with the target parameter ranges of the operating state information and the smelting process information to determine the deviation degrees of each type of operating state information and each type of smelting process information;

[0071] quantifying the raw material output quality of each smelting device, constructing a reference sequence according to the raw material output quality, constructing a comparison sequence according to the operating state information and the smelting process information, calculating the absolute difference between the comparison sequence and the reference sequence, generating a difference sequence, determining the degree of dispersion of the difference sequence, determining a resolution coefficient based on the degree of dispersion, and calculating the grey correlation degree between each comparison sequence and the reference sequence through the resolution coefficient;

[0072] Comprehensively evaluating the raw material output quality of each smelting device according to the grey correlation degree, the deviation degrees of each type of operating state information and each type of smelting process information.

[0073] In this embodiment, the raw material output quality is jointly determined by the operating state of the equipment and the smelting process. Here, the raw material output quality is indirectly evaluated through the data of both, and the specific relationship between the influencing factors (operating state information and smelting process information) and the system output (raw material output quality) is calculated through grey relational analysis. Determine the reference sequence (i.e., the ideal value or standard value) of the raw material output quality. This sequence represents the expected raw material output quality level varying with time or batches. For each specific factor (such as temperature, pressure, raw material quantity, etc.), collect the numerical sequence of its variation with time or batches to form multiple comparison sequences. Each comparison sequence represents the deviation of this factor from the expected value at different time points or batches. For each comparison sequence, calculate the absolute difference between it and the reference sequence at the same time point or batch to form an absolute difference sequence (difference sequence).

[0074] In this embodiment, determine the discreteness degree of the difference sequence. If the data discreteness between the comparison sequence and the reference sequence is large, that is, the fluctuation between data points is large, in order to more accurately reflect the subtle differences between data, the value of ρ (resolution coefficient) can be appropriately reduced. A smaller ρ value will make the difference between correlation coefficients more significant, thereby improving the analysis accuracy. After the resolution coefficient is determined, the correlation coefficient is obtained, and then the grey relational degree calculation formula is obtained, so as to accurately calculate the grey relational degree (between the factor and the raw material output quality). The grey relational degree calculation formula and the correlation coefficient formula here are conventional means in this field and will not be given.

[0075] In this embodiment, the grey relational degree shows the strength of the correlation between a certain factor and the output. Then, combined with the deviation degree of each type of operating state information and each type of smelting process information, the raw material output quality of each smelting equipment is comprehensively evaluated.

[0076] Step S103, set the dynamic monitoring baseline of the operating state information of the smelting equipment 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.

[0077] In this embodiment, for multiple smelting equipment in a series relationship, 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 state of the next smelting equipment. The dynamic monitoring baseline of the operating state information is a threshold line of the dynamic operating state information. Within the threshold line, it indicates that the operating state is relatively stable and safe.

[0078] In some embodiments of the present application, setting the dynamic monitoring baseline of the operating state information of the smelting equipment 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 includes,

[0079] The series-parallel relationship between multiple smelting devices includes a series relationship and a parallel relationship;

[0080] For multiple smelting devices in a parallel relationship, the smelting task volume is allocated according to the characteristics of each smelting device, and the operating status information of the smelting device is predicted through 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 device.

[0081] In this embodiment, the smelting task volume is allocated according to the characteristics of each smelting device to ensure the load balance of each smelting device as much as possible. The operating status information of the smelting device can be predicted through time series models such as the ARIMA model and the SARIMA model to set the monitoring baseline.

[0082] In some embodiments of the present application, the dynamic monitoring baseline of the operating status information of the smelting device is set according to the series-parallel relationship between multiple smelting devices, the fluctuation degree of the smelting device, and the raw material output quality of the smelting device. It further includes,

[0083] For multiple smelting devices in a series relationship, the original monitoring baseline of the operating status information of the smelting device is determined, the process sequence between multiple smelting devices is determined according to the series relationship, and the adjustment coefficient is determined by integrating the process sequence, the fluctuation degree of the operating status information of the smelting device, and the raw material output quality;

[0084] ;

[0085] Among them, is the adjustment coefficient of the th operating status information of the th smelting device, is the number of operating status information of the th smelting device, is the combined weight of the th operating status information of the th smelting device, is the fluctuation degree of the th operating status information of the th smelting device, is the fluctuation degree of the th operating status information of the th smelting device, represents the mapping relationship corresponding to the th operating status information, is the adjustment constant of the th operating status information of the th smelting device, is the raw material output quality of the th smelting device, is the corresponding constant for the nth smelting device;

[0086] Adjust the original monitoring baseline of the operation status information according to the adjustment coefficient, so as to set the dynamic monitoring baseline of the operation status information of the smelting device.

[0087] In this embodiment, for multiple smelting devices in series, the fluctuation degree of the raw material output quality and operation status information of the previous smelting device will affect the operation status of the next smelting device. Therefore, consider the above factors to determine the adjustment coefficient for the original monitoring baseline, and this original monitoring baseline can be the initial threshold jointly determined by the device situation and process situation. Represents the correction of the adjustment constant for the sum of all operation status information of the previous smelting device and a certain operation status information of the next smelting device by the raw material output quality of the previous smelting device. There is an adjustment constant mapped to the sum of all operation status information of the previous smelting device and a certain operation status information of the next smelting device. is a constant for balancing the size of the correction function. Adjust the original monitoring baseline of the operation status information according to the adjustment coefficient, and the adjustment method can be the way of adjustment coefficient * original monitoring baseline.

[0088] Step S104, monitor the smelting device by virtue of the relationship between the actual value of the operation status information of the smelting device and the dynamic monitoring baseline.

[0089] In this embodiment, compare the actual value according to a preset period, and set the dynamic monitoring baseline. By comparing the deviation between the two, monitor the status of the smelting device.

[0090] In some embodiments of the present application, monitor the smelting device by virtue of the relationship between the actual value of the operation status information of the smelting device and the dynamic monitoring baseline, including

[0091] Regularly collect the actual value of the operation status information and calculate the dynamic monitoring baseline of the operation status information according to the monitoring period of each smelting device, and determine the timestamps of the actual value of the operation status information and the dynamic monitoring baseline respectively. Align the actual value of the operation status information and the dynamic monitoring baseline in terms of time, compare and obtain the part where the actual value of the operation status information deviates outside the dynamic monitoring baseline and the part where the actual value of the operation status information belongs to within the dynamic monitoring baseline, and comprehensively monitor the operation status of the smelting device by combining the two parts.

[0092] In this embodiment, monitor the operation status of the smelting device by combining the part where the actual value deviates outside the dynamic monitoring baseline (operation non - reasonable part) and the part where the actual value belongs to within the dynamic monitoring baseline (operation reasonable part).

[0093] Correspondingly, the present application also provides a smelting equipment monitoring system based on operation data analysis, as Figure 2 shown, including

[0094] A determination module, configured to collect smelting process tasks, determine a smelting process according to the smelting process tasks, where the smelting process includes multiple smelting devices and the series-parallel relationships between the multiple smelting devices;

[0095] An evaluation module, configured to obtain the operation status information and smelting process information of each smelting device, define the fluctuation degree of the smelting device, and evaluate the raw material output quality of the smelting device;

[0096] A setting module, configured to set a dynamic monitoring baseline for the operation status information of the smelting device according to the series-parallel relationships between the multiple smelting devices, the fluctuation degree of the smelting device, and the raw material output quality of the smelting device;

[0097] A monitoring module, configured to implement the monitoring of the smelting device based on the relationship between the actual value of the operation status information of the smelting device and the dynamic monitoring baseline.

[0098] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0099] 1. Determine the smelting process according to the smelting process tasks, so as to determine the process sequence, series-parallel relationships, and process task-related content between the smelting devices, providing a reliable basis for setting the dynamic monitoring baseline of the subsequent smelting devices.

[0100] 2. Define the fluctuation degree of the smelting device, evaluate the raw material output quality of the smelting device, consider the fluctuation of each operation status information of the device and the raw material output of the device, so as to set the dynamic monitoring baseline of the operation status information of the smelting device, improving the adaptability and accuracy of the monitoring baseline, ensuring the working safety and efficient production of the smelting device, and providing an excellent production basis for smelting production.

[0101] Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented by hardware or by means of 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 several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various implementation scenarios of the present invention.

[0102] Those skilled in the art can understand that the drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the drawings are not necessarily essential for implementing the present invention.

[0103] Those skilled in the art can understand that the modules in the system in the implementation scenario can be distributed in the system of the implementation scenario according to the description of the implementation scenario, or can be correspondingly changed and located in one or more systems different from this implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple sub-modules.

[0104] As mentioned above, it is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered within the protection scope of the present invention.

Claims

1. A smelting equipment monitoring method based on operating data analysis, characterized in that including collecting smelting process tasks, determining a smelting process according to the smelting process tasks, where the smelting process includes multiple smelting devices and the series-parallel relationships between the multiple smelting devices; obtaining the operating status information and smelting process information of each smelting device, defining the degree of fluctuation of the smelting device, and evaluating the raw material output quality of the smelting device; setting a dynamic monitoring baseline for the operating status information of the smelting device according to the series-parallel relationships between the multiple smelting devices, the degree of fluctuation of the smelting device, and the raw material output quality of the smelting device; realizing the monitoring of the smelting device based on the relationship between the actual value of the operating status information of the smelting device and the dynamic monitoring baseline; wherein defining the degree of fluctuation of the smelting device includes classifying the operating status information of each smelting device, constructing a numerical dot matrix diagram for each type of operating status information, identifying abnormal points and non-abnormal points on the numerical dot matrix diagram, connecting the abnormal points and non-abnormal points respectively, and performing smoothing processing to obtain an abnormal curve and a non-abnormal curve, and marking the abnormal points and non-abnormal points on the abnormal curve and the non-abnormal curve respectively; uniformly splitting the abnormal curve and the non-abnormal curve into multiple sub-curves according to the respective lengths of the abnormal curve and the non-abnormal curve, calculating the average slope value of each sub-curve, and integrating the average slope values of all sub-curves to obtain the average slope values of the abnormal curve and the non-abnormal curve respectively; respectively calculating the continuity degree between the numerical points of the abnormal curve and the non-abnormal curve, determining the fluctuation indexes of the abnormal curve and the non-abnormal curve respectively based on the continuity degree and the average slope value, and calculating the coefficient of variation of each type of operating status information through the numerical dot matrix diagram; defining the degree of fluctuation of each type of operating status information of the smelting device by integrating the fluctuation indexes of the abnormal curve and the non-abnormal curve respectively and the coefficient of variation of the numerical dot matrix diagram, and describing the degree of fluctuation of the smelting device by virtue of the degree of fluctuation of all the operating status information of the smelting device; determining the smelting process according to the smelting process tasks includes the smelting process tasks include smelting process content and smelting task content, and the smelting task content includes smelting product information, smelting raw material information, and process requirement information; identifying all the basic information of the smelting devices in the smelting process content, dividing the smelting process content into multiple process steps in units of smelting devices, and formulating the target parameter ranges of the operating status information and the smelting process information involved in each process step according to the smelting product information, the smelting raw material information, and the process requirement information; identifying the series-parallel relationships between the process steps through the process steps, and drawing a corresponding flow chart to reflect the process steps and the series-parallel relationships between the process steps, so as to form and determine the smelting process; setting a dynamic monitoring baseline for the operating status information of the smelting device according to the series-parallel relationships between the multiple smelting devices, the degree of fluctuation of the smelting device, and the raw material output quality of the smelting device includes the series-parallel relationships between the multiple smelting devices include series relationships and parallel relationships; For multiple smelting devices in a parallel relationship, allocate the smelting task volume according to the characteristics of each smelting device, and predict the operating status information of the smelting device 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 device; Set the dynamic monitoring baseline of the operating status information of the smelting device according to the series-parallel relationship between multiple smelting devices, the fluctuation degree of the smelting device, and the raw material output quality of the smelting device. It also includes, For multiple smelting devices in a series relationship, determine the original monitoring baseline of the operating status information of the smelting device, determine the process sequence between multiple smelting devices according to the series relationship, and determine the adjustment coefficient by integrating the process sequence, the fluctuation degree of the operating status information of the smelting device, and the raw material output quality; ； Among them, is the adjustment coefficient of the th operating status information of the th smelting equipment, is the quantity of the operating status information of the th smelting equipment, is the combination weight of the th operating status information of the th smelting equipment, is the fluctuation degree of the th operating status information of the th smelting equipment, is the fluctuation degree of the th operating status information of the th smelting equipment, represents the mapping relationship corresponding to the th operating status information, is the adjustment constant of the th operating status information of the th smelting equipment, is the raw material output quality of the th smelting equipment, is the corresponding constant of the th smelting equipment; Adjust the original monitoring baseline of the operating status information according to the adjustment coefficient, so as to set the dynamic monitoring baseline of the operating status information of the smelting device.

2. The monitoring method for smelting equipment based on operation data analysis according to claim 1, characterized in that, Define the fluctuation degree of each type of operating status information of the smelting device by integrating the fluctuation indicators of the abnormal curve and the non-abnormal curve respectively and the coefficient of variation of the numerical dot matrix diagram, including, ； Among them, is the fluctuation degree of the type of running state information, , are the combination weights of the abnormal curve and the non-abnormal curve respectively, , are the fluctuation indexes of the abnormal curve and the non-abnormal curve respectively, is the coefficient of variation of the type of running state information, is the constant corresponding to the type of running state information.

3. The smelting equipment monitoring method based on operation data analysis according to claim 1, wherein Evaluate the raw material output quality of the smelting device, including, Real-time monitor the actual values of the operating status information and smelting process information of each smelting device, and compare the actual values of the operating status information and smelting process information with the target parameter ranges of the operating status information and smelting process information to determine the deviation degree of each type of operating status information and each type of smelting process information; Quantify the raw material output quality of each smelting device, construct a reference sequence according to the raw material output quality, construct a comparison sequence according to the operating status information and smelting process information, calculate the absolute difference between the comparison sequence and the reference sequence, generate a difference sequence, determine the dispersion degree of the difference sequence, determine the resolution coefficient based on the dispersion degree, and calculate the grey correlation degree between each comparison sequence and the reference sequence through the resolution coefficient; Comprehensively evaluate the raw material output quality of each smelting device according to the grey correlation degree, the deviation degree of each type of operating status information, and each type of smelting process information.

4. The method for monitoring a smelting device based on operating data analysis according to claim 1, wherein Realize the monitoring of the smelting device by virtue of the relationship between the actual value of the operating status information of the smelting device and the dynamic monitoring baseline, including, Regularly collect the actual value of the operating status information and calculate the dynamic monitoring baseline of the operating status information according to the monitoring period of each smelting device, determine the timestamps of the actual value of the operating status information and the dynamic monitoring baseline respectively, align the actual value of the operating status information and the dynamic monitoring baseline in time, compare and obtain the part where the actual value of the operating status information deviates outside the dynamic monitoring baseline and the part where the actual value of the operating status information belongs within the dynamic monitoring baseline, and comprehensively monitor the operating status of the smelting device based on the two parts.

5. A smelting equipment monitoring system based on operating data analysis, characterized in that, For implementing the smelting device monitoring method based on operation data analysis as described in any one of claims 1-4, the system includes, A determination module, configured to collect smelting process tasks, determine the smelting process according to the smelting process tasks, where the smelting process includes multiple smelting devices and the series-parallel relationship between multiple smelting devices; An evaluation module, configured to obtain the operation status information and smelting process information of each smelting device, define the fluctuation degree of the smelting device, and evaluate the raw material output quality of the smelting device; A setting module, configured to set a dynamic monitoring baseline for the operation status information of the smelting device according to the series-parallel relationship between multiple smelting devices, the fluctuation degree of the smelting device, and the raw material output quality of the smelting device; A monitoring module, configured to monitor the smelting device based on the relationship between the actual value of the operation status information of the smelting device and the dynamic monitoring baseline.

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