Fabricated house structure health monitoring method and system

Abstract

The invention discloses an assembly type house structure health monitoring method and system, and relates to the technical field of house monitoring, and the method comprises the steps: building a three-dimensional model of an assembly type house, carrying out the simulation of the three-dimensional model through historical environment data, and obtaining the deformation and stress data of the three-dimensional model; dividing the three-dimensional model into a plurality of monitoring areas; establishing a target function; solving the objective function to obtain a sensor mounting position; a sensor is installed in the fabricated house, and real-time state data are collected; acquiring real-time environment data of the fabricated house; and performing inversion correction on the real-time state data according to the real-time environment data, and performing structural health assessment on the fabricated house by using the corrected data. According to the method, the installation positions of the sensors are optimized, meanwhile, the data collected by the sensors are subjected to inversion correction, the data, as accurate as possible, of the multiple positions can be obtained only through a few sensors, and a foundation is laid for improving the accuracy of the structural health assessment result.

Description

Technical Field

[0001] The present application relates to the technical field of housing monitoring, and in particular to a method and system for monitoring the health of prefabricated housing structures. Background Art

[0002] Prefabricated houses are a new type of building form. The various components of the house are pre-fabricated in the factory and then assembled on the construction site. The buildings constructed in this way are not only basically the same as traditional cast-in-place buildings in performance, but also have a very short construction time on the construction site, thus greatly saving construction time and costs.

[0003] Since prefabricated houses are made up of a large number of parts, these joints are prone to large deformations due to materials, connection methods, etc., which may adversely affect the health of the house structure. Therefore, real-time monitoring of the structural health of prefabricated houses is very necessary.

[0004] The Chinese invention patent with publication number CN116542111A discloses a method and system for monitoring the structural health of the connection nodes of prefabricated house buildings. It uses CAE (computer-aided engineering) simulation to determine the locations where the structural deformation or stress of the house is large. After setting corresponding sensors at these locations to collect deformation and stress data, the structural health of the house can be evaluated in real time. However, during the use of the house, when the external environment, such as geology, strong winds, etc., changes, the deformation and stress of the house will also change. Therefore, the location with the largest deformation and stress may deviate from the location where the sensor is installed, resulting in inaccurate data monitored by the sensor, which in turn affects the accuracy of the structural health assessment. Summary of the invention

[0005] The embodiments of the present application provide a method and system for monitoring the health of a prefabricated house structure, which is used to solve the problem in the prior art that sensors are set at locations with the largest deformation and stress determined by CAE simulation and cannot be applied to a variety of external environments.

[0006] On the one hand, an embodiment of the present application provides a method for monitoring the health of a prefabricated house structure, comprising: Obtain historical environmental data for housing assembly locations; Establish a 3D model of the prefabricated house, simulate the 3D model using historical environmental data, and obtain the deformation and stress data of the 3D model; According to the distribution of deformation and stress data in the three-dimensional model, the three-dimensional model is divided into multiple monitoring areas; Analyze the local maximum values ​​of deformation and stress data in each monitoring area, and establish an objective function with the goal of minimizing the sum of the distances between the locations of all local maximum values ​​in a monitoring area and the sensor installation location; Genetic algorithm is used to solve the objective function and obtain the sensor installation location in each monitoring area; Install corresponding sensors at each sensor installation position of the prefabricated house to collect real-time status data of the prefabricated house; Obtain real-time environmental data of prefabricated houses; Invert and correct the real-time status data according to the real-time environmental data to obtain the measurement status data; Conduct structural health assessments of manufactured homes using measured condition data.

[0007] In one possible implementation, after a three-dimensional model is established using CAE technology, historical environmental data at different times are sequentially imported, and the three-dimensional model is simulated under the influence of the historical environmental data to obtain deformation and stress data.

[0008] In one possible implementation, simulations are performed sequentially using historical environmental data at different times to obtain a plurality of corresponding deformation and stress data, which are then superimposed on the same three-dimensional model to obtain the distribution of the deformation and stress data in the three-dimensional model.

[0009] In one possible implementation, when the three-dimensional model is divided into multiple monitoring areas, the number of deformation monitoring areas and the number of stress monitoring areas are determined according to a preset number of sensors, and the K-means clustering algorithm is used to perform cluster analysis on the local maximum deformation and the local maximum stress in the deformation and stress data, respectively, to obtain multiple deformation monitoring areas and multiple stress monitoring areas.

[0010] In one possible implementation, after the deformation and stress data are superimposed in the same three-dimensional model, each deformation monitoring area has multiple local deformation maxima, and each stress monitoring area also has multiple local stress maxima. Each local deformation maximum and each local stress maximum are respectively located at a position in the three-dimensional model. After determining the position of each local deformation maximum and each local stress maximum, an objective function is established.

[0011] In one possible implementation, when inverting and correcting the real-time status data, the three-dimensional model is simulated using the real-time environmental data to obtain the simulation status data of each position in the three-dimensional model, the simulation status data corresponding to the installation position of the sensor in the three-dimensional model is extracted, the difference between the simulation status data and the real-time status data is determined, the simulation status data of each position in the three-dimensional model is corrected according to the difference, and the local maximum value in the corrected simulation status data is extracted as the measurement status data.

[0012] In a possible implementation, the historical environmental data includes historical geological data and historical wind data, and the real-time environmental data includes real-time geological data and real-time wind data.

[0013] In a possible implementation, after the measurement status data is obtained, the measurement status data is displayed in the three-dimensional model, and the result of the structural health assessment is also displayed simultaneously with the three-dimensional model integrating the measurement status data.

[0014] On the other hand, the embodiment of the present application further provides a prefabricated house structure health monitoring system, including: A data acquisition module, used to acquire historical environmental data of the housing assembly location; The three-dimensional simulation module is used to establish a three-dimensional model of the prefabricated house, simulate the three-dimensional model using historical environmental data, and obtain the deformation and stress data of the three-dimensional model; A region division module is used to divide the three-dimensional model into multiple monitoring regions according to the distribution of deformation and stress data in the three-dimensional model; The target establishment module is used to analyze the local maximum values ​​of deformation and stress data in each monitoring area, and establish the target function with the goal of minimizing the sum of the distances between the positions of all local maximum values ​​in a monitoring area and the sensor installation position; A location determination module is used to solve the objective function using a genetic algorithm to obtain the sensor installation location in each monitoring area; A sensor is installed at each sensor installation position of the prefabricated house to collect real-time status data and real-time environmental data of the prefabricated house; A data correction module is used to invert and correct the real-time state data according to the real-time environmental data to obtain the measurement state data; The structural assessment module is used to perform structural health assessments on prefabricated houses using measured status data.

[0015] The present invention provides a method and system for monitoring the health of prefabricated housing structures, which has the following advantages: The sensor installation locations are optimized to respond better in a variety of external environments. At the same time, the data collected by the sensors are inverted and corrected. Only a few sensors can be used to obtain the most accurate status data possible at multiple locations in the prefabricated house, laying the foundation for improving the accuracy of structural health assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A flowchart of a method for monitoring the structural health of a prefabricated house provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0019] Figure 1 A flowchart of a method for monitoring the health of a prefabricated house structure provided in an embodiment of the present application. The present application embodiment provides a method for monitoring the health of a prefabricated house structure, comprising: S100, obtaining historical environmental data of a housing assembly location.

[0020] Exemplarily, the historical environmental data includes historical geological data and historical wind data, which can be collected by multiple sensors set at the housing assembly position. For geological data, a fiber grating inclinometer can be used to collect ground settlement data and use it as historical geological data. For wind data, an anemometer can be set at an appropriate height on the ground to collect wind data at multiple different times. It should be understood that since the impact of wind on the house is not limited to the size of the wind, but also related to the wind direction, wind direction data can be collected while collecting wind force, and the wind direction data can be used as part of the historical environmental data.

[0021] S110, establishing a three-dimensional model of the prefabricated house, simulating the three-dimensional model using historical environmental data, and obtaining deformation and stress data of the three-dimensional model.

[0022] For example, CAE software can be used to build a three-dimensional model, and then historical environmental data at different times can be imported into the CAE software in sequence. The three-dimensional model can be simulated in the CAE software under the influence of the historical environmental data to obtain deformation and stress data.

[0023] Commonly used CAE software includes ANSYS, ABAQUS, etc. These software can be used to perform mechanical analysis on prefabricated houses and generate deformation and stress data of prefabricated houses at various locations.

[0024] S120, dividing the three-dimensional model into a plurality of monitoring areas according to the distribution of the deformation and stress data in the three-dimensional model.

[0025] Exemplarily, since the historical environmental data is a plurality of data groups at different times, each data group will generate a set of deformation and stress data, and after simulation, these deformation and stress data will be displayed on the three-dimensional model, thereby forming a plurality of three-dimensional models that integrate deformation and stress data. In order to estimate the impact of future environmental data on prefabricated houses through historical environmental data of the past period of time, and then obtain a more accurate sensor installation location, it is necessary to merge all three-dimensional models that integrate deformation and stress data together. Since the three-dimensional models are the same, the data in each three-dimensional model and the position in the three-dimensional model can be extracted, and then superimposed and displayed in the same three-dimensional model. At this time, the three-dimensional model can show the impact of all historical environmental data, and its distribution in the three-dimensional model can be obtained by analyzing these superimposed data.

[0026] In the embodiment of the present application, the deformation and stress data include two parts, namely, deformation data and stress data. Since these two types of data are analyzed separately using CAE software, two three-dimensional models integrating deformation data and stress data respectively will be obtained after superposition.

[0027] Furthermore, when the three-dimensional model is divided into multiple monitoring areas, the number of deformation monitoring areas and the number of stress monitoring areas are determined according to the pre-set number of sensors, and the K-means clustering algorithm is used to perform cluster analysis on the local maximum deformation and the local maximum stress in the deformation and stress data, respectively, to obtain multiple deformation monitoring areas and multiple stress monitoring areas.

[0028] Specifically, the number of sensors installed in the prefabricated house is generally determined in advance, but the installation location needs to be determined according to the actual situation. The sensors in the embodiment of the present application include deformation sensors and stress sensors, each deformation sensor is used to monitor the situation in a deformation monitoring area, and each stress sensor is used to monitor the situation in a stress monitoring area. Therefore, the number of deformation monitoring areas needs to be the same as the number of deformation sensors, and the number of stress monitoring areas needs to be the same as the number of stress sensors.

[0029] After determining the number of monitoring areas, the number of clusters can be directly adopted when clustering using the K-means clustering algorithm. Based on this setting, the deformation data and stress data in the three-dimensional model can be clustered and analyzed separately to obtain multiple deformation monitoring areas and stress monitoring areas.

[0030] Before cluster analysis, it is necessary to determine the local maximum values ​​of deformation and stress at each position after superposition in the three-dimensional model. It should be noted that when the deformation data and stress data are superimposed in the three-dimensional model in the embodiment of the present application, the deformation data and stress data at different times are independent of each other, that is, the values ​​are not superimposed, and the data of multiple time points are only displayed at the same position of the three-dimensional model at the same time. Therefore, the determination of the local maximum is carried out in the deformation data and stress data at the same time point. In the embodiment of the present application, the local maximum is the maximum value after comparing the data of adjacent points in all directions around. Based on this principle, a large number of deformation local maximum values ​​and stress local maximum values ​​can be calculated in the deformation data and stress data at a time point. These local maximum values ​​are distributed in the three-dimensional model, so each local maximum value has a corresponding position. The values ​​and positions of these local maximum values ​​are clustered by the K-means clustering algorithm, and several local maximum values ​​can be clustered into one monitoring area, thereby obtaining multiple monitoring areas.

[0031] S130, analyzing the local maximum values ​​of deformation and stress data in each monitoring area, and establishing an objective function with the goal of minimizing the sum of distances between the positions of all local maximum values ​​in a monitoring area and the sensor installation position.

[0032] Exemplarily, after superimposing the deformation and stress data in the same three-dimensional model, each deformation monitoring area has multiple local deformation maxima, and each stress monitoring area also has multiple local stress maxima. Each local deformation maximum and each local stress maximum are respectively located at a position in the three-dimensional model. After determining the position of each local deformation maximum and each local stress maximum, an objective function is established.

[0033] Before establishing the objective function, the local maximum values ​​in each monitoring area can be normalized. According to the largest local maximum value and the smallest local maximum value at all time points, each local maximum value can be normalized to the range of [0,1]. These normalized local maxima can be added as weights in the objective function to reflect the influence of local maximum values ​​on distance.

[0034] The objective function can be expressed as:

[0035] in, F represents the objective function, i is the label of the location of the local maximum in the three-dimensional model, N is the number of locations with local maxima, After normalization, i The weight of the location of the local maximum, For the i The distance between the location of the local maximum and the sensor installation location.

[0036] S140, using a genetic algorithm to solve the objective function and obtain the sensor installation position in each monitoring area.

[0037] S150, installing a corresponding sensor at each sensor installation position of the prefabricated house to collect real-time status data of the prefabricated house.

[0038] Exemplarily, the real-time status data includes real-time deformation data and real-time stress data. The real-time deformation data can be collected by using a deformation sensor, and the real-time stress data can be collected by using a stress sensor.

[0039] S160, obtaining real-time environmental data of the prefabricated house.

[0040] For example, the types of real-time environmental data are the same as those of historical environmental data, including real-time geological data and real-time wind data, and it should be understood that real-time wind direction associated with real-time wind data in time should also be included. These data can be continuously collected by sensors that collect historical environmental data.

[0041] S170, invert and correct the real-time status data according to the real-time environmental data to obtain measurement status data.

[0042] Exemplarily, when inverting and correcting the real-time status data, the three-dimensional model is simulated using the real-time environmental data to obtain the simulation status data of each position in the three-dimensional model, the simulation status data corresponding to the installation position of the sensor in the three-dimensional model is extracted, the difference between the simulation status data and the real-time status data is determined, the simulation status data of each position in the three-dimensional model is corrected according to the difference, and the local maximum value in the corrected simulation status data is extracted as the measurement status data.

[0043] Specifically, although there is a certain correlation between historical environmental data and real-time environmental data, there are still some differences between the two. Therefore, the real-time environmental data can be used to obtain simulated state data that can reflect the current state through simulation. It should be understood that the simulated state data is the data obtained after simulating all positions in the three-dimensional model, and there must be data corresponding to the sensor installation position. Therefore, after extracting the data corresponding to the sensor installation position in the simulated state data, the difference between the extracted data and the real-time state data is calculated. This difference reflects the deviation caused by the simulation process and the actual situation. The smaller this difference is, the more accurate the simulation is.

[0044] After subtracting the difference from the simulation state data of all positions in the three-dimensional model, the corrected simulation state data can be obtained.

[0045] Since the sensor installation position has been optimized in this application, one sensor can be used to collect deformation and stress data under various possible conditions in a monitoring area. Since the deformation and stress data are continuous within a certain distance range, after optimizing the sensor installation position, the deformation and stress data collected at one position can more accurately reflect the deformation and stress conditions at other positions. Combined with the inversion correction process, the accuracy of the estimation of the local maximum value can be improved.

[0046] S180, using measurement status data to perform structural health assessment of prefabricated houses.

[0047] Exemplarily, after the measurement status data is obtained, the measurement status data is displayed in the three-dimensional model, and the result of the structural health assessment is also displayed simultaneously with the three-dimensional model integrating the measurement status data.

[0048] The present application also provides a prefabricated house structure health monitoring system, which includes: A data acquisition module, used to acquire historical environmental data of the housing assembly location; The three-dimensional simulation module is used to establish a three-dimensional model of the prefabricated house, simulate the three-dimensional model using historical environmental data, and obtain the deformation and stress data of the three-dimensional model; A region division module is used to divide the three-dimensional model into multiple monitoring regions according to the distribution of deformation and stress data in the three-dimensional model; The target establishment module is used to analyze the local maximum values ​​of deformation and stress data in each monitoring area, and establish the target function with the goal of minimizing the sum of the distances between the positions of all local maximum values ​​in a monitoring area and the sensor installation position; A location determination module is used to solve the objective function using a genetic algorithm to obtain the sensor installation location in each monitoring area; A sensor is installed at each sensor installation position of the prefabricated house to collect real-time status data and real-time environmental data of the prefabricated house; A data correction module is used to invert and correct the real-time state data according to the real-time environmental data to obtain the measurement state data; The structural assessment module is used to perform structural health assessments on prefabricated houses using measured status data.

[0049] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0050] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for monitoring the health of a prefabricated house structure, characterized in that: include: Obtain historical environmental data for housing assembly locations; Establishing a three-dimensional model of the prefabricated house, and simulating the three-dimensional model using the historical environmental data to obtain deformation and stress data of the three-dimensional model; Dividing the three-dimensional model into a plurality of monitoring areas according to the distribution of the deformation and stress data in the three-dimensional model; Analyze the local maximum values ​​of the deformation and stress data in each monitoring area, and establish an objective function with the goal of minimizing the sum of distances between the positions of all the local maximum values ​​in one monitoring area and the sensor installation position; Using a genetic algorithm to solve the objective function, and obtain the sensor installation position in each monitoring area; Install a corresponding sensor at each of the sensor installation positions of the prefabricated house to collect real-time status data of the prefabricated house; Obtain real-time environmental data of prefabricated houses; Invert and correct the real-time status data according to the real-time environmental data to obtain measurement status data; The measured status data is used to perform a structural health assessment on the prefabricated house.

2. A method for monitoring the health of a prefabricated house structure according to claim 1, characterized in that: After the three-dimensional model is established by using CAE technology, the historical environmental data at different times are sequentially imported, and the three-dimensional model is simulated under the influence of the historical environmental data to obtain the deformation and stress data.

3. A method for monitoring the health of a prefabricated house structure according to claim 2, characterized in that: After performing simulations in sequence using the historical environmental data at different times, a plurality of corresponding deformation and stress data are obtained respectively, and the plurality of deformation and stress data are superimposed in the same three-dimensional model to obtain the distribution of the deformation and stress data in the three-dimensional model.

4. A method for monitoring the health of a prefabricated house structure according to claim 3, characterized in that: When the three-dimensional model is divided into a plurality of monitoring areas, the number of deformation monitoring areas and the number of stress monitoring areas are determined according to a preset number of sensors, and a K-means clustering algorithm is used to perform cluster analysis on the local maximum values ​​of deformation and the local maximum values ​​of stress in the deformation and stress data, respectively, to obtain a plurality of deformation monitoring areas and a plurality of stress monitoring areas.

5. A method for monitoring the health of a prefabricated house structure according to claim 4, characterized in that: After superimposing the deformation and stress data in the same three-dimensional model, each deformation monitoring area has multiple local deformation maxima, and each stress monitoring area also has multiple local stress maxima. Each local deformation maximum and each local stress maximum are respectively located at a position of the three-dimensional model. After determining the position of each local deformation maximum and each local stress maximum, the objective function is established.

6. A method for monitoring the health of a prefabricated house structure according to claim 1, characterized in that: When the real-time status data is inverted and corrected, the three-dimensional model is simulated using the real-time environmental data to obtain simulation status data of each position in the three-dimensional model, the simulation status data corresponding to the installation position of the sensor in the three-dimensional model is extracted, the difference between the simulation status data and the real-time status data is determined, the simulation status data of each position in the three-dimensional model is corrected according to the difference, and the local maximum value in the corrected simulation status data is extracted as the measurement status data.

7. A method for monitoring the health of a prefabricated house structure according to claim 1, characterized in that: The historical environmental data includes historical geological data and historical wind data, and the real-time environmental data includes real-time geological data and real-time wind data.

8. A method for monitoring the health of a prefabricated house structure according to claim 1, characterized in that: After the measurement status data is obtained, the measurement status data is displayed in the three-dimensional model, and the result of the structural health assessment is also displayed simultaneously with the three-dimensional model in which the measurement status data is integrated.

9. A system using the method for monitoring the health of prefabricated house structures according to any one of claims 1 to 8, characterized in that: include: A data acquisition module, used to acquire historical environmental data of the housing assembly location; A three-dimensional simulation module, used to establish a three-dimensional model of the prefabricated house, and simulate the three-dimensional model using the historical environmental data to obtain deformation and stress data of the three-dimensional model; A region division module, used for dividing the three-dimensional model into a plurality of monitoring regions according to the distribution of the deformation and stress data in the three-dimensional model; A target establishment module, used for analyzing the local maximum values ​​of the deformation and stress data in each monitoring area, and establishing a target function with the goal of minimizing the sum of the distances between the positions of all the local maximum values ​​in one monitoring area and the sensor installation position; A position determination module, used for solving the objective function by using a genetic algorithm to obtain the sensor installation position in each monitoring area; A sensor, which is installed at each sensor installation position of the prefabricated house to collect real-time status data and real-time environmental data of the prefabricated house; A data correction module, used for inverting and correcting the real-time state data according to the real-time environmental data to obtain measurement state data; The structural assessment module is used to perform a structural health assessment on the prefabricated house using the measurement status data.

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