CN104049284A - Lightning locating method based on particle swarm genetic mixed algorithm - Google Patents
Lightning locating method based on particle swarm genetic mixed algorithm Download PDFInfo
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Abstract
The invention relates to the field of lightning science and atmospheric probing, in particular to a lightning locating method based on a particle swarm genetic mixed algorithm. According to the method, firstly a lighting stroke point initial position is obtained by adopting an oriented time difference comprehensive locating method to determine the range of a solution space, solution particles are generated randomly in the solution space, searching is carried out through a particle swarm algorithm to obtain an initial population of a certain evolution degree, then optimization of a later stage is carried out through a genetic algorithm, optimum is avoided, and finally the optimum position where lightning occurs is obtained. The position where the lightening occurs can be worked out by the lightning locating method based on the particle swarm genetic mixed algorithm, and compared with a traditional method, optimizing precision, stability and speed are all improved remarkably.
Description
Technical field
The present invention relates to thunder and lightning science and atmospheric exploration field, relate in particular to a kind of Lightning Location Method based on population Genetic Hybrid Algorithm.
Background technology
Thunder and lightning is the weather phenomenon that betides a kind of Transient Currents in atmosphere, high voltage, strong electromagnetic radiation, generation per second approximately 100 times on the earth.Because it discharges huge energy within the utmost point short time, the production to the mankind and life form larger threat, are one of the most serious disasters of nature.The key of surveying thunder and lightning is thunder and lightning location, and thunder and lightning location is method and the technology of determining lightning geographic location according to sferic signal.Thunder and lightning positioning information can be lightning monitoring, meteorological research provides valuable data information, and also can be the thunder calamity early warning of the department such as aerospace system, electric system and preventing and reducing natural disasters provides important support.
At present, Lightning Location Method is divided into Directional Method, time difference method and orientation-time difference combined method.The measuring error of Directional Method is larger, needs observed quantity less; Time difference method positioning precision is higher, needs observed quantity more.Orientation-time difference combined method, by the two comprehensive advantage complementation, is obtained direction and view of time simultaneously and is measured on a station, can improve precision.But due to the existence of antenna direction, systematic error, noise and other interference, still can there is certain deviation in the thunder and lightning position that adopts orientation-time difference combined method to obtain, therefore positioning result needs to be optimized.
Particle cluster algorithm (Particle Swarm Optimization, PSO) uses simple, fast convergence rate, but easily precocious, be absorbed in local optimum; And genetic algorithm (Genetic Algorithm, GA) ability of searching optimum is strong, but search speed is slow. can find out between these two kinds of algorithms, have very strong complementary.If the combination of the algorithm by these two kinds based on group's concept is to can thunder and lightning location Calculation optimization problem solving, utilize the feature of particle cluster algorithm fast convergence rate to carry out the optimization of previous stage, then carried out the optimization of the latter half by genetic algorithm, thereby obtain a hybrid algorithm (PSO-GA) that overall performance is more excellent.
In view of this, the invention provides a kind of Lightning Location Method based on population Genetic Hybrid Algorithm, to meet practical application needs.
Summary of the invention
The object of the invention is, for the deficiencies in the prior art, improve, propose high stability and the high-speed Lightning Location Method based on population Genetic Hybrid Algorithm, improve the precision of thunder and lightning location.
For achieving the above object, the technical solution used in the present invention is: a kind of Lightning Location Method based on population Genetic Hybrid Algorithm, comprises the steps:
(1) adopt orientation-time difference combined method to obtain lightning strike spot initial position, determine solution space scope;
(2) random generating solution particle in this solution space, searches for by particle cluster algorithm, and optimal particle is retained, and removes the poor particle of fitness, the initial population of the degree of necessarily being evolved;
(3) carried out the optimization of the latter half by genetic algorithm, avoid being absorbed in optimum, finally obtain the optimum position that thunder and lightning occurs.
The invention has the beneficial effects as follows: adopt population Genetic Hybrid Algorithm to carry out the location Calculation of thunder and lightning position, with respect to classic method, in can calculating thunder and lightning occurrence positions, population Genetic Hybrid Algorithm has had and has significantly improved in optimizing precision, stability and speed, and amount of calculation obviously reduces with respect to traditional alternative manner.The present invention is for determining that fast Lightning Disaster position is significant in weather forecast, forest fire protection, Aero-Space transmitting.
Brief description of the drawings
Fig. 1 is comprehensive positioning principle figure of orientation-time difference.
Fig. 2 is PSO-GA hybrid algorithm process flow diagram.
Fig. 3 is the Lightning Location Method schematic diagram based on population Genetic Hybrid Algorithm.
Embodiment
In order to understand better the present invention, further illustrate content of the present invention below in conjunction with embodiment, but content of the present invention is not only confined to the following examples.Those skilled in the art can make various changes or modifications the present invention, and these equivalent form of values are equally within the listed claims limited range of the application.
The step of Lightning Location Method that the present invention is based on population Genetic Hybrid Algorithm is as follows:
1. adopt orientation-time difference combined method to obtain lightning strike spot initial position, determine solution space scope.
From thunder and lightning positioning principle, lightening detection device can receive these electromagnetic waves and record its time of arrival and arrival direction.In the time that multiple acquisition stations receive thunder and lightning signal, just can calculate thunder and lightning position.As shown in Figure 1, establish thunder and lightning occur actual position be
x =(
x, y), three acquisition station coordinates are
x i =(
x i , y i ),
i=1,2,3, the time of arrival that acquisition station records
t i and arrival direction
can represent suc as formula (1):
（1）
Wherein
the geodesic line length from thunder and lightning position to acquisition station,
tfor thunder and lightning time of origin,
cfor the light velocity,
ε i with
e i be respectively the stochastic error of time and orientation measurement, can suppose that their obey that average is zero, variance is respectively
with
normal distribution, desirable in practical application
,
.
For the unknown parameter in cancelling (1)
t, can adopt time difference measurement value to carry out thunder and lightning location, each time difference measurement value exists
xyin plane, define a hyperbolic curve, thunder and lightning position is these hyp intersection points.In the time that hyperbolic curve has a more than intersection point, can remove pseudo-anchor point by the definite thunder and lightning scope of Directional Method.The lightning strike spot position that adopts orientation-time difference combined method just to calculate is (x
0, y
0), because this position and actual lightning strike spot have certain deviation, delimit solution space scope so (turn to longitude and latitude and be about 0.05 °) taking 5km as radius, within the scope of this, find optimum lightning strike spot position.
2. random generating solution particle in this solution space, searches for by particle cluster algorithm, and optimal particle is retained, and removes the poor particle of fitness, the initial population of the degree of necessarily being evolved.
As shown in Figure 2, using thunder and lightning occurrence positions as solving target, need population to exist
xytwo-dimensional space search, PSO algorithm is first at one group of particle of solution space initialization randomly of 2 dimensions, and for thunder and lightning location Calculation, through experiment, the population size of particle is generally 20, and each particle calculates corresponding fitness function value according to formula (2).Hypothetical particle has memory, can preserve coordinate and the fitness function value of the optimal location that it reaches, and can also remember the optimal location and the corresponding fitness function value that in all particle search processes of whole population, reach simultaneously.
（2）
Wherein,
nfor participating in the acquisition station number of location,
x m for particle current location, m=1,2 ..., 20,
for the current location and of particle
ithe deflection of individual acquisition station,
d i (
x m ) be the current location to the of particle
ithe distance of individual acquisition station,
t 0the mean value of the thunder and lightning time of origin of deriving for each station.
If
p m for the historical optimal location of particle,
p g for the current global optimum position of population, according to the principle of following current optimal particle, particle will upgrade by formula (3) oneself speed and position.In the time that update times is greater than maximum iteration time (through experiment, generally getting 100), stop upgrading, obtain the initial population of certain evolution degree.
（3）
Wherein,
v m for flying speed of partcles,
kfor current renewal step number,
ωfor the inertial factor between 0.1 ~ 0.9, it can reduce flying speed of partcles, prevent from searching for dispersing,
c 1with
c 2for the study factor, represent respectively the acceleration of particle towards this particle self optimal location and global optimum's position motion, thereby the speedup factor that is otherwise known as, generally get
c 1=
c 2=2;
r m1
with
r m2
the diagonal matrix that is respectively 2 × 2 dimensions, each diagonal element is the random number between [0,1].
3. carried out the optimization of the latter half by genetic algorithm, avoid being absorbed in optimum, finally obtain the optimum position that thunder and lightning occurs.
In the time carrying out genetic algorithm, first need to determine important parameters such as selecting operator, crossover operator and mutation operator.Select the design adoption rate of operator to select and optimum mixed strategy of preserving.Ratio selecting party for a Population Size is
k, ideal adaptation degree is
f i population, individuality
iselected probability
.The method can ensure to have the selected maximum probability of individuality of minimum fitness.And after new population generates, apply optimum conversation strategy, compare the minimum fitness individuality in new and old population, with the maximum adaptation degree individuality in this individuality replacement new population.The Design and implementation of crossover operator is closely related with the problem of studying, and General Requirements had not both destroyed the defect mode that represents merit in individual coded strings too much, can effectively produce again some preferably new individual mode.Implementation method is first to produce at random 1 crossover location, and then 2 father's chromosomes, taking crossover location as boundary, are intercoursed the chromosome of crossover location leading portion, thereby generate 2 new daughter chromosomes.Whether the enforcement of interlace operation is decided by crossover probability Pc, and general span is 0.3～0.9.The design of mutation operator comprises the content of two aspects: the position of definitive variation point, the Gene Replacement method of variation position.Design mutation algorithm is as follows: produce at random 2 variation positions, then exchange these 2 the locational code values of variation.Mutation operation determines whether carry out, be generally taken as 0.001 ~ 0.100 by the probability P m that makes a variation.Through experiment, carrying out in thunder and lightning location Calculation, crossover operator is taken as 0.3, and mutation operator is taken as 0.1.
As shown in Figure 2,10 particles optimum in initial population obtained in the previous step are retained, then, taking the positional value of these 10 particles as basis, select to copy to obtain 10 individualities, and intersect, the genetic operator computing such as variation.10 particle position values that finally PSO retained and the GA new particle population of 10 merging formation obtaining of evolving, carries out evolution computing of future generation.If evolution number of times is less than maximum evolution number of times (through experiment, generally getting 100), return to step 2; Otherwise, obtain the optimum solution of thunder and lightning position.
Embodiment:
A trip accident for certain electric power transmission line trip accident on August 27th, 2011 is that example describes.Trip time is 15:52:29, B phase fault, and switch trip, reclosing failure, differential, move apart from I segment protect.Line walking result is in #2 tower B() the small size side glass insulator of phase strain insulator has spark tracking, and have slightly and burn.It is hillside that lightning stroke trip Terrain occurs, and thunderbolt character is shielding, and stake resistance is 2.2 Ω, and lightning strike spot coordinate is (119.921408333249,30.131419444614).
Table 1 is the raw data of a thunder and lightning location of certain electric system the Lightning Detection Network, comprises acquisition station position and thunder and lightning time of arrival (toa).Adopt Genetic Particle Swarm Algorithm to calculate thunder and lightning this time, taking formula (2) as fitness function.Process by thinking shown in Fig. 3, the thunder and lightning occurrence positions being calculated by population genetic algorithm is (119.9234,30.1331), and line of electric force lightning strike spot is (119.921408333249,30.131419444614), both are at a distance of 267.87m.At present both at home and abroad the positioning precision of lightning location system is generally 500 ~ 1000m, and visible comparison of computational results is reasonable, further illustrates the Lightning Location Method based on population Genetic Hybrid Algorithm that this patent carries and has feasibility.
Table
lightning strike accident location raw data
| Station number | Longitude | Latitude | Time of arrival/0.1ns |
| 1 | 119.608818887016 | 29.1049488868391 | 1322604 |
| 2 | 120.081429169034 | 30.871372778765 | 1321447 |
| 3 | 120.737320553821 | 30.7808450002272 | 1322213 |
| 4 | 120.561363335635 | 29.9970863893881 | 1320784 |
| 5 | 121.520229720351 | 29.8946527770506 | 1323875 |
| 6 | 119.265223608752 | 29.4751619450696 | 1321897 |
| 10 | 121.126599441586 | 28.8514899996437 | 1324806 |
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention.The content not being described in detail in this instructions belongs to the known prior art of professional and technical personnel in the field.
Claims (1)
1. the Lightning Location Method based on population Genetic Hybrid Algorithm, is characterized in that, comprises the steps:
(1) adopt orientation-time difference combined method to obtain lightning strike spot initial position, determine solution space scope;
(2) random generating solution particle in this solution space, searches for by particle cluster algorithm, and optimal particle is retained, and removes the poor particle of fitness, the initial population of the degree of necessarily being evolved;
(3) carried out the optimization of the latter half by genetic algorithm, avoid being absorbed in optimum, finally obtain the optimum position that thunder and lightning occurs.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106501767A (en) * | 2016-10-13 | 2017-03-15 | 哈尔滨工程大学 | A kind of motion multistation passive TDOA location method |
| CN106841750A (en) * | 2017-03-13 | 2017-06-13 | 清华大学 | Lightning current waveform parameter identification method based on Powell algorithms and particle cluster algorithm |
| CN107609649A (en) * | 2017-09-13 | 2018-01-19 | 广东电网有限责任公司江门供电局 | A kind of lighting location calculation optimization method based on Genetic Particle Swarm mixing |
| CN109374986A (en) * | 2018-09-19 | 2019-02-22 | 中国气象局气象探测中心 | A kind of Lightning Location Method and system based on clustering and grid search |
| CN109870716A (en) * | 2017-12-01 | 2019-06-11 | 北京京东尚科信息技术有限公司 | Localization method and positioning device and computer readable storage medium |
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| CN102967770A (en) * | 2012-08-23 | 2013-03-13 | 南京信息工程大学 | Thunder locating method based on chaos particle swarm optimization (PSO) algorithm |
| CN103679263A (en) * | 2012-08-30 | 2014-03-26 | 重庆邮电大学 | Thunder and lightning approach forecasting method based on particle swarm support vector machine |
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| US20030187580A1 (en) * | 2002-03-29 | 2003-10-02 | The Tokyo Electric Power Company, Inc. | Lightning strike position locating method, apparatus, system and program |
| JP2006337347A (en) * | 2005-06-06 | 2006-12-14 | Nippon Telegr & Teleph Corp <Ntt> | Method and system for predicting thunder position |
| CN102967770A (en) * | 2012-08-23 | 2013-03-13 | 南京信息工程大学 | Thunder locating method based on chaos particle swarm optimization (PSO) algorithm |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106501767A (en) * | 2016-10-13 | 2017-03-15 | 哈尔滨工程大学 | A kind of motion multistation passive TDOA location method |
| CN106841750A (en) * | 2017-03-13 | 2017-06-13 | 清华大学 | Lightning current waveform parameter identification method based on Powell algorithms and particle cluster algorithm |
| CN106841750B (en) * | 2017-03-13 | 2019-07-26 | 清华大学 | Lightning current waveform parameter identification method based on Powell algorithm and particle swarm algorithm |
| CN107609649A (en) * | 2017-09-13 | 2018-01-19 | 广东电网有限责任公司江门供电局 | A kind of lighting location calculation optimization method based on Genetic Particle Swarm mixing |
| CN109870716A (en) * | 2017-12-01 | 2019-06-11 | 北京京东尚科信息技术有限公司 | Localization method and positioning device and computer readable storage medium |
| CN109374986A (en) * | 2018-09-19 | 2019-02-22 | 中国气象局气象探测中心 | A kind of Lightning Location Method and system based on clustering and grid search |
| CN109374986B (en) * | 2018-09-19 | 2021-07-09 | 中国气象局气象探测中心 | Thunder and lightning positioning method and system based on cluster analysis and grid search |
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