Construction safety risk assessment method and system, electronic equipment and storage medium

Abstract

The invention relates to a fabricated residential building construction safety risk assessment method and system, electronic equipment and a storage medium, and the method comprises the steps: constructing an analytic hierarchy structure of fabricated residential building construction safety risks, and determining the data of a plurality of scheme layers of fabricated residential building construction corresponding to the analytic hierarchy structure; determining the subjective weight of the data of each scheme layer by using a preset subjective weighting method; determining an objective weight of the data of each scheme layer by using a preset objective weighting method; processing the subjective weight and the objective weight based on a preset rule to obtain a comprehensive weight; and determining a construction safety risk assessment result of the fabricated residential building based on the scheme layer data and the comprehensive weight. According to the method, the construction safety risk of the fabricated residential building is comprehensively and effectively evaluated, so that the construction risk is reduced, and the life safety of constructors is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of safety engineering, and particularly to a construction safety risk assessment method, system, electronic device and storage medium. Background Art

[0002] With the improvement of the national industrialization technology level and the development of residential buildings, prefabricated residential buildings cannot be underestimated.

[0003] For the construction safety of traditional construction projects, there are already many relatively comprehensive safety evaluation methods and various specification standards to ensure construction safety. However, for the construction safety of prefabricated residential buildings, although some safety evaluation methods have been proposed, the safety evaluation system still has significant deficiencies. Coupled with the frequent occurrence of many construction accidents, many potential safety hazards cannot be discovered and prevented in time.

[0004] Therefore, how to design an evaluation method for the construction safety risk of prefabricated residential buildings to comprehensively evaluate the construction safety risk is an urgent problem to be solved. Summary of the Invention

[0005] In view of this, it is necessary to provide a construction safety risk assessment method, system, electronic device and medium to comprehensively and effectively evaluate the construction safety risk of prefabricated residential buildings.

[0006] To achieve the above object, in a first aspect, the present invention provides a construction safety risk assessment method, including:

[0007] Constructing an analytic hierarchy structure of the construction safety risk of prefabricated residential buildings and determining a plurality of data of the scheme layers corresponding to the construction of prefabricated residential buildings in the analytic hierarchy structure;

[0008] Using a preset subjective weighting method to determine the subjective weights of each data of the scheme layers;

[0009] Using a preset objective weighting method to determine the objective weights of each data of the scheme layers;

[0010] Processing the subjective weights and the objective weights based on a preset rule to obtain a comprehensive weight;

[0011] Determining the construction safety risk assessment result of prefabricated residential buildings based on the data of the scheme layers and the comprehensive weight.

[0012] Further, the determining a plurality of data of the scheme layers corresponding to the construction of prefabricated residential buildings in the analytic hierarchy structure includes:

[0013] Determining the criterion layer indicators of the analytic hierarchy structure;

[0014] Query the data of each scheme layer of the prefabricated residential building corresponding to the criterion layer indicators.

[0015] Furthermore, the criterion layer indicators include first-order indicators and second-order indicators;

[0016] The first-order indicators of the analytic hierarchy structure include personnel factors, environmental factors, management factors, equipment factors, and technical factors;

[0017] The second-order indicators of the analytic hierarchy structure include the professional skill level of construction workers, the safety awareness of construction workers, and the educational level of construction workers under personnel factors;

[0018] And, the on-site construction climate environment, the transportation environment of components, the safety construction work atmosphere environment, and the safety construction standard policy environment of prefabricated residential buildings under environmental factors;

[0019] And, the safety construction management system, the setting of safety management organizational structure, the education and training of safety management personnel, and the real-time supervision and emergency handling of on-site prefabricated residential building construction safety under management factors;

[0020] And, the quality of prefabricated components and mechanical equipment, the firmness of temporary supports, and the inspection and maintenance of mechanical equipment under equipment factors;

[0021] And, the use technology of machinery and tools, the installation technology of prefabricated component joints, and the safety construction technology under technical factors.

[0022] Furthermore, the subjective weights of the data of each scheme layer are determined by using a preset subjective weighting method; including:

[0023] Construct a comparison judgment matrix of the analytic hierarchy structure;

[0024] Perform a consistency test on the comparison judgment matrix. When the comparison judgment matrix meets the consistency standard, it is judged to be consistent. When the comparison judgment matrix does not meet the consistency standard, the comparison judgment matrix is adjusted to make the comparison judgment matrix meet the consistency standard;

[0025] Perform a hierarchical single sorting process on the comparison judgment matrix that meets the consistency standard;

[0026] Perform a hierarchical total sorting process on the comparison judgment matrix after the hierarchical single sorting process to obtain the importance ranking values of each hierarchical structure of the analytic hierarchy structure;

[0027] Obtain the subjective weights of the data of each scheme layer based on the importance ranking values of each hierarchical structure of the analytic hierarchy structure.

[0028] Furthermore, the objective weights of the data of each scheme layer are determined by using a preset objective weighting method, including:

[0029] Construct the original matrix of the analytic hierarchy structure and perform normalization processing on the original matrix to obtain a normalized matrix;

[0030] Calculate the coefficient of variation and the conflict quantification value of each index based on the normalized matrix;

[0031] Calculate the information amount of each index according to the coefficient of variation and the conflict quantification value;

[0032] Perform normalization processing on the information amount to obtain the objective weight of each data in the scheme layer.

[0033] Further, the processing of the subjective weight and the objective weight based on preset rules includes:

[0034] Process the subjective weight and the objective weight based on the addition integration method.

[0035] Further, the method further includes:

[0036] Obtain the construction safety rectification suggestions for prefabricated residential buildings based on the construction safety risk assessment results of prefabricated residential buildings.

[0037] In a second aspect, the present invention further provides a construction safety risk assessment system for prefabricated residential buildings, including:

[0038] An analytic hierarchy structure construction module, configured to construct an analytic hierarchy structure of the construction safety risk of prefabricated residential buildings and determine multiple data of the construction of prefabricated residential buildings corresponding to the analytic hierarchy structure;

[0039] A subjective weight determination module, configured to determine the subjective weights of each data in the scheme layer by using a preset subjective weighting method;

[0040] An objective weight determination module, configured to determine the objective weights of each data in the scheme layer by using a preset objective weighting method;

[0041] A comprehensive weight determination module, configured to process the subjective weight and the objective weight based on preset rules to obtain a comprehensive weight;

[0042] A safety risk assessment module, configured to determine the construction safety risk assessment result of prefabricated residential buildings based on the data in the scheme layer and the comprehensive weight.

[0043] In a third aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above construction safety risk assessment method are implemented.

[0044] Fourthly, the present invention also provides a computer storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above construction safety risk assessment method are implemented.

[0045] The beneficial effects of adopting the above embodiments are as follows:

[0046] By constructing an analytic hierarchy structure of the construction safety risks of prefabricated residential buildings, the present invention determines multiple sets of data at the scheme layer for the construction of prefabricated residential buildings. Then, it uses a preset subjective weighting method to determine the subjective weights of each set of data at the scheme layer, uses a preset objective weighting method to determine the objective weights of each set of data at the scheme layer, and processes the subjective weights and objective weights based on a preset rule to obtain a comprehensive weight. Finally, based on the data at the scheme layer and the comprehensive weight, the assessment result of the construction safety risks of prefabricated residential buildings is determined. Through the input and processing of data and the determination of weight indicators, a specific assessment result of the early warning assessment of the construction safety risks of prefabricated residential buildings can be obtained. This assessment result is obtained based on the actual situation of the enterprise, is true and reliable, and can also be used to improve the construction through this assessment result, reducing construction risks and ensuring the safety of construction personnel. Description of the Drawings

[0047] Figure 1 It is a schematic flowchart of an embodiment of the construction safety risk assessment method provided by the present invention;

[0048] Figure 2 It is a schematic diagram of the personnel factor interface of a construction safety risk assessment system for prefabricated residential buildings provided by an embodiment of the present invention;

[0049] Figure 3 It is a schematic structural diagram of an embodiment of the construction safety risk assessment system provided by the present invention;

[0050] Figure 4 It is a schematic flowchart of an embodiment of the electronic device provided by the present invention. Detailed Embodiments

[0051] The preferred embodiments of the present invention will be specifically described below with reference to the drawings. The drawings form a part of this application and are used together with the embodiments of the present invention to explain the principles of the present invention, rather than to limit the scope of the present invention.

[0052] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the meaning of "a plurality" is two or more unless otherwise specifically defined. The mention of "embodiment" herein means that a specific feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. The appearance of this phrase at various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0053] The following will separately elaborate on specific embodiments in detail:

[0054] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of an embodiment of the construction safety risk assessment method provided by the present invention. A specific embodiment of the present invention discloses a construction safety risk assessment method, including:

[0055] Step S101: Construct an analytic hierarchy structure for the construction safety risks of prefabricated residential buildings and determine multiple sets of data for the construction of prefabricated residential buildings corresponding to the analytic hierarchy structure;

[0056] Step S102: Use a preset subjective weighting method to determine the subjective weights of each set of data for the solution layer;

[0057] Step S103: Use a preset objective weighting method to determine the objective weights of each set of data for the solution layer;

[0058] Step S104: Process the subjective weights and objective weights based on a preset rule to obtain a comprehensive weight;

[0059] Step S105: Determine the construction safety risk assessment result of prefabricated residential buildings based on the data of the solution layer and the comprehensive weight.

[0060] The present invention determines multiple data of the scheme layer for the construction of prefabricated residential buildings by constructing an analytic hierarchy structure of the construction safety risks of prefabricated residential buildings. Then, the subjective weights of the data of each scheme layer are determined by using a preset subjective weighting method, the objective weights of the data of each scheme layer are determined by using a preset objective weighting method, and the subjective weights and objective weights are processed based on a preset rule to obtain a comprehensive weight. Finally, the construction safety risk assessment result of the prefabricated residential building is determined based on the data of the scheme layer and the comprehensive weight. Through the input and processing of data and the determination of weight indicators, the specific assessment result of the early warning assessment of the construction safety risk of the prefabricated residential building can be obtained. This assessment result is obtained according to the actual situation of the enterprise, is true and reliable, and can also be used to improve the construction through this assessment result, reduce the construction risk, and ensure the life safety of the construction personnel.

[0061] In an embodiment of the present invention, determining multiple data of the scheme layer for the construction of prefabricated residential buildings corresponding to the analytic hierarchy structure includes:

[0062] Determining the criterion layer indicators of the analytic hierarchy structure;

[0063] Querying the data of each scheme layer of the corresponding prefabricated residential building based on the criterion layer indicators.

[0064] It can be understood that the analytic hierarchy structure first rationalizes and hierarchizes the problem, constructs a model of the analytic hierarchy structure, and generally divides the model into three main layers: the target layer, the criterion layer, and the scheme layer. In this index system, the target layer is the construction index system of prefabricated residential buildings, the criterion layer is each first-order and second-order index, and the scheme layer is the data of each bottom-layer scheme without subordinate indicators. After determining the criterion layer indicators of the analytic hierarchy structure, the data of each scheme layer of the corresponding prefabricated residential building can be queried according to the criterion layer indicators.

[0065] The criterion layer indicators include first-order indicators and second-order indicators;

[0066] The first-order indicators of the analytic hierarchy structure include personnel factors, environmental factors, management factors, equipment factors, and technical factors;

[0067] The second-order indicators of the analytic hierarchy structure include the professional skill level of construction personnel, the safety awareness of construction personnel, and the educational level of construction personnel under personnel factors;

[0068] And, the on-site construction climate environment, the transportation environment of components, the safety construction work atmosphere environment, and the construction safety standard policy environment of prefabricated residential buildings under environmental factors;

[0069] And, the safety construction management system, the setting of the safety management organizational structure, the education and training of safety management personnel, and the real-time supervision and emergency handling of the on-site construction safety of prefabricated residential buildings under management factors;

[0070] and, the quality of precast components and mechanical equipment under equipment factors, the firmness of temporary supports, and the inspection and maintenance of mechanical equipment;

[0071] and, the operation techniques of machinery and tools, the installation techniques of precast component joints, and the safety construction techniques under technical factors.

[0072] In an embodiment of the present invention, a preset subjective weighting method is used to determine the subjective weights of each data at the scheme layer; including:

[0073] Construct a comparison and judgment matrix for the hierarchical analysis structure;

[0074] Perform a consistency test on the comparison and judgment matrix. When the comparison and judgment matrix meets the consistency standard, it is judged to be consistent. When the comparison and judgment matrix does not meet the consistency standard, the comparison and judgment matrix is adjusted to make it meet the consistency standard;

[0075] Perform a hierarchical single sorting process on the comparison and judgment matrix that meets the consistency standard;

[0076] Perform a hierarchical total sorting process on the comparison and judgment matrix that has undergone the hierarchical single sorting process to obtain the importance ranking values of each hierarchical structure in the hierarchical analysis structure;

[0077] Based on the importance ranking values of each hierarchical structure in the hierarchical analysis structure, obtain the subjective weights of each data at the scheme layer.

[0078] First of all, it should be noted that the AHP (Analytic Hierarchy Process) method is a hierarchical analysis method combining qualitative and quantitative methods, which belongs to a kind of subjective weighting method and is a method for solving practical problems based on systematic theory. This method hierarchizes practical problems. According to the characteristics and objectives of specific problems, the problems are analyzed into different constituent factors, and a multi-level structural analysis model is constructed based on the relationships between the factors. And based on the comparison and judgment between the factors, their ratios are quantified to form a comparison matrix, and finally the weights of each factor in each level are obtained. In order to determine the index weights, it first determines the influence degree of the indexes at the same level on the upper-level indexes, then makes pairwise comparisons of the indexes at the same level according to the influence degree on the upper-level indexes, establishes a judgment matrix according to the 1-9 scale method, solves the judgment matrix, and obtains the subjective weight of each index.

[0079] Specifically, after establishing the hierarchical analysis, pairwise comparisons need to be carried out among the elements of each layer to construct a comparison judgment matrix. The analytic hierarchy process writes the judgment matrix by introducing appropriate scale values. The judgment matrix represents the comparison of the relative importance between the factors of this layer and the relevant factors of the previous layer. The judgment matrix is the basic information of the analytic hierarchy process and also an important basis for calculating the relative importance. The basic method for constructing the comparison judgment matrix of the hierarchical analysis structure is as follows:

[0080] Assume that the element B in the previous layer k is used as the criterion, and has a dominant relationship with the lower-layer elements C1, C2,..., C n . Our goal is to assign corresponding weights to C1, C2,..., C k according to their relative importance under the criterion B n . In this step, the following questions need to be answered: For the criterion B k , which of the two elements C i , C j is more important and what is the magnitude of the importance. Assign a certain value to the importance. The value source is determined by experts in this field. After being determined by multiple experts, the importance value is weighted and averaged according to conditions such as the age, professional title, working years, and length of service in the relevant industry of the experts.

[0081] For n elements, the pairwise comparison judgment matrix C = (C ij )n×n is obtained. Where C ij represents the importance value of factor i and factor j relative to the goal.

[0082] Generally speaking, the constructed judgment matrix takes the following form:

[0083]

[0084] The matrix C has the following properties:

[0085] (1) C ij > 0

[0086] (2) C ij = 1 / Cji (i ≠ j)

[0087] (3) C ii = 1

[0088] In the analytic hierarchy process, the 1-9 scale method is adopted to quantify the above decision-making judgment to form a numerical judgment matrix.

[0089]

[0090] And for the problem that it is impossible to determine which of the two importance levels it belongs to, an even value between the two scales can be taken. After constructing the above comparison judgment matrix, the single sorting calculation of the judgment matrix can be carried out. On the basis of the single sorting calculation of each level, the total sorting calculation of each level is also required. Before performing this type of calculation, a consistency test needs to be carried out.

[0091] To ensure that the conclusions obtained by applying the analytic hierarchy process are reasonable, a consistency test needs to be carried out on the constructed judgment matrix. This type of test is usually carried out in combination with the sorting steps. According to matrix theory, the following conclusion can be obtained, that is, if λ1, λ2,..., λ n are numbers that satisfy the equation: Ax = λ x and are the eigenvalues of matrix A, and for all a ii = 1, there is

[0092] When the matrix has perfect consistency, λ1 = λ max = n, and the remaining eigenvalues are all zero; while when matrix A does not have perfect consistency, then λ1 = λ max > n, and the remaining eigenvalues λ2, λ3,..., λ n have the following relationship

[0093] And when the judgment matrix cannot guarantee perfect consistency, the eigenvalues of the corresponding judgment matrix will also change, and the change of the eigenvalues of the judgment matrix can be used to test the consistency degree of the judgment. Therefore, in the analytic hierarchy process, the negative average value of the remaining eigenvalues other than the largest eigenvalue of the judgment matrix is introduced as an index to measure the deviation of the judgment matrix from consistency, that is: Among them, the larger the CI value, the greater the degree of deviation of the judgment matrix from perfect consistency; the smaller the CI value (close to 0), the better the consistency of the judgment matrix. It is also necessary to introduce the average random consistency index RI value of the judgment matrix. For judgment matrices of order 1-9, the RI values are as follows in the table:

[0094]

[0095] When the order of the judgment matrix is 2, it has perfect consistency. When the order is greater than 2, the ratio of the consistency index CI of the judgment matrix to the average random consistency index RI of the same order is called the random consistency ratio, denoted as CR. When that is, it is considered that the judgment matrix has satisfactory consistency, otherwise the judgment matrix needs to be adjusted to make it have satisfactory consistency.

[0096] The hierarchical single sorting refers to calculating the weights of the importance order of the elements related to a certain element in the upper layer in this layer according to the judgment matrix. The weights of the priority sorting of various factors in the hierarchy given by applying the analytic hierarchy process essentially express a certain qualitative concept. Therefore, the present invention uses the iterative method to obtain the approximate maximum eigenvalue and its corresponding eigenvector on a computer, and the specific steps are as follows:

[0097] Calculate the product M of each row element of the judgment matrix i :

[0098] Calculate M i The nth root of

[0099] Normalize the vector (Normalization processing): Then W = [W1, W2,..., W n T That is the required eigenvector;

[0100] Calculate the maximum eigenvalue of the judgment matrix Among them, (AW) i Represents the i-th element of the vector AW.

[0101] Calculate layer by layer from top to bottom along the hierarchical structure in turn, and the relative importance or relative superiority ranking value of the lowest layer factors relative to the overall goal can be calculated, that is, the hierarchical total sorting. The hierarchical total sorting is for the highest layer goal, and the total sorting of the highest layer is its hierarchical total sorting.

[0102] Furthermore, the present invention comprehensively scores the importance of the indicators by 10 experts in related fields such as construction, and then evaluates each level of indicators through the analytic hierarchy process, and finally obtains the result. The results of the subjective weights calculated by using the AHP analytic hierarchy process are as follows:

[0103]

[0104] In an embodiment of the present invention, the objective weights of each data in the scheme layer are determined by using a preset objective weighting method, including:

[0105] Construct the original matrix of the hierarchical analysis structure and perform standardization processing on the original matrix to obtain the standardized matrix;

[0106] Calculate the coefficient of variation and conflict quantification value of each indicator based on the standardized matrix;

[0107] Calculate the information amount of each indicator according to the coefficient of variation and conflict quantification value;

[0108] ​Normalize the amount of information to obtain the objective weights of the data at each solution layer.

[0109] First of all, it should be noted that the CRITIC (Criteria Importance Through Intercriteria Correlation) method is a method applicable to determining the objective weights of indicators. This method comprehensively determines the objective weights of indicators based on the magnitude of variation within the indicators and the conflict between indicators. The magnitude of variation represents the size of the gap in the values of the same indicator, which is represented by the coefficient of variation. The larger the coefficient of variation, the greater the amount of information reflected and the greater the weight. Conflict refers to the correlation coefficient between two indicators. The larger the correlation coefficient, the more similar the amount of information reflected and the smaller the weight. The entropy weight method only considers the degree of variation of the indicator values, while in fact there is a certain correlation between the indicators. Therefore, it is more scientific to use the CRITIC method to determine the objective weights. The specific steps are as follows:

[0110] First, denote each indicator as i, and the evaluation sample data regarding this indicator as j, and construct an elementary matrix with m rows and n columns with x ij as elements. That is, there are m evaluation indicators, and each evaluation indicator has n data samples.

[0111] Then, since the bases for the scoring of each indicator are different, the different units between the indicators will affect the indicators. Usually, normalization processing is required. In this study, the positive extreme value normalization method is adopted: where s ij is the normalized value, x ij is the original value, x max is the maximum value of the j data of indicator i, and x min is the minimum value.

[0112] Next, calculate the coefficient of variation. The magnitude of variation within the indicator is measured by the coefficient of variation of each indicator: where σ i is the standard deviation of indicator i, is the average value of the j data of indicator i, and V i is the coefficient of variation of indicator i.

[0113] Next, calculate the conflict between indicators. The conflict between indicators can be indicated by the correlation coefficient. In the present invention, the Pearson correlation coefficient is used to calculate the conflict of each indicator: where T i is the quantitative value of the conflict of the indicator, and r ij is the Pearson correlation coefficient.

[0114] Next, calculate the amount of information: C i =V i ×T i。

[0115] Finally, calculate the objective weight ω i , normalize the information amount of index i to obtain where is the objective weight of index i, and C j is the information amount of each index.

[0116] The results of the objective weight calculated by the CRITIC method are as follows:

[0117]

[0118] In an embodiment of the present invention, processing the subjective weight and the objective weight based on a preset rule includes:

[0119] Processing the subjective weight and the objective weight based on the addition integration method.

[0120] It can be understood that the AHP method is suitable for processing the subjective information of decision-makers, and the CRITIC method is suitable for mining the objective information in sample data. Combining the two takes into account both subjectivity and objectivity. Using the AHP-CRITIC method to determine the comprehensive weight of the index is: where μ1 and μ2 are the importance coefficients of the subjective weight and the objective weight respectively, and are set to 0.5 in the present invention according to the game theory algorithm, and τ i is the comprehensive weight of the index. The specific weight values of each index are shown in the following table, and this conclusion can be applied to system development.

[0121] Combined weights of the prefabricated residential building construction safety risk warning index system

[0122]

[0123]

[0124] In an embodiment of the present invention, the above method further includes:

[0125] Obtain the prefabricated residential building construction safety rectification suggestions based on the prefabricated residential building construction safety risk assessment results.

[0126] It can be understood that, for the specific situation of the relevant enterprise input by the user, the dynamic risk value of the prefabricated residential building construction safety can be calculated by combining the corresponding weight values, and a comprehensive evaluation can be carried out according to the risk value, and rectification suggestions can be given. For example, as Figure 2 shown, Figure 2A schematic diagram of the human factor interface of a prefabricated residential construction safety risk assessment system provided by one embodiment of the present invention. The user can click on: 1. Construction workers' professional skill level, 2. Construction workers' safety awareness, 3. Construction workers' average educational level in the program layer data, and enter the calculated comprehensive weight. The calculation result is mainly determined by multiplying and adding the weights assigned to each indicator and the four pre-set assigned scores. The specific situation of each indicator is divided into four comments, namely good, general, poor and dangerous, and assigned a score of {1, 2, 3, 4} respectively, where 1 is very safe and 4 is very dangerous. The higher the score, the more necessary it is for the indicator to be rectified.

[0127] For the overall assessment indicators, the sum of the product of each indicator's score and its weight is the final assessment value. Similarly, higher scores indicate greater risk potential. The relevant assessment statements are as follows: When the score is between 3 and 4 (including 4), it reads: "This system is highly dangerous and requires immediate rectification based on the following circumstances." When the score is between 2 and 3 (including 3), it reads: "This system is relatively dangerous and has numerous hidden dangers. Rectification is required within a specified timeframe based on the following circumstances." When the score is between 1 and 2 (including 2), it reads: "This system is relatively safe, but some hidden dangers remain. Improvement is required based on the following circumstances." When the score is between 0 and 1 (including 1), it reads: "This system is safe, but some hidden dangers remain. Improvement is required based on the following circumstances." The system's calculation results also list the specific assessment results for each indicator, with a color scheme of "Dangerous," "Relatively Dangerous," "Fair," and "Safe." Furthermore, the output interface colors for the assessment results and corrective suggestions can be set to red, orange, yellow, and blue, respectively, to facilitate corrective actions.

[0128] In order to better implement the prefabricated residential building construction safety risk assessment method in the embodiment of the present invention, based on the prefabricated residential building construction safety risk assessment method, please refer to Figure 3 , Figure 3 This is a schematic diagram of an embodiment of a prefabricated residential building construction safety risk assessment system provided by the present invention. The embodiment of the present invention provides a prefabricated residential building construction safety risk assessment system 300, comprising:

[0129] A hierarchical analysis structure construction module 301 is used to construct a hierarchical analysis structure of safety risks of prefabricated residential building construction, and determine multiple scheme layer data of prefabricated residential building construction corresponding to the hierarchical analysis structure;

[0130] The subjective weight determination module 302 is used to determine the subjective weight of each solution layer data using a preset subjective weighting method;

[0131] An objective weight determination module 303 is configured to determine the objective weights of the data at each solution layer by using a preset objective weighting method;

[0132] A comprehensive weight determination module 304 is configured to process the subjective weight and the objective weight based on a preset rule to obtain a comprehensive weight;

[0133] A safety risk assessment module 305 is configured to determine the assessment result of the construction safety risk of the prefabricated residential building based on the data at the solution layer and the comprehensive weight.

[0134] It should be noted here that: the system 300 provided in the above embodiment can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be referred to the corresponding content in the above method embodiments, and will not be elaborated here.

[0135] Based on the above construction safety risk assessment method for prefabricated residential buildings, an embodiment of the present invention further provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the steps in the construction safety risk assessment method for prefabricated residential buildings in the above embodiments are implemented.

[0136] Figure 4 FIG. shows a schematic structural diagram of an electronic device 400 suitable for implementing an embodiment of the present invention. The electronic device in the embodiment of the present invention may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The electronic device shown is only an example and should not bring any limitation to the functions and usage scope of the embodiments of the present invention.

[0137] The electronic device includes: a memory and a processor. Here, the processor may be referred to as a processing device 401 below, and the memory may include at least one of a read-only memory (ROM) 402, a random access memory (RAM) 403, and a storage device 408 below, as specifically shown below:

[0138] As Figure 4As shown, the electronic device 400 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 401, which may perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0139] Generally, the following devices may be connected to the I / O interface 405: an input device 406 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 408 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 may allow the electronic device 400 to communicate with other devices wirelessly or wiredly to exchange data. Although Figure 4 the electronic device 400 with various devices is shown, it should be understood that it is not required to implement or include all the shown devices. More or fewer devices may be alternatively implemented or included.

[0140] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart may be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes program codes for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication device 409, or installed from the storage device 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the method of the embodiment of the present invention are executed.

[0141] Based on the above-mentioned prefabricated residential building construction safety risk assessment method, an embodiment of the present invention also correspondingly provides a computer-readable storage medium, which stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the prefabricated residential building construction safety risk assessment method as described in the above embodiments.

[0142] Those skilled in the art can understand that all or part of the processes for implementing the above embodiment methods can be completed by instructing relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. Among them, the computer-readable storage medium is a magnetic disk, an optical disc, a read-only memory, or a random access memory, etc.

[0143] As described above, it is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. An assessment method for the construction safety risks of prefabricated residential buildings, characterized in that, Including: Constructing an analytic hierarchy structure for the construction safety risks of prefabricated residential buildings, and determining multiple sets of program layer data for the construction of prefabricated residential buildings corresponding to the analytic hierarchy structure; Determining the subjective weights of each set of program layer data using a preset subjective weighting method; Determining the objective weights of each set of program layer data using a preset objective weighting method; Processing the subjective weights and the objective weights based on preset rules to obtain a comprehensive weight; Determining the evaluation result of the construction safety risks of prefabricated residential buildings based on the program layer data and the comprehensive weight.

2. The safety risk assessment method for the construction of prefabricated residential buildings according to claim 1, characterized in that The determining of multiple sets of program layer data for the construction of prefabricated residential buildings corresponding to the analytic hierarchy structure includes: Determining the criterion layer indicators of the analytic hierarchy structure; Querying each set of program layer data of the corresponding prefabricated residential building based on the criterion layer indicators.

3. The safety risk assessment method for prefabricated residential building construction according to claim 2, characterized in that The criterion layer indicators include first-order indicators and second-order indicators; The first-order indicators of the analytic hierarchy structure include personnel factors, environmental factors, management factors, equipment factors, and technical factors; The second-order indicators of the analytic hierarchy structure include the professional skills level of construction workers, the safety awareness of construction workers, and the educational level of construction workers under personnel factors; And, the on-site construction climate environment, the transportation environment of components, the safety construction work atmosphere environment, and the safety standard policy environment for the construction of prefabricated residential buildings under environmental factors; And, the safety construction management system, the setting of the safety management organizational structure, the education and training of safety management personnel, and the real-time supervision and emergency handling of the on-site construction safety of prefabricated residential buildings under management factors; And, the quality of prefabricated components and mechanical equipment, the firmness of temporary supports, and the inspection and maintenance of mechanical equipment under equipment factors; And, the use technology of machinery and tools, the installation technology of prefabricated component joints, and the safety construction technology under technical factors.

4. The safety risk assessment method for the construction of prefabricated residential buildings according to claim 1, characterized in that, The determining the subjective weights of each set of program layer data using a preset subjective weighting method includes: Constructing a comparison judgment matrix of the analytic hierarchy structure; Conducting a consistency test on the comparison judgment matrix. When the comparison judgment matrix meets the consistency standard, it is judged to be consistent. When the comparison judgment matrix does not meet the consistency standard, the comparison judgment matrix is adjusted to make the comparison judgment matrix meet the consistency standard; Conducting a hierarchical single sorting process on the comparison judgment matrix that meets the consistency standard; Conducting a hierarchical total sorting process on the comparison judgment matrix after the hierarchical single sorting process to obtain the importance ranking values of each hierarchical structure of the analytic hierarchy structure; Obtaining the subjective weights of each set of program layer data based on the importance ranking values of each hierarchical structure of the analytic hierarchy structure.

5. The safety risk assessment method for the construction of prefabricated residential buildings according to claim 1, wherein The determining the objective weights of each set of program layer data using a preset objective weighting method includes: Constructing an original matrix of the analytic hierarchy structure and performing a normalization process on the original matrix to obtain a normalized matrix; Calculating the coefficient of variation and the conflict quantification value of each indicator based on the normalized matrix; Calculating the information amount of each indicator according to the coefficient of variation and the conflict quantification value; Performing a normalization process on the information amount to obtain the objective weights of each set of program layer data.

6. The safety risk assessment method for the construction of prefabricated residential buildings according to claim 1, characterized in that, Processing the subjective weight and the objective weight based on a preset rule includes: Processing the subjective weight and the objective weight based on the addition integration method.

7. The safety risk assessment method for the construction of prefabricated residential buildings according to claim 1, wherein The method further includes: Obtaining construction safety rectification suggestions for prefabricated residential buildings based on the evaluation results of the construction safety risks of prefabricated residential buildings.

8. An assembly-type residential building construction safety risk assessment system, characterized in that, Including: A hierarchical analysis structure construction module, configured to construct a hierarchical analysis structure of the construction safety risks of prefabricated residential buildings and determine a plurality of scheme layer data of the construction of prefabricated residential buildings corresponding to the hierarchical analysis structure; A subjective weight determination module, configured to determine the subjective weights of the respective scheme layer data by using a preset subjective weighting method; An objective weight determination module, configured to determine the objective weights of the respective scheme layer data by using a preset objective weighting method; A comprehensive weight determination module, configured to process the subjective weight and the objective weight based on a preset rule to obtain a comprehensive weight; A safety risk evaluation module, configured to determine the evaluation results of the construction safety risks of prefabricated residential buildings based on the scheme layer data and the comprehensive weight.

9. An electronic device, characterized in that, Including a memory and a processor, wherein the memory is configured to store a program; the processor is coupled to the memory and is configured to execute the program stored in the memory to implement the steps in the construction safety risk evaluation method for prefabricated residential buildings according to any one of claims 1 to 7 above.

10. A computer-readable storage medium, characterized in that For storing computer-readable programs or instructions, when the programs or instructions are executed by a processor, the steps in the construction safety risk evaluation method for prefabricated residential buildings according to any one of claims 1 to 7 above can be implemented.

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