Steel structure communication iron tower safety evaluation method based on fuzzy mathematics

Abstract

The invention provides a fuzzy mathematics-based steel structure communication iron tower safety evaluation method. The method comprises the steps of constructing a safety fuzzy comprehensive evaluation factor set of a three-level architecture based on evaluation accuracy and operability; determining the weight of each factor in the safety fuzzy comprehensive evaluation factor set by utilizing analytic hierarchy process to obtain a weight vector of each factor set; dividing the safety risk grade of the steel structure communication iron tower into a plurality of grades based on empirical data, and constructing a safety fuzzy comprehensive evaluation set based on the divided grades; constructing a safety evaluation standard and a membership function of each safety level according to the safety fuzzy comprehensive evaluation set, constructing a risk judgment matrix of each factor set based on the membership function, and performing step-by-step calculation according to the weight vector and the risk judgment matrix to obtain a membership degree vector of the whole steel structure communication tower; and carrying out safety evaluation on the steel structure communication iron tower based on the membership of each grade shown by the membership vector. The method is simple and easy to understand in principle and calculation, and convenient for engineering technicians to master and use.

Description

Technical Field

[0001] The present invention relates to the technical field of safety evaluation, and particularly relates to a safety evaluation method for steel structure communication towers based on fuzzy mathematics. Background Technique

[0002] Steel structures have the characteristics of high strength, good overall rigidity, strong deformation ability, recyclability, etc., and play an irreplaceable role in China's industrial production. As a type of steel structure, communication towers are important infrastructure to ensure the normal use of mobile communication. In recent years, in order to meet the growing communication needs of people, the construction projects of steel structure communication towers have been increasing continuously and have spread all over urban and rural areas. After the construction of steel structure communication towers is completed and put into use, they are in the outdoor natural environment for a long time. Due to possible accidental or human defects in the design, processing, construction, and use of the tower body structure itself, as well as the effects of natural disasters such as strong winds, rain, snow, and earthquakes, safety accidents such as the collapse of steel structure communication towers often occur, causing serious economic losses and casualties. Therefore, efficiently and accurately evaluating the safety risk level of steel structure communication towers can accurately identify potential safety risks, guide the formulation of safety management work, and ensure its stability and reliability during operation.

[0003] However, due to the complex and changeable use environment of steel structure communication towers, there are many fuzzy factors that induce safety accidents of steel structure communication towers in all aspects such as their design, processing, construction, and use. For example, inaccurate geological exploration data and improper design selection during design; unqualified steel materials and non-standard processing during processing; bolts not tightened in place and foundation construction not meeting requirements during construction; no protection measures and insufficient maintenance during use, etc. The objective existence of these fuzzinesses makes it impossible to accurately quantify various risk influencing factors, seriously hindering the development of the safety evaluation of steel structure communication towers. Therefore, in order to accurately describe the levels of various fuzzy factors and their influence relationships on the safety of steel structure communication towers, it is necessary to introduce fuzzy mathematics to establish a fuzzy comprehensive evaluation method for steel structure communication towers to efficiently and accurately evaluate their safety levels. Summary of the Invention

[0004] Based on the above background, the present invention proposes a safety evaluation method for steel structure communication towers based on fuzzy mathematics, which includes the construction of a safety fuzzy comprehensive evaluation factor set, the determination of factor weights, the construction of an evaluation set, and a comprehensive evaluation, and finally realizes the safety evaluation of steel structure communication towers.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A safety evaluation method for steel structure communication towers based on fuzzy mathematics includes the following steps:

[0007] Construct a safety fuzzy comprehensive evaluation factor set with a three-level architecture based on evaluation accuracy and operability;

[0008] Use analytic hierarchy process to determine the weights of the factors in the safety fuzzy comprehensive evaluation factor set, and obtain the weight vectors of each factor set;

[0009] Based on empirical data, divide the safety risk levels of steel structure communication towers into several levels, and construct a safety fuzzy comprehensive evaluation set based on the divided levels;

[0010] According to the safety fuzzy comprehensive evaluation set, construct safety evaluation criteria and membership functions for each safety level, construct a risk judgment matrix for each factor set based on the membership functions, and calculate step by step according to the weight vectors and the risk judgment matrix to obtain the membership degree vector of the entire steel structure communication tower;

[0011] Based on the membership degrees of each level indicated by the membership degree vector, conduct safety evaluation on the steel structure communication tower.

[0012] Furthermore, the safety fuzzy comprehensive evaluation factor set of the three-level architecture includes a first-level factor set, a second-level factor set subordinate to each factor in the first-level factor set, and a third-level factor set subordinate to each factor in the second-level factor set; the value ranges of each factor are standardized to [0, 100], and the larger the value, the greater the degree of influence of the factor on the safety of the steel structure communication tower.

[0013] The safety fuzzy comprehensive evaluation factor set refers to the set composed of various factors that affect the safety of steel structure communication towers. From the perspectives of evaluation accuracy and operability, the safety evaluation factor set of steel structure communication towers generally requires a three-level architecture.

[0014] In some embodiments, assume that according to the experience of relevant staff, the three-level factor set affecting the safety of steel structure communication towers is shown in Table 1. Among them, {u 1 , u 2 , …, u n} represents the first-level factor set, with a total of n; the second column of respectively represent the second-level factor sets subordinate to factors u 1 , u 2 , …, u n , with m 1 , m 2 , …, m n respectively; the third column of respectively represent the third-level factor sets subordinate to factors , with respectively, and the other symbols in the third column have the same meaning. In addition, the value ranges of each factor are standardized to [0, 100], and the larger the level value, the greater the degree of influence of the factor on the safety of the steel structure communication tower.

[0015] Table 1

[0016]

[0017] Furthermore, the analytic hierarchy process is used to determine the weights of each factor in the safety fuzzy comprehensive evaluation factor set, and the weight vectors of each factor set obtained include:

[0018] Based on the empirical data and the preset scale, the importance of all factors in each factor set is compared in turn, and a consistency judgment matrix for each factor set is constructed based on the comparison results;

[0019] The constructed consistency judgment matrix is subjected to a consistency test, and the consistency judgment matrix with a consistency ratio greater than the preset value is corrected;

[0020] All elements in the consistency judgment matrix are first normalized by column and then averaged by row to obtain the weight vector of the factor set corresponding to the consistency judgment matrix.

[0021] Furthermore, based on the empirical data and the preset scale, the importance of all factors in each factor set is compared in turn, and the construction of the consistency judgment matrix for each factor set includes:

[0022] Based on the empirical data and the preset scale, pairwise comparisons of the importance of all factors in the three-level factor set under the same secondary factor with respect to the superior factor are carried out, a consistency judgment matrix for the three-level factor set is formed based on the comparison results, and the consistency judgment matrix construction for the three-level factor sets under all secondary factors is carried out accordingly;

[0023] Based on the empirical data and the preset scale, pairwise comparisons of the importance of all factors in the two-level factor set under the same primary factor with respect to the superior factor are carried out, a consistency judgment matrix for the two-level factor set is formed based on the comparison results, and the consistency judgment matrix construction for the two-level factor sets under all primary factors is carried out accordingly;

[0024] Based on the empirical data and the preset scale, pairwise comparisons of the importance of safety evaluation of all factors in the primary factor set are carried out, and a consistency judgment matrix corresponding to the primary factor set is formed based on the comparison results.

[0025] In some embodiments, the process of constructing the consistency judgment matrix of each level of evaluation factor set includes the following steps:

[0026] For the three-level safety fuzzy comprehensive evaluation factor set belonging to the same secondary factor u i,j (i = 1, 2, …, n; j = 1, 2, …, m i ) According to the experience of relevant staff and the scale shown in Table 3, all factors are evaluated regarding the superior factor ui,j Pairwise comparison of importance, and record as factor and factor The ratio of importance, then factor and factor The ratio of importance is Thus, a three-level factor set The consistency judgment matrix A i,j is

[0027]

[0028] And so on, complete the construction of the consistency judgment matrix for the three-level factor sets under all secondary factors.

[0029] Table 3

[0030]

[0031]

[0032] Similarly, for the secondary safety fuzzy comprehensive evaluation factor sets i (i = 1, 2,..., n) subordinate to the same primary factor u Conduct pairwise comparisons of the importance of all factors with respect to the superior factor u i and record as the ratio of importance of factor and factor Then the ratio of importance of factor and factor is Thus, a secondary factor set The consistency judgment matrix A i is

[0033]

[0034] And so on, complete the construction of the consistency judgment matrix for the secondary factor sets under all primary factors.

[0035] Similarly, for the primary safety fuzzy comprehensive evaluation factor set {u 1 , u 2 , …, u n}, conduct pairwise comparisons of the importance of all factors with respect to the safety evaluation of steel structure communication towers and record as the ratio of importance of factor and factor Then the ratio of importance of factor and factor is Thus, a primary factor set {u 1 , u2 ,…,u n The consistency judgment matrix A of {...} is

[0036]

[0037] Thus, the construction of the consistency judgment matrix for each level of the evaluation factor set is completed.

[0038] In some embodiments, the consistency test for the constructed consistency judgment matrix includes the following process:

[0039] For any of the above constructed judgment matrices, first calculate the maximum eigenvalue of the matrix and denote it as λ max , then the calculation formula for the consistency index CI is

[0040]

[0041] In the formula, h represents the order of the matrix.

[0042] Next, according to the order h of the matrix, use Table 3 to find the value of the average random consistency index RI.

[0043] Table 3

[0044]

[0045]

[0046] Finally, calculate the consistency ratio CR as

[0047]

[0048] When CR < 0.10, it is considered that the consistency of the judgment matrix is acceptable; otherwise, the judgment matrix should be appropriately corrected.

[0049] In some embodiments, obtaining the weight vector of the factor set corresponding to the consistency judgment matrix includes the following process:

[0050] For the three-level safety fuzzy comprehensive evaluation factor set Using the judgment matrix A of formula (1) i,j , first normalize all the elements in the matrix by column and then take the average by row to obtain the weight vector w of this factor set i,j which is

[0051]

[0052] In the formula, are the weights of the three-level factors respectively.

[0053] Similarly, for the two-level safety fuzzy comprehensive evaluation factor set and the first-level safety fuzzy comprehensive evaluation factor set {u 1 , u 2 , …, u n}, respectively use the judgment matrix A i and the judgment matrix A in Formula (2) and Formula (3) to obtain the weight vectors w i and w of these factor sets as shown in Formulas (7) and (8) respectively.

[0054]

[0055] In the formula, are respectively the weights of the secondary factors .

[0056]

[0057] In the formula, w 1 , w 2 , …, w n are respectively the weights of the first-level factors u 1 , u 2 , …, u n .

[0058] Furthermore, based on the empirical data, the safety risk levels of the steel structure communication tower are divided into several levels, and a safety fuzzy comprehensive evaluation set is constructed based on the divided levels, including:

[0059] The safety fuzzy comprehensive evaluation set refers to the set of safety risk levels of the steel structure communication tower. Based on the empirical data, the safety risk levels of the steel structure communication tower are divided into five levels, namely: major safety risk level V, relatively large safety risk level IV, medium safety risk level III, general safety risk level II, and low safety risk level I;

[0060] Construct a safety fuzzy comprehensive evaluation set V = {Level I, Level II, Level III, Level IV, Level V} (9).

[0061] Furthermore, construct safety evaluation criteria and membership functions for each safety level according to the safety fuzzy comprehensive evaluation set, including:

[0062] Based on the empirical data and the safety fuzzy comprehensive evaluation set, determine the boundary values corresponding to each safety risk level.

[0063] In some embodiments, according to the safety fuzzy comprehensive evaluation set in Formula (9), combined with the experience of relevant staff, for any three-level safety fuzzy comprehensive evaluation factor u i,j,l , establish the safety evaluation criteria shown in Table 4, where 0 < α i,j,l,I < α i,j,l,II < α i,j,l,III < αi,j,l,IV <α i,j,l,V <100 is the factor u i,j,l Five dividing lines for the safety risk level.

[0064] Table 4

[0065]

[0066] The membership degree characterizes the degree to which the factor level value belongs to each safety risk level, and the membership function is a mathematical function used to describe the membership degree. Under the standard shown in Table 4, "Level I" is a small-sized fuzzy concept. The lower the factor level value, the greater the degree of belonging to "Level I"; "Level II", "Level III", and "Level IV" are intermediate fuzzy concepts. When the factor level value is within a certain intermediate range, the corresponding membership degree is greater; "Level V" is a large-sized fuzzy concept. The greater the factor level value, the greater the degree of belonging to "Level V". Therefore, using the trapezoidal membership function, construct the membership functions of the five safety levels for any three-level safety fuzzy comprehensive evaluation factor u i,j,l are as follows:

[0067] Membership function of Level I r i,j,l,I (x)

[0068]

[0069] Membership function of Level II r i,j,l,II (x)

[0070]

[0071] Membership function of Level III r i,j,l,III (x)

[0072]

[0073] Membership function of Level IV r i,j,l,IV (x)

[0074]

[0075] Membership function of Level V r i,j,l,V (x)

[0076]

[0077] In the formula, x represents the level value of the factor, H(·) is the indicatrix function. When the condition in the parentheses is satisfied, H(·) takes 1, otherwise H(·) is 0; 0 < α i,j,l,I <α i,j,l,II <α i,j,l,III <α i,j,l,IV <α i,j,l,V <100 are the boundary values for each safety risk level.

[0078] Further, a risk judgment matrix for each factor set is constructed based on the membership function, and the membership degree vector of the entire steel structure communication tower is calculated step by step according to the weight vector and the risk judgment matrix, including:

[0079] For any third-level factor set i,j subordinate to the same second-level factor u Use the membership functions shown in Formulas (10) to (14) to construct the risk judgment matrix of this factor set:

[0080]

[0081] According to the weight vector, obtain the membership degree vector r i,j of the second-level factor u i,j as:

[0082] r i,j = w i,j ×R i,j (15)

[0083]

[0084] where w i,j is the weight vector corresponding to the third-level factor set under the second-level factor u i,j , and are the weights of each third-level factor in this third-level factor set respectively;

[0085] For all second-level safety fuzzy comprehensive evaluation factors i under the same first-level factor u Obtain the membership degree vectors of all factors according to the above formula, and denote them respectively as Thus, construct the risk judgment matrix R of the second-level factor set i as:

[0086]

[0087] In the formula, T is the transpose symbol;

[0088] After that, calculate the membership degree vector r i of the first-level factor u i as:

[0089] r i = w i ×R i (17)

[0090] where is the first-level factor u iThe weight vector corresponding to the secondary factor set below is the weight of each secondary factor in the secondary factor set respectively;

[0091] For all primary factors u 1 , u 2 , …, u n , according to the above formula, the membership degree vectors of all factors u 1 , u 2 , …, u n are obtained and denoted as r 1 , r 2 , …, r n respectively, so as to construct the risk judgment matrix R of the primary factor set {u 1 , u 2 , …, u n} as

[0092]

[0093] Finally, the membership degree vector r of the entire steel structure communication tower is obtained as

[0094] r = w × R (19)

[0095] where w = (w 1 , w 2 , …, w n ) is the weight of each primary factor in the primary factor set.

[0096] The present invention has the following advantages compared with the prior art:

[0097] ① For the safety evaluation of steel structure communication towers with numerous influencing factors and difficult to quantify, the present invention constructs a safety fuzzy comprehensive evaluation factor set with a three - level architecture, determines the weights of each level of factors by using the analytic hierarchy process, and describes the membership degree of each factor level belonging to each safety risk level by using the trapezoidal membership function. Finally, the safety evaluation of the steel structure communication tower is realized, thus effectively supporting the formulation of the safety management work of the steel structure communication tower.

[0098] ② The method principle and calculation proposed by the present invention are simple and easy to understand, easy to implement, convenient for engineering and technical personnel to master and use, and convenient for application and popularization. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] Figure 1 is a schematic flow chart of an embodiment of the safety evaluation method for the steel structure communication tower of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0100] Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present invention. It should be understood that the drawings and embodiments of the present invention are only for exemplary purposes and are not used to limit the protection scope of the present invention.

[0101] See Figure 1 , embodiments of the present invention provide a safety evaluation method for steel structure communication towers based on fuzzy mathematics, and the specific implementation steps are as follows:

[0102] S1. Construct a three-level safety fuzzy comprehensive evaluation factor set based on evaluation accuracy and operability.

[0103] According to the experience of relevant staff, the three-level factors affecting the safety of steel structure communication towers are determined as shown in Table 5, which includes the expert scoring values of the three-level factors. The larger the score, the higher the degree of influence of the factor on the safety of a certain steel structure communication tower.

[0104] Table 5

[0105]

[0106]

[0107] S2. Use the analytic hierarchy process to determine the weights of the factors in the safety fuzzy comprehensive evaluation factor set, and obtain the weight vectors of each factor set.

[0108] According to the safety evaluation factors of the steel structure communication tower provided in Table 5 and the experience of relevant staff, use the analytic hierarchy process to determine the weights of the factors. The specific steps are as follows:

[0109] ① Construct a consistency judgment matrix for each level of evaluation factor set

[0110] First, construct a judgment matrix for the three-level safety fuzzy comprehensive evaluation factor set. For the factor set {u 1,1,1 , u 1,1,2}, determine that the importance ratio of factor u 1,1,1 to factor u 1,1,2 is 1 / 3. Therefore, the consistency judgment matrix of this factor set is

[0111]

[0112] For the factor set {u 1,2,1 , u 1,2,2 , u 1,2,3}, determine factor u 1,2,1 , factor u1,2,2 , factor u 1,2,3 are equally important. Therefore, the consistency judgment matrix of this factor set is

[0113]

[0114] For the factor set {u 1,3,1 , u 1,3,2}, it is determined that the importance ratio of factor u 1,3,1 to factor u 1,3,2 is 1 / 2. Therefore, the consistency judgment matrix of this factor set is

[0115]

[0116] For the factor set {u 1,4,1 , u 1,4,2}, it is determined that the importance ratio of factor u 1,4,1 to factor u 1,4,2 is 1 / 3. Therefore, the consistency judgment matrix of this factor set is

[0117]

[0118] For the factor set {u 1,5,1 , u 1,5,2 , u 1,5,3}, it is determined that the importance ratio of factor u 1,5,1 to factor u 1,5,2 is 2, and the importance ratio to factor u 1,5,3 is 1; the importance ratio of factor u 1,5,2 to factor u 1,5,3 is 1 / 2. Therefore, the consistency judgment matrix of this factor set is

[0119]

[0120] For the factor set {u 2,1,1 , u 2,1,2 , u 2,1,3}, it is determined that the importance ratio of factor u 2,1,1 to factor u 2,1,2 is 2, and the importance ratio to factor u 2,1,3 is 4; the importance ratio of factor u 2,1,2 to factor u 2,1,3 is 2. Therefore, the consistency judgment matrix of this factor set is

[0121]

[0122] For the factor set {u 2,2,1 , u 2,2,2 , u 2,2,3}, it is determined that factor u2,2,1 The ratio of importance to factor u 2,2,2 is 1 / 2, and the ratio of importance to factor u 2,2,3 is 1 / 2; the ratio of importance of factor u 2,2,2 to factor u 2,2,3 is 1. Therefore, the consistency judgment matrix of this factor set is

[0123]

[0124] Next, a consistency judgment matrix is constructed for the secondary safety fuzzy comprehensive evaluation factors. For the factor set {u 1,1 , u 1,2 , u 1,3 , u 1,4 , u 1,5}, it is determined that the ratios of importance of factor u 1,1 to factors u 1,2 , u 1,3 , u 1,4 are all 6, and the ratio of importance to factor u 1,5 is 3; the ratios of importance of factor u 1,2 to factors u 1,3 , u 1,4 are all 1, and the ratio of importance to factor u 1,5 is 1 / 2; the ratios of importance of factor u 1,3 to factors u 1,4 are all 1, and the ratio of importance to factor u 1,5 is 1 / 2; the ratio of importance of factor u 1,4 to factor u 1,5 is 1 / 2. Therefore, the consistency judgment matrix of this factor set is

[0125]

[0126] For the factor set {u 2,1 , u 2,2}, it is determined that the ratio of importance of factor u 2,1 to factor u 2,2 is 1 / 5. Therefore, the consistency judgment matrix of this factor set is

[0127]

[0128] Finally, for the primary safety fuzzy comprehensive evaluation factor set {u 1 , u 2}, it is determined that the ratio of importance of factor u 1 to factor u 2 is 1. Therefore, the consistency judgment matrix of this factor set is

[0129]

[0130] ②Consistency check of the judgment matrix

[0131] The maximum eigenvalue of the judgment matrix in calculation formulas (21) to (30) is shown in Table 6 respectively as follows:

[0132] Table 6

[0133] Judgment matrix <![CDATA[A 1,1 > <![CDATA[A 1,2 > <![CDATA[A 1,3 > <![CDATA[A 1,4 > <![CDATA[A 1,5 > <![CDATA[A 2,1 > <![CDATA[A 2,2 > <![CDATA[A 1 > <![CDATA[A 2 > A <![CDATA[λ max > 2 3 2 2 3 3 3 5 2 2

[0134] Therefore, according to formulas (4) and (5), it can be known that the consistency ratio CR values of all judgment matrices are 0, meeting the requirement of CR < 0.10 and passing the consistency check.

[0135] ③Weight calculation

[0136] First, using the judgment matrices shown in formulas (6) and (21) to (27), the weight vectors of each three - level safety fuzzy comprehensive evaluation factor set are calculated and shown in Table 7 as follows:

[0137] Table 7

[0138] Factor set Weight vector <![CDATA[{u 1,1,1 ,u 1,1,2}]]> <![CDATA[w 1,1 =(0.25, 0.75)]]> <![CDATA[{u 1,2,1 ,u 1,2,2 ,u 1,2,3}]]> <![CDATA[w 1,2 =(1 / 3, 1 / 3, 1 / 3)]]> <![CDATA[{u 1,3,1 ,u 1,3,2}]]> <![CDATA[w 1,3 =(1 / 3, 2 / 3)]]> <![CDATA[{u 1,4,1 ,u 1,4,2}]]> <![CDATA[w 1,4 =(0.25, 0.75)]]> <![CDATA[{u 1,5,1 ,u 1,5,2 ,u 1,5,3}]]> <![CDATA[w 1,5 =(0.4, 0.2, 0.4)]]> <![CDATA[{u 2,1,1 ,u 2,1,2 ,u 2,1,3}]]> <![CDATA[w 2,1 =(0.5714, 0.2857, 0.1429)]]> <![CDATA[{u 2,2,1 ,u 2,2,2 ,u 2,2,3}]]> <![CDATA[w 2,2 =(0.2, 0.4, 0.4)]]>

[0139] Next, using the judgment matrices shown in formulas (7) and (28) to (29), the weight vectors of each two - level safety fuzzy comprehensive evaluation factor set are calculated and shown in Table 8 as follows:

[0140] Table 8

[0141] Factor set Weight vector <![CDATA[{u 1,1 ,u 1,2 ,u 1,3 ,u 1,4 ,u 1,5}]]> <![CDATA[w 1 =(0.5455, 0.0909, 0.0909, 0.0909, 0.1818)]]> <![CDATA[{u 2,1 ,u 2,2}]]> <![CDATA[w 2 =(0.1667, 0.8333)]]>

[0142] Finally, using the judgment matrix shown in formulas (8) and (30), the weight vector of the first - level safety fuzzy comprehensive evaluation factor set {u 1 , u 2} is

[0143] w = (0.5, 0.5) (30)

[0144] S3. Based on empirical data, divide the safety risk levels of steel - structure communication towers into several levels, and construct a safety fuzzy comprehensive evaluation set based on the divided levels.

[0145] The safety risk levels of steel - structure communication towers are divided into five levels: major safety risk (Level V), relatively large safety risk (Level IV), medium safety risk (Level III), general safety risk (Level II), and low safety risk (Level I). Therefore, establish the safety fuzzy comprehensive evaluation set V of steel - structure communication towers as

[0146] V = {Level I, Level II, Level III, Level IV, Level V} (31)

[0147] S4. Construct safety evaluation criteria and membership functions for each safety level based on the safety fuzzy comprehensive evaluation set, construct a risk judgment matrix for each factor set based on the membership functions, and calculate the membership degree vector of the entire steel structure communication tower step by step according to the weight vector and the risk judgment matrix. The specific steps are as follows:

[0148] ① Construction of safety evaluation criteria

[0149] According to the experience of relevant staff, determine that all third-level factors share the safety risk evaluation criteria shown in Table 9 below.

[0150] Table 9

[0151]

[0152] ② Construction of membership functions for each safety level

[0153] Substitute the grade boundary values in Table 9 into Formulas (10) to (14) to obtain the membership functions for each safety level as follows:

[0154] Membership function of level I, r i,j,l,II (x)

[0155]

[0156] Membership function of level II, r i,j,l,II (x)

[0157]

[0158] Membership function of level III, r i,j,l,III (x)

[0159]

[0160] Membership function of level IV, r i,j,l,IV (x)

[0161]

[0162] Membership function of level V, r i,j,l,V (x)

[0163]

[0164] ③ Fuzzy comprehensive evaluation

[0165] First, for each third-level safety fuzzy comprehensive evaluation factor set and its values shown in Table 5, use the membership functions shown in Formulas (33) to (37) to calculate the judgment matrix of each third-level safety fuzzy comprehensive evaluation factor set according to Formula (15), as shown in Table 10 below.

[0166] Table 10

[0167]

[0168]

[0169] Next, according to the weight vectors and judgment matrices of the three-level safety fuzzy comprehensive evaluation factor sets listed in Table 7 and Table 10, the judgment matrices of each secondary safety fuzzy comprehensive evaluation factor set are calculated using formulas (16) and (17) as shown in Table 11.

[0170] Table 11

[0171]

[0172] Subsequently, according to the weight vectors and judgment matrices of the secondary safety fuzzy comprehensive evaluation factor sets listed in Table 8 and Table 11, the judgment matrix of the primary safety fuzzy comprehensive evaluation factor set is calculated using formulas (18) and (19) as

[0173]

[0174] Finally, according to the weight vector and judgment matrix of the primary safety fuzzy comprehensive evaluation factor set shown in formulas (31) and (38), the membership degree vector r of the steel structure communication tower is calculated using formula (20) as

[0175] r = (0.3408 0.0803 0.1704 0.1931 0.2154) (38)

[0176] S5. Based on the membership degrees of each level shown by the membership degree vector, perform the safety evaluation of the steel structure communication tower.

[0177] It can be seen from the membership degree vector r calculated in step S4 that the membership degree of level I is the largest. Therefore, it is determined that the safety risk level of this steel structure communication tower is level I, that is, low safety risk. Thus, the safety evaluation of this steel structure communication tower is completed.

[0178] It should be noted that the method of the embodiment of the present invention can be executed by a single device, such as a computer or a server, etc. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In this case of a distributed scenario, one of these multiple devices can only execute one or more steps of the method of the embodiment of the present invention, and these multiple devices will interact with each other to complete the described method.

[0179] Embodiments of the present invention are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present invention shall be included within the protection scope of the present invention.

Claims

1. A safety evaluation method for steel structure communication tower based on fuzzy mathematics, characterized in that: The steps include: A set of safety fuzzy comprehensive evaluation factors with a three-level architecture is constructed based on evaluation accuracy and operability; Determine the weight of each factor in the safety fuzzy comprehensive evaluation factor set by using hierarchical analysis to obtain the weight vector of each factor set; Based on empirical data, the safety risk level of steel structure communication towers is divided into several levels, and a safety fuzzy comprehensive evaluation set is constructed based on the divided levels; Constructing a safety evaluation standard and a membership function of each safety level according to the safety fuzzy comprehensive evaluation set, constructing a risk judgment matrix of each factor set based on the membership function, and calculating the membership vector of the entire steel structure communication tower step by step according to the weight vector combined with the risk judgment matrix; Based on the membership levels shown by the membership vector, a safety evaluation of the steel structure communication tower is performed.

2. The safety evaluation method for steel structure communication tower based on fuzzy mathematics as claimed in claim 1 is characterized in that: The three-level architecture safety fuzzy comprehensive evaluation factor set includes a first-level factor set, a second-level factor set under each factor in the first-level factor set, and a third-level factor set under each factor in the second-level factor set; the value range of each factor is standardized to [0,100], and the larger the value, the greater the impact of the factor on the safety of the steel structure communication tower.

3. The safety evaluation method for steel structure communication tower based on fuzzy mathematics as claimed in claim 2 is characterized in that: The weight of each factor in the safety fuzzy comprehensive evaluation factor set is determined by using hierarchical analysis, and the weight vector of each factor set is obtained, including: Based on empirical data and preset scales, the importance of all factors in each factor set is compared in turn, and the consistency judgment matrix of each factor set is constructed based on the comparison results; Conduct consistency check on the constructed consistency judgment matrix, and modify the consistency judgment matrix whose consistency ratio is greater than the preset value; All elements in the consistency judgment matrix are first normalized by column and then averaged by row to obtain a weight vector of the factor set corresponding to the consistency judgment matrix.

4. The safety evaluation method for steel structure communication tower based on fuzzy mathematics as claimed in claim 3 is characterized in that: Based on the empirical data and the preset scale, the importance of all factors in each factor set is compared in turn, and the consistency judgment matrix of each factor set is constructed based on the comparison results, including: Based on empirical data and preset scales, all factors in the third-level factor set under the same second-level factor are compared with each other regarding the importance of the upper-level factor. Based on the comparison results, a consistency judgment matrix of the third-level factor set is formed, and then the consistency judgment matrix of the third-level factor set under all second-level factors is constructed accordingly. Based on empirical data and preset scales, all factors in the secondary factor set under the same primary factor are compared with each other regarding the importance of the upper-level factor. Based on the comparison results, a consistency judgment matrix of the secondary factor set is formed, and then the consistency judgment matrix of the secondary factor set under all primary factors is constructed accordingly. Based on empirical data and preset scales, the safety evaluation importance of all factors in the first-level factor set is compared pairwise, and a consistency judgment matrix corresponding to the first-level factor set is formed based on the comparison results.

5. The safety evaluation method for steel structure communication tower based on fuzzy mathematics as claimed in claim 3 is characterized in that: Based on empirical data, the safety risk level of steel structure communication towers is divided into several levels, and a safety fuzzy comprehensive evaluation set is constructed based on the divided levels, including: Based on empirical data, the safety risk level of steel structure communication towers is divided into five levels, namely: major safety risk level V, relatively large safety risk level IV, medium safety risk level III, general safety risk level II and low safety risk level I; Construct the safety fuzzy comprehensive evaluation set V = {level I, level II, level III, level IV, level V}.

6. The safety evaluation method for steel structure communication tower based on fuzzy mathematics as claimed in claim 5 is characterized in that: The safety evaluation standard and the membership functions of each safety level are constructed based on the safety fuzzy comprehensive evaluation set, including: Based on the empirical data and the safety fuzzy comprehensive evaluation set, determining the cutoff value corresponding to each safety risk level; Using the trapezoidal membership function, the five safety level membership functions of any three-level safety fuzzy comprehensive evaluation factors are constructed as follows: Level I membership function r i,j,l,I (x) Level II membership function r i,j,l,II (x) Level III membership function r i,j,l,III (x) IV level membership function r i,j,l,IV (x) V-level membership function r i,j,l,V (x) In the formula, x represents the level value of the factor, H(·) is the indicative function, and H(·) takes 1 when the conditions in the brackets are met, otherwise H(·) takes 0; 0<α i,j,l,I <α i,j,l,II <α i,j,l,III <α i,j,l,IV <α i,j,l,v <100 is the dividing value for each safety risk level.

7. The safety evaluation method for steel structure communication tower based on fuzzy mathematics as claimed in claim 6 is characterized in that: Constructing a risk judgment matrix for each factor set based on the membership function, and calculating the membership vector of the entire steel structure communication tower step by step according to the weight vector combined with the risk judgment matrix includes: For any belonging to the same secondary factor u i,j The three-level factor set Construct the risk judgment matrix of this factor set: According to the weight vector, we can get the secondary factor u i,j The membership vector r i,j for: r i,j =w i,j ×R i,j Among them, w i,j is the secondary factor u i,j The weight vector corresponding to the three-level factor set under are the weights of each third-level factor in the three-level factor set; For the same first-level factor u i All secondary safety fuzzy comprehensive evaluation factors under According to the above formula, all factors The membership vector of Thus, the second-level factor set is constructed The risk judgment matrix R i for: Where T is the transposition symbol; After that, calculate the first-level factor u i The membership vector r i for: r i =w i ×R i in, is the first-level factor u i The weight vector corresponding to the secondary factor set under are the weights of each secondary factor in the secondary factor set; For all first-level factors u1,u2,…,u n According to the above formula, we can get all factors u1,u2,…,u n The membership vectors are denoted as r1, r2, …, r n , thus constructing the first-level factor set {u1,u2,…,u n The risk judgment matrix R of} is Finally, the membership vector r of the entire steel structure communication tower is obtained as r = w × R Where w=(w1,w2,…,w n ) is the weight of each first-level factor in the first-level factor set.

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