CN113130015B - Method, device, equipment and readable storage medium for evaluating desulfurizing agent reactivity - Google Patents
Method, device, equipment and readable storage medium for evaluating desulfurizing agent reactivity Download PDFInfo
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Abstract
The application provides a method, a device, equipment and a readable storage medium for evaluating the reactivity of a desulfurizing agent, wherein the method comprises the following steps: obtaining the information of the reactivity evaluation factors of the desulfurizing agent, test data and expert scores; constructing an evaluation factor comparison matrix according to the evaluation factor information; calculating the evaluation factor weight vector according to the evaluation factor comparison matrix; constructing a gray weight matrix of the evaluation factors according to the evaluation factor information, the test data and the expert scores; and calculating a comprehensive evaluation vector according to the evaluation factor weight vector and the gray weight matrix, and obtaining the reactive grade of the desulfurizing agent under the working condition needing to be evaluated according to the comprehensive evaluation vector. The application adopts the analytic hierarchy process to determine the weight of the influence factors of the reactivity of the desulfurizing agent, and the method is simple and easy to implement, has wide applicability and strong practicability.
Description
Technical Field
The application relates to the technical field of energy conservation and environmental protection, in particular to a method, a device and equipment for evaluating the reactivity of a desulfurizing agent and a readable storage medium.
Background
At present, the effective utilization of the desulfurizing agent is not considered much in industry, the utilization rate of the desulfurizing agent is seriously unsaturated, the conversion rate of limestone and calcium is 30-40% in most of the desulfurizing processes of power plants, and the utilization rate of the desulfurizing agent has a large rising space. Because the desulfurization working condition has great influence on the reactivity of the desulfurizing agent, and the desulfurization working condition has a certain adjusting range, the particle size, the calcium-sulfur ratio, the desulfurization temperature and the like of the desulfurizing agent can be controlled manually. The improvement of the reactivity of the desulfurizing agent is not only beneficial to the improvement of the utilization rate of the desulfurizing agent, but also can improve the desulfurizing efficiency of the desulfurizing agent, so that the improvement of the reactivity of the desulfurizing agent is more beneficial, but a method for evaluating the reactivity of the desulfurizing agent under different working conditions is not available in the field of desulfurizing agents at present.
Disclosure of Invention
The present application aims to provide a method, an apparatus, a device and a readable storage medium for evaluating the reactivity of a desulfurizing agent, so as to solve the above problems.
In order to achieve the above object, the embodiment of the present application provides the following technical solutions:
in one aspect, embodiments of the present application provide a method for evaluating reactivity of a desulfurizing agent, the method including:
obtaining information of a desulfurizing agent reactivity evaluation factor, test data and expert scores, wherein the test data comprises the conversion rate of the desulfurizing agent under the reaction conditions, the reaction conditions comprise working conditions needing to be evaluated and working conditions not needing to be evaluated, and the expert scores comprise scores of the expert on all evaluation factors under the working conditions needing to be evaluated;
constructing an evaluation factor comparison matrix according to the evaluation factor information;
calculating the evaluation factor weight vector according to the evaluation factor comparison matrix;
constructing a gray weight matrix of the evaluation factors according to the evaluation factor information, the test data and the expert scores;
and calculating a comprehensive evaluation vector according to the evaluation factor weight vector and the gray weight matrix, and obtaining the reactive grade of the desulfurizing agent under the working condition needing to be evaluated according to the comprehensive evaluation vector.
Optionally, after the evaluation factor comparison matrix is constructed according to the evaluation factor information, the method further includes:
calculating a consistency index of the evaluation factor comparison matrix;
acquiring a random consistency index of the evaluation factor comparison matrix;
according to the consistency index of the evaluation factor comparison matrix and the random consistency index of the evaluation factor comparison matrix, calculating to obtain the consistency ratio of the evaluation factor comparison matrix;
judging whether the consistency ratio of the evaluation factor comparison matrix meets the requirement, if so, calculating the weight vector of the evaluation factor according to the evaluation factor comparison matrix, and if not, reconstructing the evaluation factor comparison matrix.
Optionally, the constructing a gray weight matrix of the evaluation factor according to the evaluation factor information, the test data and the expert score includes:
constructing a scoring matrix according to the scoring factor information, the test data and the expert scores;
calculating expert scoring weight vectors;
determining whitening weight functions of different activity levels according to the scoring matrix;
and constructing a gray weight matrix of the evaluation factor according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels.
Optionally, the constructing a gray weight matrix of the evaluation factor according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels includes:
according to the whitening weight functions, the scoring matrixes and the expert scoring weight vectors of the different activity levels, calculating gray statistic values of each evaluation factor under the different activity levels;
calculating the sum of gray statistic values of all the evaluation factors according to the gray statistic values of all the evaluation factors under different activity levels;
calculating gray weight values of all the evaluation factors according to the gray statistic values of all the evaluation factors under different activity levels and the sum of the gray statistic values of all the evaluation factors, and obtaining gray weight vectors of all the evaluation factors according to the gray weight values of all the evaluation factors;
and constructing a gray weight matrix of the evaluation factors according to the gray weight vector of each evaluation factor.
In a second aspect, an embodiment of the present application provides an apparatus for evaluating reactivity of a desulfurizing agent, the apparatus comprising: the device comprises a first acquisition module, a first construction module, a first calculation module, a second construction module and a second calculation module.
The first acquisition module is used for acquiring information of the desulfurizer reactivity evaluation factors, test data and expert scores, wherein the test data comprise conversion rate of the desulfurizer under the reaction conditions, the reaction conditions comprise working conditions needing evaluation and working conditions not needing evaluation, and the expert scores comprise scores of the expert on each evaluation factor under the working conditions needing evaluation;
the first construction module is used for constructing an evaluation factor comparison matrix according to the evaluation factor information;
the first calculation module is used for calculating the evaluation factor weight vector according to the evaluation factor comparison matrix;
the second construction module is used for constructing a gray weight matrix of the evaluation factors according to the evaluation factor information, the test data and the expert scores;
the second calculation module is used for calculating a comprehensive evaluation vector according to the evaluation factor weight vector and the gray weight matrix, and obtaining the reactivity grade of the desulfurizing agent under the working condition needing to be evaluated according to the comprehensive evaluation vector.
Optionally, the apparatus further includes:
the third calculation module is used for calculating the consistency index of the evaluation factor comparison matrix;
the second acquisition module is used for acquiring the random consistency index of the evaluation factor comparison matrix;
the fourth calculation module is used for calculating the consistency ratio of the evaluation factor comparison matrix according to the consistency index of the evaluation factor comparison matrix and the random consistency index of the evaluation factor comparison matrix;
the first judging module is used for judging whether the consistency proportion of the evaluation factor comparison matrix meets the requirement, if so, calculating the evaluation factor weight vector according to the evaluation factor comparison matrix, and if not, reconstructing the evaluation factor comparison matrix.
Optionally, the second building module includes:
the first construction unit is used for constructing a scoring matrix according to the evaluation factor information, the test data and the expert scores;
a first calculation unit for calculating expert scoring weight vectors;
a second calculation unit, configured to determine whitening weight functions of different activity levels according to the scoring matrix;
and the second construction unit is used for constructing a gray weight matrix of the evaluation factors according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels.
Optionally, the second building unit includes:
the first calculating subunit is used for calculating gray statistic values of each evaluation factor under different activity levels according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels;
the second calculating subunit is used for calculating the sum of the gray statistic values of all the evaluation factors according to the gray statistic values of all the evaluation factors under different activity levels;
the third computing subunit is used for computing the gray weight value of each evaluation factor according to the gray statistic value of each evaluation factor under different activity levels and the sum of the gray statistic values of each evaluation factor, and obtaining the gray weight vector of each evaluation factor according to the gray weight value of each evaluation factor;
and the construction subunit is used for constructing the gray weight matrix of the evaluation factors according to the gray weight vectors of the evaluation factors.
In a third aspect, embodiments of the present application provide an apparatus for evaluating the reactivity of a desulfurizing agent, the apparatus including a memory and a processor. The memory is used for storing a computer program; the processor is used for realizing the step of the method for evaluating the reactivity of the desulfurizing agent when executing the computer program.
In a fourth aspect, an embodiment of the present application provides a readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the above-described method for evaluating the reactivity of a desulfurizing agent.
The beneficial effects of the application are as follows:
the application adopts an analytic hierarchy process to determine the weight of the influence factor of the desulfurizer reactivity, evaluates the desulfurizer reactivity grade under the working condition, and provides a reference basis for improving the desulfurizer reactivity.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for evaluating the reactivity of a desulfurizing agent according to an embodiment of the present application;
FIG. 2 is a schematic structural diagram of an evaluation apparatus for reactivity of a desulfurizing agent according to an embodiment of the present application;
FIG. 3 is a schematic structural view of an apparatus for evaluating reactivity of a desulfurizing agent according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that: like reference numerals or letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Example 1
The present embodiment provides a method for evaluating the reactivity of a desulfurizing agent, which includes step S1, step S2, step S3, step S4, and step S5.
S1, acquiring desulfurizer reactivity evaluation factor information, test data and expert scores, wherein the test data comprise conversion rate of the desulfurizer under reaction conditions, the reaction conditions comprise working conditions needing evaluation and working conditions not needing evaluation, and the expert scores comprise scores of the expert on all evaluation factors under the working conditions needing evaluation;
s2, constructing an evaluation factor comparison matrix according to the evaluation factor information;
s3, calculating the evaluation factor weight vector according to the evaluation factor comparison matrix;
s4, constructing a gray weight matrix of the evaluation factors according to the evaluation factor information, the test data and the expert scores;
and S5, calculating a comprehensive evaluation vector according to the evaluation factor weight vector and the gray weight matrix, and obtaining the reactivity grade of the desulfurizing agent under the working condition needing to be evaluated according to the comprehensive evaluation vector.
In the embodiment, the weight of the influence factors of the reactivity of the desulfurizing agent is determined by adopting an analytic hierarchy process, the reactivity level of the desulfurizing agent under the desulfurizing condition is evaluated, and a reference basis is provided for improving the reactivity of the desulfurizing agent.
The analytic hierarchy process is an evaluation method combining qualitative analysis and quantitative analysis, and has certain practicability when applied to evaluating the risk level of engineering projects. When the historical data and the real information are relatively lacking, only the risk management expert is matched, qualitative description is firstly carried out, the expert scores the weight of each influence factor quantitatively described by experience, and consistency test is carried out, so that some meaningful and valuable qualitative conclusions can be obtained. In the embodiment, the analytic hierarchy process is applied to the evaluation of the reactivity of the desulfurizing agent, and the method has higher reliability by using the quantitative evaluation factors of experimental data compared with the quantitative evaluation factors of expert evaluation.
The other part is to carry out gray grading on the activity of the desulfurizing agent by using a gray fuzzy theory, the fuzzy mathematics can be applied to events with uncertainty and ambiguity, and the gray system theory can solve the problem of small information quantity, so that the gray fuzzy theory organically combining the gray system theory and the fuzzy mathematic theory can be applied to the grade evaluation of the reactivity of the desulfurizing agent.
In a specific embodiment of the disclosure, step S11 may further be included after step S1.
And S11, acquiring different activity grade information of the desulfurizing agent, and matching the different activity grade information with a corresponding score range.
In this embodiment, the activity level information is divided into five levels, a first level is a strong activity level, a second level is a high activity level, a third level is a medium activity level, a fourth level is a low activity level, a fifth level is a weak activity level, the strong activity fraction value range is 8-10, the high activity fraction value range is 6-8, the medium activity fraction value range is 4-6, the low activity fraction value range is 2-4, and the weak activity fraction value range is 0-2.
In a specific embodiment of the disclosure, the step S2 may further include a step S21 and a step S22.
S21, carrying out pairwise comparison on the evaluation factors to obtain an importance comparison result, and quantifying the importance comparison result to obtain a first result;
and S22, constructing an evaluation factor comparison matrix according to the first result.
Step S21 is specifically that two evaluation factors x and y are selected for comparison every time, and if the importance of the evaluation factors x and y is the same, the result is quantized to 1; if the importance of the evaluation factor x is slightly stronger than that of the evaluation factor y, the result is quantized to 3; if the importance of the evaluation factor x is stronger than that of the evaluation factor y, quantifying the result to be 5; if the evaluation factor x is more important than the evaluation factor y, the result is quantized to 7; if the evaluation factor x is more important than the evaluation factor y, the result is quantized to 9;
in step S22, an evaluation factor comparison matrix a is specifically constructed according to formula (1), where formula (1) is:
in the formula (1), a xy Representing the importance comparison result of the evaluation factor x and the evaluation factor y;
in a specific embodiment of the disclosure, after the step S2, step S23, step S24, step S25, and step S26 may further be included.
S23, calculating a consistency index of the evaluation factor comparison matrix;
s24, acquiring a random consistency index of the evaluation factor comparison matrix;
step S25, according to the consistency index of the evaluation factor comparison matrix and the random consistency index of the evaluation factor comparison matrix, calculating to obtain the consistency ratio of the evaluation factor comparison matrix;
and S26, judging whether the consistency proportion of the evaluation factor comparison matrix meets the requirement, if so, calculating the evaluation factor weight vector according to the evaluation factor comparison matrix, and if not, reconstructing the evaluation factor comparison matrix.
In step S23, the consistency index CI of the evaluation factor comparison matrix is calculated by the formula (2), where the formula (2) is:
in the formula (2), q is an evaluation factor comparisonThe order, lambda, of the matrix max Is the maximum eigenvalue of the evaluation factor comparison matrix;
in step S25, the consistency ratio of the evaluation factor comparison matrix is calculated by the formula (3), where the formula (3) is:
in the formula (3), CI is a consistency index of the evaluation factor comparison matrix, and RI is a random consistency index of the evaluation factor comparison matrix;
in step S26, it is specifically determined whether the consistency ratio of the evaluation factor comparison matrix is less than 0.10, if so, the evaluation factor weight vector is calculated according to the evaluation factor comparison matrix, and if so, the evaluation factor comparison matrix is reconstructed.
In a specific embodiment of the disclosure, step S3 is specifically that the evaluation factor weight vector is calculated by the formula (4) and the formula (5), where the formula (4) and the formula (5) are:
W＝(w 1 、w 2 、……、w n ) (5)
in the formula (4) and the formula (5), w i The weight is an evaluation factor weight, and W is an evaluation factor weight vector;
in a specific embodiment of the disclosure, the step S4 may further include a step S41, a step S42, a step S43, and a step S44.
S41, constructing a scoring matrix according to the evaluation factor information, the test data and expert scores;
step S42, calculating expert scoring weight vectors;
s43, determining whitening weight functions of different activity levels according to the scoring matrix;
and S44, constructing a gray weight matrix of the evaluation factor according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels.
The step S41 specifically includes constructing a scoring matrix according to a formula (6), where the formula (6) is:
in the formula (6), m is the number of evaluation factors, n is the result of adding 1 to the number of experts (the test data is set as one expert), and the xth expert scores the kth evaluation factor as k;
step S42 is specifically that two experts x and y are selected for comparison each time, and if the importance of the expert a is the same as that of the expert b, the result is quantized to 1; if the importance of the expert a and the expert b is slightly strong, the result is quantized to 3; if the importance of the expert a and the expert b is stronger, quantifying the result to be 5; if expert a is more important than expert b, quantifying the result to 7; if expert a is of greater importance than expert b, the result is quantized to 9;
constructing an expert weight comparison matrix through a formula (7), wherein the formula (7) is as follows:
in formula (7), b xy To represent the result of the x, y expert importance comparison;
calculating the expert scoring weight vector through a formula (8) and a formula (9), wherein the formula (8) and the formula (9) are as follows:
R＝(r 1 、r 2 、……、r n ) (9)
in the formula (8) and the formula (9), r i Is expert scoring weight, R is expert scoring weight vector.
In step S43, a strong active level whitening weight function is constructed according to the formula (10), where the formula (10) is:
in the formula (10), f 1 K is the x-th expert, and the evaluation factor of the y-th expert is scored as k;
constructing a high-activity whitening weight function through a formula (11), wherein the formula (11) is as follows:
in formula (13), f 2 K is the x-th expert, and the evaluation factor of the y-th item is scored as k;
the method comprises the steps of constructing an active level whitening weight function through a formula (12), wherein the formula (12) is as follows:
in the formula (12), f 3 K is the x-th expert, and the evaluation factor of the y-th expert is scored as k;
constructing a low-activity whitening weight function through a formula (13), wherein the formula (13) is as follows:
in formula (13), f 4 K is the x-th expert, and the evaluation factor of the y-th item is scored as k;
constructing a weak active level whitening weight function by the formula (14), wherein the formula (14) is as follows:
in formula (14), f 5 K is the x-th expert, and the evaluation factor of the y-th expert is scored as k;
in a specific embodiment of the disclosure, the step S44 may further include a step S441, a step S442, a step S443, and a step S444.
Step S441, calculating gray statistic values of each evaluation factor under different activity levels according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels;
step S442, calculating the sum of gray statistic values of all the evaluation factors according to the gray statistic values of all the evaluation factors under different activity levels;
step S443, calculating the gray weight value of each evaluation factor according to the sum of the gray statistic value of each evaluation factor under different activity levels and the gray statistic value of each evaluation factor, and obtaining the gray weight vector of each evaluation factor according to the gray weight value of each evaluation factor;
and step 444, constructing a gray weight matrix of the evaluation factors according to the gray weight vectors of the evaluation factors.
The step S441 is specifically configured to construct a gray statistic value of the i-assessment factor under a strong active level according to a formula (15), where the formula (15) is:
h i1 ＝r 1 f 1 (k 1i )+r 2 f 1 (k 2i )+…+r n f 1 (k ni ) (15)
the gray statistic value of the i evaluation factor under the high activity level is constructed through a formula (16), wherein the formula (16) is as follows:
h i2 ＝r 1 f 2 (k 1i )+r 2 f 1 (k 2i )+…+r n f 1 (k ni ) (16)
the gray statistic value of the i evaluation factor at the middle active level is constructed through a formula (17), wherein the formula (17) is as follows:
h i3 ＝r 1 f 3 (k 1i )+r 2 f 3 (k 2i )+…+r n f 3 (k ni ) (17)
the gray statistics of the i assessment factors at low activity level are constructed by the formula (18), the formula (18) is:
h i4 ＝r 1 f 4 (k 1i )+r 2 f 4 (k 2i )+…+r n f 4 (k ni ) (18)
the gray statistic of the i evaluation factor at weak active level is constructed by the formula (19), wherein the formula (19) is as follows:
h i5 ＝r 1 f 5 (k 1i )+r 2 f 5 (k 2i )+…+r n f 5 (k ni ) (19)
in step S442, the i-assessment factor gray statistic is calculated according to the formula (20), where the formula (20) is:
in the formula (20), h i Evaluating a factor gray statistic for i;
in step S443, the gray weight value of each evaluation factor is calculated according to the formula (21), where the formula (21) is:
in the formula (21), C ij The gray weight value of the i evaluation factor under the active level j is 1, 2, 3, 4 and 5;
the gray weight vector of each evaluation factor is calculated by the formula (22), the formula (22) is:
c i ＝(c i1 ，c i2 ，c i3 ，c i4 ，c i5 ) (22)
in the formula (22), C i The gray weight vector for each evaluation factor, i is 1, 2, 3 … …, m;
step S444 is specifically implemented by constructing a gray weight matrix of the evaluation factor according to the formula (23), where the formula (23) is:
in the formula (23), C is a gray weight matrix of m evaluation factors, and m is the number of the evaluation factors;
in step S5, the comprehensive evaluation vector is calculated according to the formula (24), where the formula (24) is:
in the formula (24), Z is a comprehensive evaluation vector, C is a gray weight matrix of m evaluation factors, and W is an evaluation factor weight vector.
In a specific embodiment, the desulfurizing agent is calcium carbonate, and the desulfurizing reaction of the desulfurizing agent in the embodiment needs to evaluate the condition that the desulfurizing temperature is 850 ℃ and the desulfurizing reaction atmosphere condition is 5% O 2 、15％CO 2 、2000ppmSO 2 、N 2 Balance, the gas volume flow was kept at 100ml/min throughout the experimental procedure.
The desulfurization temperature is 800-950 ℃ and CO 2 The concentration range is 0-45% SO 2 The concentration range is 1000ppm to 4000ppm.
The experimental procedure was as follows:
in this case, calcium carbonate is selected, 9mg of calcium carbonate (about 5mg of calcium oxide after calcination) is weighed and put into a Micro-thermogravimetric analyzer Micro-TGA, the temperature is raised to 850 ℃ at 20 ℃/min under the nitrogen condition, and then 5% O is introduced 2 、15％CO 2 SO of 2000ppm 2 The other gas was nitrogen, and after 300 minutes of reaction, the conversion was calculated by the formula (27).
Wherein m0 is the initial mass of the desulfurizing agent, mg; Δm is the increase in mass of the desulfurizing agent during the reaction, mg; m is M CaSO4 Is CaSO 4 G/mol; m is M CaCO3 Is CaCO 3 Molar mass, g/mol.
Then repeating the steps to sequentially change the experimental conditions: (1) only changing the desulfurization temperature to 800 ℃ and 950 ℃ to obtain the conversion rate of the calcium in the desulfurizing agent; (2) changing CO only 2 The concentration is 0 and 45 percent to obtain the conversion rate of the desulfurizing agent calcium; (3) change only SO 2 The desulfurizing agent calcium conversion was obtained at concentrations of 1000ppm and 4000ppm, and the test data obtained are shown in the following table:
the evaluation factors in the process of evaluating the reactivity of the desulfurizing agent are sequentially the desulfurizing temperature and SO 2 Concentration, CO 2 Concentration.
Firstly, obtaining an evaluation factor weight vector, specifically, w= (0.14286,0.71429,0.14286); scoring the evaluation factors by test data and an expert to construct a scoring matrixConsidering the equivalent importance of experimental data calculation results and expert experience scores, the expert score weight vector is r= (0.5 );
the first evaluation factor gray statistic values can be obtained through the steps:
h 11 ＝0；h 12 ＝0；h 13 ＝0.5；h 14 ＝0.49；h 15 =0, and the gray weight values of the first evaluation factor (desulfurization temperature) at each active level are obtained as follows: c (C) 11 ＝0；C 12 ＝0；C 13 ＝0.50505；C 14 ＝0.49495；C 15 And in the same way a second evaluation factor (O 2 Concentration) is: c (C) 21 ＝0；C 22 ＝0；C 23 ＝0；C 24 ＝1；C 25 =0, third evaluation factor (CO 2 Concentration) is: c (C) 31 ＝0；C 32 ＝0；C 33 ＝0；C 34 ＝0；C 35 =1, a gray weight matrix of the evaluation factor is obtained,further, a comprehensive evaluation vector is obtained, z=w·c= (0,0,0.07214,0.78490,0.14286);
the probability of the calcium carbonate desulfurizing agent in the medium activity grade is 0.07214 through comprehensive evaluation vectors; the probability at low activity level is 0.78490; the probability at the weak activity scale is 0.14286. Therefore, the desulfurizing agent has the highest probability of low activity level under the desulfurizing working condition to be evaluated, and has a large lifting space.
Example 2
As shown in fig. 2, the present embodiment provides an apparatus for evaluating reactivity of a desulfurizing agent, the apparatus comprising: a first acquisition module 701, a first construction module 702, a first calculation module 703, a second construction module 704 and a second calculation module 705.
The first obtaining module 701 is configured to obtain information of a desulfurizing agent reactivity evaluation factor, test data and an expert score, where the test data includes a conversion rate of the desulfurizing agent under a reaction condition, the reaction condition includes a working condition requiring evaluation and a working condition not requiring evaluation, and the expert score includes a score of each evaluation factor performed by an expert under the working condition requiring evaluation;
the first construction module 702 is configured to construct an evaluation factor comparison matrix according to the evaluation factor information;
the first calculating module 703 is configured to calculate the evaluation factor weight vector according to the evaluation factor comparison matrix;
the second construction module 704 is configured to construct a gray weight matrix of the evaluation factor according to the evaluation factor information, the test data and the expert score;
the second calculation module 705 is configured to calculate a comprehensive evaluation vector according to the evaluation factor weight vector and the gray weight matrix, and obtain a reactive level of the desulfurizing agent under the working condition to be evaluated according to the comprehensive evaluation vector.
In one embodiment of the present disclosure, the apparatus further comprises a second acquisition module 706.
The second obtaining module 706 is configured to obtain different activity level information of the desulfurizing agent, and match a corresponding score range for the different activity level information.
In a specific embodiment of the disclosure, the first building block 702 may further include a comparison unit 7021 and a first building unit 7022.
The comparison unit 7021 is configured to compare the evaluation factors in pairs to obtain an importance comparison result, and quantify the importance comparison result to obtain a first result;
the first construction unit 7022 is configured to construct an evaluation factor comparison matrix according to the first result.
In a specific embodiment of the disclosure, the apparatus further includes a third calculation module 707, a third acquisition module 708, a fourth calculation module 709, and a determination module 710.
The third calculation module 707 is configured to calculate a consistency index of the evaluation factor comparison matrix;
the third obtaining module 708 is configured to obtain a random consistency index of the evaluation factor comparison matrix;
the fourth calculating module 709 is configured to calculate a consistency ratio of the evaluation factor comparison matrix according to the consistency index of the evaluation factor comparison matrix and the random consistency index of the evaluation factor comparison matrix;
the judging module 710 is configured to judge whether the consistency ratio of the evaluation factor comparison matrix meets the requirement, calculate the evaluation factor weight vector according to the evaluation factor comparison matrix if the consistency ratio meets the requirement, and reconstruct the evaluation factor comparison matrix if the consistency ratio does not meet the requirement.
In a specific embodiment of the disclosure, the second construction module 704 includes a second construction unit 7041, a first calculation unit 7042, a second calculation unit 7043, and a third construction unit 7044.
The second construction unit 7041 is configured to construct a scoring matrix according to the evaluation factor information, the test data and the expert scores;
the first calculating unit 7042 is configured to calculate an expert scoring weight vector;
the second calculating unit 7043 is configured to determine whitening weight functions of different activity levels according to the scoring matrix;
the third construction unit 7044 is configured to construct a gray weight matrix of the evaluation factor according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels.
In one embodiment of the present disclosure, the third building unit 7044 includes a first computing subunit 70441, a second computing subunit 70442, a third computing subunit 70443, and a building subunit 70444.
The first calculating subunit 70441 is configured to calculate a gray statistic value of each evaluation factor under different activity levels according to the whitening weight function, the scoring matrix and the expert scoring weight vector of the different activity levels;
the second calculating subunit 70442 is configured to calculate a sum of the gray statistics of each evaluation factor according to the gray statistics of each evaluation factor at different activity levels;
the third computing subunit 70443 is configured to calculate a gray weight value of each evaluation factor according to a sum of the gray statistics value of each evaluation factor under different activity levels and the gray statistics value of each evaluation factor, and obtain a gray weight vector of each evaluation factor according to the gray weight value of each evaluation factor;
the construction subunit 70444 is configured to construct a gray weight matrix of the evaluation factors according to the gray weight vectors of the evaluation factors.
It should be noted that, regarding the apparatus in the above embodiments, the specific manner in which the respective modules perform the operations has been described in detail in the embodiments regarding the method, and will not be described in detail herein.
Example 3
Corresponding to the above method embodiments, the present disclosure also provides an apparatus for evaluating the reactivity of a desulfurizing agent, which is described below, and a method for evaluating the reactivity of a desulfurizing agent described above may be referred to correspondingly to each other.
Fig. 3 is a block diagram of an evaluation apparatus 800 for desulfurizing agent reactivity, according to an exemplary embodiment. As shown in fig. 3, the apparatus 800 for evaluating the reactivity of the desulfurizing agent may include: a processor 801, a memory 802. The apparatus 800 for evaluating the reactivity of the desulfurizing agent may further include one or more of a multimedia component 803, an input/output (I/O) interface 804, and a communication component 805.
Wherein the processor 801 is configured to control the overall operation of the apparatus 800 for evaluating the reactivity of the desulfurizing agent to perform all or part of the steps of the method for evaluating the reactivity of the desulfurizing agent described above. The memory 402 is used to store various types of data to support the operation of the devulcanizer reactivity evaluation device 800, which may include, for example, instructions for any application or method operating on the devulcanizer reactivity evaluation device 800, as well as application related data such as contact data, messaging, pictures, audio, video, etc. The Memory 802 may be implemented by any type or combination of volatile or non-volatile Memory devices, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia component 803 may include a screen and an audio component. Wherein the screen may be, for example, a touch screen, the audio component being for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory 802 or transmitted through the communication component 805. The audio assembly further comprises at least one speaker for outputting audio signals. The I/O interface 804 provides an interface between the processor 801 and other interface modules, which may be a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication unit 805 is configured to perform wired or wireless communication between the apparatus 800 for evaluating reactivity of the desulfurizing agent and other apparatuses. Wireless communication, such as Wi-Fi, bluetooth, near field communication (Near FieldCommunication, NFC for short), 2G, 3G or 4G, or a combination of one or more thereof, the respective communication component 805 may thus comprise: wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the apparatus 800 for evaluating the reactivity of the desulfurizing agent may be implemented by one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASIC), digital signal processor (DigitalSignal Processor, abbreviated as DSP), digital signal processing apparatus (Digital Signal Processing Device, abbreviated as DSPD), programmable logic device (Programmable Logic Device, abbreviated as PLD), field programmable gate array (Field Programmable Gate Array, abbreviated as FPGA), controller, microcontroller, microprocessor, or other electronic component for performing the method for evaluating the reactivity of the desulfurizing agent described above.
In another exemplary embodiment, there is also provided a computer-readable storage medium including program instructions that, when executed by a processor, implement the steps of the above-described method of evaluating desulfurizing agent reactivity. For example, the computer readable storage medium may be the memory 802 including the program instructions described above, which are executable by the processor 801 of the desulfurizing agent reactivity evaluation apparatus 800 to perform the desulfurizing agent reactivity evaluation method described above.
Example 4
Corresponding to the above method embodiments, the present disclosure also provides a readable storage medium, and a method for evaluating reactivity of a desulfurizing agent described below and a method for evaluating reactivity of a desulfurizing agent described above may be referred to correspondingly to each other.
A readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method for evaluating the reactivity of a desulfurizing agent of the above method embodiment.
The readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, and the like.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A method for evaluating the reactivity of a desulfurizing agent, comprising:
obtaining information of a desulfurizing agent reactivity evaluation factor, test data and expert scores, wherein the test data comprises the conversion rate of the desulfurizing agent under the reaction conditions, the reaction conditions comprise working conditions needing to be evaluated and working conditions not needing to be evaluated, and the expert scores comprise scores of the expert on all evaluation factors under the working conditions needing to be evaluated;
constructing an evaluation factor comparison matrix according to the evaluation factor information;
calculating the evaluation factor weight vector according to the evaluation factor comparison matrix;
constructing a gray weight matrix of the evaluation factors according to the evaluation factor information, the test data and the expert scores;
and calculating a comprehensive evaluation vector according to the evaluation factor weight vector and the gray weight matrix, and obtaining the reactive grade of the desulfurizing agent under the working condition needing to be evaluated according to the comprehensive evaluation vector.
2. The method for evaluating reactivity of desulfurizing agent according to claim 1, wherein after constructing the evaluation factor comparison matrix based on the evaluation factor information, further comprising:
calculating a consistency index of the evaluation factor comparison matrix;
acquiring a random consistency index of the evaluation factor comparison matrix;
according to the consistency index of the evaluation factor comparison matrix and the random consistency index of the evaluation factor comparison matrix, calculating to obtain the consistency ratio of the evaluation factor comparison matrix;
judging whether the consistency ratio of the evaluation factor comparison matrix meets the requirement, if so, calculating the weight vector of the evaluation factor according to the evaluation factor comparison matrix, and if not, reconstructing the evaluation factor comparison matrix.
3. The method for evaluating reactivity of desulfurizing agent according to claim 1, wherein constructing gray weight matrix of evaluation factors based on the evaluation factor information, test data and expert scores comprises:
constructing a scoring matrix according to the scoring factor information, the test data and the expert scores;
calculating expert scoring weight vectors;
determining whitening weight functions of different activity levels according to the scoring matrix;
and constructing a gray weight matrix of the evaluation factor according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels.
4. The method for evaluating reactivity of desulfurizing agent according to claim 3, wherein said constructing gray weight matrix of evaluation factors based on whitening weight functions, scoring matrices and expert scoring weight vectors of said different activity levels comprises:
according to the whitening weight functions, the scoring matrixes and the expert scoring weight vectors of the different activity levels, calculating gray statistic values of each evaluation factor under the different activity levels;
calculating the sum of gray statistic values of all the evaluation factors according to the gray statistic values of all the evaluation factors under different activity levels;
calculating gray weight values of all the evaluation factors according to the gray statistic values of all the evaluation factors under different activity levels and the sum of the gray statistic values of all the evaluation factors, and obtaining gray weight vectors of all the evaluation factors according to the gray weight values of all the evaluation factors;
and constructing a gray weight matrix of the evaluation factors according to the gray weight vector of each evaluation factor.
5. An apparatus for evaluating reactivity of a desulfurizing agent, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring information of a desulfurizer reactivity evaluation factor, test data and expert scores, the test data comprise conversion rate of the desulfurizer under reaction conditions, the reaction conditions comprise working conditions needing evaluation and working conditions not needing evaluation, and the expert scores comprise scores of the expert on all evaluation factors under the working conditions needing evaluation;
the first construction module is used for constructing an evaluation factor comparison matrix according to the evaluation factor information;
the first calculation module is used for calculating the evaluation factor weight vector according to the evaluation factor comparison matrix;
the second construction module is used for constructing a gray weight matrix of the evaluation factors according to the evaluation factor information, the test data and the expert scores;
and the second calculation module is used for calculating a comprehensive evaluation vector according to the evaluation factor weight vector and the gray weight matrix, and obtaining the reactivity grade of the desulfurizing agent under the working condition needing to be evaluated according to the comprehensive evaluation vector.
6. The apparatus for evaluating reactivity of a desulfurizing agent according to claim 5, further comprising:
the third calculation module is used for calculating the consistency index of the evaluation factor comparison matrix;
the second acquisition module is used for acquiring the random consistency index of the evaluation factor comparison matrix;
the fourth calculation module is used for calculating the consistency ratio of the evaluation factor comparison matrix according to the consistency index of the evaluation factor comparison matrix and the random consistency index of the evaluation factor comparison matrix;
the first judging module is used for judging whether the consistency proportion of the evaluation factor comparison matrix meets the requirement, if so, calculating the evaluation factor weight vector according to the evaluation factor comparison matrix, and if not, reconstructing the evaluation factor comparison matrix.
7. The apparatus for evaluating reactivity of a desulfurizing agent according to claim 5, wherein the second building block includes:
the first construction unit is used for constructing a scoring matrix according to the evaluation factor information, the test data and the expert scores;
a first calculation unit for calculating expert scoring weight vectors;
a second calculation unit, configured to determine whitening weight functions of different activity levels according to the scoring matrix;
and the second construction unit is used for constructing a gray weight matrix of the evaluation factors according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels.
8. The apparatus for evaluating reactivity of a desulfurizing agent according to claim 7, wherein said second construction unit includes:
the first calculating subunit is used for calculating gray statistic values of each evaluation factor under different activity levels according to the whitening weight functions, the scoring matrix and the expert scoring weight vector of the different activity levels;
the second calculating subunit is used for calculating the sum of the gray statistic values of all the evaluation factors according to the gray statistic values of all the evaluation factors under different activity levels;
the third computing subunit is used for computing the gray weight value of each evaluation factor according to the gray statistic value of each evaluation factor under different activity levels and the sum of the gray statistic values of each evaluation factor, and obtaining the gray weight vector of each evaluation factor according to the gray weight value of each evaluation factor;
and the construction subunit is used for constructing the gray weight matrix of the evaluation factors according to the gray weight vectors of the evaluation factors.
9. An apparatus for evaluating reactivity of a desulfurizing agent, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method for evaluating reactivity of a desulfurizing agent according to any one of claims 1 to 4 when executing the computer program.
10. A readable storage medium, characterized by: the readable storage medium has stored thereon a computer program which, when executed by a processor, realizes the steps of the method for evaluating the reactivity of a desulfurizing agent according to any one of claims 1 to 4.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001337068A (en) * | 2000-05-26 | 2001-12-07 | Yuasa Corp | Cell and method for evaluating state of electrode reaction |
| CN104636876A (en) * | 2015-02-13 | 2015-05-20 | 湖南有色金属研究院 | Typical mine area heavy metal pollution soil ecological restoration technology evaluating method and system |
| CN106096847A (en) * | 2016-06-16 | 2016-11-09 | 同济大学 | A kind of fuzzy change weighs Engineering-geological environmental quality method |
| CN107066823A (en) * | 2017-04-18 | 2017-08-18 | 中山大学 | Based on plant, soil, microorganism heavy-metal contaminated soil repairing effect integrated evaluating method |
| CN109214635A (en) * | 2017-07-06 | 2019-01-15 | 北京市首发天人生态景观有限公司 | A kind of evaluation method of compost maturity |
| CN110659814A (en) * | 2019-09-12 | 2020-01-07 | 国网山东省电力公司寿光市供电公司 | Power grid operation risk evaluation method and system based on entropy weight method |
-
2021
- 2021-04-08 CN CN202110378573.8A patent/CN113130015B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001337068A (en) * | 2000-05-26 | 2001-12-07 | Yuasa Corp | Cell and method for evaluating state of electrode reaction |
| CN104636876A (en) * | 2015-02-13 | 2015-05-20 | 湖南有色金属研究院 | Typical mine area heavy metal pollution soil ecological restoration technology evaluating method and system |
| CN106096847A (en) * | 2016-06-16 | 2016-11-09 | 同济大学 | A kind of fuzzy change weighs Engineering-geological environmental quality method |
| CN107066823A (en) * | 2017-04-18 | 2017-08-18 | 中山大学 | Based on plant, soil, microorganism heavy-metal contaminated soil repairing effect integrated evaluating method |
| CN109214635A (en) * | 2017-07-06 | 2019-01-15 | 北京市首发天人生态景观有限公司 | A kind of evaluation method of compost maturity |
| CN110659814A (en) * | 2019-09-12 | 2020-01-07 | 国网山东省电力公司寿光市供电公司 | Power grid operation risk evaluation method and system based on entropy weight method |
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