An industrial furnace energy-saving control system and method based on nano thermal insulation materials

Abstract

The invention discloses an energy-saving control system and method for an industrial kiln based on nano thermal insulation materials, and relates to the field of energy-saving control. The invention comprehensively considers the component characteristics of the industrial kiln, the characteristics of the nano thermal insulation materials, the characteristics of the products produced, and the parameters when the nano thermal insulation materials are applied, and constructs a final energy consumption mapping equation from the component characteristics of the industrial kiln, the characteristics of the nano thermal insulation materials, the characteristics of the products produced, and the parameters when the nano thermal insulation materials are applied to the energy consumption level data in the production process; then the energy consumption level data of each adjustment of the parameters when the nano thermal insulation materials are applied is obtained through the final energy consumption mapping equation, and the parameters when the nano thermal insulation materials are applied are reversely optimized and adjusted according to the energy consumption level data, so as to obtain a set of the most reasonable parameters when the nano thermal insulation materials are applied, so that the energy consumption level data of the industrial kiln meets the requirements, and the energy-saving control of the industrial kiln is realized.

Description

Technical Field

[0001] The present invention belongs to the field of energy-saving regulation and control, and in particular, relates to an energy-saving regulation and control system and method for an industrial kiln based on nano thermal insulation materials. Background Art

[0002] A Chinese patent with announcement number CN117311244B discloses an energy-saving control method and system based on equipment operating condition prediction, which collects multiple equipment operating condition data of each energy-consuming equipment; extracts and fuses the operating condition features of these equipment operating condition data to obtain target fusion features; creates an equipment intelligent body for each energy-consuming equipment, and analyzes the equipment control execution parameters to generate a first energy-saving control execution strategy; then inputs the target fusion features of each energy-consuming equipment into a cascade forest model to perform global control execution parameter analysis to generate a global energy-saving control execution strategy; finally, based on the global energy-saving control execution strategy, optimizes the execution strategy of the first energy-saving control execution strategy to obtain a second energy-saving control execution strategy for each energy-consuming equipment.

[0003] Nano thermal insulation material is a material with excellent thermal insulation performance. By applying nano thermal insulation material to the inside or outside of industrial kilns, the energy consumption of industrial kilns in the production process can be effectively reduced; however, industrial kilns have many components, so the function and characteristics of each component are different. If different nano thermal insulation materials are not applied to these specific components, the overall energy consumption of the industrial kiln may not achieve the expected effect, and the energy loss cannot be fully controlled. Summary of the invention

[0004] In view of the problems in the related art, the present invention proposes an industrial furnace energy-saving control system and method based on nano-insulation materials to overcome the above-mentioned technical problems existing in the existing related technology.

[0005] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

[0006] The present invention is an industrial furnace energy-saving control method based on nano thermal insulation materials, comprising the following steps:

[0007] S1. Set multiple feature types corresponding to multiple components of multiple industrial furnace types and feature types corresponding to the product types produced to obtain an industrial furnace component feature type matrix and a product feature type matrix; collect feature data of nano thermal insulation materials corresponding to multiple nano thermal insulation material types to obtain a material feature data matrix; set parameter types when applying nano thermal insulation materials to industrial furnaces to obtain an application parameter type set;

[0008] S2. Collect multiple sets of data of industrial kilns during production according to the industrial kiln component feature type matrix, material feature data matrix, coating parameter type set and product feature type matrix to obtain component feature data matrix set, coating parameter data matrix set, product feature data matrix, energy consumption level data set and historical material feature data matrix;

[0009] The final energy consumption mapping equation is constructed using component feature data matrix set, coating parameter data matrix set, product feature data matrix, energy consumption level data set and historical material feature data matrix;

[0010] S3, pre-setting the initial coating parameters to coat the components of the industrial kiln to be coated and obtaining the energy consumption level data during the production operation in conjunction with the material characteristic data matrix to obtain the initial energy consumption level data;

[0011] S4, optimizing the set initial coating parameters according to the initial energy consumption level data and in conjunction with the final energy consumption mapping equation to obtain a final industrial kiln nanomaterial coating parameter data matrix;

[0012] Since there are many types of industrial kilns, each type has greatly different components due to its different uses. Therefore, when applying nano-insulation materials to these different types of industrial kilns, it is necessary to consider the different types of components. Secondly, when the same or different types of industrial kilns produce different types of products, the energy they consume is different. Based on the above, this solution takes into account the differences in production between different kilns and different products by setting multiple feature types corresponding to multiple components of multiple types of industrial kilns and feature types corresponding to the types of products produced, so that the subsequent collection of energy consumption level data of industrial kilns during production is more comprehensive and accurate. In addition, this solution also takes into account different types of The different characteristic data between the nano-insulation materials improves the accuracy of optimizing the coating parameters when the industrial kiln is coated with nano-insulation materials in the subsequent process; by constructing the final energy consumption mapping equation, a mapping relationship is established from the component characteristic data of the industrial kiln, coating parameter data, product characteristic data and characteristic data of the nano-insulation materials to the energy consumption level data of the industrial kiln, which provides a mapping tool for optimizing the coating parameters of the nano-insulation materials in the subsequent process of coating the industrial kiln with nano-insulation materials, and simplifies the optimization process; by optimizing the set initial coating parameters, the energy consumption level data of the industrial kiln after coating the nano-insulation materials according to the optimized coating parameters is made smaller, thereby achieving the purpose of energy saving for the industrial kiln in the production process.

[0013] Preferably, the S1 comprises the following steps:

[0014] S11, setting multiple industrial furnace types and nano thermal insulation material types to obtain an industrial furnace type set and a nano thermal insulation material type set;

[0015] Then, multiple feature types corresponding to multiple component types of each industrial kiln in the industrial kiln type set that need to be coated with nano thermal insulation materials are set to obtain a matrix of feature types of industrial kiln components;

[0016] S12, setting characteristic types of multiple nano thermal insulation materials to obtain a nano thermal insulation material characteristic type set; collecting characteristic data of each type of nano thermal insulation material in the nano thermal insulation material type set according to the nano thermal insulation material characteristic type set to obtain a material characteristic data matrix;

[0017] S13, setting parameter types when applying nano thermal insulation materials to industrial kilns and feature types corresponding to product types produced by various industrial kilns, and obtaining a coating parameter type set and a product feature type matrix;

[0018] Industrial furnace types include roller furnaces, push-plate furnaces, mesh belt furnaces, bell furnaces, box furnaces, rotary furnaces and vacuum furnaces; nano thermal insulation materials include nano multi-level porous silicon-based thermal insulation materials, aerogel composite thermal insulation materials, nano powder molded composite thermal insulation materials, nanoporous super thermal insulation materials and nano ceramic microbead thermal insulation materials; the industrial furnace component feature type matrix includes high temperature resistance characteristics, corrosion resistance characteristics, structural strength characteristics, thermal expansion characteristics, thermal efficiency characteristics, maintenance and replacement convenience characteristics and automation integration characteristics; nano thermal insulation material feature types include thermal conductivity characteristics, specific surface area characteristics, density characteristics, strength characteristics, high temperature resistance characteristics, chemical stability characteristics and weather resistance characteristics; coating parameter types include coating thickness parameters, curing condition parameters after coating, ambient temperature parameters during coating and humidity parameters; the product feature type matrix includes feature types of PTC ceramics, varistors, and ZNO.

[0019] Preferably, S2 comprises the following steps:

[0020] S21, setting multiple energy consumption levels to obtain an energy consumption level set;

[0021] S22, collecting multiple sets of industrial kiln component feature data, coating parameter data, product feature data, energy consumption level data and material feature data of industrial kilns at production times in cooperation with the energy consumption level set, coating parameter type set, industrial kiln component feature type matrix, product feature type matrix and material feature data matrix, to obtain component feature data matrix set, coating parameter data matrix set, product feature data matrix, energy consumption level data set and historical material feature data matrix;

[0022] S23, constructing an initial energy consumption mapping equation; optimizing the initial energy consumption mapping equation using the component feature data matrix set, the smear parameter data matrix set, the product feature data matrix, the energy consumption level data set, and the historical material feature data matrix to obtain a final energy consumption mapping equation;

[0023] By setting multiple energy consumption levels, a measurement standard is provided for the subsequent collection of energy consumption data of industrial kilns at historical moments, making the data simpler; by collecting multiple groups of industrial kiln component characteristic data, coating parameter data, product characteristic data, energy consumption level data and material characteristic data at historical moments in the production of industrial kilns, data support is provided for the subsequent construction of the final energy consumption mapping equation.

[0024] Preferably, the S23 comprises the following steps:

[0025] S231, constructing an initial energy consumption mapping equation;

[0026] S232, substituting the data in the coating parameter type set, the industrial furnace component feature type matrix, the product feature type matrix, and the historical material feature data matrix into the initial energy consumption mapping equation to obtain an initial energy consumption level mapping data set;

[0027] S233, when the initial energy consumption level mapping data set has energy consumption level mapping data that is different from the corresponding energy consumption level data in the energy consumption level data set, optimizing the initial energy consumption mapping equation until the initial energy consumption level mapping data set has no initial energy consumption level mapping data that is different from the corresponding energy consumption level data in the energy consumption level data set, and obtaining a final energy consumption mapping equation; otherwise, there is no need to optimize the initial energy consumption mapping equation, and the initial energy consumption mapping equation is used as the final energy consumption mapping equation;

[0028] Since the energy consumption level data is an integer, a rounding function is added to the outer layer of the initial energy consumption mapping equation in this scheme, so that the values ​​mapped by the energy consumption mapping equation are all integers, which can correspond to the energy consumption level data; first, the data in the collected coating parameter type set, industrial kiln component feature type matrix, product feature type matrix and historical material feature data matrix are substituted into the initial energy consumption mapping equation, so as to preliminarily map them into corresponding energy consumption level data, and compare the energy consumption level data with the actually measured energy consumption level data. If there are inconsistent data, the multiple independent variables and offsets of the initial energy consumption mapping equation are optimized, thereby ensuring the mapping accuracy of the final energy consumption mapping equation.

[0029] Preferably, S3 comprises the following steps:

[0030] S31, setting the type data of the industrial kiln to be coated, recorded as the type data of the industrial kiln to be coated; collecting the characteristic data of multiple components in the industrial kiln to be coated that need to be coated with nano thermal insulation materials according to the characteristic type matrix of industrial kiln components and the type data of the industrial kiln to be coated, and obtaining the characteristic data matrix of the components to be coated;

[0031] S32, setting coating parameter data coated on each component in the industrial kiln to be coated according to the feature data matrix of the component to be coated and the coating parameter type set, to obtain an initial industrial kiln coating parameter data matrix;

[0032] Then, according to the product feature type matrix, the product feature data that the industrial kiln to be coated needs to produce is obtained to obtain a feature data set of the product to be produced;

[0033] S33, traversing the nano thermal insulation material characteristic type set, using the nano thermal insulation material corresponding to each nano thermal insulation material characteristic type in the nano thermal insulation material characteristic type set to coat each component in the industrial kiln to be coated according to the initial industrial kiln coating parameter data matrix, to obtain the industrial kiln after initial coating; using the industrial kiln after initial coating to produce the product corresponding to the product characteristic data set to be produced and collecting the corresponding energy consumption level data according to the energy consumption level set, to obtain the initial energy consumption level data;

[0034] By setting the type data of the industrial kiln to be coated, collecting the characteristic data of multiple components in the industrial kiln that need to be coated with nano-insulation materials, and the coating parameter data coated on each component in the industrial kiln to be coated, the industrial kiln is firstly subjected to production inspection based on these set data to obtain the corresponding energy consumption level data, which provides a basis for subsequent determination of whether the energy consumption data of the current industrial kiln meets the requirements.

[0035] Preferably, S4 comprises the following steps:

[0036] S41, setting energy consumption level data threshold;

[0037] S42. When the initial energy consumption level data is greater than or equal to the energy consumption level data threshold, the initial industrial kiln coating parameter data matrix is ​​optimized and adjusted until the initial energy consumption level data is less than the energy consumption level data threshold, thereby obtaining the final industrial kiln nanomaterial coating parameter data matrix; otherwise, there is no need to optimize and adjust the initial industrial kiln coating parameter data matrix, and the initial industrial kiln coating parameter data matrix is ​​used as the final industrial kiln nanomaterial coating parameter data matrix;

[0038] By setting the energy consumption level data threshold, a quantitative standard is provided for judging the energy consumption level data of current industrial kilns.

[0039] Preferably, the optimization and adjustment of the initial industrial kiln coating parameter data matrix in S42 includes the following steps:

[0040] S421, constructing a second locust population; setting the maximum number of iterations of the second locust population to , the current number of iterations is , respectively recorded as the second maximum number of iterations and the second current number of iterations.

[0041] S422, setting a value interval of each type of smearing parameter in the smearing parameter type set to obtain a smearing parameter value interval set;

[0042] The initial position of each locust in the second locust population is set according to the smear parameter value interval set to obtain an initial position matrix set.

[0043] S423. Construct a fitness function of the second locust population based on the initial energy consumption level data.

[0044] S424, start iteration, set the second current iteration number to 1 before iteration; in the first round of iteration, use the fitness function of the second locust population and cooperate with the final energy consumption mapping equation to calculate the fitness value of the initial position matrix of each locust in the initial position matrix set to obtain a third fitness value set; use the maximum fitness value in the third fitness value set and the initial position of the corresponding locust as the third global optimal fitness and the third global optimal position respectively; update the initial position matrix of each locust in the initial position matrix set according to the third global optimal fitness and the third global optimal position; after the update is completed, add 1 to the second current iteration number and enter the next round of iteration;

[0045] In each other round of iteration, the fitness function of the second locust population is used and the final energy consumption mapping equation is used to calculate the fitness value of the position of each locust updated in the previous round of iteration to obtain a fourth fitness value set; the maximum fitness value in the fourth fitness value set and the initial position of the corresponding locust are used as the fourth global optimal fitness and the fourth global optimal position respectively; the position of each locust updated in the previous round of iteration is updated again according to the fourth global optimal fitness and the fourth global optimal position; after the update is completed, the second current iteration number is increased by 1 and the next round of iteration is entered.

[0046] S425, when When , stop the iteration and get the second final global optimal position, otherwise, continue to iterate until until the time; the second final global optimal position is used as the optimized industrial kiln coating parameter data matrix; according to the optimized industrial kiln coating parameter data matrix, each component in the industrial kiln to be coated is coated with the nano-insulation material corresponding to each nano-insulation material feature type in the nano-insulation material feature type set to obtain the optimized coated industrial kiln; the optimized coated industrial kiln is used to produce the product corresponding to the product feature data set to be produced and the corresponding energy consumption level data is collected according to the energy consumption level set to obtain the optimized energy consumption level data;

[0047] When the optimized energy consumption level data is less than the energy consumption level data threshold, the optimized industrial kiln coating parameter data matrix is ​​used as the final industrial kiln nanomaterial coating parameter data matrix; otherwise, return to S424 to continue iterating until the optimized energy consumption level data is less than the energy consumption level data threshold, and the final industrial kiln nanomaterial coating parameter data matrix is ​​obtained;

[0048] The locust optimization algorithm is used to iteratively optimize the coating parameters of nano-insulation materials in industrial kilns for multiple times, and the energy consumption level data of the industrial kiln in the production process after coating is used as the fitness function, wherein the energy consumption level data is calculated through the final energy consumption mapping equation that has been optimized before, thereby eliminating the need to obtain data through actual production, thereby simplifying the optimization process; therefore, with the progress of iterations, the energy consumption level data in the production process of the post-industrial kiln becomes smaller and smaller, and finally meets the requirements.

[0049] An industrial kiln energy-saving control system based on nano thermal insulation materials includes an industrial kiln component feature type setting module, a nano thermal insulation material feature type setting module, a nano thermal insulation material feature data acquisition module, a coating parameter type setting module, a product feature type setting module, a historical industrial kiln production data acquisition module, an energy consumption mapping equation construction module, a component feature data acquisition module, an energy consumption level acquisition module and a coating parameter optimization module.

[0050] The present invention has the following beneficial effects:

[0051] 1. The present invention comprehensively considers the component characteristics of the industrial kiln, the characteristics of the nano thermal insulation material, the characteristics of the produced product and the parameters when the nano thermal insulation material is applied, and constructs a final energy consumption mapping equation from the component characteristics of the industrial kiln, the characteristics of the nano thermal insulation material, the characteristics of the produced product and the parameters when the nano thermal insulation material is applied to the energy consumption level data in the production process; then the energy consumption level data of each adjustment of the parameters when the nano thermal insulation material is applied is obtained through the final energy consumption mapping equation, and the parameters when the nano thermal insulation material is applied are reversely optimized and adjusted according to the energy consumption level data, so as to obtain a set of the most reasonable parameters when the nano thermal insulation material is applied, so that the energy consumption level data of the industrial kiln meets the requirements, and the energy-saving regulation of the industrial kiln is realized;

[0052] 2. The present invention collects data of multiple groups of industrial kilns at historical moments during production, providing data support for the subsequent construction of the final energy consumption mapping equation;

[0053] 3. In the present invention, the coating parameters of the nano-insulation material in the industrial kiln are iteratively optimized multiple times by using the locust optimization algorithm, and the energy consumption level data of the industrial kiln in the production process after coating is used as the fitness function, wherein the energy consumption level data is calculated by the final energy consumption mapping equation that has been optimized before, thereby eliminating the need to obtain data through actual production, thereby simplifying the optimization process; therefore, as the iteration proceeds, the energy consumption level data in the production process of the post-industrial kiln becomes smaller and smaller, and finally meets the requirements.

[0054] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, they can also obtain drawings based on these drawings without paying creative work.

[0056] Figure 1 The present invention is a schematic flow chart of an industrial furnace energy-saving control method based on nano thermal insulation materials. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the invention to clearly and completely describe the technical solutions in the embodiments of the invention. Obviously, the described embodiments are only part of the embodiments of the invention, not all of the embodiments. Based on the embodiments in the invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the invention.

[0058] In the description of the present invention, it is necessary to understand that the terms "opening", "upper", "lower", "top", "middle", "inside" and the like indicating orientation or positional relationship are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the components or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the invention.

[0059] Embodiment 1

[0060] This embodiment is a method for energy-saving control of industrial furnaces based on nano thermal insulation materials, comprising the following steps:

[0061] S1. Set multiple feature types corresponding to multiple components of multiple industrial furnace types and feature types corresponding to the product types produced to obtain an industrial furnace component feature type matrix and a product feature type matrix; collect feature data of nano thermal insulation materials corresponding to multiple nano thermal insulation material types to obtain a material feature data matrix; set parameter types when applying nano thermal insulation materials to industrial furnaces to obtain an application parameter type set;

[0062] The S1 comprises the following steps:

[0063] S11. Set multiple industrial furnace types and nano thermal insulation material types to obtain an industrial furnace type set. And nano thermal insulation material type set ; a 1i 、a 2i They represent the i-th industrial furnace type and the i-th nano thermal insulation material type respectively. , Respectively represent the total number of set industrial furnace types and nano thermal insulation material types.

[0064] Then, multiple feature types corresponding to multiple component types of each industrial kiln in the industrial kiln type set that need to be coated with nano-insulation materials are set to obtain an industrial kiln component feature type matrix. ;as follows,

[0065] ;

[0066] in, represents a feature type set of components of the jth type of industrial furnace in the i-th type of the industrial furnace type set, represents the total number of components of the i-th type of industrial furnace in the set of industrial furnace types; , express The k-th type of component feature, b ij express The total number of component feature types in the .

[0067] S12, setting multiple characteristic types of nano thermal insulation materials to obtain a characteristic type set of nano thermal insulation materials , Indicates setting the characteristics of the i-th type of nano thermal insulation material, Indicates the total number of set nano thermal insulation material characteristic types; collects characteristic data of each type of nano thermal insulation material in the nano thermal insulation material type set according to the nano thermal insulation material characteristic type set to obtain a material characteristic data matrix ;as follows,

[0068] ;

[0069] in, Representing characteristic data of the jth type of the i-th type of nano thermal insulation material type in the nano thermal insulation material type set;

[0070] S13, setting the parameter type when applying nano thermal insulation material to the industrial kiln and the feature type corresponding to the product types produced by various industrial kilns, and obtaining the application parameter type set And the product feature type matrix c 2 , c 1i Indicates the i-th type of smearing parameter set, Indicates the total number of set smear parameter types; c 2 as follows,

[0071] ;

[0072] Among them, c 2ij represents the jth characteristic type of the i-th product type produced by the set industrial kiln, Indicates the total number of feature types corresponding to each product type produced by the industrial kiln. Indicates the total quantity of the product type set to be produced by the industrial furnace.

[0073] S2. Collect multiple sets of data of industrial kilns during production according to the industrial kiln component feature type matrix, material feature data matrix, coating parameter type set and product feature type matrix to obtain component feature data matrix set, coating parameter data matrix set, product feature data matrix, energy consumption level data set and historical material feature data matrix;

[0074] The final energy consumption mapping equation is constructed using component feature data matrix set, coating parameter data matrix set, product feature data matrix, energy consumption level data set and historical material feature data matrix;

[0075] The S2 comprises the following steps:

[0076] S21. Set multiple energy consumption levels to obtain an energy consumption level set. , represents the set i-th energy consumption level, Indicates the total number of set energy consumption levels.

[0077] S22, collect multiple sets of industrial kiln component feature data, coating parameter data, product feature data, energy consumption level data and material feature data of industrial kilns at production times in accordance with the energy consumption level set, coating parameter type set, industrial kiln component feature type matrix, product feature type matrix and material feature data matrix, and obtain a component feature data matrix set , smear parameter data matrix set , product feature data matrix d 3 , Energy Consumption Level Dataset And the historical material characteristic data matrix d 5 ;d 1i represents the component feature data matrix of the i-th group of industrial kilns collected during production at the historical moment, d 2i represents the smear parameter data matrix of the i-th group of industrial kilns collected during production at the historical moment, d 4i represents the energy consumption level data of the industrial kiln during production at the i-th historical moment, Indicates the total number of data sets collected during the production of industrial kilns at historical moments; d 3 d 2i d 5 d 1i They are as follows: ; ; ; ;

[0078] Among them, d 3ij represents the characteristic data of the jth type of products produced by the i-th group of industrial kilns at the historical moment, d 2ijk Indicates d 2i The kth type of coating parameter data when applying nano thermal insulation material on the jth component of the industrial furnace, d 5ij represents the characteristic data of the jth type of nano thermal insulation material collected during the production of the industrial kiln at the i-th historical moment, d 1ijk Indicates d 1i The characteristic data of the kth type of the jth component of the industrial furnace, represents the total number of characteristic data of the jth component of the industrial kiln during production at the i-th historical moment, Represents the total number of components of the industrial kiln during production at the i-th historical moment of the collection.

[0079] S23, constructing an initial energy consumption mapping equation; optimizing the initial energy consumption mapping equation using the component feature data matrix set, the smear parameter data matrix set, the product feature data matrix, the energy consumption level data set, and the historical material feature data matrix to obtain a final energy consumption mapping equation.

[0080] The S23 comprises the following steps:

[0081] S231, construct the initial energy consumption mapping equation as follows:

[0082] ;

[0083] In the formula, is the dependent variable of the initial energy consumption mapping equation, representing the energy consumption level data; 2i is the ith independent variable of the initial energy consumption mapping equation, e 1i for e 2i The coefficient of the independent variable, e 4ij is the first independent variable, e 3ij for e 4ij The coefficient of the independent variable, e 6i is the first independent variable, e 5i for e 6i The coefficient of the independent variable, e 8ij is the first independent variable, e 7ij for e 8ij The coefficient of the independent variable, is the offset of the initial energy consumption mapping equation, Indicates the maximum number of industrial furnace components, Indicates the maximum number of characteristics of industrial furnace components; , ; ceil represents the rounding function.

[0084] S232, substituting the data in the coating parameter type set, the industrial furnace component feature type matrix, the product feature type matrix and the historical material feature data matrix into the initial energy consumption mapping equation to obtain an initial energy consumption level mapping data set , It means that the energy consumption level mapping data is obtained by substituting the data of the industrial kiln corresponding to the i-th group of historical moments in the production in the smear parameter type set, the industrial kiln component feature type matrix, the product feature type matrix and the historical material feature data matrix into the initial energy consumption mapping equation.

[0085] S233. When the initial energy consumption level mapping data set contains energy consumption level mapping data which is different from the corresponding energy consumption level data in the energy consumption level data set, the initial energy consumption mapping equation is optimized until the initial energy consumption level mapping data set contains energy consumption level mapping data which is different from the corresponding energy consumption level data in the energy consumption level data set, thereby obtaining a final energy consumption mapping equation; otherwise, the initial energy consumption mapping equation does not need to be optimized, and the initial energy consumption mapping equation is used as the final energy consumption mapping equation.

[0086] Optimizing the initial energy consumption mapping equation in S233 includes the following steps:

[0087] S2331. Constructing the first locust population , f 1i represents the i-th locust in the first locust population, represents the size of the first locust population; sets the maximum number of iterations of the first locust population to , the current number of iterations is , respectively recorded as the first maximum number of iterations and the first current number of iterations; the search space dimension of the first locust population is , .

[0088] S2332, randomly generating data values ​​multiple times within the value range of the coefficients of each independent variable and the bias value of the initial energy consumption mapping equation as the initial position of each locust in the first locust population, and obtaining a first initial position matrix g 1 ;as follows,

[0089] ;

[0090] Among them, g 1ij Represents the component of the initial position of the i-th locust in the first locust population in the j-th search space dimension.

[0091] S2333: Mapping a data set according to the initial energy consumption level And energy consumption level dataset Construct the fitness function of the first locust population ;as follows,

[0092] ;

[0093] In the formula, β is a positive number, indicating the correction parameter.

[0094] S2334, start iteration, before iteration, set the first current iteration number Set to 1; the fitness function of the first locust population is used in the first round of iteration Calculate the first initial position matrix g 1 The fitness value of the initial position of each locust in the first fitness value set is obtained to obtain a first fitness value set; the maximum fitness value in the first fitness value set and the initial position of the corresponding locust are respectively used as the first global optimal fitness and the first global optimal position; the first initial position matrix g is calculated according to the first global optimal fitness and the first global optimal position. 1 The initial position of each locust in is updated; after the update is completed, the first current iteration number is Add 1 and enter the next iteration.

[0095] In each other iteration, the fitness function of the first locust population is used Calculate the fitness value of each locust position updated in the previous round of iterations to obtain a second fitness value set; use the maximum fitness value in the second fitness value set and the initial position of the corresponding locust as the second global optimal fitness and the second global optimal position respectively; update the position of each locust updated in the previous round of iterations according to the second global optimal fitness and the second global optimal position; after the update is completed, the first current iteration number Add 1 and enter the next iteration.

[0096] S2335, when When , stop the iteration and get the first final global optimal position, otherwise, continue to iterate until until the time; substitute the first final global optimal position into the initial energy consumption mapping equation to obtain the optimized energy consumption mapping equation; substitute the data in the coating parameter type set, industrial kiln component feature type matrix, product feature type matrix and historical material feature data matrix in S232 into the optimized energy consumption mapping equation to obtain the optimized energy consumption level mapping data set.

[0097] When the optimized energy consumption level mapping data set does not contain energy consumption level mapping data that is different from the corresponding energy consumption level data in the energy consumption level data set, the optimized energy consumption mapping equation is used as the final energy consumption mapping equation; otherwise, return to S2334 to continue iterating until the optimized energy consumption level mapping data set does not contain energy consumption level mapping data that is different from the corresponding energy consumption level data in the energy consumption level data set;

[0098] The locust optimization algorithm solves the optimization problem by simulating the foraging behavior of locust colonies. It can effectively perform global search and avoid premature convergence to the local optimal solution. It has fewer control parameters, which simplifies the algorithm tuning process and can usually find a higher quality solution in a shorter time. Based on the above advantages, the locust optimization algorithm is used in this scheme to perform multiple iterative optimizations on multiple independent variable coefficients and biases of the initial energy consumption mapping equation, and the difference between the mapping data of the initial energy consumption mapping equation and the actual data is used as its fitness function. Therefore, as the iteration proceeds, the mapping accuracy of the initial energy consumption mapping equation becomes higher and higher, and finally meets the mapping requirements.

[0099] S3. Preset the initial coating parameters to coat the parts of the industrial kiln to be coated and obtain the energy consumption level data during the production operation in conjunction with the material characteristic data matrix to obtain the initial energy consumption level data.

[0100] The S3 comprises the following steps:

[0101] S31, set the type data of the industrial kiln to be coated, recorded as the type data of the industrial kiln to be coated; according to the industrial kiln component feature type matrix The data of the type of industrial kiln to be coated is collected, and the characteristic data of multiple parts in the industrial kiln to be coated that need to be coated with nano-insulation materials are obtained to obtain the characteristic data matrix of the parts to be coated. ;as follows,

[0102] ;

[0103] in, represents the characteristic data of the jth type of the i-th component to be coated in the industrial kiln to be coated, represents the total number of types of feature data of the i-th component to be coated in the industrial kiln to be coated, It indicates the total number of parts that need to be coated in the industrial kiln to be coated.

[0104] S32, according to the characteristic data matrix of the component to be painted And the smudge parameter type set Set the coating parameter data coated on each component in the industrial kiln to be coated, and obtain the initial industrial kiln coating parameter data matrix h; as follows,

[0105] ;

[0106] Among them, h ij Represents the j-th type of coating parameter data of the ith component to be coated in the industrial kiln to be coated.

[0107] According to the product feature type matrix c 2 Obtain the product feature data that the industrial kiln to be coated needs to produce, and obtain the product feature data set to be produced , Indicates the characteristic data of the i-th type of the product that the industrial kiln to be coated needs to produce.

[0108] S33, traverse the nano thermal insulation material feature type set, and use the nano thermal insulation material corresponding to each nano thermal insulation material feature type in the nano thermal insulation material feature type set to coat each component in the industrial furnace to be coated according to the initial industrial furnace coating parameter data matrix h, to obtain the industrial furnace after initial coating; use the industrial furnace after initial coating to treat the product feature data set The corresponding products are produced and grouped according to energy consumption levels. Collect the corresponding energy consumption level data to obtain the initial energy consumption level data .

[0109] S4. Optimize the set initial coating parameters according to the initial energy consumption level data and in conjunction with the final energy consumption mapping equation to obtain a final industrial kiln nanomaterial coating parameter data matrix.

[0110] The S4 comprises the following steps:

[0111] S41. Setting energy consumption level data threshold.

[0112] S42, when the initial energy consumption level data When the energy consumption level data threshold is greater than or equal to the energy consumption level data threshold, the initial industrial kiln smear parameter data matrix h is optimized and adjusted until the initial energy consumption level data Until the energy consumption level data is less than the energy consumption level data threshold, the final industrial kiln nanomaterial coating parameter data matrix is ​​obtained; otherwise, there is no need to optimize and adjust the initial industrial kiln coating parameter data matrix h, and the initial industrial kiln coating parameter data matrix h is used as the final industrial kiln nanomaterial coating parameter data matrix.

[0113] The optimization and adjustment of the initial industrial furnace coating parameter data matrix h in S42 includes the following steps:

[0114] S421. Constructing the second locust population , f 2i represents the i-th locust in the second locust population, represents the size of the second locust population; sets the maximum number of iterations of the second locust population to , the current number of iterations is , respectively recorded as the second maximum number of iterations and the second current number of iterations; the search space dimension of the second locust population is .

[0115] S422: Setting the smear parameter type set The value interval of each type of smear parameter in is obtained, and the smear parameter value interval set c is obtained. 3 ;as follows,

[0116] ;

[0117] in, , They respectively represent the lower limit and upper limit of the value of the ith type of smear parameter in the smear parameter type set.

[0118] According to the smear parameter value interval set c 3 Set the initial position of each locust in the second locust population and obtain the initial position matrix set , g 2k represents the initial position matrix of the kth locust in the second locust population; as follows,

[0119] ;

[0120] Among them, g 2kij The component representing the initial position of the kth locust in the second locust population on the jth type of coating parameter data dimension of the i-th component to be coated in the industrial kiln to be coated is calculated as follows:

[0121] ;

[0122] Among them, rand kij Indicates that for g 2kij Generates a random number between 0 and 1.

[0123] S423, according to the initial energy consumption level data Constructing the fitness function of the second locust population ;as follows,

[0124] .

[0125] S424, start iteration, before iteration, set the second current iteration number Set to 1; the fitness function of the second locust population is used in the first round of iteration And calculate the initial position matrix set with the final energy consumption mapping equation The fitness value of the initial position matrix of each locust in the third fitness value set is obtained to obtain a third fitness value set; the maximum fitness value in the third fitness value set and the initial position of the corresponding locust are respectively used as the third global optimal fitness and the third global optimal position; the initial position matrix set is adjusted according to the third global optimal fitness and the third global optimal position. The initial position matrix of each locust in is updated; after the update is completed, the second current iteration number Add 1 and enter the next iteration;

[0126] The fitness function of the second locust population is used in each other iteration process The fitness value of each locust position updated in the previous round of iterations is calculated in conjunction with the final energy consumption mapping equation to obtain a fourth fitness value set; the maximum fitness value in the fourth fitness value set and the initial position of the corresponding locust are respectively used as the fourth global optimal fitness and the fourth global optimal position; the position of each locust updated in the previous round of iterations is updated again according to the fourth global optimal fitness and the fourth global optimal position; after the update is completed, the second current iteration number is Add 1 and enter the next iteration.

[0127] S425, when When , stop the iteration and get the second final global optimal position, otherwise, continue to iterate until until the second final global optimal position is used as the optimized industrial kiln coating parameter data matrix; according to the optimized industrial kiln coating parameter data matrix, the nano-insulation material corresponding to each nano-insulation material feature type in the nano-insulation material feature type set is used to coat each component in the industrial kiln to be coated, and the optimized coated industrial kiln is obtained; the optimized coated industrial kiln is used to treat the product feature data set The corresponding products are produced and grouped according to energy consumption levels. Collect corresponding energy consumption level data to obtain optimized energy consumption level data;

[0128] When the optimized energy consumption level data is less than the energy consumption level data threshold, the optimized industrial kiln coating parameter data matrix is ​​used as the final industrial kiln nanomaterial coating parameter data matrix; otherwise, return to S424 to continue iterating until the optimized energy consumption level data is less than the energy consumption level data threshold, and the final industrial kiln nanomaterial coating parameter data matrix is ​​obtained.

[0129] Embodiment 2

[0130] This embodiment discloses an energy-saving control system for industrial kilns based on nano thermal insulation materials. The system can implement the method of the above embodiment, including an industrial kiln component feature type setting module, a nano thermal insulation material feature type setting module, a nano thermal insulation material feature data collection module, a coating parameter type setting module, a product feature type setting module, a historical industrial kiln production data collection module, an energy consumption mapping equation construction module, a component feature data collection module, an energy consumption level collection module and a coating parameter optimization module;

[0131] The industrial furnace component feature type setting module is used to set multiple feature types corresponding to multiple components of multiple industrial furnace types to obtain an industrial furnace component feature type matrix;

[0132] The nano thermal insulation material characteristic type setting module is used to set the characteristic types of multiple nano thermal insulation material types to obtain a nano thermal insulation material characteristic type set;

[0133] The nano thermal insulation material characteristic data acquisition module is used to acquire characteristic data of corresponding nano thermal insulation materials according to the nano thermal insulation material characteristic type set to obtain a material characteristic data matrix;

[0134] The coating parameter type setting module is used to set the parameter type when applying nano thermal insulation material to the industrial furnace, and obtain a coating parameter type set;

[0135] The product feature type setting module is used to set the feature types corresponding to the product types produced by various industrial kilns to obtain a product feature type matrix;

[0136] The historical industrial kiln production data acquisition module is used to collect data of multiple groups of industrial kilns at historical moments during production according to the industrial kiln component feature type matrix, material feature data matrix, coating parameter type set and product feature type matrix, and obtain component feature data matrix set, coating parameter data matrix set, product feature data matrix, energy consumption level data set and historical material feature data matrix;

[0137] The energy consumption mapping equation construction module is used to construct a final energy consumption mapping equation using a component feature data matrix set, a coating parameter data matrix set, a product feature data matrix, an energy consumption level data set, and a historical material feature data matrix;

[0138] The component feature data acquisition module is used to acquire feature data of components of the industrial kiln to be coated, and obtain a feature data matrix of the components to be coated;

[0139] The energy consumption level acquisition module is used to acquire energy consumption level data during the production operation of coating the components of the industrial kiln to be coated according to the set initial coating parameters, and obtain initial energy consumption level data;

[0140] The coating parameter optimization module is used to optimize the set initial coating parameters according to the initial energy consumption level data to obtain the final industrial kiln nanomaterial coating parameter data matrix.

[0141] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0142] The preferred embodiments of the invention disclosed above are only used to help explain the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the invention, so that those skilled in the art can understand and use the invention well.

Claims

1. An industrial furnace energy-saving control method based on nano thermal insulation materials, characterized in that: The following steps are involved: S1. Set multiple feature types corresponding to multiple components of multiple industrial furnace types and feature types corresponding to the product types produced to obtain an industrial furnace component feature type matrix and a product feature type matrix; Collect characteristic data of nano thermal insulation materials corresponding to various types of nano thermal insulation materials to obtain a material characteristic data matrix; Set the parameter type when applying nano thermal insulation material to the industrial furnace, and obtain the application parameter type set; S2. Collect multiple sets of data of industrial kilns during production according to the industrial kiln component feature type matrix, material feature data matrix, coating parameter type set and product feature type matrix to obtain component feature data matrix set, coating parameter data matrix set, product feature data matrix, energy consumption level data set and historical material feature data matrix; The final energy consumption mapping equation is constructed using component feature data matrix set, coating parameter data matrix set, product feature data matrix, energy consumption level data set and historical material feature data matrix; S3, pre-setting the initial coating parameters to coat the components of the industrial kiln to be coated and obtaining the energy consumption level data during the production operation in conjunction with the material characteristic data matrix to obtain the initial energy consumption level data; S4, optimizing the set initial coating parameters according to the initial energy consumption level data and in conjunction with the final energy consumption mapping equation to obtain a final industrial kiln nanomaterial coating parameter data matrix; The S4 comprises the following steps: S41, setting energy consumption level data threshold; S42. When the initial energy consumption level data is greater than or equal to the energy consumption level data threshold, the initial industrial kiln coating parameter data matrix is ​​optimized and adjusted until the initial energy consumption level data is less than the energy consumption level data threshold, so as to obtain the final industrial kiln nanomaterial coating parameter data matrix; otherwise, there is no need to optimize and adjust the initial industrial kiln coating parameter data matrix, and the initial industrial kiln coating parameter data matrix is ​​used as the final industrial kiln nanomaterial coating parameter data matrix.

2. The method for energy-saving control of industrial furnaces based on nano thermal insulation materials according to claim 1 is characterized in that: The S1 comprises the following steps: S11, setting multiple industrial furnace types and nano thermal insulation material types to obtain an industrial furnace type set and a nano thermal insulation material type set; Then, multiple feature types corresponding to multiple component types of each industrial kiln in the industrial kiln type set that need to be coated with nano thermal insulation materials are set to obtain a matrix of feature types of industrial kiln components; S12, setting characteristic types of multiple nano thermal insulation materials to obtain a nano thermal insulation material characteristic type set; collecting characteristic data of each type of nano thermal insulation material in the nano thermal insulation material type set according to the nano thermal insulation material characteristic type set to obtain a material characteristic data matrix; S13. Setting parameter types when applying nano thermal insulation materials to industrial furnaces and feature types corresponding to product types produced by various industrial furnaces to obtain a coating parameter type set and a product feature type matrix.

3. The method for energy-saving control of industrial furnaces based on nano thermal insulation materials according to claim 2 is characterized in that: The S2 comprises the following steps: S21, setting multiple energy consumption levels to obtain an energy consumption level set; S22, collecting multiple sets of industrial kiln component feature data, coating parameter data, product feature data, energy consumption level data and material feature data of industrial kilns at production times in cooperation with the energy consumption level set, coating parameter type set, industrial kiln component feature type matrix, product feature type matrix and material feature data matrix, to obtain component feature data matrix set, coating parameter data matrix set, product feature data matrix, energy consumption level data set and historical material feature data matrix; S23, constructing an initial energy consumption mapping equation; optimizing the initial energy consumption mapping equation using the component feature data matrix set, the smear parameter data matrix set, the product feature data matrix, the energy consumption level data set, and the historical material feature data matrix to obtain a final energy consumption mapping equation.

4. The method for energy-saving control of industrial furnaces based on nano thermal insulation materials according to claim 3 is characterized in that: The S23 comprises the following steps: S231, constructing an initial energy consumption mapping equation; S232, substituting the data in the coating parameter type set, the industrial furnace component feature type matrix, the product feature type matrix, and the historical material feature data matrix into the initial energy consumption mapping equation to obtain an initial energy consumption level mapping data set; S233: Determine whether to optimize the initial energy consumption mapping equation according to the initial energy consumption level mapping data set.

5. The method for energy-saving control of industrial furnaces based on nano thermal insulation materials according to claim 4 is characterized in that: The S233 comprises the following steps: S2331. When the initial energy consumption level mapping data set contains energy consumption level mapping data which is different from the corresponding energy consumption level data in the energy consumption level data set, the initial energy consumption mapping equation is optimized until the initial energy consumption level mapping data set contains no initial energy consumption level mapping data which is different from the corresponding energy consumption level data in the energy consumption level data set, and a final energy consumption mapping equation is obtained; otherwise, there is no need to optimize the initial energy consumption mapping equation, and the initial energy consumption mapping equation is used as the final energy consumption mapping equation.

6. The method for energy-saving control of industrial furnaces based on nano thermal insulation materials according to claim 5 is characterized in that: In S2331, the locust optimization algorithm is used to optimize the initial energy consumption mapping equation.

7. The method for energy-saving control of industrial furnaces based on nano thermal insulation materials according to claim 6 is characterized in that: The S3 comprises the following steps: S31, setting the type data of the industrial kiln to be coated, recorded as the type data of the industrial kiln to be coated; collecting the characteristic data of multiple components in the industrial kiln to be coated that need to be coated with nano thermal insulation materials according to the characteristic type matrix of industrial kiln components and the type data of the industrial kiln to be coated, and obtaining the characteristic data matrix of the components to be coated; S32, setting coating parameter data coated on each component in the industrial kiln to be coated according to the feature data matrix of the component to be coated and the coating parameter type set, to obtain an initial industrial kiln coating parameter data matrix; Then, according to the product feature type matrix, the product feature data that the industrial kiln to be coated needs to produce is obtained to obtain a feature data set of the product to be produced; S33, traverse the nano thermal insulation material characteristic type set, and use the nano thermal insulation material corresponding to each nano thermal insulation material characteristic type in the nano thermal insulation material characteristic type set to coat each component in the industrial kiln to be coated according to the initial industrial kiln coating parameter data matrix to obtain the industrial kiln after initial coating; use the industrial kiln after initial coating to produce the product corresponding to the product characteristic data set to be produced and collect the corresponding energy consumption level data according to the energy consumption level set to obtain the initial energy consumption level data.

8. The method for energy-saving control of industrial furnaces based on nano thermal insulation materials according to claim 7 is characterized in that: The optimization and adjustment of the initial industrial kiln coating parameter data matrix in S42 includes the following steps: S421, constructing a second locust population; setting the maximum number of iterations of the second locust population to , the current number of iterations is , respectively recorded as the second maximum number of iterations and the second current number of iterations; S422, setting the value interval of each type of smear parameter in the smear parameter type set to obtain a smear parameter value interval set; setting the initial position of each locust in the second locust population according to the smear parameter value interval set to obtain an initial position matrix set; S423, constructing a fitness function of the second locust population according to the initial energy consumption level data; S424, start iteration; in each round of iteration, use the fitness function of the second locust population and cooperate with the final energy consumption mapping equation to calculate the fitness value of each locust position updated in the previous round of iteration, and update the position of each locust updated in the previous round of iteration again; S425, when When , stop the iteration and get the second final global optimal position, otherwise, continue to iterate until until the time; the second final global optimal position is used as the optimized industrial kiln coating parameter data matrix; according to the optimized industrial kiln coating parameter data matrix, each component in the industrial kiln to be coated is coated with the nano-insulation material corresponding to each nano-insulation material feature type in the nano-insulation material feature type set to obtain the optimized coated industrial kiln; the optimized coated industrial kiln is used to produce the product corresponding to the product feature data set to be produced and the corresponding energy consumption level data is collected according to the energy consumption level set to obtain the optimized energy consumption level data; When the optimized energy consumption level data is less than the energy consumption level data threshold, the optimized industrial kiln coating parameter data matrix is ​​used as the final industrial kiln nanomaterial coating parameter data matrix; otherwise, return to S424 to continue iterating until the optimized energy consumption level data is less than the energy consumption level data threshold, and the final industrial kiln nanomaterial coating parameter data matrix is ​​obtained.

9. A system for implementing the method for energy-saving and control of industrial furnaces based on nano thermal insulation materials as described in any one of claims 1 to 8.

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