CN107870591A - A kind of underground engineering deformation remote auto monitoring control system based on internet - Google Patents
A kind of underground engineering deformation remote auto monitoring control system based on internet Download PDFInfo
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- CN107870591A CN107870591A CN201711079691.9A CN201711079691A CN107870591A CN 107870591 A CN107870591 A CN 107870591A CN 201711079691 A CN201711079691 A CN 201711079691A CN 107870591 A CN107870591 A CN 107870591A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0428—Safety, monitoring
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24024—Safety, surveillance
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Abstract
The invention belongs to Internet technical field, disclose a kind of underground engineering deformation remote auto monitoring control system based on internet, the underground engineering deformation remote auto monitoring set-up of control system based on internet has mobile terminal, and the mobile terminal is connected by internet with single-chip microcomputer；Single-chip microcomputer is connected by internet with data conversion sending module；Data conversion sending module is connected with primary data processor by internet；Primary data processor is connected by wire with automatic detection measurement module.The underground engineering deformation remote auto monitoring control system based on internet, by the mobile terminal that control people is directly inputted to after data acquisition, conversion, analysis, single-chip microcomputer can speculate to data simultaneously, and provided and intuitively shown using statistical two dimension or three-dimensional line chart and column diagram.
Description
Technical field
The invention belongs to Internet technical field, more particularly to a kind of underground engineering deformation remote auto based on internet
Monitoring control system.
Background technology
At present, internet develops rapidly, can control invention provide the underground engineering deformation based on internet remotely from
Dynamic monitoring control system, data monitoring collection is carried out by processor, but data query bothers, and can not carry out data prediction.
In summary, the problem of prior art is present be：Data query bothers at present, can not carry out data prediction.
The content of the invention
The problem of existing for prior art, invention can be controlled to provide the underground engineering deformation based on internet long-range
Automatic monitoring control system.
The present invention is achieved in that a kind of underground engineering deformation remote auto monitoring control system based on internet,
The underground engineering deformation remote auto monitoring control system based on internet includes：Mobile terminal, single-chip microcomputer, data conversion
Sending module, primary data processor, automatic detection measurement module；
The mobile terminal is connected by internet with single-chip microcomputer；The single-chip microcomputer is by internet with being sent out with data conversion
Module is sent to connect；
The step of data aggregation method of the single-chip microcomputer, is as follows：
Step 1, in the deployment region that area is S=LL, the wireless sensor node of the N number of isomorphism of random distribution, sink
Node is located at outside deployment region, the data being collected into the whole wireless sensor network of node processing；
Step 2, non-homogeneous cluster
Sink nodes are located at the top of deployment region；Deployment region X-axis is divided into S swimming lane first, and all swimming lanes have phase
Same width w, and each length of swimming lane and the equal length of deployment region；By the use of the ID from 1 to s as swimming lane, high order end
The ID of swimming lane be 1, then each swimming lane is divided into multiple rectangular mesh along y-axis, each grid in each swimming lane by
A level is defined, the level of the grid of bottom is 1, and each grid and each swimming lane have identical width w；In each swimming lane
Distance dependent of number, length and the swimming lane of grid to sink；The size of grid is adjusted by setting the length of grid；For
Different swimming lanes, the lattice number that swimming lane more remote distance sink contains are smaller；For same swimming lane, net more remote distance sink
The length of lattice is bigger；Assuming that contain S element, the number of k-th of element representation grid in k-th of swimming lane in A；Each grid
ID is used as with an array (i, j), represents that i-th of swimming lane has horizontal j；Define the length of S array representation grid, v-th of number
Group HvRepresent the length of grid in v-th of swimming lane, and HvW-th of element hvwRepresent the length of grid (v, w)；Grid (i,
J) border is：
O_x+ (i-1) × w ＜ x≤o_x+i × w
Non-uniform grid carries out the cluster stage after dividing；Algorithm, which is divided into many wheels, to be carried out, and is chosen in each round each
The maximum node of dump energy adds cluster according to nearby principle, then enters line number again as cluster head node, remaining node in grid
According to polymerization；
Step 3, Grubbs pretreatment
Sensor node needs to pre-process the data of collection, then transmits data to cluster head node again；Using lattice
The data that this pre- criterion of granny rag is collected to sensor node carry out pretreatment and assume that some cluster head node contains a sensor
Node, the data that sensor node is collected into are x1,x2,…,xn, Normal Distribution, and set：
According to order statistics principle, Grubbs statistic is calculated：
After given significance (α=0.05), measured value meets gi≤g0(n, α), then it is assumed that measured value is effective, surveys
Value participates in the data aggregate of next level；It is on the contrary, then it is assumed that measured value is invalid, it is therefore desirable to reject, that is, be not involved in down
The data aggregate of one level；
Step 4, adaptive aggregating algorithm
The unbiased estimator of each node measurement data is obtained by iteration, asks for the measurement data of each sensor node
Euclidean distance between value and estimate, adaptive weighted warm weights are used as using normalized Euclidean distance；From in cluster
The average value of the maxima and minimas of data that collects of sensor node as centre data；
There is individual sensor node in some cluster, with dimensional vector D=(d1,d2,…,dn) represent respective nodes measured value,
Euclidean distance by calculating each node data and centre data reacts the deviation between different node datas and centre data
Size, wherein liCalculation formula be：
According to the corresponding weights size of Euclidean distance adaptive setting, the bigger weights of distance are smaller, got over apart from smaller weights
Greatly；
WhereinwiFor corresponding weights；
The data conversion sending module is connected with primary data processor by internet；The primary data processor
It is connected by wire with automatic detection measurement module.
Further, the automatic detection measurement module is installed on the ground；
The sensor node energy consumption of the automatic detection measurement module is divided into transmitting data energy consumption, receives data energy consumption and gather
Data energy consumption is closed, the distance of node to receiving point is less than threshold value d0, then using free space model, otherwise, declined using multipath
Subtract model, it is as follows so as to launch the energy expenditure for the receiving point that bit data is to distance：
Wherein EelecFor radiating circuit energy expenditure, εfsFor energy, ε needed for power amplification circuit under free space modelmp
For energy needed for power amplification circuit under multipath attenuation model, bit data energy consumption is received：
ERx(l)=l × Eelec；
It polymerize the energy expenditure of bit data：
EA=l × EDA；
Wherein EDARepresent the energy expenditure of 1 bit data of polymerization.
The present invention controls the mobile terminal of people by being directly inputted to after data acquisition, conversion, analysis, while single-chip microcomputer can
To speculate to data, and using statistical two dimension or three-dimensional line chart and column diagram provide and intuitively show.
Brief description of the drawings
Fig. 1 is the underground engineering deformation remote auto monitoring control system provided in an embodiment of the present invention based on internet；
In figure：1st, mobile terminal；2nd, single-chip microcomputer；3rd, data conversion sending module；4th, primary data processor；5th, automatic inspection
Survey measurement module.
Embodiment
In order to further understand the content, features and effects of the present invention, hereby enumerating following examples, and coordinate accompanying drawing
Describe in detail as follows.
The structure of the present invention is explained in detail below in conjunction with the accompanying drawings.
As shown in figure 1, the underground engineering deformation remote auto monitoring control provided in an embodiment of the present invention based on internet
System includes：Mobile terminal 1, single-chip microcomputer 2, data conversion sending module 3, primary data processor 4, automatic detection measurement module
5。
The mobile terminal 1 is connected by internet with single-chip microcomputer 2；The single-chip microcomputer 2 is by internet with turning with data
Sending module 3 is changed to connect；The data conversion sending module 3 is connected with primary data processor 4 by internet；The primary
Data processor 4 is connected by wire with automatic detection measurement module 5.
Further, the automatic detection measurement module 5 is installed on the ground.
The step of data aggregation method of the single-chip microcomputer, is as follows：
Step 1, in the deployment region that area is S=LL, the wireless sensor node of the N number of isomorphism of random distribution, sink
Node is located at outside deployment region, the data being collected into the whole wireless sensor network of node processing；
Step 2, non-homogeneous cluster
Sink nodes are located at the top of deployment region；Deployment region X-axis is divided into S swimming lane first, and all swimming lanes have phase
Same width w, and each length of swimming lane and the equal length of deployment region；By the use of the ID from 1 to s as swimming lane, high order end
The ID of swimming lane be 1, then each swimming lane is divided into multiple rectangular mesh along y-axis, each grid in each swimming lane by
A level is defined, the level of the grid of bottom is 1, and each grid and each swimming lane have identical width w；In each swimming lane
Distance dependent of number, length and the swimming lane of grid to sink；The size of grid is adjusted by setting the length of grid；For
Different swimming lanes, the lattice number that swimming lane more remote distance sink contains are smaller；For same swimming lane, net more remote distance sink
The length of lattice is bigger；Assuming that contain S element, the number of k-th of element representation grid in k-th of swimming lane in A；Each grid
ID is used as with an array (i, j), represents that i-th of swimming lane has horizontal j；Define the length of S array representation grid, v-th of number
Group HvRepresent the length of grid in v-th of swimming lane, and HvW-th of element hvwRepresent the length of grid (v, w)；Grid (i,
J) border is：
O_x+ (i-1) × w ＜ x≤o_x+i × w
Non-uniform grid carries out the cluster stage after dividing；Algorithm, which is divided into many wheels, to be carried out, and is chosen in each round each
The maximum node of dump energy adds cluster according to nearby principle, then enters line number again as cluster head node, remaining node in grid
According to polymerization；
Step 3, Grubbs pretreatment
Sensor node needs to pre-process the data of collection, then transmits data to cluster head node again；Using lattice
The data that this pre- criterion of granny rag is collected to sensor node carry out pretreatment and assume that some cluster head node contains a sensor
Node, the data that sensor node is collected into are x1,x2,…,xn, Normal Distribution, and set：
According to order statistics principle, Grubbs statistic is calculated：
After given significance (α=0.05), measured value meets gi≤g0(n, α), then it is assumed that measured value is effective, surveys
Value participates in the data aggregate of next level；It is on the contrary, then it is assumed that measured value is invalid, it is therefore desirable to reject, that is, be not involved in down
The data aggregate of one level；
Step 4, adaptive aggregating algorithm
The unbiased estimator of each node measurement data is obtained by iteration, asks for the measurement data of each sensor node
Euclidean distance between value and estimate, adaptive weighted warm weights are used as using normalized Euclidean distance；From in cluster
The average value of the maxima and minimas of data that collects of sensor node as centre data；
There is individual sensor node in some cluster, with dimensional vector D=(d1,d2,…,dn) represent respective nodes measured value,
Euclidean distance by calculating each node data and centre data reacts the deviation between different node datas and centre data
Size, wherein liCalculation formula be：
According to the corresponding weights size of Euclidean distance adaptive setting, the bigger weights of distance are smaller, got over apart from smaller weights
Greatly；
WhereinwiFor corresponding weights；
The data conversion sending module is connected with primary data processor by internet；The primary data processor
It is connected by wire with automatic detection measurement module.
The sensor node energy consumption of the automatic detection measurement module is divided into transmitting data energy consumption, receives data energy consumption and gather
Data energy consumption is closed, the distance of node to receiving point is less than threshold value d0, then using free space model, otherwise, declined using multipath
Subtract model, it is as follows so as to launch the energy expenditure for the receiving point that bit data is to distance：
Wherein EelecFor radiating circuit energy expenditure, εfsFor energy, ε needed for power amplification circuit under free space modelmp
For energy needed for power amplification circuit under multipath attenuation model, bit data energy consumption is received：
ERx(l)=l × Eelec；
It polymerize the energy expenditure of bit data：
EA=l × EDA；
Wherein EDARepresent the energy expenditure of 1 bit data of polymerization.
The automatic detection measurement module 5 of the present invention carries out DATA REASONING；Primary data processor 4 carries out data statistics and turned
Change；Data conversion sending module 3 carries out the transmission of data；Single-chip microcomputer 2 is analyzed data, is predicted and is inferred；It is final to send
To mobile terminal 1.
It is described above to be only the preferred embodiments of the present invention, any formal limitation not is made to the present invention,
Every technical spirit according to the present invention belongs to any simple modification made for any of the above embodiments, equivalent variations and modification
In the range of technical solution of the present invention.
Claims (2)
1. a kind of underground engineering deformation remote auto monitoring control system based on internet, it is characterised in that described based on mutual
The underground engineering deformation remote auto monitoring control system of networking includes：Mobile terminal, single-chip microcomputer, data conversion sending module,
Primary data processor, automatic detection measurement module；
The mobile terminal is connected by internet with single-chip microcomputer；The single-chip microcomputer is by internet with sending mould with data conversion
Block connects；
The step of data aggregation method of the single-chip microcomputer, is as follows：
Step 1, in the deployment region that area is S=LL, the wireless sensor node of the N number of isomorphism of random distribution, sink nodes
Outside deployment region, the data that are collected into the whole wireless sensor network of node processing；
Step 2, non-homogeneous cluster
Sink nodes are located at the top of deployment region；Deployment region X-axis is divided into S swimming lane first, and all swimming lanes have identical
Width w, and each length of swimming lane and the equal length of deployment region；By the use of the ID from 1 to s as swimming lane, the swimming of high order end
The ID in road is 1, and then each swimming lane is divided into multiple rectangular mesh along y-axis, and each grid in each swimming lane is defined
One level, the level of the grid of bottom is 1, and each grid and each swimming lane have identical width w；Grid in each swimming lane
Number, length and swimming lane to sink distance dependent；The size of grid is adjusted by setting the length of grid；For difference
Swimming lane, the lattice number that swimming lane more remote distance sink contains is smaller；For same swimming lane, grid more remote distance sink
Length is bigger；Assuming that contain S element, the number of k-th of element representation grid in k-th of swimming lane in A；Each grid is with one
Individual array (i, j) is used as ID, represents that i-th of swimming lane has horizontal j；Define the length of S array representation grid, v-th of array Hv
Represent the length of grid in v-th of swimming lane, and HvW-th of element hvwRepresent the length of grid (v, w)；Grid (i, j)
Border is：
O_x+ (i-1) × w ＜ x≤o_x+i × w
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The maximum node of middle dump energy adds cluster according to nearby principle, then carries out data again and gather as cluster head node, remaining node
Close；
Step 3, Grubbs pretreatment
Sensor node needs to pre-process the data of collection, then transmits data to cluster head node again；Using Ge Labu
The data that this pre- criterion is collected to sensor node carry out pretreatment and assume that some cluster head node contains a sensor node,
The data that sensor node is collected into are x1,x2,…,xn, Normal Distribution, and set：
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According to order statistics principle, Grubbs statistic is calculated：
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Secondary data aggregate；
Step 4, adaptive aggregating algorithm
The unbiased estimator of each node measurement data is obtained by iteration, ask for the measured data values of each sensor node with
Euclidean distance between estimate, adaptive weighted warm weights are used as using normalized Euclidean distance；From the biography in cluster
The average value of the maxima and minima for the data that sensor node collects is as centre data；
There is individual sensor node in some cluster, with dimensional vector D=(d1,d2,…,dn) represent respective nodes measured value, pass through
The deviation size between the different node datas of Euclidean distance reaction of each node data and centre data and centre data is calculated,
Wherein liCalculation formula be：
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WhereinwiFor corresponding weights；
The data conversion sending module is connected with primary data processor by internet；The primary data processor passes through
Wire is connected with automatic detection measurement module.
2. the underground engineering deformation remote auto monitoring control system based on internet, its feature exist as claimed in claim 1
In the automatic detection measurement module installation is on the ground；
The sensor node energy consumption of the automatic detection measurement module is divided into transmitting data energy consumption, receives data energy consumption and aggregate number
According to energy consumption, the distance of node to receiving point is less than threshold value d0, then using free space model, otherwise, using multipath attenuation mould
Type is as follows so as to launch the energy expenditure for the receiving point that bit data is to distance：
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Wherein EelecFor radiating circuit energy expenditure, εfsFor energy, ε needed for power amplification circuit under free space modelmpTo be more
Energy needed for power amplification circuit under path attenuation model, receive bit data energy consumption：
ERx(l)=l × Eelec；
It polymerize the energy expenditure of bit data：
EA=l × EDA；
Wherein EDARepresent the energy expenditure of 1 bit data of polymerization.
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| CN109332433A (en) * | 2018-08-20 | 2019-02-15 | 湄洲湾职业技术学院 | A kind of bending robot control method and control system based on numerical control |
| CN109519645A (en) * | 2018-11-01 | 2019-03-26 | 湖南城市学院 | The processing method of discharge drainage facility noise reduction in a kind of interior decoration engineering |
| CN109762872A (en) * | 2019-02-22 | 2019-05-17 | 甘肃省农业科学院作物研究所 | A kind of field identification method of cotton Adult plant verticillium wilt |
| CN109799420A (en) * | 2019-02-13 | 2019-05-24 | 临沂大学 | A kind of the internet of things functional detection system and detection method of internet of things home appliance |
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| CN103616011A (en) * | 2013-12-06 | 2014-03-05 | 天津大学 | Automatic remote monitoring system for underground engineering deformation |
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