CN111709664A - Bridge structure safety monitoring management system based on big data - Google Patents

Bridge structure safety monitoring management system based on big data Download PDF

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CN111709664A
CN111709664A CN202010594744.6A CN202010594744A CN111709664A CN 111709664 A CN111709664 A CN 111709664A CN 202010594744 A CN202010594744 A CN 202010594744A CN 111709664 A CN111709664 A CN 111709664A
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张玉红
王亚运
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Abstract

The invention discloses a road tunnel engineering safety real-time monitoring and management system based on big data, which comprises a settlement observation point division module, a foundation settlement monitoring and analyzing module, a stay cable force monitoring and analyzing module, a tower crane inclination detecting and analyzing module, a standard database, a data processing center, a central server and a display terminal. According to the road tunnel engineering safety real-time monitoring and management system based on the big data, provided by the invention, the comprehensive health coefficient of the bridge structure is counted by integrating the uneven settlement coefficient, the cable force risk coefficient and the inclination risk coefficient of the bridge deck, the comprehensive health coefficient of the bridge structure is matched with the comprehensive health coefficient of the bridge structure corresponding to each health grade of the bridge structure, and the health grade corresponding to the comprehensive health coefficient of the bridge structure is screened, so that the safe and accurate monitoring of various parameters of the bridge structure is realized, the comprehensive health condition of the bridge structure can be evaluated, the technical level of bridge management is improved, and the normal operation of the bridge is guaranteed.

Description

Bridge structure safety monitoring management system based on big data
Technical Field
The invention relates to the technical field of bridge structure monitoring, in particular to a bridge structure safety monitoring and management system based on big data.
Background
In recent decades, the construction of highway bridges in China enters a high-speed development period, a plurality of bridges are constructed every year, and caused bridge engineering accidents sometimes occur.
Therefore, each highway management department strengthens the detection strength of the bridge, and carries out safety evaluation on the bridge in operation, but the general bridge structure detection is that the appearance of the bridge is evaluated by combining visual inspection with an instrument, the deformation of the bridge structure cannot be accurately known, meanwhile, in daily inspection, the phenomena of bridge deck settlement and tower crane inclination of some bridges are observed by naked eyes, but whether the settlement deformation and the inclination deformation of the bridges are within safety limits cannot be known, more importantly, the comprehensive health condition of the bridge structure cannot be evaluated, so that corresponding maintenance measures cannot be executed, and therefore, the invention designs the bridge structure safety monitoring and management system based on big data.
Disclosure of Invention
The invention aims to provide a road tunnel engineering safety real-time monitoring and management system based on big data, which quantifies a bridge deck uneven settlement coefficient, a cable force danger coefficient and an inclination danger coefficient of a bridge structure through a comprehensive foundation settlement monitoring and analyzing module, a cable force monitoring and analyzing module, a tower crane inclination detecting and analyzing module and a data processing center, further counts out a comprehensive health coefficient of the bridge structure, matches the comprehensive health coefficient of the bridge structure corresponding to each health grade of the bridge structure, screens the health grade corresponding to the comprehensive health coefficient of the bridge structure, and executes corresponding measures, thereby solving the problems in the background technology.
The purpose of the invention can be realized by the following technical scheme:
a bridge structure safety monitoring and management system based on big data comprises a settlement observation point dividing module, a foundation settlement monitoring and analyzing module, a guy cable force monitoring and analyzing module, a tower crane inclination detecting and analyzing module, a standard database, a data processing center, a central server and a display terminal;
the system comprises a basic settlement monitoring and analyzing module, a data processing center, a central server, a settlement observation point dividing module, a data processing center, a inhaul cable force monitoring and analyzing module, a standard database, a display terminal and a control module, wherein the basic settlement monitoring and analyzing module is connected with the settlement observation point dividing module;
the settlement observation point dividing module is used for uniformly dividing the whole bridge floor into m sections along the linear distance from the bridge head to the bridge tail, each division point is used as a settlement observation point, an auxiliary observation point is arranged in the middle of a certain bridge pier, the settlement observation points are numbered along the direction from the bridge head to the bridge tail and are sequentially marked as 1,2, j, m-1, and the settlement observation points are fixed on a bridge deck;
the foundation settlement monitoring and analyzing module comprises an optical fiber displacement sensor and is connected with a settlement observation point dividing module, and the foundation settlement monitoring comprises the following steps:
s1: connecting each settlement observation point with an auxiliary observation point, measuring the distance from each settlement observation point to the auxiliary observation point by using an optical fiber displacement sensor, recording the distance as a basic settlement displacement, and forming a primary basic settlement displacement set S (S) by using each obtained basic settlement displacement1,s2,...,sj,...,sm-1),sjExpressed as the base settlement displacement between the jth settlement observation point and the auxiliary observation point;
s2: comparing the basic settlement displacement of each settlement observation point with the initial basic settlement displacement of each settlement observation point in the standard database to obtain a comparison difference value, recording the comparison difference value as primary basic settlement deformation, and forming a basic settlement displacement deformation set delta S (delta S) by the obtained primary basic settlement deformation1,Δs2,...,Δsj,...,Δsm-1), ΔsjPrimary settlement deformation expressed as the jth settlement observation point;
s3: re-measuring the distance from each settlement observation point to the auxiliary observation point at fixed time intervals, and forming a secondary foundation settlement displacement set S ' (S ') by each obtained foundation settlement displacement '1,s′2,...,s′j,...,s′m-1),s′jThe base settlement displacement between the jth settlement observation point and the auxiliary observation point expressed as measurements after a fixed time interval;
s4: and comparing the secondary basic settlement displacement set with the initial basic settlement displacement of each settlement observation point in the standard database to obtain a comparison difference value, recording the comparison difference value as a secondary basic settlement deformation, and forming a secondary basic settlement displacement deformation set delta S '(delta S'1,Δs′2,...,Δs′j,...,Δs′m-1),Δs′jExpressing the secondary foundation settlement deformation of the jth settlement observation point;
s5: counting the relative foundation settlement deformation of each settlement observation point according to the primary foundation settlement displacement deformation set and the secondary foundation settlement displacement deformation set, comparing the relative foundation settlement deformation with the safe foundation settlement deformation of each settlement observation point, counting the settlement observation points with uneven settlement if the relative foundation settlement deformation of the settlement observation points is greater than the safe foundation settlement deformation of the settlement observation points, sequentially marking the settlement observation points with uneven settlement as 1,2.
The stay cable force monitoring module comprises a plurality of magnetic flux sensors, each bundle of stay cables is evenly divided into a plurality of sections along the length from one end to the other end of the stay cable, each equal division end point of each equal division end point is used as a cable force monitoring point, the plurality of magnetic flux sensors are respectively installed at each monitoring point on each bundle of stay cables of the bridge, when a hanging cable is tensioned, the magnetic flux sensors of each monitoring point respectively display the force value of the corresponding hole position, the arithmetic mean value of the force measured by three hole positions on the magnetic flux sensor on a certain monitoring point is multiplied by the total number of steel strands of the stay cable where the monitoring point is located, the stay cable force value of the monitoring point is measured and calculated, the calculated stay cable force values of each monitoring point on each bundle of stay cables form a single-bundle stay cable force set F (F1, F2.,. fi.,. fn), fn represents the stay cable force value of the ith monitoring point of the stay cable, n is the number of the monitoring points, the cable force variation is obtained by comparing the cable force variation with the original cable force value of the inhaul cable, the obtained cable force variation of each monitoring point of each bundle of inhaul cable forms a single bundle of inhaul cable force variation set delta F (delta F1, delta F2, a.,. delta fi.,. delta fn) which is the cable force variation of the ith monitoring point of the inhaul cable, the cable force variation of each monitoring point of each bundle of inhaul cable is averaged to obtain the cable force average variation, the cable force average variation is compared with the preset safe cable force average variation, the preset safe cable force average variation comprises a first safe cable force average variation and a second safe cable force average variation, if the cable force average variation is smaller than the first safe cable force average variation, the cable force danger level is one level, if the cable force average variation is larger than the first safe cable force average variation and is smaller than the second safe cable force average variation, the cable force danger level is two levels, if the cable force is larger than the second safe cable force average variable quantity, the cable force danger level is three levels, and the cable force danger level of the cable is sent to the data processing center by the cable force monitoring module;
the tower crane inclination detection and analysis module comprises an inclination angle sensor, and the detection method comprises the following steps:
w1: arranging points, namely uniformly dividing the central axis of the bridge tower crane into four sections along the vertical distance H from the tower top to the tower bottom, wherein the arrangement point positions are sequentially a tower top fulcrum, an H/4 point, a middle point, a 3H/4 point and a tower bottom fulcrum along the direction from the tower top to the tower bottom;
w2: the inclination angle sensors are respectively placed at the positions of all arrangement points, the tower crane is supposed to incline in a linear range, and the inclination angle value of each arrangement point on the central axis of the tower crane can be obtained according to the voltage difference output by each arrangement point inclination angle sensor before and after loading;
w3: setting the total measurement time as T, and determining an inclination angle time course curve theta of each distribution point of the tower crane according to the voltage output by the inclination angle sensor of each distribution point at each moment and the voltage difference output by the inclination angle sensor at the initial momentk(t)(k=1,2,3,4,5,t=t1,t2,...,tf),θk(t) as the kth layout pointThe inclination angle time course curves t1, t2, and tf are represented as measuring moments, and the inclination degree of the tower crane is counted according to the inclination angle time course curves of all the arrangement points;
w4: comparing the counted inclination of the tower crane with a preset safe inclination of the tower crane, wherein if the calculated inclination of the tower crane is greater than the preset safe inclination, the inclination risk coefficient mu is 0.75, and if the calculated inclination of the tower crane is less than the preset safe inclination, the inclination risk coefficient mu is 0.25;
the standard database stores the initial foundation settlement displacement and the safe foundation settlement deformation of each settlement observation point, stores the stress value of each bundle of guy cables, the average change amount of the safe guy cables and the cable force danger coefficient corresponding to each cable force danger level, stores the safe inclination of the tower crane and stores the structure health coefficient corresponding to each health level of the bridge structure;
the data processing center receives the cable force danger levels of the cables sent by the cable force monitoring module, extracts cable force danger coefficients corresponding to the cable force danger levels in the standard database, screens the cable force danger coefficients corresponding to the cable force danger levels and sends the cable force danger coefficients to the central server;
the central server receives the uneven settlement coefficient sent by the basic settlement monitoring and analyzing module, receives the inclination risk coefficient sent by the tower crane inclination detecting and analyzing module, receives the cable force risk coefficient sent by the data processing center, superposes the uneven settlement coefficient, the cable force risk coefficient and the inclination risk coefficient to obtain a comprehensive health coefficient of the bridge structure, matches the counted comprehensive health coefficient of the bridge structure with a comprehensive health coefficient of a structure corresponding to each preset health grade of the bridge structure, screens the health grade corresponding to the comprehensive health coefficient of the bridge structure, and executes corresponding measures;
and the display terminal is used for receiving and displaying the comprehensive health coefficient of the bridge structure sent by the central server.
Preferably, the initial foundation settlement displacement is a foundation settlement displacement measured when the bridge is put into use formally.
Further, the calculation formula of the uneven settlement coefficient of the bridge deck is as follows
Figure BDA0002557115470000051
Δs′aExpressed as the second degree of primary settlement deformation, Δ s, at the a-th differential settlement observation pointaPrimary basis settlement distortion, s, expressed as the a-th uneven settlement observation pointa0Expressing the safe base settlement deformation amount of the a-th differential settlement observation point, g is the number of the differential settlement observation points, delta s'jSecond order base settlement distortion, Δ s, expressed as the jth settlement observation pointjPrimary basis settlement distortion, s, expressed as the jth settlement observation pointj0Expressed as safe base settlement distortion for the jth settlement observation point.
Further, the formula for calculating the inclination of the tower crane is as follows:
Figure BDA0002557115470000061
θk(t) is represented by a slope time curve, λ, for the kth set pointkExpressed as the proportional influence coefficient of the kth set point, and T as the total measurement time.
Furthermore, the magnitude sequence corresponding to the comprehensive health coefficients of the bridge structure corresponding to different health grades of the bridge structure is sigmaA>σB>σC>σD
Furthermore, each health level of the preset bridge structure comprises a level A, a level B, a level C and a level D, the health and safety condition of the bridge corresponding to each health level and the corresponding countermeasure are respectively the health and safety condition of the bridge corresponding to the level A, the bridge is free of structure damage, the countermeasure is to keep normal monitoring frequency and observation, the health and safety condition of the bridge corresponding to the level B is slight damage of the structure, the countermeasure is to increase the monitoring frequency and to observe continuously, the health and safety condition of the bridge corresponding to the level C is local damage of the structure, the countermeasure is to perform related renovation on the local damaged part, the health and safety condition of the bridge corresponding to the level D is serious structural damage, and the countermeasure is to close the whole bridge, and complete renovation is performed.
Has the advantages that:
(1) according to the invention, the uneven settlement coefficient, the cable force danger coefficient and the inclination risk coefficient of the bridge deck of the bridge structure are counted by the foundation settlement monitoring and analyzing module, the cable force monitoring and analyzing module, the tower crane inclination degree detecting and analyzing module and the data processing center, so that the comprehensive health coefficient of the bridge structure is obtained, is matched with the comprehensive health coefficient of the bridge structure corresponding to each health grade of the bridge structure, and the health grade corresponding to the comprehensive health coefficient of the bridge structure is screened.
(2) According to the invention, a plurality of monitoring points are arranged on the foundation settlement monitoring and analyzing module, the inhaul cable force monitoring and analyzing module and the tower crane inclination degree detecting and analyzing module, so that the detected data is closer to a real numerical value, the detection error phenomenon caused by detection of a single monitoring point is avoided, and the monitoring accuracy is improved.
(3) According to the method, the quantification of the health condition of the bridge structure is realized through the statistics of the safety coefficient of the bridge structure, bridge managers can conveniently and visually know the health condition of the bridge structure, meanwhile, the health grade of the bridge is divided according to the safety coefficient of the bridge structure, and the bridge managers can conveniently execute corresponding treatment measures according to different health grades of the bridge.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying 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 bridge structure safety monitoring and management system based on big data includes a settlement observation point division module, a foundation settlement monitoring and analyzing module, a guy cable force monitoring and analyzing module, a tower crane inclination detecting and analyzing module, a standard database, a data processing center, a central server and a display terminal.
The basic settlement monitoring and analyzing module is connected with the settlement observation point dividing module, the data processing center is connected with the inhaul cable force monitoring and analyzing module, the central server is respectively connected with the basic settlement monitoring and analyzing module, the inhaul cable force monitoring and analyzing module, the data processing center and the standard database, and the display terminal is connected with the central server.
The settlement observation point dividing module is characterized in that settlement observation points of the bridge deck are arranged along two sides of a lane, the whole bridge deck is uniformly divided into m sections along the linear distance from the bridge head to the bridge tail, each division point serves as a settlement observation point, an auxiliary observation point is arranged in the middle of a certain bridge pier, the settlement observation points are numbered along the direction from the bridge head to the bridge tail and are sequentially marked as 1,2.
The foundation settlement monitoring and analyzing module comprises an optical fiber displacement sensor and is connected with a settlement observation point dividing module, and the foundation settlement monitoring comprises the following steps:
s1: connecting each settlement observation point with an auxiliary observation point, measuring the distance from each settlement observation point to the auxiliary observation point by using an optical fiber displacement sensor, recording the distance as a basic settlement displacement, and forming a primary basic settlement displacement set S (S) by using each obtained basic settlement displacement1,s2,...,sj,...,sm-1),sjExpressed as the base settlement displacement between the jth settlement observation point and the auxiliary observation point;
s2: comparing the basic settlement displacement of each settlement observation point with the initial basic settlement displacement of each settlement observation point in the standard database to obtain a comparison difference value, marking the comparison difference value as primary basic settlement deformation, wherein the initial basic settlement displacement is the basic settlement displacement measured when the bridge is put into use formally, and the obtained primary basic settlement deformation forms a basic settlement displacement deformation set delta S (delta S)1,Δs2,...,Δsj,...,Δsm-1),ΔsjPrimary settlement deformation expressed as the jth settlement observation point;
s3: re-measuring the distance from each settlement observation point to the auxiliary observation point at fixed time intervals, and forming a secondary foundation settlement displacement set S ' (S ') by each obtained foundation settlement displacement '1,s′2,...,s′j,...,s′m-1),s′jThe base settlement displacement between the jth settlement observation point and the auxiliary observation point expressed as measurements after a fixed time interval;
s4: and comparing the secondary basic settlement displacement set with the initial basic settlement displacement of each settlement observation point in the standard database to obtain a comparison difference value, recording the comparison difference value as a secondary basic settlement deformation, and forming a secondary basic settlement displacement deformation set delta S '(delta S'1,Δs′2,...,Δs′j,...,Δs′m-1),Δs′jExpressing the secondary foundation settlement deformation of the jth settlement observation point;
s5: counting the relative foundation settlement deformation of each settlement observation point according to the primary foundation settlement displacement deformation set and the secondary foundation settlement displacement deformation set, comparing the relative foundation settlement deformation with the safe foundation settlement deformation of each settlement observation point, counting the settlement observation points with uneven settlement if the relative foundation settlement deformation of the settlement observation points is larger than the safe foundation settlement deformation of the settlement observation points, sequentially marking the settlement observation points with uneven settlement as 1,2
Figure BDA0002557115470000091
Δs′aExpressed as the second degree of primary settlement deformation, Δ s, at the a-th differential settlement observation pointaPrimary basis settlement distortion, s, expressed as the a-th differential settlement observation pointa0Is expressed as the safe base settlement deformation amount of the a-th uneven settlement observation point, g is the number of the uneven settlement observation points, delta s'jSecond order base settlement distortion, Δ s, expressed as the jth settlement observation pointjPrimary basis settlement distortion, s, expressed as the jth settlement observation pointj0And (3) representing the safe foundation settlement deformation quantity of the jth settlement observation point, wherein the larger the uneven settlement coefficient is, the higher the bridge deck deformation danger degree is, and sending the counted uneven settlement coefficient of the bridge deck to the central server.
The inhaul cable force monitoring module comprises a plurality of magnetic flux sensors, each magnetic flux sensor is a non-loss detection technology, the inhaul cable force is measured in a non-contact mode, the bridge structure cannot be damaged, and the inhaul cable force monitoring module is strong in anti-interference capacity, high in measurement precision and good in repeatability in the measurement process. Evenly dividing the length of each bundle of stay cables from one end to the other end of the stay cable into a plurality of sections, taking each equal division end point as a cable force monitoring point, determining the specification of a magnetic flux sensor according to the outer diameter of the stay cable, simultaneously respectively installing the selected magnetic flux sensors at each monitoring point on each bundle of stay cables of the bridge, respectively displaying the force value of the corresponding hole position by the magnetic flux sensors at each monitoring point when the stay cable is tensioned, multiplying the arithmetic mean value of the forces measured by three hole positions on the magnetic flux sensor at a certain monitoring point by the total number of steel strands of the stay cable at the monitoring point, measuring and calculating the cable force value of the monitoring point, and forming a single-bundle cable force set F (F1, F2.,. fi.,. fn), wherein fn represents the cable force value of the ith monitoring point of the stay cable, n is the number of the monitoring points, the cable force variation is obtained by comparing with the original cable force value of the inhaul cable, the obtained cable force variation of each monitoring point of each bundle of inhaul cable forms a single bundle of inhaul cable force variation set delta F (delta F1, delta F2, a., (delta fi., (delta fn), the delta fi is the cable force variation of the ith monitoring point of the inhaul cable, the cable force variation of each monitoring point of each bundle of inhaul cable is averaged to obtain the cable force average variation, the cable force average variation is compared with the preset safe cable force average variation, the preset safe cable force average variation comprises a first safe cable force average variation and a second safe cable force average variation, if the cable force danger level is one level, if the cable force average variation is larger than the first safe cable force average variation and is smaller than the second safe cable force average variation, the cable force danger level is two levels, if the cable force danger level is larger than the second safe cable force average variable quantity, the cable force danger level is three levels, and the cable force monitoring module sends the cable force danger level of the cable to the data processing center.
The tower crane inclination detection and analysis module comprises an inclination angle sensor, and the detection and analysis method comprises the following steps:
w1: arranging points, namely uniformly dividing the central axis of the bridge tower crane into four sections along the vertical distance H from the tower top to the tower bottom, wherein the arrangement point positions are sequentially a tower top fulcrum, an H/4 point, a middle point, a 3H/4 point and a tower bottom fulcrum along the direction from the tower top to the tower bottom;
w2: the inclination angle sensors are respectively placed at the positions of all arrangement points, the tower crane is supposed to incline in a linear range, and the inclination angle value of each arrangement point on the central axis of the tower crane can be obtained according to the voltage difference output by each arrangement point inclination angle sensor before and after loading;
w3: setting the total measurement time as T, and determining an inclination angle time course curve theta of each distribution point of the tower crane according to the voltage output by the inclination angle sensor of each distribution point at each moment and the voltage difference output by the inclination angle sensor at the initial momentk(t) (k is 1,2,3,4,5, t is t1, t2, t.t., tf), dynamically shows the inclination angle change of each layout point of the tower crane, t1, t2, t.t.t.f are expressed as measuring moments, and the interval time between the measuring moments is
Figure BDA0002557115470000111
Counting the gradient of the tower crane according to the inclination angle time course curve of each distribution point
Figure BDA0002557115470000112
θk(t) is represented by a slope time curve, λ, for the kth set pointkThe proportional influence coefficient is expressed as the kth distribution point, T is expressed as the total measurement time, and the higher the inclination is, the higher the inclination risk degree is;
w4: the tower crane inclination of statistics is compared with the preset tower crane safety inclination, if the tower crane inclination is greater than the preset safety inclination, the inclination risk coefficient mu is 0.75, and if the tower crane inclination is less than the preset safety inclination, the inclination risk coefficient mu is 0.25.
This embodiment has all set up a plurality of monitoring points at basic settlement monitoring analysis module, cable force monitoring analysis module and tower crane gradient detection analysis module for the data that detect are closer real numerical value, avoid the detection error phenomenon that single monitoring point detected and caused, have improved the degree of accuracy of monitoring.
The standard database stores initial foundation settlement displacement and safe foundation settlement deformation of each settlement observation point, stores stress values of each bundle of guy cables, safe cable force average variation and cable force danger coefficients corresponding to each cable force danger level, stores safe inclination of the tower crane, and stores structural health coefficients corresponding to each health level of the bridge structure, wherein the magnitude sequence corresponding to the comprehensive health coefficients of the bridge structure corresponding to different health levels of the bridge structure is sigmaA>σB>σC>σD
And the data processing center receives the cable force danger levels of the cables sent by the cable force monitoring module, extracts cable force danger coefficients corresponding to the cable force danger levels in the standard database, screens the cable force danger coefficients corresponding to the cable force danger levels and sends the cable force danger coefficients to the central server.
The central server receives the uneven settlement coefficient sent by the foundation settlement monitoring and analyzing module, receives the inclination risk coefficient sent by the tower crane inclination detecting and analyzing module, receives the cable force risk coefficient sent by the data processing center, and superposes the uneven settlement coefficient, the cable force risk coefficient and the inclination risk coefficient to obtain a comprehensive health coefficient of the bridge structure.
The preset health levels of the bridge structure comprise an A level, a B level, a C level and a D level, the health and safety conditions of the bridge corresponding to the health levels and corresponding countermeasures are respectively that the health and safety conditions of the bridge corresponding to the A level health level are non-damaged, the countermeasures are to keep normal monitoring frequency and observation, the health and safety conditions of the bridge corresponding to the B level health level are that the structure is slightly damaged, the countermeasures are to increase the monitoring frequency and continue observation, the dynamic development situation of the health condition of the bridge structure is facilitated to related bridge managers to master by increasing the monitoring frequency, the health and safety conditions of the bridge corresponding to the C level health level are that the structure is locally damaged, the countermeasures are to perform related renovation on the damaged local part, the health and safety conditions of the bridge corresponding to the D level health level are that the structure is seriously damaged, and the countermeasures are to close the whole bridge, and (5) performing full-range rectification.
And the display terminal is used for receiving the comprehensive health coefficient of the bridge structure sent by the central server and displaying the comprehensive health coefficient, so that bridge management personnel can know the health condition of the bridge structure intuitively.
According to the invention, the uneven settlement coefficient, the cable force danger coefficient and the inclination danger coefficient of the bridge deck of the bridge structure are counted through the foundation settlement monitoring and analyzing module, the cable force monitoring and analyzing module, the tower crane inclination detecting and analyzing module and the data processing center, so that the comprehensive health coefficient of the bridge structure is obtained, is matched with the comprehensive health coefficient of the bridge structure corresponding to each health grade of the bridge structure, and the health grade corresponding to the comprehensive health coefficient of the bridge structure is screened.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions may be made in the specific embodiments described by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.

Claims (6)

1. The utility model provides a bridge structures safety monitoring management system based on big data which characterized in that: the system comprises a settlement observation point dividing module, a foundation settlement monitoring and analyzing module, a stay cable force monitoring and analyzing module, a tower crane inclination detecting and analyzing module, a standard database, a data processing center, a central server and a display terminal;
the system comprises a basic settlement monitoring and analyzing module, a data processing center, a central server, a settlement observation point dividing module, a data processing center, a inhaul cable force monitoring and analyzing module, a standard database, a display terminal and a central server, wherein the basic settlement monitoring and analyzing module is connected with the settlement observation point dividing module;
the settlement observation point dividing module is used for uniformly dividing a whole bridge floor into m sections along the linear distance from a bridge head to a bridge tail by setting bridge floor settlement observation points along two sides of a traffic lane, each division point is used as a settlement observation point, an auxiliary observation point is set in the middle of a certain bridge pier, the settlement observation points are numbered along the direction from the bridge head to the bridge tail and are sequentially marked as 1,2, j, m-1, and the settlement observation points are fixed on a bridge deck;
the basic settlement monitoring and analyzing module comprises an optical fiber displacement sensor and is connected with a settlement observation point dividing module, and the basic settlement monitoring comprises the following steps:
s1: connecting each settlement observation point with an auxiliary observation point, respectively measuring the distance from each settlement observation point to the auxiliary observation point by using an optical fiber displacement sensor, recording the distance as the basic settlement displacement, and forming a primary basic settlement displacement set S (S) by using each obtained basic settlement displacement1,s2,...,sj,...,sm-1),sjExpressed as the base settlement displacement between the jth settlement observation point and the auxiliary observation point;
s2: comparing the basic settlement displacement of each settlement observation point with the initial basic settlement displacement of each settlement observation point in the standard database to obtain a comparison difference value, recording the comparison difference value as primary basic settlement deformation, and forming a basic settlement displacement deformation set delta S (delta S) by the obtained primary basic settlement deformation1,Δs2,...,Δsj,...,Δsm-1),ΔsjPrimary settlement deformation expressed as the jth settlement observation point;
s3: re-measuring the distance from each settlement observation point to the auxiliary observation point at fixed time intervals, and forming a secondary foundation settlement displacement set S ' (S ') by each obtained foundation settlement displacement '1,s′2,...,s′j,...,s′m-1),s′jThe base settlement displacement between the jth settlement observation point and the auxiliary observation point expressed as measurements after a fixed time interval;
s4: and comparing the secondary foundation settlement displacement set with the initial foundation settlement displacement of each settlement observation point in the standard database to obtain a comparison difference, recording the comparison difference as a secondary foundation settlement deformation, and forming a secondary foundation settlement displacement deformation set delta S '(delta S'1,Δs′2,...,Δs′j,...,Δs′m-1),Δs′jExpressing the secondary foundation settlement deformation of the jth settlement observation point;
s5: counting the relative foundation settlement deformation of each settlement observation point according to the primary foundation settlement displacement deformation set and the secondary foundation settlement displacement deformation set, comparing the relative foundation settlement deformation with the safe foundation settlement deformation of each settlement observation point, counting the settlement observation points with uneven settlement if the relative foundation settlement deformation of the settlement observation points is greater than the safe foundation settlement deformation of the settlement observation points, sequentially marking the settlement observation points with uneven settlement as 1,2.
The inhaul cable force monitoring module comprises a plurality of magnetic flux sensors, each bundle of inhaul cable is evenly divided into a plurality of sections along the length from one end to the other end of the inhaul cable, each equal division end point of each magnetic flux sensor is used as a cable force monitoring point, the magnetic flux sensors are respectively installed at each monitoring point on each bundle of inhaul cable of the bridge, when a hanging cable is tensioned, the magnetic flux sensors of each monitoring point respectively display the force value of the corresponding hole position, the arithmetic mean value of the forces measured by three hole positions on the magnetic flux sensor on a certain monitoring point is multiplied by the total number of steel strands of the inhaul cable where the monitoring point is located, the inhaul cable force value of the monitoring point is measured and calculated, the inhaul cable force values of each monitoring point on each bundle of inhaul cable which are calculated are formed into a single-bundle inhaul cable force set F (F1, F2.,..,. fi.,. fn), wherein fn represents the inhaul cable force value of the ith, n is the number of the monitoring points, the cable force variation is obtained by comparing with the original cable force value of the inhaul cable, the obtained cable force variation of each monitoring point of each bundle of inhaul cable forms a single bundle of inhaul cable force variation set delta F (delta F1, delta F2, delta F, delta fi, delta F), the delta F is the cable force variation of the ith monitoring point of the inhaul cable, the cable force variation of each monitoring point of each bundle of inhaul cable is averaged to obtain the cable force average variation, the cable force average variation is compared with the preset safe cable force average variation, the preset safe cable force average variation comprises a first safe cable force average variation and a second safe cable force average variation, if the cable force danger level is one level, if the cable force average variation is larger than the first safe cable force average variation and is smaller than the second safe cable force average variation, the cable force danger level is two levels, if the cable force is larger than the second safe cable force average variable quantity, the cable force danger level is three levels, and the cable force danger level of the cable is sent to the data processing center by the cable force monitoring module;
the tower crane inclination detection and analysis module comprises an inclination angle sensor, and the detection method comprises the following steps:
w1: arranging points, namely uniformly dividing the central axis of the bridge tower crane into four sections along the vertical distance H from the tower top to the tower bottom, wherein the arrangement point positions are sequentially a tower top fulcrum, an H/4 point, a middle point, a 3H/4 point and a tower bottom fulcrum along the direction from the tower top to the tower bottom;
w2: the inclination angle sensors are respectively placed at the positions of all the arrangement points, the inclination angle value of each arrangement point on the axis of the tower crane can be obtained according to the voltage difference output by each arrangement point inclination angle sensor before and after loading on the assumption that the tower crane inclines in a linear range;
w3: setting the total measurement time as T, and determining an inclination angle time course curve theta of each distribution point of the tower crane according to the voltage output by the inclination angle sensor of each distribution point at each moment and the voltage difference output by the inclination angle sensor at the initial momentk(t)(k=1,2,3,4,5,t=t1,t2,...,tf),θk(t) representing an inclination angle time course curve of the kth distribution point, and t1, t2, and tf representing a measurement moment, and counting the inclination of the tower crane according to the inclination angle time course curve of each distribution point;
w4: comparing the counted inclination of the tower crane with a preset safe inclination of the tower crane, wherein if the calculated inclination of the tower crane is greater than the preset safe inclination, the inclination risk coefficient mu is 0.75, and if the calculated inclination of the tower crane is less than the preset safe inclination, the inclination risk coefficient mu is 0.25;
the standard database stores initial foundation settlement displacement and safe foundation settlement deformation of each settlement observation point, stores stress values of each bundle of stay cables, average change amount of safe cable force and cable force danger coefficients corresponding to each cable force danger level, stores safe inclination of the tower crane and stores structure health coefficients corresponding to each health level of the bridge structure;
the data processing center receives the cable force danger levels of the cables sent by the cable force monitoring module, extracts cable force danger coefficients corresponding to the cable force danger levels in the standard database, screens the cable force danger coefficients corresponding to the cable force danger levels and sends the cable force danger coefficients to the central server;
the central server receives the uneven settlement coefficient sent by the foundation settlement monitoring and analyzing module, receives the inclination risk coefficient sent by the tower crane inclination detecting and analyzing module, receives the cable force risk coefficient sent by the data processing center, superposes the uneven settlement coefficient, the cable force risk coefficient and the inclination risk coefficient to obtain a comprehensive health coefficient of the bridge structure, matches the counted comprehensive health coefficient of the bridge structure with a comprehensive health coefficient of a structure corresponding to each preset health grade of the bridge structure, screens the health grade corresponding to the comprehensive health coefficient of the bridge structure, and executes corresponding measures;
and the display terminal is used for receiving and displaying the comprehensive health coefficient of the bridge structure sent by the central server.
2. The bridge structure safety monitoring and management system based on big data according to claim 1, characterized in that: the initial foundation settlement displacement is measured when the bridge is put into use formally.
3. The bridge structure safety monitoring and management system based on big data according to claim 1, characterized in that: the calculation formula of the uneven settlement coefficient of the bridge deck is
Figure FDA0002557115460000051
Δs′aExpressed as the second degree of primary settlement deformation, Δ s, at the a-th differential settlement observation pointaPrimary basis settlement distortion, s, expressed as the a-th differential settlement observation pointa0Is expressed as the safe base settlement deformation amount of the a-th uneven settlement observation point, g is expressed as the number of uneven settlement observation points, delta s'jSecond order base settlement distortion, Δ s, expressed as the jth settlement observation pointjPrimary basis settlement distortion, s, expressed as the jth settlement observation pointj0Expressed as safe base settlement distortion for the jth settlement observation point.
4. The bridge structure safety monitoring and management system based on big data according to claim 1, characterized in that: the inclination calculation formula of the tower crane is as follows:
Figure FDA0002557115460000052
θk(t) is represented by a slope time curve, λ, for the kth set pointkExpressed as the proportional influence coefficient of the kth set point, and T as the total measurement time.
5. The bridge structure safety monitoring and management system based on big data according to claim 1, characterized in that: the corresponding magnitude sequence of the comprehensive health coefficients of the bridge structure corresponding to different health grades of the bridge structure is sigmaA>σB>σC>σD
6. The road tunnel engineering safety real-time monitoring management system based on big data according to claim 1, characterized in that: each health grade of the preset bridge structure comprises an A grade, a B grade, a C grade and a D grade, the bridge health safety condition corresponding to each health grade and corresponding countermeasures are respectively the bridge health safety condition corresponding to the A grade health grade and are non-damaged, the countermeasures are used for keeping normal monitoring frequency and observation, the bridge health safety condition corresponding to the B grade health grade is slightly damaged, the countermeasures are used for increasing the monitoring frequency and continuing observation, the bridge health safety condition corresponding to the C grade health grade is locally damaged, the countermeasures are used for performing related renovation on damaged local parts, the bridge health safety condition corresponding to the D grade health grade is severely damaged, and the countermeasures are used for closing the whole bridge and performing comprehensive renovation.
CN202010594744.6A 2020-06-28 2020-06-28 Bridge structure safety monitoring management system based on big data Withdrawn CN111709664A (en)

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112232685A (en) * 2020-10-20 2021-01-15 汤涛 Engineering quality supervision acceptance real-time detection analysis management system based on big data
CN113049029A (en) * 2021-03-06 2021-06-29 义乌市叶微建筑科技有限公司 Urban road operation safety online monitoring cloud platform based on wireless communication technology
CN117495111A (en) * 2023-12-29 2024-02-02 广州市嘉品电子科技有限公司 Building engineering safety management system based on BIM technology
CN117541234A (en) * 2023-12-04 2024-02-09 南京新鸿运物业管理股份有限公司 Engineering maintenance diagnosis system and method based on big data

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112232685A (en) * 2020-10-20 2021-01-15 汤涛 Engineering quality supervision acceptance real-time detection analysis management system based on big data
CN112232685B (en) * 2020-10-20 2021-05-07 武汉华胜工程建设科技有限公司 Engineering quality supervision acceptance real-time detection analysis management system based on big data
CN113049029A (en) * 2021-03-06 2021-06-29 义乌市叶微建筑科技有限公司 Urban road operation safety online monitoring cloud platform based on wireless communication technology
CN117541234A (en) * 2023-12-04 2024-02-09 南京新鸿运物业管理股份有限公司 Engineering maintenance diagnosis system and method based on big data
CN117541234B (en) * 2023-12-04 2024-04-26 南京新鸿运物业管理股份有限公司 Engineering maintenance diagnosis system and method based on big data
CN117495111A (en) * 2023-12-29 2024-02-02 广州市嘉品电子科技有限公司 Building engineering safety management system based on BIM technology
CN117495111B (en) * 2023-12-29 2024-03-26 广州市嘉品电子科技有限公司 Building engineering safety management system based on BIM technology

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