Bridge girder erection machine pre-construction safety risk comprehensive rating method based on multi-attribute decision

Abstract

The invention provides a multi-attribute decision-making-based comprehensive safety risk rating method for a bridge girder erection machine before construction, and the method comprises the steps: obtaining the related information data of the bridge girder erection machine before construction, and enabling the related information data to at least comprise an equipment state, an operator condition and an environment condition; constructing a bridge girder erection machine accident case library, and extracting risk factors influencing safe operation from the accident case library; establishing a safety risk comprehensive rating index system according to the risk factors; performing data mining on the accident case library, and determining weight values of the risk factors; according to the related information data and the weight value, calculating a safety risk comprehensive evaluation value before construction of the bridge girder erection machine; and according to the comprehensive evaluation value, judging whether the bridge girder erection machine has conditions for carrying out girder erection operation. The comprehensive weight value and the index grade are comprehensive and accurate, when safety risk comprehensive rating is carried out before bridge girder erection machine construction, the related weight value can be directly used for calculation, the rating result can be conveniently and rapidly obtained, and beam erection construction or rectification stopping is convenient to carry out.

Description

Technical Field

[0001] The invention relates to a comprehensive rating method for safety risks before bridge erection machine construction, in particular to a comprehensive rating method for safety risks before bridge erection machine construction based on multi-attribute decision making. Background Art

[0002] At present, there are few studies on the comprehensive safety status rating of bridge erection machines before construction. Domestic research on bridge erection machine safety issues mainly focuses on the safety evaluation during the construction process of bridge erection machines, and the research content has the following deficiencies:

[0003] 1. Current safety assessment methods for bridge-erecting machines tend to focus on safety conditions during construction. Pre-construction safety conditions and the availability of beam-erecting conditions are understudied, resulting in limited guidance for pre-construction preparations. Without a comprehensive safety assessment of the bridge-erecting machine's construction conditions before construction, it's impossible to comprehensively and intuitively assess the risk level of the machine's beam-erecting operations. This can't provide a reliable basis for the upcoming beam-erecting operations, nor can it provide guidance for the management of the bridge-erecting machine and its decision-making, or for the operators' operations. Blindly commencing construction could result in irreparable losses.

[0004] 2. Statistical analysis of past bridge-erecting machine accidents reveals that many accidents are caused by factors beyond the equipment itself. Existing bridge-erecting machine safety evaluation research has primarily focused on the equipment itself, failing to adequately understand the importance of human, technical, management, and environmental factors that influence safe bridge-erecting machine operation. These factors have been neglected or underestimated, resulting in the existing bridge-erecting machine construction safety research system failing to fully encompass the comprehensive safety status of the machine prior to construction.

[0005] 3. The factors affecting the safety of bridge-building machine construction are complex and there are many evaluation indicators. The existing safety evaluation methods mostly use fuzzy comprehensive evaluation methods, probabilistic evaluation methods, etc. to evaluate the equipment status during the construction process. The identification of randomness and fuzziness is not perfect, and expert scoring methods are mostly used for weight calculation, which is highly subjective. The evaluation results obtained have large deviations and are insufficient in guiding construction safety. Summary of the Invention

[0006] To solve the above problems, the present invention proposes a comprehensive rating method for safety risks before bridge-erecting machine construction based on multi-attribute decision-making. It mainly realizes a comprehensive and objective rating of the safety risk status after the installation and preparation work of the bridge-erecting machine equipment is completed and before the bridge-erecting construction, and provides a decision-making basis for whether the conditions for bridge-erecting are met.

[0007] To solve the above technical problems, the technical solution adopted by the present invention is: a comprehensive rating method for safety risks before bridge erection machine construction based on multi-attribute decision making, the method comprising: S1, obtaining relevant information data before bridge erection machine construction, the relevant information data at least including equipment status, operator status and environmental conditions;

[0008] S2. Build a bridge erection machine accident case database, and extract risk factors affecting safe operation from the accident case database;

[0009] S3. Establish a comprehensive safety risk rating indicator system based on the risk factors;

[0010] S4. Performing data mining on the accident case database to determine the weight values ​​of the risk factors;

[0011] S5. Calculate a comprehensive safety risk evaluation value before the bridge erection machine is constructed based on the relevant information data and the weight value;

[0012] S6. Determine whether the bridge erection machine is capable of carrying out the beam erection operation based on the comprehensive evaluation value.

[0013] In the preferred solution, in step S1: collecting status information of the bridge erection machine after installation and preparation work are completed, the status information covers the performance of the equipment itself and historical usage records;

[0014] Obtaining data on the qualifications, training, and health status of operating personnel, which is used to assess the impact of human factors on safety;

[0015] Collecting environmental condition information at the construction site, including meteorological, topographical, and geological characteristics;

[0016] Organize technical and management related materials, including construction plans and safety management systems;

[0017] By integrating the above information data, comprehensive basic data for pre-construction safety assessment is formed, which is used for subsequent quantitative analysis of risk factors and comprehensive rating calculation.

[0018] In the preferred solution, in step S2, building a bridge crane accident case library includes:

[0019] Collect historical bridge-erecting machine accident cases by querying public information sources, including government department notifications and construction records;

[0020] Structuring the collected cases to form a database containing various accident causes, wherein the database at least records the time, location, and casualties of the accident;

[0021] Categorize and organize the cases in the database and extract key information related to pre-construction safety;

[0022] Based on the classification results, analyze the common characteristics of accidents and provide data support for the subsequent identification of risk factors;

[0023] By constructing the database, a systematic basis for historical accident analysis is formed.

[0024] In the preferred solution, in step S3, the risk factors establish a comprehensive safety risk rating index system, including:

[0025] The factors affecting the safety of bridge erection machine construction are divided into multiple first-level risk factors, and the first-level risk factors include at least personnel, management, equipment, technology and environment;

[0026] Each type of first-level risk factor is subdivided to determine the corresponding second-level risk factor, which covers specific safety impact factors;

[0027] By organizing the first-level risk factors and the second-level risk factors in a hierarchical manner, a multi-dimensional rating indicator system is formed;

[0028] According to the rating index system, clarify the scope of each factor in the comprehensive rating;

[0029] The establishment of the indicator system provides a structured framework for subsequent weight calculation and risk assessment.

[0030] In the preferred solution, in step S4, the accident case database performs data mining to determine the weight values ​​of the risk factors, including:

[0031] By analyzing the frequency data in the accident case database, a direct impact matrix is ​​constructed, which reflects the interaction relationship between various risk factors;

[0032] The direct impact matrix is ​​normalized using the decision laboratory method to obtain a normalized impact matrix; based on the normalized impact matrix, a comprehensive impact matrix is ​​calculated, and the comprehensive impact matrix is ​​used to determine the influence and the degree of influence of each risk factor;

[0033] Calculate the weight value of the first-level risk factor through analysis of the impact and the impact;

[0034] The Bayesian modified contribution allocation method is used to calculate the weights of secondary risk factors. The calculation combines historical data and prior parameters to ensure the rationality of the weight values.

[0035] In the preferred solution, by analyzing the frequency data in the accident case database, a direct impact matrix A = [a ij ]n×n , the matrix is

[0036] where a ij represents the number of times factors i and j in the kth row are both 1, and the matrix reflects the interaction between the risk factors;

[0037] The direct impact matrix is ​​normalized by the decision laboratory method, and the standardized direct impact matrix N is obtained by maximization. The formula is: And the asymmetric mapping processing is performed on the directional impact of risk factors to obtain a normalized impact matrix;

[0038] According to the normalized influence matrix, the comprehensive influence matrix T is calculated, and the formula is T = N (IN) -1 , where I is the unit matrix, and the comprehensive impact matrix is ​​used to determine the impact of each risk factor and influence

[0039] According to the influence D i and the degree of influence C i Calculate the centrality M of the first-level risk factor i =D i +C i and causal degree N i =D i -C i , and combined with the centrality M i Normalization is performed to obtain the first-level risk factor weights, and the formula is: The weight value of the first-level risk factor is calculated through analysis of the influence and the influence.

[0040] In the preferred solution, the Bayesian modified contribution allocation method is used to calculate the weights of the secondary risk factors and calculate the number of factors that appear in each accident. where X ij =1 means factor j appears in the i-th accident; if factor j appears in the i-th accident, its contribution is After all accidents are accumulated, the total contribution of factor j is where k i ≠0; add the prior parameter γ and calculate the posterior parameter Posterior of each factor j =C j +γ;

[0041] By normalizing the posterior parameters, the formula is: The calculation combines historical data and prior parameters to ensure the rationality of the weight value;

[0042] Using the multi-attribute decision-making combined weighting method, the weight values ​​obtained from the first-level factors and the second-level factors are combined. The formula is: The comprehensive weight value is calculated, where α is the weight of the first-level factor and β is the weight of the second-level factor.

[0043] In the preferred embodiment, in step S5, the relevant information data and the weight values ​​are used to calculate the comprehensive safety risk evaluation value before the construction of the bridge erection machine, including:

[0044] Quantitatively process the relevant information data to obtain an index value of each risk factor, wherein the index value reflects a specific safety status;

[0045] Match the index values ​​with the corresponding weight values ​​and calculate the weighted scores of each factor using a linear weighting method;

[0046] By accumulating the weighted scores of all factors, a comprehensive evaluation value is obtained, which represents the overall safety risk level of the bridge erection machine before construction;

[0047] Determine the safety risk level based on the calculated result of the comprehensive evaluation value and the preset level standard;

[0048] The quantitative analysis of the comprehensive evaluation value provides a data basis for subsequent decision-making.

[0049] In the preferred solution, the formula of the linear weighted comprehensive method is: where w i is the weight of the i-th indicator, x i is the quantitative value of the i-th indicator, and i is the number of indicators.

[0050] In the preferred solution, in step S6, the comprehensive evaluation value determines whether the bridge erection machine has the conditions to carry out the beam erection operation, including:

[0051] Comparing the comprehensive evaluation value with a preset safety risk level standard, wherein the standard is divided into multiple risk levels;

[0052] If the comprehensive evaluation value reaches a higher safety level, it is determined that the bridge erection machine is qualified to carry out the beam erection operation;

[0053] If the comprehensive evaluation value does not meet the safety level requirements, it is determined that corrective measures need to be taken;

[0054] Generating corresponding construction suggestions based on the determination results, wherein the suggestions are used to guide whether to carry out the operation;

[0055] Through the above judgment process, a comprehensive assessment conclusion of the safety status before construction is formed.

[0056] The present invention provides a comprehensive rating method for safety risks before bridge erection machine construction based on multi-attribute decision making, which has the following advantages:

[0057] 1. Shifting the risk assessment process forward. Adhering to the principle of "safety in production, prevention first," this method brings safety risk management and control work forward, conducting a comprehensive safety risk assessment after the installation and preparation of the bridge-erecting machine equipment is complete, but before the start of beam erection construction. The assessment results determine whether the bridge-erecting machine is ready for beam erection, providing guidance for the upcoming beam erection work and effectively preventing blind construction operations that could lead to safety accidents.

[0058] 2. Comprehensive and objective risk factors. To address the issues of existing bridge-erecting machine accident analysis, which relies heavily on subjective experience and has a single data dimension, an objective accident cause analysis method based on big data text mining was proposed. By constructing a structured database containing 39 typical accident cases and applying natural language processing technology to perform entity recognition and semantic analysis on accident reports, five primary risk factors were proposed for pre-construction bridge-erecting machine operations, including personnel factors, technical factors, management factors, equipment factors, and environmental factors. These five primary risk factors were further subdivided into 23 secondary risk factors. Risk factors such as bridge-erecting machine selection, beam transport vehicle safety status, and bridge structure type were creatively proposed. This makes the rating content more complete and comprehensive, and the rating results more objective.

[0059] 3. The rating method is scientific and accurate. This method uses Dematel to calculate the weights of primary risk factors, uses the Bayesian correction contribution allocation method to calculate the weights of secondary risk factors, and uses the multi-attribute decision-making combined weighting method to combine the two weights. The resulting comprehensive weight is more comprehensive, objective, scientific, accurate, and more in line with actual conditions.

[0060] 4. The rating operation is convenient and practical. The comprehensive weight values ​​and index levels determined by this method are comprehensive and accurate. When conducting a comprehensive safety risk rating before bridge erection construction, the relevant weight values ​​can be directly used for calculation, and the rating results can be obtained conveniently and quickly, facilitating the implementation of bridge erection construction or rectification, and playing a significant role in guiding safe and efficient construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The present invention will be further described below with reference to the accompanying drawings and examples:

[0062] Figure 1 This is a flow chart for comprehensive rating of safety risks before construction of the bridge erecting machine of the present invention. DETAILED DESCRIPTION

[0063] Example 1

[0064] like Figure 1As shown, a comprehensive rating method for safety risks before bridge erection machine construction based on multi-attribute decision making comprises: S1, obtaining relevant information data before bridge erection machine construction, wherein the relevant information data at least includes equipment status, operator status and environmental conditions;

[0065] S2. Build a bridge erection machine accident case database, and extract risk factors affecting safe operation from the accident case database;

[0066] S3. Establish a comprehensive safety risk rating indicator system based on the risk factors;

[0067] S4. Performing data mining on the accident case database to determine the weight values ​​of the risk factors;

[0068] S5. Calculate a comprehensive safety risk evaluation value before the bridge erection machine is constructed based on the relevant information data and the weight value;

[0069] S6. Determine whether the bridge erection machine is capable of carrying out the beam erection operation based on the comprehensive evaluation value.

[0070] In the preferred solution, in step S1: collecting status information of the bridge erection machine after installation and preparation work are completed, the status information covers the performance of the equipment itself and historical usage records;

[0071] Obtaining data on the qualifications, training, and health status of operating personnel, which is used to assess the impact of human factors on safety;

[0072] Collecting environmental condition information at the construction site, including meteorological, topographical, and geological characteristics;

[0073] Organize technical and management related materials, including construction plans and safety management systems;

[0074] By integrating the above information data, comprehensive basic data for pre-construction safety assessment is formed, which is used for subsequent quantitative analysis of risk factors and comprehensive rating calculation.

[0075] In the preferred solution, in step S2, building a bridge crane accident case library includes:

[0076] Collect historical bridge-erecting machine accident cases by querying public information sources, including government department notifications and construction records;

[0077] Structuring the collected cases to form a database containing various accident causes, wherein the database at least records the time, location, and casualties of the accident;

[0078] Categorize and organize the cases in the database and extract key information related to pre-construction safety;

[0079] Based on the classification results, analyze the common characteristics of accidents and provide data support for the subsequent identification of risk factors;

[0080] By constructing the database, a systematic basis for historical accident analysis is formed.

[0081] In the preferred solution, in step S3, the risk factors establish a comprehensive safety risk rating index system, including:

[0082] The factors affecting the safety of bridge erection machine construction are divided into multiple first-level risk factors, and the first-level risk factors include at least personnel, management, equipment, technology and environment;

[0083] Each type of first-level risk factor is subdivided to determine the corresponding second-level risk factor, which covers specific safety impact factors;

[0084] By organizing the first-level risk factors and the second-level risk factors in a hierarchical manner, a multi-dimensional rating indicator system is formed;

[0085] Based on the rating indicator system, clarify the scope of each factor in the comprehensive rating;

[0086] The establishment of the indicator system provides a structured framework for subsequent weight calculation and risk assessment.

[0087] In the preferred solution, in step S4, the accident case database performs data mining to determine the weight values ​​of the risk factors, including:

[0088] By analyzing the frequency data in the accident case database, a direct impact matrix is ​​constructed, which reflects the interaction relationship between various risk factors;

[0089] The direct impact matrix is ​​normalized using the decision laboratory method to obtain a normalized impact matrix; based on the normalized impact matrix, a comprehensive impact matrix is ​​calculated, and the comprehensive impact matrix is ​​used to determine the influence and the degree of influence of each risk factor;

[0090] Calculate the weight value of the first-level risk factor through analysis of the impact and the impact;

[0091] The Bayesian modified contribution allocation method is used to calculate the weights of secondary risk factors. The calculation combines historical data and prior parameters to ensure the rationality of the weight values.

[0092] In the preferred solution, by analyzing the frequency data in the accident case database, a direct impact matrix A = [a ij ] n×n , the matrix is

[0093] where a ij represents the number of times factors i and j in the kth row are both 1, and the matrix reflects the interaction between the risk factors;

[0094] The direct impact matrix is ​​normalized by the decision laboratory method, and the standardized direct impact matrix N is obtained by maximization. The formula is: And the asymmetric mapping processing is performed on the directional impact of risk factors to obtain a normalized impact matrix;

[0095] According to the normalized influence matrix, the comprehensive influence matrix T is calculated, and the formula is T = N (IN) -1 , where I is the unit matrix, and the comprehensive impact matrix is ​​used to determine the impact of each risk factor and degree of influence

[0096] According to the influence D i and the degree of influence C i Calculate the centrality M of the first-level risk factor i =D i +C i and causal degree N i =D i -C i , and combined with the centrality M i Normalization is performed to obtain the first-level risk factor weights, and the formula is: The weight value of the first-level risk factor is calculated through analysis of the influence and the influence.

[0097] In the preferred solution, the Bayesian modified contribution allocation method is used to calculate the weights of the secondary risk factors and calculate the number of factors that appear in each accident. where X ij =1 means factor j appears in the i-th accident; if factor j appears in the i-th accident, its contribution is After all accidents are accumulated, the total contribution of factor j is where k i ≠0; add the prior parameter γ and calculate the posterior parameter Posterior of each factor j =C j +γ;

[0098] By normalizing the posterior parameters, the formula is: The calculation combines historical data and prior parameters to ensure the rationality of the weight value;

[0099] Using the multi-attribute decision-making combined weighting method, the weight values ​​obtained from the first-level factors and the second-level factors are combined. The formula is: The comprehensive weight value is calculated, where α is the weight of the first-level factor and β is the weight of the second-level factor.

[0100] In the preferred embodiment, in step S5, the relevant information data and the weight values ​​are used to calculate the comprehensive safety risk evaluation value before the bridge erection machine is constructed, including:

[0101] Quantitatively process the relevant information data to obtain an index value of each risk factor, wherein the index value reflects a specific safety status;

[0102] Match the index values ​​with the corresponding weight values ​​and calculate the weighted scores of each factor using a linear weighting method;

[0103] By accumulating the weighted scores of all factors, a comprehensive evaluation value is obtained, which represents the overall safety risk level of the bridge erection machine before construction;

[0104] Determine the safety risk level based on the calculated result of the comprehensive evaluation value and the preset level standard;

[0105] The quantitative analysis of the comprehensive evaluation value provides a data basis for subsequent decision-making.

[0106] In the preferred solution, the formula of the linear weighted comprehensive method is: where w i is the weight of the i-th indicator, x i is the quantitative value of the i-th indicator, and i is the number of indicators.

[0107] In the preferred solution, in step S6, the comprehensive evaluation value determines whether the bridge erection machine has the conditions to carry out the beam erection operation, including:

[0108] Comparing the comprehensive evaluation value with a preset safety risk level standard, wherein the standard is divided into multiple risk levels;

[0109] If the comprehensive evaluation value reaches a high safety level, it is determined that the bridge erection machine is qualified to carry out the beam erection operation;

[0110] If the comprehensive evaluation value does not meet the safety level requirements, it is determined that corrective measures need to be taken;

[0111] Generating corresponding construction suggestions based on the determination results, wherein the suggestions are used to guide whether to carry out the operation;

[0112] Through the above judgment process, a comprehensive assessment conclusion of the safety status before construction is formed.

[0113] Example 2

[0114] Further illustrate with reference to Example 1, Figure 1 The structure shown in FIG, the implementation steps include the following:

[0115] Step 1: Rating preparation;

[0116] Step 1.1: Collect relevant information on the bridge-building machine, operators, environment, etc. required for the rating;

[0117] Step 1.2: Prepare the rating instrument;

[0118] Step 1.3: Prepare technical information for rating;

[0119] Step 2: Establish a bridge crane accident case database;

[0120] Step 3: Identify the risk factors that affect the safe operation of the bridge-erecting machine and establish a comprehensive safety risk rating index system before the construction of the bridge-erecting machine;

[0121] Step 4: Conduct data mining on the bridge crane accident safety case database to obtain relevant data;

[0122] Step 4.1: Use Dematel to calculate the weight of the first-level risk factors;

[0123] Step 4.2: Calculate the weights of the secondary risk factors using the Bayesian correction contribution allocation method;

[0124] Step 5: Use the multi-attribute decision-making combined weighting method to calculate the comprehensive weight value;

[0125] Step 6: Obtain the quantitative value of each risk factor indicator;

[0126] Step 7: Comprehensively calculate and obtain the comprehensive rating result of the safety risk of the bridge erection machine;

[0127] Step 8: Determine whether the bridge-erecting machine can carry out the bridge-erecting operation.

[0128] The present invention provides a comprehensive safety risk rating method for a bridge erection machine before construction based on multi-attribute decision making, and the specific steps are as follows:

[0129] Step 1: Prepare for rating. Collect relevant information such as the bridge-building machine, operators, environment, etc. required for rating, prepare rating instruments, and prepare technical data for rating.

[0130] Step 2: Establish a case database of bridge crane accidents.

[0131] By querying public information such as lifting machinery accidents and key project construction accidents reported on government websites such as emergency management departments and housing and construction management departments, a case database of bridge-building machine accidents that occurred between 2000 and 2024 was collected and established.

[0132] The third step was to identify the risk factors affecting the safe operation of bridge-erecting cranes and establish a comprehensive rating index system for pre-construction safety risks. Data mining and analogical analysis revealed that bridge-erecting crane accidents are primarily caused by a combination of factors, including personnel, management, equipment, technology, and the environment, and their coupling effects. Therefore, based on the hierarchy of primary and secondary risk factors, the comprehensive rating index system for pre-construction safety risks of bridge-erecting cranes was divided into five primary risk factors and 23 secondary risk factors (see Table 1).

[0133] Table 1 Risk factors for safety rating of bridge erecting machines

[0134]

[0135]

[0136] Step 4: Data mining was performed on the bridge crane accident safety case database to obtain relevant data. This included using Dematel to calculate the weights of the first-level risk factors and the Bayesian modified contribution allocation method to calculate the weights of the second-level risk factors.

[0137] Step 4.1: Obtain the frequency data of first-level risk factors and use the Dematel method to calculate the weight value of first-level risk factors.

[0138] The Decision-Making Trial and Evaluation Laboratory (DTL) is a systematic analysis method that uses graph theory and matrix tools to interpret problems. By analyzing the logical relationships and direct influence matrices between system elements, it can calculate the degree of influence and impact of each element on other elements. This allows the calculation of each element's causal and central degrees, which serve as the basis for constructing a model to determine the causal relationships between elements and the position of each element in the system.

[0139] The Dematel analysis calculation process is as follows:

[0140] 1. Provide a 'relationship matrix', i.e., raw data. By statistically analyzing the bridge crane accident case database, summarize the occurrence frequency of primary risk factors to establish a relationship matrix and construct a direct influence matrix (DIM).

[0141] The formula is:

[0142] Input data: Boolean matrix (0 or 1) indicating the occurrence of each factor in the accident.

[0143] Matrix definition: Assume that there are n factors in the system that directly affect the matrix A = [a ij ] n×n”, where: the number of times factors i and j are both 1 in row k.

[0144] The frequency table of first-level risk factors was obtained through statistical analysis of the bridge-erecting machine accident case database.

[0145] Table 2 Frequency table of first-level risk factors

[0146]

[0147] The direct impact matrix is ​​constructed from the frequency table of first-level risk factors.

[0148] result:

[0149] Table 3 Relationship Matrix

[0150]

[0151] 2. Normalization calculations are performed to obtain the "standardized direct influence matrix". This matrix is ​​the normalized version of the "relationship matrix" (i.e., the original data). Normalization is usually performed using the "maximization" method, which means all numbers are divided by the maximum value in the "relationship matrix":

[0152] Normalized direct impact matrix (Normalized direct impact matrix),

[0153] formula:

[0154]

[0155] Purpose: Normalize the direct impact matrix to the [0,1] interval to avoid numerical overflow.

[0156] DEMATEL requires defining the direction of influence. This can be handled in the following ways: (1) Symmetric mapping: If the relationship between variables is symmetrical (e.g., equipment and personnel influence each other), then the same score is assigned in both directions. (2) Asymmetric mapping: If domain knowledge indicates that one variable influences another in a unidirectional manner (e.g., the environment influences technology, but technology does not influence the environment), then a unidirectional value is assigned.

[0157] Through normalized calculation, asymmetric mapping processing is performed on the risk factors considering the directional impact.

[0158] result:

[0159] Table 4 Standard direct impact matrix

[0160]

[0161] 3. Calculate the 'comprehensive impact matrix T', which is calculated as follows: comprehensive impact matrix T = standard direct impact matrix * inverse matrix of (unit matrix - standard direct matrix),

[0162] Formula: T=N·(IN)-1 ;

[0163] result:

[0164] Table 5 Comprehensive impact matrix T

[0165]

[0166] 4. Combined with the 'comprehensive influence matrix T', various index values ​​are calculated, including the influence degree D value, the influence degree C value, the centrality M value, and the cause degree N value.

[0167] Impact D value:

[0168]

[0169] Result: [2.1248 1.2682 1.61 1.6975 1.0977]

[0170] Influence C value:

[0171]

[0172] Result: [2.4993 1.4604 1.432 1.9953 0.0000]

[0173] Centrality M value:

[0174] M i =D i +C i ;

[0175] Result: [4.6241 2.7286 3.4531 3.6927 1.0977]

[0176] Cause degree N value:

[0177] N i =D i -R i ;

[0178] Result: [2.1248.1268 1.6100 1.6975 1.0977]

[0179] 5. Combined with the 'centrality M value', i.e. the importance of the factor, normalize it and finally calculate the weight of each factor. The formula is:

[0180]

[0181] result:

[0182] Table 6 First-level factor weights

[0183]

[0184] In step 4.2, the contribution allocation method with Bayesian correction is used to calculate the weight values ​​of the secondary risk factors.

[0185] The Bayesian correction contribution allocation method is an improved weight calculation method designed to address the limitations of traditional contribution allocation methods in small samples or sparse data. The traditional method counts the frequency of occurrence of each factor in the Boolean matrix (each row is 1 / k i Weights are calculated by assigning contributions and then accumulating them, but this can easily lead to zero weights when insufficient data is available. Bayesian correction introduces a priori parameters (such as pseudo-count α), adding the original contributions to the prior value and then normalizing it. This ensures that non-zero weights are assigned even when a factor is absent. This method combines observed data with prior knowledge (such as the uniformity assumption) to enhance the stability and rationality of the results.

[0186] 1. Obtain the occurrence data of secondary factors including human factors, technical factors, management factors, environmental factors and equipment factors in 39 accident cases, and establish a Boolean matrix, taking human factors as an example.

[0187] Table 7 Boolean matrix of personnel factors

[0188]

[0189] 2. Calculate the number of factors present in each accident:

[0190]

[0191] Where: X ij =1 means factor j occurs in the i-th accident.

[0192] 3. Allocate contribution:

[0193] If factor j appears in the i-th accident (X ij =1), then its contribution is 1 / k i After all accidents are accumulated, the total contribution of factor j is:

[0194] where k i ≠0;

[0195] Table 8 Secondary Factor Contribution Distribution Table (Personnel Factors)

[0196]

[0197] The total contribution of factor A11 is: C1 = 7.4833;

[0198] The total contribution of factor A12 is: C2 = 7.1500;

[0199] The total contribution of factor A13 is: C3 = 6.9000;

[0200] The total contribution of factor A14 is: C4 = 2.7333;

[0201] The total contribution of factor A15 is: C5 = 9.7333;

[0202] 4. Add the prior parameter γ:

[0203] Uniform prior is selected as the prior parameter, and γ is taken as 0.5.

[0204] 5. Calculate the posterior parameters of each factor:

[0205] Posterior j =C j +γ;

[0206] The posterior parameters of factor A11 are: C1 = 7.9833;

[0207] The posterior parameters of factor A12 are: C2 = 7.6500;

[0208] The posterior parameters of factor A13 are: C3 = 7.4000;

[0209] The posterior parameters of factor A14 are: C4 = 3.2333;

[0210] Posterior parameter of factor A15: C5 = 10.2333;

[0211] 6. Normalized posterior parameters:

[0212]

[0213] Weight of factor A11

[0214] Weight of factor A12

[0215] Weight of Factor A13

[0216] Weight of Factor A14

[0217] Weight of factor A15

[0218] Repeat the above steps to calculate the secondary factor weights of personnel factors, technical factors, management factors, environmental factors, and equipment factors:

[0219] Table 9 Secondary factor weights

[0220]

[0221]

[0222] Step 5: Use the multi-attribute decision-making combined weighting method to calculate the comprehensive weight value. The weight values ​​obtained from the first-level factors and the second-level factors are combined to obtain the comprehensive weight value.

[0223] formula:

[0224]

[0225] Among them, α and β are the weights obtained by two methods.

[0226] The final weight values ​​of the causes of the bridge erection machine accident are calculated as follows:

[0227] Table 10 Combination weight values

[0228]

[0229]

[0230] Step 6: Obtain the quantitative value of each risk factor indicator.

[0231] According to the relevant information and data collected and prepared in step 1, the quantitative values ​​of each risk factor indicator are obtained.

[0232] Step 7: Calculate the comprehensive rating value of the bridge-building machine. Use the linear weighted comprehensive method: multiply the quantitative value of each indicator by its weight and then add them together to obtain the comprehensive evaluation value of the safety risk of the bridge-building machine.

[0233] formula:

[0234]

[0235] Where G is the comprehensive evaluation value, w i is the weight of the i-th indicator, X i is the quantitative value of the i-th indicator, and i is the number of indicators.

[0236] Table 11 Comprehensive index level of safety risk of bridge erection machine

[0237]

[0238]

[0239] Step 8: Determine whether the bridge-erecting machine can carry out beam erection operations based on the comprehensive safety risk assessment results before construction.

[0240] The above embodiments are merely preferred technical solutions of the present invention and should not be construed as limiting the present invention. The scope of protection of the present invention shall be the technical solutions set forth in the claims, including equivalent alternatives to the technical features of the technical solutions set forth in the claims. In other words, equivalent alternatives and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A comprehensive safety risk rating method for bridge erection machinery before construction based on multi-attribute decision making, characterized by: The method includes: S1. Obtain relevant information data before the construction of the bridge erection machine, wherein the relevant information data at least includes equipment status, operator status and environmental conditions; S2. Build a bridge erection machine accident case database, and extract risk factors affecting safe operation from the accident case database; S3. Establish a comprehensive safety risk rating indicator system based on the risk factors; S4. Performing data mining on the accident case database to determine the weight values ​​of the risk factors; S5. Calculate a comprehensive safety risk evaluation value before the bridge erection machine is constructed based on the relevant information data and the weight value; S6. Determine whether the bridge erection machine is capable of carrying out the beam erection operation based on the comprehensive evaluation value.

2. The method for comprehensive rating of safety risks before construction of a bridge erecting machine based on multi-attribute decision making according to claim 1 is characterized in that: in step S1: Collecting status information of the bridge crane equipment after installation and preparation work is completed, including the performance of the equipment itself and historical usage records; Obtaining data on the qualifications, training, and health status of operating personnel, which is used to assess the impact of human factors on safety; Collecting environmental condition information at the construction site, including meteorological, topographical, and geological characteristics; Organize technical and management related materials, including construction plans and safety management systems; By integrating the above information data, comprehensive basic data for pre-construction safety assessment is formed, which is used for subsequent quantitative analysis of risk factors and comprehensive rating calculation.

3. The method for comprehensive safety risk rating of a bridge erection machine before construction based on multi-attribute decision making according to claim 1 is characterized by: In step S2, a bridge crane accident case library is constructed, including: Collect historical bridge-erecting machine accident cases by querying public information sources, including government department notifications and construction records; Structuring the collected cases to form a database containing various accident causes, wherein the database at least records the time, location, and casualties of the accident; Categorize and organize the cases in the database and extract key information related to pre-construction safety; Based on the classification results, analyze the common characteristics of accidents and provide data support for the subsequent identification of risk factors; By constructing the database, a systematic basis for historical accident analysis is formed.

4. The method for comprehensive safety risk rating of a bridge erection machine before construction based on multi-attribute decision making according to claim 1 is characterized by: In step S3, the risk factors establish a comprehensive safety risk rating indicator system, including: The factors affecting the safety of bridge erection machine construction are divided into multiple first-level risk factors, and the first-level risk factors include at least personnel, management, equipment, technology and environment; Each type of first-level risk factor is subdivided to determine the corresponding second-level risk factor, which covers specific safety impact factors; By organizing the first-level risk factors and the second-level risk factors in a hierarchical manner, a multi-dimensional rating indicator system is formed; Based on the rating indicator system, clarify the scope of each factor in the comprehensive rating; The establishment of the indicator system provides a structured framework for subsequent weight calculation and risk assessment.

5. The method for comprehensive safety risk rating of a bridge erection machine before construction based on multi-attribute decision making according to claim 1 is characterized by: In step S4, the accident case database performs data mining to determine the weight values ​​of the risk factors, including: By analyzing the frequency data in the accident case database, a direct impact matrix is ​​constructed, which reflects the interaction relationship between various risk factors; The direct impact matrix is ​​normalized using the decision laboratory method to obtain a normalized impact matrix; based on the normalized impact matrix, a comprehensive impact matrix is ​​calculated, and the comprehensive impact matrix is ​​used to determine the influence and the degree of influence of each risk factor; Calculate the weight value of the first-level risk factor through analysis of the impact and the impact; The Bayesian modified contribution allocation method is used to calculate the weights of secondary risk factors. The calculation combines historical data and prior parameters to ensure the rationality of the weight values.

6. The method for comprehensive safety risk rating of a bridge erection machine before construction based on multi-attribute decision-making according to claim 5 is characterized by: By analyzing the frequency data in the accident case database, a direct impact matrix A=[a ij ] n×n , the matrix is where a ij represents the number of times factors i and j in the kth row are both 1, and the matrix reflects the interaction between the risk factors; The direct impact matrix is ​​normalized by the decision laboratory method, and the standardized direct impact matrix N is obtained by maximization. The formula is: And the asymmetric mapping processing is performed on the directional impact of risk factors to obtain a normalized impact matrix; According to the normalized influence matrix, the comprehensive influence matrix T is calculated, and the formula is T = N (IN) -1 , where I is the unit matrix, and the comprehensive impact matrix is ​​used to determine the impact of each risk factor and influence According to the influence D i and the degree of influence C i Calculate the centrality M of the first-level risk factor i =D i +C i and causal degree N i =D i -C i , and combined with the centrality M i Normalization is performed to obtain the first-level risk factor weights, and the formula is: The weight value of the first-level risk factor is calculated through analysis of the influence and the influence.

7. The method for comprehensive safety risk rating of a bridge erection machine before construction based on multi-attribute decision making according to claim 5 is characterized by: The Bayesian modified contribution allocation method is used to calculate the weights of the secondary risk factors and the number of factors that appear in each accident. where X ij =1 means factor j occurs in the i-th accident; If factor j appears in the i-th accident, its contribution is After all accidents are accumulated, the total contribution of factor j is where k i ≠0; add the prior parameter γ and calculate the posterior parameter Posterior of each factor j =C j +γ; By normalizing the posterior parameters, the formula is: The calculation combines historical data and prior parameters to ensure the rationality of the weight value; Using the multi-attribute decision-making combined weighting method, the weight values ​​obtained from the first-level factors and the second-level factors are combined. The formula is: The comprehensive weight value is calculated, where α is the weight of the first-level factor and β is the weight of the second-level factor.

8. The method for comprehensive safety risk rating of a bridge erection machine before construction based on multi-attribute decision making according to claim 1 is characterized by: In step S5, the relevant information data and the weight values ​​are used to calculate the comprehensive safety risk evaluation value before the bridge erection machine is constructed, including: Quantitatively process the relevant information data to obtain an index value of each risk factor, wherein the index value reflects a specific safety status; Match the index values ​​with the corresponding weight values ​​and calculate the weighted scores of each factor using a linear weighting method; By accumulating the weighted scores of all factors, a comprehensive evaluation value is obtained, which represents the overall safety risk level of the bridge erection machine before construction; Determine the safety risk level based on the calculated result of the comprehensive evaluation value and the preset level standard; The quantitative analysis of the comprehensive evaluation value provides a data basis for subsequent decision-making.

9. The method for comprehensive safety risk rating of a bridge erection machine before construction based on multi-attribute decision making according to claim 8 is characterized by: The formula of linear weighted comprehensive method is: where w i is the weight of the i-th indicator, x i is the quantitative value of the i-th indicator, and i is the number of indicators.

10. The method for comprehensive safety risk rating of a bridge erection machine before construction based on multi-attribute decision making according to claim 8 is characterized by: Step S6 In the evaluation, the comprehensive evaluation value determines whether the bridge erection machine has the conditions to carry out the bridge erection operation, including: Comparing the comprehensive evaluation value with a preset safety risk level standard, wherein the standard is divided into multiple risk levels; If the comprehensive evaluation value reaches a higher safety level, it is determined that the bridge erection machine is qualified to carry out the beam erection operation; If the comprehensive evaluation value does not meet the safety level requirements, it is determined that corrective measures need to be taken; Generating corresponding construction suggestions based on the determination results, wherein the suggestions are used to guide whether to carry out the operation; Through the above judgment process, a comprehensive assessment conclusion of the safety status before construction is formed.

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