Production process selection method of tunnel hole slag product

Abstract

The invention relates to a tunnel hole slag product production process selection method, which comprises the steps of determining weight coefficients of a plurality of first evaluation factors of a plurality of first process schemes and weight coefficients of a plurality of second evaluation factors of a plurality of second process schemes, according to feature vector values of a plurality of first evaluation factors of the plurality of first process schemes and feature vector values of a plurality of second evaluation factors of the plurality of second process schemes, calculating a total sorting vector of the plurality of first process schemes and a total sorting vector of the plurality of second process schemes; combining the optimal scheme in the first process scheme with the optimal scheme in the second process scheme to obtain the optimal scheme of the production process of the tunnel hole slag product; according to the production process selection method of the tunnel hole slag product, the mathematical model for optimal selection of the production process is established, so that quantitative decision reference is provided, the accuracy and applicability of experience selection are ensured, and the situation that process rectification is carried out in the later period due to improper process selection is improved.

Description

Technical Field

[0001] The present application relates to the technical field of tunnel engineering, and in particular to a method for selecting a production process for tunnel slag products. Background Art

[0002] In the production process design of tunnel slag preparation mechanism products, the selection of production processes such as dry and wet methods, number of crushing stages, combination of crushing equipment, and shaping sand making is the most important.

[0003] At present, when selecting the production process of tunnel slag products, most of them rely on the experience of the selectors, but this selection based on experience is often only applicable to simple conditions. The slag raw materials along the plateau railway are affected by many factors such as complex and changeable characteristics, different production requirements, and strict quality requirements for finished products. Therefore, this selection based on experience is difficult to ensure the accuracy and applicability of the experience selection when facing the complex conditions along the plateau railway. As a result, there are cases where the process is rectified later due to improper process selection, which will not only cause economic losses, but also may affect the overall construction progress of the project. Summary of the invention

[0004] Based on this, it is necessary to provide a method for selecting a production process for tunnel slag products in order to address the above-mentioned problem that the accuracy and applicability of the selection of the production process for tunnel slag products cannot be guaranteed.

[0005] A method for selecting a production process for a tunnel slag product, comprising:

[0006] Acquire a plurality of first evaluation factors of a plurality of first process schemes and a plurality of second evaluation factors of a plurality of second process schemes, wherein the production process of the tunnel slag product includes the first process scheme and the second process scheme;

[0007] Determining weight coefficients of a plurality of first evaluation factors of a plurality of first process solutions and weight coefficients of a plurality of second evaluation factors of a plurality of second process solutions;

[0008] Determine characteristic vector values ​​of a plurality of first evaluation factors of a plurality of first process schemes and characteristic vector values ​​of a plurality of second evaluation factors of a plurality of second process schemes;

[0009] According to the weight coefficients and characteristic vector values ​​of the multiple first evaluation factors of the multiple first process solutions, the total ranking vector of the multiple first process solutions is calculated, and according to the weight coefficients and characteristic vector values ​​of the multiple second evaluation factors of the multiple second process solutions, the total ranking vector of the multiple second process solutions is calculated;

[0010] Compare the total ranking vectors of the plurality of first process solutions to determine the best solution among the plurality of first process solutions, and compare the total ranking vectors of the plurality of second process solutions to determine the best solution among the plurality of second process solutions;

[0011] The optimal solution in the first process solution is combined with the optimal solution in the second process solution to obtain the optimal solution for the production process of tunnel slag products.

[0012] In one embodiment, the method for selecting a production process for tunnel slag products further includes:

[0013] Acquire a plurality of third evaluation factors of a plurality of third process schemes, wherein the production process of the tunnel slag product includes the third process scheme;

[0014] Determining weight coefficients of a plurality of third evaluation factors of a plurality of third process solutions;

[0015] Determining characteristic vector values ​​of a plurality of third evaluation factors of a plurality of third process schemes;

[0016] Calculate the total ranking vector of the plurality of third process schemes according to the weight coefficients and characteristic vector values ​​of the plurality of third evaluation factors of the plurality of third process schemes;

[0017] Comparing the total ranking vectors of the plurality of third process solutions, and determining the best solution among the plurality of third process solutions;

[0018] The optimal solution in the third process solution is combined with the optimal solution in the second process solution and the optimal solution in the first process solution to obtain the optimal solution for the production process of tunnel slag products.

[0019] In one embodiment, the first process scheme is a crushing process scheme, the second process scheme is a dry-wet process scheme, and the third process scheme is a shaping sand making process scheme.

[0020] In one embodiment, determining the characteristic vector values ​​of the plurality of first evaluation factors of the plurality of first process schemes includes:

[0021] Establishing a plurality of adaptability score tables of a plurality of first process schemes with respect to a plurality of first evaluation factors;

[0022] The characteristic vector values ​​of the plurality of first evaluation factors in different first process schemes are obtained according to the adaptability score table.

[0023] In one embodiment, the first process solution is a crushing process solution, and the plurality of first evaluation factors include raw material characteristics, output configuration, finished product quality and comprehensive cost.

[0024] In one embodiment, the step of establishing a plurality of adaptability score tables of a plurality of first process schemes with respect to a plurality of first evaluation factors comprises:

[0025] According to the adaptability of the crushing process to raw material characteristics, output configuration, finished product quality and comprehensive cost, multiple adaptability score tables for multiple crushing process schemes with respect to raw material characteristics, output configuration, finished product quality and comprehensive cost are established respectively.

[0026] In one embodiment, the step of obtaining characteristic vector values ​​of a plurality of first evaluation factors in different first process schemes according to the adaptability score table includes:

[0027] When the judgment standard of the first evaluation factor is "the better the adaptability, the greater the score", according to the formula:

[0028]

[0029] The eigenvector value of the first evaluation factor is obtained, where Characterizing parameters of a plurality of first evaluation factors for a plurality of first process schemes;

[0030] When the judgment standard of the first evaluation factor is "the better the adaptability, the smaller the score", according to the formula:

[0031]

[0032] The eigenvector value of the first evaluation factor is obtained, where Characteristic parameters of a plurality of first process schemes for a plurality of first evaluation factors.

[0033] In one embodiment, the multiple second evaluation factors include at least one evaluation factor among the multiple first evaluation factors; the multiple third evaluation factors include at least one evaluation factor among the multiple first evaluation factors, and / or the multiple third evaluation factors include at least one evaluation factor among the multiple second evaluation factors.

[0034] In one embodiment, the multiple first evaluation factors include raw material characteristics, production configuration, finished product quality and comprehensive cost; the multiple second evaluation factors include raw material characteristics, finished product quality, environmental factors and comprehensive cost; the multiple third evaluation factors include production configuration, finished product quality and comprehensive cost.

[0035] In one embodiment, the total ranking vector of the plurality of first process schemes is calculated based on the weight coefficients and characteristic vector values ​​of the plurality of first evaluation factors of the plurality of first process schemes, including:

[0036] The weight coefficients of the first evaluation factors of the first process schemes are used as column vectors to form a matrix ;

[0037] The characteristic vector values ​​of the first evaluation factors of the first process schemes are taken as column vectors to form a matrix ;

[0038] According to the formula The total sorting vectors of the plurality of first process plans are obtained by calculation.

[0039] The production process selection method for the above-mentioned tunnel slag products is based on the factors affecting the production process, establishes a mathematical model for the optimal selection of the production process, screens the main factors affecting the production process selection, and analyzes the impact of the optimal selection target of the production process when each factor changes, thereby forming a quantitative model for the optimal selection of the production process, and then provides a quantitative decision-making reference based on evidence, ensuring the accuracy and applicability of the experience selection, and improving the situation of subsequent process rectification due to improper process selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] FIG1 is a flow chart of a method for selecting a production process for tunnel slag products according to some embodiments of the present application.

[0041] FIG. 2 is a schematic diagram of a multi-level structural model of a first process scheme of a method for selecting a production process for tunnel slag products in some embodiments of the present application.

[0042] FIG3 is a schematic diagram of a multi-level structural model of a second process scheme of a method for selecting a production process for tunnel slag products in some embodiments of the present application.

[0043] FIG. 4 is a schematic diagram of a multi-level structural model of a third process solution of a method for selecting a production process for tunnel slag products according to some embodiments of the present application. DETAILED DESCRIPTION

[0044] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present application, so the present application is not limited by the specific embodiments disclosed below.

[0045] In the description of the present application, it should be understood that if the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. appear, the orientation or position relationship indicated by these terms is based on the orientation or position relationship shown in the accompanying drawings, which is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application.

[0046] In addition, if the terms "first" or "second" appear, these terms are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, if the term "plurality" appears, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0047] In this application, unless otherwise clearly specified and limited, if the terms "installed", "connected", "connected", "fixed" and the like appear, these terms should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integrated connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to the specific circumstances.

[0048] In the present application, unless otherwise clearly specified and limited, if there is a description that a first feature is "above" or "below" a second feature, etc., or similar descriptions appear, it may mean that the first and second features are in direct contact, or that the first and second features are in indirect contact through an intermediate medium. Moreover, the first feature being "above", "above" and "above" the second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. The first feature being "below", "below" and "below" the second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0049] It should be noted that if an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or there may be a central element. If an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. If any, the terms "vertical", "horizontal", "upper", "lower", "left", "right" and similar expressions used in this application are for illustrative purposes only and do not represent the only implementation method.

[0050] In the production process design of tunnel slag preparation mechanism products, the selection of production processes such as dry and wet methods, number of crushing stages, combination of crushing equipment, and shaping sand making is the most important. In the production process design of tunnel slag preparation mechanism products, the selection of production processes such as dry and wet methods, number of crushing stages, combination of crushing equipment, and shaping sand making is the most important. At the same time, due to the complex and changeable characteristics of slag raw materials along the plateau railway, different production requirements, and strict requirements on the quality of finished products, the process design is more difficult.

[0051] At present, when selecting the production process of tunnel slag products, most of the selection depends on the experience of the selection personnel. However, this selection based on experience is often only applicable to selection under simple conditions. When faced with complex conditions along the plateau railway, it is difficult to ensure the accuracy and applicability of the experience selection, resulting in the situation where the process is rectified later due to improper process selection, which will not only cause economic losses, but may also affect the overall construction progress of the project.

[0052] Therefore, this application proposes a production process selection method for tunnel slag products, uses the hierarchical analysis method to establish a mathematical model for the optimal selection of production processes, screens the main factors affecting the selection of production processes, and analyzes the impact of changes in various factors on the optimal selection target of production processes, thereby forming a quantitative model for the optimal selection of production processes. In view of the complex conditions along the plateau railway and the demand for tunnel slag utilization, a quantitative decision-making reference can be provided in a reasonable manner.

[0053] Referring to FIG. 1 , an embodiment of the present application provides a method for selecting a production process for a tunnel slag product, comprising:

[0054] S1. Obtain multiple first evaluation factors of multiple first process solutions, multiple second evaluation factors of multiple second process solutions, and multiple third evaluation factors of multiple third process solutions. The production process of the tunnel slag product includes a first process solution, a second process solution, and a third process solution.

[0055] In the embodiment of the present application, the first process scheme is a crushing process scheme, the second process scheme is a dry-wet process scheme, and the third process scheme is a shaping sand making process scheme. The present application combines the optimal crushing process scheme, dry-wet process scheme, and shaping sand making process scheme to obtain the optimal solution for the production process of tunnel slag products.

[0056] In addition, in an embodiment of the present application, multiple first evaluation factors include raw material characteristics, production configuration, finished product quality and comprehensive cost, multiple second evaluation factors include raw material characteristics, finished product quality, environmental factors and comprehensive cost, and multiple third evaluation factors include production configuration, finished product quality and comprehensive cost.

[0057] S2. Determine weight coefficients of a plurality of first evaluation factors of a plurality of first process solutions, weight coefficients of a plurality of second evaluation factors of a plurality of second process solutions, and weight coefficients of a plurality of third evaluation factors of a plurality of third process solutions.

[0058] Specifically, referring to FIG2, for the first process solution, a multi-level structural model is established using the analytic hierarchy process theory with the crushing process optimization solution as the target layer, multiple first evaluation factors as the criterion layer, and multiple first process solutions as the solution layer. According to the multi-level structural model, the factors of the same level in the multi-level structural model are compared with each other, and the optimal judgment matrix ratio scale is selected to evaluate the relative importance of each factor. A judgment matrix A1 is established for multiple first evaluation factors, and the maximum characteristic root and the normalized characteristic vector are obtained, and then the weight coefficients of the multiple first evaluation factors are obtained.

[0059] Referring to FIG3 , for the second process scheme, a multi-level structural model is established using the hierarchical analysis theory with the dry-wet process optimization scheme as the target layer, multiple second evaluation factors as the criterion layer, and multiple second process schemes as the scheme layer. According to the multi-level structural model, the factors of the same level in the multi-level structural model are compared with each other, and the optimal judgment matrix ratio scale is selected to evaluate the relative importance of each factor. A judgment matrix A2 is established for multiple second evaluation factors, and the maximum characteristic root and the normalized characteristic vector are obtained, and then the weight coefficients of the multiple second evaluation factors are obtained.

[0060] Referring to Figure 4, for the third process solution, a multi-level structural model is established using the hierarchical analysis theory, with the shaping sand making process optimization solution as the target layer, multiple third evaluation factors as the criterion layer, and multiple third process solutions as the solution layer. According to the multi-level structural model, the factors of the same level in the multi-level structural model are compared with each other, and the optimal judgment matrix ratio scale is selected to evaluate the relative importance of each factor. A judgment matrix A3 is established for multiple third evaluation factors, and the maximum characteristic root and normalized characteristic vector are obtained, and then the weight coefficients of multiple third evaluation factors are obtained.

[0061] It can be understood that, referring to FIG. 2 , in the embodiment of the present application, for the first process scheme, a crushing process optimization scheme can be established as the target layer, and raw material characteristics, output configuration, finished product quality and comprehensive cost can be established as the criterion layer, with P1—two-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JS), P2—three-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JSS), P3—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P4—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P5—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P6—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P7—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P8—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P9—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JS), P10—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P11—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P12—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JS), P13—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P14—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JS), P15—two The three-stage crushing process of P5—jaw crusher + medium crushing multi-cylinder cone crusher + fine crushing multi-cylinder cone crusher (JMM), P6—jaw crusher + medium and fine crushing impact crusher (JI), P7—jaw crusher + medium crushing impact crusher + fine crushing impact crusher (JII) and P8—coarse crushing impact crusher + medium and fine crushing impact crusher (II) are the multi-level structural models of the scheme layer.

[0062] According to the multi-level structural model, the factors at the same level in the multi-level structural model are compared pairwise:

[0063] Comparing the raw material characteristics and production configuration factors, we take C1: C2=1 / 2;

[0064] Comparing the raw material characteristics with the finished product quality factors, take C1: C3=1 / 3;

[0065] Comparing the raw material characteristics with the comprehensive cost factors, we take C1: C4=1 / 3;

[0066] Comparing the output configuration and finished product quality factors, take C2: C3=1 / 2;

[0067] Comparing the output configuration and comprehensive cost factors, we take C2: C4=1 / 2;

[0068] Comparing the quality of finished products with the comprehensive cost factors, take C3: C4=1.

[0069] Select the optimal judgment matrix ratio scale to assess the relative importance of each factor, and establish a judgment matrix A1 for multiple evaluation factors:

[0070] ;

[0071] Calculate its maximum characteristic root according to the judgment matrix A1: ;

[0072] And the weight coefficients (normalized eigenvectors): .

[0073] Calculated according to the consistency ratio formula and random consistency index table: , which meets the consistency requirement, indicating that the judgment matrix A1 is reasonably set (since the above calculation method belongs to a common calculation formula in this field, the calculation formula and calculation process will not be described in detail).

[0074] For the second process scheme, a multi-level structural model can be established with the dry and wet process optimization scheme as the target layer, raw material characteristics, finished product quality, environmental factors and comprehensive cost as the criterion layer, and dry process and wet process as the scheme layer.

[0075] According to the multi-level structural model, the factors at the same level in the multi-level structural model are compared pairwise:

[0076] Comparing the raw material characteristics with the finished product quality factors, we take C1: C2=2, so C2: C1=1 / 2;

[0077] Comparing the raw material characteristics and environmental factors, take C1: C3=1;

[0078] Comparing the raw material characteristics with the comprehensive cost factors, we take C1: C4=3, so C4: C1=1 / 3;

[0079] Comparing the quality of finished products with environmental factors, we take C2: C3=1 / 2, so C3: C2=2;

[0080] Comparing environmental factors with comprehensive cost factors, we take C3: C4=3, so C4: C3=1 / 3.

[0081] In summary, we get the judgment matrix A2:

[0082] ;

[0083] Calculate its maximum characteristic root according to the judgment matrix A2: ;

[0084] And the weight coefficients (normalized eigenvectors): .

[0085] Calculated according to the consistency ratio formula and random consistency index table: , which meets the consistency requirement, indicating that the judgment matrix A2 is reasonably set (since the above calculation method belongs to a common calculation formula in this field, the calculation formula and calculation process will not be described in detail).

[0086] For the third process scheme, a multi-level structural model can be established with the optimal scheme of shaping sand making process as the target layer, the output configuration, finished product quality and comprehensive cost as the criterion layer, and the single vertical shaft process and double vertical shaft process as the scheme layer.

[0087] According to the multi-level structural model, the factors at the same level in the multi-level structural model are compared pairwise:

[0088] Comparing the output configuration and the finished product quality factors, we take C1: C2=2, so C2: C1=1 / 2;

[0089] Comparing the output configuration and comprehensive cost factors, we take C1: C3=3, so C3: C1=1 / 3;

[0090] Comparing the quality of finished products with the comprehensive cost factors, we take C2: C3=2, so C3: C2=1 / 2.

[0091] In summary, we get the judgment matrix A3:

[0092] ;

[0093] Calculate its maximum characteristic root according to the judgment matrix A3: ;

[0094] And the weight coefficients (normalized eigenvectors): .

[0095] Calculated according to the consistency ratio formula and random consistency index table: , which meets the consistency requirement, indicating that the judgment matrix A2 is reasonably set (since the above calculation method belongs to a common calculation formula in this field, the calculation formula and calculation process will not be described in detail).

[0096] S3. Determine characteristic vector values ​​of multiple first evaluation factors of multiple first process solutions, characteristic vector values ​​of multiple second evaluation factors of multiple second process solutions, and characteristic vector values ​​of multiple third evaluation factors of multiple third process solutions.

[0097] Specifically, for the characteristic vector values ​​of multiple first evaluation factors of multiple first process schemes, multiple adaptability score tables of the multiple first process schemes with respect to the multiple first evaluation factors are first established, and then the characteristic vector values ​​of the multiple first evaluation factors in different first process schemes are obtained according to the adaptability score tables.

[0098] According to the adaptability score table, characteristic vector values ​​of multiple first evaluation factors in different first process schemes are obtained, including:

[0099] When the judgment standard of the first evaluation factor is "the better the adaptability, the greater the score", according to the formula:

[0100]

[0101] The eigenvector value of the first evaluation factor is obtained, where Characterizing parameters of a plurality of first evaluation factors for a plurality of first process schemes;

[0102] When the judgment standard of the first evaluation factor is "the better the adaptability, the smaller the score", according to the formula:

[0103]

[0104] The eigenvector value of the first evaluation factor is obtained, where Characteristic parameters of a plurality of first process schemes for a plurality of first evaluation factors.

[0105] The characteristic vector values ​​of the multiple second evaluation factors of the multiple second process solutions and the characteristic vector values ​​of the multiple third evaluation factors of the multiple third process solutions are similar.

[0106] Exemplarily, in an embodiment of the present application, multiple adaptability score tables of multiple first process schemes with respect to multiple first evaluation factors are established, including:

[0107] According to the adaptability of the crushing process to raw material characteristics, output configuration, finished product quality and comprehensive cost, multiple adaptability score tables for multiple crushing process schemes with respect to raw material characteristics, output configuration, finished product quality and comprehensive cost are established respectively.

[0108] Among them, the adaptability of the crushing process to the raw material characteristics can be measured with a score ranging from 0 to 1 as a characterization parameter. For example, the cone crushing process is generally adaptable to all types of rock types, and the score is 1; the impact crushing process is generally adaptable to limestone, and the score is 1, but it is not adaptable to granite and gneiss, and the score is 0. Then, the adaptability score table of the crushing process scheme to the raw material characteristics can be obtained:

[0109]

[0110] According to the formula of "the better the adaptability, the greater the score", based on the adaptability score of the crushing process to the raw material characteristics, the characteristic vector value table of the crushing process to the raw material characteristics is obtained:

[0111]

[0112] The way to establish the adaptability score table of the crushing process plan regarding output configuration, finished product quality and comprehensive cost is similar.

[0113] S4. According to the weight coefficients and characteristic vector values ​​of the multiple first evaluation factors of the multiple first process solutions, the total ranking vector of the multiple first process solutions is calculated. According to the weight coefficients and characteristic vector values ​​of the multiple second evaluation factors of the multiple second process solutions, the total ranking vector of the multiple second process solutions is calculated. According to the weight coefficients and characteristic vector values ​​of the multiple third evaluation factors of the multiple third process solutions, the total ranking vector of the multiple third process solutions is calculated.

[0114] Specifically, according to the weight coefficients and characteristic vector values ​​of the multiple first evaluation factors of the multiple first process solutions, the total ranking vector of the multiple first process solutions is calculated, including:

[0115] The weight coefficients of the first evaluation factors of the first process schemes are used as column vectors to form a matrix .

[0116] The characteristic vector values ​​of the first evaluation factors of the first process schemes are taken as column vectors to form a matrix .

[0117] According to the formula The total sorting vectors of the plurality of first process plans are obtained by calculation.

[0118] The total ranking vectors of the plurality of second process solutions and the total ranking vectors of the plurality of third process solutions are calculated in the same manner.

[0119] For example, in the embodiment of the present application, after establishing the judgment matrix A1 and comparing the importance of each design influencing factor, it can be known that P1 is a two-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JS), P2 is a three-stage crushing process of jaw crusher + medium crushing single-cylinder cone crusher + fine crushing single-cylinder cone crusher (JSS), P3 is a two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P4 is a three-stage crushing process of jaw crusher + medium crushing multi-cylinder cone crusher + fine crushing multi-cylinder cone crusher The weight coefficients of raw material characteristics, output configuration, finished product quality and comprehensive cost for crushing process (JMM), P5—three-stage crushing process of jaw crusher + medium crushing single-cylinder cone crusher + fine crushing multi-cylinder cone crusher (JSM), P6—two-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JI), P7—three-stage crushing process of jaw crusher + medium crushing impact crusher + fine crushing impact crusher (JII) and P8—two-stage crushing process of coarse crushing impact crusher + medium and fine crushing impact crusher (II) are as follows: .

[0120] Based on the adaptability score of the crushing process to the raw material characteristics, after the characteristic vector value table of the crushing process to the raw material characteristics is obtained, it can be known that the characteristic values ​​of the raw material characteristics of P1—two-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JS), P2—three-stage crushing process of jaw crusher + medium crushing single-cylinder cone crusher + fine crushing single-cylinder cone crusher (JSS), P3—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P4—three-stage crushing process of jaw crusher + medium crushing multi-cylinder cone crusher + fine crushing multi-cylinder cone crusher (JMM), P5—three-stage crushing process of jaw crusher + medium crushing single-cylinder cone crusher + fine crushing multi-cylinder cone crusher (JSM), P6—two-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JI), P7—three-stage crushing process of jaw crusher + medium crushing impact crusher + fine crushing impact crusher (JII) and P8—two-stage crushing process of coarse crushing impact crusher + medium and fine crushing impact crusher (II) are , the normalized eigenvector is .

[0121] Based on the adaptability score of the crushing process to the output configuration, after the characteristic vector value table of the crushing process to the output configuration is obtained, it can be known that the characteristic values ​​of the output configuration of P1—two-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JS), P2—three-stage crushing process of jaw crusher + medium crushing single-cylinder cone crusher + fine crushing single-cylinder cone crusher (JSS), P3—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P4—three-stage crushing process of jaw crusher + medium crushing multi-cylinder cone crusher + fine crushing multi-cylinder cone crusher (JMM), P5—three-stage crushing process of jaw crusher + medium crushing single-cylinder cone crusher + fine crushing multi-cylinder cone crusher (JSM), P6—two-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JI), P7—three-stage crushing process of jaw crusher + medium crushing impact crusher + fine crushing impact crusher (JII) and P8—two-stage crushing process of coarse crushing impact crusher + medium and fine crushing impact crusher (II) are , the normalized eigenvector is .

[0122] Based on the adaptability score of the crushing process to the quality of the finished product, after the characteristic vector value table of the crushing process to the quality of the finished product is obtained, it can be known that the normalized characteristic vectors of the finished product quality of P1—two-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JS), P2—three-stage crushing process of jaw crusher + medium crushing single-cylinder cone crusher + fine crushing single-cylinder cone crusher (JSS), P3—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P4—three-stage crushing process of jaw crusher + medium crushing multi-cylinder cone crusher + fine crushing multi-cylinder cone crusher (JMM), P5—three-stage crushing process of jaw crusher + medium crushing single-cylinder cone crusher + fine crushing multi-cylinder cone crusher (JSM), P6—two-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JI), P7—three-stage crushing process of jaw crusher + medium crushing impact crusher + fine crushing impact crusher (JII) and P8—two-stage crushing process of coarse crushing impact crusher + medium and fine crushing impact crusher (II) are .

[0123] Based on the adaptability score of the crushing process to the comprehensive cost, after the characteristic vector value table of the crushing process to the comprehensive cost is obtained, it can be known that the two-stage crushing process of P1—jaw crusher + medium and fine crushing single-cylinder cone crusher (JS), P2—jaw crusher + medium crushing single-cylinder cone crusher + fine crushing single-cylinder cone crusher three-stage crushing process (JSS), P3—jaw crusher + medium and fine crushing multi-cylinder cone crusher two-stage crushing process (JM), P4—jaw crusher + medium crushing multi-cylinder cone crusher + fine crushing multi-cylinder cone crusher three-stage crushing process (JMM), P5—jaw crusher + medium crushing single-cylinder cone crusher + fine crushing multi-cylinder cone crusher three-stage crushing process (JSM), P6—jaw crusher + medium and fine crushing impact crusher two-stage crushing process (JI), P7—jaw crusher + medium crushing impact crusher + fine crushing impact crusher three-stage crushing process (JII) and P8—coarse crushing impact crusher + medium and fine crushing impact crusher two-stage crushing process (II) The normalized characteristic vectors of the comprehensive cost are .

[0124] After summarizing the above eigenvectors, we can form the matrix :

[0125]

[0126] Then, the total ordering vectors of P1—two-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JS), P2—three-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JSS), P3—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P4—three-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JMM), P5—three-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JSM), P6—two-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JI), P7—three-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JII) and P8—two-stage crushing process of coarse crushing impact crusher + medium and fine crushing impact crusher (II) can be calculated as follows: .

[0127] The calculation method of the total ranking vector of multiple dry and wet process solutions and the total ranking vector of multiple shaping sand making process solutions is similar. For example, the present application can bring in the specific tunnel situation and calculate the total ranking vector of the dry process and the wet process in the same way: , the total sorting vector of the double vertical axis process and the single vertical axis process is .

[0128] S5. Compare the total ranking vectors of multiple first process solutions to determine the optimal solution among the multiple first process solutions, compare the total ranking vectors of multiple second process solutions to determine the optimal solution among the multiple second process solutions; compare the total ranking vectors of multiple third process solutions to determine the optimal solution among the multiple third process solutions.

[0129] Specifically, according to the total sorting vectors among P1—two-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JS), P2—three-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JSS), P3—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P4—three-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JMM), P5—three-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JSM), P6—two-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JI), P7—three-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JII) and P8—two-stage crushing process of coarse crushing impact crusher + medium and fine crushing impact crusher (II), the total sorting vectors among P1—two-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JS), P2—three-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher (JSS), P3—two-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JM), P4—three-stage crushing process of jaw crusher + medium and fine crushing multi-cylinder cone crusher (JMM), P5—three-stage crushing process of jaw crusher + medium and fine crushing single-cylinder cone crusher + fine crushing multi-cylinder cone crusher (JSM), P6—two-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JI), P7—three-stage crushing process of jaw crusher + medium and fine crushing impact crusher (JII) and P8—two-stage crushing process of coarse crushing impact crusher + medium and fine crushing impact crusher (II) It can be seen that the total sorting result Therefore, it can be concluded that in the embodiment of the present application, the two-stage crushing process (JM) of P3—jaw crusher + medium and fine crushing multi-cylinder cone crusher is the optimal solution among the crushing process solutions.

[0130] Total sorting vector according to dry process and wet process It can be seen that in the embodiments of the present application, the dry process is the optimal solution among the dry and wet process solutions.

[0131] According to the total sorting vector of double vertical axis process and single vertical axis process It can be seen that in the embodiments of the present application, the double vertical shaft process is the optimal solution among the shaping sand making process solutions.

[0132] S6. Combining the optimal solution in the third process solution with the optimal solution in the second process solution and the optimal solution in the first process solution to obtain the optimal solution for the production process of tunnel slag products.

[0133] Specifically, in the embodiments of the present application, the optimal solution for the production process of tunnel slag products is dry production, two-stage crushing of jaw crusher + multi-cylinder cone crusher with double vertical shaft shaping sand making.

[0134] In summary, the production process selection method for tunnel slag products of the present application establishes a mathematical model for the optimal selection of the production process based on the factors affecting the production process, screens the main factors affecting the production process selection, and analyzes the impact of the optimal selection target of the production process when each factor changes, thereby forming a quantitative model for the optimal selection of the production process, and then providing a quantitative decision-making reference based on evidence, ensuring the accuracy and applicability of the empirical selection, and improving the situation of subsequent process rectification due to improper process selection.

[0135] In one embodiment, the plurality of second evaluation factors include at least one evaluation factor among the plurality of first evaluation factors; the plurality of third evaluation factors include at least one evaluation factor among the plurality of first evaluation factors, and / or the plurality of third evaluation factors include at least one evaluation factor among the plurality of second evaluation factors.

[0136] Specifically, the first evaluation factors include raw material characteristics, output configuration, finished product quality and comprehensive cost; the second evaluation factors include raw material characteristics, finished product quality, environmental factors and comprehensive cost; the third evaluation factors include output configuration, finished product quality and comprehensive cost. By making the first evaluation factors, the second evaluation factors and the third evaluation factors overlap, the time for statistical induction of data can be effectively saved and the workload for process selection can be reduced.

[0137] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0138] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A method for selecting a production process for tunnel slag products, characterized in that: include: Acquire a plurality of first evaluation factors of a plurality of first process solutions and a plurality of second evaluation factors of a plurality of second process solutions; Determining weight coefficients of a plurality of first evaluation factors of a plurality of first process solutions and weight coefficients of a plurality of second evaluation factors of a plurality of second process solutions; Determine characteristic vector values ​​of a plurality of first evaluation factors of a plurality of first process schemes and characteristic vector values ​​of a plurality of second evaluation factors of a plurality of second process schemes; According to the weight coefficients and characteristic vector values ​​of the multiple first evaluation factors of the multiple first process solutions, the total ranking vector of the multiple first process solutions is calculated, and according to the weight coefficients and characteristic vector values ​​of the multiple second evaluation factors of the multiple second process solutions, the total ranking vector of the multiple second process solutions is calculated; Compare the total ranking vectors of the plurality of first process solutions to determine the best solution among the plurality of first process solutions, and compare the total ranking vectors of the plurality of second process solutions to determine the best solution among the plurality of second process solutions; The optimal solution in the first process solution is combined with the optimal solution in the second process solution to obtain the optimal solution for the production process of tunnel slag products.

2. The method for selecting a production process for tunnel slag products according to claim 1, characterized in that: The method for selecting the production process of the tunnel slag product also includes: Acquire a plurality of third evaluation factors of a plurality of third process schemes, wherein the production process of the tunnel slag product includes the third process scheme; Determining weight coefficients of a plurality of third evaluation factors of a plurality of third process solutions; Determining characteristic vector values ​​of a plurality of third evaluation factors of a plurality of third process schemes; Calculate the total ranking vector of the plurality of third process solutions according to the weight coefficients and characteristic vector values ​​of the plurality of third evaluation factors of the plurality of third process solutions; Comparing the total ranking vectors of the plurality of third process solutions, and determining the best solution among the plurality of third process solutions; The optimal solution in the third process solution is combined with the optimal solution in the second process solution and the optimal solution in the first process solution to obtain the optimal solution for the production process of tunnel slag products.

3. The method for selecting a production process for tunnel slag products according to claim 2, characterized in that: The first process scheme is a crushing process scheme, the second process scheme is a dry-wet process scheme, and the third process scheme is a shaping sand making process scheme.

4. The method for selecting a production process for tunnel slag products according to claim 2, characterized in that: The plurality of second evaluation factors include at least one evaluation factor among the plurality of first evaluation factors; the plurality of third evaluation factors include at least one evaluation factor among the plurality of first evaluation factors, and / or the plurality of third evaluation factors include at least one evaluation factor among the plurality of second evaluation factors.

5. The method for selecting a production process for tunnel slag products according to claim 4, characterized in that: The multiple first evaluation factors include raw material characteristics, output configuration, finished product quality and comprehensive cost; the multiple second evaluation factors include raw material characteristics, finished product quality, environmental factors and comprehensive cost; the multiple third evaluation factors include output configuration, finished product quality and comprehensive cost.

6. The method for selecting a production process for tunnel slag products according to claim 1, characterized in that: The determining of the characteristic vector values ​​of the plurality of first evaluation factors of the plurality of first process schemes comprises: Establishing a plurality of adaptability score tables of a plurality of first process schemes with respect to a plurality of first evaluation factors; The characteristic vector values ​​of the plurality of first evaluation factors in different first process schemes are obtained according to the adaptability score table.

7. The method for selecting a production process for tunnel slag products according to claim 6, characterized in that: The first process solution is a crushing process solution, and the plurality of first evaluation factors include raw material characteristics, output configuration, finished product quality and comprehensive cost.

8. The method for selecting a production process for tunnel slag products according to claim 7, characterized in that: The step of establishing a plurality of adaptability score tables of a plurality of first process schemes with respect to a plurality of first evaluation factors comprises: According to the adaptability of the crushing process to raw material characteristics, output configuration, finished product quality and comprehensive cost, multiple adaptability score tables for multiple crushing process schemes with respect to raw material characteristics, output configuration, finished product quality and comprehensive cost are established respectively.

9. The method for selecting a production process for tunnel slag products according to claim 8, characterized in that: The step of obtaining characteristic vector values ​​of a plurality of first evaluation factors in different first process schemes according to the adaptability score table includes: When the judgment standard of the first evaluation factor is "the better the adaptability, the greater the score", according to the formula: Get the eigenvector value of the first evaluation factor, in, Characterizing parameters of a plurality of first evaluation factors for a plurality of first process schemes; When the judgment standard of the first evaluation factor is "the better the adaptability, the smaller the score", according to the formula: Get the eigenvector value of the first evaluation factor, in, Characteristic parameters of a plurality of first process schemes for a plurality of first evaluation factors.

10. The method for selecting a production process for tunnel slag products according to claim 1, characterized in that: The method of calculating the total ranking vector of the plurality of first process schemes according to the weight coefficients and characteristic vector values ​​of the plurality of first evaluation factors of the plurality of first process schemes comprises: The weight coefficients of the first evaluation factors of the first process schemes are used as column vectors to form a matrix ; The characteristic vector values ​​of the first evaluation factors of the first process schemes are taken as column vectors to form a matrix ; According to the formula The total sorting vectors of the plurality of first process plans are obtained by calculation.

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