A construction engineering leakage risk level analysis method, system and medium

Abstract

The present application provides a method, system, and medium for analyzing the leakage risk level of a construction project. The method comprises: generating a construction distribution information portrait based on detailed building feature information and extracting leakage prevention node distribution information; then classifying and aggregating the data according to the information queue table to obtain category attribute data of each category of leakage prevention nodes; processing the data to obtain leakage prevention implementation effectiveness index; then combining the visual evaluation data of leakage degree and the historical actual inspection coefficient to obtain leakage risk assessment correction data and leakage risk level; then combining the category node leakage weight index aggregation processing to obtain the building area leakage risk level aggregation value; thereby, processing the information data of the category leakage prevention nodes of the building area to obtain the node leakage risk assessment result and the corresponding leakage risk level; and then aggregating the leakage risk level values of all building leakage prevention nodes to achieve the identification of building leakage risk nodes and the assessment and analysis of risk status.

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 project. 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 the digital and precise identification and evaluation of leakage risks based on the quality information of construction projects. As a result, there is a lack of technology for accurate leakage identification and risk status assessment of leakage risks in construction projects.

[0003] In response to 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 building leakage prevention nodes to realize the identification of building leakage risk nodes and the assessment and analysis of risk status.

[0005] The present application also provides a method for analyzing the leakage risk level of a construction project, comprising the following steps:

[0006] Obtain detailed building feature information for a preset construction project area, including building material feature information, construction process feature information, and building function distribution information;

[0007] Inputting the building detailed feature information into a preset building information layout depiction 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 to obtain leakage prevention node category attribute information of each category of leakage prevention nodes;

[0008] 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;

[0009] Visual identification of node leakage of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage, and combined with the extracted historical leakage risk 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;

[0010] Processing the category node leakage risk assessment correction data of each category of 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 of leakage prevention node;

[0011] 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. According to the leakage risk level of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index, aggregation processing is performed to obtain the aggregated value of the building area leakage risk level of the preset construction project area.

[0012] Optionally, in the construction project leakage risk level analysis method described in the embodiment of the present application, 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, includes:

[0013] 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,

[0014] The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information;

[0015] The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof filling overlap information, pipeline hanging hole layout information and door and window sealing information;

[0016] 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.

[0017] Optionally, in the construction project leakage risk level analysis method 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. The leakage prevention node distribution information is classified and summarized using a preset construction point information queue table to obtain leakage prevention node category attribute information of each category of leakage prevention nodes, including:

[0018] 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 to generate a building construction distribution information portrait of the preset building project area;

[0019] Extracting leakage prevention node distribution information of a preset construction project area based on the construction distribution information portrait, including node location distribution information of each leakage prevention node, waterproofing and plugging process information, sealing and filling material information, water immersion frequency information, and leakage prevention demand information;

[0020] 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 preset construction point information queue table is used to classify and summarize them to obtain the leakage prevention node category attribute information corresponding to each category of leakage prevention node.

[0021] Optionally, in the construction project leakage risk level analysis method described in an embodiment of the present application, extracting corresponding leakage prevention node category attribute data based on the leakage prevention node category attribute information, and processing to obtain the leakage prevention construction evaluation index and the leakage prevention implementation effectiveness index of each category of leakage prevention node, includes:

[0022] Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, including the node location anti-leakage level, water immersion frequency level, waterproofing and plugging construction standard data, and sealing and filling material standard data;

[0023] The standard data for waterproofing and leak-proofing construction include grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data;

[0024] Processing the grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data of each type of leak-proof node to obtain a leak-proof construction evaluation index;

[0025] 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.

[0026] Optionally, in the construction engineering leakage risk level analysis method described in the embodiment of the present application, the visual identification of the node leakage degree of each category of leakage prevention node is performed to obtain 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 node and the leakage prevention implementation effectiveness index, the obtained category node leakage risk assessment correction data is obtained, including:

[0027] According to the preset building node leakage visual recognition model, the node leakage degree of each category of leakage prevention nodes is visually identified, and the visual evaluation data of the node leakage degree of each category is obtained;

[0028] Extract the historical leakage risk inspection average coefficient of each category of leakage prevention nodes based on the preset building leakage information monitoring database;

[0029] According to the leakage prevention implementation effectiveness index of each category of leakage prevention node, combined with the corresponding category node leakage visual evaluation data and the category node historical leakage risk inspection average coefficient, the category node leakage risk assessment correction data is obtained;

[0030] The calculation formula for the correction data of the leakage risk assessment of the category node is:

[0031] ;

[0032] in, Correcting data for category node leakage risk assessment, To prevent leakage, implement 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.

[0033] Optionally, in the construction engineering leakage risk level analysis method described in an embodiment of the present application, the processing of the category node leakage risk assessment correction data of each category of 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 of leakage prevention node includes:

[0034] Processing the corrected data of the leakage risk assessment of the category nodes of each category of leakage prevention nodes and the corrected data of the leakage risk assessment 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 node;

[0035] The calculation formula of the category node leakage weight index is:

[0036] ;

[0037] 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 anti-leakage node, n is the number of categories of all categories of anti-leakage nodes, 、 The preset characteristic coefficient of the anti-leakage node of the i-th category.

[0038] Optionally, in the construction project leakage risk level analysis method described in an embodiment of the present application, the threshold comparison is performed based on 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 based on 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:

[0039] Performing a 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;

[0040] According to the threshold comparison results, the leakage risk level of each type of leakage prevention node is obtained;

[0041] Aggregation processing is performed based on 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 an aggregated value of the building area leakage risk level of the preset construction project area;

[0042] The aggregate calculation formula for the aggregate value of the leakage risk level of the building area is:

[0043] ;

[0044] in, is the aggregate value of leakage risk level in the building area, is the category node leakage weight index of the i-th category anti-leakage node, is the node position leakage prevention level of the i-th category leakage prevention node, is the leakage risk level of the i-th type of leakage prevention node, 、 The preset characteristic coefficient of the anti-leakage node of the i-th category.

[0045] In a second aspect, an embodiment of the present application provides a system for analyzing a leakage risk level of a construction project. The system includes: a memory and a processor. The memory includes a program for analyzing a leakage risk level of a construction project. When the program for analyzing a leakage risk level of a construction project is executed by the processor, the following steps are implemented:

[0046] Obtain detailed building feature information for a preset construction project area, including building material feature information, construction process feature information, and building function distribution information;

[0047] Inputting the building detailed feature information into a preset building information layout depiction 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 to obtain leakage prevention node category attribute information of each category of leakage prevention nodes;

[0048] 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;

[0049] Visual identification of node leakage of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage, and combined with the extracted historical leakage risk 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;

[0050] Processing the category node leakage risk assessment correction data of each category of 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 of leakage prevention node;

[0051] 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. According to the leakage risk level of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index, aggregation processing is performed to obtain the aggregated value of the building area leakage risk level of the preset construction project area.

[0052] Optionally, in the construction project leakage risk level analysis system described in the embodiment of the present application, 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, includes:

[0053] 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,

[0054] The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information;

[0055] The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof filling overlap information, pipeline hanging hole layout information and door and window sealing information;

[0056] 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.

[0057] In a third aspect, an embodiment of the present application further 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.

[0058] 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 based on 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 it to obtain the leakage prevention implementation effectiveness index, and then combines the visual evaluation data of the leakage degree of the category node and the average coefficient of the historical leakage risk of the category node to obtain the category node leakage risk assessment correction data, and then compares and corrects it with all category leakage prevention nodes to obtain the category node leakage weight index, and then aggregates it with 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 node of the building area is 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 realize the identification of building leakage risk nodes and the assessment and analysis of risk status.

[0059] Other features and advantages of the present application will be described in the following description, and in part will become apparent from the description, or understood by practicing the embodiments of the present application. The objectives and other advantages of the present application can be achieved and obtained through the structures particularly pointed out in the written description and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. 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 relevant drawings can be obtained based on these drawings without creative work.

[0061] Figure 1 A flow chart of a construction engineering leakage risk level analysis method provided in an embodiment of the present application;

[0062] Figure 2A flowchart of obtaining the 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;

[0063] 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 and a leakage prevention implementation effectiveness index for each type of leakage prevention node;

[0064] 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

[0065] 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 generally 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 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 fall within the scope of protection of the present application.

[0066] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or 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 should not be understood as indicating or implying relative importance.

[0067] Please refer to Figure 1 , Figure 1 This is a flow chart of a method for analyzing the risk level of leakage in a construction project in some embodiments of the present application. The method is used in a terminal device, such as a computer or mobile phone terminal. The method includes the following steps:

[0068] S11. 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;

[0069] S12, inputting the building detailed feature information into a preset building information layout depiction 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 using a preset construction point information queue table to obtain leakage prevention node category attribute information of each category of leakage prevention nodes;

[0070] S13, 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 the leakage prevention implementation effectiveness index of each category of leakage prevention node;

[0071] S14, performing visual identification of node leakage for each category of leakage prevention nodes to obtain visual evaluation data of category node leakage, and processing the extracted historical leakage risk average coefficient of each category of leakage prevention nodes and the leakage prevention implementation effectiveness index to obtain revised category node leakage risk assessment data;

[0072] 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;

[0073] 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.

[0074] 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 data 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. The weight index of the category node is then combined to aggregate all nodes to obtain the leakage risk level value in the entire construction 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 feature information of the building in the preset construction project area is obtained. The detailed information includes the building's 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, and water drainage in the building area. The anti-leakage node distribution information is then 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 the distributed anti-leakage nodes 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, technology, 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. At the same time, the average coefficient of the historical leakage risk inspection of the category nodes of each category of leakage prevention nodes is extracted from the database for combined calculation to obtain the leakage risk evaluation index of the category node. The estimated correction data is used, 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 to obtain the evaluation correction data and the corresponding leakage risk level, so as to realize 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 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 category node leakage risk assessment correction data of each category of leakage prevention node is processed with all categories of leakage prevention nodes.Obtain the leakage weight index of each category of leakage prevention node, and then perform an aggregate calculation based on the weight index combined with the leakage risk level of the corresponding category of leakage prevention node to obtain the aggregate value of the building area leakage risk level of all leakage risk nodes in the preset construction project area, that is, the full node leakage risk assessment level value of the construction project area, to achieve a graded assessment of the leakage situation in the construction project area.

[0075] According to an embodiment of the present invention, the acquisition 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, is specifically as follows:

[0076] 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,

[0077] The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information;

[0078] The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof filling overlap information, pipeline hanging hole layout information and door and window sealing information;

[0079] 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.

[0080] Among them, in order to accurately identify and evaluate the leakage risk status of the preset construction project area, it is necessary to find 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 building materials, construction technology and building function distribution information, among which the building material characteristic information includes pipe The information includes the laying of materials, the use of sand and mud, the use of waterproof coatings, the use of sealing materials and fillers; the construction process characteristic information includes the overlap and routing of layer structures, the pouring of mortar concrete surfaces, the laying of waterproof interfaces and waterproof surfaces, the overlap of leak-proof caulking, the routing and layout of pipeline hanging holes, and the installation and sealing of doors and windows; the building function distribution information 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.

[0081] Please refer to Figure 2 , Figure 2This is a flowchart of obtaining the anti-leakage node category attribute information of each category of anti-leakage node in a method for analyzing the leakage risk level of a construction 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. The anti-leakage node distribution information is classified and summarized using a preset construction point information queue table to obtain the anti-leakage node category attribute information of each category of anti-leakage node, specifically:

[0082] 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 to generate a building construction distribution information portrait of the preset building project area;

[0083] S22, extracting leakage prevention node distribution information of a preset construction project area based on the construction distribution information portrait, including node location distribution information of each leakage prevention node, waterproofing and plugging process information, sealing and filling material information, water immersion frequency information, and leakage prevention demand information;

[0084] S23, classify and summarize the node position distribution information, waterproofing and 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.

[0085] Among them, after obtaining the detailed feature information in the construction project area, in order to describe the distribution of construction in the construction project area in an information-based manner, a preset building information layout description model is used to process the building detailed feature information to generate a construction distribution information portrait. The distribution information portrait 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 calibration 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 immersion, and the node In order to further evaluate the leakage risk of each leakage prevention node obtained, 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 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 to facilitate further leakage risk assessment and analysis.

[0086] Please refer to Figure 3 , Figure 2 This is a flow chart of obtaining a leakage prevention construction evaluation index and a leakage prevention implementation effectiveness index for each category of leakage prevention node in a construction project leakage risk level analysis method in some embodiments of the present application. According to an embodiment of the present invention, the corresponding leakage prevention node category attribute data is extracted based on the leakage prevention node category attribute information, and the leakage prevention construction evaluation index and leakage prevention implementation effectiveness index for each category of leakage prevention node are obtained through processing, specifically:

[0087] S31, extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, including the node location anti-leakage level, water immersion frequency level, waterproofing and plugging construction standard data, and sealing and filling material standard data;

[0088] S32, the standard data for waterproofing and leak-proofing construction includes grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data;

[0089] S33, processing the grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data of each type of leak-proof node to obtain a leak-proof construction evaluation index;

[0090] S34. Processing is performed based on the leakage prevention construction evaluation index in combination with the standard data of sealing and filling materials, 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.

[0091] 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 waterproofing and plugging construction standard, and the data of the sealing and filling material standard. The waterproofing and plugging construction standard data includes the grouting density of the mortar concrete soil, the grouting viscosity, the fullness of the filling, and the coating thickness data. Then, according to the construction standard data, calculation and processing are performed to obtain the evaluation index of the node leakage-proof construction effect. Then, according to the leakage-proof construction evaluation index combined with the sealing and filling material standard data, the node position leakage level, and the water immersion frequency level, the calculation formula of the preset leakage-proof effect verification model is used to calculate and obtain the corresponding leakage-proof implementation effectiveness index of each category of leakage-proof nodes, 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:

[0092] ;

[0093] in, It is the leak-proof construction evaluation index. 、 、 、 They are respectively the grouting density data, grouting viscosity data, filling fullness data, and coating thickness data. 、 、 、 is the preset characteristic coefficient;

[0094] The calculation formula for the leakage prevention implementation effectiveness index is:

[0095] ;

[0096] in, To prevent leakage, implement the effectiveness index. It is the leak-proof construction evaluation index. Standard data for sealing and filling materials, is the immersion frequency level, is the leak-proof level of the node position, 、 、 、 、 It is a preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0097] Please refer to Figure 4 , Figure 4 This is a flowchart of obtaining revised data for category node leakage risk assessments in a construction project leakage risk level analysis method in some embodiments of the present application. According to an embodiment of the present invention, the visual identification of node leakage for each category of leakage prevention nodes is performed to obtain visual evaluation data for the category node leakage degree, and the extracted historical node leakage risk average coefficient of each category of leakage prevention nodes and the leakage prevention implementation effectiveness index are combined to obtain revised data for the category node leakage risk assessment, specifically:

[0098] 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;

[0099] S42, extracting the historical leakage risk inspection average coefficient of each category of leakage prevention nodes according to the preset building leakage information monitoring database;

[0100] 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;

[0101] The calculation formula for the correction data of the leakage risk assessment of the category node is:

[0102] ;

[0103] in, Correcting data for category node leakage risk assessment, To prevent leakage, implement 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 a preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0104] 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 is also added, as well as the historical leakage risk inspection average coefficient of each category of leakage prevention nodes extracted from the preset building leakage information monitoring database. The preset building node leakage visual recognition model is a leakage assessment model that performs visual recognition of leakage on the appearance of building nodes, and an evaluation of the node leakage degree can be obtained. The historical leakage risk 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 results with the historical leakage risk inspection average coefficient and 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.

[0105] 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:

[0106] Processing the corrected data of the leakage risk assessment of the category nodes of each category of leakage prevention nodes and the corrected data of the leakage risk assessment 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 node;

[0107] The calculation formula of the category node leakage weight index is:

[0108] ;

[0109] 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 anti-leakage node, n is the number of categories of all categories of anti-leakage 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).

[0110] 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 weighted influence of the leakage risk of various types of leakage-proof nodes on the entire construction project area, the weight calculation processing is performed based on the leakage risk assessment correction data of the category nodes of each category of leakage-proof nodes and all categories of leakage-proof nodes to obtain the category node leakage weight index of each category of leakage-proof nodes.

[0111] 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 node. The leakage risk level of all category leakage prevention nodes is aggregated in combination 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, which is specifically:

[0112] Performing a 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;

[0113] According to the threshold comparison results, the leakage risk level of each type of leakage prevention node is obtained;

[0114] Aggregation processing is performed based on 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 an aggregated value of the building area leakage risk level of the preset construction project area;

[0115] The aggregate calculation formula for the aggregate value of the leakage risk level of the building area is:

[0116] ;

[0117] in, is the aggregate value of leakage risk level in the building area, is the category node leakage weight index of the i-th category anti-leakage node, is the node position leakage prevention level of the i-th category leakage prevention 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 leakage prevention node (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0118] 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 levels 1 to 5, with level 5 being the highest. The threshold ranges corresponding to the 5 levels are (0, 0.18), [0.18, 0.47), [0.47, 0.62), [0.62, 0.83), and [0.83, 1.0], respectively. The threshold comparison result of a certain category node X is 0.77, so the corresponding risk level threshold range of X is level 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 project area, an aggregation calculation is performed based on 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 to obtain the building area leakage risk level aggregation value of the preset construction project area, that is, the leakage risk assessment level value of all nodes in the construction project area, thereby realizing the assessment of the leakage risk of each category of nodes and the entire building in the construction project area.

[0119] A second aspect of the present invention further discloses a construction project leakage risk level analysis system, comprising a memory and a processor. The memory includes a construction project leakage risk level analysis method program. When the construction project leakage risk level analysis method program is executed by the processor, the following steps are implemented:

[0120] Obtain detailed building feature information for a preset construction project area, including building material feature information, construction process feature information, and building function distribution information;

[0121] Inputting the building detailed feature information into a preset building information layout depiction 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 to obtain leakage prevention node category attribute information of each category of leakage prevention nodes;

[0122] 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;

[0123] Visual identification of node leakage of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage, and combined with the extracted historical leakage risk 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;

[0124] Processing the category node leakage risk assessment correction data of each category of 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 of leakage prevention node;

[0125] 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. According to the leakage risk level of all categories of leakage prevention nodes combined with the corresponding category node leakage weight index, aggregation processing is performed to obtain the aggregated value of the building area leakage risk level of the preset construction project area.

[0126] 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 data 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. The weight index of the category node is then combined to aggregate all nodes to obtain the leakage risk level value in the entire construction 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 feature information of the building in the preset construction project area is obtained. The detailed information includes the building's 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, and water drainage in the building area. The anti-leakage node distribution information is then 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 the distributed anti-leakage nodes 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, technology, 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. At the same time, the average coefficient of the historical leakage risk inspection of the category nodes of each category of leakage prevention nodes is extracted from the database for combined calculation to obtain the leakage risk evaluation index of the category node. The estimated correction data is used, 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 to obtain the evaluation correction data and the corresponding leakage risk level, so as to realize 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 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 category node leakage risk assessment correction data of each category of leakage prevention node is processed with all categories of leakage prevention nodes.Obtain the leakage weight index of each category of leakage prevention node, and then perform an aggregate calculation based on the weight index combined with the leakage risk level of the corresponding category of leakage prevention node to obtain the aggregate value of the building area leakage risk level of all leakage risk nodes in the preset construction project area, that is, the full node leakage risk assessment level value of the construction project area, to achieve a graded assessment of the leakage situation in the construction project area.

[0127] According to an embodiment of the present invention, the acquisition 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, is specifically as follows:

[0128] 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,

[0129] The building material characteristic information includes laying pipe information, sand and mud information, waterproof coating information, sealing edge material information and caulking agent information;

[0130] The construction process characteristic information includes layer structure information, mortar concrete surface pouring information, waterproof edge laying information, leak-proof filling overlap information, pipeline hanging hole layout information and door and window sealing information;

[0131] 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.

[0132] Among them, in order to accurately identify and evaluate the leakage risk status of the preset construction project area, it is necessary to find 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 building materials, construction technology and building function distribution information, among which the building material characteristic information includes pipe The information includes the laying of materials, the use of sand and mud, the use of waterproof coatings, the use of sealing materials and fillers; the construction process characteristic information includes the overlap and routing of layer structures, the pouring of mortar concrete surfaces, the laying of waterproof interfaces and waterproof surfaces, the overlap of leak-proof caulking, the routing and layout of pipeline hanging holes, and the installation and sealing of doors and windows; the building function distribution information 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.

[0133] 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 leakage prevention node distribution information is extracted. The leakage prevention node distribution information is classified and summarized using a preset construction point information queue table to obtain leakage prevention node category attribute information of each category of leakage prevention nodes, specifically:

[0134] 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 to generate a building construction distribution information portrait of the preset building project area;

[0135] Extracting leakage prevention node distribution information of a preset construction project area based on the construction distribution information portrait, including node location distribution information of each leakage prevention node, waterproofing and plugging process information, sealing and filling material information, water immersion frequency information, and leakage prevention demand information;

[0136] 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 preset construction point information queue table is used to classify and summarize them to obtain the leakage prevention node category attribute information corresponding to each category of leakage prevention node.

[0137] Among them, after obtaining the detailed feature information in the construction project area, in order to describe the distribution of construction in the construction project area in an information-based manner, a preset building information layout description model is used to process the building detailed feature information to generate a construction distribution information portrait. The distribution information portrait 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 calibration 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 immersion, and the node In order to further evaluate the leakage risk of each leakage prevention node obtained, 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 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 to facilitate further leakage risk assessment and analysis.

[0138] According to an embodiment of the present invention, the corresponding leakage prevention node category attribute data is extracted based on the leakage prevention node category attribute information, and the leakage prevention construction evaluation index and leakage prevention implementation effectiveness index of each category of leakage prevention node are obtained through processing, specifically:

[0139] Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, including the node location anti-leakage level, water immersion frequency level, waterproofing and plugging construction standard data, and sealing and filling material standard data;

[0140] The standard data for waterproofing and leak-proofing construction include grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data;

[0141] Processing the grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data of each type of leak-proof node to obtain a leak-proof construction evaluation index;

[0142] 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.

[0143] 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 waterproofing and plugging construction standard, and the data of the sealing and filling material standard. The waterproofing and plugging construction standard data includes the grouting density of the mortar concrete soil, the grouting viscosity, the fullness of the filling, and the coating thickness data. Then, according to the construction standard data, calculation and processing are performed to obtain the evaluation index of the node leakage-proof construction effect. Then, according to the leakage-proof construction evaluation index combined with the sealing and filling material standard data, the node position leakage level, and the water immersion frequency level, the calculation formula of the preset leakage-proof effect verification model is used to calculate and obtain the corresponding leakage-proof implementation effectiveness index of each category of leakage-proof nodes, 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:

[0144] ;

[0145] in, It is the leak-proof construction evaluation index. 、 、 、 They are respectively the grouting density data, grouting viscosity data, filling fullness data, and coating thickness data. 、 、 、 is the preset characteristic coefficient;

[0146] The calculation formula for the leakage prevention implementation effectiveness index is:

[0147] ;

[0148] in, To prevent leakage, implement the effectiveness index. It is the leak-proof construction evaluation index. Standard data for sealing and filling materials, is the immersion frequency level, is the leakage-proof level of the node position, 、 、 、 、 It is a preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0149] According to an embodiment of the present invention, the node leakage degree visual identification of each category of leakage prevention nodes is performed to obtain 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 data is processed to obtain category node leakage risk assessment correction data, specifically:

[0150] According to the preset building node leakage visual recognition model, the node leakage degree of each category of leakage prevention nodes is visually identified, and the visual evaluation data of the node leakage degree of each category is obtained;

[0151] Extract the historical leakage risk inspection average coefficient of each category of leakage prevention nodes based on the preset building leakage information monitoring database;

[0152] According to the leakage prevention implementation effectiveness index of each category of leakage prevention node, combined with the corresponding category node leakage visual evaluation data and the category node historical leakage risk inspection average coefficient, the category node leakage risk assessment correction data is obtained;

[0153] The calculation formula for the correction data of the leakage risk assessment of the category node is:

[0154] ;

[0155] in, Correcting data for category node leakage risk assessment, To prevent leakage, implement 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 a preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0156] 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 is also added, as well as the historical leakage risk inspection average coefficient of each category of leakage prevention nodes extracted from the preset building leakage information monitoring database. The preset building node leakage visual recognition model is a leakage assessment model that performs visual recognition of leakage on the appearance of building nodes, and an evaluation of the node leakage degree can be obtained. The historical leakage risk 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 results with the historical leakage risk inspection average coefficient and 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.

[0157] 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:

[0158] Processing the corrected data of the leakage risk assessment of the category nodes of each category of leakage prevention nodes and the corrected data of the leakage risk assessment 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 node;

[0159] The calculation formula of the category node leakage weight index is:

[0160] ;

[0161] 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 anti-leakage node, n is the number of categories of all categories of anti-leakage nodes, 、 is the preset characteristic coefficient of the i-th category leakage prevention node (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0162] 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 weighted influence of the leakage risk of various types of leakage-proof nodes on the entire construction project area, the weight calculation processing is performed based on the leakage risk assessment correction data of the category nodes of each category of leakage-proof nodes and all categories of leakage-proof nodes to obtain the category node leakage weight index of each category of leakage-proof nodes.

[0163] 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 node. The leakage risk level of all category leakage prevention nodes is aggregated in combination 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, which is specifically:

[0164] Performing a 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;

[0165] According to the threshold comparison results, the leakage risk level of each type of leakage prevention node is obtained;

[0166] Aggregation processing is performed based on 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 an aggregated value of the building area leakage risk level of the preset construction project area;

[0167] The aggregate calculation formula for the aggregate value of the leakage risk level of the building area is:

[0168] ;

[0169] in, is the aggregate value of leakage risk level in the building area, is the category node leakage weight index of the i-th category anti-leakage node, is the node position leakage prevention level of the i-th category leakage prevention 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 leakage prevention node (the characteristic coefficient is obtained by querying the preset construction project monitoring information database).

[0170] 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 levels 1 to 5, with level 5 being the highest. The threshold ranges corresponding to the 5 levels are (0, 0.18), [0.18, 0.47), [0.47, 0.62), [0.62, 0.83), and [0.83, 1.0], respectively. The threshold comparison result of a certain category node X is 0.77, so the corresponding risk level threshold range of X is level 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 project area, an aggregation calculation is performed based on 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 to obtain the building area leakage risk level aggregation value of the preset construction project area, that is, the leakage risk assessment level value of all nodes in the construction project area, thereby realizing the assessment of the leakage risk of each category of nodes and the entire building in the construction project area.

[0171] 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.

[0172] The present invention discloses a method, system and medium for analyzing leakage risk levels of construction projects. The method generates a construction distribution information portrait based on detailed building feature information and extracts 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 based on an information queue table, extracts leakage prevention node category attribute data, processes the information to obtain a leakage prevention implementation effectiveness index, combines the category node leakage degree visual evaluation data and the category node historical leakage risk actual inspection coefficient to obtain category node leakage risk assessment correction data, compares and corrects the data with all category leakage prevention nodes to obtain category node leakage weight index, and aggregates the data with the leakage risk level of all category node leakage risk assessment correction data to obtain a building area leakage risk level aggregation value. The method then processes the information data of the category leakage prevention nodes of the building area to obtain a node leakage risk assessment result and a corresponding leakage risk level, and aggregates the leakage risk level values of all building leakage prevention nodes to obtain identification of building leakage risk nodes and assessment and analysis of risk conditions.

[0173] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, 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.

[0174] 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 across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0175] 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.

[0176] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware related to program instructions, and the aforementioned program may be stored in a readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0177] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as standalone products, they can also be stored on a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This software product, stored on a storage medium, includes instructions for enabling a computer device (such as a personal computer, server, or network device) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as removable 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 for a preset construction project area, including building material feature information, construction process feature information, and building function distribution information; Inputting the building detailed feature information into a preset building information layout depiction 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 to obtain leakage prevention node category attribute information of each category of leakage prevention nodes; 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 of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage, and combined with the extracted historical leakage risk 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 of 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 of leakage prevention node; Comparing the leakage risk assessment correction data of the category nodes with the corresponding preset category node leakage risk level thresholds to obtain the leakage risk level of the corresponding category anti-leakage nodes, and performing aggregation processing based on the leakage risk level of all category anti-leakage 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; The acquisition 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: 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 filling 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; 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. The leak prevention node distribution information is classified and summarized through a preset construction point information queue table to obtain leak prevention node category attribute information of each category of leak 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 to generate a building construction distribution information portrait of the preset building project area; Extracting leakage prevention node distribution information of a preset construction project area based on the construction distribution information portrait, including node location distribution information of each leakage prevention node, waterproofing and plugging process information, sealing and filling material information, water immersion frequency information, and leakage prevention demand information; According to the node location distribution information, waterproofing and 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 the preset construction point information queue table; 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 comprises: Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, including the node location anti-leakage level, water immersion frequency level, waterproofing and plugging construction standard data, and sealing and filling material standard data; The standard data for waterproofing and leak-proofing construction include grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data; Processing the grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data of each type of leak-proof node to obtain a leak-proof 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.

2. The construction engineering leakage risk level analysis method according to claim 1 is characterized in that: The node leakage degree visual identification of each category of leakage prevention nodes is performed to obtain 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 leakage prevention nodes is visually identified, and the visual evaluation data of the node leakage degree of each category is obtained; Extract the historical leakage risk inspection average coefficient of each category of leakage prevention nodes based on the preset building leakage information monitoring database; According to the leakage prevention implementation effectiveness index of each category of leakage prevention node, combined with the corresponding category node leakage visual evaluation data and the category node historical leakage risk inspection average coefficient, the category node leakage risk assessment correction data is obtained; The calculation formula for the correction data of the leakage risk assessment of the category node is: ； in, Correcting data for category node leakage risk assessment, To prevent leakage, implement 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.

3. The construction engineering leakage risk level analysis method according to claim 2 is 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 corrected data of the leakage risk assessment of the category nodes of each category of leakage prevention nodes and the corrected data of the leakage risk assessment 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 node; 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 anti-leakage node, n is the number of categories of all categories of anti-leakage nodes, 、 The preset characteristic coefficient of the anti-leakage node of the i-th category.

4. The construction engineering leakage risk level analysis method according to claim 3 is characterized in that: The correction data of the leakage risk assessment of the category nodes is compared with the corresponding preset category node leakage risk level threshold to obtain the leakage risk level of the corresponding category leakage prevention nodes, and the leakage risk level of all category leakage prevention nodes is aggregated in combination 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, including: Performing a 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 based on 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 an aggregated value of the building area leakage risk level 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 leakage risk level in the building area, is the category node leakage weight index of the i-th category anti-leakage node, is the node position leakage prevention level of the i-th category leakage prevention node, is the leakage risk level of the i-th type of leakage prevention node, 、 The preset characteristic coefficient of the anti-leakage node of the i-th category.

5. 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 for a preset construction project area, including building material feature information, construction process feature information, and building function distribution information; Inputting the building detailed feature information into a preset building information layout depiction 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 to obtain leakage prevention node category attribute information of each category of leakage prevention nodes; 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 of each category of leakage prevention nodes is performed to obtain visual evaluation data of category node leakage, and combined with the extracted historical leakage risk 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 of 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 of leakage prevention node; Comparing the leakage risk assessment correction data of the category nodes with the corresponding preset category node leakage risk level thresholds to obtain the leakage risk level of the corresponding category anti-leakage nodes, and performing aggregation processing based on the leakage risk level of all category anti-leakage 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; The acquisition 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: 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 filling 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; 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. The leak prevention node distribution information is classified and summarized through a preset construction point information queue table to obtain leak prevention node category attribute information of each category of leak 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 to generate a building construction distribution information portrait of the preset building project area; Extracting leakage prevention node distribution information of a preset construction project area based on the construction distribution information portrait, including node location distribution information of each leakage prevention node, waterproofing and plugging process information, sealing and filling material information, water immersion frequency information, and leakage prevention demand information; According to the node location distribution information, waterproofing and 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 the preset construction point information queue table; 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 comprises: Extracting corresponding anti-leakage node category attribute data according to the anti-leakage node category attribute information, including the node location anti-leakage level, water immersion frequency level, waterproofing and plugging construction standard data, and sealing and filling material standard data; The standard data for waterproofing and leak-proofing construction include grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data; Processing the grouting density data, grouting viscosity data, caulking fullness data, and coating thickness data of each type of leak-proof node to obtain a leak-proof 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.

6. 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 4 are implemented.

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