CN112859681A - Intelligent monitoring method for safety and stability of building steel structure based on big data analysis and cloud monitoring platform - Google Patents
Intelligent monitoring method for safety and stability of building steel structure based on big data analysis and cloud monitoring platform Download PDFInfo
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Abstract
The invention discloses an intelligent monitoring method of safety and stability of a building steel structure based on big data analysis and a cloud monitoring platform, which are characterized in that steel structure layer division and node statistics are carried out on a building steel structure frame, the current position three-dimensional coordinates and the original position three-dimensional coordinates of each node are obtained, the offset displacement of each node of each steel structure layer is counted, a dangerous offset steel structure layer and a corresponding dangerous offset node thereof are screened out, a plane scanning image of each steel structure layer is obtained at the same time, and then the plane scanning image is compared with the original plane scanning image, so that the depression approximate area corresponding to each depression area of each depression steel structure layer is counted, the safety and stability coefficient of the building steel structure is counted, the defects of the sheet surface, low accuracy and low reliability of the current monitoring means of the safety and stability of the building steel structure are overcome, and the monitoring accuracy and reliability are improved, the comprehensive and accurate monitoring requirement on the safety and stability of the building steel structure is greatly met.
Description
Technical Field
The invention belongs to the technical field of monitoring of stability of a building steel structure, and particularly relates to an intelligent monitoring method and a cloud monitoring platform for safety and stability of the building steel structure based on big data analysis.
Background
The steel structure is a structural design type which is widely applied in modern building engineering, has the characteristics of high construction speed, good earthquake resistance and good corrosion resistance, and has obvious building advantages compared with other structural types. Therefore, with the development of the construction industry, high-rise buildings and super high-rise buildings are more and more, and steel structures are more and more applied to the buildings, but if the steel structures have defects in the buildings, the defects will affect the overall structure of the buildings, and even cause serious quality and safety accidents. Therefore, it is very necessary to monitor the safety and stability of the construction steel structure.
Most of the existing monitoring means for the safety and stability of the building steel structure only adopt a manual visual inspection mode to observe whether the building steel structure frame has concave deformation or not, on one hand, the monitoring means does not consider the influence of the deviation of a connecting node on the building steel structure frame on the safety and stability of the steel structure, so that the monitoring is in a one-sided mode, and the monitoring result is difficult to comprehensively reflect the safety and stability of the building steel structure; on the other hand, the monitoring means monitors the sunken deformation of the building steel structure frame in an artificial visual inspection mode, the accuracy is low, and some tiny sunken parts cannot be monitored by artificial visual inspection, so that the reliability of a monitoring result is low.
Disclosure of Invention
In order to overcome the defects, the invention provides an intelligent monitoring method for the safety and stability of the building steel structure based on big data analysis and a cloud monitoring platform, so as to effectively overcome the defects of one-sidedness, low accuracy and low reliability of the existing monitoring means for the safety and stability of the building steel structure.
The invention provides a building steel structure safety and stability intelligent monitoring method based on big data analysis, which needs to use a building steel structure safety and stability intelligent monitoring system based on big data analysis in the specific implementation process, wherein the system comprises a building steel structure layer dividing module, a steel structure layer node counting module, a node current position obtaining module, a node original position obtaining module, a database, a steel structure layer sunken area obtaining module, a modeling analysis module, a management server, a display terminal and a remote supervision center;
the building steel structure layer dividing module is used for counting the number of steel structure layers of a building steel structure frame to be monitored, dividing the building steel structure frame to be monitored into a plurality of steel structure layers according to the counted number of the steel structure layers, and numbering the divided steel structure layers according to the length distance from the ground, wherein the divided steel structure layers are sequentially marked as 1,2.
The steel structure layer node counting module is used for counting the number of nodes existing in each divided steel structure layer, numbering the counted nodes existing in each steel structure layer, and marking the nodes as 1,2.. j.. m respectively;
the node current position acquisition module is used for acquiring corresponding current position three-dimensional coordinates of each node on each steel structure layer in statistics and forming a node current position three-dimensional coordinate set G [ G1 (x)1,y1,z1),g2(x2,y2,z2),…,gj(xj,yj,zj),…gm(xm,ym,zm)]，gj(xj,yj,zj) The three-dimensional coordinate of the current position corresponding to the jth node on the ith steel structure layer is represented as g, the number of the steel structure layer is represented as g, and the g is 1,2, i, n, so that the three-dimensional coordinate set of the current position of the node is sent to a modeling analysis module;
the node original position acquisition module is used for acquiring an original design frame of a building steel structure frame to be monitored, acquiring original position three-dimensional coordinates corresponding to each node of the building steel structure original design frame, and further forming a node original position three-dimensional coordinate set G '[ G1 (x'1,y′1,z′1),g2(x′2,y′2,z′2),…,gj(x′j,y′j,z′j),...gm(x′m,y′m,z′m)]，gj(x′j,y′j,z′j) Expressing the three-dimensional coordinates of the original position corresponding to the jth node on the g steel structure layer, and sending the three-dimensional coordinates of the original position of the node to a modeling analysis module by a node original position acquisition module;
the steel structure layer sunken area acquisition module is used for acquiring plane scanning images of all steel structure layers divided by the building steel structure frame to be monitored and acquiring all steel structure layersComparing the planar scanning image with original planar scanning images of all steel structure layers stored in a database, checking whether a sunken area appears, counting the number of the steel structure layers with the sunken area if the sunken area appears, wherein the number of the steel structure layers with the sunken area can be recorded as 1,2, a, z, the steel structure layers are recorded as sunken steel structure layers, counting the number of the sunken areas corresponding to the sunken steel structure layers, numbering the sunken areas corresponding to the sunken steel structure layers, respectively marking as 1,2, k, p, focusing the planar scanning image of each sunken steel structure layer on each sunken area, further acquiring the sunken height and the sunken length of each sunken area, thereby acquiring the sunken approximate area corresponding to each sunken area in each sunken steel structure layer, and further forming a sunken approximate area set S of the sunken areas of the sunken steel structure layersf(sf1,sf2,…,sfk,…,sfp)，sfk is expressed as a depression approximate area corresponding to a kth depression region in an fth depression steel structure layer, f is expressed as a depression steel structure layer number, f is 1,2.. a.. z, and a steel structure layer depression region acquisition module sends a depression approximate area set of depression steel structure layer depression regions to a management server and sends each depression steel structure layer number to a remote supervision center;
the modeling analysis module receives the node current position three-dimensional coordinate set sent by the node current position acquisition module and the node original position three-dimensional coordinate set sent by the node original position acquisition module respectively, counts the offset displacement corresponding to each node of each steel structure layer according to the node current position three-dimensional coordinate set and the node original position three-dimensional coordinate set, compares the counted offset displacement corresponding to each node of each steel structure layer with the node safety offset displacement set in the database, if the offset displacement corresponding to a certain node of a certain steel structure layer is greater than the set node safety offset displacement, the steel structure layer is marked as a dangerous offset steel structure layer, the node is marked as a dangerous offset node, counts the number of the dangerous offset steel structure layer and the number of the dangerous offset node corresponding to each dangerous offset steel structure layer at the moment, and the number of each dangerous offset steel structure layer can be marked as 1, y, the dangerous offset node number corresponding to each dangerous offset steel structure layer can be recorded as 1,2.. c.. u, the modeling analysis module sends the number of the dangerous offset steel structure layer and the dangerous offset node number corresponding to each dangerous offset steel structure layer to a remote supervision center, and the offset displacement corresponding to each dangerous offset node in each dangerous offset steel structure layer is sent to a management server;
the management server respectively receives the sunken approximate area set of the sunken area of the sunken steel structure layer sent by the sunken area acquisition module of the steel structure layer and the offset displacement corresponding to each dangerous offset node in each dangerous offset steel structure layer sent by the modeling analysis module, extracts the plane area corresponding to each steel structure layer and the set node safe offset displacement stored in the database, further counts the safe stability coefficient of the building steel structure and sends the safe stability coefficient to the display terminal;
the display terminal is used for receiving and displaying the safety and stability coefficient of the building steel structure sent by the management server;
the remote supervision center is used for respectively receiving the numbers of the sunken steel structure layers sent by the steel structure layer sunken area acquisition module, the numbers of the dangerous offset steel structure layers sent by the modeling analysis module and the dangerous offset node numbers corresponding to the dangerous offset steel structure layers, and then dispatching related management personnel to carry out targeted rectification;
when the intelligent monitoring system for the safety and stability of the building steel structure based on big data analysis is adopted to carry out intelligent monitoring on the safety and stability of the building steel structure, the intelligent monitoring system comprises the following steps;
s1, building steel structure layer division: dividing a building steel structure frame to be monitored into a plurality of steel structure layers according to the counted number of the steel structure layers, and numbering the divided steel structure layers;
s2, steel structure layer node statistics: counting the number of nodes existing in each divided steel structure layer, and numbering the counted nodes existing in each steel structure layer;
s3, acquiring the current position of the node: acquiring current position three-dimensional coordinates corresponding to each node on each counted steel structure layer;
s4, acquiring an original position of a node: acquiring three-dimensional coordinates of corresponding original positions of all nodes on all the counted steel structure layers;
s5, acquiring a sunken area of a steel structure layer: acquiring plane scanning images of each steel structure layer divided by the building steel structure frame to be monitored, and comparing the acquired plane scanning images of each steel structure layer with original plane scanning images of each steel structure layer stored in a database, so as to acquire the depression approximate area of each depression area corresponding to each depression steel structure layer;
s6, dangerous offset steel structure layer and dangerous offset node statistics: counting offset displacements corresponding to nodes of each steel structure layer according to the three-dimensional coordinate set of the current position of the node and the three-dimensional coordinate set of the original position of the node, and comparing the offset displacements with the set safe offset displacements of the nodes, so as to count the numbers of dangerous offset steel structure layers and the numbers of dangerous offset nodes corresponding to the dangerous offset steel structure layers;
s7, safety and stability coefficient statistics: according to the set of the sinking approximate areas of the sinking steel structure layers and the offset displacement corresponding to each dangerous offset node in each dangerous offset steel structure layer, the safety and stability coefficients of the building steel structure are counted;
s8, remote supervision and modification: and dispatching related management personnel to carry out targeted correction according to the numbers of the sunken steel structure layers, the dangerous offset steel structure layers and the dangerous offset node numbers corresponding to the dangerous offset steel structure layers.
In a possible design of the first aspect, the database is configured to store original plane scan images of each steel structure layer, store plane areas corresponding to each steel structure layer, and store set node safety offset displacements.
In a possible design of the first aspect, the monitoring system further includes a concave area positioning module, configured to perform position positioning on a concave area corresponding to each concave steel structure layer, obtain a geographic position of each concave area corresponding to each concave steel structure layer, and send the geographic position to the remote monitoring center.
In a possible design of the first aspect, a calculation formula of a depression approximate area corresponding to each depression region in each depression steel structure layer is
sfk is expressed as the approximate area of the corresponding depression of the kth depressed area in the fth depressed steel structure layer, xfk is expressed as the depression length corresponding to the kth depression region of the fth depression steel structure layer, hfk is expressed as the depression height corresponding to the kth depression region of the fth depression steel structure layer.
In a possible design of the first aspect, the offset displacement corresponding to each node of each steel structure layer is calculated by the following formula
Lg jExpressed as the offset displacement corresponding to the jth node in the jth steel structure layer, gjxj、gjyj、gjzjRespectively expressed as the current position coordinate of the jth node in the jth steel structure layer on the x axis, the current position coordinate on the y axis and the current position coordinate on the z axis, gjx'j、gjy′j、gjz′jExpressed as the original position coordinate of the jth node in the jth steel structure layer on the x axis, the original position coordinate on the y axis and the original position coordinate on the z axis respectively.
In a possible design of the first aspect, the calculation formula of the safety and stability factor of the construction steel structure is
sfk is expressed as the approximate area of the depression corresponding to the kth depressed area in the fth depressed steel structure layer, SfExpressed as the planar area, L, corresponding to the f-th sunken steel structure layerbc is represented as the offset displacement corresponding to the c dangerous offset node in the b dangerous offset steel structure layer, L0Node safety offset displacement, D, expressed as set0Expressed as a predetermined constant, noted 1.25.
The second aspect of the invention provides a cloud monitoring platform, which comprises a processor, a machine-readable storage medium and a network interface, wherein the machine-readable storage medium, the network interface and the processor are connected through a bus system, the network interface is used for being in communication connection with at least one intelligent monitoring device for the safety and stability of the building steel structure, the machine-readable storage medium is used for storing a program, an instruction or a code, and the processor is used for executing the program, the instruction or the code in the machine-readable storage medium so as to execute the intelligent monitoring method for the safety and stability of the building steel structure based on big data analysis.
Based on any one of the above aspects, the invention has the following beneficial effects:
(1) the invention carries out steel structure layer division and node statistics on a building steel structure frame, acquires the current position three-dimensional coordinate and the original position three-dimensional coordinate of each node of each steel structure layer, counts the offset displacement of each node of each steel structure layer, compares the offset displacement with the set node safety offset displacement, screens out dangerous offset steel structure layers and corresponding dangerous offset nodes thereof, simultaneously acquires a plane scanning image of each steel structure layer, further compares the plane scanning image of each steel structure layer with the original plane scanning image thereof, counts the depression approximate area corresponding to each depression area of each depressed steel structure layer, counts the safety stability coefficient of the building steel structure according to the offset displacement corresponding to the dangerous offset node in the dangerous offset steel structure layer and the depression approximate area corresponding to each depression area of each depressed steel structure layer, realizes the intelligent monitoring of the safety stability of the building steel structure, the monitoring method overcomes the defects of one-sidedness, low accuracy and low reliability existing in the conventional monitoring means for the safety and stability of the building steel structure, improves the accuracy and reliability of monitoring, and greatly meets the comprehensive and accurate monitoring requirement for the safety and stability of the building steel structure.
(2) According to the invention, the counted numbers of the sunken steel structure layers, the geographical positions of the sunken areas corresponding to the sunken steel structure layers, the numbers of the dangerous offset steel structure layers and the dangerous offset node numbers corresponding to the dangerous offset steel structure layers are sent to the remote monitoring center, so that relevant monitoring personnel can find corresponding positions quickly, and can perform targeted rectification in time, thereby improving the rectification efficiency and being beneficial to reducing the occurrence of building safety accidents caused by instability of the building steel structure.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a flow chart of the steps of a method of the present invention;
fig. 2 is a schematic diagram of the system module connection according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a first aspect of the present invention provides a building steel structure safety and stability intelligent monitoring method based on big data analysis, including the following steps:
s1, building steel structure layer division: dividing a building steel structure frame to be monitored into a plurality of steel structure layers according to the counted number of the steel structure layers, and numbering the divided steel structure layers;
s2, steel structure layer node statistics: counting the number of nodes existing in each divided steel structure layer, and numbering the counted nodes existing in each steel structure layer;
s3, acquiring the current position of the node: acquiring current position three-dimensional coordinates corresponding to each node on each counted steel structure layer;
s4, acquiring an original position of a node: acquiring three-dimensional coordinates of corresponding original positions of all nodes on all the counted steel structure layers;
s5, acquiring a sunken area of a steel structure layer: acquiring plane scanning images of each steel structure layer divided by the building steel structure frame to be monitored, and comparing the acquired plane scanning images of each steel structure layer with original plane scanning images of each steel structure layer stored in a database, so as to acquire the depression approximate area of each depression area corresponding to each depression steel structure layer;
s6, dangerous offset steel structure layer and dangerous offset node statistics: counting offset displacements corresponding to nodes of each steel structure layer according to the three-dimensional coordinate set of the current position of the node and the three-dimensional coordinate set of the original position of the node, and comparing the offset displacements with the set safe offset displacements of the nodes, so as to count the numbers of dangerous offset steel structure layers and the numbers of dangerous offset nodes corresponding to the dangerous offset steel structure layers;
s7, safety and stability coefficient statistics: according to the set of the sinking approximate areas of the sinking steel structure layers and the offset displacement corresponding to each dangerous offset node in each dangerous offset steel structure layer, the safety and stability coefficients of the building steel structure are counted;
s8, remote supervision and modification: and dispatching related management personnel to carry out targeted correction according to the numbers of the sunken steel structure layers, the dangerous offset steel structure layers and the dangerous offset node numbers corresponding to the dangerous offset steel structure layers.
Referring to fig. 2, the intelligent monitoring method for safety and stability of a building steel structure based on big data analysis of the present invention requires an intelligent monitoring system for safety and stability of a building steel structure based on big data analysis in the specific implementation process, the system comprises a building steel structure layer division module, a steel structure layer node statistical module, a node current position acquisition module, a node original position acquisition module, a database, a steel structure layer depressed region acquisition module, a depressed region positioning module, a modeling analysis module, a management server, a display terminal and a remote supervision center, wherein the building steel structure layer division module is connected with the steel structure layer node statistical module, the steel structure layer node statistical module is connected with the node current position acquisition module, the modeling analysis module is respectively connected with the node current position acquisition module and the node original position acquisition module, the depressed area positioning module is connected with the depressed area acquisition module of the steel structure layer, the management server is respectively connected with the depressed area acquisition module of the steel structure layer, the modeling analysis module and the display terminal, and the remote supervision center is respectively connected with the modeling analysis module, the depressed area acquisition module of the steel structure layer and the depressed area positioning module.
The building steel structure layer division module is used for counting the number of steel structure layers of a building steel structure frame to be monitored, dividing the building steel structure frame to be monitored into a plurality of steel structure layers according to the counted number of steel structure layers, numbering the divided steel structure layers according to the length distance sequence from the ground, and sequentially marking the divided steel structure layers as 1,2.
The steel structure layer node counting module is used for counting the number of nodes existing in each divided steel structure layer, numbering the nodes existing in each counted steel structure layer, and marking the nodes as 1,2.
In the embodiment, the nodes on each divided steel structure layer are counted and numbered, so that a bedding is provided for obtaining the current position three-dimensional coordinates and the original position three-dimensional coordinates of each node later.
The node current position acquisition module is used for acquiring corresponding current position three-dimensional coordinates of each node on each steel structure layer, and forming a node current position three-dimensional coordinate set G [ G1 (x)1,y1,z1),g2(x2,y2,z2),...,gj(xj,yj,zj),...gm(xm,ym,zm)]，gj(xj,yj,zj) The three-dimensional coordinate of the current position corresponding to the jth node existing on the ith steel structure layer is represented as g, the number of the steel structure layer is represented as g, and g is 1,2.
The node original position acquisition module is used for acquiring an original design frame of a building steel structure frame to be monitored, acquiring original position three-dimensional coordinates corresponding to each node of the building steel structure original design frame, and further forming a node original position three-dimensional coordinate set G '[ G1 (x'1,y′1,z′1),g2(x′2,y′2,z′2),...,gj(x′j,y′j,z′j),...gm(x′m,y′m,z′m)]，gj(x′j,y′j,z′j) And the three-dimensional coordinates of the original position corresponding to the jth node on the g steel structure layer are represented, and the original position acquisition module of the node sends the three-dimensional coordinates of the original position of the node to the modeling analysis module.
The method and the device lay a foundation for later-stage statistics of the offset displacement of each node of each steel structure layer by acquiring the current position three-dimensional coordinates and the original position three-dimensional coordinates of each node of each steel structure layer.
The database is used for storing original plane scanning images of all steel structure layers, storing plane areas corresponding to all the steel structure layers and storing set node safety offset displacement.
The steel structure layer sunken area acquisition module is used for acquiring a plane scanning image of each steel structure layer divided by the building steel structure frame to be monitored, comparing the obtained planar scanning image of each steel structure layer with the original planar scanning image of each steel structure layer stored in the database, checking whether a concave area appears, if so, counting the number of the steel structure layer with the occurrence of the depressed area, which can be marked as 1,2.. a.. z, the steel structure layer is marked as a sunken steel structure layer, the number of sunken areas corresponding to each sunken steel structure layer is counted, simultaneously numbering the corresponding sunken areas of each sunken steel structure layer, respectively marking the sunken areas as 1,2.. k.. p, so as to focus the plane scanning images of each sunken steel structure layer on each sunken area, and further acquiring the depression height and the depression length of each depression region, thereby obtaining the depression approximate area corresponding to each depression region in each depression steel structure layer.
sfk is expressed as the approximate area of the corresponding depression of the kth depressed area in the fth depressed steel structure layer, xfk is expressed as the depression length corresponding to the kth depression region of the fth depression steel structure layer, hfk is expressed as the depression height corresponding to the kth depression region of the f-th depression steel structure layer, so that a depression approximate area set S of the depression region of the depression steel structure layer is formedf(sf1,sf2,...,sfk,...,sfp)，sfk represents the depression approximate area corresponding to the kth depression area in the fth depression steel structure layer, f represents the depression steel structure layer number, f is 1,2.
In the embodiment, when the depressed regions of the depressed steel structure layers are obtained, each steel structure layer is scanned in a planar image scanning mode, and the planar scanning images of the steel structure layers are compared with the original planar scanning images of the steel structure layers, so that the depressed regions of the depressed steel structure layers are obtained.
In the embodiment, after the sunken areas of the sunken steel structure layers are obtained, the sunken lengths and the sunken heights of the sunken areas are counted, so that the sunken areas are approximated to triangles, and the sunken correlation coefficients of the steel structure are provided for later counting the safety and stability coefficients of the building steel structure.
And the sunken area positioning module is used for positioning the sunken areas corresponding to the sunken steel structure layers to obtain the geographical positions of the sunken areas corresponding to the sunken steel structure layers and sending the geographical positions to the remote supervision center.
The modeling analysis module respectively receives the node current position three-dimensional coordinate set sent by the node current position acquisition module and the node original position three-dimensional coordinate set sent by the node original position acquisition module, and counts the offset displacement corresponding to each node of each steel structure layer according to the node current position three-dimensional coordinate set and the node original position three-dimensional coordinate set
Lg jExpressed as the offset displacement corresponding to the jth node in the jth steel structure layer, gjxj、gjyj、gjzjRespectively expressed as the current position coordinate of the jth node in the jth steel structure layer on the x axis, the current position coordinate on the y axis and the current position coordinate on the z axis, gjx'j、gjy′j、gjz′jRespectively representing the original position coordinates of the jth node in the g-th steel structure layer on the x axis, the original position coordinates of the jth node in the y axis and the original position coordinates of the jth node in the z axis, comparing the counted offset displacement corresponding to each node of each steel structure layer with the node safety offset displacement set in the database, if the offset displacement corresponding to a certain node of a certain steel structure layer is greater than the set node safety offset displacement, marking the steel structure layer as a dangerous offset steel structure layer, marking the node as a dangerous offset node, counting the number of the dangerous offset steel structure layer and the number of the dangerous offset node corresponding to each dangerous offset steel structure layer at the moment, marking the number of each dangerous offset steel structure layer as 1,2 And the signal is sent to a remote supervision center, and the offset displacement corresponding to each dangerous offset node in each dangerous offset steel structure layer is sent to a management server.
The management server respectively receives the sunken approximate area set of the sunken area of the sunken steel structure layer sent by the sunken area acquisition module of the steel structure layer and the offset displacement corresponding to each dangerous offset node in each dangerous offset steel structure layer sent by the modeling analysis module, extracts the plane area corresponding to each steel structure layer stored in the database and the set node safety offset displacement, and further counts the safety stability coefficient of the building steel structure
sfk is expressed as the approximate area of the depression corresponding to the kth depressed area in the fth depressed steel structure layer, SfExpressed as the planar area, L, corresponding to the f-th sunken steel structure layerbc is represented as the offset displacement corresponding to the c dangerous offset node in the b dangerous offset steel structure layer, L0Node safety offset displacement, D, expressed as set0Expressed as a preset constant, is recorded as 1.25 and is sent to the display terminal.
The safety and stability coefficient of the building steel structure counted by the embodiment synthesizes the offset displacement corresponding to the dangerous offset node in the dangerous offset steel structure layer and the sunken approximate area corresponding to each sunken area in the sunken steel structure layer, realizes the comprehensive quantitative display of the safety and stability condition of the building steel structure, has larger safety and stability coefficient, shows that the safety and stability are better, overcomes the defect of one-sidedness existing in the current monitoring means of the safety and stability of the building steel structure, and greatly meets the comprehensive and accurate monitoring requirement of the safety and stability of the building steel structure.
And the display terminal is used for receiving and displaying the safety and stability coefficient of the building steel structure sent by the management server.
The remote supervision center is used for respectively receiving the numbers of the sunken steel structure layers sent by the steel structure layer sunken area acquisition module, the numbers of the dangerous offset steel structure layers sent by the sunken area positioning module and the dangerous offset node numbers corresponding to the dangerous offset steel structure layers, and related supervision personnel can find corresponding positions quickly, so that the pertinent rectification can be performed in time, the rectification efficiency can be improved, and the occurrence of construction safety accidents caused by the instability of the construction steel structure can be reduced.
The second aspect of the invention provides a cloud monitoring platform, which comprises a processor, a machine-readable storage medium and a network interface, wherein the machine-readable storage medium, the network interface and the processor are connected through a bus system, the network interface is used for being in communication connection with at least one intelligent monitoring device for building steel structure safety and stability, the machine-readable storage medium is used for storing programs, instructions or codes, such as instructions/modules of the intelligent monitoring program for building steel structure safety and stability in the embodiment of the invention, and the processor is used for executing the programs, instructions or codes in the machine-readable storage medium so as to execute the intelligent monitoring method for building steel structure safety and stability based on big data analysis.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (7)
1. The intelligent monitoring method for the safety and stability of the building steel structure based on big data analysis is characterized by comprising the following steps of: the method needs to use an intelligent monitoring system for the safety and stability of the building steel structure based on big data analysis in the specific implementation process, and the system comprises a building steel structure layer dividing module, a steel structure layer node counting module, a node current position obtaining module, a node original position obtaining module, a database, a steel structure layer sunken area obtaining module, a modeling analysis module, a management server, a display terminal and a remote supervision center;
the building steel structure layer dividing module is used for counting the number of steel structure layers of a building steel structure frame to be monitored, dividing the building steel structure frame to be monitored into a plurality of steel structure layers according to the counted number of the steel structure layers, and numbering the divided steel structure layers according to the length distance from the ground, wherein the divided steel structure layers are sequentially marked as 1,2.
The steel structure layer node counting module is used for counting the number of nodes existing in each divided steel structure layer, numbering the counted nodes existing in each steel structure layer, and marking the nodes as 1,2.. j.. m respectively;
the node current position acquisition module is used for acquiring corresponding current position three-dimensional coordinates of each node on each steel structure layer in statistics and forming a node current position three-dimensional coordinate set G [ G1 (x)1,y1,z1),g2(x2,y2,z2),...,gj(xj,yj,zj),...gm(xm,ym,zm)]，gj(xj,yj,zj) Is shown asThe method comprises the steps that current position three-dimensional coordinates corresponding to a jth node on g steel structure layers are represented as steel structure layer numbers, g is 1,2, i, n, and then a node current position three-dimensional coordinate set is sent to a modeling analysis module;
the node original position acquisition module is used for acquiring an original design frame of a building steel structure frame to be monitored, acquiring original position three-dimensional coordinates corresponding to each node of the building steel structure original design frame, and further forming a node original position three-dimensional coordinate set G '[ G1 (x'1,y′1,z′1),g2(x′2,y′2,z′2),...,gj(x′j,y′j,z′j),...gm(x′m,y′m,z′m)]，gj(x′j,y′j,z′j) Expressing the three-dimensional coordinates of the original position corresponding to the jth node on the g steel structure layer, and sending the three-dimensional coordinates of the original position of the node to a modeling analysis module by a node original position acquisition module;
the steel structure layer depressed area acquisition module is used for acquiring a plane scanning image of each steel structure layer divided by the building steel structure frame to be monitored, comparing the acquired plane scanning image of each steel structure layer with each original plane scanning image of each steel structure layer stored in a database, checking whether a depressed area appears, counting the number of the steel structure layer with the depressed area if the depressed area appears, wherein the number can be marked as 1,2.. a.. z, the steel structure layer is marked as a depressed steel structure layer, counting the number of the depressed areas corresponding to each depressed steel structure layer, simultaneously numbering the depressed areas corresponding to each depressed steel structure layer, respectively marking as 1,2.. k.. p, so as to focus the plane scanning image of each depressed steel structure layer on each depressed area, further acquiring the depressed height and the depressed length of each depressed area, and further acquiring the depressed approximate area corresponding to each depressed area in each depressed steel structure layer, thereby forming a set S of approximate concave areas of the concave steel structure layerf(sf1,sf2,...,sfk,...,sfp)，sfk is expressed as the approximate area of the corresponding depression of the kth depressed area in the fth depressed steel structure layer,f is expressed as a sunken steel structure layer number, f is 1,2.. a.. z, a steel structure layer sunken area acquisition module sends a sunken approximate area set of a sunken steel structure layer sunken area to a management server, and sends each sunken steel structure layer number to a remote supervision center;
the modeling analysis module receives the node current position three-dimensional coordinate set sent by the node current position acquisition module and the node original position three-dimensional coordinate set sent by the node original position acquisition module respectively, counts the offset displacement corresponding to each node of each steel structure layer according to the node current position three-dimensional coordinate set and the node original position three-dimensional coordinate set, compares the counted offset displacement corresponding to each node of each steel structure layer with the node safety offset displacement set in the database, if the offset displacement corresponding to a certain node of a certain steel structure layer is greater than the set node safety offset displacement, the steel structure layer is marked as a dangerous offset steel structure layer, the node is marked as a dangerous offset node, counts the number of the dangerous offset steel structure layer and the number of the dangerous offset node corresponding to each dangerous offset steel structure layer at the moment, and the number of each dangerous offset steel structure layer can be marked as 1, y, the dangerous offset node number corresponding to each dangerous offset steel structure layer can be recorded as 1,2.. c.. u, the modeling analysis module sends the number of the dangerous offset steel structure layer and the dangerous offset node number corresponding to each dangerous offset steel structure layer to a remote supervision center, and the offset displacement corresponding to each dangerous offset node in each dangerous offset steel structure layer is sent to a management server;
the management server respectively receives the sunken approximate area set of the sunken area of the sunken steel structure layer sent by the sunken area acquisition module of the steel structure layer and the offset displacement corresponding to each dangerous offset node in each dangerous offset steel structure layer sent by the modeling analysis module, extracts the plane area corresponding to each steel structure layer and the set node safe offset displacement stored in the database, further counts the safe stability coefficient of the building steel structure and sends the safe stability coefficient to the display terminal;
the display terminal is used for receiving and displaying the safety and stability coefficient of the building steel structure sent by the management server;
the remote supervision center is used for respectively receiving the numbers of the sunken steel structure layers sent by the steel structure layer sunken area acquisition module, the numbers of the dangerous offset steel structure layers sent by the modeling analysis module and the dangerous offset node numbers corresponding to the dangerous offset steel structure layers, and then dispatching related management personnel to carry out targeted rectification;
when the intelligent monitoring system for the safety and stability of the building steel structure based on big data analysis is adopted to carry out intelligent monitoring on the safety and stability of the building steel structure, the intelligent monitoring system comprises the following steps;
s1, building steel structure layer division: dividing a building steel structure frame to be monitored into a plurality of steel structure layers according to the counted number of the steel structure layers, and numbering the divided steel structure layers;
s2, steel structure layer node statistics: counting the number of nodes existing in each divided steel structure layer, and numbering the counted nodes existing in each steel structure layer;
s3, acquiring the current position of the node: acquiring current position three-dimensional coordinates corresponding to each node on each counted steel structure layer;
s4, acquiring an original position of a node: acquiring three-dimensional coordinates of corresponding original positions of all nodes on all the counted steel structure layers;
s5, acquiring a sunken area of a steel structure layer: acquiring plane scanning images of each steel structure layer divided by the building steel structure frame to be monitored, and comparing the acquired plane scanning images of each steel structure layer with original plane scanning images of each steel structure layer stored in a database, so as to acquire the depression approximate area of each depression area corresponding to each depression steel structure layer;
s6, dangerous offset steel structure layer and dangerous offset node statistics: counting offset displacements corresponding to nodes of each steel structure layer according to the three-dimensional coordinate set of the current position of the node and the three-dimensional coordinate set of the original position of the node, and comparing the offset displacements with the set safe offset displacements of the nodes, so as to count the numbers of dangerous offset steel structure layers and the numbers of dangerous offset nodes corresponding to the dangerous offset steel structure layers;
s7, safety and stability coefficient statistics: according to the set of the sinking approximate areas of the sinking steel structure layers and the offset displacement corresponding to each dangerous offset node in each dangerous offset steel structure layer, the safety and stability coefficients of the building steel structure are counted;
s8, remote supervision and modification: and dispatching related management personnel to carry out targeted correction according to the numbers of the sunken steel structure layers, the dangerous offset steel structure layers and the dangerous offset node numbers corresponding to the dangerous offset steel structure layers.
2. The intelligent monitoring method for safety and stability of the building steel structure based on big data analysis according to claim 1, characterized in that: the database is used for storing original plane scanning images of all steel structure layers, storing plane areas corresponding to all the steel structure layers and storing set node safety offset displacement.
3. The intelligent monitoring method for safety and stability of the building steel structure based on big data analysis according to claim 1, characterized in that: the device also comprises a sunken area positioning module which is used for carrying out position positioning on the sunken areas corresponding to the sunken steel structure layers to obtain the geographical positions of the sunken areas corresponding to the sunken steel structure layers and sending the geographical positions to a remote supervision center.
4. The intelligent monitoring method for safety and stability of the building steel structure based on big data analysis according to claim 1, characterized in that: the calculation formula of the depression approximate area corresponding to each depression region in each depression steel structure layer is
sfk is expressed as the approximate area of the corresponding depression of the kth depressed area in the fth depressed steel structure layer, xfk is expressed as the depression length corresponding to the kth depression region of the fth depression steel structure layer, hfk is expressed as the depression height corresponding to the kth depression region of the fth depression steel structure layer.
5. Big data based on claim 1The intelligent monitoring method for the safety and stability of the analyzed building steel structure is characterized by comprising the following steps of: the calculation formula of the offset displacement corresponding to each node of each steel structure layer is
Lg jExpressed as the offset displacement corresponding to the jth node in the jth steel structure layer, gjxj、gjyj、gjzjRespectively expressed as the current position coordinate of the jth node in the jth steel structure layer on the x axis, the current position coordinate on the y axis and the current position coordinate on the z axis, gjx'j、gjy′j、gjz′jExpressed as the original position coordinate of the jth node in the jth steel structure layer on the x axis, the original position coordinate on the y axis and the original position coordinate on the z axis respectively.
6. The intelligent monitoring method for safety and stability of the building steel structure based on big data analysis according to claim 1, characterized in that: the calculation formula of the safety and stability coefficient of the building steel structure is
sfk is expressed as the approximate area of the depression corresponding to the kth depressed area in the fth depressed steel structure layer, SfExpressed as the planar area, L, corresponding to the f-th sunken steel structure layerbc is represented as the offset displacement corresponding to the c dangerous offset node in the b dangerous offset steel structure layer, L0Node safety offset displacement, D, expressed as set0Expressed as a predetermined constant, noted 1.25.
7. A cloud monitoring platform, its characterized in that: the cloud monitoring platform comprises a processor, a machine-readable storage medium and a network interface, wherein the machine-readable storage medium, the network interface and the processor are connected through a bus system, the network interface is used for being in communication connection with at least one intelligent monitoring device for the safety and stability of the building steel structure, the machine-readable storage medium is used for storing a program, an instruction or a code, and the processor is used for executing the program, the instruction or the code in the machine-readable storage medium so as to execute the intelligent monitoring method for the safety and stability of the building steel structure based on big data analysis according to any one of claims 1 to 6.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113596813A (en) * | 2021-08-09 | 2021-11-02 | 北京恒安嘉新安全技术有限公司 | Flow shunting method and device, electronic equipment and storage medium |
| CN114858223A (en) * | 2022-07-06 | 2022-08-05 | 南通大学 | Building stability monitoring method based on artificial intelligence and sensor |
| CN116838114A (en) * | 2023-07-06 | 2023-10-03 | 同创华建集团有限公司 | Steel construction and curtain intelligent monitoring system based on data analysis |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109975314A (en) * | 2018-12-27 | 2019-07-05 | 江苏理工学院 | A kind of wood surface detection system and detection method based on three-dimensional laser point cloud data |
| CN110805139A (en) * | 2019-11-08 | 2020-02-18 | 漳州和瑞建材有限公司 | Multi-layer steel structure building frame |
| CN111627099A (en) * | 2019-02-27 | 2020-09-04 | 上海捷规建筑工程咨询有限公司 | Steel structure non-contact actual measurement method and system based on three-dimensional scanning technology |
| CN111929307A (en) * | 2020-08-07 | 2020-11-13 | 上海市建筑科学研究院有限公司 | On-site nondestructive testing and evaluating method for corrosion degree of existing steel structural member |
| CN112053073A (en) * | 2020-09-11 | 2020-12-08 | 张婉婷 | Intelligent detection management platform for quality supervision, acceptance and acceptance of constructional engineering based on big data |
-
2021
- 2021-01-07 CN CN202110019275.XA patent/CN112859681B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109975314A (en) * | 2018-12-27 | 2019-07-05 | 江苏理工学院 | A kind of wood surface detection system and detection method based on three-dimensional laser point cloud data |
| CN111627099A (en) * | 2019-02-27 | 2020-09-04 | 上海捷规建筑工程咨询有限公司 | Steel structure non-contact actual measurement method and system based on three-dimensional scanning technology |
| CN110805139A (en) * | 2019-11-08 | 2020-02-18 | 漳州和瑞建材有限公司 | Multi-layer steel structure building frame |
| CN111929307A (en) * | 2020-08-07 | 2020-11-13 | 上海市建筑科学研究院有限公司 | On-site nondestructive testing and evaluating method for corrosion degree of existing steel structural member |
| CN112053073A (en) * | 2020-09-11 | 2020-12-08 | 张婉婷 | Intelligent detection management platform for quality supervision, acceptance and acceptance of constructional engineering based on big data |
Non-Patent Citations (1)
| Title |
|---|
| 叶珉吕等: "基于点云平面拟合的建筑面积测量方法研究", 《测绘通报》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113596813A (en) * | 2021-08-09 | 2021-11-02 | 北京恒安嘉新安全技术有限公司 | Flow shunting method and device, electronic equipment and storage medium |
| CN113596813B (en) * | 2021-08-09 | 2024-04-05 | 北京恒安嘉新安全技术有限公司 | Flow diversion method and device, electronic equipment and storage medium |
| CN114858223A (en) * | 2022-07-06 | 2022-08-05 | 南通大学 | Building stability monitoring method based on artificial intelligence and sensor |
| CN116838114A (en) * | 2023-07-06 | 2023-10-03 | 同创华建集团有限公司 | Steel construction and curtain intelligent monitoring system based on data analysis |
| CN116838114B (en) * | 2023-07-06 | 2024-01-23 | 同创华建集团有限公司 | Steel construction and curtain intelligent monitoring system based on data analysis |
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