CN106384196A - Power distribution network monitor method - Google Patents
Power distribution network monitor method Download PDFInfo
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- CN106384196A CN106384196A CN201610816208.XA CN201610816208A CN106384196A CN 106384196 A CN106384196 A CN 106384196A CN 201610816208 A CN201610816208 A CN 201610816208A CN 106384196 A CN106384196 A CN 106384196A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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Abstract
The invention discloses a power distribution network monitor method and belongs to the technical field of electrical power system. The method comprises the steps: monitoring data is acquired in real time; three-dimensional coordinates of the monitoring data is determined; according to the three-dimensional coordinates, the monitoring data is loaded to a panorama three-dimensional model; if the monitoring data meets early warning conditions, a plurality of candidate early warning schemes corresponding to the monitoring data is determined according to the monitoring data, current time and a preset early warning scheme; the feasibility of the early warning schemes are evaluated based on the panorama three-dimensional model for loading the monitor data; and a final early warning scheme is determined according to the monitoring data and the feasibility of the early warning schemes. According to the invention, the plurality of candidate early warning schemes corresponding to the monitoring data is determined according to the monitoring data, current time and a preset early warning scheme; the feasibility of the early warning schemes are evaluated based on the panorama three-dimensional model for loading the monitor data; the final early warning scheme is determined according to the monitoring data and the feasibility of the early warning schemes, and the feasibility of the final early warning scheme can be improved.
Description
Technical field
The present invention relates to technical field of power systems, particularly to a kind of distribution network monitoring method.
Background technology
With the fast development of distribution network construction, electric network data just progressively complicates to type, the direction of message diversification
Development.The power distribution network of complicated pluralism is put forward higher requirement to the safe operation of electric power, in order to ensure the safety fortune of power distribution network
OK, need power distribution network is monitored, to find potential safety hazard in advance, to process safety problem in time.
At present, generate the panorama threedimensional model of monitor area by GIS-Geographic Information System, monitoring data is incorporated panorama three
In dimension module, show the panorama threedimensional model after merging and monitoring data so that monitoring personnel determine can be comprehensive during early warning scheme
Close the actual scene considering the reaction of panorama threedimensional model and monitoring data.
When carrying out distribution network monitoring, monitoring personnel determines early warning according to monitoring data and panorama threedimensional model to said method
Scheme, and the early warning concept feasible manually determining is not high.
Content of the invention
(1) technical problem to be solved
In order to improve the feasibility of early warning scheme, the invention provides a kind of distribution network monitoring method, can be according to monitoring
The feasibility of data and each candidate's early warning scheme determines final early warning scheme, lifts the feasibility of final early warning scheme.
(2) technical scheme
In order to achieve the above object, the main technical schemes that the present invention adopts include：
Distribution network monitoring method, comprises the following steps：
101, obtain monitoring data in real time；
102, determine the three-dimensional coordinate of described monitoring data, described three-dimensional coordinate includes：Longitude, dimension, highly；
103, according to described three-dimensional coordinate, described monitoring data is loaded onto in panorama threedimensional model；
104, if described monitoring data meets early-warning conditions, according to described monitoring data, current time and default
Early warning scheme, determines the corresponding multiple candidate's early warning schemes of described monitoring data, described candidate's early warning scheme, including：Early warning portion
Door, early warning personnel, alarm mode, effective pre-warning time, alarm mode includes：Network processes, walking is processed, using mini engineering
Car is processed, and is processed using heavy construction car；
105, determine the three-dimensional coordinate of each candidate's early warning department；
106, according to the three-dimensional coordinate of described each candidate's early warning department, each candidate's early warning department is loaded onto described loading and supervises
In the panorama threedimensional model of control data；
107, according to described early warning personnel, alarm mode, effective pre-warning time, plan the early warning road of each candidate's early warning scheme
Line；
108, the early warning route according to each candidate's early warning scheme assesses the feasibility of each candidate's early warning scheme, described feasibility
Including each candidate's early warning scheme required time, required distance, required cost；
109, final early warning scheme is determined according to the feasibility of described monitoring data and each candidate's early warning scheme；
Wherein, step 109, including following sub-step：
109-1, determines that described monitoring data meets the degree of early-warning conditions；
109-2, meets degree and each candidate's early warning scheme required time, the institute of early-warning conditions according to described monitoring data
Need distance, required cost, determine a final early warning scheme from candidate's early warning scheme.
Step 109-1, including：
If described early-warning conditions are higher than threshold value of warning for monitoring data, or, described early-warning conditions are less than for monitoring data
Threshold value of warning is it is determined that the degree that described monitoring data meets early-warning conditions is | described monitoring data-described threshold value of warning |/institute
State threshold value of warning；
If described early-warning conditions are located in early warning interval (a, b) for monitoring data, or, described early-warning conditions are monitoring number
According to positioned at early warning interval [a, b] in it is determined that described monitoring data meet early-warning conditions degree be (described monitoring data-a)/
(b-a)；
If described early-warning conditions are located at early warning interval (a, b) outward for monitoring data, or, described early-warning conditions are monitoring number
According to positioned at early warning interval [a, b] outward, and described monitoring data is not less than b it is determined that described monitoring data meets early-warning conditions
Degree is (described monitoring data-b)/(b-a)；
If described early-warning conditions are located at early warning interval (a, b) outward for monitoring data, or, described early-warning conditions are monitoring number
According to positioned at early warning interval [a, b] outward, and described monitoring data is not more than a it is determined that described monitoring data meets early-warning conditions
Degree is (monitoring data described in a-)/(b-a).
Step 109-2, including：
Determine the maximum candidate's early warning scheme of selective value as final early warning scheme；
Described selective value=cost needed for distance+c3* needed for c1* candidate early warning scheme required time+c2*；
Wherein, c1 is time-concerning impact factor, and c2 is factor of influence, and c3 is factor of influence；
If the degree that described monitoring data meets early-warning conditions is not less than 1, c1, c2, c3 are respectively：0.99,0.27,
0.1；
If the degree that described monitoring data meets early-warning conditions is higher than 0.68, and described monitoring data meets early-warning conditions
Degree is less than 1, then c1, c2, c3 are respectively：0.95,0.45,0.48；
If the degree that described monitoring data meets early-warning conditions is not higher than 0.68, c1, c2, c3 are respectively：0.3,0.65,
0.98.
Alternatively, step 102, including：
The three-dimensional coordinate of the monitoring device of described monitoring data is defined as the three-dimensional coordinate of described monitoring data.
Alternatively, step 103, including following sub-step：
103-1, determines the corresponding position of described monitoring data in panorama threedimensional model, the three-dimensional coordinate of described position with
The three-dimensional coordinate of described monitoring data is identical；
103-2, described monitoring data is loaded onto at described position.
Alternatively, before step 104 execution, also comprise the steps：
Determine whether described monitoring data meets early-warning conditions.
Alternatively, after step 109 execution, also comprise the steps：
The early warning route of final early warning scheme is shown in panorama threedimensional model.
(3) beneficial effect
The invention has the beneficial effects as follows：According to monitoring data, current time and default early warning scheme, determine monitoring number
According to corresponding multiple candidate's early warning schemes；Based on the panorama threedimensional model loading monitoring data, assess each candidate's early warning scheme
Feasibility；Final early warning scheme, the lifting finally pre- police are determined according to the feasibility of monitoring data and each candidate's early warning scheme
The feasibility of case.
Brief description
Fig. 1 is a kind of distribution network monitoring method flow diagram that the embodiment of the present invention one provides；
Fig. 2 is a kind of distribution network monitoring method flow diagram that the embodiment of the present invention two provides.
Specific embodiment
In order to preferably explain the present invention, in order to understand, below in conjunction with the accompanying drawings, by specific embodiment, to this
Bright it is described in detail.
In prior art, monitoring personnel determines early warning scheme according to monitoring data and panorama threedimensional model, can make early warning
Concept feasible is not high, for solving this problem, the invention provides a kind of distribution network monitoring method, according to monitoring data, currently
Time and default early warning scheme, determine the corresponding multiple candidate's early warning schemes of monitoring data；Based on loading monitoring data
Panorama threedimensional model, assesses the feasibility of each candidate's early warning scheme；Feasible according to monitoring data and each candidate's early warning scheme
Property determine final early warning scheme, lift the feasibility of final early warning scheme.
Embodiment one
Present embodiments provide a kind of distribution network monitoring method, referring to Fig. 1, the method flow that the present embodiment provides is concrete such as
Under：
101, obtain monitoring data in real time；
102, determine the three-dimensional coordinate of monitoring data, three-dimensional coordinate includes：Longitude, dimension, highly；
Alternatively, step 102, including：
The three-dimensional coordinate of the monitoring device of monitoring data is defined as the three-dimensional coordinate of monitoring data.
103, according to three-dimensional coordinate, monitoring data is loaded onto in panorama threedimensional model；
Alternatively, step 103, including following sub-step：
103-1, determines the corresponding position of monitoring data, the three-dimensional coordinate of position and monitoring data in panorama threedimensional model
Three-dimensional coordinate identical；
103-2, monitoring data is loaded onto at position.
104, if monitoring data meets early-warning conditions, according to monitoring data, current time and default early warning scheme,
Determine the corresponding multiple candidate's early warning schemes of monitoring data, candidate's early warning scheme, including：Early warning department, early warning personnel, the pre- police
Formula, effective pre-warning time, alarm mode includes：Network processes, walking is processed, and is processed using Mini-type mobile machinery shop, using large-scale work
Journey car is processed；
Alternatively, before step 104 execution, also comprise the steps：
Determine whether monitoring data meets early-warning conditions.
105, determine the three-dimensional coordinate of each candidate's early warning department；
106, according to the three-dimensional coordinate of each candidate's early warning department, each candidate's early warning department is loaded onto and loads monitoring data
In panorama threedimensional model；
107, according to early warning personnel, alarm mode, effective pre-warning time, plan the early warning route of each candidate's early warning scheme；
108, the early warning route according to each candidate's early warning scheme assesses the feasibility of each candidate's early warning scheme, and feasibility includes
Each candidate's early warning scheme required time, required distance, required cost；
109, final early warning scheme is determined according to the feasibility of monitoring data and each candidate's early warning scheme.
Wherein, step 109, including following sub-step：
109-1, determines that monitoring data meets the degree of early-warning conditions；
109-2, meets degree and each candidate's early warning scheme required time, the required road of early-warning conditions according to monitoring data
Journey, required cost, determine a final early warning scheme from candidate's early warning scheme.
Step 109-1, including：
If early-warning conditions are higher than threshold value of warning for monitoring data, or, early-warning conditions are less than threshold value of warning for monitoring data,
Then determine that the degree that monitoring data meets early-warning conditions is | monitoring data-threshold value of warning |/threshold value of warning；
If early-warning conditions are located in early warning interval (a, b) for monitoring data, or, early-warning conditions are located at pre- for monitoring data
It is determined that the degree that monitoring data meets early-warning conditions is (monitoring data-a)/(b-a) in [a, b] between police region；
If early-warning conditions are located at early warning interval (a, b) outward for monitoring data, or, early-warning conditions are located at pre- for monitoring data
Between police region [a, b] outward, and monitoring data be not less than b it is determined that monitoring data meet early-warning conditions degree be (monitoring data-
b)/(b-a)；
If early-warning conditions are located at early warning interval (a, b) outward for monitoring data, or, early-warning conditions are located at pre- for monitoring data
Between police region [a, b] outward, and monitoring data be not more than a it is determined that monitoring data meet early-warning conditions degree be (a- monitor number
According to)/(b-a).
Step 109-2, including：
Determine the maximum candidate's early warning scheme of selective value as final early warning scheme；
Selective value=cost needed for distance+c3* needed for c1* candidate early warning scheme required time+c2*；
Wherein, c1 is time-concerning impact factor, and c2 is factor of influence, and c3 is factor of influence；
If the degree that monitoring data meets early-warning conditions is not less than 1, c1, c2, c3 are respectively：0.99,0.27,0.1；
If the degree that monitoring data meets early-warning conditions is higher than 0.68, and monitoring data meets the degree of early-warning conditions and is less than
1, then c1, c2, c3 are respectively：0.95,0.45,0.48；
If the degree that monitoring data meets early-warning conditions is not higher than 0.68, c1, c2, c3 are respectively：0.3,0.65,
0.98.
Alternatively, after step 109 execution, also comprise the steps：
The early warning route of final early warning scheme is shown in panorama threedimensional model.
The method that the present embodiment provides, according to monitoring data, current time and default early warning scheme, determines monitoring number
According to corresponding multiple candidate's early warning schemes；Based on the panorama threedimensional model loading monitoring data, assess each candidate's early warning scheme
Feasibility；Final early warning scheme, the lifting finally pre- police are determined according to the feasibility of monitoring data and each candidate's early warning scheme
The feasibility of case.
In order to clearly illustrate the distribution network monitoring method that above-described embodiment provides, in conjunction with above-described embodiment
Hold, taking following examples two as a example, distribution network monitoring method is described in detail, sees below embodiment two：
Embodiment two
Present embodiments provide a kind of distribution network monitoring method, referring to Fig. 2, the method flow that the present embodiment provides is concrete such as
Under：
201, obtain monitoring data in real time, determine the three-dimensional coordinate of monitoring data；
Wherein, three-dimensional coordinate includes：Longitude, dimension, highly.
In the specific implementation, the three-dimensional coordinate of the monitoring device of monitoring data can be defined as the three-dimensional seat of monitoring data
Mark.
202, according to three-dimensional coordinate, monitoring data is loaded onto in panorama threedimensional model；
This step in the specific implementation, can be achieved by the steps of：1) determine monitoring number in panorama threedimensional model
According to corresponding position, wherein, the three-dimensional coordinate of the corresponding position of monitoring data is identical with the three-dimensional coordinate of monitoring data；2) will supervise
Control data is loaded onto at the corresponding position of monitoring data.
203, determine whether monitoring data meets early-warning conditions, if meeting early-warning conditions, execution step 204, if discontented
Sufficient early-warning conditions, then execution step 201；
Wherein, early-warning conditions include but is not limited to：Monitoring data is higher than threshold value of warning, or, monitoring data is less than early warning
Threshold value, or, monitoring data is located in early warning interval (a, b), or, monitoring data is located in early warning interval [a, b], or,
Monitoring data is located at early warning interval (a, b) outward, or, monitoring data is located at early warning interval [a, b] outward.
204, according to monitoring data, current time and default early warning scheme, determine the corresponding multiple times of monitoring data
Select early warning scheme；
Wherein, candidate's early warning scheme, at least includes：Early warning department, early warning personnel, alarm mode, effective pre-warning time.
Alarm mode includes but is not limited to：Network processes, walking is processed, and is processed using Mini-type mobile machinery shop, using large-scale work
Journey car process etc..
Monitoring data can affect the determination of early warning department.For example：The monitoring data of transformer business is by transformer correlation
Early warning department is processed.In addition, monitoring data also can affect the determination of early warning personnel, for example：The asking of transformer voltage aspect
Topic is processed by the early warning personnel of voltage aspect in the related early warning department of transformer.
Current time can affect early warning personnel, effective pre-warning time.For example, if current time is morning 3：00, and early warning
Personnel's A working time is 0:00-8:00, early warning personnel's B working time is 8:00-16:00, early warning personnel's C working time is 16:
00-24:00, then the early warning personnel currently meeting condition are A.And then according to working time of early warning personnel A it may be determined that A
Effectively pre-warning time is 3:00-8:00.In addition, current time also can affect the determination of alarm mode, for example：Current time
For morning peak 9：00, if utilizing works car is processed, the congestion time on the way can be much more than active repair time, now,
If the corresponding position of monitoring data is not far away from early warning department position, can be in the way of being processed using walking.
Therefore, it can determine that monitoring data is corresponding many from default early warning scheme according to monitoring data, current time
Individual candidate's early warning scheme.
205, determine the three-dimensional coordinate of each candidate's early warning department；
Wherein, three-dimensional coordinate includes：Longitude, dimension, highly.
206, according to the three-dimensional coordinate of each candidate's early warning department, each candidate's early warning department is loaded onto and loads monitoring data
In panorama threedimensional model；
Step 206 in the specific implementation, can be with 1) determine the corresponding position of each candidate's early warning department in panorama threedimensional model
Put, wherein, the three-dimensional coordinate of the corresponding position of each candidate's early warning department is identical with the three-dimensional coordinate of each candidate's early warning department；2) will
Each candidate's early warning department is loaded onto at the corresponding position of each candidate's early warning department.
207, according to early warning personnel, alarm mode, effective pre-warning time, plan the early warning route of each candidate's early warning scheme；
For example, if candidate's early warning scheme is：Early warning personnel A, using Mini-type mobile machinery shop, in 3:00-8:00 process, then basis
The vehicle of Mini-type mobile machinery shop, selects the lane that can directly reach the corresponding position of monitoring data as early warning route.If candidate
Early warning scheme is：Early warning personnel A, using heavy construction car, in 3:00-8:00 process, then the vehicle according to heavy construction car, then
Though selecting around reaching the corresponding position of monitoring data, the turnpike road that it can be exercised is as early warning route.
208, the early warning route according to each candidate's early warning scheme assesses the feasibility of each candidate's early warning scheme；
Different early warning routes can correspond to different times, distance, cost, therefore, the feasibility bag of assessment in step 208
Include：Each candidate's early warning scheme required time, required distance, required cost.
209, final early warning scheme is determined according to the feasibility of monitoring data and each candidate's early warning scheme；
This step in the specific implementation, can be with 1) determine that monitoring data meets the degree of early-warning conditions；2) according to monitoring number
According to the degree meeting early-warning conditions and each candidate's early warning scheme required time, required distance, required cost, from the pre- police of candidate
A final early warning scheme is determined in case.
Determination monitoring data is met to the implementation of the degree of early-warning conditions, including but not limited to：
If early-warning conditions are higher than threshold value of warning for monitoring data, or, early-warning conditions are less than threshold value of warning for monitoring data,
Then determine that the degree that monitoring data meets early-warning conditions is | monitoring data-threshold value of warning |/described threshold value of warning；
If early-warning conditions are located in early warning interval (a, b) for monitoring data, or, early-warning conditions are located at pre- for monitoring data
It is determined that the degree that monitoring data meets early-warning conditions is (monitoring data-a)/(b-a) in [a, b] between police region；
If early-warning conditions are located at early warning interval (a, b) outward for monitoring data, or, early-warning conditions are located at pre- for monitoring data
Between police region [a, b] outward, and monitoring data be not less than b it is determined that monitoring data meet early-warning conditions degree be (monitoring data-
b)/(b-a)；
If early-warning conditions are located at early warning interval (a, b) outward for monitoring data, or, early-warning conditions are located at pre- for monitoring data
Between police region [a, b] outward, and monitoring data be not more than a it is determined that monitoring data meet early-warning conditions degree be (a- monitor number
According to)/(b-a).
In addition, when determining a final early warning scheme, can determine which selects according to combined factors such as emergencies
As final early warning scheme.
For example：If the situation is critical, the short candidate's early warning scheme of required time may be selected as final early warning scheme.
Therefore, degree and each candidate's early warning scheme required time, the required road of early-warning conditions is met according to monitoring data
Journey, required cost, determine the specific implementation of a final early warning scheme, including but not limited to from candidate's early warning scheme：
Determine the maximum candidate's early warning scheme of selective value as final early warning scheme；
Selective value=cost needed for distance+c3* needed for c1* candidate early warning scheme required time+c2*；
Wherein, c1 is time-concerning impact factor, and c2 is factor of influence, and c3 is factor of influence；
If the degree that monitoring data meets early-warning conditions is not less than 1, c1, c2, c3 are respectively：0.99,0.27,0.1；
If the degree that monitoring data meets early-warning conditions is higher than 0.68, and monitoring data meets the degree of early-warning conditions and is less than
1, then c1, c2, c3 are respectively：0.95,0.45,0.48；
If the degree that monitoring data meets early-warning conditions is not higher than 0.68, c1, c2, c3 are respectively：0.3,0.65,
0.98.
210, panorama threedimensional model is shown the early warning route of final early warning scheme.
In order to allow early warning personnel be familiar with early warning circuit, or, in order to allow related leader know early warning circuit, in execution step
The early warning route of final early warning scheme after 206 determine final early warning scheme, can be shown in panorama threedimensional model, related personnel can
To check early warning route in panorama threedimensional model.
The method that the present embodiment provides, according to monitoring data, current time and default early warning scheme, determines monitoring number
According to corresponding multiple candidate's early warning schemes；Based on the panorama threedimensional model loading monitoring data, assess each candidate's early warning scheme
Feasibility；Final early warning scheme, the lifting finally pre- police are determined according to the feasibility of monitoring data and each candidate's early warning scheme
The feasibility of case.
Claims (5)
1. a kind of distribution network monitoring method, it is characterised in that methods described, comprises the steps：
101, obtain monitoring data in real time；
102, determine the three-dimensional coordinate of described monitoring data, described three-dimensional coordinate includes：Longitude, dimension, highly；
103, according to described three-dimensional coordinate, described monitoring data is loaded onto in panorama threedimensional model；
104, if described monitoring data meets early-warning conditions, according to described monitoring data, current time and default early warning
Scheme, determines the corresponding multiple candidate's early warning schemes of described monitoring data, described candidate's early warning scheme, including：Early warning department, pre-
Alert personnel, alarm mode, effective pre-warning time, alarm mode includes：Network processes, walking is processed, at Mini-type mobile machinery shop
Reason, is processed using heavy construction car；
105, determine the three-dimensional coordinate of each candidate's early warning department；
106, according to the three-dimensional coordinate of described each candidate's early warning department, each candidate's early warning department is loaded onto described loading and monitors number
According to panorama threedimensional model in；
107, according to described early warning personnel, alarm mode, effective pre-warning time, plan the early warning route of each candidate's early warning scheme；
108, the early warning route according to each candidate's early warning scheme assesses the feasibility of each candidate's early warning scheme, and described feasibility includes
Each candidate's early warning scheme required time, required distance, required cost；
109, final early warning scheme is determined according to the feasibility of described monitoring data and each candidate's early warning scheme；
Wherein, step 109, including following sub-step：
109-1, determines that described monitoring data meets the degree of early-warning conditions；
109-2, meets degree and each candidate's early warning scheme required time, the required road of early-warning conditions according to described monitoring data
Journey, required cost, determine a final early warning scheme from candidate's early warning scheme.
Step 109-1, including：
If described early-warning conditions are higher than threshold value of warning for monitoring data, or, described early-warning conditions are less than early warning for monitoring data
| described monitoring data-described threshold value of warning | that threshold value is it is determined that the degree that described monitoring data meets early-warning conditions is/described pre-
Alert threshold value；
If described early-warning conditions are located in early warning interval (a, b) for monitoring data, or, described early-warning conditions are monitoring data position
It is determined that the degree that described monitoring data meets early-warning conditions is (described monitoring data-a)/(b- in early warning interval [a, b]
a)；
If described early-warning conditions are located at early warning interval (a, b) outward for monitoring data, or, described early-warning conditions are monitoring data position
In early warning interval [a, b] outward, and described monitoring data be not less than b it is determined that described monitoring data meets the degree of early-warning conditions
For (described monitoring data-b)/(b-a)；
If described early-warning conditions are located at early warning interval (a, b) outward for monitoring data, or, described early-warning conditions are monitoring data position
In early warning interval [a, b] outward, and described monitoring data be not more than a it is determined that described monitoring data meets the degree of early-warning conditions
For (monitoring data described in a-)/(b-a).
Step 109-2, including：
Determine the maximum candidate's early warning scheme of selective value as final early warning scheme；
Described selective value=cost needed for distance+c3* needed for c1* candidate early warning scheme required time+c2*；
Wherein, c1 is time-concerning impact factor, and c2 is factor of influence, and c3 is factor of influence；
If the degree that described monitoring data meets early-warning conditions is not less than 1, c1, c2, c3 are respectively：0.99,0.27,0.1；
If the degree that described monitoring data meets early-warning conditions is higher than 0.68, and described monitoring data meets the degree of early-warning conditions
Less than 1, then c1, c2, c3 are respectively：0.95,0.45,0.48；
If the degree that described monitoring data meets early-warning conditions is not higher than 0.68, c1, c2, c3 are respectively：0.3,0.65,
0.98.
2. step according to claim 1 is it is characterised in that step 102, including：
The three-dimensional coordinate of the monitoring device of described monitoring data is defined as the three-dimensional coordinate of described monitoring data.
3. step according to claim 1 is it is characterised in that step 103, including following sub-step：
103-1, determines the corresponding position of described monitoring data in panorama threedimensional model, the three-dimensional coordinate of described position with described
The three-dimensional coordinate of monitoring data is identical；
103-2, described monitoring data is loaded onto at described position.
4. step according to claim 1 is it is characterised in that before step 104 execution, also comprise the steps：
Determine whether described monitoring data meets early-warning conditions.
5. step according to claim 1 is it is characterised in that after step 109 execution, also comprise the steps：
The early warning route of final early warning scheme is shown in panorama threedimensional model.
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| CN103716586A (en) * | 2013-12-12 | 2014-04-09 | 中国科学院深圳先进技术研究院 | Monitoring video fusion system and monitoring video fusion method based on three-dimension space scene |
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| US20060033615A1 (en) * | 2004-08-12 | 2006-02-16 | Seong Taeg Nou | Emergency safety service system and method using telematics system |
| CN103716586A (en) * | 2013-12-12 | 2014-04-09 | 中国科学院深圳先进技术研究院 | Monitoring video fusion system and monitoring video fusion method based on three-dimension space scene |
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