Prefabricated building component stability monitoring and early warning method and system

Abstract

A prefabricated building component stability monitoring and early warning method and system, relating to the technical field of engineering project management. The method comprises: on the basis of a target building engineering drawing, constructing a construction node sequence; generating a plurality of engineering construction simulation models; acquiring a sample data set of a plurality of construction nodes, performing stability-associated factor analysis, and constructing a node factor mapping sequence; by using the node factor mapping sequence as monitoring data, performing construction monitoring, and determining construction monitoring data of a first construction node; on the basis of the construction monitoring data, performing mapping and acquiring a first engineering construction simulation model, performing error analysis by means of a twin comparison channel, and determining a first construction error; and on the basis of the first construction error, generating a construction early warning signal, and, on the basis of the construction early warning signal, acquiring a first construction compensation parameter and performing subsequent construction compensation for target building engineering, thereby achieving the technical effects of improving the safety and reliability of a prefabricated building structure and reducing potential risks and losses.

Description

A method and system for monitoring and warning the stability of assembled building components Technical Field

[0001] The present invention relates to the technical field of engineering project management, and in particular to a method and system for monitoring and warning the stability of assembled building components. Background Art

[0002] Prefabricated construction is a construction method in which building components are prefabricated in a factory and then assembled on-site. This construction method generally improves construction efficiency and reduces waste. It is suitable for a variety of building types and has been widely adopted and promoted. The application of prefabricated construction involves multiple stages, including design, manufacturing, transportation, and installation. The stability of prefabricated building components is crucial to the safety and reliability of the building. Traditional structural monitoring methods suffer from long response times and are unable to cope with large amounts of data and high complexity.

[0003] Summary of the Invention

[0004] The purpose of this application is to provide a method and system for monitoring and warning the stability of prefabricated building components, in order to solve the technical problems in the prior art such as long response time and difficulty in coping with large amounts of data and high complexity.

[0005] In view of the above technical problems, the present application provides a method and system for monitoring and early warning the stability of prefabricated building components.

[0006] In a first aspect, the present application provides a method for monitoring and early warning the stability of prefabricated building components, wherein the method comprises:

[0007] Extract multiple construction nodes based on the target building engineering drawings and construct a construction node sequence;

[0008] Based on the construction node sequence, simulation modeling is performed according to the target building engineering drawings to generate multiple engineering construction simulation models;

[0009] Obtaining a sample data set of the plurality of construction nodes, performing stable correlation factor analysis, and constructing a node factor mapping sequence;

[0010] Taking the node factor mapping sequence as monitoring data, performing construction monitoring based on the construction node sequence, and determining construction monitoring data of the first construction node;

[0011] Acquire a first engineering construction simulation model based on the construction monitoring data mapping, and perform error analysis on the construction monitoring data and the first construction simulation model through a twin comparison channel to determine a first construction error;

[0012] A construction warning signal is generated based on the first construction error, and a first construction compensation parameter is obtained according to the construction warning signal to perform construction compensation for a subsequent target construction project.

[0013] In a second aspect, the present application further provides a prefabricated building component stability monitoring and early warning system, wherein the system comprises:

[0014] A node extraction module, the node extraction module is used to extract multiple construction nodes based on the target building engineering drawings and construct a construction node sequence;

[0015] A simulation modeling module, configured to perform simulation modeling based on the construction node sequence and the target building engineering drawings to generate a plurality of engineering construction simulation models;

[0016] An association analysis module, the association analysis module is used to obtain a sample data set of the plurality of construction nodes, perform stable association factor analysis, and construct a node factor mapping sequence;

[0017] a construction monitoring module, configured to use the node factor mapping sequence as monitoring data, perform construction monitoring based on the construction node sequence, and determine construction monitoring data of a first construction node;

[0018] a simulation analysis module, the simulation analysis module being configured to obtain a first engineering construction simulation model based on the construction monitoring data mapping, and perform error analysis on the construction monitoring data and the first construction simulation model through a twin comparison channel to determine a first construction error;

[0019] A construction warning module is used to generate a construction warning signal based on the first construction error, and obtain a first construction compensation parameter according to the construction warning signal to perform construction compensation for the subsequent target construction project.

[0020] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0021] The method extracts multiple construction nodes based on the target building engineering drawings and constructs a construction node sequence. Based on the construction node sequence, simulation modeling is performed according to the target building engineering drawings to generate multiple construction simulation models. Sample data sets of multiple construction nodes are obtained, and stable correlation factor analysis is performed to construct a node factor mapping sequence. The node factor mapping sequence is used as monitoring data, and construction monitoring is performed based on the construction node sequence to determine the construction monitoring data of the first construction node. Based on the construction monitoring data mapping, a first construction simulation model is obtained, and error analysis is performed between the construction monitoring data and the first construction simulation model through a twin comparison channel to determine the first construction error. A construction warning signal is generated based on the first construction error, and a first construction compensation parameter is obtained based on the construction warning signal to perform construction compensation for the subsequent target building project. This achieves the technical effect of improving the safety and reliability of prefabricated building structures and reducing potential risks and losses.

[0022] The above description is only an overview of the technical solution of the present application. In order to more clearly illustrate the technical means of the present application and to implement it in accordance with the contents of the specification, and to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The embodiments of the present invention and the following brief description are illustrated in conjunction with the accompanying drawings, which are described as follows:

[0024] FIG1 is a flow chart of a method for monitoring and early warning the stability of prefabricated building components according to the present application;

[0025] FIG2 is a schematic diagram of a process for constructing a node factor mapping sequence in a method for monitoring and early warning the stability of prefabricated building components of the present application;

[0026] FIG3 is a schematic structural diagram of a prefabricated building component stability monitoring and early warning system according to the present application.

[0027] Explanation of the accompanying drawings: node extraction module 11, simulation modeling module 12, correlation analysis module 13, construction monitoring module 14, simulation analysis module 15, construction early warning module 16. DETAILED DESCRIPTION

[0028] This application solves the technical problems faced by the existing technology, such as long response time and difficulty in coping with large amounts of data and high complexity, by providing a method and system for monitoring and early warning the stability of prefabricated building components.

[0029] The solution in this technical embodiment, in order to solve the above problems, adopts the following overall ideas:

[0030] First, using the target construction project drawings, multiple construction nodes are extracted and formed into a construction node sequence. Based on this sequence, construction project simulation modeling is then performed to generate multiple construction simulation models. Simultaneously, a sample dataset of multiple construction nodes is obtained and subjected to stable correlation factor analysis to form a node factor mapping sequence. Next, monitoring data is generated using the node factor mapping sequence, and construction monitoring is performed based on the construction node sequence to obtain monitoring data for the first construction node. Based on the monitoring data mapping, a first construction simulation model is generated. Error analysis is then performed between the monitoring data and the first construction simulation model using a twin comparison channel to obtain a first construction error. Finally, a construction warning signal is generated based on this error, and a first construction compensation parameter is derived from this signal for subsequent construction compensation in the target construction project. This results in a technical effect of improving the safety and reliability of prefabricated building structures and reducing potential risks and losses.

[0031] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the drawings and specific implementation methods of the specification. It should be noted that the described embodiments are only part of the embodiments of this application, rather than all the embodiments of this application. It should be understood that this application is not limited to the example embodiments described herein. 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. It should also be noted that for the convenience of description, only the parts related to the present invention, rather than all, are shown in the drawings.

[0032] Example 1

[0033] As shown in FIG1 , the present application provides a method for monitoring and early warning the stability of prefabricated building components, the method comprising:

[0034] S100: extracting multiple construction nodes based on the target building engineering drawing and constructing a construction node sequence;

[0035] The target building is a prefabricated building with known engineering drawings. The target building is constructed by arranging multiple prefabricated building components according to a specific construction sequence and steps. The target building engineering drawings provide construction information such as the installation steps, locations, and combinations of the target building's prefabricated building components. By analyzing the target building engineering drawings, construction information related to the construction nodes is extracted. Based on this extracted information, a construction node sequence is established. This construction node sequence represents the order of construction or other related sequential relationships. It includes information about dependencies between nodes, connection methods, and component types.

[0036] The construction of the construction node sequence provides a basis for subsequent stability monitoring and early warning. By establishing the construction node sequence, we can better understand the components and construction sequence of the building, thereby conducting more effective monitoring and early warning.

[0037] S200: Based on the construction node sequence, simulation modeling is performed according to the target building engineering drawing to generate multiple engineering construction simulation models;

[0038] Optionally, using Building Information Modeling (BIM) or other modeling technologies, simulation modeling is performed based on the drawings and design information of the target building project to create multiple construction simulation models. These models reflect information covering the building's geometry, structure, material properties, and other aspects.

[0039] Optionally, during the simulation modeling process, multiple different construction simulation models can be generated based on different construction plans, materials, processes, and other factors. These models can represent different states or stages of the building's construction process. Through this process, the system can simulate different construction scenarios in a simulation environment, providing more contextual information for subsequent monitoring and early warning.

[0040] Optionally, multiple engineering construction simulation models correspond to multiple nodes in a construction node sequence. By combining the multiple engineering construction simulation models based on the construction node sequence and setting coordination relationships and coordination parameters, the target building model at different construction nodes can be obtained. This achieves the technical effect of obtaining a simulation model of the target building in any construction state.

[0041] S300: Obtaining a sample data set of the plurality of construction nodes, performing stable correlation factor analysis, and constructing a node factor mapping sequence;

[0042] Optionally, the sample dataset refers to historical construction record data for multiple construction nodes. The sample dataset is obtained by acquiring relevant sample data such as construction logs and monitoring records for each construction node to generate a sample dataset. The sample dataset includes measurement data, sensor data, quality inspection records, stability evaluation results, and other data from the construction process.

[0043] Optionally, the stability evaluation of the target prefabricated building involves structural analysis, material analysis, connection method evaluation, etc. Exemplarily, it includes static and dynamic analysis to ensure the stability of the building under various external forces and loads.

[0044] Optionally, node factors refer to parameters highly correlated with the stability of construction nodes. Alternatively, factor analysis can be performed on a sample dataset for each node to identify and extract key factors influencing node stability. These factors include structural parameters, material properties, and construction techniques. Furthermore, different construction nodes correspond to different node factors. The key factors for each node are mapped into a sequence, forming a node factor mapping sequence. This node factor mapping sequence reflects the changing trends of key factors during the construction process.

[0045] Furthermore, as shown in FIG2 , a sample data set of the plurality of construction nodes is obtained, and a stable correlation factor analysis is performed to construct a node factor mapping sequence. Step S300 further includes:

[0046] Randomly selecting a first construction node from the multiple construction nodes, and obtaining a first sample data set of the first construction node;

[0047] Taking construction stability as a goal, performing stability correlation factor analysis on the first sample data set in sequence to determine multiple first stability correlation factor sets;

[0048] Marking a first stable correlation factor whose occurrence frequency is greater than a preset frequency threshold in the plurality of first stable correlation factor sets as a first main correlation factor, to obtain a first main correlation factor set;

[0049] A node factor mapping sequence is constructed based on the mapping relationship between the first construction node and the first main association factor set.

[0050] Optionally, a node corresponding to the current construction progress or a node next to the current construction progress among multiple construction nodes is selected as the first construction node, thereby ensuring a better response speed even for target prefabricated buildings that start stability monitoring midway.

[0051] Optionally, a key node among multiple construction nodes is selected as the first construction node. Key nodes are construction nodes that play a key role in the entire building structure. They may bear large loads or have special structural designs, so monitoring their stability is particularly important. Exemplary construction nodes include foundation construction and weighing component installation. By prioritizing key nodes as the first construction node, stability control of prefabricated buildings can be quickly achieved, preventing the occurrence of serious safety risks.

[0052] Optionally, during the construction process, multiple construction nodes are traversed to select a first construction node, and the stability of each node is gradually monitored. By monitoring in an orderly manner, it is ensured that each node is carefully monitored.

[0053] Optionally, a stability correlation factor analysis is performed on the first sample dataset. This analysis involves statistical analysis and data mining to determine which factors are associated with construction stability. Factors can include various parameters, such as structural design, construction material quality, and construction speed. Exemplarily, the stability correlation factor analysis of the first sample dataset is performed based on the Apriori algorithm.

[0054] The first main correlation factor refers to a selected correlation factor that has a high correlation with the stability of the first construction node. By setting a preset frequency threshold, multiple first stability correlation factor sets are screened to obtain the first main correlation factor set.

[0055] S400: Using the node factor mapping sequence as monitoring data, performing construction monitoring based on the construction node sequence, and determining construction monitoring data of a first construction node;

[0056] Optionally, construction monitoring of multiple construction nodes is performed based on the node factor mapping sequence and the construction node sequence. For example, a sensor deployment plan is first designed based on the node factor corresponding to the first construction node. Then, based on the sensor deployment plan, sensors are deployed and node factor monitoring and collection are performed to obtain construction monitoring data for the first construction node. The sensor deployment plan is determined based on the node factor type corresponding to the first construction node and the monitoring requirements of the first construction node.

[0057] Optionally, the construction monitoring data obtained at the first construction node is preprocessed, including data deduplication, data cleaning, standardization, etc., to improve the quality and availability of the construction monitoring data and provide a more reliable basis for subsequent building stability evaluation and early warning.

[0058] S500: Acquire a first engineering construction simulation model based on the construction monitoring data mapping, and perform error analysis on the construction monitoring data and the first construction simulation model through a twin comparison channel to determine a first construction error;

[0059] Optionally, the first construction simulation model is initialized by mapping based on construction monitoring data, and reflects the characteristics and features of the target prefabricated building at the first construction node. Error analysis at the first construction node is performed using the first construction simulation model, enabling early warning and accurate detection of construction errors.

[0060] Furthermore, error analysis is performed on the construction monitoring data and the first construction simulation model through the twin comparison channel to determine a first construction error. Step S500 further includes:

[0061] The twin comparison channel includes a first twin sub-channel, a second twin sub-channel, and a similar comparison sub-channel, wherein the first twin sub-channel is embedded with an engineering construction simulation model;

[0062] Inputting the construction monitoring data into the second twin channel, and acquiring the first engineering construction simulation model in the first twin channel based on the construction monitoring data mapping;

[0063] First construction standard data is extracted based on the first construction simulation model, and the construction monitoring data and the first construction standard data are input into the similarity comparison sub-channel to perform construction error analysis, and a first construction error is output.

[0064] The first construction simulation model is a standard model under ideal conditions based on construction monitoring data mapping. A simulation is performed based on the first construction simulation model to obtain first construction standard data, which reflects the construction data of the first construction node under ideal conditions.

[0065] The optional outputs of the first and second twin sub-channels are connected to the inputs of the similarity comparison sub-channel. The similarity comparison sub-channel performs construction error analysis by comparing the outputs of the first and second twin sub-channels. The similarity comparison sub-channel includes an error similarity analysis function for quantitatively calculating and obtaining the first construction error.

[0066] Furthermore, step S500 further includes:

[0067] Construct an error similarity analysis function:

[0068] Among them, S is the first construction error, n is the number of construction monitoring data types at the first construction node, and w i is the weight of the i-th construction monitoring data, y i is the i-th construction monitoring data, Y i is the i-th construction standard data.

[0069] Optionally, the weight of the construction monitoring data is determined based on the correlation between the correlation factor corresponding to the data and the construction node. The weight value of the construction monitoring data corresponding to the correlation factor with high correlation and large correlation coefficient is large, and the sum of n weight values ​​is 1.

[0070] By comprehensively considering the differences between construction monitoring data and construction standard data corresponding to multiple correlation factors, the first construction error is generated, which allows for a better understanding and quantification of the construction error at the first construction node. This provides a data foundation for subsequent stability warnings and treatment.

[0071] S600: Generate a construction warning signal based on the first construction error, and obtain a first construction compensation parameter according to the construction warning signal to perform construction compensation for a subsequent target construction project.

[0072] Furthermore, based on the first construction error, a construction warning signal is generated, and step S600 further includes:

[0073] Obtaining a preset first construction error threshold;

[0074] When the first construction error is greater than the first construction error threshold, a construction warning signal is generated, wherein the construction warning signal carries a first construction node identifier.

[0075] Optionally, a preset first construction error threshold is obtained. This threshold is set based on actual conditions, such as historical data, industry standards, design safety factors, or professional settings. A determination is made as to whether the first construction error is greater than the first construction error threshold. If so, a significant construction error exists, requiring early warning.

[0076] Optionally, the first construction error threshold includes multiple threshold levels corresponding to different degrees of construction error, and the multiple threshold levels correspond to multiple levels of construction warning signals. The setting of the multiple threshold levels is based on a comprehensive consideration of multiple dimensions, including the size of the construction error, the impact of the accident error, and the risk. For example, different construction nodes have different error correction coefficients, which comprehensively reflect factors such as the impact of the accident error and the risk, and are used to correct the first construction error. Key nodes have larger error correction coefficients, while non-key nodes have smaller error correction coefficients.

[0077] Optionally, if the first construction error is greater than a first construction error threshold, a construction warning signal is generated. This signal includes: a first construction node identifier: the identifier of the first construction node is added to the warning signal to accurately identify the specific construction node; a warning level: the warning level is determined based on the size and impact of the error, such as level one or level two; warning content: a description of the error, including its size, location, and direction; and a warning time: the time the warning signal was generated is recorded for subsequent tracking and processing.

[0078] Optionally, the generated construction warning signal is sent to relevant personnel or systems so that appropriate measures can be taken to address and adjust the situation in a timely manner. Through the above steps, a construction warning signal with the first construction node identifier can be generated in a timely manner based on the size and impact of the first construction error, helping relevant personnel or systems to promptly discover and resolve construction error issues, thereby improving construction quality and efficiency.

[0079] Furthermore, a first construction compensation parameter is obtained according to the construction early warning signal to perform construction compensation for the subsequent target construction project. Step S600 further includes:

[0080] The construction compensation model is trained by using multiple historical construction data to obtain a construction compensation model that meets the expected indicators;

[0081] The first construction error is compensated and analyzed using the construction compensation model to output a first construction compensation parameter.

[0082] Optionally, the construction compensation model is based on a neural network model, which provides end-to-end construction compensation based on the first construction error and generates first construction compensation parameters. Exemplarily, the construction compensation model is trained using multiple historical construction data sets to obtain a construction compensation model that meets expected performance indicators. First, relevant data from multiple historical construction projects is collected, including error data during the construction process, compensation parameters, and final construction results. The collected historical construction data is then cleaned and processed, including outlier removal, missing value filling, and standardization to ensure data quality and consistency. Next, based on actual needs and domain knowledge, meaningful features are extracted from the historical construction data, such as construction environment, material properties, and construction methods. The historical construction dataset is then divided into a training set and a test set for model training and evaluation. An appropriate machine learning algorithm or deep learning model is then selected and trained using the data in the training set. Exemplary models include regression models, decision tree models, and neural network models. The trained model is then evaluated using data from the test set, calculating error metrics between the predicted and actual results, such as root mean square error (RMSE), mean absolute error (MAE), and the F1 function. Based on the evaluation results, the model is fine-tuned, such as by adjusting hyperparameters and adding regularization terms. The model is validated using an independent validation set or cross-validation to ensure good generalization on unknown data. If the validation results meet the expected monitoring indicators for the target prefabricated building, the model is stored as a construction compensation model, and a compensation analysis is performed on the first construction error to calculate the corresponding first construction compensation parameters.

[0083] In summary, the present invention provides a method for monitoring and early warning the stability of prefabricated building components, which has the following technical effects:

[0084] The method extracts multiple construction nodes based on the target building engineering drawings and constructs a construction node sequence. Based on the construction node sequence, simulation modeling is performed according to the target building engineering drawings to generate multiple construction simulation models. Sample data sets of multiple construction nodes are obtained, and stable correlation factor analysis is performed to construct a node factor mapping sequence. The node factor mapping sequence is used as monitoring data, and construction monitoring is performed based on the construction node sequence to determine the construction monitoring data of the first construction node. Based on the construction monitoring data mapping, a first construction simulation model is obtained, and error analysis is performed between the construction monitoring data and the first construction simulation model through a twin comparison channel to determine the first construction error. A construction warning signal is generated based on the first construction error, and a first construction compensation parameter is obtained based on the construction warning signal to perform construction compensation for the subsequent target building project. This achieves the technical effect of improving the safety and reliability of prefabricated building structures and reducing potential risks and losses.

[0085] Example 2

[0086] Based on the same concept as the method for monitoring and warning the stability of prefabricated building components in the embodiment, as shown in FIG3 , the present application also provides a system for monitoring and warning the stability of prefabricated building components, the system comprising:

[0087] A node extraction module 11 is used to extract multiple construction nodes based on the target building engineering drawings and construct a construction node sequence;

[0088] A simulation modeling module 12 is configured to perform simulation modeling based on the construction node sequence and the target building engineering drawings to generate a plurality of engineering construction simulation models;

[0089] The correlation analysis module 13 is used to obtain the sample data set of the plurality of construction nodes, perform stable correlation factor analysis, and construct a node factor mapping sequence;

[0090] A construction monitoring module 14 is configured to use the node factor mapping sequence as monitoring data, perform construction monitoring based on the construction node sequence, and determine construction monitoring data of a first construction node;

[0091] a simulation analysis module 15 for obtaining a first engineering construction simulation model based on the construction monitoring data mapping, and performing error analysis on the construction monitoring data and the first construction simulation model through a twin comparison channel to determine a first construction error;

[0092] The construction warning module 16 is configured to generate a construction warning signal based on the first construction error, and obtain a first construction compensation parameter according to the construction warning signal to perform construction compensation for a subsequent target construction project.

[0093] Furthermore, the association analysis module 13 also includes:

[0094] A sample data unit, configured to randomly select a first construction node from the plurality of construction nodes and obtain a first sample data set of the first construction node;

[0095] a correlation factor acquisition unit, configured to perform stability correlation factor analysis on the first sample data set in sequence with construction stability as a goal, and determine a plurality of first stability correlation factor sets;

[0096] a main correlation factor extraction unit, configured to mark a first stable correlation factor whose occurrence frequency is greater than a preset frequency threshold in the plurality of first stable correlation factor sets as a first main correlation factor, to obtain a first main correlation factor set;

[0097] A mapping unit is used to construct a node factor mapping sequence based on the mapping relationship between the first construction node and the first main association factor set.

[0098] Furthermore, the simulation analysis module 15 also includes:

[0099] A twin comparison channel unit, wherein the twin comparison channel includes a first twin sub-channel, a second twin sub-channel, and a similarity comparison sub-channel, wherein the first twin sub-channel is embedded with an engineering construction simulation model;

[0100] a data input unit, configured to input the construction monitoring data into the second twin channel, and acquire the first engineering construction simulation model in the first twin channel based on the construction monitoring data mapping;

[0101] The error analysis unit is used to extract first construction standard data based on the first construction simulation model, input the construction monitoring data and the first construction standard data into the similarity comparison sub-channel to perform construction error analysis, and output a first construction error.

[0102] Furthermore, the simulation analysis module 15 also includes:

[0103] Subchannel construction unit, used to construct error similarity analysis function:

[0104] Among them, S is the first construction error, n is the number of construction monitoring data types at the first construction node, and w i is the weight of the i-th construction monitoring data, y i is the i-th construction monitoring data, Y i is the i-th construction standard data.

[0105] Furthermore, the construction early warning module 16 also includes:

[0106] A threshold setting unit, configured to obtain a preset first construction error threshold;

[0107] The warning generating unit is configured to generate a construction warning signal when the first construction error is greater than the first construction error threshold, wherein the construction warning signal carries a first construction node identifier.

[0108] Furthermore, the construction early warning module 16 also includes:

[0109] A compensation training unit is used to train a construction compensation model using multiple historical construction data to obtain a construction compensation model that meets expected indicators;

[0110] A compensation analysis unit is configured to perform compensation analysis on the first construction error using the construction compensation model and output a first construction compensation parameter.

[0111] It should be understood that the embodiments mentioned in this specification focus on their differences from other embodiments. The specific embodiments in the aforementioned embodiment one are also applicable to the prefabricated building component stability monitoring and early warning system described in embodiment two. For the sake of brevity of the specification, they will not be further elaborated here.

[0112] It should be understood that the embodiments disclosed in this application and the above description can enable those skilled in the art to use this application to implement this application. At the same time, this application is not limited to the embodiments mentioned above. Obvious modifications and variations of the embodiments mentioned in this application also fall within the scope of the principles of this application.

Claims

1. A method for monitoring and warning the stability of prefabricated building components, characterized in that, the method includes: extracting multiple construction nodes based on the target building engineering drawings and constructing a construction node sequence; based on the construction node sequence, performing simulation modeling according to the target building engineering drawings to generate multiple engineering construction simulation models; obtaining a sample data set of the multiple construction nodes, performing stable correlation factor analysis, and constructing a node factor mapping sequence; using the node factor mapping sequence as monitoring data, performing construction monitoring based on the construction node sequence, and determining the construction monitoring data of the first construction node; mapping and obtaining the first engineering construction simulation model based on the construction monitoring data, and performing error analysis on the construction monitoring data and the first construction simulation model through a twin comparison channel to determine the first construction error; generating a construction warning signal based on the first construction error, and obtaining a first construction compensation parameter according to the construction warning signal for subsequent construction compensation of the target building project.

2. The method according to claim 1, characterized in that, the obtaining a sample data set of the multiple construction nodes, performing stable correlation factor analysis, and constructing a node factor mapping sequence further includes: randomly selecting a first construction node from the multiple construction nodes and obtaining a first sample data set of the first construction node; taking construction stability as the goal, performing stable correlation factor analysis on the first sample data set in sequence to determine multiple first stable correlation factor sets; marking the first stable correlation factors with a frequency of occurrence greater than a preset frequency threshold in the multiple first stable correlation factor sets as first main correlation factors to obtain a first main correlation factor set; constructing a node factor mapping sequence based on the mapping relationship between the first construction node and the first main correlation factor set.

3. The method according to claim 1, characterized in that, the performing error analysis on the construction monitoring data and the first construction simulation model through a twin comparison channel to determine the first construction error further includes: the twin comparison channel includes a first twin channel, a second twin channel, and a similarity comparison sub-channel, wherein the first twin channel is embedded with an engineering construction simulation model; inputting the construction monitoring data into the second twin channel, and obtaining the first engineering construction simulation model in the first twin channel based on the mapping of the construction monitoring data; extracting first construction standard data based on the first construction simulation model, and inputting the construction monitoring data and the first construction standard data into the similarity comparison sub-channel for construction error analysis, and outputting the first construction error.

4. The method according to claim 3, characterized in that, the method further includes: Construct an error similarity analysis function: Among them, S is the first construction error, n is the number of types of construction monitoring data at the first construction node, w i is the weight of the i-th construction monitoring data, y i is the i-th construction monitoring data, Y i is the i-th construction standard data.

5. The method according to claim 1, characterized in that, the generating a construction warning signal based on the first construction error further includes: obtaining a preset first construction error threshold; when the first construction error is greater than the first construction error threshold, generating a construction warning signal, wherein the construction warning signal carries a first construction node identifier.

6. The method according to claim 5, characterized in that, Performing construction compensation for the subsequent target building project by obtaining the first construction compensation parameter according to the construction warning signal further includes: Training a construction compensation model with multiple historical construction data to obtain a construction compensation model that meets the expected indicators; Performing compensation analysis on the first construction error through the construction compensation model and outputting the first construction compensation parameter.

7. An assembly building component stability monitoring and warning system Characterized in that The system includes: A node extraction module for extracting multiple construction nodes based on the target building project drawings and constructing a construction node sequence; A simulation modeling module for performing simulation modeling based on the construction node sequence according to the target building project drawings to generate multiple engineering construction simulation models; An association analysis module for obtaining a sample data set of the multiple construction nodes, performing stable association factor analysis, and constructing a node factor mapping sequence; A construction monitoring module for using the node factor mapping sequence as monitoring data and performing construction monitoring based on the construction node sequence to determine the construction monitoring data of the first construction node; The construction monitoring data of the first construction node; A simulation analysis module for obtaining the first engineering construction simulation model based on the mapping of the construction monitoring data, and performing error analysis on the construction monitoring data and the first construction simulation model through a twin comparison channel to determine the first construction error; A construction warning module for generating a construction warning signal based on the first construction error and obtaining the first construction compensation parameter according to the construction warning signal for performing construction compensation for the subsequent target building project.

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