Fabricated fire engineering management optimization method based on digital platform application program

Abstract

The invention discloses an assembly type fire protection project management optimization method based on a digital platform application program, and relates to the technical field of project management, and the method comprises the steps: connecting a digital platform, and obtaining the constructed first node project information and the to-be-constructed second node project information of a target assembly type fire protection project; activating the BIM system, and constructing a construction scene model of the second node based on the first node information; activating construction influence factors of the fabricated fire-fighting engineering, wherein the construction influence factors comprise the influence of the constructed engineering, the to-be-constructed engineering and the geology; performing risk prediction in combination with the construction influence factor and the second node information, and generating a construction risk report; and optimizing the engineering information of the second node based on the report, and finally executing management and control and optimization adjustment of the to-be-constructed engineering. Therefore, the technical effect of improving the management efficiency and the management fineness is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering management, and in particular to an assembly-type fire protection engineering management optimization method based on a digital platform application program. Background Art

[0002] In modern construction projects, prefabricated fire protection projects have gradually become the first choice in engineering projects due to their advantages such as fast construction speed and controllable quality. However, the existing management methods of prefabricated fire protection projects still have many limitations, especially in terms of construction progress, risk prediction, and project coordination. There are technical problems such as low information integration, high prediction difficulty, and low management efficiency. Summary of the invention

[0003] The present invention provides an optimization method for prefabricated fire protection engineering management based on a digital platform application to solve the technical problems of low information integration, great prediction difficulty, and low management efficiency in the prior art, and achieve the technical effect of improving management efficiency and management precision.

[0004] The present invention provides a method for optimizing the management of assembled fire protection engineering based on a digital platform application, comprising: Connect to the digital platform application, obtain the first node prefabricated fire protection engineering information and the second node prefabricated fire protection engineering information, wherein the first node prefabricated fire protection engineering information is the constructed engineering information of the target prefabricated fire protection engineering, and the second node prefabricated fire protection engineering information is the to-be-constructed engineering information of the target prefabricated fire protection engineering; activate the BIM system, and build a second node construction scenario model based on the first node prefabricated fire protection engineering information; activate the prefabricated fire protection engineering construction influencing factors, wherein the prefabricated fire protection engineering construction influencing factors include the passive impact of the constructed project, the impact of the to-be-constructed project and the passive impact of the construction geology; based on the prefabricated fire protection engineering construction influencing factors, combine the second node prefabricated fire protection engineering information and the second node construction scenario model to perform construction risk prediction, and obtain a second node construction risk prediction report; optimize the second node prefabricated fire protection engineering information based on the second node construction risk prediction report, and obtain the second node optimized prefabricated fire protection engineering information; based on the second node optimized prefabricated fire protection engineering information, execute the to-be-constructed engineering management and control of the target prefabricated fire protection engineering. The method for optimizing the management of prefabricated fire protection engineering based on a digital platform application disclosed in the present invention solves the technical problems of low information integration, great prediction difficulty, and low management efficiency, and achieves the technical effect of improving management efficiency and management precision. BRIEF DESCRIPTION OF THE DRAWINGS

[0005] Figure 1 It is a flow chart of the method for optimizing the management of assembled fire protection engineering based on a digital platform application program of the present invention; Figure 2 It is a flow chart of the method for optimizing the management of prefabricated fire protection engineering based on a digital platform application program of the present invention. DETAILED DESCRIPTION

[0006] The technical solution provided in the embodiments of the present invention is to solve the technical problems of low information integration, great prediction difficulty and low management efficiency in the prior art. The overall idea adopted is as follows: First, connect the digital platform application to obtain two node information of the target prefabricated fire protection project: the first node is the information of the constructed project, and the second node is the information of the project to be constructed. This information contains detailed data on project progress, material use, equipment installation, etc. Next, activate the BIM (Building Information Model) system, and build a construction scenario model of the second node based on the information of the constructed project of the first node. This model will simulate the construction environment of the second node, including details such as the structure of the building and equipment layout. Then, activate the influencing factors of the construction of the prefabricated fire protection project, which include the passive impact of the constructed project (such as the obstruction of existing facilities to subsequent construction), the impact of the project to be constructed (such as material transportation, equipment installation difficulty), and the passive impact of construction geology (such as terrain changes). Based on these influencing factors and combined with the construction scenario model of the second node, the construction risk prediction is carried out to generate a detailed construction risk prediction report. The report may include potential risks such as construction delays, quality problems and safety hazards. According to the risk prediction report, the information of the prefabricated fire protection project of the second node is optimized. This optimization may involve adjusting the construction plan, improving the engineering design, optimizing resource allocation, etc. Finally, based on the optimized second-node project information, project management and control of the part to be constructed is implemented to ensure smooth construction, reduce risks, and improve project quality and efficiency.

[0007] The above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods of the specification to better understand the above technical solution. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments used only to explain the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, it should be noted that, for the convenience of description, only the parts related to the present invention are shown in the drawings, rather than all of them.

[0008] Example

[0009] Figure 1 The figure is a flow chart of the method for optimizing the management of assembled fire protection engineering based on a digital platform application program of the present invention, wherein the method comprises: Connect to the digital platform application to obtain the first-node prefabricated fire protection engineering information and the second-node prefabricated fire protection engineering information, wherein the first-node prefabricated fire protection engineering information is the constructed project information of the target prefabricated fire protection engineering, and the second-node prefabricated fire protection engineering information is the to-be-constructed project information of the target prefabricated fire protection engineering.

[0010] Specifically, first, a connection with the digital platform application is established through the interactive terminal, involving API interfaces or data transmission protocols to communicate with the digital platform, and identity authentication and authority identification. Then, the first-node prefabricated fire protection engineering information is obtained. The first-node prefabricated fire protection engineering information refers to the part of the target prefabricated fire protection engineering that has been completed. For example, installed fire protection facilities, safety systems that have been inspected, etc. The first-node prefabricated fire protection engineering information includes relevant project progress reports, construction logs, equipment acceptance reports and other content. Exemplary, it includes equipment installation status, pipeline layout, installation information of key components such as fire pumps, etc.

[0011] Specifically, the second node prefabricated fire protection engineering information is obtained. The second node prefabricated fire protection engineering information refers to the construction part that has not yet started or is being planned. For example, the equipment to be installed in the next stage, the pipeline connection to be completed, etc. The first node prefabricated fire protection engineering information includes relevant construction plans, construction schedules, blueprints of the area to be constructed, and equipment lists. Exemplarily, it includes the time nodes corresponding to the planned construction nodes, the required materials and equipment, and the arrangement of construction personnel.

[0012] Specifically, obtaining the first node prefabricated fire engineering information and the second node prefabricated fire engineering information also includes data cleaning and standardization, thereby improving the information quality of the acquired information. The prefabricated fire engineering information obtained in the above manner can provide more accurate basic data for the construction management of the project, thereby improving the progress management and quality control of the project. At the same time, using the digital platform application as the acquisition path improves the reliability and convenience of the data source.

[0013] Activate the BIM system and build a second node construction scene model based on the first node prefabricated fire protection engineering information.

[0014] In some embodiments, activating the BIM system and constructing a second node construction scenario model based on the first node prefabricated fire protection engineering information includes: Based on the BIM system, a first-node prefabricated fire protection engineering model is established according to the first-node prefabricated fire protection engineering information; based on the second-node prefabricated fire protection engineering information, construction area information is collected to obtain the second-node construction area information; based on the second-node prefabricated fire protection engineering information, construction environment prediction is performed to obtain the second-node construction environment information; based on the second-node construction area information and the second-node construction environment information, the first-node prefabricated fire protection engineering model is optimized to generate the second-node construction scene model.

[0015] Specifically, firstly, based on the BIM system, according to the first node prefabricated fire engineering information, the first node prefabricated fire engineering model is established. The model content includes the installed fire fighting equipment (such as water pipes, sprinkler heads, fire pumps, control panels, etc.), as well as the relevant building and space layout information.

[0016] Then, based on the second node prefabricated fire engineering information, data of the area to be constructed is collected and output as the second node construction area information. This includes information such as the spatial layout, size, and equipment placement of the construction area. Exemplarily, the method for collecting the second node construction area information includes real-scene collection based on scanning, sensors, and drone mapping, information extraction based on the first node prefabricated fire engineering model, or a hybrid collection combining the two.

[0017] Next, based on the second node prefabricated fire protection engineering information, by analyzing the environmental factors that affect the construction process, such as weather, temperature and humidity, and air quality, various risks and obstacles in the construction are simulated to obtain the second node construction environment information. Among them, the environmental factors that affect the construction include the number of construction personnel, the frequency of equipment use, the ventilation conditions of the site, etc. For example, if the second node prefabricated fire protection engineering information indicates that the second node construction area is a confined space, it is necessary to analyze the ventilation level of the site.

[0018] Finally, based on the construction area information and construction environment information of the second node, the first node prefabricated fire engineering model is optimized to generate the second node construction scene model. The model content includes the location of the equipment to be installed, the path of the fire pipe, the available space, the work area of ​​the personnel, etc. Exemplarily, the optimization steps include adjusting the equipment installation position in the model to adapt to the actual changes in the construction site, predicting potential construction obstacles (such as insufficient space, channel blockage, etc.) and reflecting them in the model in advance, etc., to ensure that the scene environment in the scene model is consistent with the actual situation and reduce sudden problems in subsequent construction.

[0019] The second-node construction scenario model helps the construction team understand and predict possible problems that may arise during the construction process, and provides accurate visualization to ensure that the scenario model is consistent with the actual construction progress.

[0020] The above method steps use the BIM (Building Information Modeling) system to combine the prefabricated fire protection engineering information, construction area information and construction environment information to generate an accurate construction scene model, which provides a good spatial scene foundation for subsequent risk prediction and facilitates subsequent analysis and optimization.

[0021] Activate the influencing factors of the construction of prefabricated fire protection projects, wherein the influencing factors of the construction of prefabricated fire protection projects include the passive impact of the constructed projects, the impact of the projects to be constructed and the passive impact of the construction geology.

[0022] Specifically, the influencing factors of the construction of prefabricated fire protection projects include multiple influencing factors, which define the multi-dimensional factors that affect the construction of prefabricated fire protection projects, involving the passive impact of constructed projects, the impact of projects to be constructed, and the passive impact of construction geology.

[0023] Specifically, the passive impact of the construction project refers to the fact that when the construction project is in progress, the fire protection project that has been constructed may be affected by vibration, material splashing, accidental collision of equipment, structural stress changes, etc.

[0024] The impact of the construction project refers to the compatibility of the newly installed equipment and pipelines with the current environment, as well as the mutual impact with other equipment systems, which need to be considered during the construction of the construction project. The passive impact of construction geology refers to the impact of excavation, equipment installation, foundation treatment and other operations during construction on the construction geological structure. For example, it may cause foundation settlement, damage to surrounding building structures and other problems.

[0025] Specifically, activating the construction influencing factors of prefabricated fire protection engineering refers to selecting the corresponding influencing factor measurements that need to be monitored and collected according to the node characteristics of the project to be constructed. Among them, the activated and acquired construction influencing factors of prefabricated fire protection engineering are extracted from a pre-established construction influencing factor library, which is a collection of relevant influencing factors of constructed projects, projects to be constructed, and construction geology determined by analyzing and collecting sensors, construction equipment feedback, and worker operation data at historical construction sites.

[0026] Exemplarily, the factors affecting the construction of prefabricated fire protection projects include: vibration impact factor, noise impact factor, stress change factor, temperature impact factor, humidity impact factor, foundation settlement factor, air quality factor (such as dust particle concentration and harmful gas concentration at the construction site), electromagnetic interference factor, etc.

[0027] By activating the influencing factors of prefabricated fire protection engineering construction, it is possible to comprehensively monitor and manage various influences in the construction process, providing a data basis for subsequent predictive analysis.

[0028] Based on the construction influencing factors of the prefabricated fire protection engineering, combined with the second-node prefabricated fire protection engineering information and the second-node construction scenario model, construction risk prediction is performed to obtain a second-node construction risk prediction report.

[0029] In some embodiments, Figure 2 As shown, based on the construction influencing factor of the prefabricated fire protection engineering, the construction risk prediction is performed in combination with the second node prefabricated fire protection engineering information and the second node construction scenario model to obtain a second node construction risk prediction report, including: Based on the information of the prefabricated fire protection project at the second node, a construction simulation is performed according to the construction scenario model of the second node to obtain a construction simulation data set of the second node; based on the construction influencing factor of the prefabricated fire protection project, a construction impact prediction is performed according to the construction simulation data set of the second node to obtain passive impact prediction results of constructed projects, impact prediction results of projects to be constructed and passive impact prediction results of construction geology; based on the passive impact prediction results of constructed projects, risk prediction is performed to obtain risk prediction results of constructed projects; based on the impact prediction results of projects to be constructed, risk prediction is performed to obtain risk prediction results of projects to be constructed; based on the passive impact prediction results of construction projects, risk prediction is performed to obtain risk prediction results of projects to be constructed; based on the passive impact prediction results of construction geology, risk prediction is performed to obtain construction geology risk prediction results; the risk prediction results of constructed projects, the risk prediction results of projects to be constructed and the construction geology risk prediction results are sorted out to generate a construction risk prediction report for the second node.

[0030] The construction risk prediction based on the construction influencing factors of prefabricated fire protection engineering combined with the second node prefabricated fire protection engineering information and construction scene model can effectively help identify potential risks and formulate countermeasures. Specifically, first, the second node prefabricated fire protection engineering information and the second node construction scene model are used as input data, and the construction scene is digitally restored and simulated based on the BIM system to generate a detailed second node construction simulation data set, covering possible construction scenarios and construction steps. Then, the influencing factors related to the second node construction are activated from the construction influencing factor library to predict the passive impact of the constructed project (analyze the potential impact of the pending construction operation on the completed fire protection equipment, pipelines and other facilities, especially the closely related parts in the same structure), the impact prediction of the pending construction project (evaluate the impact of the pending construction tasks, such as equipment installation, pipeline laying, etc. on the overall project, including time, resources and safety considerations), and the passive impact prediction of construction geology. Combined with the geological conditions of the construction environment, such as the foundation soil layer and groundwater level, the possible geological changes in the construction process and their impact on the project are predicted.

[0031] Specifically, based on the passive impact prediction results of the constructed projects, the possible safety hazards or construction obstacles are evaluated, the vulnerability of key equipment or pipelines is determined, and the risk prediction results of the constructed projects are generated, which include risk categories, such as equipment damage, loose fire pipes, system failures, etc.; risk levels, which characterize the severity of possible impacts (such as high, medium, and low).

[0032] Specifically, based on the impact prediction results of the projects to be constructed, the success rate of the construction tasks is evaluated, potential project delays, cost overruns or quality problems are determined, and risk prediction results of the projects to be constructed are generated, including: construction schedule risks, such as delays in the installation of key equipment and material supply problems; quality risks, such as the possibility of quality deviations of the projects to be constructed; personnel safety risks, such as toxic and harmful gases and possible personal injuries.

[0033] Specifically, based on the prediction results of passive impacts of construction geology, the impact of possible changes in geological conditions during the construction process on the project is analyzed to generate construction geological risk prediction results, including: geological risks, such as unstable foundation, geological subsidence, landslides and other potential problems; changes in the construction environment, such as interference with construction caused by rising water levels or changes in underground soil structure.

[0034] Furthermore, the risk prediction results of the constructed projects, the risk prediction results of the projects to be constructed, and the construction geological risk prediction results are sorted out and integrated, and the correlation between various risks is analyzed to generate a detailed second-node construction risk prediction report. Exemplarily, the second-node construction risk prediction report includes a total risk assessment covering the overall risk analysis of the constructed projects, the projects to be constructed, and geological factors; sorting different categories of risks so as to give priority to controlling the risk level and priority ranking of high-risk factors during the construction process; and proposing measures to reduce or eliminate risks based on the prediction results, such as strengthening vibration monitoring, adjusting the construction sequence, or strengthening structural support.

[0035] In some implementations, based on the construction impact factor of the prefabricated fire protection engineering, a construction impact prediction is performed according to the second node construction simulation data set to obtain the passive impact prediction results of the constructed engineering, the impact prediction results of the engineering to be constructed, and the passive impact prediction results of the construction geology, including: Feature recognition is performed based on the second node construction simulation data set to obtain passive simulation data of constructed projects, simulation data of projects to be constructed and passive simulation data of construction geology; based on the construction influencing factors of the prefabricated fire protection project, an impact detection model of the prefabricated fire protection project is constructed, wherein the impact detection model of the prefabricated fire protection project includes a passive impact detection model of constructed projects, an impact detection model of projects to be constructed and a passive impact detection model of construction geology; the passive simulation data of the constructed projects are input into the passive impact detection model of the constructed projects to generate a passive impact prediction result of the constructed projects; based on the simulation data of the projects to be constructed and according to the impact detection model of the projects to be constructed, the impact prediction result of the projects to be constructed is generated; based on the passive simulation data of the construction geology and according to the passive impact detection model of the construction geology, the passive impact prediction result of the construction geology is generated.

[0036] Specifically, by analyzing various influencing factors in the construction scene, key construction features are identified. Among them, the passive simulation data of the constructed project includes vibration parameters, stress-strain parameters, construction noise, thermal impact, etc., which are used to measure the impact of the construction project on the constructed part. The simulation data of the project to be constructed includes parameters simulated in the construction process, such as material strength, equipment installation stress, construction sequence, etc. The construction geological passive simulation data is an indicator that reflects the geological environment response during the construction process, including foundation settlement, soil displacement, hydrological changes, etc.

[0037] Optionally, a special detection model can be established based on different construction influencing factors. Specifically, it includes a passive impact detection model for evaluating the impact of the pending construction tasks on the completed fire protection facilities or structures, especially in terms of vibration and stress changes; a pending construction project impact detection model for predicting the impact of the pending construction tasks on the project during execution, including analysis of construction progress, process interaction, etc.; and a construction geology passive impact detection model for evaluating changes in geological conditions during the construction process and predicting potential geological risks such as foundation subsidence or landslides.

[0038] Optionally, the prefabricated fire protection engineering impact detection model is an analysis model constructed by machine learning, decision tree, support vector machine, hierarchical analysis method, etc., and adaptive training is performed through prefabricated fire protection engineering impact samples. Among them, the prefabricated fire protection engineering construction impact factor is the input parameter dimension of the prefabricated fire protection engineering impact detection model.

[0039] Exemplarily, a prefabricated fire protection engineering impact detection model is constructed. First, based on the factors that affect the prefabricated fire protection engineering (i.e., the prefabricated fire protection engineering construction influencing factors), for each influencing factor, relevant data is collected. Preferably, historical engineering log data is obtained from an existing database or report. Then, the acquired data is processed in a structured and standardized manner to generate the above-mentioned prefabricated fire protection engineering impact samples, and one or more selected suitable model architectures are trained, including training with a part of the data and verifying with another part of the data. Through the training process, the model can obtain the relevant mapping relationship between the factors in the prediction detection project and the project. Finally, the performance of the model is evaluated, such as accuracy, recall rate, F1 score, etc., and the parameters of the model are adjusted or other models are selected according to the evaluation results. Until the performance of the model reaches a satisfactory level.

[0040] For example, the passive simulation data of the constructed project is input into the passive impact detection model of the constructed project, the simulated vibration parameters are analyzed, and the stability of the constructed structure, especially the tolerance of fire pipes and devices to vibration, is calculated. The stress-strain parameters are simulated to evaluate whether the constructed structure will have potential failures due to stress concentration or material fatigue. The prediction results are generated, and specific impact results are obtained based on the detection model, such as displacement caused by vibration, possible damage to equipment, etc., to form the passive impact prediction results of the constructed project.

[0041] For example, the simulation data of the project to be constructed is input into the impact detection model of the project to be constructed, and based on the simulation of material installation and equipment laying, possible project progress problems such as process delays and equipment installation deviations are predicted to analyze the construction progress. The quality of materials and equipment in the construction process is evaluated to predict whether they meet the standard requirements to achieve quality control.

[0042] For example, the construction geological passive simulation data is input into the construction geological passive impact detection model to evaluate the impact on the foundation and soil layer during the construction process, especially during excavation and foundation treatment, to predict possible geological problems and conduct geological condition analysis. Analyze the fluctuation of groundwater level and its impact on the construction area, predict potential hydrological risks during construction, and conduct hydrological change assessment.

[0043] In some implementations, based on the construction influencing factors of the prefabricated fire protection engineering, a prefabricated fire protection engineering impact detection model is constructed, including: Based on the construction impact factor of the prefabricated fire protection engineering, the passive impact detection record set of the constructed engineering, the impact detection record set of the engineering to be constructed and the passive impact detection record set of the construction geology are loaded; based on the integrated learning algorithm and the engineering impact detection loss threshold, according to the passive impact detection record set of the constructed engineering, the passive impact detection model of the constructed engineering is constructed; based on the integrated learning algorithm and the engineering impact detection loss threshold, according to the impact detection record set of the engineering to be constructed, the impact detection model of the engineering to be constructed is generated; based on the integrated learning algorithm and the engineering impact detection loss threshold, according to the construction geology passive impact detection record set, the construction geology passive impact detection model is built; the passive impact detection model of the constructed engineering, the impact detection model of the engineering to be constructed and the construction geology passive impact detection model are connected as parallel independent nodes to generate the prefabricated fire protection engineering impact detection model.

[0044] Optionally, the impact factor of prefabricated fire protection engineering construction is used as an index constraint, and the historical engineering record data is interactively extracted to extract the passive impact detection record set of the constructed engineering, the impact detection record set of the engineering to be constructed, and the passive impact detection record set of the construction geology. Among them, the above detection record set includes data categories such as detection reports, rectification notices, construction logs, etc.

[0045] Optionally, three sub-models are constructed based on their respective data sets using an integrated learning algorithm and a loss threshold for engineering impact detection. They are finally integrated into an assembled fire engineering impact detection model. Among them, the passive impact detection model for constructed engineering, the impact detection model for engineering to be constructed, and the passive impact detection model for construction geology are connected in parallel as independent nodes to a classifier to generate an assembled fire engineering impact detection model. The classifier is used to transmit the input data to the corresponding impact detection model. Through this structure of classification training and parallel connection, a specific detection model is constructed for each type of impact, which helps to improve detection efficiency and avoid overfitting.

[0046] In some implementations, performing risk prediction based on the passive impact prediction result of the constructed project to obtain the risk prediction result of the constructed project includes: Activate the risk prediction model for the constructed project, wherein the risk prediction model for the constructed project includes a risk prediction input layer for the constructed project, a risk depth prediction layer for the constructed project, a risk breadth prediction layer for the constructed project, a risk weighting layer for the constructed project and a risk prediction output layer for the constructed project; input the passive impact prediction result of the constructed project into the risk depth prediction layer for the constructed project to obtain the risk depth prediction coefficient for the constructed project; based on the passive impact prediction result of the constructed project and according to the risk breadth prediction layer for the constructed project, obtain the risk breadth coefficient for the constructed project; based on the risk weighting layer for the constructed project, obtain the risk breadth coefficient for the constructed project The comprehensive risk coefficient of the constructed project is calculated by combining the risk depth prediction coefficient of the constructed project and the risk breadth coefficient of the constructed project; it is determined whether the comprehensive risk coefficient of the constructed project is less than the predetermined comprehensive risk coefficient of the constructed project; if the comprehensive risk coefficient of the constructed project is less than the predetermined comprehensive risk coefficient of the constructed project, the risk prediction result of the constructed project is recorded as zero; if the comprehensive risk coefficient of the constructed project is greater than / equal to the predetermined comprehensive risk coefficient of the constructed project, the passive impact prediction result of the constructed project and the comprehensive risk coefficient of the constructed project are added to the risk prediction result of the constructed project.

[0047] Specifically, the depth prediction layer of risks of constructed projects is used to analyze the severity of potential risks of constructed projects at different construction stages; the breadth prediction layer of risks of constructed projects is used to evaluate the extent to which constructed projects are affected by the external environment and construction operations; the weighted layer of risks of constructed projects is used to comprehensively weight the results of the depth prediction layer and the breadth prediction layer, and to assign weights according to the importance of different influencing factors to generate a comprehensive risk coefficient for constructed projects. The comprehensive risk coefficient for constructed projects is a numerical measure of the risks of constructed projects.

[0048] Optionally, the constructed project risk prediction output layer is used to convert the comprehensive risk score of the weighted layer into a specific risk assessment result, and output a visualized risk level, warning information, and recommended risk response measures.

[0049] Specifically, if the comprehensive risk coefficient of the constructed project is less than the predetermined comprehensive risk coefficient of the constructed project, the risk prediction result of the constructed project will be recorded as zero, which means that the predicted risk at this time is not enough to trigger any warning or response measures, and is considered to be a risk within an acceptable safety range. If the comprehensive risk coefficient of the constructed project is greater than or equal to the predetermined comprehensive risk coefficient of the constructed project, the passive impact prediction result of the constructed project and the comprehensive risk coefficient of the constructed project will be added to the risk prediction result of the constructed project. This means that the risk in this case has reached the standard of early warning or intervention, and it is necessary to combine the specific data of the passive impact prediction with the comprehensive risk coefficient for evaluation to determine the potential construction safety hazards.

[0050] Optionally, the comprehensive risk factor of the predetermined constructed project is determined based on a statistical analysis method and a selected confidence level (eg, a 95% confidence interval) to ensure the accuracy and reliability of the risk assessment.

[0051] In some implementations, performing risk prediction based on the impact prediction result of the project to be constructed to obtain the risk prediction result of the project to be constructed includes: Activate the risk prediction model for the project to be constructed, wherein the risk prediction model for the project to be constructed includes a risk prediction input layer for the project to be constructed, a risk depth prediction layer for the project to be constructed, a risk breadth prediction layer for the project to be constructed, a risk weighting layer for the project to be constructed and a risk prediction output layer for the project to be constructed; input the impact prediction result of the project to be constructed into the risk depth prediction layer for the project to be constructed to obtain a risk depth prediction coefficient for the project to be constructed; based on the impact prediction result of the project to be constructed, according to the risk breadth prediction layer for the project to be constructed, obtain a risk breadth coefficient for the project to be constructed; based on the risk weighting layer for the project to be constructed, combined with the risk The risk depth prediction coefficient of the project to be constructed and the risk breadth coefficient of the project to be constructed are used to calculate the comprehensive risk coefficient of the project to be constructed; it is determined whether the comprehensive risk coefficient of the project to be constructed is less than the predetermined comprehensive risk coefficient of the project to be constructed; if the comprehensive risk coefficient of the project to be constructed is less than the predetermined comprehensive risk coefficient of the project to be constructed, the risk prediction result of the project to be constructed is recorded as zero; if the comprehensive risk coefficient of the project to be constructed is greater than / equal to the predetermined comprehensive risk coefficient of the project to be constructed, the impact prediction result of the project to be constructed and the comprehensive risk coefficient of the project to be constructed are added to the risk prediction result of the project to be constructed.

[0052] Specifically, the same method and principle as the above-mentioned risk prediction results of the constructed project are adopted to perform risk prediction based on the impact prediction results of the project to be constructed, and obtain the risk prediction results of the project to be constructed. In other words, through a similar risk prediction model, including risk depth prediction, breadth prediction, weighted calculation and comprehensive coefficient evaluation, the risk prediction results of the project to be constructed are finally generated. In order to ensure the simplicity of the specification, this process will not be further described in detail. The relevant details are the same as the process of risk prediction of the constructed project, that is, by comparing the comprehensive risk coefficient, it is decided whether to record the risk prediction result as zero or retain and output it.

[0053] In some implementations, performing risk prediction based on the construction geological passive impact prediction result to obtain the construction geological risk prediction result includes: Activate a construction geological risk prediction model, wherein the construction geological risk prediction model includes a construction geological risk prediction input layer, a construction geological risk depth prediction layer, a construction geological risk breadth prediction layer, a construction geological risk weighting layer and a construction geological risk prediction output layer; Input the construction geological passive impact prediction result into the construction geological risk depth prediction layer to obtain the construction geological risk depth prediction coefficient; based on the construction geological passive impact prediction result, according to the construction geological risk breadth prediction layer, obtain the construction geological risk breadth coefficient; based on the construction geological risk weighted layer, combine the construction geological risk depth prediction coefficient and the construction geological risk breadth coefficient to calculate the construction geological risk comprehensive coefficient; determine whether the construction geological risk comprehensive coefficient is less than the predetermined construction geological risk comprehensive coefficient; if the construction geological risk comprehensive coefficient is less than the predetermined construction geological risk comprehensive coefficient, record the construction geological risk prediction result as zero; if the construction geological risk comprehensive coefficient is greater than / equal to the predetermined construction geological risk comprehensive coefficient, add the construction geological passive impact prediction result and the construction geological risk comprehensive coefficient to the construction geological risk prediction result.

[0054] Specifically, the same method and principle as that for obtaining the risk prediction results of the constructed project and the risk prediction results of the project to be constructed is adopted, and the risk prediction is performed based on the prediction results of the passive impact of the construction geology to obtain the construction geology risk prediction results. In other words, through a similar risk prediction model, including risk depth prediction, breadth prediction, weighted calculation and comprehensive coefficient evaluation, the prediction results of the construction geology risk are finally generated. In order to ensure the simplicity of the specification, this process will not be further described in detail, and the relevant details are the same as the aforementioned process, that is, by comparing the comprehensive risk coefficient, it is decided whether to record the risk prediction result as zero or retain and output it.

[0055] Based on the second-node construction risk prediction report, the second-node prefabricated fire protection engineering information is optimized to obtain the second-node optimized prefabricated fire protection engineering information.

[0056] Specifically, the information of the second-node prefabricated fire protection engineering project is optimized, including adjusting the construction sequence, changing the construction process, replacing construction equipment, improving the construction environment, adjusting the construction time nodes, controlling the number of people on the construction site, adjusting the multi-professional parallel strategy of the construction project (adjusting the construction window), etc.

[0057] Based on the second node, the prefabricated fire protection engineering information is optimized to perform the construction project management and control of the target prefabricated fire protection engineering.

[0058] Specifically, based on the optimized prefabricated fire protection engineering information, the pending projects of the target prefabricated fire protection engineering are managed and controlled, so that the pending projects can be better controlled, thereby improving the construction quality and ensuring the construction safety.

[0059] In summary, the prefabricated fire engineering management optimization method based on the digital platform application provided by the present invention has the following technical effects: By connecting the digital platform application, the first node prefabricated fire protection engineering information and the second node prefabricated fire protection engineering information are obtained; the BIM system is activated, and the second node construction scenario model is constructed based on the first node prefabricated fire protection engineering information; the prefabricated fire protection engineering construction influencing factors are activated, wherein the prefabricated fire protection engineering construction influencing factors include the passive impact of the constructed project, the impact of the project to be constructed and the passive impact of the construction geology; based on the prefabricated fire protection engineering construction influencing factors, the second node prefabricated fire protection engineering information and the second node construction scenario model are combined to perform construction risk prediction and obtain the second node construction risk prediction report; based on the second node construction risk prediction report, the second node prefabricated fire protection engineering information is optimized to obtain the second node optimized prefabricated fire protection engineering information; based on the second node optimized prefabricated fire protection engineering information, the target prefabricated fire protection engineering to be constructed project management and control is performed. Thus, the technical effect of improving management efficiency and management precision is achieved.

[0060] It should be understood that the embodiments disclosed in the present invention and the above description can enable those skilled in the art to use the present invention to implement the present invention. At the same time, the present invention is not limited to the above-mentioned embodiments. It should be understood that those skilled in the art can still modify the technical solutions recorded in the above-mentioned embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. The method for optimizing the management of assembled fire protection engineering based on digital platform application is characterized in that: The method comprises: Connect to the digital platform application to obtain first-node prefabricated fire protection engineering information and second-node prefabricated fire protection engineering information, wherein the first-node prefabricated fire protection engineering information is the constructed engineering information of the target prefabricated fire protection engineering, and the second-node prefabricated fire protection engineering information is the pending engineering information of the target prefabricated fire protection engineering; Activate the BIM system and build a second node construction scenario model based on the first node prefabricated fire protection engineering information; Activate the influencing factors of the construction of prefabricated fire protection engineering, wherein the influencing factors of the construction of prefabricated fire protection engineering include the passive impact of the constructed engineering, the impact of the engineering to be constructed and the passive impact of the construction geology; Based on the construction influencing factor of the prefabricated fire protection engineering, combined with the second node prefabricated fire protection engineering information and the second node construction scenario model, a construction risk prediction is performed to obtain a second node construction risk prediction report; Optimizing the second node prefabricated fire protection engineering information based on the second node construction risk prediction report to obtain the second node optimized prefabricated fire protection engineering information; Based on the second node, the prefabricated fire protection engineering information is optimized to perform the construction project management and control of the target prefabricated fire protection engineering.

2. The method according to claim 1, characterized in that Activate the BIM system, and build a second node construction scenario model based on the first node prefabricated fire protection engineering information, including: Based on the BIM system, a first-node prefabricated fire protection engineering model is established according to the first-node prefabricated fire protection engineering information; Based on the second node prefabricated fire protection engineering information, construction area information is collected to obtain the second node construction area information; Perform construction environment prediction based on the second node prefabricated fire protection engineering information to obtain the second node construction environment information; Based on the second node construction area information and the second node construction environment information, the first node prefabricated fire protection engineering model is optimized to generate the second node construction scene model.

3. The method according to claim 1, characterized in that Based on the construction influencing factors of the prefabricated fire protection engineering, the construction risk prediction is performed in combination with the second node prefabricated fire protection engineering information and the second node construction scenario model to obtain a second node construction risk prediction report, including: Based on the second node prefabricated fire protection engineering information, performing construction simulation according to the second node construction scene model to obtain a second node construction simulation data set; Based on the construction impact factor of the prefabricated fire protection project, a construction impact prediction is performed according to the second node construction simulation data set to obtain the passive impact prediction results of the constructed project, the impact prediction results of the project to be constructed, and the passive impact prediction results of the construction geology; Perform risk prediction based on the passive impact prediction results of the constructed project to obtain risk prediction results of the constructed project; Perform risk prediction based on the impact prediction result of the project to be constructed to obtain a risk prediction result of the project to be constructed; Perform risk prediction based on the construction geological passive impact prediction result to obtain a construction geological risk prediction result; The risk prediction results of the constructed projects, the risk prediction results of the projects to be constructed and the construction geological risk prediction results are sorted out to generate the second node construction risk prediction report.

4. The method according to claim 3, characterized in that Based on the construction impact factor of the prefabricated fire protection project, the construction impact prediction is performed according to the second node construction simulation data set to obtain the passive impact prediction results of the constructed project, the impact prediction results of the project to be constructed and the passive impact prediction results of the construction geology, including: Perform feature recognition based on the second node construction simulation data set to obtain passive simulation data of constructed projects, simulation data of projects to be constructed, and passive simulation data of construction geology; Based on the construction influencing factors of the prefabricated fire protection engineering, an impact detection model of the prefabricated fire protection engineering is constructed, wherein the impact detection model of the prefabricated fire protection engineering includes a passive impact detection model of the constructed engineering, an impact detection model of the engineering to be constructed, and a passive impact detection model of the construction geology; Inputting the passive simulation data of the constructed project into the passive impact detection model of the constructed project to generate a passive impact prediction result of the constructed project; Based on the simulation data of the project to be constructed and according to the impact detection model of the project to be constructed, generating a prediction result of the impact of the project to be constructed; Based on the construction geology passive simulation data and according to the construction geology passive impact detection model, the construction geology passive impact prediction result is generated.

5. The method according to claim 4, characterized in that Based on the influencing factors of the prefabricated fire protection engineering construction, an impact detection model of the prefabricated fire protection engineering is constructed, including: Based on the construction impact factor of the prefabricated fire protection project, load the passive impact detection record set of the constructed project, the impact detection record set of the project to be constructed, and the passive impact detection record set of the construction geology; Based on the integrated learning algorithm and the engineering impact detection loss threshold, and according to the passive impact detection record set of the constructed engineering, a passive impact detection model of the constructed engineering is constructed; Based on the ensemble learning algorithm and the engineering impact detection loss threshold, generating the to-be-constructed engineering impact detection model according to the to-be-constructed engineering impact detection record set; Based on the ensemble learning algorithm and the engineering impact detection loss threshold, and according to the construction geology passive impact detection record set, the construction geology passive impact detection model is constructed; The passive impact detection model of the constructed project, the impact detection model of the project to be constructed and the passive impact detection model of the construction geology are connected as parallel independent nodes to generate the prefabricated fire protection project impact detection model.

6. The method according to claim 3, characterized in that Based on the passive impact prediction results of the constructed project, risk prediction is performed to obtain risk prediction results of the constructed project, including: Activate a risk prediction model for a constructed project, wherein the risk prediction model for a constructed project includes a risk prediction input layer for a constructed project, a risk depth prediction layer for a constructed project, a risk breadth prediction layer for a constructed project, a risk weighting layer for a constructed project, and a risk prediction output layer for a constructed project; Inputting the passive impact prediction result of the constructed project into the risk depth prediction layer of the constructed project to obtain the risk depth prediction coefficient of the constructed project; Based on the passive impact prediction result of the constructed project, and according to the risk breadth prediction layer of the constructed project, a risk breadth coefficient of the constructed project is obtained; Based on the risk weighted layer of the constructed project, combined with the risk depth prediction coefficient of the constructed project and the risk breadth coefficient of the constructed project, a comprehensive risk coefficient of the constructed project is calculated; Determining whether the comprehensive risk coefficient of the constructed project is less than the predetermined comprehensive risk coefficient of the constructed project; If the comprehensive risk coefficient of the constructed project is less than the predetermined comprehensive risk coefficient of the constructed project, the risk prediction result of the constructed project is recorded as zero; If the comprehensive risk coefficient of the constructed project is greater than / equal to the predetermined comprehensive risk coefficient of the constructed project, the passive impact prediction result of the constructed project and the comprehensive risk coefficient of the constructed project are added to the risk prediction result of the constructed project.

7. The method according to claim 3, characterized in that Based on the impact prediction result of the project to be constructed, risk prediction is performed to obtain risk prediction results of the project to be constructed, including: Activate a risk prediction model for a project to be constructed, wherein the risk prediction model for a project to be constructed includes a risk prediction input layer for a project to be constructed, a risk depth prediction layer for a project to be constructed, a risk breadth prediction layer for a project to be constructed, a risk weighting layer for a project to be constructed, and a risk prediction output layer for a project to be constructed; Inputting the impact prediction result of the project to be constructed into the risk depth prediction layer of the project to be constructed to obtain the risk depth prediction coefficient of the project to be constructed; Based on the impact prediction result of the project to be constructed, and according to the risk breadth prediction layer of the project to be constructed, a risk breadth coefficient of the project to be constructed is obtained; Based on the risk weighted layer of the project to be constructed, combined with the risk depth prediction coefficient of the project to be constructed and the risk breadth coefficient of the project to be constructed, a comprehensive risk coefficient of the project to be constructed is calculated; Determining whether the comprehensive risk coefficient of the project to be constructed is less than a predetermined comprehensive risk coefficient of the project to be constructed; If the comprehensive risk coefficient of the project to be constructed is less than the predetermined comprehensive risk coefficient of the project to be constructed, the risk prediction result of the project to be constructed is recorded as zero; If the comprehensive risk coefficient of the project to be constructed is greater than / equal to the predetermined comprehensive risk coefficient of the project to be constructed, the impact prediction result of the project to be constructed and the comprehensive risk coefficient of the project to be constructed are added to the risk prediction result of the project to be constructed.

8. The method according to claim 3, characterized in that Based on the construction geological passive impact prediction results, risk prediction is performed to obtain construction geological risk prediction results, including: Activate a construction geological risk prediction model, wherein the construction geological risk prediction model includes a construction geological risk prediction input layer, a construction geological risk depth prediction layer, a construction geological risk breadth prediction layer, a construction geological risk weighting layer and a construction geological risk prediction output layer; Inputting the construction geological passive impact prediction result into the construction geological risk depth prediction layer to obtain a construction geological risk depth prediction coefficient; Based on the construction geological passive impact prediction result, according to the construction geological risk breadth prediction layer, a construction geological risk breadth coefficient is obtained; Based on the construction geological risk weighted layer, combined with the construction geological risk depth prediction coefficient and the construction geological risk breadth coefficient, a construction geological risk comprehensive coefficient is calculated; Determining whether the comprehensive construction geological risk coefficient is less than a predetermined comprehensive construction geological risk coefficient; If the construction geological risk comprehensive coefficient is less than the predetermined construction geological risk comprehensive coefficient, the construction geological risk prediction result is recorded as zero; If the comprehensive construction geological risk coefficient is greater than / equal to the predetermined comprehensive construction geological risk coefficient, the construction geological passive impact prediction result and the comprehensive construction geological risk coefficient are added to the construction geological risk prediction result.

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