Construction engineering leakage risk grade analysis method and system and medium

Abstract

The embodiment of the invention provides a building engineering leakage risk grade analysis method and system and a medium. The method comprises the steps that a building construction distribution information portrait is generated according to building detail feature information, leakage-proof node distribution information is extracted, classification summarization is performed according to an information queue list to obtain category attribute data of each category of leakage-proof nodes, and the category attribute data is processed to obtain a leakage-proof implementation effect index; leakage risk assessment correction data and leakage risk grades are obtained by combining leakage degree visual evaluation data and historical real inspection average coefficient processing, and a building area leakage risk grade aggregation value is obtained by combining category node leakage weight index aggregation processing; therefore, according to the information data of the category leakage-proof nodes of the building area, processing is carried out to obtain the assessment result of the node leakage risk and the corresponding leakage risk grade, and the leakage risk grade values of all the building leakage-proof nodes are obtained through aggregation, so that the identification of the building leakage risk nodes and the assessment analysis of the risk condition are realized.

Description

Technical Field

[0001] The present application relates to the technical field of construction engineering, and in particular to a method, system and medium for analyzing the leakage risk level of a construction engineering. Background Art

[0002] Due to the hidden nature of quality risks in construction projects, it is difficult to assess the leakage risks of buildings. The effective identification and assessment of quality risks in construction projects, especially leakage risks, is of great significance to the insurance of construction projects. However, at present, the leakage risks of construction projects mostly rely on the experience and judgment of engineering or supervision personnel, without digitizing and accurately identifying and evaluating the leakage risks based on the quality information of the construction projects. As a result, there is a lack of technology for accurate leakage identification and risk status assessment of construction project leakage risks.

[0003] In view of the above problems, effective technical solutions are urgently needed. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a method, system and medium for analyzing the leakage risk level of a construction project, which can process the information data of the category leakage prevention nodes of the building area to obtain the assessment results of the node leakage risk and the corresponding leakage risk level, and aggregate the leakage risk level values ​​of all the building leakage prevention nodes to achieve the identification of the building leakage risk nodes and the assessment and analysis of the risk status.

[0005] The present application also provides a method for analyzing the leakage risk level of a construction project, comprising the following steps: Obtain detailed building feature information of a preset construction project area, including building material feature information, construction process feature information, and building function distribution information; Input the building detailed feature information into a preset building information layout description model for processing to generate a building construction distribution information portrait, and extract the anti-leakage node distribution information, classify and summarize the anti-leakage node distribution information through a preset construction point information queue table, and obtain the anti-leakage node category attribute information of each category of anti-leakage node; Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, and processing to obtain anti-leakage construction evaluation index and anti-leakage implementation effectiveness index of each category of anti-leakage node; Visual identification of node leakage degree of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage degree, and combined with the extracted historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes and the leakage prevention implementation effectiveness index, processing is performed to obtain category node leakage risk assessment correction data; Processing the category node leakage risk assessment correction data of each category leakage prevention node and the category node leakage risk assessment correction data of all category leakage prevention nodes to obtain the category node leakage weight index of each category leakage prevention node; According to the correction data of the leakage risk assessment of the category nodes, a threshold comparison is performed with the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of each category of leakage prevention node, and aggregation processing is performed according to the leakage risk level of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index to obtain the aggregated value of the building area leakage risk level of the preset construction project area.

[0006] Optionally, in the construction engineering leakage risk level analysis method described in the embodiment of the present application, the obtaining of building detailed feature information of a preset construction engineering area, including building material feature information, construction process feature information, and building function distribution information, comprises: Obtain detailed building feature information of the preset construction project area, including building material feature information, construction process feature information and building function distribution information, The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information; The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof caulking overlap information, pipeline hanging hole layout information and door and window sealing information; The building function distribution information includes regional function distribution information, water infiltration distribution information, leakage and moisture prevention point layout information, drainage routing information and water supply and drainage pipeline layout information.

[0007] Optionally, in the method for analyzing the leakage risk level of a construction project described in an embodiment of the present application, the building detailed feature information is input into a preset building information layout description model for processing to generate a building construction distribution information portrait, and leakage prevention node distribution information is extracted, and the leakage prevention node distribution information is classified and summarized through a preset construction point information queue table according to the leakage prevention node distribution information to obtain leakage prevention node category attribute information of each category of leakage prevention nodes, including: Inputting the building material characteristic information, construction process characteristic information and building function distribution information into a preset building information layout depiction model for processing, and generating a building construction distribution information portrait of the preset building project area; Extracting the anti-leakage node distribution information of the preset construction project area according to the construction distribution information portrait, including the node position distribution information of each anti-leakage node, the waterproof plugging process information, the sealing and filling material information, the water immersion frequency information and the anti-leakage demand information; According to the node location distribution information, waterproof plugging process information, sealing and filling material information and leakage prevention demand information of each leakage prevention node, the leakage prevention node category attribute information corresponding to each category of leakage prevention node is obtained by classifying and summarizing them through a preset construction point information queue table.

[0008] Optionally, in the construction engineering leakage risk level analysis method described in the embodiment of the present application, extracting corresponding leakage prevention node category attribute data according to the leakage prevention node category attribute information, and processing to obtain the leakage prevention construction evaluation index and leakage prevention implementation effectiveness index of each category of leakage prevention nodes, including: Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, including the node position anti-leakage level, water immersion frequency level, waterproof plugging construction standard data and sealing filling material standard data; The standard data for waterproof and leak-proof construction include grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data; According to the injection density data, injection viscosity data, filling fullness data and coating thickness data of each type of leakproof node, a leakproof construction evaluation index is obtained; The leakage prevention construction evaluation index is combined with the standard data of sealing and filling materials as well as the leakage prevention level of the node position and the water immersion frequency level through a preset leakage prevention effect verification model to obtain the leakage prevention implementation effectiveness index of each category of leakage prevention node.

[0009] Optionally, in the construction engineering leakage risk level analysis method described in the embodiment of the present application, the node leakage degree of each category of leakage prevention nodes is visually identified to obtain category node leakage degree visual evaluation data, and the category node historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes extracted and the leakage prevention implementation effectiveness index are processed to obtain category node leakage risk assessment correction data, including: According to the preset building node leakage visual recognition model, the node leakage degree of each category of anti-leakage node is visually identified, and the visual evaluation data of the node leakage degree of each category is obtained; According to the preset building leakage information monitoring database, the historical leakage risk inspection average coefficient of each category of leakage prevention nodes is extracted; According to the leakage prevention implementation effectiveness index of each category of leakage prevention node, combined with the visual evaluation data of the leakage degree of the corresponding category node and the average coefficient of the historical leakage risk of the category node, the leakage risk assessment correction data of the category node is obtained; The calculation formula for the correction data of the leakage risk assessment of the category node is: ; in, Correct data for category node leakage risk assessment, To prevent leakage, we implemented the effectiveness index. is the visual evaluation data of the leakage degree of the category node, is the average coefficient of historical leakage risk of category nodes, , , , is the preset characteristic coefficient.

[0010] Optionally, in the construction engineering leakage risk level analysis method described in the embodiment of the present application, the category node leakage risk assessment correction data of each category of leakage prevention nodes and the category node leakage risk assessment correction data of all category leakage prevention nodes are processed to obtain the category node leakage weight index of each category of leakage prevention nodes, including: Processing the leakage risk assessment correction data of the category nodes of each category of leakage prevention nodes and the leakage risk assessment correction data of the category nodes corresponding to all category leakage prevention nodes of the preset construction project area to obtain the category node leakage weight index corresponding to each category of leakage prevention nodes; The calculation formula of the category node leakage weight index is: ; in, is the category node leakage weight index of the i-th category anti-leakage node, is the correction data of the leakage risk assessment of the i-th category leakage prevention node, n is the number of categories of all category leakage prevention nodes, , is the preset characteristic coefficient of the anti-leakage node of the i-th category.

[0011] Optionally, in the construction engineering leakage risk level analysis method described in the embodiment of the present application, the threshold comparison is performed according to the leakage risk assessment correction data of the category node and the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of each category of leakage prevention node, and the aggregation processing is performed according to the leakage risk level of all category leakage prevention nodes combined with the corresponding category node leakage weight index to obtain the building area leakage risk level aggregation value of the preset construction engineering area, including: Perform threshold comparison based on the category node leakage risk assessment correction data of each category leakage prevention node and the preset category node leakage risk level threshold corresponding to the category leakage prevention node; According to the threshold comparison results, the leakage risk level of each type of leakage prevention node is obtained; Aggregation processing is performed according to the corresponding leakage risk levels of all categories of leakage prevention nodes in the preset construction project area, combined with the corresponding category node leakage weight index and the node position leakage prevention level, to obtain the building area leakage risk level aggregation value of the preset construction project area; The aggregate calculation formula for the aggregate value of the leakage risk level of the building area is: ; in, is the aggregate value of the leakage risk level of the building area, is the category node leakage weight index of the i-th category anti-leakage node, is the node position leakage-proof level of the i-th category leakage-proof node, is the leakage risk level of the i-th type of leakage prevention node, , is the preset characteristic coefficient of the anti-leakage node of the i-th category.

[0012] In a second aspect, an embodiment of the present application provides a system for analyzing the leakage risk level of a construction project, the system comprising: a memory and a processor, the memory comprising a program of a method for analyzing the leakage risk level of a construction project, and the program of the method for analyzing the leakage risk level of a construction project when executed by the processor implements the following steps: Obtain detailed building feature information of a preset construction project area, including building material feature information, construction process feature information, and building function distribution information; Input the building detailed feature information into a preset building information layout description model for processing to generate a building construction distribution information portrait, and extract the anti-leakage node distribution information, classify and summarize the anti-leakage node distribution information through a preset construction point information queue table, and obtain the anti-leakage node category attribute information of each category of anti-leakage node; Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, and processing to obtain anti-leakage construction evaluation index and anti-leakage implementation effectiveness index of each category of anti-leakage node; Visual identification of node leakage degree of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage degree, and combined with the extracted historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes and the leakage prevention implementation effectiveness index, processing is performed to obtain category node leakage risk assessment correction data; Processing the category node leakage risk assessment correction data of each category leakage prevention node and the category node leakage risk assessment correction data of all category leakage prevention nodes to obtain the category node leakage weight index of each category leakage prevention node; According to the correction data of the leakage risk assessment of the category nodes, a threshold comparison is performed with the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of each category of leakage prevention node, and aggregation processing is performed according to the leakage risk level of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index to obtain the aggregated value of the building area leakage risk level of the preset construction project area.

[0013] Optionally, in the construction engineering leakage risk level analysis system described in the embodiment of the present application, the obtaining of building detailed feature information of a preset construction engineering area, including building material feature information, construction process feature information, and building function distribution information, comprises: Obtain detailed building feature information of the preset construction project area, including building material feature information, construction process feature information and building function distribution information, The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information; The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof caulking overlap information, pipeline hanging hole layout information and door and window sealing information; The building function distribution information includes regional function distribution information, water infiltration distribution information, leakage and moisture prevention point layout information, drainage routing information and water supply and drainage pipeline layout information.

[0014] In a third aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium includes a construction project leakage risk level analysis method program, and when the construction project leakage risk level analysis method program is executed by a processor, the steps of the construction project leakage risk level analysis method as described in any one of the above items are implemented.

[0015] As can be seen from the above, the embodiment of the present application provides a method, system and medium for analyzing the leakage risk level of a construction project, which generates a construction distribution information portrait according to the detailed feature information of the building and extracts the leakage prevention node distribution information, and then classifies and summarizes the leakage prevention node category attribute information of each category of leakage prevention nodes according to the information queue table and extracts the leakage prevention node category attribute data, and processes to obtain the leakage prevention implementation effectiveness index, and then combines the visual evaluation data of the category node leakage degree and the category node historical leakage risk actual inspection coefficient to obtain the category node leakage risk assessment correction data, and then compares and corrects with all category leakage prevention nodes to obtain the category node leakage weight index, and then aggregates the leakage risk level of all category node leakage risk assessment correction data to obtain the building area leakage risk level aggregation value; thereby, the information data of the category leakage prevention nodes in the building area are processed to obtain the node leakage risk assessment result and the corresponding leakage risk level, and the leakage risk level values ​​of all building leakage prevention nodes are aggregated to achieve the identification of building leakage risk nodes and the assessment and analysis of risk conditions.

[0016] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A flow chart of a method for analyzing the leakage risk level of a construction project provided in an embodiment of the present application; Figure 2 A flowchart of obtaining leakage prevention node category attribute information of each category of leakage prevention nodes in a construction engineering leakage risk level analysis method provided in an embodiment of the present application; Figure 3 A flowchart of a method for analyzing the leakage risk level of a construction project provided in an embodiment of the present application for obtaining a leakage prevention construction evaluation index of each type of leakage prevention node and a leakage prevention implementation effectiveness index; Figure 4 A flowchart of obtaining category node leakage risk assessment correction data for a construction project leakage risk level analysis method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0020] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0021] Please refer to Figure 1 , Figure 1The flowchart of a method for analyzing the risk level of leakage in a construction project in some embodiments of the present application is shown in FIG. The method for analyzing the risk level of leakage in a construction project is used in a terminal device, such as a computer, a mobile phone terminal, etc. The method for analyzing the risk level of leakage in a construction project comprises the following steps: S11, obtaining detailed building feature information of a preset construction project area, including building material feature information, construction process feature information, and building function distribution information; S12, inputting the building detailed feature information into a preset building information layout description model for processing to generate a building construction distribution information portrait, and extracting leakage prevention node distribution information, classifying and summarizing the leakage prevention node distribution information through a preset construction point information queue table, and obtaining leakage prevention node category attribute information of each category of leakage prevention nodes; S13, extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, and processing to obtain the anti-leakage construction evaluation index and the anti-leakage implementation effectiveness index of each category of anti-leakage node; S14, visually identify the node leakage degree of each category of leakage prevention nodes to obtain visual evaluation data of the category node leakage degree, and process it in combination with the extracted category node historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes and the leakage prevention implementation effectiveness index to obtain category node leakage risk assessment correction data; S15, processing the category node leakage risk assessment correction data of each category leakage prevention node and the category node leakage risk assessment correction data of all category leakage prevention nodes to obtain the category node leakage weight index of each category leakage prevention node; S16. Perform threshold comparison based on the leakage risk assessment correction data of the category nodes and the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of each category of leakage prevention node, and perform aggregation processing based on the leakage risk level of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index to obtain the aggregated value of the building area leakage risk level of the preset construction project area.

[0022] Among them, in order to obtain an assessment of the leakage risk status in the preset construction project area, the leakage prevention nodes that are prone to leakage and have high hidden dangers in the construction area are identified and classified, and the relevant information of the category leakage prevention nodes is processed and visually evaluated. The historical leakage risk situation of the category leakage prevention nodes is evaluated to obtain the assessment results of the node leakage risk and the corresponding leakage risk level. Then, all nodes are aggregated in combination with the weight index of the category node to obtain the leakage risk level value in the overall building area, thereby realizing the risk assessment of the building's high leakage hidden danger points and the leakage risk level assessment of the entire building area. First, the detailed building feature information of the preset construction project area is obtained. The detailed information includes the building materials, construction technology and building function distribution. Then, a construction distribution information portrait is generated in the preset building information layout description model. The distribution information portrait is an information portrait that describes the distribution of materials, processes and functional elements of buildings in the building area. It is used to distribute the building information in the building area, and then extract the distribution information of each preset anti-leakage node in the building area. The anti-leakage node is a node with anti-leakage function settings such as easy leakage, flooding, drainage and water supply in the building area. Then, the anti-leakage node distribution information is classified and summarized through the preset construction point information queue table to obtain the anti-leakage node category attribute information of each category of anti-leakage node, that is, the preset information queue table is used to classify and classify each distributed anti-leakage node to obtain various categories of anti-leakage nodes, such as drainage nodes, pipe nodes, etc. The leakage prevention node category attribute information of nodes, sealing nodes, ditch nodes, etc. is extracted, and then the corresponding leakage prevention node category attribute data is extracted according to the information, that is, the attribute characteristic data of the waterproof location, materials, process, and requirements of each category of leakage prevention node, and the process attribute data of the attribute data is processed to obtain the leakage prevention construction evaluation index, and then the leakage prevention implementation effectiveness index of each category of leakage prevention node is further calculated. In order to obtain accurate identification of the leakage prevention situation of the leakage prevention nodes in the construction project area, each category of leakage prevention nodes is identified through a visual recognition model to obtain visual evaluation data of the leakage degree, and at the same time, the average coefficient of the leakage risk actual inspection of each category of leakage prevention nodes in history is extracted from the database for combined calculation to obtain the leakage risk evaluation index of the category node. The corrected data is estimated, and the threshold comparison is performed according to the preset leakage risk level threshold corresponding to the category to obtain the leakage risk level, that is, the leakage risk of the category leakage prevention node is corrected and calculated according to the visually identifiable evaluation data combined with the historical category node actual inspection coefficient and the leakage prevention construction evaluation index, and the evaluation correction data and the corresponding leakage risk level are obtained to achieve the level evaluation of the leakage risk node. Furthermore, due to the differences in the leakage risks of different categories of leakage prevention nodes, such as the leakage risk of floor drain waterproofing is greater than the leakage risk at the corners of the floor, therefore, in order to measure the weighted influence of the leakage risk of each category of leakage prevention node on the entire construction project area, the leakage risk assessment correction data of the category node of each category of leakage prevention node is processed with all categories of leakage prevention nodes.Obtain the category node leakage weight index of each category of leakage prevention node, and then perform aggregation calculation based on the weight index combined with the leakage risk level of the corresponding category of leakage prevention node to obtain the building area leakage risk level aggregation value of all leakage risk nodes in the preset building engineering area, that is, the full node leakage risk assessment level value of the building engineering area, to achieve the level assessment of the leakage situation in the building engineering area.

[0023] According to an embodiment of the present invention, the acquisition of detailed building feature information of a preset construction project area includes building material feature information, construction process feature information, and building function distribution information, specifically: Obtain detailed building feature information of the preset construction project area, including building material feature information, construction process feature information and building function distribution information, The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information; The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof caulking overlap information, pipeline hanging hole layout information and door and window sealing information; The building function distribution information includes regional function distribution information, water infiltration distribution information, leakage and moisture prevention point layout information, drainage routing information and water supply and drainage pipeline layout information.

[0024] Among them, in order to accurately identify and evaluate the leakage risk status of the preset construction project area, it is necessary to find out the category leakage prevention nodes with higher leakage risk according to the building attribute characteristics. The leakage prevention nodes are the local leakage prevention construction points such as waterproof surface, waterproof corner, waterproof line, etc. that are prone to leakage. In order to find the key category leakage prevention nodes, it is necessary to first clarify the status of the construction project area and obtain the detailed characteristic information of the building in the preset construction project area. The detailed information includes the information of the building materials, construction technology and building function distribution. The characteristic information of building materials includes pipe The information on construction process characteristics includes the overlapping and routing of layer structures, the pouring of mortar concrete surfaces, the laying of waterproof interfaces and waterproof surfaces, the overlapping of leak-proof caulking, the routing and layout of pipeline hanging holes, and the installation and sealing of doors and windows; the information on building function distribution includes the distribution of regional functions such as dry and wet areas, drainage areas, flooded areas, the distribution of water immersion in each sub-area, the layout of leak-proof and moisture-proof points, the setting of drainage routing, and the layout of water supply and drainage pipelines.

[0025] Please refer to Figure 2 , Figure 2It is a flowchart of obtaining the anti-leakage node category attribute information of each category of anti-leakage node in the method for analyzing the leakage risk level of a building project in some embodiments of the present application. According to an embodiment of the present invention, the building detailed feature information is input into a preset building information layout description model for processing to generate a building construction distribution information portrait, and the anti-leakage node distribution information is extracted, and the anti-leakage node distribution information is classified and summarized through a preset construction point information queue table according to the anti-leakage node distribution information, and the anti-leakage node category attribute information of each category of anti-leakage node is obtained, specifically: S21, inputting the building material characteristic information, construction process characteristic information and building function distribution information into a preset building information layout depiction model for processing, and generating a building construction distribution information portrait of the preset building project area; S22, extracting the leakage prevention node distribution information of the preset construction project area according to the construction distribution information portrait, including the node position distribution information of each leakage prevention node, the waterproof plugging process information, the sealing and filling material information, the water immersion frequency information and the leakage prevention demand information; S23, classify and summarize the node position distribution information, waterproof plugging process information, sealing and filling material information and leakage prevention demand information of each leakage prevention node through a preset construction point information queue table to obtain the leakage prevention node category attribute information corresponding to each category of leakage prevention node.

[0026] Among them, after obtaining the detailed characteristic information in the construction project area, in order to describe the distribution of construction in the construction project area in an information-based manner, the preset building information layout description model is used to process the building detailed characteristic information to generate a construction distribution information portrait, which is an information portrait that describes the distribution of materials, processes and functional elements of buildings in the construction area. Then, based on the distribution information portrait, the leakage prevention node distribution information in the preset construction project area is extracted, that is, the distribution information of each construction node where the leakage prevention construction requirements are set is extracted, including the calibrated distribution of the node position of each leakage prevention node, the construction process of waterproofing and plugging, the materials used for sealing and filling, the frequency and amount of node water immersion, and the node In order to further evaluate the leakage risk of each leakage prevention node, it is necessary to classify and integrate each node, so as to conduct risk analysis through the integrated node category, and classify and summarize the leakage prevention node distribution information of each leakage prevention node through the preset construction point information queue table to obtain the summarized leakage prevention node category attribute information of each category of leakage prevention node, that is, according to the distribution information of the leakage prevention construction of the node, classify and summarize it through the preset queue table to obtain the summarized category node and leakage prevention attribute information, such as summarizing the drainage nodes with the same process, material and water infiltration volume, or the interface joints of the doors and windows installed on the exterior wall, and extract the category attribute information for further leakage risk assessment and analysis.

[0027] Please refer to Figure 3 , Figure 2 The present invention is a flowchart of obtaining the leakage prevention construction evaluation index and the leakage prevention implementation effectiveness index of each category of leakage prevention nodes of the construction engineering leakage risk level analysis method in some embodiments of the present application. According to the embodiment of the present invention, the corresponding leakage prevention node category attribute data is extracted according to the leakage prevention node category attribute information, and the leakage prevention construction evaluation index and the leakage prevention implementation effectiveness index of each category of leakage prevention nodes are obtained by processing, specifically: S31, extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, including the node position anti-leakage level, water immersion frequency level, waterproof plugging construction standard data and sealing filling material standard data; S32, the standard data of waterproof and leak-proof construction includes grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data; S33, processing the grouting density data, grouting viscosity data, caulking fullness data and coating thickness data of each type of leakproof node to obtain a leakproof construction evaluation index; S34, according to the leakage prevention construction evaluation index combined with the standard data of sealing and filling materials, as well as the leakage prevention level of the node position and the water immersion frequency level, a preset leakage prevention effect verification model is used for processing to obtain the leakage prevention implementation effectiveness index of each category of leakage prevention node.

[0028] Among them, after obtaining the category attribute information of each category of leakage-proof nodes, the leakage-proof construction effect of each category of leakage-proof nodes is evaluated, and the corresponding leakage-proof node category attribute data is extracted according to the leakage-proof node category attribute information of each category of nodes, including the preset leakage-proof rating level of the node position, the preset rating level of the water immersion frequency, the data of the waterproof plugging construction standard, and the data of the sealing and filling material standard. The waterproof plugging construction standard data includes the data of the grouting density of the mortar concrete soil, the grouting viscosity, the fullness of the filling, and the coating thickness. Then, according to the construction standard data, calculation and processing are performed to obtain the evaluation index of the node leakage-proof construction effect, and then according to the leakage-proof construction evaluation index combined with the standard data of the sealing and filling materials, the leakage level of the node position, and the water immersion frequency level, the calculation formula of the preset leakage-proof effect verification model is used to calculate, and the corresponding leakage-proof implementation effectiveness index of each category of leakage-proof nodes is obtained, that is, the result index of the leakage-proof implementation effectiveness evaluation of each category of leakage-proof nodes, reflecting the implementation effect of the leakage-proof construction of a certain type of leakage-proof and waterproof nodes; wherein, the calculation formula of the leakage-proof construction evaluation index is: ; in, It is the leak-proof construction evaluation index. , , , They are respectively the pouring density data, grouting viscosity data, filling fullness data, and coating thickness data. , , , is the preset characteristic coefficient; The calculation formula of the leakage prevention implementation effectiveness index is: ; in, To prevent leakage, we implemented the effectiveness index. It is the leak-proof construction evaluation index. Standard data for sealing and filling materials, is the water immersion frequency order, is the leak-proof level of the node position, , , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0029] Please refer to Figure 4 , Figure 4 It is a flowchart of obtaining the correction data of leakage risk assessment of category nodes in the construction engineering leakage risk level analysis method in some embodiments of the present application. According to the embodiment of the present invention, the visual identification of the node leakage degree of each category of leakage prevention node is performed to obtain the visual evaluation data of the leakage degree of the category node, and the historical leakage risk actual inspection coefficient of the category node of each category of leakage prevention node extracted and the leakage prevention implementation effectiveness index are processed to obtain the correction data of leakage risk assessment of the category node, which is specifically: S41, visually identifying the node leakage degree of each category of anti-leakage node according to a preset building node leakage visual recognition model, and obtaining visual evaluation data of the node leakage degree of each category; S42, extracting the historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes according to the preset building leakage information monitoring database; S43, processing the leakage prevention implementation effectiveness index of each category of leakage prevention node in combination with the visual evaluation data of the leakage degree of the corresponding category node and the average coefficient of the historical leakage risk inspection of the category node to obtain the category node leakage risk assessment correction data; The calculation formula for the correction data of the leakage risk assessment of the category node is: ; in, Correct data for category node leakage risk assessment, To prevent leakage, we implemented the effectiveness index. is the visual evaluation data of the leakage degree of the category node, is the average coefficient of historical leakage risk of category nodes, , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0030] Among them, in order to obtain an accurate assessment of the leakage situation in the construction project area, in addition to the assessment based on the extracted node attribute feature data, the visual evaluation data of the leakage degree obtained by visually identifying the node leakage degree according to the preset building node leakage visual recognition model, as well as the historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes extracted from the preset building leakage information monitoring database are added. The preset building node leakage visual recognition model is a leakage assessment model that performs visual leakage recognition on the appearance of building nodes, and an evaluation of the node leakage degree can be obtained. The historical leakage risk actual inspection average coefficient of the category node is the actual inspection average coefficient obtained by actual inspection of each category of leakage prevention nodes in history. The accuracy of the node leakage risk assessment is increased by combining the node leakage visual evaluation result with the historical leakage risk inspection average coefficient and the correction processing of the leakage prevention implementation effectiveness index, and the category node leakage risk assessment correction data is calculated, that is, the correction result data of the leakage risk assessment of each category of leakage prevention nodes.

[0031] According to an embodiment of the present invention, the category node leakage risk assessment correction data of each category leakage prevention node and the category node leakage risk assessment correction data of all category leakage prevention nodes are processed to obtain the category node leakage weight index of each category leakage prevention node, specifically: Processing the leakage risk assessment correction data of the category nodes of each category of leakage prevention nodes and the leakage risk assessment correction data of the category nodes corresponding to all category leakage prevention nodes of the preset construction project area to obtain the category node leakage weight index corresponding to each category of leakage prevention nodes; The calculation formula of the category node leakage weight index is: ; in, is the category node leakage weight index of the i-th category anti-leakage node, is the correction data of the leakage risk assessment of the i-th category leakage prevention node, n is the number of categories of all category leakage prevention nodes, , is the preset characteristic coefficient of the i-th category anti-leakage node (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0032] Among them, after obtaining the leakage risk assessment results of various types of leakage-proof nodes in the construction project area, since there are differences in the leakage risks of different types of leakage-proof nodes, such as the leakage risk of floor drain waterproofing is greater than the leakage risk at the floor corners, therefore, in order to measure the weight influence of the leakage risk of various types of leakage-proof nodes on the entire construction project area, the weight calculation is performed on the leakage risk assessment correction data of the category nodes of each type of leakage-proof node and all types of leakage-proof nodes to obtain the category node leakage weight index of each type of leakage-proof node.

[0033] According to an embodiment of the present invention, the leakage risk assessment correction data of the category nodes is compared with the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of each category of leakage prevention nodes, and the leakage risk level of all category leakage prevention nodes is combined with the corresponding category node leakage weight index to perform aggregation processing to obtain the building area leakage risk level aggregation value of the preset building project area, which is specifically: Perform threshold comparison based on the category node leakage risk assessment correction data of each category leakage prevention node and the preset category node leakage risk level threshold corresponding to the category leakage prevention node; According to the threshold comparison results, the leakage risk level of each type of leakage prevention node is obtained; Aggregation processing is performed according to the corresponding leakage risk levels of all categories of leakage prevention nodes in the preset construction project area, combined with the corresponding category node leakage weight index and the node position leakage prevention level, to obtain the building area leakage risk level aggregation value of the preset construction project area; The aggregate calculation formula for the aggregate value of the leakage risk level of the building area is: ; in, is the aggregate value of the leakage risk level of the building area, is the category node leakage weight index of the i-th category anti-leakage node, is the node position leakage-proof level of the i-th category leakage-proof node, is the leakage risk level of the i-th type of leakage prevention node, , is the preset characteristic coefficient of the i-th category anti-leakage node (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0034] Among them, according to the leakage risk assessment correction data of each category of leakage prevention nodes, the corresponding leakage risk level is obtained by threshold comparison, that is, the threshold range and level corresponding to the leakage risk assessment result of each category of leakage prevention nodes are obtained through the segmented threshold range of the preset category node leakage risk level threshold. In this embodiment, the preset category node leakage risk level threshold of a certain category of leakage prevention nodes is divided into level 1 to level 5, with level 5 being the highest. The 5 levels correspond to threshold ranges of (0, 0.18), [0.18, 0.47), [0.47, 0.62), [0.62, 0.83), [0.83, 1.0], respectively. The threshold comparison result of a certain category node X is 0.77, then the corresponding risk level threshold range of X is 4, that is, the leakage risk level of X is 4. In order to evaluate the overall leakage risk level value of all categories of leakage prevention nodes in the preset construction engineering area, according to the corresponding leakage risk levels of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index and the node position leakage prevention level, aggregation calculation processing is performed to obtain the building area leakage risk level aggregation value of the preset construction engineering area, that is, the leakage risk assessment level value of all nodes in the construction engineering area, so as to realize the evaluation of the leakage risk of each category of nodes and the overall building in the construction engineering area.

[0035] The second aspect of the present invention further discloses a construction engineering leakage risk level analysis system, comprising a memory and a processor, wherein the memory comprises a construction engineering leakage risk level analysis method program, and when the construction engineering leakage risk level analysis method program is executed by the processor, the following steps are implemented: Obtain detailed building feature information of a preset construction project area, including building material feature information, construction process feature information, and building function distribution information; Input the building detailed feature information into a preset building information layout description model for processing to generate a building construction distribution information portrait, and extract the anti-leakage node distribution information, classify and summarize the anti-leakage node distribution information through a preset construction point information queue table, and obtain the anti-leakage node category attribute information of each category of anti-leakage node; Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, and processing to obtain anti-leakage construction evaluation index and anti-leakage implementation effectiveness index of each category of anti-leakage node; Visual identification of node leakage degree of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage degree, and combined with the extracted historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes and the leakage prevention implementation effectiveness index, processing is performed to obtain category node leakage risk assessment correction data; Processing the category node leakage risk assessment correction data of each category leakage prevention node and the category node leakage risk assessment correction data of all category leakage prevention nodes to obtain the category node leakage weight index of each category leakage prevention node; According to the correction data of the leakage risk assessment of the category nodes, a threshold comparison is performed with the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of each category of leakage prevention node, and aggregation processing is performed according to the leakage risk level of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index to obtain the aggregated value of the building area leakage risk level of the preset construction project area.

[0036] Among them, in order to obtain an assessment of the leakage risk status in the preset construction project area, the leakage prevention nodes that are prone to leakage and have high hidden dangers in the construction area are identified and classified, and the relevant information of the category leakage prevention nodes is processed and visually evaluated. The historical leakage risk situation of the category leakage prevention nodes is evaluated to obtain the assessment results of the node leakage risk and the corresponding leakage risk level. Then, all nodes are aggregated in combination with the weight index of the category node to obtain the leakage risk level value in the overall building area, thereby realizing the risk assessment of the building's high leakage hidden danger points and the leakage risk level assessment of the entire building area. First, the detailed building feature information of the preset construction project area is obtained. The detailed information includes the building materials, construction technology and building function distribution. Then, a construction distribution information portrait is generated in the preset building information layout description model. The distribution information portrait is an information portrait that describes the distribution of materials, processes and functional elements of buildings in the building area. It is used to distribute the building information in the building area, and then extract the distribution information of each preset anti-leakage node in the building area. The anti-leakage node is a node with anti-leakage function settings such as easy leakage, flooding, drainage and water supply in the building area. Then, the anti-leakage node distribution information is classified and summarized through the preset construction point information queue table to obtain the anti-leakage node category attribute information of each category of anti-leakage node, that is, the preset information queue table is used to classify and classify each distributed anti-leakage node to obtain various categories of anti-leakage nodes, such as drainage nodes, pipe nodes, etc. The leakage prevention node category attribute information of nodes, sealing nodes, ditch nodes, etc. is extracted, and then the corresponding leakage prevention node category attribute data is extracted according to the information, that is, the attribute characteristic data of the waterproof location, materials, process, and requirements of each category of leakage prevention node, and the process attribute data of the attribute data is processed to obtain the leakage prevention construction evaluation index, and then the leakage prevention implementation effectiveness index of each category of leakage prevention node is further calculated. In order to obtain accurate identification of the leakage prevention situation of the leakage prevention nodes in the construction project area, each category of leakage prevention nodes is identified through a visual recognition model to obtain visual evaluation data of the leakage degree, and at the same time, the average coefficient of the leakage risk actual inspection of each category of leakage prevention nodes in history is extracted from the database for combined calculation to obtain the leakage risk evaluation index of the category node. The corrected data is estimated, and the threshold comparison is performed according to the preset leakage risk level threshold corresponding to the category to obtain the leakage risk level, that is, the leakage risk of the category leakage prevention node is corrected and calculated according to the visually identifiable evaluation data combined with the historical category node actual inspection coefficient and the leakage prevention construction evaluation index, and the evaluation correction data and the corresponding leakage risk level are obtained to achieve the level evaluation of the leakage risk node. Furthermore, due to the differences in the leakage risks of different categories of leakage prevention nodes, such as the leakage risk of floor drain waterproofing is greater than the leakage risk at the corners of the floor, therefore, in order to measure the weighted influence of the leakage risk of each category of leakage prevention node on the entire construction project area, the leakage risk assessment correction data of the category node of each category of leakage prevention node is processed with all categories of leakage prevention nodes.Obtain the category node leakage weight index of each category of leakage prevention node, and then perform aggregation calculation based on the weight index combined with the leakage risk level of the corresponding category of leakage prevention node to obtain the building area leakage risk level aggregation value of all leakage risk nodes in the preset building engineering area, that is, the full node leakage risk assessment level value of the building engineering area, to achieve the level assessment of the leakage situation in the building engineering area.

[0037] According to an embodiment of the present invention, the acquisition of detailed building feature information of a preset construction project area includes building material feature information, construction process feature information, and building function distribution information, specifically: Obtain detailed building feature information of the preset construction project area, including building material feature information, construction process feature information and building function distribution information, The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information; The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof caulking overlap information, pipeline hanging hole layout information and door and window sealing information; The building function distribution information includes regional function distribution information, water infiltration distribution information, leakage and moisture prevention point layout information, drainage routing information and water supply and drainage pipeline layout information.

[0038] Among them, in order to accurately identify and evaluate the leakage risk status of the preset construction project area, it is necessary to find out the category leakage prevention nodes with higher leakage risk according to the building attribute characteristics. The leakage prevention nodes are the local leakage prevention construction points such as waterproof surface, waterproof corner, waterproof line, etc. that are prone to leakage. In order to find the key category leakage prevention nodes, it is necessary to first clarify the status of the construction project area and obtain the detailed characteristic information of the building in the preset construction project area. The detailed information includes the information of the building materials, construction technology and building function distribution. The characteristic information of building materials includes pipe The information on construction process characteristics includes the overlapping and routing of layer structures, the pouring of mortar concrete surfaces, the laying of waterproof interfaces and waterproof surfaces, the overlapping of leak-proof caulking, the routing and layout of pipeline hanging holes, and the installation and sealing of doors and windows; the information on building function distribution includes the distribution of regional functions such as dry and wet areas, drainage areas, flooded areas, the distribution of water immersion in each sub-area, the layout of leak-proof and moisture-proof points, the setting of drainage routing, and the layout of water supply and drainage pipelines.

[0039] According to an embodiment of the present invention, the building detailed feature information is input into a preset building information layout depiction model for processing to generate a building construction distribution information portrait, and leak prevention node distribution information is extracted. According to the leak prevention node distribution information, the leak prevention node category attribute information of each category of leak prevention nodes is obtained by classifying and summarizing the leak prevention node category attribute information through a preset construction point information queue table, specifically: Inputting the building material characteristic information, construction process characteristic information and building function distribution information into a preset building information layout depiction model for processing, and generating a building construction distribution information portrait of the preset building project area; Extracting the anti-leakage node distribution information of the preset construction project area according to the construction distribution information portrait, including the node position distribution information of each anti-leakage node, the waterproof plugging process information, the sealing and filling material information, the water immersion frequency information and the anti-leakage demand information; According to the node location distribution information, waterproof plugging process information, sealing and filling material information and leakage prevention demand information of each leakage prevention node, the leakage prevention node category attribute information corresponding to each category of leakage prevention node is obtained by classifying and summarizing them through a preset construction point information queue table.

[0040] Among them, after obtaining the detailed characteristic information in the construction project area, in order to describe the distribution of construction in the construction project area in an information-based manner, the preset building information layout description model is used to process the building detailed characteristic information to generate a construction distribution information portrait, which is an information portrait that describes the distribution of materials, processes and functional elements of buildings in the construction area. Then, based on the distribution information portrait, the leakage prevention node distribution information in the preset construction project area is extracted, that is, the distribution information of each construction node where the leakage prevention construction requirements are set is extracted, including the calibrated distribution of the node position of each leakage prevention node, the construction process of waterproofing and plugging, the materials used for sealing and filling, the frequency and amount of node water immersion, and the node In order to further evaluate the leakage risk of each leakage prevention node, it is necessary to classify and integrate each node, so as to conduct risk analysis through the integrated node category, and classify and summarize the leakage prevention node distribution information of each leakage prevention node through the preset construction point information queue table to obtain the summarized leakage prevention node category attribute information of each category of leakage prevention node, that is, according to the distribution information of the leakage prevention construction of the node, classify and summarize it through the preset queue table to obtain the summarized category node and leakage prevention attribute information, such as summarizing the drainage nodes with the same process, material and water infiltration volume, or the interface joints of the doors and windows installed on the exterior wall, and extract the category attribute information for further leakage risk assessment and analysis.

[0041] According to an embodiment of the present invention, the corresponding anti-leakage node category attribute data is extracted according to the anti-leakage node category attribute information, and the anti-leakage construction evaluation index and the anti-leakage implementation effectiveness index of each category of anti-leakage node are obtained by processing, specifically: Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, including the node position anti-leakage level, water immersion frequency level, waterproof plugging construction standard data and sealing filling material standard data; The standard data for waterproof and leak-proof construction include grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data; According to the injection density data, injection viscosity data, filling fullness data and coating thickness data of each type of leakproof node, a leakproof construction evaluation index is obtained; The leakage prevention construction evaluation index is combined with the standard data of sealing and filling materials as well as the leakage prevention level of the node position and the water immersion frequency level through a preset leakage prevention effect verification model to obtain the leakage prevention implementation effectiveness index of each category of leakage prevention node.

[0042] Among them, after obtaining the category attribute information of each category of leakage-proof nodes, the leakage-proof construction effect of each category of leakage-proof nodes is evaluated, and the corresponding leakage-proof node category attribute data is extracted according to the leakage-proof node category attribute information of each category of nodes, including the preset leakage-proof rating level of the node position, the preset rating level of the water immersion frequency, the data of the waterproof plugging construction standard, and the data of the sealing and filling material standard. The waterproof plugging construction standard data includes the data of the grouting density of the mortar concrete soil, the grouting viscosity, the fullness of the filling, and the coating thickness. Then, according to the construction standard data, calculation and processing are performed to obtain the evaluation index of the node leakage-proof construction effect, and then according to the leakage-proof construction evaluation index combined with the standard data of the sealing and filling materials, the leakage level of the node position, and the water immersion frequency level, the calculation formula of the preset leakage-proof effect verification model is used to calculate, and the corresponding leakage-proof implementation effectiveness index of each category of leakage-proof nodes is obtained, that is, the result index of the leakage-proof implementation effectiveness evaluation of each category of leakage-proof nodes, reflecting the implementation effect of the leakage-proof construction of a certain type of leakage-proof and waterproof nodes; wherein, the calculation formula of the leakage-proof construction evaluation index is: ; in, It is the leak-proof construction evaluation index. , , , They are respectively the pouring density data, grouting viscosity data, filling fullness data, and coating thickness data. , , , is the preset characteristic coefficient; The calculation formula of the leakage prevention implementation effectiveness index is: ; in, To prevent leakage, we implemented the effectiveness index. It is the leak-proof construction evaluation index. Standard data for sealing and filling materials, is the water immersion frequency order, is the leak-proof level of the node position, , , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0043] According to an embodiment of the present invention, the visual identification of the node leakage degree of each category of leakage prevention nodes is performed to obtain the visual evaluation data of the category node leakage degree, and the category node historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes extracted and the leakage prevention implementation effectiveness index are processed to obtain the category node leakage risk assessment correction data, specifically: According to the preset building node leakage visual recognition model, the node leakage degree of each category of anti-leakage node is visually identified, and the visual evaluation data of the node leakage degree of each category is obtained; According to the preset building leakage information monitoring database, the historical leakage risk inspection average coefficient of each category of leakage prevention nodes is extracted; According to the leakage prevention implementation effectiveness index of each category of leakage prevention node, combined with the visual evaluation data of the leakage degree of the corresponding category node and the average coefficient of the historical leakage risk of the category node, the leakage risk assessment correction data of the category node is obtained; The calculation formula for the correction data of the leakage risk assessment of the category node is: ; in, Correct data for category node leakage risk assessment, To prevent leakage, we implemented the effectiveness index. is the visual evaluation data of the leakage degree of the category node, is the average coefficient of historical leakage risk of category nodes, , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0044] Among them, in order to obtain an accurate assessment of the leakage situation in the construction project area, in addition to the assessment based on the extracted node attribute feature data, the visual evaluation data of the leakage degree obtained by visually identifying the node leakage degree according to the preset building node leakage visual recognition model, as well as the historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes extracted from the preset building leakage information monitoring database are added. The preset building node leakage visual recognition model is a leakage assessment model that performs visual leakage recognition on the appearance of building nodes, and an evaluation of the node leakage degree can be obtained. The historical leakage risk actual inspection average coefficient of the category node is the actual inspection average coefficient obtained by actual inspection of each category of leakage prevention nodes in history. The accuracy of the node leakage risk assessment is increased by combining the node leakage visual evaluation result with the historical leakage risk inspection average coefficient and the correction processing of the leakage prevention implementation effectiveness index, and the category node leakage risk assessment correction data is calculated, that is, the correction result data of the leakage risk assessment of each category of leakage prevention nodes.

[0045] According to an embodiment of the present invention, the category node leakage risk assessment correction data of each category leakage prevention node and the category node leakage risk assessment correction data of all category leakage prevention nodes are processed to obtain the category node leakage weight index of each category leakage prevention node, specifically: Processing the leakage risk assessment correction data of the category nodes of each category of leakage prevention nodes and the leakage risk assessment correction data of the category nodes corresponding to all category leakage prevention nodes of the preset construction project area to obtain the category node leakage weight index corresponding to each category of leakage prevention nodes; The calculation formula of the category node leakage weight index is: ; in, is the category node leakage weight index of the i-th category anti-leakage node, is the correction data of the leakage risk assessment of the i-th category leakage prevention node, n is the number of categories of all category leakage prevention nodes, , is the preset characteristic coefficient of the i-th category anti-leakage node (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0046] Among them, after obtaining the leakage risk assessment results of various types of leakage-proof nodes in the construction project area, since there are differences in the leakage risks of different types of leakage-proof nodes, such as the leakage risk of floor drain waterproofing is greater than the leakage risk at the floor corners, therefore, in order to measure the weight influence of the leakage risk of various types of leakage-proof nodes on the entire construction project area, the weight calculation is performed on the leakage risk assessment correction data of the category nodes of each type of leakage-proof node and all types of leakage-proof nodes to obtain the category node leakage weight index of each type of leakage-proof node.

[0047] According to an embodiment of the present invention, the leakage risk assessment correction data of the category nodes is compared with the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of each category of leakage prevention nodes, and the leakage risk level of all category leakage prevention nodes is combined with the corresponding category node leakage weight index to perform aggregation processing to obtain the building area leakage risk level aggregation value of the preset building project area, which is specifically: Perform threshold comparison based on the category node leakage risk assessment correction data of each category leakage prevention node and the preset category node leakage risk level threshold corresponding to the category leakage prevention node; According to the threshold comparison results, the leakage risk level of each type of leakage prevention node is obtained; Aggregation processing is performed according to the corresponding leakage risk levels of all categories of leakage prevention nodes in the preset construction project area, combined with the corresponding category node leakage weight index and the node position leakage prevention level, to obtain the building area leakage risk level aggregation value of the preset construction project area; The aggregate calculation formula for the aggregate value of the leakage risk level of the building area is: ; in, is the aggregate value of the leakage risk level of the building area, is the category node leakage weight index of the i-th category anti-leakage node, is the node position leakage-proof level of the i-th category leakage-proof node, is the leakage risk level of the i-th type of leakage prevention node, , is the preset characteristic coefficient of the i-th category anti-leakage node (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0048] Among them, according to the leakage risk assessment correction data of each category of leakage prevention nodes, the corresponding leakage risk level is obtained by threshold comparison, that is, the threshold range and level corresponding to the leakage risk assessment result of each category of leakage prevention nodes are obtained through the segmented threshold range of the preset category node leakage risk level threshold. In this embodiment, the preset category node leakage risk level threshold of a certain category of leakage prevention nodes is divided into level 1 to level 5, with level 5 being the highest. The 5 levels correspond to threshold ranges of (0, 0.18), [0.18, 0.47), [0.47, 0.62), [0.62, 0.83), [0.83, 1.0], respectively. The threshold comparison result of a certain category node X is 0.77, then the corresponding risk level threshold range of X is 4, that is, the leakage risk level of X is 4. In order to evaluate the overall leakage risk level value of all categories of leakage prevention nodes in the preset construction engineering area, according to the corresponding leakage risk levels of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index and the node position leakage prevention level, aggregation calculation processing is performed to obtain the building area leakage risk level aggregation value of the preset construction engineering area, that is, the leakage risk assessment level value of all nodes in the construction engineering area, so as to realize the evaluation of the leakage risk of each category of nodes and the overall building in the construction engineering area.

[0049] The third aspect of the present invention provides a computer-readable storage medium, which includes a construction project leakage risk level analysis method program. When the construction project leakage risk level analysis method program is executed by a processor, the steps of the construction project leakage risk level analysis method as described in any one of the above items are implemented.

[0050] The invention discloses a method, system and medium for analyzing the leakage risk level of a construction project. The method generates a construction distribution information portrait according to detailed characteristic information of a building and extracts the leakage prevention node distribution information. The method then classifies and summarizes the leakage prevention node category attribute information of each category of leakage prevention nodes according to an information queue table, extracts the leakage prevention node category attribute data, processes the leakage prevention implementation effectiveness index, combines the category node leakage degree visual evaluation data and the category node historical leakage risk actual inspection coefficient processing to obtain the category node leakage risk assessment correction data, compares and corrects with all category leakage prevention nodes to obtain the category node leakage weight index, and aggregates the leakage risk level of all category node leakage risk assessment correction data to obtain the building area leakage risk level aggregation value. The information data of the category leakage prevention nodes in the building area are processed to obtain the node leakage risk assessment result and the corresponding leakage risk level, and the leakage risk level values ​​of all building leakage prevention nodes are aggregated to obtain the leakage risk level values ​​of all building leakage prevention nodes, thereby realizing the identification of building leakage risk nodes and the evaluation and analysis of risk conditions.

[0051] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0052] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0053] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0054] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, the aforementioned program can be stored in a readable storage medium, and when the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0055] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A method for analyzing the leakage risk level of a construction project, characterized in that: The following steps are involved: Obtain detailed building feature information of a preset construction project area, including building material feature information, construction process feature information, and building function distribution information; Input the building detailed feature information into a preset building information layout description model for processing to generate a building construction distribution information portrait, and extract the anti-leakage node distribution information, classify and summarize the anti-leakage node distribution information through a preset construction point information queue table, and obtain the anti-leakage node category attribute information of each category of anti-leakage node; Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, and processing to obtain anti-leakage construction evaluation index and anti-leakage implementation effectiveness index of each category of anti-leakage node; Visual identification of node leakage degree of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage degree, and combined with the extracted historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes and the leakage prevention implementation effectiveness index, processing is performed to obtain category node leakage risk assessment correction data; Processing the category node leakage risk assessment correction data of each category leakage prevention node and the category node leakage risk assessment correction data of all category leakage prevention nodes to obtain the category node leakage weight index of each category leakage prevention node; According to the correction data of the leakage risk assessment of the category nodes, a threshold comparison is performed with the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of each category of leakage prevention node, and aggregation processing is performed according to the leakage risk level of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index to obtain the aggregated value of the building area leakage risk level of the preset construction project area.

2. The method for analyzing the leakage risk level of a construction project according to claim 1, characterized in that: The obtaining of detailed building feature information of a preset construction project area, including building material feature information, construction process feature information, and building function distribution information, includes: Obtain detailed building feature information of the preset construction project area, including building material feature information, construction process feature information and building function distribution information, The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information; The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof caulking overlap information, pipeline hanging hole layout information and door and window sealing information; The building function distribution information includes regional function distribution information, water infiltration distribution information, leakage and moisture prevention point layout information, drainage routing information and water supply and drainage pipeline layout information.

3. The method for analyzing the leakage risk level of a construction project according to claim 2, characterized in that: The building detailed feature information is input into a preset building information layout description model for processing to generate a building construction distribution information portrait, and the anti-leakage node distribution information is extracted. According to the anti-leakage node distribution information, the anti-leakage node category attribute information of each category of anti-leakage node is obtained by classifying and summarizing the preset construction point information queue table. The process includes: Inputting the building material characteristic information, construction process characteristic information and building function distribution information into a preset building information layout depiction model for processing, and generating a building construction distribution information portrait of the preset building project area; Extracting the anti-leakage node distribution information of the preset construction project area according to the construction distribution information portrait, including the node position distribution information of each anti-leakage node, the waterproof plugging process information, the sealing and filling material information, the water immersion frequency information and the anti-leakage demand information; According to the node location distribution information, waterproof plugging process information, sealing and filling material information and leakage prevention demand information of each leakage prevention node, the leakage prevention node category attribute information corresponding to each category of leakage prevention node is obtained by classifying and summarizing through a preset construction point information queue table.

4. The method for analyzing the leakage risk level of a construction project according to claim 3 is characterized in that: The step of extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, and processing to obtain the anti-leakage construction evaluation index and the anti-leakage implementation effectiveness index of each category of anti-leakage node includes: Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, including the node position anti-leakage level, water immersion frequency level, waterproof plugging construction standard data and sealing filling material standard data; The standard data for waterproof and leak-proof construction include grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data; Processing is performed according to the grouting density data, grouting viscosity data, caulking fullness data and coating thickness data of each type of leakproof node to obtain a leakproof construction evaluation index; The leakage prevention construction evaluation index is combined with the standard data of sealing and filling materials as well as the leakage prevention level and water immersion frequency level of the node position through a preset leakage prevention effect verification model to obtain the leakage prevention implementation effectiveness index of each category of leakage prevention node.

5. The method for analyzing the leakage risk level of a construction project according to claim 4 is characterized in that: The node leakage degree visualization identification of each category of leakage prevention nodes is performed to obtain the category node leakage degree visual evaluation data, and combined with the extracted category node historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes and the leakage prevention implementation effectiveness index, the category node leakage risk assessment correction data is obtained, including: According to the preset building node leakage visual recognition model, the node leakage degree of each category of anti-leakage node is visually identified, and the visual evaluation data of the node leakage degree of each category is obtained; According to the preset building leakage information monitoring database, the historical leakage risk inspection average coefficient of each category of leakage prevention nodes is extracted; According to the leakage prevention implementation effectiveness index of each category of leakage prevention node, combined with the visual evaluation data of the leakage degree of the corresponding category node and the average coefficient of the historical leakage risk of the category node, the leakage risk assessment correction data of the category node is obtained; The calculation formula for the correction data of the leakage risk assessment of the category node is: ； in, Correct data for category node leakage risk assessment, To prevent leakage, we implemented the effectiveness index. is the visual evaluation data of the leakage degree of the category node, is the average coefficient of historical leakage risk of category nodes, , , , is the preset characteristic coefficient.

6. The method for analyzing the leakage risk level of a construction project according to claim 5, characterized in that: The step of processing the category node leakage risk assessment correction data of each category leakage prevention node and the category node leakage risk assessment correction data of all category leakage prevention nodes to obtain the category node leakage weight index of each category leakage prevention node includes: Processing the leakage risk assessment correction data of the category nodes of each category of leakage prevention nodes and the leakage risk assessment correction data of the category nodes corresponding to all category leakage prevention nodes of the preset construction project area to obtain the category node leakage weight index corresponding to each category of leakage prevention nodes; The calculation formula of the category node leakage weight index is: ； in, is the category node leakage weight index of the i-th category anti-leakage node, is the correction data of the leakage risk assessment of the i-th category leakage prevention node, n is the number of categories of all category leakage prevention nodes, , is the preset characteristic coefficient of the anti-leakage node of the i-th category.

7. The method for analyzing the leakage risk level of a construction project according to claim 6, characterized in that: The threshold comparison is performed according to the correction data of the leakage risk assessment of the category nodes and the corresponding preset category node leakage risk level threshold, to obtain the leakage risk level of the corresponding category leakage prevention nodes, and the aggregation processing is performed according to the leakage risk level of all category leakage prevention nodes combined with the corresponding category node leakage weight index to obtain the building area leakage risk level aggregation value of the preset construction project area, including: Perform threshold comparison based on the category node leakage risk assessment correction data of each category leakage prevention node and the preset category node leakage risk level threshold corresponding to the category leakage prevention node; According to the threshold comparison results, the leakage risk level of each type of leakage prevention node is obtained; Aggregation processing is performed according to the corresponding leakage risk levels of all categories of leakage prevention nodes in the preset construction project area, combined with the corresponding category node leakage weight index and the node position leakage prevention level, to obtain the building area leakage risk level aggregation value of the preset construction project area; The aggregate calculation formula for the aggregate value of the leakage risk level of the building area is: ； in, is the aggregate value of the leakage risk level of the building area, is the category node leakage weight index of the i-th category anti-leakage node, is the node position leakage-proof level of the i-th category leakage-proof node, is the leakage risk level of the i-th type of leakage prevention node, , is the preset characteristic coefficient of the anti-leakage node of the i-th category.

8. A construction engineering leakage risk level analysis system, characterized in that: The system includes: a memory and a processor, wherein the memory includes a program of a construction engineering leakage risk level analysis method, and when the program of the construction engineering leakage risk level analysis method is executed by the processor, the following steps are implemented: Obtain detailed building feature information of a preset construction project area, including building material feature information, construction process feature information, and building function distribution information; Input the building detailed feature information into a preset building information layout description model for processing to generate a building construction distribution information portrait, and extract the anti-leakage node distribution information, classify and summarize the anti-leakage node distribution information through a preset construction point information queue table, and obtain the anti-leakage node category attribute information of each category of anti-leakage node; Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, and processing to obtain anti-leakage construction evaluation index and anti-leakage implementation effectiveness index of each category of anti-leakage node; Visual identification of node leakage degree of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage degree, and combined with the extracted historical leakage risk actual inspection average coefficient of each category of leakage prevention nodes and the leakage prevention implementation effectiveness index, processing is performed to obtain category node leakage risk assessment correction data; Processing the category node leakage risk assessment correction data of each category leakage prevention node and the category node leakage risk assessment correction data of all category leakage prevention nodes to obtain the category node leakage weight index of each category leakage prevention node; According to the correction data of the leakage risk assessment of the category nodes, a threshold comparison is performed with the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of each category of leakage prevention node, and aggregation processing is performed according to the leakage risk level of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index to obtain the aggregated value of the building area leakage risk level of the preset construction project area.

9. The construction engineering leakage risk level analysis system according to claim 8, characterized in that: The obtaining of detailed building feature information of a preset construction project area, including building material feature information, construction process feature information, and building function distribution information, includes: Obtain detailed building feature information of the preset construction project area, including building material feature information, construction process feature information and building function distribution information, The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information; The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof caulking overlap information, pipeline hanging hole layout information and door and window sealing information; The building function distribution information includes regional function distribution information, water infiltration distribution information, leakage and moisture prevention point layout information, drainage routing information and water supply and drainage pipeline layout information.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a construction project leakage risk level analysis method program. When the construction project leakage risk level analysis method program is executed by a processor, the steps of the construction project leakage risk level analysis method as described in any one of claims 1 to 7 are implemented.

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