CN104581089A - Quantitative landslide change monitoring system and landslide change predicting method - Google Patents

Quantitative landslide change monitoring system and landslide change predicting method Download PDF

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Publication number
CN104581089A
CN104581089A CN201510064448.4A CN201510064448A CN104581089A CN 104581089 A CN104581089 A CN 104581089A CN 201510064448 A CN201510064448 A CN 201510064448A CN 104581089 A CN104581089 A CN 104581089A
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monitoring
node
landslide
computer
mountain
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CN201510064448.4A
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张朝利
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张朝利
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Abstract

The invention discloses a quantitative landslide change monitoring system and a landslide change predicting method. The monitoring system comprises a monitoring node, a gateway node and an electronic computer in a monitoring center; the monitoring node is a ZigBee based wireless sensing network node with an image taking sensor and is used for transmitting the image information of the mountain fissure to the electronic computer in the monitoring center in real time by the gateway node through a GPRS network and an Internet. The contactless monitoring system adopts the image taking sensor to monitor the mountain fissure, can be improved in reliability and monitoring precision and is particularly suitable for monitoring multiple large-area terrains without the necessity of laying a large number of leads on the mountain, thus cost and a large quantity of manpower resources can be saved, and the construction difficulty can be decreased. The monitoring system can be used for monitoring the change of the landslide for 24 hours by adopting the infrared image taking sensor without being affected by weather.

Description

A kind of landslide change Quantitative Monitoring system and Forecasting Methodology thereof
Technical field
The invention belongs to the safety testing field of massif (as abrupt slope, overhanging cliff), particularly a kind of landslide change Quantitative Monitoring system and Forecasting Methodology thereof.
Background technology
Often there is the natural calamities such as landslide now, it can produce secondary disaster again, as landslide blocking current cause barrier lake, threaten the security of the lives and property in downstream, landslide blocking highway, railway, affect traffic safety, landslide also can produce security threat etc. to resident below and building.Its status quo and development trend of periodic monitoring is answered to the massif of key area, to analyze producing cause of its change and the security implication to relevant environment or mankind's activity thereof, and effectively reinforce or tackle the measures such as transfer human, financial, and material resources in time, to eliminate its hidden danger brought and disturbance factor.
Summary of the invention
In order to achieve the above object, the present invention adopts radio sensing network and image processing techniques, and is aided with certain Forecasting Methodology, realizes carrying out Quantitative Monitoring and trend prediction thereof to the change of crack, landslide.Concrete technical scheme is as follows:
A kind of landslide change Quantitative Monitoring system, by monitoring node, gateway node, monitoring center's electronic computer composition, it is characterized in that, monitoring node distribution is arranged on massif, particularly steep hill Cracks In Upper place, monitoring node comprises the ZigBee radio sensing network node with image sensor, monitoring node is connected monitoring center electronic computer by GPRS network with Internet network through gateway node, the image information of mountain cracks is real-time transmitted in monitoring center's electronic computer, automatically the changing value of each concrete mountain cracks of position really of monitoring is shown on the computer screen, changing value exceeds defined threshold, computer automatic early-warning, early warning is sent on operating personnel's mobile phone simultaneously, and utilize the development trend of computer forecast mountain cracks.
Further, monitoring node forms by with lower component: image sensor, signal conditioning circuit, radiofrequency emitting module based on ZigBee communication agreement, wherein image sensor is connected with the radiofrequency emitting module based on ZigBee communication agreement by signal conditioning circuit, and be all connected with photoelectric source, photoelectric source is connected with power management chip, and unified control is powered; Radiofrequency emitting module based on ZigBee communication agreement is connected with liquid crystal display and USB interface.
Preferably, image sensor is SAT series of IR detector.
Preferably, the radiofrequency emitting module based on ZigBee communication agreement is CC2430 chip.
Further, webmaster node is by with lower component: the radio frequency based on ZigBee communication agreement accepts module, microprocessor, SIM card holder, GPRS module are formed by connecting in turn, and they are powered by wind-solar power supply, and to be sought unity of action power supply management by power management chip.
Preferably, AT91RM9200 chip selected by microprocessor.
A Forecasting Methodology for landslide change Quantitative Monitoring system, uses gray prediction method, opens up the geomery parameter X that grey forecasting model makes full use of crack 1, X 2, X 3cumulative for time dependent size summation, generate new sequence, approach with a curve, be after approximating curve reduction and open up grey forecasting model.
Beneficial effect
The present invention compared with prior art has following good effect: (1) adopts camera sensing device, monitors mountain cracks, is a kind of contactless, can increases the reliability of monitoring system, improve monitoring accuracy; (2) adopt ZigBee-network agreement, due to network configuration flexibly, the network capacity of super large, is particularly suitable for the safety monitoring in the many locations of large area; (3) radio sensing network is adopted, without the need to laying a large amount of wire on massif, cost-saving, reduce difficulty of construction; (4) without the need to the regular tours of inspection monitoring system of staff, a large amount of human cost is saved; (5) ZigBee-network, GPRS network and Internet network are combined, be applicable to the safety monitoring in large area and precipitous location; (6) infrared photography transducer is adopted can not to implement monitoring in 24 hours by weather effect.
Accompanying drawing explanation
Fig. 1 is a kind of landslide change Quantitative Monitoring system schematic;
Fig. 2 is ZigBee-network monitoring node schematic diagram;
Fig. 3 is ZigBee-network gateway node schematic diagram.
Wherein, 1. monitoring node; 2. gateway node; 3.GPRS network; 4.Internet network; 5. monitoring center's computer; 6. image sensor; 7. signal conditioning circuit; 8. based on radio-frequency transmissions (reception) module of ZigBee communication agreement; 9 liquid crystal display; 10.USB interface; 11. photoelectric sources; 12. power management chips; 13. microprocessors; 14. wind-solar power supply; 15.SIM deck; 16.GPRS module.
Embodiment
For making object of the present invention and technical scheme clearly, be clearly and completely described below in conjunction with the technical scheme of accompanying drawing to the application.Described embodiment is a part of embodiment of the application; instead of whole embodiments; based on the embodiment of described the application, the every other embodiment that those of ordinary skill in the art obtain under without the need to the prerequisite of creative work, all belongs to the scope of the application's protection.
Embodiment 1: a kind of landslide change Quantitative Monitoring system, by monitoring node 1, gateway node 2, monitoring center's electronic computer 5 forms, it is characterized in that, monitoring node 1 is the ZigBee radio sensing network node with image sensor 6, the image information of mountain cracks is real-time transmitted in monitoring center's electronic computer 5 through gateway node 2 by GPRS network 3 and Internet network 4 by monitoring node 1, automatically the changing value of each concrete mountain cracks of position really of monitoring is shown on the computer screen, when changing value exceeds defined threshold, computer shows early warning automatically, early warning is sent on operating personnel's mobile phone simultaneously, calculate the development trend of function prediction mountain cracks.
(1) monitoring node
Monitoring node 1 as shown in Figure 2, infrared photography transducer 6 will monitor the crack of massif by aiming at, by the image of production after signal conditioning circuit 7 processes, launch image information by the radio-frequency module 8 based on ZigBee communication agreement.Monitoring node 1 photo-voltaic power supply 11.Each chip model of monitoring node 1 can do following selection: CC2430 is the chip system being used for realizing embedded ZigBee application that Chipcon company produces, and its supports 2.4GHz IEEE802.15.4/ZigBee agreement.CC2430 chip is using powerful Integrated Development Environment as support, the interactive mode debugging of internal wiring is to defer to the IAR industrial standard of IDE for supporting, obtain the height accreditation of embedded mechanism, CC2430 chip system module integration CC2420RF transceiver, strengthen the 8051MCU.32/64/128KB flash memory of industrial standard, the contour performance module of 8KB SRAM, and built-in Zigbee protocol, add super low energy consumption, make it to use very low expenditure pattern ZigBee node.
Infrared photography transducer 6 adopts SAT series of IR video camera, it all adopts non-brake method Jiaozhuo plane Infrared Detectors, the one chip resistor-type microbolometer technology that this Infrared Detectors adopts polycrystalline silicon material to prepare, detector column outmoded conventions mould 320 × 240, pixel centre-to-centre spacing 45 μMs, fill factor, curve factor is greater than 80%, and noise equivalent temperature difference (NETD) reaches 100mk (representative value).
In order to adapt to the actual needs of landslide safety monitoring, energy savings, monitoring node 1 applies photo-voltaic power supply, and the photo-voltaic power supply model selected is SAS2.5-WED.
(2) gateway node
Because Zigbee protocol is according to IEEE802.15.4 standard, mutually coordinate to realize communication between thousands of small monitoring node 1, the energy that these monitoring nodes 1 need are little, by radio wave, data are delivered to another monitoring node 1 from a monitoring node 1 in the mode of relay, their communication efficiencies are very high, but also illustrate that the low data rate of ZigBee technology and the less feature of communication range simultaneously.Therefore, when landslide safety monitoring system monitoring node information is transmitted, gateway node 2 must be set, monitoring node 1 information can be made to transfer on the electronic computer 5 of monitoring center smoothly, the schematic diagram of gateway node 2 as shown in Figure 3, its course of work is as follows: by receiving the image information that monitoring node is sent based on the Receiver Module 8 of ZigBee communication agreement, denoising is carried out by microprocessor 13 pairs of image files, after compression process, launched by GPRS module 16 again, be coupled with Internet network 4 through GPRS network 3, monitoring center's electronic computer 5 can receive the image that monitoring node 1 is produced.
Microprocessor 13 selects the high speed arm processor AT91RM9200 of a embedded 32 ARM920T cores of Atmel company as center processor, there is high-performance, low-power consumption, low cost feature, its instruction process speed can reach 200MI/s (million VAX Instructions Per Second VAXs), the high-speed transfer requirement of monitoring net artis 2 can be met, it is again a technical grade microprocessor simultaneously, gateway node 2 can be applicable to work the severe requirement in looped network border, ensure the stability that gateway node 2 works.AT91RM9200 can transplant the (SuSE) Linux OS of standard simultaneously, decrease the development difficulty of webmaster node 2 software, and enhance its portability, be conducive to the secondary development of software.
Wireless launcher comprises sim card socket 15, GPRS module 16 and antenna, and the input of sim card socket 15 connects microprocessor 13, and output connects GPRS module 16.GPRS module 16 selects Mc55 module, and the built-in ICP/IP protocol of Mc55 module controls service routine by AT instruction and is easy to access network.
Wind-solar power supply 14 selects wind and light complementary power supply, and model is SDC-DMI150.
Carry out in microprocessor 13 and carry out preliminary treatment and compress transmitting to image file.
Image denoising application self-adapting medium filtering (AMF), principle is as follows: establish S xyrepresent and make Z by the mask window that central pixel point (x, y) is corresponding when filtering minfor S xymiddle gray scale minimum value, Z maxfor S xymiddle gray scale maximum, Z medfor S xymiddle gray scale intermediate value, Z xyfor the gray scale on coordinate (x, y), S maxfor S xythe full-size allowed.Adaptive median filter algorithm is operated in two levels, is defined as A layer and B layer, A layer: A 1=Z med-Z min, A 2=Z med-Z maxif, A 1>0, A 2<0, forwards B layer to, otherwise increases window size, if window size≤S max, repeat A layer, otherwise export Z xy; B layer: B 1=Z xy-Z min, B 2=Z xy-Z maxif, B 1>0, B 2<0, exports Z xy, otherwise export Z med.
Image compression encoding method is as follows: the average number of bits of image entropy presentation video gray scale set, unit is bits/pixel, describes the average information of image information source.Entropy code algorithm has multiple, image compression application Huffman encoding of the present invention, and its principle is as follows: Huffman encoding determines code length in strict accordance with probability match method, and the gray value that probability is large corresponds to short code, and the gray value that probability is little corresponds to long code.Huffman encoding step is as follows: (1) counts the probability that in image, each gray value occurs, and according to order arrangement from big to small; (2) select two values that probability is minimum each time, they be added, the new frequency values of formation and other frequency values form a new frequency sets; (3) repeat (2) step, to the last obtain frequency and be 1; (4) distribution codeword, progressively encodes forward conversely to above-mentioned steps, and each Bu Youliangge branch respectively gives a binary code, the imparting code element 0 large to probability, the imparting code element 1 (or contrary) little to probability.
(3) electronic computer of monitoring center
The monitoring image file compressed through gateway node 2 passes in the electronic computer (5) of monitoring center through GPRS network and Internet network.First carry out image decompression, application inverse discrete cosine transform fast algorithm (IDCT fast algorithm), its basic thought can be described below: to calculate two dimension 8 × 8IDCT:
F ( u , v ) = 1 4 c ( u ) c ( v ) &Sigma; m = 0 7 &Sigma; n = 0 7 [ f ( m , n ) &CenterDot; cos ( 2 m + 1 ) &pi;u 16 &CenterDot; cos ( 2 n + 1 ) &pi;v 16 ] f ( m , n ) = 1 4 &Sigma; u = 0 7 &Sigma; v = 0 7 [ c ( u ) &CenterDot; c ( v ) &CenterDot; F ( u , v ) &CenterDot; cos ( 2 m + 1 ) &pi;u 16 &CenterDot; cos ( 2 n + 1 ) &pi;v 16 ] - - - ( 1 )
Wherein m, n, u, v=0,1 ..., 7.
Formula (1) matrix notation: [ F ] = [ G ] &CenterDot; [ f ] &CenterDot; [ G ] T [ f ] = [ G ] T &CenterDot; [ F ] &CenterDot; [ G ]
[ F ] = F ( 0,0 ) F ( 0,0 ) . . . F ( 0,0 ) F ( 1,0 ) F ( 1,1 ) . . . F ( 1,7 ) . . . F ( 7,0 ) F ( 7,1 ) . . . F ( 7,7 )
Wherein: [ f ] = f ( 0,0 ) f ( 0,0 ) . . . f ( 0,0 ) f ( 1,0 ) f ( 1,1 ) . . . f ( 1,7 ) . . . f ( 7,0 ) f ( 7,1 ) . . . f ( 7,7 )
[ G ] = 1 2 2 1 2 2 . . . 1 2 2 1 2 cos &pi; 16 1 2 cos 3 &pi; 16 . . . 1 2 cos 15 &pi; 16 . . . 1 2 cos 7 &pi; 16 1 2 cos 21 &pi; 16 . . . 1 2 cos 105 &pi; 16 = G 0 G 1 . . . G 7
Note for the vector that u in matrix [G] is capable formed, then
[ f ] = G 0 T G 1 T . . . G 7 T &CenterDot; [ F ] &CenterDot; G 0 G 1 . . . G 7
Matrix F is write as following summation form:
[ F ] = F ( 0,0 ) 0 . . . 0 0 0 . . . 0 . . . 0 0 . . . 0 + 0 F ( 0,1 ) 0 . . . 0 0 0 0 . . . 0 . . . 0 0 0 . . . 0 + . . .
Then have f = &Sigma; u = 0 7 &Sigma; v = 0 7 { [ F ( u , v ) ] &CenterDot; [ G u ] T &CenterDot; [ G v ] } = &Sigma; u = 0 7 &Sigma; v = 0 7 { [ F ( u , v ) ] &CenterDot; [ T uv ] } - - - ( 2 )
Wherein, [T uv]=[G u] t× [G v] (u, v=0,1 ..., 7) and be called as primary image corresponding to conversion coefficient F (u, v).The physical significance of formula (2) is: using coefficient in transform domain F (u, v) as weight coefficient when, can obtain original image matrix [f] by the linear combination of all primary images.
At [F (the u that formula (2) calculates, v)] coefficient is all through quantification treatment, after general quantification 8 × 8 sub-blocks DCT coefficient in, the low frequency coefficient of minority is only had to be nonzero value, the conversion coefficient of all the other most of upper frequencies is all null value, and have the value of quite a few nonzero-value coefficient to be ± 1, there is very large symmetry between the element simultaneously in IDCT in each primary image matrix.Make full use of the amount of calculation that above-mentioned feature can greatly reduce formula (2).
Through the image of decompress(ion), be presented on the screen of computer, for the surveillance map picture be sent on screen, what calculate the mountain cracks that function automatic recognition image absorbs specifically determines position, and specific algorithm is as follows:
In monitoring system, the position of description node is come in embedded space, measures the coordinate that estimated value locates it linear system from a monitoring node 1 to gateway node 2.Suppose to there is M gateway node 2, monitoring node 1 S icoordinate in the embedded space of M dimension represents with estimated value vector value: [P i]=[P i1, P i2, P i3..., P iM] t, [P ij] represent the measured value of node i to node j, [P ii]=0.Whole embedded space can be expressed as [P]=[P with the estimated matrix of a M × M 1, P 2..., P m].
In like manner, geographic distance vector representation is [L i]=[L i1, L i2..., L iM] t, [L ij] represent the geographic distance of node i to node j.Then geographic distance matrix notation is [L]=[L 1, L 2..., L m].Location algorithm main thought of the present invention is structure optimum linearity conversion [T], provides one from estimated matrix [P] to the mapping relations of distance matrix [L].Unknown node, after obtaining an estimated vector, just can utilize this mapping relations to calculate its vector distance, thus the position coordinates of computing node.[T] is the matrix of a M × M, and each row of [T] is by minimizing variance to obtain.
e i = &Sigma; k = 1 M ( l ik - t i p k ) 2 = | | l i T - t i p | | 2
[L 1,L 2,…,L M]=[T][P 1,P 2,…,P M]
Row vector is obtained by minimum variance [T]=[L] [P] [T] { [P] [P] t} -1.
Image scale size marking is carried out to the crack of massif of monitoring, and in image processing software, application ruler measure crack the widest part is of a size of X1, the narrowest place is of a size of X2, the distance of two end points in crack is X3.To often open transmitting image (X1, X2, X3), consecutive variations situation is by computer automatic drafting curve, if the value of X1, X2, X3 exceedes defined threshold, automatically show early warning information by computer, and early warning information is sent on the mobile phone of staff.Open up grey forecasting model (EGM (1,1)) according to the numerical applications of (X1, X2, X3) to predict the crack progressing trend of massif simultaneously.
Open up the geomery parameter X that grey forecasting model (EGM (1,1)) makes full use of mountain cracks 1, X 2, X 3cumulative for time dependent size summation, generate new ordered series of numbers, approach with a suitable curve, be after approximating curve reduction and open up grey forecasting model.Be provided with the discrete data of one group of unequal time-interval:
X (0)=x (0)(t 1),x (0)(t 2),...,x (0)(t n)
T in formula i(i=1,2 ..., n) be time that discrete data is corresponding.
For solving data rows difference and the non-linearity of time difference, on GM (1,1) the model basis of even time interval, requirement forecast value and original value approximately equal, propose following equation group:
x ( 0 ) ( t i ) = c ( 1 - e a ) e - at i x ( 0 ) ( t j ) = c ( 1 - e a ) e - at j , i = 2,3 , . . . , n - 1 ; j = i + 1 , . . . , n
Solution above formula obtains:
a ij = 1 t i - t j ln x ( 0 ) ( t j ) x ( 0 ) ( t i )
The a drawn ijaverage is got in summation: a ^ = 1 ( n - 1 ) 2 &Sigma; i = 2 m - 1 &Sigma; j = i + 1 m a ij
Solve: x ( 0 ) = ( t i ) = c i ( 1 - e a ^ ) e - a ^ t i , i = 1,2 , . . . , n
According to above formula, try to achieve c i, cumulative summation is averaged:
c ^ = 1 n - 1 c i
Finally solve and open up grey forecasting model:

Claims (4)

1. a landslide change Quantitative Monitoring system, by monitoring node (1), gateway node (2), monitoring center's electronic computer (5) forms, it is characterized in that, monitoring node (1) distribution is arranged on massif, particularly steep hill Cracks In Upper place, monitoring node (1) comprises the ZigBee radio sensing network node with image sensor (6), monitoring node (1) is connected monitoring center electronic computer (5) by GPRS network (3) with Internet network (4) through gateway node (2), the image information of mountain cracks is real-time transmitted in monitoring center's electronic computer (5), automatically the changing value of each concrete mountain cracks of position really of monitoring is shown on the computer screen, changing value exceeds defined threshold, computer automatic early-warning, early warning is sent on operating personnel's mobile phone simultaneously, and utilize the development trend of computer forecast mountain cracks.
2. a kind of landslide changes Quantitative Monitoring system according to claim 1, it is characterized in that, monitoring node (1) forms by with lower component: image sensor (6), signal conditioning circuit (7), radiofrequency emitting module (8) based on ZigBee communication agreement, wherein image sensor (6) is connected with the radiofrequency emitting module (8) based on ZigBee communication agreement by signal conditioning circuit (7), and be all connected with photoelectric source (11), photoelectric source (11) is connected with power management chip (12), unified control is powered.
3. a kind of landslide changes Quantitative Monitoring system according to claim 1, it is characterized in that, webmaster node (2) is by with lower component: the radio frequency based on ZigBee communication agreement accepts module (8), microprocessor (13), SIM card holder (15), GPRS module (16) are formed by connecting in turn, they by wind-solar power supply (14) power supply, and to be sought unity of action power supply management by power management chip (12).
4. the Forecasting Methodology of a kind of landslide change Quantitative Monitoring system described in claim 1,2 or 3, use gray prediction method, it is characterized in that, open up grey forecasting model and make full use of the geomery parameter X1 in crack, X2, X3 cumulative for time dependent size summation, generate new sequence, approach with a curve, be after approximating curve reduction and open up grey forecasting model.
CN201510064448.4A 2015-02-08 2015-02-08 Quantitative landslide change monitoring system and landslide change predicting method CN104581089A (en)

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Application publication date: 20150429