CN112927480A - Geological disaster monitoring method and early warning management platform based on Internet of things and big data collaborative analysis - Google Patents
Geological disaster monitoring method and early warning management platform based on Internet of things and big data collaborative analysis Download PDFInfo
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Abstract
The invention discloses a geological disaster monitoring method and an early warning management platform based on the Internet of things and big data collaborative analysis, which calculate the volume of each sub-area in each layer of curved retaining wall by detecting each basic parameter data of each sub-area in each step type curved retaining wall, arrange a plurality of detection points at the back of each sub-area in each layer of curved retaining wall, detect the soil pressure and the soil water content at each detection point position in each sub-area in each layer of curved retaining wall, analyze the soil thrust force on the back of each sub-area wall in each layer of curved retaining wall and the average soil water content on the back of each sub-area wall, calculate the comprehensive stability influence coefficient of each layer of curved retaining wall area, analyze whether each layer of curved retaining wall area is in a dangerous stage, and number each layer of curved retaining wall area in the dangerous stage for early warning and reminding, thereby realizing the timely early warning effect, avoiding great threat to pedestrians, vehicles and buildings.
Description
Technical Field
The invention relates to the technical field of geological disaster monitoring, in particular to a geological disaster monitoring method and an early warning management platform based on the Internet of things and big data collaborative analysis.
Background
The retaining wall is the important component of various road beds, side slopes and building foundations, but because construction quality has the problem and external factor influences for the retaining wall has great potential safety hazard, causes very big threat for pedestrian, vehicle and building.
At present, present cascaded retaining wall stable monitoring technique is most monitored in individual layer retaining wall region, can't realize the regional real-time supervision of multilayer retaining wall, there is great monitoring limitation, thereby it is lower to cause the precision and the reliability of monitoring data, simultaneously current cascaded retaining wall stable monitoring technique can't consider the stable influence of many-sided factor to the retaining wall, lead to the unable accurate stable state who judges the retaining wall region, thereby can't realize timely early warning effect, make people not have counter-time and maintenance measure well, give the pedestrian, vehicle and building cause very big threat, in order to solve above problem, the geological disasters monitoring method and early warning management platform based on thing networking and big data collaborative analysis are now designed.
Disclosure of Invention
The invention aims to provide a geological disaster monitoring method and an early warning management platform based on the Internet of things and big data collaborative analysis, the invention divides a step-type curved retaining wall area into each subregion in each layer of curved retaining wall, detects each basic parameter data of each subregion in each layer of curved retaining wall, calculates the volume of each subregion in each layer of curved retaining wall, simultaneously arranges a plurality of detection points on the wall back of each subregion in each layer of curved retaining wall, counts the number of each detection point position in each subregion in each layer of curved retaining wall, detects the soil pressure at each detection point position in each subregion in each layer of curved retaining wall, calculates the soil thrust borne by each subregion wall back of each layer of curved retaining wall, detects the soil water content at each detection point position in each subregion in each layer of curved retaining wall, calculates the average soil water content behind each subregion in each layer of curved retaining wall, the contrast obtains the average soil water content difference behind one's back of each subregion wall in the curved retaining wall of each layer, calculates the regional comprehensive stability influence coefficient of each curved retaining wall of each layer simultaneously, whether the curved retaining wall region of each layer of analysis is in dangerous stage to carry out the early warning with the curved retaining wall region number of each layer that is in dangerous stage and remind, solved the problem that exists among the background art.
The purpose of the invention can be realized by the following technical scheme:
in a first aspect, the invention provides a geological disaster monitoring method based on the internet of things and big data collaborative analysis, which comprises the following steps:
s1, dividing the stepped curved retaining wall area into sub-areas in each layer of curved retaining wall, and sequentially numbering positions;
s2, detecting each basic parameter data of each sub-region in each layer of curved retaining wall, and calculating the volume of each sub-region in each layer of curved retaining wall;
s3, arranging a plurality of detection points on the wall backs of the sub-areas in the curved retaining walls of the layers at the same time, and counting the position numbers of the detection points in the sub-areas in the curved retaining walls of the layers;
s4, detecting the soil pressure at the position of each detection point in each sub-area of each layer of curved retaining wall, and calculating the soil thrust on the back of each sub-area of each layer of curved retaining wall;
s5, detecting the soil water content of each detection point position in each sub-area in each layer of curved retaining wall, calculating the average soil water content behind each sub-area wall in each layer of curved retaining wall, and comparing to obtain the average soil water content difference behind each sub-area wall in each layer of curved retaining wall;
s6, calculating the comprehensive stability influence coefficient of each layer of curved retaining wall area, analyzing whether each layer of curved retaining wall area is in a dangerous stage, and numbering each layer of curved retaining wall area in the dangerous stage to perform early warning and reminding;
the geological disaster monitoring method based on the Internet of things and the big data collaborative analysis uses a geological disaster monitoring system based on the Internet of things and the big data collaborative analysis, and comprises a region division module, a basic parameter detection module, a detection point arrangement module, a soil pressure detection module, a soil water content analysis module, an analysis server, a cloud computing center, an early warning reminding module and a cloud database;
the region division module is used for dividing the step-type curved retaining wall region, dividing the step-type curved retaining wall region into a plurality of layers of curved retaining wall regions according to a multilayer step division mode of the retaining wall, numbering the curved retaining wall regions from bottom to top in sequence, and dividing the curved retaining wall regions into 1,2, i, n according to a set arc length equal division modeEach subarea is sequentially subjected to position numbering according to the sequence, the position numbers of the subareas in each layer of curved retaining wall are counted, and a position number set A of the subareas in each layer of curved retaining wall is formedi(ai1,ai2,...,aij,...,aim)，aij represents the position number of the jth sub-region in the ith layer of curved retaining wall, and the position number sets of all sub-regions in each layer of curved retaining wall are respectively sent to the basic parameter detection module and the detection point arrangement module;
the basic parameter detection module is connected with the area division module and comprises a laser range finder for receiving the position number set of each sub-area in each layer of the curved retaining wall sent by the area division module, the laser range finder is used for respectively detecting the chord length, the radius, the width and the height of each sub-area in each layer of the curved retaining wall, each basic parameter data of each sub-area in each layer of the curved retaining wall is counted, and each basic parameter data set W of each sub-area in each layer of the curved retaining wall is formediX(wix1,wix2,...,wixj,...,wixm)，wixjThe method comprises the steps that x-th basic parameter data, expressed as jth sub-regions in the ith curved retaining wall, are respectively expressed as chord length, radius, width and height of the sub-regions in the retaining wall, and each basic parameter data set of each sub-region in each curved retaining wall is sent to an analysis server;
the analysis server is connected with the basic parameter detection module and used for receiving each basic parameter data set of each sub-region in each layer of curved retaining wall sent by the basic parameter detection module, calculating the volume of each sub-region in each layer of curved retaining wall, counting the volume of each sub-region in each layer of curved retaining wall and forming a volume set V of each sub-region in each layer of curved retaining walli(Vi1,Vi2,...,Vij,...,Vim)，Vij is expressed as the volume of the jth sub-area in the ith layer of curved retaining wall, and the volume set of each sub-area in each layer of curved retaining wall is sent to the cloud computing center;
the detection point distribution module is connected with the area division module and used for receiving the position number sets of all sub-areas in each layer of curved retaining wall sent by the area division module, distributing the detection points of all sub-areas in each layer of curved retaining wall, distributing a plurality of detection points in the wall back of each sub-area in an evenly distributed mode, enabling the number of the detection points distributed in the wall back of each sub-area to be the same, sequentially numbering the detection point positions distributed in all sub-areas in each layer of curved retaining wall according to the distribution sequence, counting the position numbers of all the detection points distributed in all sub-areas in each layer of curved retaining wall, and forming a detection point position number set A distributed in all sub-areas in each layer of curved retaining walli jB(ai jb1,ai jb2,...,ai jbr,...,ai jbk)，ai jbrExpressed as the position number of the r-th detection point arranged in the j sub-area of the ith layer of curved retaining wall, and respectively sending the position number sets of the detection points arranged in the sub-areas of the curved retaining walls of each layer to the soil pressure detection module and the soil water content detection module;
the soil pressure detection module is connected with the detection point arrangement module and used for receiving a position number set of each detection point arranged in each sub-area of each layer of curved retaining wall sent by the detection point arrangement module, detecting the received soil pressure at each detection point position in each sub-area of each layer of curved retaining wall, counting the soil pressure at each detection point position in each sub-area of each layer of curved retaining wall, and forming a soil pressure set F at each detection point position in each sub-area of each layer of curved retaining walli jB(fi jb1,fi jb2,...,fi jbr,...,fi jbk)，fi jbrExpressing the soil pressure at the position of the r-th detection point in the j sub-area of the ith layer of curved retaining wall, and detecting each detection point in each sub-area of each layer of curved retaining wallThe set of the soil pressure at the position is sent to an analysis server;
the analysis server is connected with the soil pressure detection module and used for receiving a soil pressure set at each detection point position in each subregion in each layer of curved retaining wall sent by the soil pressure detection module, extracting the chord length and the radius of each subregion in each layer of curved retaining wall, calculating the soil thrust borne by each subregion wall back in each layer of curved retaining wall, counting the soil thrust borne by each subregion wall back in each layer of curved retaining wall, and forming a soil thrust set F borne by each subregion wall back in each layer of curved retaining walliA(Fia1,Fia2,...,Fiaj,...,Fiam)，FiajThe soil thrust force received by the jth sub-area wall back in the ith layer of curved retaining wall is expressed, and the soil thrust force received by each sub-area wall back in each layer of curved retaining wall is sent to the cloud computing center;
the soil water content detection module is connected with the detection point laying module and comprises a soil water content determinator for receiving detection point position number sets laid in each sub-area in each layer of curved retaining wall sent by the detection point laying module, detecting the soil water content at each detection point position in each sub-area in each layer of curved retaining wall through the soil water content determinator, counting the soil water content at each detection point position in each sub-area in each layer of curved retaining wall, and forming a soil water content set G at each detection point position in each sub-area in each layer of curved retaining walli jB(gi jb1,gi jb2,...,gi jbr,...,gi jbk)，gi jbrThe soil water content is represented as the soil water content at the position of the r-th detection point in the j sub-area in the ith layer of curved retaining wall, and the soil water content set at the position of each detection point in each sub-area in each layer of curved retaining wall is sent to the soil water content analysis module;
the soil water content analysis module is connected with the soil water content detection module and used for receiving a soil water content set at each detection point position in each sub-area in each layer of curved retaining wall sent by the soil water content detection module, calculating the average soil water content behind each sub-area wall in each layer of curved retaining wall, counting the average soil water content behind each sub-area wall in each layer of curved retaining wall, and sending the average soil water content behind each sub-area wall in each layer of curved retaining wall to the analysis server;
analysis server is connected with soil water content analysis module for the average soil water content behind each subregion wall in the curved retaining wall of each layer that receives soil water content analysis module and send, draw the safe soil water content behind the curved retaining wall of storage in the cloud database, compare each subregion wall average soil water content behind one's back and safe soil water content in each layer curved retaining wall, obtain the average soil water content difference set behind one's back of each subregion wall in each layer curved retaining wall
The difference value of the average soil water content at the back of the jth sub-area wall in the ith layer of curved retaining wall is expressed as a comparison difference value of the safe soil water content, and the average soil water content difference value at the back of each sub-area wall in each layer of curved retaining wall is sent to the cloud computing center in a set mode;
the cloud computing center is connected with the analysis server and used for receiving the volume set of each sub region in each layer of curved retaining wall, the soil thrust set borne by each sub region wall back in each layer of curved retaining wall and the average soil water content difference set behind each sub region wall in each layer of curved retaining wall sent by the analysis server, extracting the volume of the curved retaining wall stored in the cloud database, the stability influence proportion coefficient of the soil thrust borne by each curved retaining wall back and the soil water content behind the curved retaining wall, computing the comprehensive stability influence coefficient of each layer of curved retaining wall region, simultaneously extracting the safety stability influence coefficient of the curved retaining wall region stored in the cloud database, comparing the comprehensive stability influence coefficient of each layer of curved retaining wall region with the safety stability influence coefficient, if the comprehensive stability influence coefficient of a certain layer of curved retaining wall region is less than or equal to the safety stability influence coefficient, the method comprises the steps that a layer of curved retaining wall area is shown to be in a stable stage, if the comprehensive stability influence coefficient of the layer of curved retaining wall area is larger than the safety stability influence coefficient, the layer of curved retaining wall area is shown to be in a dangerous stage, the serial numbers of the layers of curved retaining wall areas in the dangerous stage are counted, and the serial numbers of the layers of curved retaining wall areas in the dangerous stage are sent to an early warning reminding module;
the early warning reminding module is connected with the cloud computing center and used for receiving serial numbers of curved retaining wall areas of each layer in a dangerous stage, sent by the cloud computing center, and carrying out early warning reminding, and related personnel carry out maintenance measures of corresponding areas according to the early warning reminding;
the cloud database is connected with analysis server and cloud computing center respectively for safe soil water content G' a behind the curved retaining wall of storage, the stable influence proportionality coefficient of storing curved retaining wall volume, curved retaining wall back of the body and receiving soil thrust and curved retaining wall back of the body soil water content simultaneously, record as lambda respectivelyV,λF,λGAnd storing the safety and stability influence coefficient of the curved retaining wall area.
In one possible design of the first aspect, the volume calculation formula of each sub-area in each layer of the curved retaining wall is
Vij is expressed as the volume of the jth sub-area in the ith curved retaining wall, and pi is expressed as the circumferential ratio and is equal to 3.14, wiljExpressed as the chord length, w, of the jth sub-zone in the ith curved retaining wallirjExpressed as the radius, w, of the jth sub-zone in the ith curved retaining wallidjExpressed as the width, w, of the jth sub-zone in the ith curved retaining wallihjExpressed as the height of the jth sub-zone in the ith course of curved retaining wall.
In a possible design of the first aspect, the soil pressure detection module includes a plurality of pressure sensors, where the plurality of pressure sensors are respectively installed at each detection point in each sub-area of each layer of curved retaining wall, and the plurality of pressure sensors are in one-to-one correspondence with each detection point in each sub-area of each layer of curved retaining wall.
In a possible design of the first aspect, the calculation formula of the soil thrust force applied to the back of each sub-area wall in each layer of curved retaining wall is
FiajExpressed as the thrust of the soil to which the jth sub-area wall back of the curved retaining wall of the ith layer is subjected, fi jbrExpressed as the soil pressure at the location of the r-th detection point in the j-th sub-area of the curved retaining wall of the i-th layer, wiljExpressed as the chord length, w, of the jth sub-zone in the ith curved retaining wallirjExpressed as the radius of the jth sub-zone in the ith course of curved retaining wall.
In one possible design of the first aspect, the calculation formula of the average soil moisture content behind the sub-region walls in each of the layers of the curved retaining walls is
Expressed as the average soil moisture content behind the jth sub-section wall in the ith curved retaining wall, gi jbrThe soil water content at the position of the r-th detection point in the j-th sub-region in the ith curved retaining wall is expressed, and k is the number of detection points arranged in the wall back of each sub-region in each curved retaining wall.
In one possible design of the first aspect, the calculation formula of the comprehensive stability influence coefficient of each layer of the curved retaining wall area is
ξiExpressed as the overall stability coefficient of influence, λ, of the curved retaining wall area of the ith courseF,λG,λVRespectively expressed as the stable influence proportionality coefficient of soil thrust on the back of curved retaining wall, the water content of soil behind the back of curved retaining wall and the volume of curved retaining wall, FiajExpressed as the soil thrust received by the back of the jth sub-area wall in the ith layer of curved retaining wall, m is expressed as the number of sub-areas divided in the ith layer of curved retaining wall,
expressed as the difference of the average soil moisture content behind the jth sub-area wall in the ith curved retaining wall compared with the safe soil moisture content, G' a is expressed as the safe soil moisture content behind the curved retaining wall, e is expressed as a natural number, equal to 2.718, Vij is expressed as the volume of the jth sub-zone in the ith layer of curved retaining wall.
In a second aspect, the present invention further provides an early warning management platform, where the early warning management platform includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is configured to be communicatively connected to at least one geological disaster monitoring device, the machine-readable storage medium is configured to store a program, instructions, or codes, and the processor is configured to execute the program, instructions, or codes in the machine-readable storage medium to perform the geological disaster monitoring method according to the present invention.
Has the advantages that:
(1) the invention provides a geological disaster monitoring method and an early warning management platform based on the Internet of things and big data collaborative analysis, which divide a step-type curved retaining wall area into each subregion in each layer of curved retaining wall, detect each basic parameter data of each subregion in each layer of curved retaining wall, calculate the volume of each subregion in each layer of curved retaining wall, lay a foundation for analyzing the comprehensive stability influence coefficient of each layer of curved retaining wall area in the later period, simultaneously arrange a plurality of detection points on the wall back of each subregion in each layer of curved retaining wall, count the position numbers of each detection point in each subregion in each layer of curved retaining wall, thereby realizing the real-time monitoring of the multilayer retaining wall area, avoiding the existence of larger monitoring limitation, improving the accuracy and reliability of monitoring data, detecting the soil pressure at each detection point position in each subregion in each layer of curved retaining wall, the soil thrust that each subregion wall received back of the body in the curved retaining wall of each layer is calculated to the soil water content of each check point position department in each subregion in the curved retaining wall of each layer is detected, calculate the average soil water content behind each subregion wall in each layer curved retaining wall, the contrast obtains the average soil water content difference behind each subregion wall in each layer curved retaining wall, it provides reliable reference data to calculate the regional comprehensive stability influence coefficient of each layer curved retaining wall in later stage.
(2) According to the method, whether each layer of curved retaining wall area is in a dangerous stage or not is analyzed by calculating the comprehensive stability influence coefficient of each layer of curved retaining wall area, so that the stable state of each layer of curved retaining wall area is accurately judged, and the number of each layer of curved retaining wall area in the dangerous stage is early-warned, so that a timely early warning effect is realized, people can have enough coping time and preparation maintenance measures, and great threats to pedestrians, vehicles and buildings are avoided.
Drawings
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 flow chart of the method steps of the present invention;
fig. 2 is a schematic view of a module connection structure 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 geological disaster monitoring method based on internet of things and big data collaborative analysis, including the following steps:
s1, dividing the stepped curved retaining wall area into sub-areas in each layer of curved retaining wall, and sequentially numbering positions;
s2, detecting each basic parameter data of each sub-region in each layer of curved retaining wall, and calculating the volume of each sub-region in each layer of curved retaining wall;
s3, arranging a plurality of detection points on the wall backs of the sub-areas in the curved retaining walls of the layers at the same time, and counting the position numbers of the detection points in the sub-areas in the curved retaining walls of the layers;
s4, detecting the soil pressure at the position of each detection point in each sub-area of each layer of curved retaining wall, and calculating the soil thrust on the back of each sub-area of each layer of curved retaining wall;
s5, detecting the soil water content of each detection point position in each sub-area in each layer of curved retaining wall, calculating the average soil water content behind each sub-area wall in each layer of curved retaining wall, and comparing to obtain the average soil water content difference behind each sub-area wall in each layer of curved retaining wall;
s6, calculating the comprehensive stability influence coefficient of each layer of curved retaining wall area, analyzing whether each layer of curved retaining wall area is in a dangerous stage, and carrying out early warning and reminding on the serial number of each layer of curved retaining wall area in the dangerous stage.
Referring to fig. 2, the geological disaster monitoring method based on the internet of things and big data collaborative analysis uses a geological disaster monitoring system based on the internet of things and big data collaborative analysis, and the geological disaster monitoring system comprises a region division module, a basic parameter detection module, a detection point arrangement module, a soil pressure detection module, a soil water content analysis module, an analysis server, a cloud computing center, an early warning reminding module and a cloud database.
The region division module is used for dividing the step-type curved retaining wall region, dividing the step-type curved retaining wall region into a plurality of layers of curved retaining wall regions according to the multilayer step division mode of the retaining wall, and sequentially dividing the plurality of layers of curved retaining wall regions from bottom to topNumbering is carried out in sequence, the number of a plurality of layers of curved retaining wall areas is 1,2, thei(ai1,ai2,...,aij,...,aim)，aij is the position number of the jth sub-area in the ith layer of curved retaining wall, and the position number sets of all sub-areas in each layer of curved retaining wall are respectively sent to the basic parameter detection module and the detection point layout module.
The basic parameter detection module is connected with the area division module and comprises a laser range finder for receiving the position number set of each sub-area in each layer of the curved retaining wall sent by the area division module, the laser range finder is used for respectively detecting the chord length, the radius, the width and the height of each sub-area in each layer of the curved retaining wall, each basic parameter data of each sub-area in each layer of the curved retaining wall is counted, and each basic parameter data set W of each sub-area in each layer of the curved retaining wall is formediX(wix1,wix2,...,wixj,...,wixm)，wixjAnd (3) expressing the x-th basic parameter data of the j-th sub-area in the ith curved retaining wall, wherein x is l, r, d, h, l, r, d and h respectively express the chord length, the radius, the width and the height of the sub-area in the retaining wall, and sending each basic parameter data set of each sub-area in each curved retaining wall to an analysis server.
The analysis server is connected with the basic parameter detection module and used for receiving each basic parameter data set of each sub-region in each layer of curved retaining wall sent by the basic parameter detection module and calculating the volume of each sub-region in each layer of curved retaining wall
Vij being the jth sub-zone of the curved retaining wall of the ith courseVolume, π is expressed as a circumference ratio, equal to 3.14, wiljExpressed as the chord length, w, of the jth sub-zone in the ith curved retaining wallirjExpressed as the radius, w, of the jth sub-zone in the ith curved retaining wallidjExpressed as the width, w, of the jth sub-zone in the ith curved retaining wallihjThe height of the jth sub-area in the ith layer of curved retaining wall is expressed, the volume of each sub-area in each layer of curved retaining wall is counted, and a volume set V of each sub-area in each layer of curved retaining wall is formedi(Vi1,Vi2,...,Vij,...,Vim), a foundation is laid for analyzing the comprehensive stability influence coefficient of each layer of curved retaining wall area in the later stage, and the volume set of each sub-area in each layer of curved retaining wall is sent to the cloud computing center.
The detection point distribution module is connected with the area division module and used for receiving the position number sets of all sub-areas in each layer of curved retaining wall sent by the area division module, distributing the detection points of all sub-areas in each layer of curved retaining wall, distributing a plurality of detection points in the wall back of each sub-area in an evenly distributed mode, enabling the number of the detection points distributed in the wall back of each sub-area to be the same, sequentially numbering the detection point positions distributed in all sub-areas in each layer of curved retaining wall according to the distribution sequence, counting the position numbers of all the detection points distributed in all sub-areas in each layer of curved retaining wall, and forming a detection point position number set A distributed in all sub-areas in each layer of curved retaining walli jB(ai jb1,ai jb2,...,ai jbr,...,ai jbk)，ai jbrThe detection device comprises a soil pressure detection module, a soil water content detection module, a first detection point position number, a second detection point position number, a third detection point position number and a fourth detection point position number, wherein the first detection point position number is distributed in the jth sub-area of the ith layer of curved retaining wall, the second detection point position number is distributed in each sub-area of each layer of curved retaining wall, the first detection point position number and the second detection point position number are respectively sent to the soil pressure detection module and the soil water content detection module, and thereforeAccuracy and reliability.
The soil pressure detection module is connected with the detection point laying module, and comprises a plurality of pressure sensors, the pressure sensors are respectively arranged at detection points in each sub-area of each layer of curved retaining wall, the pressure sensors are in one-to-one correspondence with the detection points in each sub-area of each layer of curved retaining wall, and are used for receiving detection point position number sets which are arranged in each sub-area of each layer of curved retaining wall and sent by the detection point laying module, detecting the received soil pressure at the detection point positions in each sub-area of each layer of curved retaining wall, counting the soil pressure at the detection point positions in each sub-area of each layer of curved retaining wall, and forming a soil pressure set F at the detection point positions in each sub-area of each layer of curved retaining walli jB(fi jb1,fi jb2,...,fi jbr,...,fi jbk)，fi jbrAnd (3) expressing the soil pressure at the position of the r-th detection point in the j sub-area in the ith layer of curved retaining wall, and sending the soil pressure set at the position of each detection point in each sub-area in each layer of curved retaining wall to an analysis server.
The analysis server is connected with the soil pressure detection module and used for receiving the soil pressure set at the position of each detection point in each sub-area in each layer of curved retaining wall sent by the soil pressure detection module, extracting the chord length and the radius of each sub-area in each layer of curved retaining wall and calculating the soil thrust borne by the wall back of each sub-area in each layer of curved retaining wall
FiajExpressed as the thrust of the soil to which the jth sub-area wall back of the curved retaining wall of the ith layer is subjected, fi jbrExpressed as the soil pressure at the location of the r-th detection point in the j-th sub-area of the curved retaining wall of the i-th layer, wiljExpressed as the chord length, w, of the jth sub-zone in the ith curved retaining wallirjCurved retaining soil expressed as ith layerThe radius of the jth sub-area in the wall is counted, the soil thrust force borne by each sub-area wall back in each layer of curved retaining wall is counted, and a soil thrust force set F borne by each sub-area wall back in each layer of curved retaining wall is formediA(Fia1,Fia2,...,Fiaj,...,Fiam) And reliable reference data are provided for later-stage calculation of comprehensive stability influence coefficients of each layer of curved retaining wall area, and soil thrust borne by each sub-area wall back in each layer of curved retaining wall is integrally sent to the cloud computing center.
The soil water content detection module is connected with the detection point laying module and comprises a soil water content determinator for receiving detection point position number sets laid in each sub-area in each layer of curved retaining wall sent by the detection point laying module, detecting the soil water content at each detection point position in each sub-area in each layer of curved retaining wall through the soil water content determinator, counting the soil water content at each detection point position in each sub-area in each layer of curved retaining wall, and forming a soil water content set G at each detection point position in each sub-area in each layer of curved retaining walli jB(gi jb1,gi jb2,...,gi jbr,...,gi jbk)，gi jbrAnd (3) expressing the soil water content at the position of the r-th detection point in the j sub-area in the ith layer of curved retaining wall, and sending the soil water content set at each detection point position in each sub-area in each layer of curved retaining wall to a soil water content analysis module.
Soil water content analysis module is connected with soil water content detection module for the soil water content set of each check point position department in each subregion in the curved retaining wall of each layer that receiving soil water content detection module sent calculates the average soil water content behind each subregion wall in each layer curved retaining wall
Denoted as the jth sub-wall in the ith curved retaining wallAverage soil moisture content behind regional walls, gi jbrThe method comprises the steps of representing the soil water content at the position of an r-th detection point in a j-th sub-area in the ith layer of curved retaining wall, representing k as the number of detection points distributed in the wall back of each sub-area in each layer of curved retaining wall, counting the average soil water content behind each sub-area wall in each layer of curved retaining wall, and sending the average soil water content behind each sub-area wall in each layer of curved retaining wall to an analysis server.
Analysis server is connected with soil water content analysis module for the average soil water content behind each subregion wall in the curved retaining wall of each layer that receives soil water content analysis module and send, draw the safe soil water content behind the curved retaining wall of storage in the cloud database, compare each subregion wall average soil water content behind one's back and safe soil water content in each layer curved retaining wall, obtain the average soil water content difference set behind one's back of each subregion wall in each layer curved retaining wall
The comparison difference value of the average soil water content and the safe soil water content at the back of the jth sub-area wall in the ith layer of curved retaining wall is represented, reliable reference data are provided for the comprehensive stability influence coefficient of each layer of curved retaining wall area in the later period calculation, and the average soil water content difference value set at the back of each sub-area wall in each layer of curved retaining wall is sent to the cloud calculation center.
The cloud computing center is connected with the analysis server, the volume set of each subregion in each layer of curved retaining wall for receiving analysis server transmission, the soil thrust set that each subregion wall received on the back of the body in each layer of curved retaining wall and the average soil moisture content differential value set behind each subregion wall in each layer of curved retaining wall, draw the curved retaining wall volume of storage in the cloud database, the curved retaining wall receives on the back of the body soil thrust and the stable influence proportionality coefficient of soil moisture content behind the curved retaining wall, calculate the regional comprehensive stable influence coefficient of each layer of curved retaining wall
ξiExpressed as the overall stability coefficient of influence, λ, of the curved retaining wall area of the ith courseF,λG,λVRespectively expressed as the stable influence proportionality coefficient of soil thrust on the back of curved retaining wall, the water content of soil behind the back of curved retaining wall and the volume of curved retaining wall, FiajExpressed as the soil thrust received by the back of the jth sub-area wall in the ith layer of curved retaining wall, m is expressed as the number of sub-areas divided in the ith layer of curved retaining wall,
expressed as the difference of the average soil moisture content behind the jth sub-area wall in the ith curved retaining wall compared with the safe soil moisture content, G' a is expressed as the safe soil moisture content behind the curved retaining wall, e is expressed as a natural number, equal to 2.718, Vij represents the volume for jth sub-region in the curved retaining wall of ith layer, draw the regional safety and stability influence coefficient of curved retaining wall of storage in the cloud database simultaneously, compare the regional comprehensive stability influence coefficient and the safety and stability influence coefficient of curved retaining wall of each layer, if the regional comprehensive stability influence coefficient of curved retaining wall of certain layer is less than or equal to the safety and stability influence coefficient, show that this layer of curved retaining wall region is in stable stage, if the regional comprehensive stability influence coefficient of curved retaining wall of certain layer is greater than the safety and stability influence coefficient, show that this layer of curved retaining wall region is in dangerous stage, the regional serial number of curved retaining wall of each layer that statistics is in dangerous stage, send the regional serial number of curved retaining wall of each layer that will be in dangerous stage to early warning module, thereby the stable state in curved retaining wall region of each layer is judged to the accuracy.
The early warning reminding module is connected with the cloud computing center and used for receiving serial numbers of the curved retaining wall areas of each layer in the dangerous stage, sent by the cloud computing center, and carrying out early warning reminding, and related personnel carry out maintenance measures corresponding to the areas according to the early warning reminding, so that a timely early warning effect is achieved, people can have enough coping time and prepare maintenance measures, and great threats to pedestrians, vehicles and buildings are avoided.
The cloud database is connected with analysis server and cloud computing center respectively for safe soil water content G' a behind the curved retaining wall of storage, the stable influence proportionality coefficient of storing curved retaining wall volume, curved retaining wall back of the body and receiving soil thrust and curved retaining wall back of the body soil water content simultaneously, record as lambda respectivelyV,λF,λGAnd storing the safety and stability influence coefficient of the curved retaining wall area.
In a second aspect, the present invention further provides an early warning management platform, where the early warning management platform includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is configured to be communicatively connected to at least one geological disaster monitoring device, the machine-readable storage medium is configured to store a program, instructions, or codes, and the processor is configured to execute the program, instructions, or codes in the machine-readable storage medium to perform the geological disaster monitoring method according to the present invention.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made 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 (7)
1. The geological disaster monitoring method based on the Internet of things and big data collaborative analysis is characterized by comprising the following steps: the method comprises the following steps:
s1, dividing the stepped curved retaining wall area into sub-areas in each layer of curved retaining wall, and sequentially numbering positions;
s2, detecting each basic parameter data of each sub-region in each layer of curved retaining wall, and calculating the volume of each sub-region in each layer of curved retaining wall;
s3, arranging a plurality of detection points on the wall backs of the sub-areas in the curved retaining walls of the layers at the same time, and counting the position numbers of the detection points in the sub-areas in the curved retaining walls of the layers;
s4, detecting the soil pressure at the position of each detection point in each sub-area of each layer of curved retaining wall, and calculating the soil thrust on the back of each sub-area of each layer of curved retaining wall;
s5, detecting the soil water content of each detection point position in each sub-area in each layer of curved retaining wall, calculating the average soil water content behind each sub-area wall in each layer of curved retaining wall, and comparing to obtain the average soil water content difference behind each sub-area wall in each layer of curved retaining wall;
s6, calculating the comprehensive stability influence coefficient of each layer of curved retaining wall area, analyzing whether each layer of curved retaining wall area is in a dangerous stage, and numbering each layer of curved retaining wall area in the dangerous stage to perform early warning and reminding;
the geological disaster monitoring method based on the Internet of things and the big data collaborative analysis uses a geological disaster monitoring system based on the Internet of things and the big data collaborative analysis, and comprises a region division module, a basic parameter detection module, a detection point arrangement module, a soil pressure detection module, a soil water content analysis module, an analysis server, a cloud computing center, an early warning reminding module and a cloud database;
the region division module is used for dividing a step-type curved retaining wall region, dividing the step-type curved retaining wall region into a plurality of layers of curved retaining wall regions according to a multilayer step division mode of the retaining wall, numbering the curved retaining wall regions from bottom to top in sequence, wherein the numbering of the curved retaining wall regions is 1,2, 1, i, n, dividing the curved retaining wall regions into sub-regions according to a set arc length equal division mode, numbering the sub-regions in the curved retaining wall regions in sequence, counting the position numbers of the sub-regions in the curved retaining wall regions in each layer, and forming a position number set A of the sub-regions in the curved retaining wall regions in each layeri(ai1,ai2,...,aij,...,aim)，aij is the position number of the jth sub-area in the ith layer of curved retaining wallThe position number sets of all the sub-areas are respectively sent to a basic parameter detection module and a detection point layout module;
the basic parameter detection module is connected with the area division module and comprises a laser range finder for receiving the position number set of each sub-area in each layer of the curved retaining wall sent by the area division module, the laser range finder is used for respectively detecting the chord length, the radius, the width and the height of each sub-area in each layer of the curved retaining wall, each basic parameter data of each sub-area in each layer of the curved retaining wall is counted, and each basic parameter data set W of each sub-area in each layer of the curved retaining wall is formediX(wix1,wix2,...,wixj,...,wixm)，wixjThe method comprises the steps that x-th basic parameter data, expressed as jth sub-regions in the ith curved retaining wall, are respectively expressed as chord length, radius, width and height of the sub-regions in the retaining wall, and each basic parameter data set of each sub-region in each curved retaining wall is sent to an analysis server;
the analysis server is connected with the basic parameter detection module and used for receiving each basic parameter data set of each sub-region in each layer of curved retaining wall sent by the basic parameter detection module, calculating the volume of each sub-region in each layer of curved retaining wall, counting the volume of each sub-region in each layer of curved retaining wall and forming a volume set V of each sub-region in each layer of curved retaining walli(Vi1,Vi2,...,Vij,...,Vim)，Vij is expressed as the volume of the jth sub-area in the ith layer of curved retaining wall, and the volume set of each sub-area in each layer of curved retaining wall is sent to the cloud computing center;
the detection point distribution module is connected with the area division module and used for receiving the position number set of each sub-area in each layer of the curved retaining wall sent by the area division module, distributing the detection points of each sub-area in each layer of the curved retaining wall, distributing a plurality of detection points in the wall back of each sub-area in an evenly distributed mode, wherein the number of the detection points distributed in the wall back of each sub-area is the same, and distributing the detection points in each sub-areaThe detection point positions distributed in each sub-region in the layer curved retaining wall are numbered in sequence according to the distribution sequence, the detection point position numbers distributed in each sub-region in each layer curved retaining wall are counted, and a detection point position number set A distributed in each sub-region in each layer curved retaining wall is formedi jB(ai jb1,ai jb2,...,ai jbr,...,ai jbk)，ai jbrExpressed as the position number of the r-th detection point arranged in the j sub-area of the ith layer of curved retaining wall, and respectively sending the position number sets of the detection points arranged in the sub-areas of the curved retaining walls of each layer to the soil pressure detection module and the soil water content detection module;
the soil pressure detection module is connected with the detection point arrangement module and used for receiving a position number set of each detection point arranged in each sub-area of each layer of curved retaining wall sent by the detection point arrangement module, detecting the received soil pressure at each detection point position in each sub-area of each layer of curved retaining wall, counting the soil pressure at each detection point position in each sub-area of each layer of curved retaining wall, and forming a soil pressure set F at each detection point position in each sub-area of each layer of curved retaining walli jB(fi jb1,fi jb2,...,fi jbr,...,fi jbk)，fi jbrThe soil pressure at the position of an r-th detection point in a j-th sub-area in the ith layer of curved retaining wall is expressed, and the soil pressure set at the position of each detection point in each sub-area in each layer of curved retaining wall is sent to an analysis server;
the analysis server is connected with the soil pressure detection module and used for receiving the soil pressure set at the position of each detection point in each sub-area in each layer of curved retaining wall sent by the soil pressure detection module, extracting the chord length and the radius of each sub-area in each layer of curved retaining wall, calculating the soil thrust borne by the wall back of each sub-area in each layer of curved retaining wall, and counting the soil thrust borne by each sub-area wall backThe soil thrust borne by the wall backs of the sub-areas in each layer of curved retaining wall forms a soil thrust set F borne by the wall backs of the sub-areas in each layer of curved retaining walliA(Fia1,Fia2,...,Fiaj,...,Fiam)，FiajThe soil thrust force received by the jth sub-area wall back in the ith layer of curved retaining wall is expressed, and the soil thrust force received by each sub-area wall back in each layer of curved retaining wall is sent to the cloud computing center;
the soil water content detection module is connected with the detection point laying module and comprises a soil water content determinator for receiving detection point position number sets laid in each sub-area in each layer of curved retaining wall sent by the detection point laying module, detecting the soil water content at each detection point position in each sub-area in each layer of curved retaining wall through the soil water content determinator, counting the soil water content at each detection point position in each sub-area in each layer of curved retaining wall, and forming a soil water content set G at each detection point position in each sub-area in each layer of curved retaining walli jB(gi jb1,gi jb2,...,gi jbr,...,gi jbk)，gi jbrThe soil water content is represented as the soil water content at the position of the r-th detection point in the j sub-area in the ith layer of curved retaining wall, and the soil water content set at the position of each detection point in each sub-area in each layer of curved retaining wall is sent to the soil water content analysis module;
the soil water content analysis module is connected with the soil water content detection module and used for receiving a soil water content set at each detection point position in each sub-area in each layer of curved retaining wall sent by the soil water content detection module, calculating the average soil water content behind each sub-area wall in each layer of curved retaining wall, counting the average soil water content behind each sub-area wall in each layer of curved retaining wall, and sending the average soil water content behind each sub-area wall in each layer of curved retaining wall to the analysis server;
the above-mentionedAnalysis server is connected with soil water content analysis module for receive the average soil water content behind each subregion wall among each layer curved retaining wall that soil water content analysis module sent, draw the safe soil water content behind the curved retaining wall of storage among the cloud database, compare each subregion wall average soil water content behind one's back and safe soil water content among each layer curved retaining wall, the average soil water content difference set behind each subregion wall among the curved retaining wall of each layer is obtained
The difference value of the average soil water content at the back of the jth sub-area wall in the ith layer of curved retaining wall is expressed as a comparison difference value of the safe soil water content, and the average soil water content difference value at the back of each sub-area wall in each layer of curved retaining wall is sent to the cloud computing center in a set mode;
the cloud computing center is connected with the analysis server and used for receiving the volume set of each sub region in each layer of curved retaining wall, the soil thrust set borne by each sub region wall back in each layer of curved retaining wall and the average soil water content difference set behind each sub region wall in each layer of curved retaining wall sent by the analysis server, extracting the volume of the curved retaining wall stored in the cloud database, the stability influence proportion coefficient of the soil thrust borne by each curved retaining wall back and the soil water content behind the curved retaining wall, computing the comprehensive stability influence coefficient of each layer of curved retaining wall region, simultaneously extracting the safety stability influence coefficient of the curved retaining wall region stored in the cloud database, comparing the comprehensive stability influence coefficient of each layer of curved retaining wall region with the safety stability influence coefficient, if the comprehensive stability influence coefficient of a certain layer of curved retaining wall region is less than or equal to the safety stability influence coefficient, the method comprises the steps that a layer of curved retaining wall area is shown to be in a stable stage, if the comprehensive stability influence coefficient of the layer of curved retaining wall area is larger than the safety stability influence coefficient, the layer of curved retaining wall area is shown to be in a dangerous stage, the serial numbers of the layers of curved retaining wall areas in the dangerous stage are counted, and the serial numbers of the layers of curved retaining wall areas in the dangerous stage are sent to an early warning reminding module;
the early warning reminding module is connected with the cloud computing center and used for receiving serial numbers of curved retaining wall areas of each layer in a dangerous stage, sent by the cloud computing center, and carrying out early warning reminding, and related personnel carry out maintenance measures of corresponding areas according to the early warning reminding;
the cloud database is connected with analysis server and cloud computing center respectively for safe soil water content G' a behind the curved retaining wall of storage, the stable influence proportionality coefficient of storing curved retaining wall volume, curved retaining wall back of the body and receiving soil thrust and curved retaining wall back of the body soil water content simultaneously, record as lambda respectivelyV,λF,λGAnd storing the safety and stability influence coefficient of the curved retaining wall area.
2. The geological disaster monitoring method based on the internet of things and big data collaborative analysis is characterized in that: the volume calculation formula of each sub-area in each layer of curved retaining wall is
Vij is expressed as the volume of the jth sub-area in the ith curved retaining wall, and pi is expressed as the circumferential ratio and is equal to 3.14, wiljExpressed as the chord length, w, of the jth sub-zone in the ith curved retaining wallirjExpressed as the radius, w, of the jth sub-zone in the ith curved retaining wallidjExpressed as the width, w, of the jth sub-zone in the ith curved retaining wallihjExpressed as the height of the jth sub-zone in the ith course of curved retaining wall.
3. The geological disaster monitoring method based on the internet of things and big data collaborative analysis is characterized in that: the soil pressure detection module comprises a plurality of pressure sensors, wherein the pressure sensors are respectively installed at each detection point in each sub-area in each layer of curved retaining wall, and the pressure sensors are in one-to-one correspondence with each detection point in each sub-area in each layer of curved retaining wall.
4. The geological disaster monitoring method based on the internet of things and big data collaborative analysis is characterized in that: the calculation formula of the soil thrust borne by the wall backs of all the sub-areas in each layer of curved retaining wall is
FiajExpressed as the thrust of the soil to which the jth sub-area wall back of the curved retaining wall of the ith layer is subjected, fi jbrExpressed as the soil pressure at the location of the r-th detection point in the j-th sub-area of the curved retaining wall of the i-th layer, wiljExpressed as the chord length, w, of the jth sub-zone in the ith curved retaining wallirjExpressed as the radius of the jth sub-zone in the ith course of curved retaining wall.
5. The geological disaster monitoring method based on the internet of things and big data collaborative analysis is characterized in that: the calculation formula of the average soil water content behind each sub-area wall in each layer of curved retaining wall is
Expressed as the average soil moisture content behind the jth sub-section wall in the ith curved retaining wall, gi jbrThe soil water content at the position of the r-th detection point in the j-th sub-region in the ith curved retaining wall is expressed, and k is the number of detection points arranged in the wall back of each sub-region in each curved retaining wall.
6. The geological disaster monitoring method based on the internet of things and big data collaborative analysis according to claim 1, wherein the geological disaster monitoring method is based on the internet of things and big data collaborative analysisIs characterized in that: the calculation formula of the comprehensive stability influence coefficient of each layer of curved retaining wall area is
ξiExpressed as the overall stability coefficient of influence, λ, of the curved retaining wall area of the ith courseF,λG,λVRespectively expressed as the stable influence proportionality coefficient of soil thrust on the back of curved retaining wall, the water content of soil behind the back of curved retaining wall and the volume of curved retaining wall, FiajExpressed as the soil thrust received by the back of the jth sub-area wall in the ith layer of curved retaining wall, m is expressed as the number of sub-areas divided in the ith layer of curved retaining wall,
expressed as the difference of the average soil moisture content behind the jth sub-area wall in the ith curved retaining wall compared with the safe soil moisture content, G' a is expressed as the safe soil moisture content behind the curved retaining wall, e is expressed as a natural number, equal to 2.718, Vij is expressed as the volume of the jth sub-zone in the ith layer of curved retaining wall.
7. An early warning management platform, its characterized in that: the early warning management 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 geological disaster monitoring device, the machine-readable storage medium is used for storing programs, instructions or codes, and the processor is used for executing the programs, the instructions or the codes in the machine-readable storage medium so as to execute the geological disaster monitoring method as claimed in any one of claims 1 to 6.
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