CN109033607A - A kind of optimization method of microseism seismic source location parameter - Google Patents
A kind of optimization method of microseism seismic source location parameter Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
- G01S5/22—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/288—Event detection in seismic signals, e.g. microseismics
Abstract
The invention discloses a kind of optimization methods of microseism seismic source location parameter, it is the difference picked up with two geophones then and the minimum target of residual sum of squares (RSS) for the difference then being calculated, hypocentral location and equivalent velocity of wave are calculated using particle swarm algorithm, further according to hypocentral location and equivalent velocity of wave, the origin time of earthquake is directly calculated.The constraint rule of the parameters such as the practical inertia weight given in PSO derivation algorithm of incorporation engineering of the present invention, aceleration pulse, particle maximum flying speed, avoiding the improper selection due to these parameters causes algorithm to fail, the robustness for improving derivation algorithm achievees the purpose that reduce the number of iterations, improves positioning accuracy and algorithm speed.
Description
Technical field
The invention belongs to the microseism vibroseis positioning techniques of technical field of information processing, especially microseism seismic source location parameter
Optimization method, specifically, easily occur when aiming at microseism seismic source location parametric solution multiple parameters it is interrelated, convergence
The problems such as speed is slow, solution is not unique, proposes a kind of particle group optimizing (PSO, particle swarm optimization) algorithm
Focus is positioned, technical field of information processing is belonged to.
Background technique
The effectively position of monitoring rock micro rupture generation, can be improved the Coal Mine Disasters such as bump, coal and gas prominent
Monitoring and warning accuracy rate, all the time, the research to the accuracy and precision of seismic source location is the one of On Microseismic Monitoring Technique research
Item important content.The essence that Focal Parameters of Microearthquakes solves is, it is known that the space coordinate of each monitoring station is picked up according to each station
Microseism wave first arrival-time, determines the attributes such as space coordinate, the origin time of earthquake of focus, concrete principle and is analyzed as follows:
If microseismic system has n geophone (as shown in Figure 1), if note hypocentral location is (x0, y0, z0), each geophone coordinate
For (xi, yi, zi) (i=1,2 ..., n), the equivalent spread speed of P wave in the medium is V, at the time of P wave reaches each geophone
For ti, origin time of earthquake t0, then the calculated value of the difference for the microseism wave first arrival-time that geophone i and j are received are as follows:
Wherein,
For a pair of of geophone i and j, the difference regressand value of the microseism wave first arrival-time of pickup are as follows:
All regressand valuesWith calculated value Δ tijThe quadratic sum of difference reflect the departure degree of pickup value and calculated value,
Therefore the function model of identification microseism hypocentral location can be described as:
Wherein,
When Q is equal to or is intended to 0, (x is solved0, y0, z0), V be microseism hypocentral location and equivalent velocity of wave value, according to
Difference positioning principle then evaluates origin time of earthquake t0Function can be described as:
When F is equal to or is intended to 0, the origin time of earthquake are as follows:
Wherein,
When determining seismic source location and the origin time of earthquake, (x first is solved according to formula (3)0, y0, z0) and equivalent velocity of wave V, then by (x0,
y0, z0) and V value substitution formula (5) solution origin time of earthquake t0Value.Since formula (3) are (x0, y0, z0) and V secondary nonnegative function,
What minimum value was constantly present, therefore solution hypocentral location, equivalent velocity of wave and the origin time of earthquake are a nonlinear fitting problems, classics are done
Method is to seek its least square solution, but the parameters such as hypocentral location and the origin time of earthquake are interrelated in solution procedure, algorithmic statement is fast
Degree is slow, and is also easy to produce the problems such as solution is not unique.
To overcome problem above, present invention introduces adaptive PSO methods to optimize to positional parameter process.PSO is meter
A kind of kind of swarm intelligence algorithm for calculating smart field has many advantages, such as that algorithm realizes that simple, precision is high, convergence is fast, exists in recent years
Optimization field obtains many successful applications.
Summary of the invention
In order to solve the prior art in microseism seismic source location parameter determination process, there are hypocentral location and origin time of earthquake etc.
The technological deficiency that positional parameter is interrelated, positioning accuracy is low, positioning time is long and positioning result is not unique etc., the present invention provide
A kind of optimization method of the microseism seismic source location parameter based on population.
In order to achieve the above objectives, the technical solution adopted by the present invention is that:
A kind of optimization method of microseism seismic source location parameter, it is the difference picked up with two geophones then and calculated
The minimum target of the residual sum of squares (RSS) of the difference then arrived calculates hypocentral location and equivalent velocity of wave using particle swarm algorithm, then
According to hypocentral location and equivalent velocity of wave, the origin time of earthquake is directly calculated.Incorporation engineering is practical, solves and calculates The present invention gives PSO
The constraint rule of the parameters such as inertia weight, aceleration pulse, particle maximum flying speed in method, avoids due to these parameters not
When selection causes algorithm to fail, the robustness of derivation algorithm is improved, is reached and is reduced the number of iterations, improves positioning accuracy and algorithm
The purpose of speed.Specifically includes the following steps:
Step 1: multiple geophones are arranged in the different location first in microseism focus place to be measured, when microseismic event occurs
When, the microseism wave of generation receives and sends to computer by geophone, and computer carries out the microseism wave that each geophone receives
First arrival-time picks up, and establishes the function model of microseism hypocentral location, and model is expressed as follows formula:
Wherein,
In formula: (x0, y0, z0) it is hypocentral location；
I and j is two geophone labels；
(xi, yi, zi) be geophone i position；
(xj, yj, zj) be geophone j position；
liAnd ljDistance of the expression geophone i and geophone j to focus；
V indicates the equivalent spread speed of microseism wave in the earth formation；
Indicate the difference regressand value for the microseism P wave first arrival-time that geophone i and j are picked up；
Step 2: being solved using function model of the particle swarm algorithm to microseism hypocentral location, the specific method is as follows:
2.1: initialization a group particle makes its population scale size N (150≤N≤300), each particle exists in population
The position of flight space is expressed as a four-tuple, is denoted as zk(x, y, z, V), k=1,2 ..., N (are abbreviated as zk), wherein (x,
Y, z) indicate focus space coordinate, V indicates the equivalent velocity of wave that microseism wave is propagated in the earth formation；Correspondingly, each particle in population
Flying speed be also expressed as a four-tuple, be denoted as vk(x, y, z, V), k=1,2 ..., N (are abbreviated as vk)；Random initializtion
The position z of each particle in populationk, it is located at (x, y, z) in the space that the monitoring station is surrounded, and make 0 < V < 10；With
Machine initializes the initial velocity v of each particle flightk, and make 0 < vk< 5；Initialize the algebra g=0 that population is evolved；Maximum into
Change algebra Tmax=3000；
2.2: calculating the adaptive value of current each particle
G=g+1, (6) calculate the adaptive value Q of each particle according to the following formulak,
Define the history optimal location pBest of particlek=zk, in QkMiddle selection minimum value Qm, obtain the overall situation of particle group
Optimal location gBest=pBestm；
2.3: the algebra g and maximum evolutionary generation T that judgement initialization population is evolvedmaxSize relation
If g < Tmax, using the flying speed v of following formula (7) more new particlekWith the position z in flight spacek, then go to
2.2 steps calculate the adaptive value of current each particle,
In formula, ω is inertia weight, generally takes the number in [0,1] section；c1And c2It is accelerator coefficient, r1And r2It is [0,1] area
Between random number；
Otherwise, 2.4 are gone to step；
2.4: output zk, zkMiddle first three items are focus three-dimensional coordinate (x0, y0, z0), zkMiddle Section 4 is equivalent value of wave speed
V；
Step 3: equivalent value of wave speed V substitution following formula is calculated and exports origin time of earthquake t0, so far, seismic source location parameter is asked
Solution is completed；
In formula:
tiAt the time of representing P wave each geophone of arrival；
Preferably, to avoid in step 2.3 particle from falling into local optimum too early or missing globally optimal solution, using based on kind
The adaptive inertia weight value strategy of group velocity determines ω value, the method is as follows: sets initial inertia weight as ω0, kth is for population
The desired value of particle average speed isActual average speed isRemember that ω (k) is kth for particle inertia weight, p is normal
Number, then kth+1 generation inertia weight ω (k+1) is determined by following formula:
Its average speed is necessarily decremented to zero during ensuring that Evolution of Population in this way, the best value of p in the present invention
It is 1.07.The phase of kind of group-averaged velocity is defined referring to the Annealing function in simulated annealing for the exploring ability for reinforcing algorithm
Prestige value are as follows:
Wherein v0For the initial average speed of population, TmaxFor the maximum evolutionary generation of population.In focal shock parameter solution procedure
In, particle group-averaged velocity is defined as follows: because population particle dimension is 4 (focus three-dimensional coordinate and velocities of wave), population population is
N, then when kth time iteration population average speed are as follows:
In formulaFor velocity component of i-th of particle in jth dimension.
Preferably, aceleration pulse c in step 2.3 Chinese style (7)1And c2It is defined as follows:
In formula, C=2.0.
Further, it is preferable to particle maximum flying speed vmax, the present invention improves PSO algorithm performance using following formula (12):
Wherein, xmax、xminIt is the maximum and minimum value in presently found each dimension, M is the space-number designed in every dimension.
The positive effect of the present invention is: the difference regressand value of the microseism p wave first arrival-time picked up first with two geophones is timely
The minimum target of the residual sum of squares (RSS) of poor calculated value goes out hypocentral location and optimum speed value using PSO Algorithm, considers
The constraint rule of the parameters such as inertia weight, aceleration pulse, particle maximum flying speed avoids PSO Algorithm process from falling into
Enter local optimum；Then according to the hypocentral location acquired and optimum speed value, when being monitored with geophone with calculating then residual
The poor minimum target of quadratic sum, solves the focus origin time of earthquake；There is fast convergence rate compared to classical least square method, determine
The advantages that position precision is high, and the method does not need to measure microseism velocity of wave in advance can solve seismic source location parameter and the origin time of earthquake,
It eliminates in conventional mapping methods and is adversely affected due to wave speed measurement error to seismic source location bring.
Detailed description of the invention
Attached drawing 1 is that geophone receives microseism wave schematic diagram in the present invention.
Attached drawing 2 is that PSO algorithm solves flow chart in the present invention.
Specific embodiment
Technical solution of the present invention is further illustrated in the following with reference to the drawings and specific embodiments.
Embodiment, certain mine bump take place frequently, and are mounted with 24 Microseismic monitoring systems of multichannel thus, the mine is in different positions
Total installation geophone 18 are set, is chosen in -520 horizontal and -840 horizontal installations 9 respectively to verify effectiveness of the invention
The bursting work of known location is research object, shares 10 geophones in operation process and detects that effective microseismic signals are shown in Fig. 1,
The pretreatment such as de-noising, filtering is carried out to the signal that on-site test arrives, obtains the high signal of signal-to-noise ratio, then therefrom choose waveform take-off
Obviously, convenient for capture first arrival-time 2 blow-up points analyzed, spatial position coordinate be respectively A (1495.60,
998.50, -685.10), (1298.70,855.30, -576.20) B are detected after the coordinate and two separate explosions of 10 geophones
The 2 blow-up point first arrival-times arrived are as shown in table 1.
1 sensor coordinates of table and P wave first arrival-time
Note: in table first arrival-time be relative to detonation the moment microseism seismic wave walk when.
The mathematical model as shown in formula (3) is initially set up, is then optimized according to inventive algorithm, specific as follows:
Step 1: initialization population makes its population scale size N=200, each particle in random initializtion population
Position zk, it is located at (x, y, z) in the space that the monitoring station is surrounded, and make 0 < V < 10；The each particle of random initializtion
The initial velocity v of flightk, make 0 < vk< 5；The algebra g=0 that population is evolved；Maximum evolutionary generation Tmax=3000；
Step 2: g=g+1 calculates the fitness function value Q of each particle according to formula (6)k, the history for defining particle is optimal
Position pBestk=zk, in QkMiddle selection minimum value Qm, obtain the global optimum position gBest=pBest of particle groupm；
Step 3: the algebra g and maximum evolutionary generation T that judgement initialization population is evolvedmaxSize relation
If g < Tmax, the flying speed v of applying equation (7) more new particlekWith position zk；Wherein, ω is determined by formula (8), c1,
c2It is determined by formula (11), takes r1=r2=0.75；Then the adaptive value that step 2 calculates current each particle is come back to
Otherwise, 4 are gone to step
Step 4: output zk, zkMiddle first three items are focus three-dimensional coordinate (x0, y0, z0), zkMiddle Section 4 is equivalent velocity of wave
Value V.
Step 5: equivalent value of wave speed V is substituted into formula (5) calculating and exports origin time of earthquake t0。
Based on the data that table 1 provides, seismic source location parameter and the origin time of earthquake are solved using PSO method proposed by the present invention,
It is as shown in table 2 to solve obtained position error.
2 seismic source location error of table and algorithm are time-consuming
As shown in Table 2, algorithm of the present invention can be according to given initial parameter range auto-feeding true value, in X, Y, Z
Mean error on three directions is respectively 6.37m, 5.78m and 9.03m, and relative error is within 5%.The present invention proposes
PSO optimization method can obtain higher positioning accuracy.
Above embodiments explanation solves seismic source location parameter and the origin time of earthquake more compared with conventional method using PSO optimization algorithm
To be superior, algorithm has the characteristics that positioning accuracy height, fast convergence rate, initial parameter setting are easy, this is because adaptive PSO
Algorithm has accurately been fitted each geophone coordinate and the relationship between the time difference, in an iterative process dynamic adjustment value of wave speed, directly
To approach this microseismic event most preferably averagely value of wave speed, to meet each geophone coordinate and the non-linear relation between the time difference,
Greatly reducing is influenced due to velocity of wave error to positioning accuracy bring.
The above is the citing of embodiment of the present invention, wherein the part that do not address in detail is ordinary skill
The common knowledge of personnel.Protection scope of the present invention is based on the contents of the claims, any based on technical inspiration of the invention
And the equivalent transformation carried out, also within protection scope of the present invention.
Claims (4)
1. a kind of optimization method of microseism seismic source location parameter, which is characterized in that it is arrived with what two geophones picked up
When difference and the difference then being calculated the minimum target of residual sum of squares (RSS), calculate hypocentral location using particle swarm algorithm
The origin time of earthquake is directly calculated further according to hypocentral location and equivalent velocity of wave with equivalent velocity of wave, specifically includes the following steps:
Step 1: multiple geophones are arranged in the different location first in microseism focus place to be measured, when microseismic event occurs, produce
Raw microseism wave receives and sends to computer by geophone, and computer carries out first arrival to the microseism wave that each geophone receives and arrives
When pick up, and establish the function model of microseism hypocentral location, model is expressed as follows formula:
Wherein,
In formula: (x0, y0, z0) it is hypocentral location；
I and j is two geophone labels；
(xi, yi, zi) be geophone i position；
(xj, yj, zj) be geophone j position；
liAnd ljDistance of the expression geophone i and geophone j to focus；
V indicates the equivalent spread speed of microseism wave in the earth formation；
Indicate the difference regressand value for the microseism P wave first arrival-time that geophone i and j are picked up；
Step 2: being solved using function model of the particle swarm algorithm to microseism hypocentral location, the specific method is as follows:
2.1: initialization a group particle makes its population scale size N (150≤N≤300), each particle is flying in population
The position in space is expressed as a four-tuple, is denoted as zk(x, y, z, V), k=1,2 ..., N (are abbreviated as zk), wherein (x, y, z)
Indicate focus space coordinate, V indicates the equivalent velocity of wave that microseism wave is propagated in the earth formation；Correspondingly, in population each particle fly
Scanning frequency degree is also expressed as a four-tuple, is denoted as vk(x, y, z, V), k=1,2 ..., N (are abbreviated as vk)；Random initializtion population
In each particle position zk, it is located at (x, y, z) in the space that the monitoring station is surrounded, and make 0 < V < 10；It is random first
The initial velocity v of each particle flight of beginningizationk, and make 0 < vk< 5；Initialize the algebra g=0 that population is evolved；Maximum is evolved generation
Number Tmax=3000；
2.2: calculating the adaptive value of current each particle
G=g+1 calculates the adaptive value Q of each particle according to the following formulak,
Define the history optimal location pBest of particlek=zk, in QkMiddle selection minimum value Qm, obtain the global optimum of particle group
Position gBest=pBestm；
2.3: the algebra g and maximum evolutionary generation T that judgement initialization population is evolvedmaxSize relation
If g < Tmax, using the flying speed v of following formula more new particlekWith the position z in flight spacek, then go to 2.2 step meters
The adaptive value of current each particle is calculated,
In formula, ω is inertia weight, generally takes the number in [0,1] section；c1And c2It is accelerator coefficient, r1And r2It is [0,1] section
Random number；
Otherwise, 2.4 are gone to step；
2.4: output zk, zkMiddle first three items are focus three-dimensional coordinate (x0, y0, z0), zkMiddle Section 4 is equivalent value of wave speed V；
Step 3: equivalent value of wave speed V substitution following formula is calculated and exports origin time of earthquake t0, so far, seismic source location parametric solution is complete
At；
In formula:
tiAt the time of representing P wave each geophone of arrival.
2. the optimization method of microseism seismic source location parameter as described in claim 1, which is characterized in that the step
Inertia weight ω value in 2.3 uses the adaptive inertia weight value strategy based on kind of group velocity to determine, the method is as follows: sets just
Beginning inertia weight is ω0, kth is for the desired value of population particle average speedActual average speed isRemember ω (k)
It is kth for particle inertia weight, p is constant, then kth+1 generation inertia weight ω (k+1) is determined by following formula:
In formula:
The value of p is 1.07
Kth is for the desired value of population particle average speed
Wherein v0For the initial average speed of population, TmaxFor the maximum evolutionary generation of population；In focal shock parameter solution procedure, particle
Group-averaged velocity is defined as follows: because population particle dimension is 4, population population is N, then population is averaged when kth time iteration
Speed are as follows:
In formulaFor velocity component of i-th of particle in jth dimension.
3. the optimization method of microseism seismic source location parameter as claimed in claim 2, which is characterized in that step 2.3 accelerates
Constant c1And c2It is defined as follows:
In formula, C=2.0.
4. the optimization method of microseism seismic source location parameter as claimed in claim 3, which is characterized in that maximum flying speed
vmax, obtained using following formula
Wherein, xmax、xminIt is the maximum and minimum value in presently found each dimension, M is the space-number designed in every dimension.
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| CN109597120A (en) * | 2019-01-08 | 2019-04-09 | 中国矿业大学 | A kind of method of acoustic emission experiment seismic source location under laboratory scale |
| CN110018062A (en) * | 2019-05-07 | 2019-07-16 | 中国科学院武汉岩土力学研究所 | Rock structural face failure by shear location positioning method in a kind of direct shear test |
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| CN110514745A (en) * | 2019-09-02 | 2019-11-29 | 北京理工大学 | A method of it is determined based on the cable circuit wire position of multifrequency acoustic emission signal |
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| CN111736208A (en) * | 2020-06-24 | 2020-10-02 | 重庆大学 | Microseismic event Bayes positioning method, system and medium combining P wave and S wave first-motion data by variable weight |
| CN111736208B (en) * | 2020-06-24 | 2023-04-07 | 重庆大学 | Microseismic event Bayes positioning method, system and medium combining P wave and S wave first-arrival data through variable weight |
| CN112731523A (en) * | 2020-12-22 | 2021-04-30 | 北京环境特性研究所 | Seismic source positioning method, computer equipment and computer readable storage medium |
| CN112731523B (en) * | 2020-12-22 | 2022-09-16 | 北京环境特性研究所 | Seismic source positioning method, computer equipment and computer readable storage medium |
| CN113176606A (en) * | 2021-06-02 | 2021-07-27 | 中国恩菲工程技术有限公司 | Method, system, equipment and storage medium for positioning micro-seismic source |
| CN113176606B (en) * | 2021-06-02 | 2023-09-26 | 中国恩菲工程技术有限公司 | Microseism focus positioning method, system, equipment and storage medium |
| CN114047546A (en) * | 2021-11-18 | 2022-02-15 | 辽宁大学 | Crowd-sourcing spiral mine earthquake positioning method based on three-dimensional spatial joint arrangement of sensors |
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Application publication date: 20181218 |