CN118278900A - Whole-flow integrated control system and method for rare earth smelting production and manufacturing - Google Patents

Whole-flow integrated control system and method for rare earth smelting production and manufacturing Download PDF

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CN118278900A
CN118278900A CN202410707749.3A CN202410707749A CN118278900A CN 118278900 A CN118278900 A CN 118278900A CN 202410707749 A CN202410707749 A CN 202410707749A CN 118278900 A CN118278900 A CN 118278900A
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value
time
processing equipment
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苏横军
徐芳萍
苏灿
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Nanchang Lingxing Information Technology Co ltd
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Nanchang Lingxing Information Technology Co ltd
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract

The invention is suitable for the technical field of production control, and particularly relates to a full-flow integrated control system and method for rare earth smelting production, wherein the method comprises the following steps: constructing a virtual production line model based on the sequence of rare earth smelting manufacturing equipment; acquiring material data in the stage processing equipment, recording the material data according to a time sequence, and determining a material change record; generating material change parameter coordinates, and performing function fitting to obtain a material change function; predicting the material consumption to obtain predicted material consumption data, and performing visual processing on the virtual production line model based on the predicted material consumption data to generate a visual result. According to the invention, the virtual production line model is rendered based on the estimated result, the visual result is output, the working state of the production line can be intuitively displayed through the visual result, the material supervision of processing equipment at each stage is better realized, and the production efficiency is ensured.

Description

Whole-flow integrated control system and method for rare earth smelting production and manufacturing
Technical Field
The invention belongs to the technical field of production control, and particularly relates to a full-flow integrated control system and method for rare earth smelting production.
Background
Rare earth smelting refers to the process of extracting, separating and purifying rare earth elements from rare earth ores, and because the rare earth elements coexist in nature and have similar properties, the smelting and refining processes are very complex. The rare earth smelting mainly comprises two methods: hydrometallurgy and pyrometallurgy.
In the current rare earth smelting production manufacturing process, data parameters are usually collected independently, each control flow is completed independently, visual automatic control on the material capacity in production equipment cannot be achieved, and production staff cannot effectively manage and control the material capacity.
Disclosure of Invention
The invention aims to provide a full-flow integrated control method for rare earth smelting production and manufacturing, and aims to solve the problem that in the existing production process, the material capacity in production equipment cannot be visually and automatically controlled, and production staff cannot effectively control the material capacity.
The invention is realized in such a way that the whole flow integrated control method for rare earth smelting production comprises the following steps:
Based on the sequence of rare earth smelting manufacturing equipment, constructing a virtual production line model, wherein the virtual production line model consists of different stages of processing equipment, and all stages of processing equipment are provided with material detection sensors;
acquiring material data in the stage processing equipment, recording the material data according to a time sequence, and determining a material change record corresponding to each stage processing equipment;
Generating material change parameter coordinates corresponding to each stage of processing equipment based on the material change records, and performing function fitting based on the material parameter coordinates to obtain a material change function;
predicting the material consumption based on the material change function to obtain predicted material consumption data, and performing visual processing on the virtual production line model based on the predicted material consumption data to generate a visual result.
Preferably, the step of acquiring material data in the stage processing equipment, recording the material data according to a time sequence, and determining a material change record corresponding to each stage processing equipment specifically includes:
Dynamically acquiring material data in the stage processing equipment according to a preset time interval;
Constructing a two-dimensional coordinate system, carrying out segmentation processing on the two-dimensional coordinate system based on data acquisition intervals, and determining reference lines corresponding to all moments;
And marking the numerical value of the corresponding material data in a two-dimensional coordinate system based on the material data corresponding to each moment to obtain the material change record of the single-stage processing equipment.
Preferably, the step of generating the material change parameter coordinates corresponding to the processing equipment at each stage based on the material change record, and performing function fitting based on the material parameter coordinates to obtain a material change function specifically includes:
Extracting a time value and a corresponding material residual value from a material change record according to a preset data reading interval, and constructing to obtain a material change parameter coordinate, wherein the abscissa of the material change parameter coordinate is the time value, and the ordinate of the material change parameter coordinate is the material residual value;
calling a preset function fitting type table, and performing function fitting based on the function fitting type table to obtain a plurality of groups of function fitting results;
And retrieving the material change record again to obtain verification data, verifying the precision of fitting results of the functions based on the verification data, and selecting a material change function with highest precision.
Preferably, the step of predicting the material usage based on the material change function to obtain predicted material usage data, and performing visualization processing on the virtual production line model based on the predicted material usage data to generate a visualization result specifically includes:
generating time gradient data based on a preset prediction gradient, substituting the time gradient data into a material change function, and obtaining predicted material consumption data;
Determining a first model color value based on the currently detected material remainder value and a second model color value based on the predicted material usage data;
and coloring the virtual production line model based on the first model color value and the second model color value to generate a visual result, and generating a material consumption estimated report based on the predicted material consumption data.
Preferably, before the step of constructing the virtual production line model based on the sequence of the rare earth smelting manufacturing equipment, the method further comprises the steps of detecting the components and the content of materials, setting an automatic control strategy for the stage processing equipment, performing process simulation based on the production processing process and generating a visual animation, and after the step of generating a visual result, constructing a big data cloud platform, and performing data statistics and analysis through the big data cloud platform, wherein the big data cloud platform comprises an intelligent control module, a roaming module, a production management module, an enterprise module, an equipment management module and a system early warning module.
Another object of the present invention is to provide a full-flow integrated control system for rare earth smelting production, the system comprising:
The model construction module is used for constructing a virtual production line model based on the sequence of rare earth smelting manufacturing equipment, wherein the virtual production line model consists of different stages of processing equipment, and all stages of processing equipment are provided with material detection sensors;
the data recording module is used for acquiring material data in the stage processing equipment, recording the material data according to a time sequence and determining a material change record corresponding to each stage processing equipment;
The function fitting module is used for generating material change parameter coordinates corresponding to the processing equipment at each stage based on the material change records, and performing function fitting based on the material parameter coordinates to obtain a material change function;
And the visualization module is used for predicting the material consumption based on the material change function to obtain predicted material consumption data, and performing visualization processing on the virtual production line model based on the predicted material consumption data to generate a visualization result.
Preferably, the data recording module includes:
The material data extraction unit is used for dynamically acquiring material data in the stage processing equipment according to a preset time interval;
The coordinate system construction unit is used for constructing a two-dimensional coordinate system, carrying out segmentation processing on the two-dimensional coordinate system based on the data acquisition interval, and determining a reference line corresponding to each moment;
And the recording and marking unit is used for marking the numerical value of the corresponding material data in a two-dimensional coordinate system based on the material data corresponding to each moment to obtain the material change record of the single-stage processing equipment.
Preferably, the function fitting module includes:
The parameter coordinate construction unit is used for extracting a time value and a corresponding material residual value from the material change record according to a preset data reading interval, constructing and obtaining a material change parameter coordinate, wherein the abscissa of the material change parameter coordinate is the time value, and the ordinate of the material change parameter coordinate is the material residual value;
the data fitting unit is used for calling a preset function fitting type table, and performing function fitting based on the function fitting type table to obtain a plurality of groups of function fitting results;
And the function screening unit is used for recalling the material change records to obtain verification data, verifying the precision of each function fitting result based on the verification data, and selecting the material change function with the highest precision.
Preferably, the visualization module includes:
The material consumption prediction unit is used for generating time gradient data based on a preset prediction gradient, substituting the time gradient data into a material change function to obtain predicted material consumption data;
a color value calculation unit for determining a first model color value based on the currently detected material residual value and a second model color value based on the predicted material usage data;
and the model processing unit is used for coloring the virtual production line model based on the first model color value and the second model color value, generating a visual result and generating a material consumption estimated report based on the predicted material consumption data.
Preferably, before the step of constructing the virtual production line model based on the sequence of the rare earth smelting manufacturing equipment, the method further comprises the steps of detecting the components and the content of materials, setting an automatic control strategy for the stage processing equipment, performing process simulation based on the production processing process and generating a visual animation, and after the step of generating a visual result, constructing a big data cloud platform, and performing data statistics and analysis through the big data cloud platform, wherein the big data cloud platform comprises an intelligent control module, a roaming module, a production management module, an enterprise module, an equipment management module and a system early warning module.
According to the full-flow integrated control method for rare earth smelting production, provided by the invention, the material change condition in each stage of processing equipment is determined by monitoring the material consumption of each equipment in the full production period of rare earth smelting, so that the material consumption is estimated according to the material change quantity, a virtual production line model is rendered based on the estimated result, a visual result is output, the working state of the production line can be intuitively displayed through the visual result, the material supervision of each stage of processing equipment is better realized, and the production efficiency is ensured.
Drawings
FIG. 1 is a flow chart of a full-flow integrated control method for rare earth smelting production, provided by an embodiment of the invention;
FIG. 2 is a flowchart of steps involved in a method for determining a record of material changes corresponding to each stage of processing equipment according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating steps involved in a method for determining a material variation function according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating steps involved in a method for generating a report of estimated material usage according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an integrated control system for the whole flow of rare earth smelting production provided by the embodiment of the invention;
FIG. 6 is a block diagram of a data recording module according to an embodiment of the present invention;
FIG. 7 is a block diagram of a function fitting module according to an embodiment of the present invention;
Fig. 8 is a schematic diagram of a visualization module according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
It will be understood that the terms "first," "second," and the like, as used herein, may be used to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another element. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script, without departing from the scope of this disclosure.
As shown in fig. 1, a flowchart of a full-process integrated control method for rare earth smelting production and manufacturing is provided in an embodiment of the present invention, where the method includes:
S100, constructing a virtual production line model based on the sequence of rare earth smelting manufacturing equipment, wherein the virtual production line model consists of different stages of processing equipment, and all stages of processing equipment are provided with material detection sensors.
In the step, a virtual production line model is built based on the sequence of rare earth smelting manufacturing equipment, a plurality of production equipment are used in the rare earth smelting manufacturing process, a corresponding three-dimensional model is built, each production equipment is one stage of processing equipment, each stage of processing equipment is responsible for one processing link, the virtual production line model can be obtained after the modeling is completed, and the sequence of each stage of processing equipment is recorded in the virtual production line model.
And S200, acquiring material data in the stage processing equipment, recording the material data according to a time sequence, and determining a material change record corresponding to each stage processing equipment.
In the step, material data in the stage processing equipment are acquired, in the production process, the material sensors arranged in the stage processing equipment are utilized to determine the residual quantity of materials in the stage processing equipment, namely the material data, when the sensor data are read, a plurality of material change records are obtained according to preset time intervals, in the material change records, different material residual quantity values are read at different times until the recorded material data quantity reaches the preset quantity, namely the monitoring of material change is stopped.
S300, generating material change parameter coordinates corresponding to each stage of processing equipment based on the material change records, and performing function fitting based on the material parameter coordinates to obtain a material change function.
In the step, a material change parameter coordinate corresponding to each stage of processing equipment is generated based on a material change record, in order to realize continuous monitoring of materials in each stage of processing equipment and prediction of material change, the change of the materials in future time is determined by analyzing data, then function fitting is performed by constructing the material change parameter coordinate, the material change parameter coordinate is generated according to the acquired material remainder value, the abscissa of the material change parameter coordinate is a time value, the ordinate of the material change parameter coordinate is the material remainder value corresponding to the time value, the material change parameter coordinate is obtained, a material change function is obtained by performing function fitting, and the independent variable in the material change function is the time value, and then the future time value is substituted, so that the material value prediction in a short time can be realized.
S400, predicting the material consumption based on the material change function to obtain predicted material consumption data, and performing visualization processing on the virtual production line model based on the predicted material consumption data to generate a visualization result.
In the step, the material consumption is predicted based on a material change function, the time period to be predicted is divided according to the time period to be predicted, the time period is divided into a plurality of intervals through a plurality of time nodes, the time length between adjacent time nodes is the same, the time value corresponding to the time node is substituted into the material change function, the material prediction quantity in the processing equipment at the corresponding stage can be predicted and obtained when the time node is obtained, namely the predicted material consumption data, then the material value detected in real time is marked by a first color detection through visual processing, the future predicted material consumption is marked by a second color, the change trend of the material in a short time can be directly seen, the preparation of the material is facilitated for production staff, the early warning of the material change can be completed based on the predicted material consumption data, and the warning is carried out when the material change exceeds a preset range.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of acquiring material data in the stage processing apparatus, recording the material data according to a time sequence, and determining a material change record corresponding to each stage processing apparatus specifically includes:
s201, material data in the stage processing equipment are dynamically acquired according to a preset time interval.
In this step, the material data in the processing equipment in the stage is dynamically acquired according to a preset time interval, and in order to dynamically acquire the amount and the allowance of the material, a period of time is required to be used for acquisition, for example, data acquisition is performed every 10 seconds, so as to obtain the material data at the moment, the time interval can be modified according to the change speed of the material, and the faster the material changes, the shorter the time interval.
S202, constructing a two-dimensional coordinate system, carrying out segmentation processing on the two-dimensional coordinate system based on data acquisition intervals, and determining reference lines corresponding to all moments.
In step S202, in the two-dimensional coordinate system, the firstReference lines corresponding to the data acquisition moments are in a two-dimensional coordinate systemThe coordinate values correspond to the following formulas:
；
Wherein, Represent the firstReference lines corresponding to data acquisition moments in two-dimensional coordinate systemThe coordinate value of the axis,Representing the time interval of the data acquisition,Representing the absolute point in time of the current data acquisition,Representing the absolute point in time of the first data acquisition,Representing in a two-dimensional coordinate systemThe maximum scale value of the shaft,Representing in a two-dimensional coordinate systemMinimum scale value of the shaft.
In particular, for a two-dimensional coordinate system,Each point or scale on the axis may represent a particular point in time for data acquisition. For example, if the time interval of data acquisition is fixed, thenEquidistant graduations on the axis can represent the time of each data acquisition. In practical application, the device can be adjusted according to the needsThe scale density of the shaft is used for clearly showing the change condition of material data along with time.
And S203, marking the numerical value of the corresponding material data in a two-dimensional coordinate system based on the material data corresponding to each moment, and obtaining the material change record of the single-stage processing equipment.
In the step of marking the numerical value of the corresponding material data in the two-dimensional coordinate system, the coordinates of the marking point in the two-dimensional coordinate system are expressed as follows:
；
Wherein, Representing marked points in a two-dimensional coordinate systemThe axis of the rotation is set to be at the same position,Representing marked points in a two-dimensional coordinate systemThe axis of the rotation is set to be at the same position,Represent the firstThe time of the data acquisition is the same,Represent the firstMaterial data values acquired at the moment of data acquisition,Representing in a two-dimensional coordinate systemThe maximum value of the axis is,Representing in a two-dimensional coordinate systemThe minimum value of the axis is set to,Representing the maximum value in the acquired material data,Representing the minimum value in the collected material data,Representing an adjustment parameter for controlling the data point inDistribution on the axis.
It should be added here that whenAt the time, the data point isThe distribution on the axis is linear; when (when)Data points will tend to be more distributed in timeThe upper end of the shaft; when (when)Data points will tend to be more distributed in timeThe lower end of the shaft.
In the step, a two-dimensional coordinate system is constructed, wherein the abscissa axis is a time value, the ordinate axis is a material residual value, corresponding data are extracted according to the sequence of data acquisition, the material residual value detected at the corresponding moment is marked in the two-dimensional coordinate system according to the time value, then a plurality of points are marked in the two-dimensional coordinate system, and marked points in the two-dimensional coordinate system can be connected through a smooth curve to obtain a material change trend curve.
As shown in fig. 3, as a preferred embodiment of the present invention, the step of generating the material variation parameter coordinates corresponding to each stage of processing equipment based on the material variation record, and performing function fitting based on the material parameter coordinates to obtain a material variation function specifically includes:
s301, extracting a time value and a corresponding material residual value from a material change record according to a preset data reading interval, and constructing to obtain a material change parameter coordinate, wherein the abscissa of the material change parameter coordinate is the time value, and the ordinate of the material change parameter coordinate is the material residual value.
In this step, a time value and a corresponding material Yu Liangzhi are extracted from a material change record according to a preset data reading interval, in this step, the data reading interval may be the same as or different from the time interval during data acquisition, the specific data reading interval is not the same as the time interval during data acquisition, the time value during data acquisition is not the same as the time value during data reading, and a material change parameter coordinate is constructed and obtained, wherein the abscissa of the material change parameter coordinate is the time value, and the ordinate of the material change parameter coordinate is a material residual value.
S302, a preset function fitting type table is called, and function fitting is conducted based on the function fitting type table, so that a plurality of groups of function fitting results are obtained.
In step S302, the function fitting formula corresponding to the function fitting type table is expressed as:
；
Wherein, Is shown at the momentThe material balance of the furnace is equal to the total material balance,All of which represent parameters that need to be fitted,Representing a time value.
It should be noted here that,Representing a nonlinear variation trend of material allowance along with time, and parametersControlling the amplitude of the variation, while the parametersThe rate of change is controlled. When (when)When the material allowance is increased with time, the material allowance is increased; when (when)And when the material allowance is reduced with time.The term is a sinusoidal wave term that simulates the periodic variation that may exist in the material balance. Parameters (parameters)Controlling the amplitude, parameters of the fluctuationControlling the frequency of the wave motion, while the parameterThe phase of the ripple is controlled.Is a constant term representing the base level of material balance.
In this step, a preset function fitting type table is called, in which a plurality of types of functions are recorded, and each function type is fitted based on the material change parameter coordinates, so that a plurality of function fitting results are obtained.
S303, retrieving the material change record again to obtain verification data, verifying the accuracy of fitting results of the functions based on the verification data, and selecting a material change function with highest accuracy.
In the step, the material change record is recalled, a plurality of function fitting results are obtained through fitting, but only a small amount of data is used when the function fitting is carried out, verification data are again extracted for further determining the precision of each function fitting result, verification coordinates are also constructed and obtained, the verification coordinates are substituted into all function fitting results, screening is carried out according to the fitting precision, and the material change function with the highest precision is selected.
As shown in fig. 4, as a preferred embodiment of the present invention, the step of predicting the material usage based on the material change function to obtain predicted material usage data, and performing visualization processing on the virtual production line model based on the predicted material usage data to generate a visualization result specifically includes:
S401, generating time gradient data based on a preset prediction gradient, and substituting the time gradient data into a material change function to obtain predicted material consumption data.
In step S401, the formula corresponding to the predicted material usage data is:
；
Wherein, Expressed in timeThe material consumption is predicted in the process,Indicating the residual quantity of the initial material,All of which represent parameters that need to be fitted,The current point in time is indicated and,The previous point in time is indicated and,Indicating the corresponding amount of material at the current point in time,Indicating the amount of material corresponding to the previous time point.
It should be noted here that,Expressed in timeTime to dateA change in material usage due to a nonlinear change in time; Expressed in time Time to dateAnd the material consumption changes due to periodic fluctuation.
In this step, time gradient data is generated based on a preset prediction gradient, and the smaller the prediction gradient, the finer the prediction result to be obtained is, for example, one second is taken as a prediction gradient, more time gradient data will be generated, if two seconds are taken as the prediction gradient, the gradient time data will be reduced to half of the original time, and the corresponding predicted material consumption data will be correspondingly reduced.
S402, determining a first model color value based on the currently detected material residual value, and determining a second model color value based on the predicted material usage data.
In step S402, the calculation formula of the first model color value is expressed as:
；
Wherein, A color value of the first model is represented,Representing the value of the remainder of the material currently detected,Representing the maximum value of the material allowance; A downward rounding symbol is indicated to indicate that the largest integer is taken that is no greater than the value in brackets.
The calculation formula of the color value of the second model is expressed as:
；
Wherein, Representing a color value of a second model,The predicted material consumption is indicated,Representing the minimum value of the material balance.
It should be noted that, for the second model color value, a color intensity or brightness value mapped according to the amount of change in the amount of material is represented, and this value is used in the visualization to represent the difference or change between the predicted amount of material and the current amount of material. In addition, the multiplication operation of x 255 maps the normalized ratio into an integer range of 0 to 255 to match the 8-bit intensity value representing the color in the computer graph.
In this step, a first model color value is determined based on the currently detected material residual value, specifically, the material residual value obtained by real-time detection is represented by blue, and the material residual value is subtracted from the material predicted value recorded in the predicted material usage data to obtain a change value, where the change value is marked with a second model color value, and may be green.
S403, coloring the virtual production line model based on the first model color value and the second model color value, generating a visual result, and generating a material consumption estimated report based on the predicted material consumption data.
In the step, a virtual production line model is colored based on a first model color value and a second model color value, the actual value of a current material and the change value of the material in future time can be intuitively seen according to the first model color value and the second model color value, and when the change value of the material exceeds a preset range, a manager is prompted by marking through a third model color value, and meanwhile, a material consumption estimated report is generated to early warn the change of the material; in the production process, automatic control is carried out according to the predicted material consumption data in the processing equipment at each stage, and the feeding of materials is controlled.
In the embodiment of the invention, before the step of constructing the virtual production line model based on the sequence of the rare earth smelting manufacturing equipment, the method further comprises the steps of detecting the components and the content of materials, setting an automatic control strategy for the stage processing equipment, performing process simulation based on the production processing process and generating a visual animation, and after the step of generating a visual result, constructing a big data cloud platform, and performing data statistics and analysis through the big data cloud platform, wherein the big data cloud platform comprises an intelligent control module, a roaming module, a production management module, an enterprise module, an equipment management module and a system early warning module.
As shown in fig. 5, an architecture diagram of a full-flow integrated control system for rare earth smelting production and manufacturing provided by an embodiment of the present invention includes:
the model construction module 100 is configured to construct a virtual production line model based on the sequence of rare earth smelting manufacturing equipment, where the virtual production line model is composed of different stage processing equipment, and all stage processing equipment are provided with material detection sensors.
In the system, the model construction module 100 constructs a virtual production line model based on the sequence of rare earth smelting manufacturing equipment, and in the rare earth smelting manufacturing process, multiple production equipment are used to construct a corresponding three-dimensional model, each production equipment is a stage processing equipment, each stage processing equipment is responsible for a processing link, after the modeling is completed, the virtual production line model can be obtained, and the sequence of each stage processing equipment is recorded in the virtual production line model.
The data recording module 200 is configured to acquire material data in the stage processing equipment, record the material data according to a time sequence, and determine a material change record corresponding to each stage processing equipment.
In the system, the data recording module 200 acquires material data in the stage processing equipment, in the production process, the material sensors arranged in the stage processing equipment are utilized to determine the residual quantity of materials in the stage processing equipment, namely the material data, when the sensor data is read, the material data are read according to preset time intervals, a plurality of material change records are obtained, in the material change records, different material residual quantity values are read at different times until the obtained material data quantity reaches the preset quantity, namely the monitoring of material change is stopped.
The function fitting module 300 is configured to generate material variation parameter coordinates corresponding to each stage of processing equipment based on the material variation record, and perform function fitting based on the material parameter coordinates to obtain a material variation function.
In the system, the function fitting module 300 generates a material change parameter coordinate corresponding to each stage of processing equipment based on a material change record, in order to realize continuous monitoring of materials in each stage of processing equipment and prediction of material change, the change of the materials in future time is determined by analyzing data, then function fitting is performed by constructing the material change parameter coordinate, the material change parameter coordinate is generated according to the acquired material remainder value, the abscissa of the material change parameter coordinate is a time value, the ordinate is the material remainder value corresponding to the time value, the material change parameter coordinate is obtained, a material change function is obtained by performing function fitting, the independent variable in the material change function is the time value, and then the future time value is substituted, so that the material value prediction in a short time can be realized.
And the visualization module 400 is used for predicting the material consumption based on the material change function to obtain predicted material consumption data, and performing visualization processing on the virtual production line model based on the predicted material consumption data to generate a visualization result.
In the system, the visualization module 400 predicts the material consumption based on a material change function, segments the time period to be predicted according to the time period to be predicted, divides the time period into a plurality of intervals through a plurality of time nodes, substitutes the time value corresponding to the time node into the material change function, and predicts the material prediction amount in the processing equipment at the corresponding stage when the time node is obtained, namely, the predicted material consumption data, then the visualized processing is performed, the material value detected in real time is marked by the first color detection, the future predicted material consumption is marked by the second color, thus the change trend of the material in a short time can be directly seen, the preparation of the material is facilitated for production personnel, the early warning of the material change can be completed based on the predicted material consumption data, and the warning is performed when the material change exceeds the preset range.
As shown in fig. 6, as a preferred embodiment of the present invention, the data recording module 200 includes:
The material data extraction unit 201 is configured to dynamically acquire material data in the stage processing equipment according to a preset time interval.
In this module, the material data extraction unit 201 dynamically obtains the material data in the processing device according to a preset time interval, so that in order to dynamically obtain the usage amount and the allowance of the material, it needs to perform data acquisition at intervals of a period of time, for example, data acquisition is performed every 10 seconds to obtain the material data at the moment, the time interval can be modified according to the change speed of the material, and the faster the material changes, the shorter the time interval.
The coordinate system construction unit 202 is configured to construct a two-dimensional coordinate system, segment the two-dimensional coordinate system based on the data acquisition interval, and determine a reference line corresponding to each moment.
The recording and marking unit 203 is configured to mark the numerical value of the material data in a two-dimensional coordinate system based on the material data corresponding to each moment, and obtain a material change record of the single-stage processing device.
In the module, a two-dimensional coordinate system is constructed, wherein the abscissa axis is a time value, the ordinate axis is a material residual value, corresponding data are extracted according to the sequence of data acquisition, the material residual value detected at the corresponding moment is marked in the two-dimensional coordinate system according to the time value, then a plurality of points are marked in the two-dimensional coordinate system, and marked points in the two-dimensional coordinate system can be connected through a smooth curve to obtain a material change trend curve.
As shown in fig. 7, as a preferred embodiment of the present invention, the function fitting module 300 includes:
The parameter coordinate construction unit 301 is configured to extract a time value and a corresponding material residual value from the material change record according to a preset data reading interval, and construct a material change parameter coordinate, where an abscissa of the material change parameter coordinate is the time value, and an ordinate of the material change parameter coordinate is the material residual value.
In this module, the parameter coordinate construction unit 301 extracts a time value and a corresponding material Yu Liangzhi from a material change record according to a preset data reading interval, in this step, the data reading interval may be the same as or different from the time interval when data is acquired, the specific data reading interval is not the same as the time interval when data is acquired, the time value when data is acquired is not the same as the time value when data is acquired, and a material change parameter coordinate is constructed, where the abscissa of the material change parameter coordinate is the time value, and the ordinate is a material residual value.
The data fitting unit 302 is configured to call a preset function fitting type table, perform function fitting based on the function fitting type table, and obtain a plurality of groups of function fitting results.
In this module, the data fitting unit 302 invokes a preset function fitting type table, in which a plurality of types of functions are recorded, and fits each function type based on the coordinates of the material variation parameters, so as to obtain a plurality of function fitting results.
And the function screening unit 303 is configured to recall the material change record to obtain verification data, verify the accuracy of the fitting result of each function based on the verification data, and select the material change function with the highest accuracy.
In this module, the function screening unit 303 recalls the material change records, and although the fitting obtains a plurality of function fitting results, only a small amount of data is used when performing the function fitting, in order to further determine the accuracy of each function fitting result, verification data is extracted again, verification coordinates are also constructed and obtained, the verification coordinates are substituted into all function fitting results, screening is performed according to the fitting accuracy, and the material change function with the highest accuracy is selected.
As shown in fig. 8, as a preferred embodiment of the present invention, the visualization module 400 includes:
The material usage prediction unit 401 is configured to generate time gradient data based on a preset prediction gradient, and substitute the time gradient data into a material change function to obtain predicted material usage data.
In this module, the material usage prediction unit 401 generates time gradient data based on a preset prediction gradient, and the smaller the prediction gradient, the finer the prediction result to be obtained is, for example, one second is taken as a prediction gradient, so that more time gradient data will be generated, if two seconds are taken as the prediction gradient, the gradient time data will be reduced to half of the original time, and the corresponding predicted material usage data will be correspondingly reduced.
A color value calculation unit 402 for determining a first model color value based on the currently detected material balance value and a second model color value based on the predicted material usage data.
In this module, the color value calculating unit 402 determines a first model color value based on the currently detected material residual value, specifically, the material residual value obtained by real-time detection is represented by blue, and the material residual value is subtracted from the material predicted value recorded in the predicted material usage data to obtain a change value, where the change value is marked with a second model color value, and may be green.
The model processing unit 403 is configured to color the virtual production line model based on the first model color value and the second model color value, generate a visual result, and generate a material usage prediction report based on the predicted material usage data.
In this module, the model processing unit 403 colors the virtual production line model based on the first model color value and the second model color value, and can intuitively see the actual value of the current material and the change value of the material in the future according to the first model color value and the second model color value, and when the change value of the material exceeds the preset range, the change value of the material can be marked by the third model color value, thereby prompting a manager, generating a material consumption prediction report, and early warning the change of the material.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.

Claims (10)

1. The full-flow integrated control method for rare earth smelting production is characterized by comprising the following steps of:
Based on the sequence of rare earth smelting manufacturing equipment, constructing a virtual production line model, wherein the virtual production line model consists of different stages of processing equipment, and all stages of processing equipment are provided with material detection sensors;
acquiring material data in the stage processing equipment, recording the material data according to a time sequence, and determining a material change record corresponding to each stage processing equipment;
Generating material change parameter coordinates corresponding to each stage of processing equipment based on the material change records, and performing function fitting based on the material parameter coordinates to obtain a material change function;
Predicting the material consumption based on the material change function to obtain predicted material consumption data, and performing visual processing on the virtual production line model based on the predicted material consumption data to generate a visual result;
the step of acquiring the material data in the stage processing equipment, recording the material data according to the time sequence, and determining the material change record corresponding to each stage processing equipment specifically comprises the following steps:
Dynamically acquiring material data in the stage processing equipment according to a preset time interval;
Constructing a two-dimensional coordinate system, carrying out segmentation processing on the two-dimensional coordinate system based on data acquisition intervals, and determining reference lines corresponding to all moments;
And marking the numerical value of the corresponding material data in a two-dimensional coordinate system based on the material data corresponding to each moment to obtain the material change record of the single-stage processing equipment.
2. The integrated control method for the whole process of rare earth smelting production as set forth in claim 1, wherein in the step of constructing a two-dimensional coordinate system, segmenting the two-dimensional coordinate system based on data acquisition intervals, and determining reference lines corresponding to respective times, the firstReference lines corresponding to the data acquisition moments are in a two-dimensional coordinate systemThe coordinate values correspond to the following formulas:
；
Wherein, Represent the firstReference lines corresponding to data acquisition moments in two-dimensional coordinate systemThe coordinate value of the axis,Representing the time interval of the data acquisition,Representing the absolute point in time of the current data acquisition,Representing the absolute point in time of the first data acquisition,Representing in a two-dimensional coordinate systemThe maximum scale value of the shaft,Representing in a two-dimensional coordinate systemMinimum scale value of the shaft.
3. The integrated control method for the whole flow of rare earth smelting production and manufacturing according to claim 2, wherein in the step of marking the numerical value of the corresponding material data in a two-dimensional coordinate system based on the material data corresponding to each moment to obtain the material change record of the single-stage processing equipment, the coordinates of the marked points in the two-dimensional coordinate system are expressed as follows:
；
Wherein, Representing marked points in a two-dimensional coordinate systemThe axis of the rotation is set to be at the same position,Representing marked points in a two-dimensional coordinate systemThe axis of the rotation is set to be at the same position,Represent the firstThe time of the data acquisition is the same,Represent the firstMaterial data values acquired at the moment of data acquisition,Representing in a two-dimensional coordinate systemThe maximum value of the axis is,Representing in a two-dimensional coordinate systemThe minimum value of the axis is set to,Representing the maximum value in the acquired material data,Representing the minimum value in the collected material data,Representing an adjustment parameter for controlling the data point inDistribution on the axis.
4. The integrated control method for the whole process of rare earth smelting production and manufacturing according to claim 3, wherein the step of generating the material variation parameter coordinates corresponding to each stage of processing equipment based on the material variation records, performing function fitting based on the material parameter coordinates, and obtaining a material variation function specifically comprises the following steps:
Extracting a time value and a corresponding material residual value from a material change record according to a preset data reading interval, and constructing to obtain a material change parameter coordinate, wherein the abscissa of the material change parameter coordinate is the time value, and the ordinate of the material change parameter coordinate is the material residual value;
calling a preset function fitting type table, and performing function fitting based on the function fitting type table to obtain a plurality of groups of function fitting results;
And retrieving the material change record again to obtain verification data, verifying the precision of fitting results of the functions based on the verification data, and selecting a material change function with highest precision.
5. The integrated control method for the whole flow of rare earth smelting production process according to claim 4, wherein in the step of retrieving a preset function fitting type table, performing function fitting based on the function fitting type table to obtain a plurality of groups of function fitting results, a function fitting formula corresponding to the function fitting type table is expressed as:
；
Wherein, Is shown at the momentThe material balance of the furnace is equal to the total material balance,All of which represent parameters that need to be fitted,Representing a time value.
6. The method for controlling the whole process of rare earth smelting production and manufacturing according to claim 5, wherein the step of predicting the material usage based on the material change function to obtain predicted material usage data, and performing visualization processing on the virtual production line model based on the predicted material usage data to generate a visualization result specifically comprises the following steps:
generating time gradient data based on a preset prediction gradient, substituting the time gradient data into a material change function, and obtaining predicted material consumption data;
Determining a first model color value based on the currently detected material remainder value and a second model color value based on the predicted material usage data;
and coloring the virtual production line model based on the first model color value and the second model color value to generate a visual result, and generating a material consumption estimated report based on the predicted material consumption data.
7. The integrated control method for the whole flow of rare earth smelting production process according to claim 6, wherein in the step of generating time gradient data based on a preset prediction gradient, substituting the time gradient data into a material change function to obtain predicted material amount data, a formula expression corresponding to the predicted material amount data is:
；
Wherein, Expressed in timeThe material consumption is predicted in the process,Indicating the residual quantity of the initial material,All of which represent parameters that need to be fitted,The current point in time is indicated and,The previous point in time is indicated and,Indicating the corresponding amount of material at the current point in time,Indicating the amount of material corresponding to the previous time point.
8. The integrated control method for the whole flow of rare earth smelting production process according to claim 7, wherein in the step of determining a first model color value based on the currently detected material remaining value and determining a second model color value based on the predicted material usage data, a calculation formula of the first model color value is expressed as:
；
Wherein, A color value of the first model is represented,Representing the value of the remainder of the material currently detected,Representing the maximum value of the material allowance; A downward rounding symbol for representing a maximum integer that is not greater than the value in brackets;
The calculation formula of the color value of the second model is expressed as:
；
Wherein, Representing a color value of a second model,The predicted material consumption is indicated,Representing the minimum value of the material balance.
9. The integrated control method for the whole process of rare earth smelting production and manufacturing according to claim 8, wherein before the step of constructing the virtual production line model based on the sequence of the rare earth smelting production equipment, the method further comprises:
Detecting the components and the contents of materials, setting an automatic control strategy for stage processing equipment, performing process simulation based on a production and processing process, and generating a visual animation;
After the step of generating the visualization result, further comprising:
The method comprises the steps of constructing a big data cloud platform, and carrying out data statistics and analysis through the big data cloud platform, wherein the big data cloud platform comprises an intelligent control module, a roaming module, a production management module, an enterprise module, an equipment management module and a system early warning module.
10. A rare earth smelting production and manufacturing full-process integrated control system, characterized in that the full-process integrated control method for rare earth smelting production and manufacturing according to any one of claims 1 to 9 is applied, the system comprising:
The model construction module is used for constructing a virtual production line model based on the sequence of rare earth smelting manufacturing equipment, wherein the virtual production line model consists of different stages of processing equipment, and all stages of processing equipment are provided with material detection sensors;
the data recording module is used for acquiring material data in the stage processing equipment, recording the material data according to a time sequence and determining a material change record corresponding to each stage processing equipment;
The function fitting module is used for generating material change parameter coordinates corresponding to the processing equipment at each stage based on the material change records, and performing function fitting based on the material parameter coordinates to obtain a material change function;
The visualization module is used for predicting the material consumption based on the material change function to obtain predicted material consumption data, and performing visualization processing on the virtual production line model based on the predicted material consumption data to generate a visualization result;
The data recording module comprises:
The material data extraction unit is used for dynamically acquiring material data in the stage processing equipment according to a preset time interval;
The coordinate system construction unit is used for constructing a two-dimensional coordinate system, carrying out segmentation processing on the two-dimensional coordinate system based on the data acquisition interval, and determining a reference line corresponding to each moment;
The recording and marking unit is used for marking the numerical value of the corresponding material data in a two-dimensional coordinate system based on the material data corresponding to each moment to obtain a material change record of the single-stage processing equipment;
the function fitting module comprises:
The parameter coordinate construction unit is used for extracting a time value and a corresponding material residual value from the material change record according to a preset data reading interval, constructing and obtaining a material change parameter coordinate, wherein the abscissa of the material change parameter coordinate is the time value, and the ordinate of the material change parameter coordinate is the material residual value;
the data fitting unit is used for calling a preset function fitting type table, and performing function fitting based on the function fitting type table to obtain a plurality of groups of function fitting results;
The function screening unit is used for recalling the material change records to obtain verification data, verifying the precision of each function fitting result based on the verification data, and selecting a material change function with highest precision;
the visualization module comprises:
The material consumption prediction unit is used for generating time gradient data based on a preset prediction gradient, substituting the time gradient data into a material change function to obtain predicted material consumption data;
a color value calculation unit for determining a first model color value based on the currently detected material residual value and a second model color value based on the predicted material usage data;
the model processing unit is used for coloring the virtual production line model based on the first model color value and the second model color value, generating a visual result and generating a material consumption estimated report based on the predicted material consumption data;
the method is characterized in that the method further comprises the following steps before the step of constructing the virtual production line model based on the sequence of the rare earth smelting manufacturing equipment:
Detecting the components and the contents of materials, setting an automatic control strategy for stage processing equipment, performing process simulation based on a production and processing process, and generating a visual animation;
After the step of generating the visualization result, further comprising:
The method comprises the steps of constructing a big data cloud platform, and carrying out data statistics and analysis through the big data cloud platform, wherein the big data cloud platform comprises an intelligent control module, a roaming module, a production management module, an enterprise module, an equipment management module and a system early warning module.
CN202410707749.3A 2024-06-03 2024-06-03 Whole-flow integrated control system and method for rare earth smelting production and manufacturing Pending CN118278900A (en)

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