CN109117495B - Robust data coordination method, device and storage medium in alumina production evaporation process - Google Patents
Robust data coordination method, device and storage medium in alumina production evaporation process Download PDFInfo
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Abstract
The invention relates to a method and a device for coordinating robust data in an evaporation process of alumina production and a storage medium. The method comprises the steps of obtaining data of each measurement variable in the evaporation process of alumina production, and establishing a layered robust data coordination model based on a robust estimation function of the data of each measurement variable; and processing the data of each measurement variable based on the hierarchical robust data coordination model to obtain a first coordination result. When the first coordination result obtained by the method has obvious errors and is uncertain in size, the coordination result is accurate. 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 described above when executing the computer program. The storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the method described above.
Description
Technical Field
The invention relates to the field of data processing and modeling in an evaporation process of alumina production, in particular to a robust data coordination method, a robust data coordination device and a robust data coordination storage medium in the evaporation process of alumina production.
Background
The evaporation process is one of the key processes in the production process of the aluminum oxide, and plays an important role in recycling useful resources and reducing the discharge of waste alkali liquor. In the process, excessive water in seed precipitation mother liquor and washing filtrate is evaporated by heating steam, and high-concentration circulating mother liquor is provided for a 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 alumina production evaporation process, 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, and on the basis of meeting mechanism balance constraint and parameter boundary conditions, measurement errors are reduced, and unmeasured parameters are estimated. However, process measurement data has significant errors due to factors such as meter failures, equipment leaks, manual errors, and the like. If the traditional least square data coordination method with errors subject to normal distribution is adopted, significant error diffusion can be caused, other data without significant errors are polluted, and the coordination result is influenced. Therefore, aiming at the phenomenon, a new robust data coordination model is constructed based on the robust estimation theory. And analyzing the robustness of the robust estimation function through the influence function. The robust estimation function is less affected by significant errors as they tend to large values. Under the condition that the significant error is uncertain, the constructed robust data coordination method is utilized to coordinate data, and the method has important significance for improving the accuracy of measured data, realizing stable and optimized control of an evaporation process and improving the product quality and the production efficiency.
Disclosure of Invention
Based on this, it is necessary to provide a robust data coordination method, apparatus and storage medium for the alumina production evaporation process, aiming at the technical problems that the coordination result is inaccurate when the measurement data has significant errors and uncertain size.
The invention provides a robust data coordination method in an evaporation process of alumina production, which comprises the following steps:
acquiring data of each measured variable in the evaporation process of alumina production, and establishing a hierarchical robust data coordination model based on a robust estimation function of the data of each measured variable;
and processing the data of each measurement variable based on the hierarchical robust data coordination model to obtain a first coordination result.
Further, the expression of the robust estimation function is:
in the formula (I), the compound is shown in the specification,
representing a relative deviation, x representing a measured value>
Denotes the coordination value, and σ denotes the standard deviation of the measured variable.
Preferably, the robustness of the robust estimation function is evaluated based on an influence function.
Further, the step of processing the data of each measured variable based on the hierarchical robust data coordination model and obtaining the first coordination result further includes:
and detecting the significant error of the first coordination result, and judging whether the significant error exists in the measured value in the measured variable.
Further, the step of detecting a significant error of the first coordination result and determining whether the significant error exists in the measured value of the measured variable specifically includes: definition of
For the difference of the jth measured value of the ith measured variable from the coordination value, a statistical test quantity is constructed>
Given a significance level α for the overall online data, the significance level for each measurement data is β =1- (1- α) 1/n The corresponding critical value is xi c ＝ξ 1-β2 And comparing the magnitude of the statistical test quantity with the critical value, and if the statistical test quantity is greater than the critical value, determining that the measured value has a significant error.
Preferably, the layered robust data coordination model comprises a mass balance layer data coordination model and a heat balance layer data coordination model;
correspondingly, the step of processing the data of each measurement variable based on the hierarchical robust data coordination model to obtain a first coordination result specifically includes:
and 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 data coordination model of the heat balance layer to obtain the first coordination result.
Preferably, the specific step of establishing a hierarchical robust data coordination model based on the robust estimation function of the data of each measurement variable includes:
establishing a data coordination model of the mass balance layer based on a robust estimation function of data of each measurement variable in the evaporation process of alumina production;
processing the data of each measurement variable based on a 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.
Preferably, the expression of the objective function of the data coordination model of the quality balance layer is as follows:
the expression of the objective function of the heat balance layer data coordination model is as follows:
wherein f is 1 And f 2 Respectively representing the objective functions of a data coordination model of the material mass balance layer and a data coordination model of the heat balance layer;
a coordinated data sample set representing m measurement variables; />
Coordination data representing the ith measurement variableA sample set; />
And &>
Respectively representing the jth measured value and the coordination value of the ith measured variable; sigma i Represents the standard deviation of the ith measured variable; 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; l represents the number of measurement variables contained in the mass balance of the material; m-l represents the number of measurement variables involved in the heat balance.
Furthermore, the invention proposes an apparatus for robust data reconciliation in an alumina production evaporation process, comprising a display, a processor and a computer program stored on a memory and executable on said processor, said processor implementing the steps of any of the above methods when executing said computer program.
The invention also proposes a storage medium on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method of any one of the above-mentioned.
Compared with the prior art, the invention has the advantages that: acquiring data of each measured variable in an evaporation process, and establishing a hierarchical robust data coordination model based on a robust estimation function of the data of each measured variable; and processing the data of each measurement variable based on the hierarchical robust data coordination model to obtain a first coordination result. The hierarchical robust data coordination model can reduce the influence of random errors and significant errors in measured data, and the obtained first coordination result is accurate when significant errors exist and the size is uncertain.
Drawings
FIG. 1 is a flow chart of a robust data coordination method in an alumina production evaporation process according to an embodiment of the present invention.
Fig. 2 is a graph comparing a robust estimation function with other robust estimation functions according to an embodiment of the present invention.
FIG. 3 is a graph of an impact function in an embodiment of the invention.
FIG. 4 is a schematic structural diagram of a hierarchical data coordination model according to an embodiment of the present invention.
FIG. 5 is a comparison graph of the six-effect feed stock solution flow coordination result and the six-effect feed stock solution flow coordination result obtained by the least square data coordination method in the embodiment of the present invention.
Fig. 6 is a comparison graph of the five-effect raw liquid flow coordination result and the five-effect raw liquid flow coordination result obtained by the least square data coordination method in the embodiment of the present invention.
FIG. 7 is a comparison graph of the coordination result of the discharge flow of the four-stage flash evaporator and the coordination result of the discharge flow of the four-stage flash evaporator obtained by the least square data coordination method in the embodiment of the present invention.
Fig. 8 is a comparison graph of the new steam flow coordination result and the new steam flow coordination result obtained by the least square data coordination method in the embodiment of the present invention.
FIG. 9 is a graph comparing the standard deviation of the reconciliation results obtained in the example of the present invention with the standard deviation of the reconciliation results obtained in other methods.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, embodiments accompanying 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 invention provides a robust data coordination method in an evaporation process of aluminum oxide production, which aims at the problems that random errors and significant errors exist in measured data in the evaporation process of aluminum oxide production, the measured data cannot meet material and heat balance, part of important parameters cannot be detected, and the significant errors have large influence on coordination results, constructs a robust data coordination model based on a robust estimation principle, replaces a traditional least square data coordination model with the measured errors obeying normal distribution, and analyzes the robustness of the provided data coordination model through an influence function; and establishing a layered robust data coordination model in the evaporation process of the aluminum oxide production by taking the minimum robust estimation function as an optimization target and taking the process mechanism balance and the process parameter boundary conditions as constraints. The effectiveness of the constructed robust data coordination method is verified through actual alumina production evaporation process data, and the constructed robust data coordination method is compared and analyzed with coordination results obtained by other existing robust data coordination methods, so that the robust data coordination method provided by the invention has high coordination precision under the condition of obvious error interference. The following examples are given to illustrate the present invention.
With reference to fig. 1, the present embodiment provides a method for coordinating robust data in an evaporation process of alumina production, including the following steps:
s1, acquiring data of each measured variable in an evaporation process of alumina production, and establishing a hierarchical robust data coordination model based on a robust estimation function of the data of each measured variable;
and S2, processing the data of each measurement variable based on the hierarchical robust data coordination model to obtain a first coordination result.
On the basis of the above embodiment, the expression of the robust estimation function in this embodiment is:
in the formula (I), the compound is shown in the specification,
representing a relative deviation, x representing a measured value, and>
denotes the tuning value and σ denotes the standard deviation of the measured variable. As can be seen from fig. 2, the robust estimation function constructed by the present embodiment is less affected by relative bias than other robust estimation functions.
On the basis of the above embodiment, further, the present embodiment further includes:
evaluating the robustness of the robust estimation function based on an influence function. The expression of the influence function is IF (ξ) = d ρ (ξ)/d ξ, as shown in fig. 3, the influence function of the constructed robust estimation function gradually approaches zero with the increase of the relative deviation, which indicates that the influence function is less influenced by a significant error.
On the basis of the above embodiment, the step of processing the online data based on the hierarchical robust data coordination model and obtaining the first coordination result further includes:
and detecting the significant error of the first coordination result, and judging whether the significant error exists in the measured value in the measured variable.
Detecting a significant error of the first coordination result, and judging whether the significant error exists in the measurement value of the measurement variable specifically includes: definition of
For the difference of the jth measured value of the ith measured variable from the coordination value, a statistical test quantity is constructed>
Given a significance level α for the overall online data, the significance level for each measurement data is β =1- (1- α) 1/n Corresponding to a threshold value ofξ c ＝ξ 1-β2 And comparing the magnitude of the statistical test quantity with the critical value, and if the statistical test quantity is greater than the critical value, determining that the measured value has a significant error.
In the embodiment, the problem of insufficient data redundancy caused by the fact that the number of unmeasured variables in the evaporation process is larger than that of a balance equation is considered, and the layered robust data coordination model comprises a mass balance layer data coordination model and a heat balance layer data coordination model;
correspondingly, the step of processing the data of each measurement variable based on the hierarchical robust data coordination model to obtain a first coordination result specifically includes:
and 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 data coordination model of the heat balance layer to obtain the first coordination result.
With reference to fig. 4, the specific steps of establishing a hierarchical robust data coordination model based on the robust estimation function of the data of each measurement variable include:
establishing a data coordination model of the mass balance layer based on a robust estimation function of data of each measurement variable in the evaporation process of alumina production;
processing the data of each measurement variable based on a 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.
Wherein the second coordination result comprises a coordination value and an evaluation value; further, coordinating the stock solution flow, the stock solution concentration, the four flash solution outlet flow and the four flash solution outlet concentration of the five-effect evaporator and the six-effect evaporator to obtain a coordination value based on a data coordination model of the mass balance layer, and estimating the discharge flow, the discharge concentration and the secondary steam flow of each device to obtain an estimated value;
establishing a heat balance layer data coordination model based on the second coordination result specifically comprises the steps of taking a coordination value and an estimation value in the material balance layer data coordination model as known data, and establishing the heat balance layer data coordination model by combining the discharge temperature, the secondary steam temperature, the new steam flow, the new steam temperature, the condensed water temperature and the stock solution temperature in each device; the data coordination model can coordinate the discharge temperature, the secondary steam temperature, the new steam flow, the new steam temperature, the condensed water temperature and the stock solution temperature, and can estimate the heat dissipation capacity of each device.
Wherein, the expression of the objective function of the data coordination model of the mass balance layer is as follows:
wherein, the expression of the objective function of the heat balance layer data coordination model is as follows:
wherein f is 1 And f 2 Respectively representing the objective functions of a data coordination model of the material mass balance layer and a data coordination model of the heat balance layer;
a coordinated data sample set representing m measurement variables; />
A coordinated data sample set representing the ith measured variable; />
And &>
Respectively representing the jth measured value and the coordination value of the ith measured variable; sigma i Represents the standard deviation of the ith measured variable; h represents the 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; l represents the number of measurement variables contained in the mass balance of the material; m-l represents the number of measurement variables involved in the heat balance.
Further, the specific objective function and constraint equation is expressed as:
the objective function of the data coordination model of the material mass balance layer and the data coordination model of the heat balance layer is defined as follows:
in the formula, λ 1 r (F) is represented by
λ 2 r (C) is represented by
λ represents a weight, which can be determined by empirical rules. />
And &>
Respectively representing the discharge flow and the concentration of the first-six-effect evaporator and the first-three-stage flash evaporator, and giving numerical values according to operation knowledge.
Representing the coordination value.
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
Feed liquid flow, temperature, concentration and steam flow, temperature boundary constraints are expressed as:
j＝1,2,...,9,i＝1,2,,10,m＝1,2,...,6
in the formula (I), the compound is shown in the specification,
represents a variation lower limit of the coordinate 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.
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 by adopting a state transition algorithm.
The data coordination method provided by the invention is adopted to carry out data coordination on 100 groups of measurement data with significant errors, and the coordination results of six-effect stock solution flow, five-effect stock solution flow, four-stage flash evaporator discharge flow and new steam flow are respectively shown in figures 5-8 by performing comparative analysis on a least square data coordination method which assumes that errors obey normal distribution and the robust data coordination method provided by the invention. As can be seen from fig. 5 to 8, the coordination result obtained by the least square data coordination method is seriously polluted by significant errors, and the coordination data deviation range is wide. The robust data coordination method provided by the invention is compared with other robust data coordination methods, such as Fair, welsch and Cauchy, and standard deviations of coordination values and measurement values obtained by data coordination in different methods are respectively calculated, as shown in FIG. 9, the standard deviation of the coordination result obtained by adopting the robust data coordination method constructed by the invention is smaller than that obtained by adopting other robust data coordination methods and least square data coordination methods, which shows that the robust data coordination model constructed by the invention has high coordination precision, the influence of a significant error is eliminated under the conditions of existence and uncertainty of the significant error, and the robust data coordination model has stronger robustness.
An apparatus for robust data reconciliation in an alumina production evaporation process, comprising a display, a processor and a computer program stored on a memory and executable on the processor, the processor when executing the computer program implementing the steps of the method according to the above embodiment.
A storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method of the above-mentioned embodiments.
Those of ordinary skill in the art will understand that: all or part of the steps of 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, executes 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 can be implemented by software plus a necessary general hardware platform, and certainly can 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 more specific and detailed, but not construed 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 shall be subject to the appended claims.
Claims (7)
1. A robust data coordination method in an alumina production evaporation process is characterized by comprising the following steps:
acquiring data of each measurement variable in the evaporation process of alumina production, and establishing a hierarchical robust data coordination model based on a robust estimation function of the data of each measurement variable;
processing the data of each measurement variable based on the hierarchical robust data coordination model to obtain a first coordination result;
the layered robust data coordination model comprises a mass balance layer data coordination model and a heat balance layer data coordination model;
correspondingly, the step of processing the data of each measurement variable based on the hierarchical robust data coordination model to obtain a first coordination result specifically 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 data coordination model of the heat balance layer to obtain the first coordination result;
the specific steps of establishing a hierarchical robust data coordination model based on the robust estimation function of the data of each measurement variable comprise:
establishing a data coordination model of the mass balance layer based on a robust estimation function of data of each measurement variable in the evaporation process of alumina production;
processing the data of each measurement variable based on a 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 expression of the objective function of the data coordination model of the mass balance layer is as follows:
the expression of the objective function of the heat balance layer data coordination model is as follows:
wherein f is 1 And f 2 Respectively representing the target functions of a material mass balance layer data coordination model and a heat balance layer data coordination model;
a coordinated data sample set representing m measurement variables; />
A coordinated data sample set representing an ith measured variable; />
And &>
Respectively representing the jth measured value and the coordination value of the ith measured variable; sigma i Represents the standard deviation of the ith measured variable; 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; l represents the number of measurement variables contained in the mass balance of the material; m-l represents the number of measurement variables involved in the heat balance.
2. The method of claim 1, wherein the robust estimation function is expressed as:
in the formula (I), the compound is shown in the specification,
representing a relative deviation, x representing a measured value, and>
denotes the tuning value and σ denotes the standard deviation of the measured variable.
3. The method of claim 1, further comprising:
evaluating the robustness of the robust estimation function based on an influence function.
4. The method as claimed in claim 1, wherein the step of processing the data of the measured variables based on the hierarchical robust data coordination model and obtaining the first coordination result further comprises:
and detecting the significant error of the first coordination result, and judging whether the significant error exists in the measured value in the measured variable.
5. The method according to claim 4, wherein the step of performing significant error detection on the first coordination result and determining whether the significant error exists in the measured value of the measured variable specifically comprises:
definition of
Constructing a statistical test quantity for the difference between the jth measurement value and the coordination value of the ith measurement variable
Given a significance level α for the overall online data, the significance level for each measurement data is β =1- (1- α) 1n The corresponding critical value is xi c ＝ξ 1-β2 And comparing the magnitude of the statistical test quantity with the critical value, and if the statistical test quantity is greater than the critical value, determining that the measured value has a significant error.
6. An apparatus for robust 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, characterized in that said processor when executing said computer program realizes the steps of the method according to any one of claims 1 to 5.
7. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method according to any one of claims 1 to 5.
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