CN116821637B - Building steel structure data processing method based on data twinning technology - Google Patents
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Abstract
The application provides a building steel structure data processing method based on a data twinning technology, which relates to the technical field of building steel structure data processing, and is used for scanning and measuring point cloud data before and after deformation of a stress area of a steel structure and establishing digital twinning virtual point cloud coordinates; calculating deformation of a stress area of the steel structure by using the surface topography obtained by fitting the scanning point cloud data; and (3) monitoring stress data of a stress area of the steel structure in real time by adopting a sensor, and carrying out association judgment on the change amount of the stress data and the deformation amount of the stress area, wherein if the change amount and the deformation amount of the stress data have larger mutation in the same direction, the danger can be considered to occur in the concerned area.
Description
Technical Field
The application relates to the technical field of building steel structure data processing, in particular to a building steel structure data processing method based on a data twinning technology.
Background
The building digital twin model fully utilizes data such as a physical model, sensor updating, operation history and the like, integrates simulation processes of multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities, and completes mapping in a virtual space, thereby reflecting the full life cycle process of corresponding entity equipment. The information mapping model for maintaining the symbiotic evolution relation between the building digital twin model and the building physical entity in the virtual world has important significance for improving the building management capability. In the prior art, a twin technology is generally used to build a digital model of a certain building structure, and the actual building structure is monitored through the digital model, so that a user in a monitoring room can conveniently know the actual situation of the building.
However, the building suffers from aging and performance degradation during the evolution of life, and some parameters and physical laws of the building can generate a series of uncertain continuous changes under the influence of complex environments, so that the digital twin model of the building is generally difficult to keep dynamic consistency with physical entities of the building, meanwhile, a building is provided with various different sensors and monitoring facilities, and if the contents transmitted by the facilities are rendered in the digital model in real time, the calculation pressure of the model is increased.
Disclosure of Invention
In order to solve the technical problems, the application provides a building steel structure data processing method based on a data twinning technology, which comprises the following steps:
step one, scanning and measuring point cloud data before and after deformation of a stress area of a steel structure, and establishing digital twin virtual point cloud coordinates;
step two, calculating the deformation of the stress area of the steel structure by using the surface configuration obtained by fitting the scanning point cloud data;
and thirdly, adopting a sensor to monitor stress data of the stress area of the steel structure in real time, and carrying out association judgment on the change quantity of the stress data and the deformation quantity of the stress area.
Further, in the first step, the coordinates of the point cloud data P1 at the first time T1 before the deformation of the stressed area are set as { x } 1 ,y 1 ,z l }：
；
Let the coordinates of the point cloud data P2 at the second moment T2 after the deformation of the stress area be { x } 2 ,y 2 ,z 2 }：
；
Wherein S is 1 ，S 2 Respectively corresponding to the actual steel structure surface functions of the point cloud data P1 and the point cloud data P2, S 1 (x 1 ,y 1 ) As a practical surface function S 1 Upper (x) 1 ,y 1 ) Function value at S 2 (x 2 ,y 2 ) As a practical surface function S 2 Upper (x) 2 ,y 2 ) The function value of the position,for measuring noise of the point cloud data P2 in the z-direction, +.>Is the measurement noise of the point cloud data P1 in the z direction.
Further, in the second step, the first step,
let { X ] 1 ,Y 1 ,Z 1 } ’ And { X ] 2 ,Y 2 ,Z 2 } ’ The surface topography obtained by fitting the point cloud data P1 and P2 at the first time T1 and the second time T2 are respectively:
the surface potential shape obtained by fitting the surface of the steel structure at the first moment T1 is as follows:
；
the surface potential shape obtained by fitting the surface of the steel structure at the second moment T2 is as follows:
；
in the method, in the process of the application,scanning absolute precision drift amounts for the first time T1 and the second time T2 respectively; />Coordinate values of surface topography obtained by fitting the surface of the steel structure at the first moment T1 are respectively +.>Respectively obtaining coordinate values of the surface topography obtained by fitting the surface of the steel structure at the first moment T2;
the deformation of the steel structure surface at the second moment T2 with respect to the first moment T1 is then:
；
the average value of the actual point cloud data at the first time T1 and the second time T2 is respectively、/>；/>、/>Is mean->、Deviation from the overall mean, +.>The deformation amounts in the x, y and z directions are respectively.
Further, in step three, a fixed time interval elapsesAfter that, the variation of the stress data is calculated +.>Analysis of the variation of stress data +.>Components in the x, y, z direction +.>And if the variation component and the deformation component of the stress data exceed the abrupt threshold in the same direction, judging that the stress area is dangerous.
In the first step, the point cloud data band of the stress area is segmented by adopting the following steps:
s11, ensuring that point cloud data P1 of a first moment T1 and point cloud data P2 of a second moment T2 both contain stress areas;
s12, dividing point cloud blocks from the point cloud data by adopting a movable sliding window along the stress direction;
s13, setting the length of a sliding window as lw and the width as S, and respectively dividing point cloud blocks in the point cloud data P1 and P2 by taking the sliding window as a unit;
s14, transforming the point cloud block data from the integral coordinate system xyz to a local coordinate system；
S15, in a local coordinate systemIn (1) respectively solving for +.in the local coordinate system of the point cloud data P1 and P2>Mean>Andthen->And->Conversion to the global coordinate system z 1 And z 2 Respectively obtaining the integral coordinates { x ] of the point cloud data P1 and P2 at the same measuring point 1 ,y 1 ,z l Sum { x } 2 ,y 2 ,z 2 }。
Compared with the prior art, the application has the following beneficial technical effects:
scanning and measuring point cloud data before and after deformation of a stress area of the steel structure, and establishing digital twin virtual point cloud coordinates; calculating deformation of a stress area of the steel structure by using the surface topography obtained by fitting the scanning point cloud data; and (3) monitoring stress data of a stress area of the steel structure in real time by adopting a sensor, and carrying out association judgment on the change amount of the stress data and the deformation amount of the stress area, wherein if the change amount and the deformation amount of the stress data have larger mutation in the same direction, the danger can be considered to occur in the concerned area.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a flow chart of an inventive method for processing data of a construction steel structure based on a data twinning technique;
FIG. 2 is a diagram of the sliding window setting parameters of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the drawings of the specific embodiments of the present application, in order to better and more clearly describe the working principle of each element in the system, the connection relationship of each part in the device is represented, but only the relative positional relationship between each element is clearly distinguished, and the limitations on the signal transmission direction, connection sequence and the structure size, dimension and shape of each part in the element or structure cannot be constructed.
As shown in fig. 1, the application is a flow chart of a data processing method of a building steel structure based on a data twinning technology, which comprises the following steps:
step one, scanning and measuring point cloud data before and after deformation of a stress area of a steel structure, and establishing digital twin virtual point cloud coordinates.
Let the scanning moment before the deformation of the stress area of the steel structure be the first moment T1, and the scanning moment after the deformation of the stress area of the steel structure be the second moment T2.
And scanning the same stress area of the steel structure by using a scanner at the first moment T1 and the second moment T2.
Defining the scanning point cloud data of the first moment T1 as point cloud data P1, and the scanning point cloud data of the second moment T2 as point cloud data P2; s is S 1 ，S 2 Respectively corresponding to the actual steel structure surface functions of the point cloud data P1 and the point cloud data P2, S 1 (x 1 ,y 1 ) As a practical surface function S 1 Upper (x) 1 ,y 1 ) Function value at S 2 (x 2 ,y 2 ) As a practical surface function S 2 Upper (x) 2 ,y 2 ) A function value at the location.
Let the coordinates of the point cloud data P1 be { x } 1 ,y 1 ,z l -it satisfies the following relationship:
；
in the method, in the process of the application,the measurement noise of the point cloud data P1 in the z direction is subjected to gaussian distribution.
{x 1 ,y 1 ,z l The coordinates { x } are 1 ,y 1 ,S 1 (x 1 ,y 1 ) Sum ofSuperposition in z-direction, ++>Is a measurement error point cloud of the point cloud data P1.
Let the coordinates of the point cloud data P2 be { x } 2 ,y 2 ,z 2 -it satisfies the following relationship:
；
in the method, in the process of the application,measuring noise in the z direction for the point cloud data P2; { x 2 ,y 2 ,z 2 Is the coordinatesAnd->Superposition in the z-direction. />Is a measurement error point cloud of the point cloud data P2.
In a preferred embodiment, the following steps may be used to segment out the point cloud data bands of the force-bearing region.
S11, ensuring that the point cloud data P1 of the first moment T1 and the point cloud data P2 of the second moment T2 both contain stress areas.
S12, dividing point cloud blocks from the point cloud data by adopting a movable sliding window along the stress direction, wherein the distance between the sliding windows is S, and the plane coordinates of the middle points of the sliding windows are (x) i ,y i ) S control calculates the distance between the measuring points. The width of the sliding window is hw, the hw controls the width of the point cloud intercepted in the transverse direction of the steel structure, when the surface to be measured is a plane in the transverse direction, the more the hw is, the more the number of points participating in calculation is, and the reliability of a calculation result is stronger.
And S13, setting the length of the sliding window as lw and the width as S, and respectively dividing the point cloud blocks in the point cloud data P1 and P2 by taking the sliding window as a unit.
S14, transforming the point cloud block data from the integral coordinate system xyz to a local coordinate system。
S15, in a local coordinate systemIn (1) respectively solving for +.in the local coordinate system of the point cloud data P1 and P2>Mean>Andthen->And->Conversion to the global coordinate system z 1 And z 2 Respectively obtaining the integral coordinates { x ] of the point cloud data P1 and P2 at the same measuring point 1 ,y 1 ,z l Sum { x } 2 ,y 2 ,z 2 }。
And secondly, calculating the deformation of the stress area of the steel structure by using the surface configuration obtained by fitting the scanning point cloud data.
Under the condition of a certain point cloud density, { X } 1 ,Y 1 ,Z 1 } ’ And { X ] 2 ,Y 2 ,Z 2 } ’ The surface topography resulting from the fitting of the point cloud data P1 and P2 at the first instant T1 and the second instant T2 respectively,the absolute precision drift amount is scanned for a first time T1 and a second time T2 respectively, and the average value of the actual point cloud data of the first time T1 and the second time T2 is +.>、/>。
Definition:；/>；
in the method, in the process of the application,、/>is mean->、/>Deviation from the overall mean.
The surface topography obtained by surface fitting of the structure at time T1 is:
；
the surface topography obtained by fitting the steel structure at the time T2 is as follows:
；
wherein,respectively the coordinate values of the surface topography obtained by fitting the surface of the steel structure at the first moment T1,and respectively obtaining coordinate values of the surface topography obtained by fitting the surface of the steel structure at the first moment T2.
The deformation of the steel structure at time T2 relative to time T1 is:
；
in the method, in the process of the application,the deformation amounts in the x, y and z directions are respectively.
When the conditions (scanning resolution and scanning distance) of the two observations are similar, the number of points and the standard deviation of the point errors of the two point clouds in the stressed area are the same, and o 2 -o 1 Rewritten asIs standard deviation from the scanning point>A random term related to the number of data n.
And thirdly, adopting a sensor to monitor stress data of the stress area of the steel structure in real time, and carrying out association judgment on the change quantity of the stress data and the deformation quantity of the stress area.
The sensor technology is adopted to realize the real-time monitoring of the stress data of the physical model of the steel structure connecting node, and the acquisition and construction of the physical data of the steel structure are realized.
The change of the stress data is compared with the deformation measured by digital twin, namely, a fixed time interval is passedAfter that, calculate the change of the stress dataQuantity->Analysis of the variation of stress data +.>Components in x, y, z direction of (c)And if the variation component and the deformation component of the stress data exceed the abrupt threshold in the same direction, judging that the stress area is dangerous.
In the preferred embodiment, the input and output data of the digital twin model are utilized to carry out the association judgment on the variation of the stress data and the deformation of the stress area. The method specifically comprises the following steps:
when the digital twin model works in the analog mode, the output function G(s) from the input end Y(s) to the output end U(s) of the digital twin model is calculated as follows:
；
wherein: t is a time constant, s is a judgment parameter; wherein, the decision parameter s can be selected and input with different decision parameter types according to actual needs. K is a gain function that varies according to the variation of the type of the determination parameter s.
The output function G(s) of the digital twin model represents the variation of the stress data and the mutation of the deformation, the input end Y(s) of the digital twin model represents the variation of the stress data, and the output end U(s) represents the deformation of the digital twin measurement.
The digital twin model is used for comparing the change amount and the deformation amount of the stress data with the deformation amount measured by the digital twin, so that whether the curve mutation of the change amount and the deformation amount of the stress data exceeds a mutation threshold value is judged, and the danger is judged to occur in the stress area.
In a preferred embodiment, after stress data of a stress area of the steel structure is monitored in real time by adopting a sensor, sensor monitoring system information is obtained and stored in a database, and the stress data monitored in real time is stored in a knowledge base by utilizing a semantic Web knowledge storage function.
Furthermore, the structural monitoring system, the building information model at a specific construction stage and the FEA model are associated by utilizing an ontology method in the semantic Web technology, and the integration and the interoperation of heterogeneous and heterogeneous information are realized from the data layer.
And establishing a corresponding database according to a real-time monitoring data structure system of the sensor monitoring system, and recording the real-time monitoring data by using the MySQL relational database in a form of multi-table storage respectively.
And establishing a self-defined SSN ontology model according to the SSN ontology framework and the sensor arrangement condition, and developing an ontology model applicable to the field of structural analysis according to the building structural form, structural analysis reference and structural monitoring scheme.
The semantic description of sensor location information is refined by introducing the sensor ontology into the SSN ontology, enhancing the representation of location concepts related to the sensor information. The class and the attribute in the SSN body represent the position information related to the sensing information, an association strategy of real-time monitoring data and the sensor position information is designed, and reasonable semantic association is established between the real-time monitoring data and the sensor position information.
And secondly, carrying out correlation judgment on the variation of the stress data and the deformation of the stress area.
The potential relation between the variation of the stress data and the deformation of the stress area is described by designing the variation relation and the logic rule based on the variation of the stress data, and the corresponding logic rule can support the semantic reasoning of association judgment. The correlation prototype system and the variable quantity visualization prototype system of the stress data are designed, so that a user is helped to correlate the stress area with the sensor position information conveniently and quickly, and the SPARQL query statement meeting the conditions is dynamically and automatically generated according to the query conditions selected by the user.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted across a computer-readable storage medium. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.
While the application has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (4)
1. The building steel structure data processing method based on the data twinning technology is characterized by comprising the following steps of:
step one, scanning and measuring point cloud data before and after deformation of a stress area of a steel structure, and establishing digital twin virtual point cloud coordinates; the point cloud data band of the stress area is segmented by adopting the following steps:
s11, ensuring that point cloud data P1 of a first moment T1 and point cloud data P2 of a second moment T2 both contain stress areas;
s12, dividing point cloud blocks from the point cloud data by adopting a movable sliding window along the stress direction;
s13, setting the length of a sliding window as lw and the width as S, and respectively dividing point cloud blocks in the point cloud data P1 and P2 by taking the sliding window as a unit;
s14, transforming the point cloud block data from the integral coordinate system xyz to a local coordinate system；
S15, in a local coordinate systemIn (1) respectively solving for +.in the local coordinate system of the point cloud data P1 and P2>Mean>And->Then->And->Conversion to the global coordinate system z 1 And z 2 Respectively obtaining the integral coordinates { x ] of the point cloud data P1 and P2 at the same measuring point 1 ,y 1 ,z l Sum { x } 2 ,y 2 ,z 2 }；
Step two, calculating the deformation of the stress area of the steel structure by using the surface configuration obtained by fitting the scanning point cloud data;
and thirdly, adopting a sensor to monitor stress data of the stress area of the steel structure in real time, and carrying out association judgment on the change quantity of the stress data and the deformation quantity of the stress area.
2. The method according to claim 1, wherein in the first step, coordinates of the point cloud data P1 at the first time T1 before deformation of the stressed area are set to { x } 1 ,y 1 ,z l }：
；
Let the coordinates of the point cloud data P2 at the second moment T2 after the deformation of the stress area be { x } 2 ,y 2 ,z 2 }：
；
Wherein S is 1 ，S 2 Respectively corresponding to the actual steel structure surface functions of the point cloud data P1 and the point cloud data P2, S 1 (x 1 ,y 1 ) As a practical surface function S 1 Upper (x) 1 ,y 1 ) Function value at S 2 (x 2 ,y 2 ) As a practical surface function S 2 Upper (x) 2 ,y 2 ) The function value of the position,for measuring noise of the point cloud data P2 in the z-direction, +.>Is the measurement noise of the point cloud data P1 in the z direction.
3. The method for processing building steel structure data according to claim 2, wherein in the second step,
let { X ] 1 ,Y 1 ,Z 1 } ’ And { X ] 2 ,Y 2 ,Z 2 } ’ The surface topography obtained by fitting the point cloud data P1 and P2 at the first time T1 and the second time T2 are respectively:
the surface potential shape obtained by fitting the surface of the steel structure at the first moment T1 is as follows:
；
the surface potential shape obtained by fitting the surface of the steel structure at the second moment T2 is as follows:
；
in the method, in the process of the application,scanning absolute precision drift amounts for the first time T1 and the second time T2 respectively; />Coordinate values of surface topography obtained by fitting the surface of the steel structure at the first moment T1 are respectively +.>Respectively obtaining coordinate values of the surface topography obtained by fitting the surface of the steel structure at the first moment T2;
the deformation of the steel structure surface at the second moment T2 relative to the first moment T1The method comprises the following steps:
；
the average value of the actual point cloud data at the first time T1 and the second time T2 is respectively、/>；/>、/>Is mean->、/>Deviation from the overall mean; />The deformation amounts in the x, y and z directions are respectively.
4. The method for processing structural data of construction steel according to claim 1, wherein in the third step, after a fixed time interval Δt, the variation amount Δf of the stress data is calculated, and components in x, y, z directions of the variation amount Δf of the stress data are analyzedIf the variation component and the mutation of the deformation component of the stress data exceed the mutation threshold in the same direction, judging that the stress area is dangerous.
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| CN115601008A (en) * | 2022-09-29 | 2023-01-13 | 中交一公局第七工程有限公司（Cn） | Engineering settlement deformation monitoring system and method based on digital twinning |
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