A method for visual comprehensive analysis of deformation monitoring of a structure

Abstract

The application discloses a kind of building deformation monitoring visual comprehensive analysis methods, belong to building deformation monitoring technical field, comprising the following steps: S1: instrument is laid out;S2: obtain point cloud data transmission to cloud server;S3: obtain elevation data transmission to cloud server;S4: obtain displacement data transmission to cloud server;S5: pre-process initial point cloud data;S6: pre-process initial elevation data;S7: pre-process initial displacement data;S8: construct three kinds of initial building three-dimensional model;S9: obtain existing data and carry out differentiating judgment;S10: generate existing building three-dimensional model and local building three-dimensional model, and generate deformation chart;S11: multi-screen display, analyze deformation reason;S12: reciprocating cycle;The application can intuitively view the deformation model of building, and can also intuitively view the corresponding deformation degree of building, which is beneficial to the deformation analysis of building.

Description

Technical Field

[0001] This invention belongs to the field of building deformation monitoring technology, specifically relating to a visual comprehensive analysis method for building deformation monitoring. Background Technology

[0002] During the construction and use of buildings, uneven geological structures of the foundation, different physical properties of the soil, plastic deformation of the subgrade, changes in groundwater level, changes in atmospheric temperature, and the effects of loads on the building itself, such as wind and vibration, can cause settlement, displacement, bending, tilting and cracking of buildings over time. These phenomena are collectively referred to as deformation. If the deformation of buildings is not addressed in a timely manner, it may endanger the safety and normal use of the buildings. Therefore, methods for monitoring the deformation of buildings have emerged.

[0003] Existing methods for monitoring the deformation of structures generally involve collecting data from the structure using instruments, then manually importing the collected data into data processing software for preprocessing to form initial data. Subsequently, the collected data is imported into the data processing software in real time and compared with the initial data. When discrepancies exist, the causes of deformation are analyzed based on the discrepancies. However, this method cannot intuitively display the results of the deformation of the structure and requires professional personnel to analyze the discrepancies. The effectiveness of this method still needs improvement. Summary of the Invention

[0004] To address the problems mentioned in the background section, this invention provides a comprehensive visualization and analysis method for monitoring and analyzing the deformation of structures. This method allows for both intuitive viewing of the deformation model and the degree of deformation, facilitating deformation analysis and yielding excellent results.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a comprehensive and visual analysis method for monitoring and analyzing the deformation of structures, comprising the following steps:

[0006] S1: Set up scanning points and install a 3D laser scanner with electronic positioning tags; set up settlement observation points and install a precision engineering level with electronic positioning tags; set up displacement observation points and install a total station and a distance measuring instrument with electronic positioning tags.

[0007] S2: The target structure is scanned on-site using a 3D laser scanner to collect complete and accurate original data of the target structure, and point cloud data with precise spatial information is obtained. The electronic positioning tag transmits the scanning positioning information to the cloud server through the AP locator. At the same time, the 3D laser scanner transmits the point cloud data to the cloud server through a wireless transmitter.

[0008] S3: The target structure is observed on-site using a precision engineering level, and complete and accurate original data of the target structure is collected to obtain elevation data with accurate spatial information. The electronic positioning tag transmits the scanning positioning information to the cloud server through the AP locator, while the precision engineering level transmits the elevation data to the cloud server through the wireless transmitter.

[0009] S4: The target structure is observed on-site using a total station and a rangefinder, and complete and accurate original data of the target structure is collected to obtain displacement data with precise spatial information. The electronic positioning tag transmits the scanning positioning information to the cloud server through the AP locator, while the total station and rangefinder transmit the displacement data to the cloud server through the wireless transmitter.

[0010] S5: The cloud server stores the transmitted point cloud data sequentially according to the positioning information and sets it as the initial point cloud database. The point cloud data in the initial point cloud database is sequentially spliced, denoised, classified and colored by the data preprocessing software to form the initial data of the three-dimensional model of the structure.

[0011] S6: The cloud server stores the transmitted elevation data sequentially according to the positioning information and sets it as the initial elevation database. The data preprocessing software performs sequential splicing, noise reduction, classification and coloring preprocessing on the elevation data in the initial elevation database to form the initial data of the three-dimensional model of the structure.

[0012] S7: The cloud server stores the transmitted displacement data sequentially according to the positioning information and sets it as the initial displacement database. The data preprocessing software performs sequential splicing, noise reduction, classification and coloring preprocessing on the displacement data in the initial displacement database to form the initial data of the three-dimensional model of the structure.

[0013] S8: Monitoring terminal A receives the initial data of three types of 3D models of the three structures from the cloud server in real time, and renders and generates three types of 3D models of the three structures. It compares the three initial 3D models of the three structures, judges the accuracy of any one of the 3D models of the three structures, and uses the three initial 3D models of the three structures as the three initial 3D models when there is no difference.

[0014] S9: The cloud server periodically sends acquisition commands to the 3D laser scanner, precision engineering level, total station, and distance measuring instrument. The 3D laser scanner, precision engineering level, total station, and distance measuring instrument periodically transmit structure point cloud data, elevation data, and displacement data to the cloud server. Upon receiving the structure point cloud data, elevation data, and displacement data, the cloud server performs a filtering and overlap search based on the positioning information and the data with the same positioning in the initial point cloud database, the original elevation database, and the original displacement database. If there is no difference, the cloud server does nothing; if there is a difference, the cloud server establishes a new existing point cloud database, an existing elevation database, an existing displacement database, and a difference point cloud database. The difference elevation database and the difference displacement database will receive point cloud data, elevation data, and displacement data with differences, as well as point cloud data, elevation data, and displacement data adjacent to each other, and store them sequentially in the existing point cloud database, the existing elevation database, the existing displacement database, and the difference point cloud database, the difference elevation database, and the difference displacement database, respectively, according to the positioning information. The point cloud data in the existing point cloud database, the existing elevation database, the existing displacement database, and the difference point cloud database, the difference elevation database, and the difference displacement database will be sequentially stitched, denoised, classified, and colored preprocessed by data preprocessing software to form the existing data and difference data of the 3D model of the structure.

[0015] S10: Monitoring terminals B and C receive existing and difference data of the 3D model of the structure from the cloud server in real time, and render and generate existing and local 3D models of the structure to complete the data monitoring of settlement deformation, displacement deformation, tilt deformation, crack deformation, etc. of the target structure. Monitoring terminal D receives difference data of the 3D model of the structure from the cloud server in real time and generates deformation charts based on the difference data.

[0016] S11: Analyze the causes of the deformation of the structure by displaying the initial 3D model of the structure, the existing 3D model of the structure, the local 3D model of the structure and the deformation analysis chart on multiple screens.

[0017] S12: Following this pattern, the cloud server receives point cloud data, elevation data, and displacement data from the 3D laser scanner, precision engineering level, total station, and rangefinder. It then establishes new historical point cloud databases, historical elevation databases, and historical displacement databases. The previously received point cloud data, elevation data, and displacement data are stored in these databases, and existing point cloud data, elevation data, and displacement data are stored in the existing point cloud database, existing elevation database, and existing displacement database. This process is repeated continuously.

[0018] Preferably, in step S1, an environmental monitoring sensor including a temperature sensor, a humidity sensor, a wind sensor, and a rainfall sensor is installed to obtain environmental data of the target structure.

[0019] Preferably, in step S1, if the 3D laser scanner, precision engineering level, total station, or rangefinder malfunctions and needs to be replaced after long-term operation, it can be re-set based on the positioning information of the electronic positioning tag without the need for re-measurement and re-setting.

[0020] Preferably, in steps S5, 6, and 7, if the preprocessing software discovers missing data during the sequential stitching of stored point cloud data, elevation data, or displacement data, it stops denoising, classification, and coloring preprocessing. Simultaneously, the cloud server extracts the location information of the missing data and sends an instruction to the staff to re-collect the point cloud data, elevation data, or displacement data of the target structure at the location of the missing data, until the point cloud data, elevation data, or displacement data in the stitching process can completely construct the three-dimensional model of the structure to proceed to the next step.

[0021] Preferably, in step S10, the difference data is stored in the form of difference values ​​plus arrows. The difference value is based on the difference between the initial value and the current value of the point cloud data, and the arrow points in the direction of displacement change.

[0022] Preferably, in step S10, the deformed chart is generated by interpolating the difference data, i.e., the regional change amount, using the spatial interpolation analysis related interface in the ArcENGINE plugin.

[0023] Preferably, in step S11, the analysis results of the deformation causes can be stored on the monitoring terminal E. At the same time, the deformation data of the structure and the corresponding deformation causes are used as training samples to train the deformation cause analysis model on the monitoring terminal E. The monitoring terminal E shares data with the monitoring terminals C and D via USB, which can quickly pre-analyze the deformation causes of the structure in the later stage.

[0024] Compared with the prior art, the beneficial effects of the present invention are:

[0025] 1. This invention uses a 3D laser scanner to scan the point cloud data of a structure and transmits it to a cloud server. The cloud server preprocesses the point cloud data to form initial 3D model data and existing 3D model data. By filtering and overlapping the initial and existing 3D model data, the difference data is filtered out. The monitoring terminal displays the initial 3D model, the existing 3D model, and the difference 3D model in a split-screen manner to visualize the deformation data of the structure. The monitoring terminal also displays the deformation chart generated by the ArcENGINE plugin to analyze the deformation data of the structure. This allows for a direct view of the deformation model of the structure and the corresponding degree of deformation, which is beneficial for the deformation analysis of the structure.

[0026] 2. The present invention configures an electronic positioning tag on the 3D laser scanner. When the 3D laser scanner transmits point cloud data, the electronic positioning tag transmits positioning information to the cloud server in real time, enabling the cloud server to store the point cloud data in an orderly manner according to the positioning information. This facilitates the subsequent point cloud data stitching preprocessing and the construction of 3D models of structures. At the same time, when the 3D laser scanner is replaced due to failure, it can be directly set up at the positioning information position of the electronic positioning tag without the need for re-measurement and re-setting, which is convenient and quick.

[0027] 3. In this invention, the causes of deformation in each structure analysis are stored on the monitoring terminal and used in conjunction with the structure deformation data as training samples for the structure deformation analysis model. After the model training is completed, the structure deformation is analyzed by the model first, which reduces the workload of staff and improves accuracy, pertinence and speed. Attached Figure Description

[0028] Figure 1 This is a flowchart of the visualization and comprehensive analysis method for monitoring the deformation of structures according to the present invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Please see Figure 1 The present invention provides the following technical solution: a comprehensive and visual analysis method for monitoring the deformation of structures, comprising the following steps:

[0031] S1: Set up scanning points using a 3D laser scanner with electronic positioning tags; set up settlement observation points using a precision engineering level with electronic positioning tags; set up displacement observation points using a total station and distance measuring instrument with electronic positioning tags; and set up environmental monitoring sensors including temperature sensors, humidity sensors, wind sensors, and rainfall sensors to obtain environmental data of the target structure. If the 3D laser scanner, precision engineering level, total station, or distance measuring instrument malfunctions and needs to be replaced after long-term operation, it can be re-set up directly based on the positioning information of the electronic positioning tags without the need for re-measurement and re-positioning.

[0032] S2: The target structure is scanned on-site using a 3D laser scanner to collect complete and accurate original data of the target structure, and point cloud data with precise spatial information is obtained. The electronic positioning tag transmits the scanning positioning information to the cloud server through the AP locator. At the same time, the 3D laser scanner transmits the point cloud data to the cloud server through a wireless transmitter.

[0033] S3: The target structure is observed on-site using a precision engineering level, and complete and accurate original data of the target structure is collected to obtain elevation data with accurate spatial information. The electronic positioning tag transmits the scanning positioning information to the cloud server through the AP locator, while the precision engineering level transmits the elevation data to the cloud server through the wireless transmitter.

[0034] S4: The target structure is observed on-site using a total station and a rangefinder, and complete and accurate original data of the target structure is collected to obtain displacement data with precise spatial information. The electronic positioning tag transmits the scanning positioning information to the cloud server through the AP locator, while the total station and rangefinder transmit the displacement data to the cloud server through the wireless transmitter.

[0035] S5: The cloud server stores the transmitted point cloud data sequentially based on the location information, setting it as the initial point cloud database. The data preprocessing software performs sequential stitching, denoising, classification, and coloring preprocessing on the point cloud data in the initial point cloud database. If the preprocessing software finds missing data during the sequential stitching of the stored point cloud data, it stops the denoising, classification, and coloring preprocessing. At the same time, the cloud server extracts the location information of the missing data and sends an instruction to the staff to re-collect the point cloud data of the target structure at the location information until the point cloud data in the stitching process can completely construct the three-dimensional model of the structure and proceed to the next step, forming the initial data of the three-dimensional model of the structure.

[0036] S6: The cloud server stores the transmitted elevation data sequentially based on the positioning information, setting it as the initial elevation database. The data preprocessing software performs sequential splicing, noise reduction, classification, and coloring preprocessing on the elevation data in the initial elevation database. If the preprocessing software finds missing data during the sequential splicing of the stored elevation data, it stops the noise reduction, classification, and coloring preprocessing. At the same time, the cloud server extracts the positioning information of the missing data and sends an instruction to the staff to re-collect the elevation data of the target structure at the location of the positioning information until the elevation data in the splicing process can completely construct the three-dimensional model of the structure and proceed to the next step, forming the initial data of the three-dimensional model of the structure.

[0037] S7: The cloud server stores the transmitted displacement data sequentially based on the positioning information, setting it as the initial displacement database. The data preprocessing software performs sequential splicing, denoising, classification, and coloring preprocessing on the displacement data in the initial displacement database. If the preprocessing software finds missing data during the sequential splicing of the stored displacement data, it stops the denoising, classification, and coloring preprocessing. At the same time, the cloud server extracts the positioning information of the missing data and sends an instruction to the staff to re-collect the displacement data of the target structure at the location of the positioning information until the displacement data in the splicing process can completely construct the three-dimensional model of the structure and proceed to the next step, forming the initial data of the three-dimensional model of the structure.

[0038] S8: Monitoring terminal A receives the initial data of three types of 3D models of the three structures from the cloud server in real time, and renders and generates three types of 3D models of the three structures. It compares the three initial 3D models of the three structures, judges the accuracy of any one of the 3D models of the three structures, and uses the three initial 3D models of the three structures as the three initial 3D models when there is no difference.

[0039] S9: The cloud server periodically sends acquisition commands to the 3D laser scanner, precision engineering level, total station, and distance measuring instrument. These instruments periodically transmit point cloud data, elevation data, and displacement data of the structure to the cloud server. Upon receiving the point cloud data, elevation data, and displacement data, the cloud server performs a selective overlap search based on the location information and the data with the same location in the initial point cloud database, original elevation database, and original displacement database. If there is no difference, the cloud server takes no action. If there is a difference, the cloud server establishes new databases for existing point cloud, existing elevation, and existing displacement, as well as databases for different point cloud, different elevation, and different displacement. The received point cloud data with differences will be processed accordingly. Data, elevation data, displacement data, and point cloud data with differences and adjacent differences are stored sequentially in the existing point cloud database, existing elevation database, existing displacement database, and difference point cloud database, difference elevation database, and difference displacement database according to the positioning information. Among them, the difference value is based on the difference between the initial value and the current value of the point cloud data, and the direction of the arrow is based on the direction of displacement change. The point cloud data in the existing point cloud database, existing elevation database, existing displacement database, difference point cloud database, difference elevation database, and difference displacement database are sequentially stitched, denoised, classified, and colored preprocessed by data preprocessing software to form the existing data and difference data of the 3D model of the structure.

[0040] S10: Monitoring terminals B and C receive existing and differential data of the 3D model of the structure from the cloud server in real time, and render and generate existing and local 3D models of the structure to complete the data monitoring of settlement deformation, displacement deformation, tilt deformation, crack deformation, etc. of the target structure. Monitoring terminal D receives differential data of the 3D model of the structure from the cloud server in real time, and uses the spatial interpolation analysis interface in the ArcENGINE plugin to interpolate the differential data, i.e., the regional change amount, to generate deformation charts.

[0041] S11: By displaying the initial 3D model of the structure, the existing 3D model of the structure, the local 3D model of the structure, and the deformation analysis charts on multiple screens, the causes of deformation of the structure are analyzed. The results of the deformation cause analysis can be stored on the monitoring terminal E. At the same time, the deformation data of the structure and the corresponding deformation causes are used as training samples to train the deformation cause analysis model on the monitoring terminal E. The monitoring terminal E shares data with the monitoring terminals C and D via USB, which can quickly pre-analyze the causes of deformation of the structure in the later stage.

[0042] S12: Following this pattern, the cloud server receives point cloud data, elevation data, and displacement data from the 3D laser scanner, precision engineering level, total station, and rangefinder. It then establishes new historical point cloud databases, historical elevation databases, and historical displacement databases. The previously received point cloud data, elevation data, and displacement data are stored in these databases, and existing point cloud data, elevation data, and displacement data are stored in the existing point cloud database, existing elevation database, and existing displacement database. This process is repeated continuously.

[0043] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A comprehensive and visual analysis method for monitoring and analyzing the deformation of structures, characterized in that, Includes the following steps: S1: Set up scanning points and install a 3D laser scanner with electronic positioning tags; set up settlement observation points and install a precision engineering level with electronic positioning tags; set up displacement observation points and install a total station and a distance measuring instrument with electronic positioning tags. S2: The target structure is scanned on-site using a 3D laser scanner to collect complete and accurate original data of the target structure, and point cloud data with precise spatial information is obtained. The electronic positioning tag transmits the scanning positioning information to the cloud server through the AP locator. At the same time, the 3D laser scanner transmits the point cloud data to the cloud server through a wireless transmitter. S3: The target structure is observed on-site using a precision engineering level, and complete and accurate original data of the target structure is collected to obtain elevation data with accurate spatial information. The electronic positioning tag transmits the scanning positioning information to the cloud server through the AP locator, while the precision engineering level transmits the elevation data to the cloud server through the wireless transmitter. S4: The target structure is observed on-site using a total station and a rangefinder, and complete and accurate original data of the target structure is collected to obtain displacement data with precise spatial information. The electronic positioning tag transmits the scanning positioning information to the cloud server through the AP locator, while the total station and rangefinder transmit the displacement data to the cloud server through the wireless transmitter. S5: The cloud server stores the transmitted point cloud data sequentially according to the positioning information and sets it as the initial point cloud database. The point cloud data in the initial point cloud database is sequentially spliced, denoised, classified and colored by the data preprocessing software to form the initial data of the three-dimensional model of the structure. S6: The cloud server stores the transmitted elevation data sequentially according to the positioning information and sets it as the initial elevation database. The data preprocessing software performs sequential splicing, noise reduction, classification and coloring preprocessing on the elevation data in the initial elevation database to form the initial data of the three-dimensional model of the structure. S7: The cloud server stores the transmitted displacement data sequentially according to the positioning information and sets it as the initial displacement database. The data preprocessing software performs sequential splicing, noise reduction, classification and coloring preprocessing on the displacement data in the initial displacement database to form the initial data of the three-dimensional model of the structure. S8: Monitoring terminal A receives the initial data of three types of 3D models of the three structures from the cloud server in real time, and renders and generates three types of 3D models of the three structures. It compares the three initial 3D models of the three structures, judges the accuracy of any one of the 3D models of the three structures, and uses the three initial 3D models of the three structures as the three initial 3D models when there is no difference. S9: The cloud server periodically sends acquisition commands to the 3D laser scanner, precision engineering level, total station, and distance measuring instrument. The 3D laser scanner, precision engineering level, total station, and distance measuring instrument periodically transmit structure point cloud data, elevation data, and displacement data to the cloud server. Upon receiving the structure point cloud data, elevation data, and displacement data, the cloud server performs a filtering and overlap search based on the positioning information and the data with the same positioning in the initial point cloud database, the original elevation database, and the original displacement database. If there is no difference, the cloud server does nothing; if there is a difference, the cloud server establishes a new existing point cloud database, an existing elevation database, an existing displacement database, and a difference point cloud database. The difference elevation database and the difference displacement database will receive point cloud data, elevation data, and displacement data with differences, as well as point cloud data, elevation data, and displacement data adjacent to each other, and store them sequentially in the existing point cloud database, the existing elevation database, the existing displacement database, and the difference point cloud database, the difference elevation database, and the difference displacement database, respectively, according to the positioning information. The point cloud data in the existing point cloud database, the existing elevation database, the existing displacement database, and the difference point cloud database, the difference elevation database, and the difference displacement database will be sequentially stitched, denoised, classified, and colored preprocessed by data preprocessing software to form the existing data and difference data of the 3D model of the structure. S10: Monitoring terminals B and C receive the existing and difference data of the 3D model of the structure from the cloud server in real time, and render and generate the existing 3D model of the structure and the local 3D model of the structure to complete the data monitoring of settlement deformation, displacement deformation, tilt deformation and crack deformation of the target structure. Monitoring terminal D receives the difference data of the 3D model of the structure from the cloud server in real time and generates deformation charts based on the difference data. S11: Analyze the causes of the deformation of the structure by displaying the initial 3D model of the structure, the existing 3D model of the structure, the local 3D model of the structure and the deformation analysis chart on multiple screens. S12: Following this pattern, the cloud server receives point cloud data, elevation data, and displacement data from the 3D laser scanner, precision engineering level, total station, and rangefinder. It then establishes new historical point cloud databases, historical elevation databases, and historical displacement databases. The previously received point cloud data, elevation data, and displacement data are stored in these databases, and existing point cloud data, elevation data, and displacement data are stored in the existing point cloud database, existing elevation database, and existing displacement database. This process is repeated continuously.

2. The visualization and comprehensive analysis method for monitoring the deformation of structures according to claim 1, characterized in that: In step S1, an environmental monitoring sensor, including a temperature sensor, a humidity sensor, a wind sensor, and a rainfall sensor, is installed to obtain environmental data of the target structure.

3. The visualization and comprehensive analysis method for monitoring the deformation of structures according to claim 1, characterized in that: In step S1, if the 3D laser scanner, precision engineering level, total station, or rangefinder malfunctions and needs to be replaced after long-term operation, it can be re-set up directly based on the positioning information of the electronic positioning tag, without the need for re-measurement and re-positioning.

4. The visualization and comprehensive analysis method for monitoring and analyzing the deformation of structures according to claim 1, characterized in that: In steps S5, 6, and 7, if the preprocessing software discovers missing data during the sequential stitching of stored point cloud data, elevation data, or displacement data, it stops denoising, classification, and coloring preprocessing. Simultaneously, the cloud server extracts the location information of the missing data and sends an instruction to the staff to re-collect the point cloud data, elevation data, or displacement data of the target structure at that location information until the point cloud data, elevation data, or displacement data in the stitching process can completely construct the three-dimensional model of the structure to proceed to the next step.

5. The visualization and comprehensive analysis method for monitoring the deformation of structures according to claim 1, characterized in that: In step S9, the difference data is stored in the form of difference values ​​plus arrows. The difference value is based on the difference between the initial value and the current value of the point cloud data, and the arrow points in the direction of displacement change.

6. The visualization and comprehensive analysis method for monitoring the deformation of structures according to claim 1, characterized in that: In step S10, the deformed chart is generated by interpolating the differential data, i.e., the regional change, using the spatial interpolation analysis interface in the ArcENGINE plugin.

7. The visualization and comprehensive analysis method for monitoring the deformation of structures according to claim 1, characterized in that: In step S11, the analysis results of the deformation causes can be stored on the monitoring terminal E. At the same time, the deformation data of the structure and the corresponding deformation causes are used as training samples to train the deformation cause analysis model on the monitoring terminal E. The monitoring terminal E shares data with the monitoring terminals C and D via USB, which can quickly pre-analyze the deformation causes of the structure in the later stage.

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