CN109190138B - Method and device for coordinating evaporation process data in alumina production based on mutual information - Google Patents
Method and device for coordinating evaporation process data in alumina production based on mutual information Download PDFInfo
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Abstract
The invention relates to a method and a device for coordinating evaporation process data in alumina production based on mutual information. The method comprises the steps of obtaining data of all measurement variables in the alumina evaporation process, establishing a mutual information matrix among all the measurement variables based on the data of all the measurement variables, and establishing a hierarchical data coordination model based on the mutual information matrix; and processing the data of the measurement variables based on the hierarchical data coordination model to obtain a first coordination result. The hierarchical data coordination model is established by utilizing the mutual information relation among the measurement variables, so that the accuracy of data coordination can be improved, the influence of errors in the measurement data is reduced, and the accuracy of the obtained first coordination result is high. The apparatus comprises a display, a processor and a computer program stored on a memory and executable on the processor, the processor implementing the steps of the method when executing the computer program.
Description
Technical Field
The invention relates to the field of data processing and modeling in an evaporation process of aluminum oxide production, in particular to a method and a device for coordinating data in the evaporation process of aluminum oxide production based on mutual information.
Background
The evaporation process is one of the key processes in the production process of the alumina, and plays an important role in recycling useful resources and reducing the discharge of waste alkali liquor. The process evaporates the excess water in the seed precipitation mother liquor and the washing filtrate by heating steam to provide a high concentration circulating mother liquor for the dissolution process. In the actual evaporation process of alumina production, process measurement data is inevitably interfered by errors, so that the measurement data deviates from a true value and does not meet the boundary constraint conditions of material mass balance, heat balance relation and process parameters. In addition, some important parameters cannot be obtained due to the limitation of detection technology and economic conditions. Inaccurate measurement data will influence modeling, optimization, control and even management decisions of the evaporation process of alumina production, and are related to economic and technical indexes of the whole alumina production.
Data coordination is used as a data processing technology, redundant information of measured data is utilized, measurement errors are reduced on the basis that mechanism balance constraint and parameter boundary conditions are met, and unmeasured parameters are estimated. In an actual industrial process, the sensor errors involved in the measurement errors are usually independent of each other, and therefore, the covariance matrix of most data coordination models takes into account the form of a diagonal matrix. However, there may be a non-linear correlation of measurement errors between variables caused by model errors, external disturbances or feedback control. In the prior art, a diagonal matrix with mutually independent measurement errors or a correlation coefficient matrix representing a linear correlation relationship is adopted to describe a data coordination model, so that the accuracy of a data coordination result is influenced.
Disclosure of Invention
Therefore, it is necessary to provide a method and an apparatus for coordinating data in an evaporation process of aluminum oxide production based on mutual information, aiming at the technical problem that a coordination result is inaccurate when a non-linear correlation exists in a measurement error.
The invention provides a data coordination method for an evaporation process of aluminum oxide production based on mutual information, which comprises the following steps:
acquiring data of each measurement variable in the alumina evaporation process, establishing a mutual information matrix among the measurement variables based on the data of the measurement variables, and establishing a hierarchical data coordination model based on the mutual information matrix;
and processing the data of the measurement variables based on the hierarchical data coordination model to obtain a first coordination result.
Preferably, the expression of the mutual information matrix is:
where w represents mutual information between any two measured variables.
Further, the expression of the hierarchical data coordination model is as follows:
in the formula, a sample set defining measurement data is represented by X = [ X ] 1 ,x 2 ,K,x m ]∈R n×m N and m represent the total number of samples and the dimension of the variables, respectively;
measurement data representing the ith measurement variable; />
A coordination data set representing a measured variable; />
Coordination data representing the ith measurement variable; />
Represents the difference between the nth measured value of the mth measured variable and the tuning value; h represents a mechanistic equation constraint; />
And &>
Respectively representing the variation lower limit of the ith coordinated variable and the qth unmeasured variable; />
And &>
Respectively representThe upper limit of the variation of the i coordinated variables and the q unmeasured variables; M-M represents the number of unmeasured variables.
Further, the hierarchical data coordination model comprises a mass balance layer data coordination model and a heat balance layer data coordination model;
correspondingly, the specific step of processing the data of each measurement variable based on the hierarchical data coordination model to obtain a first coordination result includes:
processing the data of each measurement variable based on the data coordination model of the mass balance layer to obtain a second coordination result of the data of each measurement variable; and inputting the second coordination result into the heat balance layer data coordination model to obtain the first coordination result.
Further, the specific step of establishing a hierarchical data coordination model based on the mutual information matrix includes:
establishing a data coordination model of a quality balance layer based on the mutual information matrix;
processing the data of each measurement variable based on the data coordination model of the mass balance layer to obtain a second coordination result;
and establishing a heat balance layer data coordination model based on the second coordination result.
Further, the specific steps of establishing a data coordination model of the quality balance layer based on the mutual information matrix include: establishing a data coordination model of the mass balance layer based on the mutual information matrix and combined with the five-effect raw liquid inlet flow, the six-effect raw liquid inlet flow, the raw liquid concentration, the four-flash material flow and/or the four-flash material liquid concentration of each device;
and/or the specific steps of establishing a heat balance layer data coordination model based on the second coordination result comprise: and establishing a heat balance layer data coordination model based on the second coordination result by combining the outlet feed liquid temperature, the outlet secondary steam temperature, the new steam flow, the evaporator outlet condensate water temperature, the new steam temperature and/or the stock solution temperature of each device.
Preferably, the expression of the objective function of the data coordination model of the mass balance layer is as follows:
wherein r (F) represents
r (C) denotes->
And &>
Respectively represents the discharge flow and the concentration of the evaporator with one to six effects and the flash evaporator with one to three stages, and the evaporator and the concentration are combined together>
Representing the difference between the nth measured value and the coordination value of the first variable in the material balance layer; />
Respectively representing the difference between the measured values and the coordination values of six-effect raw liquid inlet flow, five-effect raw liquid inlet flow, raw liquid concentration, four-flash material concentration and four-flash material outlet flow；λ 1 And λ 2 Respectively representing the weight of the flow and the concentration of the material liquid at the outlet of each evaporator.
Preferably, the expression of the objective function of the heat balance layer data coordination model is as follows:
wherein the content of the first and second substances,
and e represents the difference between the measured value and the coordination value of the m-l variable in the heat balance layer, and the measured value and the coordination value of the outlet feed liquid temperature, the outlet secondary steam temperature, the evaporator outlet condensed water temperature, the new steam flow, the stock solution temperature and the new steam temperature of each device in the heat balance layer.
The invention also provides a device for coordinating data in an alumina production evaporation process based on mutual information, which comprises a display, a processor and a computer program stored on a memory and capable of running on the processor, and is characterized in that the processor implements any one of the steps of the method when executing the computer program.
Furthermore, the present invention also proposes a storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method according to any one of the preceding claims.
Compared with the prior art, the invention has the advantages that: acquiring data of each measurement variable in the alumina evaporation process, establishing a mutual information matrix among the measurement variables based on the data of the measurement variables, and establishing a hierarchical data coordination model based on the mutual information matrix; and processing the data of the measurement variables based on the hierarchical data coordination model to obtain a first coordination result. The hierarchical data coordination model is established by utilizing the mutual information relation among the measurement variables, so that the data coordination accuracy can be improved, the influence of errors in the measurement data is reduced, and the accuracy of the obtained first coordination result is high.
Drawings
FIG. 1 is a flow chart of a data coordination method for an alumina production evaporation process based on mutual information in the embodiment of the invention.
FIG. 2 is a schematic structural diagram of a hierarchical data coordination model according to an embodiment of the present invention.
FIG. 3 is a graph comparing the measured variable reconciliation data against the standard deviation obtained by different methods in an embodiment of the present invention.
FIG. 4 is a graph comparing measured data with coordinated data of six-effect feed stock solution flow obtained by different methods in the embodiment of the present invention.
FIG. 5 is a graph comparing measured data with coordination data of the flow rate of feed solution in five different embodiments obtained by different methods of the present invention.
FIG. 6 is a graph of coordination data versus measured data for four-stage flash vessel discharge flow obtained by various methods in accordance with embodiments of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as broadly as the present invention is capable of modification in various respects, all without departing from the spirit and scope of the present invention.
The embodiment of the invention provides a mutual information-based data coordination method for an evaporation process in alumina production, which aims at solving the problems that the measurement data has errors in the evaporation process in alumina production, the measurement data cannot meet the balance between materials and heat, part of important parameters cannot be detected, and the measurement errors have nonlinear correlation due to the reasons of dynamic relationship, external interference, feedback control and the like in the production process, and establishes a mutual information matrix among all measurement variables based on a mutual information theory; and then, establishing an evaporation process hierarchical data coordination model based on mutual information by combining a mechanism model and a process parameter boundary constraint condition. The coordination result of the measurement data is obtained through a state transition algorithm, and the influence of errors in the measurement data is reduced.
Under the condition that the measurement error has a nonlinear relation, more accurate measured data is provided for modeling, optimizing and controlling the evaporation process, and stable and efficient production is ensured. The method can be effectively applied to the actual production process for a long time, has low cost and high reliability, can improve the accuracy of process measurement data, and provides reliable actual measurement data for modeling, optimizing and controlling the evaporation process of alumina production.
The following examples are given to illustrate the present invention.
With reference to fig. 1, this embodiment provides a method for coordinating evaporation process data in alumina production based on mutual information, which includes the following steps:
s1, acquiring data of each measured variable in an alumina evaporation process, establishing a mutual information matrix among the measured variables based on the data of the measured variables, and establishing a hierarchical data coordination model based on the mutual information matrix;
and S2, processing the data of each measurement variable based on the hierarchical data coordination model to obtain a first coordination result.
On the basis of the above embodiment, the expression of the mutual information matrix in this embodiment is:
where w represents mutual information between any two measured variables.
Based on the above embodiments, a sample set of measurement data is defined as X = [ X ] 1 ,x 2 ,K,x m ]∈R n×m And n and m represent the total number of samples and the variable dimension, respectively.
Measurement data representing the ith measurement variable.
In this embodiment, the expression of the hierarchical data coordination model is:
in the formula (I), the compound is shown in the specification,
a coordination data set representing a measured variable; />
Coordinating data representing the ith measured variable; />
Represents the difference between the nth measured value of the mth measured variable and the tuning value; h represents a mechanistic equation constraint; />
And &>
Respectively representing the variation lower limit of the ith coordinated variable and the qth unmeasured variable; />
And &>
Respectively representing the variation upper limits of the ith coordinated variable and the qth unmeasured variable; M-M represents the number of unmeasured variables.
Based on the embodiment, considering that the number of unmeasured variables in the evaporation process is larger than the number of balance equations and the problem of insufficient data redundancy exists, a hierarchical data coordination model is adopted and combined with a graph 2, wherein the hierarchical data coordination model comprises a mass balance layer data coordination model and a heat balance layer data coordination model;
correspondingly, the specific step of processing the data of each measurement variable based on the hierarchical data coordination model to obtain a first coordination result includes:
processing the data of each measurement variable based on the data coordination model of the mass balance layer to obtain a second coordination result of the data of each measurement variable; and inputting the second coordination result into the heat balance layer data coordination model to obtain the first coordination result.
On the basis of the foregoing embodiment, the specific steps of establishing a hierarchical data coordination model based on the mutual information matrix in this embodiment include:
establishing a data coordination model of the quality balance layer based on the mutual information matrix;
processing the data of each measurement variable based on the data coordination model of the mass balance layer to obtain a second coordination result;
and establishing a heat balance layer data coordination model based on the second coordination result.
It should be noted that the first coordination result and the second coordination result in the present embodiment include a coordination value and an estimation value, respectively.
Further, in this embodiment, the variables in the data coordination model of the mass balance layer include: the flow of the five-effect stock solution, the flow of the six-effect stock solution, the concentration of the stock solution, the flow of the four-flash material and/or the concentration of the four-flash material liquid.
Based on the foregoing embodiment, in this embodiment, the specific steps of establishing a data coordination model of a quality balance layer based on the mutual information matrix include: and establishing a data coordination model of the mass balance layer based on the mutual information matrix and combining the five-effect stock solution inlet flow, the six-effect stock solution inlet flow, the stock solution concentration, the four-flash material flow and/or the four-flash material liquid concentration of each device.
Further, the variables in the heat balance layer data coordination model include: the temperature of the material liquid at the outlet of each device, the temperature of the secondary steam at the outlet, the flow of the new steam, the temperature of the condensed water at the outlet of the evaporator, the temperature of the new steam and/or the temperature of the stock solution.
Based on the foregoing embodiment, in this embodiment, the specific step of establishing a thermal balance layer data coordination model based on the second coordination result includes: and establishing a heat balance layer data coordination model based on the second coordination result by combining the outlet feed liquid temperature, the outlet secondary steam temperature, the new steam flow, the evaporator outlet condensed water temperature, the new steam temperature and/or the stock solution temperature of each device.
With reference to fig. 2, further, in this embodiment, a material quality balance layer data coordination model is established, and the five-effect raw liquid inlet flow, the six-effect raw liquid inlet flow, the raw liquid concentration, the four-flash material outlet flow and the four-flash material liquid concentration are coordinated to obtain a coordination value, and the material outlet flow, the material outlet concentration and the secondary steam flow of each device are estimated to obtain an estimated value; and then substituting the coordination value and the estimated value in the data coordination model of the material balance layer into the heat balance layer as known data to establish the data coordination model of the heat balance layer, wherein the data coordination model of the heat balance layer can coordinate the material liquid temperature at the outlet of each device, the secondary steam temperature at the outlet, the new steam flow, the new steam temperature, the condensate water temperature at the outlet of the evaporator and the stock solution temperature to obtain coordination values, and can estimate the heat dissipation capacity of each device to obtain the estimated value.
Based on the above embodiment, the expression of the objective function of the data coordination model in the mass balance layer in this embodiment is as follows:
wherein r (F) represents
r (C) means->
And &>
Respectively represents the discharge flow and the concentration of the evaporator with one to six effects and the evaporator with one to three stages, and is used for determining the concentration of the evaporator>
Representing the difference between the nth measured value and the coordination value of the first variable in the material balance layer; />
Respectively representing the difference between the measured values and the coordination values of six-effect raw liquid inlet flow, five-effect raw liquid inlet flow, raw liquid concentration, four-flash material concentration and four-flash material outlet flow; lambda [ alpha ] 1 And λ 2 And respectively representing the weight of the material liquid flow and the concentration of the outlet of each evaporator.
Based on the above embodiment, the expression of the objective function of the heat balance layer data coordination model in this embodiment is as follows:
wherein the content of the first and second substances,
and e represents the difference between the measured values and the coordination values of the feed liquid temperature at the outlet of each device, the secondary steam temperature at the outlet, the condensed water temperature at the outlet of the evaporator, the new steam flow, the stock solution temperature and the new steam temperature in the data coordination model of the heat balance layer.
In fact, the data coordination problem can be regarded as an optimization problem. And establishing a data coordination model for acquiring coordination data of each measurement variable, and solving the hierarchical data coordination model based on the mutual information by adopting a state transition algorithm.
Boundary conditions of material mass balance, heat balance and decision variables in the evaporation process are used as constraint conditions of the data coordination model. The constraints of the equation for material balance and heat balance for the one to six effect evaporators and the one to four stage flash evaporators are shown in table 1.
TABLE 1
The boundary constraints of feed liquid flow, temperature, concentration, steam flow and temperature are expressed as follows:
j＝1,2,K,9,i＝1,2,K,10,m＝1,2,K,6
in the formula (I), the compound is shown in the specification,
a change lower limit representing a coordination value of the measured variable; c jmin ,F jmin ,V lmin ,Q imin Representing a lower limit of variation of the estimated value of the unmeasured variable; />
Representing an upper limit of variation of the coordination value of the measured variable; c jmax ,F jmax ,V lmax ,Q imax Represents the lower limit of variation of the estimated value of the unmeasured variable.
The invention is adopted to carry out data coordination on 100 groups of measured data in the actual evaporation process, and the data coordination models of an diagonal matrix form (method 1), a correlation coefficient full matrix form (method 2) and a mutual information full matrix form (method 3) are respectively established for comparative analysis. A comparison of the reconciliation data versus standard deviation for the different measured variables is shown in figure 3. The relative standard deviation of the coordination data obtained by the method 3 is smaller than zero, which shows that the standard deviation of the coordination data is smaller than the standard deviation of the measurement data, and the accuracy of the coordination result is high. And the standard deviation of the coordination data obtained by the method 2 and the method 1 is partially larger than zero, which indicates that the coordination data has large fluctuation and poorer coordination precision. The coordination data and the measurement data of the six-effect raw liquid inlet flow, the five-effect raw liquid inlet flow and the four-stage flash evaporator discharge flow (four-flash discharge flow) are compared as shown in fig. 4-6. The fluctuation range of the coordination data obtained by the data coordination method based on mutual information is narrower than that obtained by the other two methods, which shows that the coordination data obtained by the data coordination method based on mutual information is more accurate.
The above results fully show that the method provided by the invention can reduce the influence of random errors on the measured data and improve the precision of the measured data under the condition that the measured errors have nonlinear correlation.
The invention also provides a device for coordinating data in an alumina production evaporation process based on mutual information, which comprises a display, a processor and a computer program stored on a memory and capable of running on the processor, wherein the processor realizes the steps of any one of the methods when executing the computer program.
Furthermore, the present invention proposes a storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method of any one of the above.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. All possible combinations of the technical features of the above embodiments may not be described for the sake of brevity, but should be considered as within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is specific and detailed, but not to be understood as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent should be subject to the appended claims.
Claims (4)
1. A mutual information-based method for coordinating data in an evaporation process of aluminum oxide production is characterized by comprising the following steps:
acquiring data of each measurement variable in the alumina evaporation process, establishing a mutual information matrix among the measurement variables based on the data of the measurement variables, and establishing a hierarchical data coordination model based on the mutual information matrix;
processing the data of each measurement variable based on the hierarchical data coordination model to obtain a first coordination result;
the expression of the hierarchical data coordination model is as follows:
in the formula, a sample set defining measurement data is represented by X = [ X ] 1 ,x 2 ,K,x m ]∈R n×m N and m represent the total number of samples and the dimension of the variables, respectively;
measurement data representing an ith measurement variable; />
A coordination data set representing a measured variable; />
Coordination data representing the ith measurement variable; />
Represents the difference between the nth measured value of the mth measured variable and the tuning value; h represents a mechanistic equation constraint; />
And &>
Respectively representing the variation lower limit of the ith coordinated variable and the qth unmeasured variable; />
And &>
Respectively representing the variation upper limits of the ith coordinated variable and the qth unmeasured variable; M-M represents the number of unmeasured variables;
the hierarchical data coordination model comprises a mass balance layer data coordination model and a heat balance layer data coordination model;
correspondingly, the specific step of processing the data of each measurement variable based on the hierarchical data coordination model to obtain a first coordination result includes:
processing the data of each measurement variable based on the data coordination model of the mass balance layer to obtain a second coordination result of the data of each measurement variable; inputting the second coordination result into the heat balance layer data coordination model to obtain the first coordination result;
the specific steps of establishing a hierarchical data coordination model based on the mutual information matrix comprise:
establishing a data coordination model of the quality balance layer based on the mutual information matrix;
processing the data of each measurement variable based on the data coordination model of the mass balance layer to obtain a second coordination result;
establishing a heat balance layer data coordination model based on the second coordination result;
the specific steps of establishing a data coordination model of the quality balance layer based on the mutual information matrix comprise: establishing a data coordination model of the mass balance layer based on the mutual information matrix in combination with the five-effect stock solution inlet flow, the six-effect stock solution inlet flow, the stock solution concentration, the four-flash material flow and/or the four-flash material liquid concentration of each device;
and/or the specific step of establishing a heat balance layer data coordination model based on the second coordination result comprises the following steps: establishing a heat balance layer data coordination model based on the second coordination result by combining the outlet feed liquid temperature, the outlet secondary steam temperature, the new steam flow, the evaporator outlet condensing water temperature, the new steam temperature and/or the stock solution temperature of each device;
the expression of the objective function of the data coordination model of the mass balance layer is as follows:
wherein r (F) represents
r (C) means->
And &>
Respectively represents the discharge flow and the concentration of the evaporator with one to six effects and the evaporator with one to three stages, and is used for determining the concentration of the evaporator>
Representing the difference between the nth measured value and the coordination value of the first variable in the material balance layer; lambda [ alpha ] 1 And λ 2 Respectively representing the weight of the flow and the concentration of the feed liquid at the outlet of each effect evaporator;
the expression of the objective function of the heat balance layer data coordination model is as follows:
wherein, the first and the second end of the pipe are connected with each other,
the difference between the nth measured value and the coordination value of the m-l variable in the heat balance layer is represented, and e represents the material liquid temperature of the outlet and the secondary steam temperature of the outlet of each device in the heat balance layerThe temperature of the condensed water at the outlet of the evaporator, the flow rate of the new steam, the temperature of the stock solution and the difference between the measured value and the coordinated value of the temperature of the new steam.
2. The method of claim 1, wherein the mutual information matrix is expressed as:
where w represents mutual information between any two measured variables.
3. An apparatus for mutual information based data reconciliation of alumina production evaporation processes comprising a display, a processor and a computer program stored on a memory and executable on said processor, wherein said processor when executing said computer program implements the steps of the method according to any one of claims 1-2.
4. A storage medium on which a computer program is stored which, when being executed by a processor, carries out the steps of a method according to any one of claims 1-2.
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