CN108802834A - A kind of buried target recognition methods based on joint inversion - Google Patents
A kind of buried target recognition methods based on joint inversion Download PDFInfo
- Publication number
- CN108802834A CN108802834A CN201810150310.XA CN201810150310A CN108802834A CN 108802834 A CN108802834 A CN 108802834A CN 201810150310 A CN201810150310 A CN 201810150310A CN 108802834 A CN108802834 A CN 108802834A
- Authority
- CN
- China
- Prior art keywords
- buried target
- recognition methods
- algorithm
- target recognition
- buried
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
- G01V3/10—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices using induction coils
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Geophysics (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Environmental & Geological Engineering (AREA)
- Electromagnetism (AREA)
- Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The buried target recognition methods based on joint inversion that the present invention provides a kind of comprising following steps:Step 1: establishing observation coordinate system near abnormal area, the coordinate of transmitting coil and receiving coil is recorded, one-point measurement obtains the survey area response of secondary field;Step 2: parameter, observation coordinate and the observed responses of input electromagnetic survey system dispatch coil;Step 3: carrying out first inverting using the first optimization algorithm, inversion result is obtained;It is solved Step 4: the inversion result that step 3 obtains is input to the second optimization algorithm, obtains final inversion result;Step 5: the final inversion result obtained according to step 4, object to be measured is identified into row information.In practical applications, the present invention as accurate inverting buried target information and can judge the method for target signature.
Description
Technical field
The invention belongs to buried target identification technology field, more particularly to a kind of buried target identification based on joint inversion
Method.
Background technology
Time domain electromagnetic method is a kind of artificial source's lossless detection method established on the basis of electromagnetic induction principle, it is utilized
Earth-free loop line (magnetic source) or ground connection line source (Electric Dipole) emit primary field to underground, under its excitation, in sub-surface conductors target
The induction field that the inductive loop encouraged changes over time generation.Due to very low emission signal frequency, time-domain electricity
What magnetic method met is the diffusion equation rather than wave equation of electromagnetic wave, since the bulk effect in diffusion field makes its resolution ratio very
It is low, lead to that direct imaging can not possibly be carried out to buried target using time domain electromagnetic method, it can only be by forward model to underground mesh
Mark carries out inverting solution, but the response of the secondary field of general finite conductor can not acquire analytic solutions, according to finite element or limited
The numerical computation method of difference, then calculation amount is excessively huge, therefore using dipole model come approximatively equivalent sub-surface conductors mesh
Mark obtains the equivalent dipole intensity of target by inverting iteration, and further judges to obtain the information of target.
In the implementation of the present invention, it is found by the applicant that the above-mentioned prior art there are following technological deficiencies:
In inverting iterative process, the selection of initial value is particularly important, directly affects final inversion result.It is currently used
Method be provide the general plan-position of buried target using actual measurement response, but target buried depth, inclination angle and dipole strength without
Method is obtained by surveying response, can only provide the initial value of conjecture, and requirement of the local optimum LM algorithms generally used to initial value
Very high, if initial value is inaccurate, the inversion result finally solved differs quite big with practical.And global optimization DE algorithms is used to take
It is long, and DE algorithms global search and local search ability be contradictory, equally exist the problem of cannot converging to optimal solution.
On the basis of inversion result, obtained the fitting expression of dipole strength, but fit procedure need to substitute into it is secondary
All observation time points of response, include the late period signal very sensitive to noise, this can cause larger calculation amount, and have
Inaccurate result may be fitted.
Invention content
In view of above-mentioned technical problem, the purpose of the present invention is to provide a kind of buried target identification side based on joint inversion
Method.
In order to achieve the above object, the technical solution adopted by the present invention is as follows:
A kind of buried target recognition methods based on joint inversion comprising following steps:
Step 1: establishing observation coordinate system near abnormal area, the coordinate of transmitting coil and receiving coil, fixed point are recorded
Measure the survey area response for obtaining secondary field;
Step 2: parameter, observation coordinate and the observed responses of input electromagnetic survey system dispatch coil;
Step 3: carrying out first inverting using the first optimization algorithm, inversion result is obtained;
It solves, obtains final anti-Step 4: the inversion result that step 3 obtains is input to the second optimization algorithm
Drill result;
Step 5: the final inversion result obtained according to step 4, object to be measured is identified into row information.
It can be seen from the above technical proposal that the present invention is based on the buried target recognition methods of joint inversion at least have with
One of lower advantageous effect:
(1) present invention taken for global optimization but relatively accurate, local optimum convergence it is fast but easily by initial value affecting the characteristics of,
It proposes that combined optimization algorithm carries out inverting to buried target, accurate inverting knot can be obtained under the premise of not needing prior information
Fruit;
(2) present invention proposes that the new algorithm of target component extraction, the expression formula for not needing fit object dipole curve carry
Parameter is taken, calculation amount is small, can promptly determine the property of buried target itself.
Description of the drawings
Fig. 1 is the flow chart of buried target recognition methods of the embodiment of the present invention based on DE-LM joint inversions.
Fig. 2 is that secondary field response measurement of the embodiment of the present invention records coordinate schematic diagram.
Fig. 3 is changing rule figures of the improved CR of the embodiment of the present invention with iterative steps.
Fig. 4 is that the embodiment of the present invention improves DE and tradition DE convergence comparison schematic diagrams.
Fig. 5 is the convergence comparison schematic diagram of DE-LM of embodiment of the present invention algorithms and DE algorithms, LM algorithms.
Fig. 6 is the corresponding dipole strength figure of three kinds of inversion methods.
Fig. 7 is the survey area inversion chart comparison schematic diagram of three kinds of algorithms.
Specific implementation mode
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference
Attached drawing, the present invention is described in more detail.
The buried target recognition methods based on joint inversion that the present invention provides a kind of comprising following steps:
Step 1: establishing observation coordinate system near abnormal area, the coordinate of transmitting coil and receiving coil, fixed point are recorded
Measure the survey area response for obtaining secondary field;
Step 2: parameter, observation coordinate and the observed responses of input electromagnetic survey system dispatch coil;
Step 3: carrying out first inverting using the first optimization algorithm, inversion result is obtained;
It solves, obtains final anti-Step 4: the inversion result that step 3 obtains is input to the second optimization algorithm
Drill result;
Step 5: the final inversion result obtained according to step 4, object to be measured is identified into row information.
Wherein, the first optimization algorithm that step 3 uses can be improved differential evolution DE algorithms, genetic algorithm, simulation
Annealing algorithm, tabu search algorithm, particle cluster algorithm, ant group algorithm.The second optimization algorithm in step 4 can be
Levenberg-MarquardtLM algorithms, Newton's algorithm, conjugate gradient algorithms.
Below by taking the buried target recognition methods based on DE-LM joint inversions as an example, elaborate to the present invention.
Fig. 1 is the flow chart of buried target recognition methods of the embodiment of the present invention based on DE-LM joint inversions.Such as Fig. 1 institutes
Show, the present invention is based on the buried target recognition methods of DE-LM joint inversions to include the following steps:
Step 1: establishing observation coordinate system near abnormal area, the coordinate of transmitting coil and receiving coil, fixed point are recorded
Measure the survey area response for obtaining secondary field;
Step 2: parameter, observation coordinate and the observed responses of input electromagnetic survey system dispatch coil;
Step 3: carrying out first inverting using improved differential evolution DE algorithms, inversion result is obtained;
It solves, obtains Step 4: the inversion result that step 3 obtains is input to Levenberg-Marquardt algorithms
To final inversion result;
Step 5: the final inversion result obtained according to step 4, object to be measured is identified into row information.
In step 2, the parameter of dispatch coil includes:Transmitting coil size, emission current size, receiving coil size
And the position relationship etc. of transmitting coil and receiving coil.
In step 3, first inverting is carried out using improved differential evolution algorithm, obtains more accurately inversion result,
The information such as three-dimensional coordinate, inclination angle and three-dimensional doublet intensity including target.When time domain electromagnetic method inverting buried target, wait for anti-
It is needed when it is more to drill parameter, and dipole strength is big in early late period magnitude difference, therefore inverting is carried out using differential evolution (DE) algorithm
Reinforce ability of searching optimum, once navigating to the Position Approximate of optimal solution, and needs to reinforce local search ability.And the overall situation is searched
Rope and local search ability are contradictory.The crossover probability CR of original algorithm is that constant starts to hold if CR values are excessive just
Premature Convergence is easily caused, if CR values are too small, late local search ability is not good enough.Therefore a crossover probability is reconfigured
The factor
Wherein, G is the current iteration number of differential evolution algorithm, and Gm is the maximum iteration of differential evolution algorithm.
When just starting search, CR is smaller and is kept for a period of time, ensures the diversity and ability of searching optimum of population;So
It is transitioned into greatly by small afterwards, finally slowly ensures late convergence and local search ability close to 1.
Three-dimensional position range, inclination angle range and the three-dimensional doublet strength range for setting target, are calculated using improved DE
Method carries out first inverting, obtains more accurately inversion result.
Though the reconstruct crossover probability factor overcomes premature problem to a certain extent, but still cannot accurately converge to most
Excellent solution, and because time-consuming for its inverting, it is unsatisfactory for actual demand.And when LM algorithms being utilized to solve, though it is easily received when far from optimal solution
Locally optimal solution is held back, but convergence rate is exceedingly fast when its initial value is near globally optimal solution.So by the inverting in step 3
As a result it substitutes into Levenberg-Marquardt (LM) algorithm and obtains final inversion result.
In step 5, following sub-step is specifically included:
S1, dipole strength is subjected to parametric synthesis, obtains the characteristic information about object to be measured, as size, attenuation rate,
Symmetry, axis ratio etc..
The dipole strength of inversion result in step 4 is subjected to parametric synthesis, is obtained about clarification of objective information
Size,Decay,Symmetry,Ratio.Target sizes are different, internal to pass through the magnetic flux generated by primary field different, after
And when off between after, the eddy current that target internal generates is different (having corresponded to different equivalent magnetic dipole strengths), is connecing
The induced voltage that take-up circle generates is different.Target is bigger, and equivalent magnetic dipole strength is bigger, and induced voltage is bigger.Therefore it uses
Size characterizes the size of target
t1Indicate the central instant of first time window.
Object to be measured material is different, and the rate of decay of internal vortex is different (have been corresponded to different equivalent magnetic dipoles to decline
Subtract the Different Slope of curve).Object to be measured conductivity is bigger, and equivalent magnetic dipole rate of decay is slower.Therefore it is indicated with Decay
Target attenuation rate,
tnFor the central instant of late period sampling time window.
Target shape is different, and the distribution of internal vortex is different.Target is more symmetrical, and Eddy Distribution is more symmetrical, equivalent magnetic couple
Pole sub-feature is also more similar.Therefore with the symmetry of the proportionate relationship characterization target between magnetic dipole attenuation characteristic curve.
Symmetry indicates target symmetry,
Target axial ratio is bigger, and the Eddy Distribution difference that primary field has been encouraged when different direction irradiates target is got over
Greatly, the difference between equivalent magnetic dipole attenuation characteristic is also bigger.But it goes to characterize with the proportionate relationship between dipole strength
When the geometrical relationship of target, first have to consider the different characteristics that target different materials cause response.
So indicate mesh parameter-ratio with Ratio,
The characteristic information comprehensive descision object to be measured that S2, basis obtain.
Specific embodiment:
In this embodiment, by the buried target recognition methods based on DE-LM joint inversions illustrated, over the ground
Lower target is identified.
Survey area is 5m*5m, establishes observation coordinate system, the steel drum that size is 20*10*10 (cm) be placed on coordinate (2.5,
2.5, -1.5) at, the inclination angle α, β is 0 °.The secondary field of electromagnetic survey system interval 50cm one-point measurement targets responds, referring to
Fig. 2.
Input the parameter of electromagnetic survey system dispatch coil, square emitter coil 1m*1m, emission current 6A, rectangular reception
Coil 0.5m*0.5m, with the concentric coplanar placement of transmitting coil.
When time domain electromagnetic method inverting buried target, wait for that inverted parameters are more, and dipole strength is in early late period magnitude difference
Greatly, it needs to reinforce ability of searching optimum when therefore carrying out inverting using differential evolution (DE) algorithm, once navigate to optimal solution
Position Approximate, and need to reinforce local search ability.And global search and local search ability are contradictory.The friendship of original algorithm
Fork probability CR is that constant starts to be easy to cause Premature Convergence, if CR values are too small, late if CR values are excessive just
Local search ability is not good enough.Therefore a crossover probability factor is reconfigured
As shown in figure 3, when just starting search, CR is smaller and is kept for a period of time, ensures the diversity and the overall situation of population
Search capability;Then it is transitioned into greatly by small, finally slowly ensures late convergence and local search ability close to 1.
The x of setting target, y-coordinate range [0,2], z coordinate range [- 2,0], the inclination angle α, β range [0,180], it is three-dimensional even
Extremely sub- strength range [10-1, 102], first inverting is carried out using improved DE algorithms, obtains more accurately inversion result,
Improved DE algorithms and tradition DE algorithm inversion results are compared, as shown in table 1, convergence curve such as Fig. 4 of two methods
It is shown.
The inversion result that table 1 improves DE and tradition DE compares
Above-mentioned more accurately inversion result substitution Levenberg-Marquardt (LM) algorithm is obtained into final inverting
As a result, as shown in table 2, the convergence curve of three kinds of inversion algorithms is as shown in figure 5, DE-LM joint inversion algorithmic statements are most fast, accidentally
It is poor minimum.The corresponding dipole strength figure of three kinds of inversion algorithms is as shown in fig. 6, obtain first of DE-LM joint inversion algorithms
Dipole strength is more than second and third dipole strength, and second and third dipole strength is roughly equal, closest to steel drum
Dipole model can reflect tubbiness clarification of objective, and late difference becomes second and third dipole of DE algorithm invertings
Greatly, three dipoles of LM algorithms inverting can not correctly reflect the tubbiness feature of target;First is classified as survey area actual measurement sound in Fig. 7
It answers, second is classified as the survey area inversion chart (being followed successively by LM, DE, DE-LM algorithm from top to bottom) of the inversion algorithm of three kinds of algorithms, third
It is classified as the above two residual plot, it can be seen that the DE-LM joint inversions arithmetic result that inverting proposes is responded closest to actual measurement, accidentally
It is poor minimum.
The inversion result of 2 three kinds of algorithms of table compares
The three-dimensional doublet intensity of final inversion result is subjected to parametric synthesis, is obtained about clarification of objective information
Size, Decay, Symmetry, Ratio, wherein
Size indicates target sizes,
t1Indicate the central instant of first time window;
Decay indicates target attenuation rate,
tnFor the central instant of late period sampling time window.
Symmetry indicates target symmetry,
Ratio indicates mesh parameter-ratio,
According to above-mentioned formula, the parameter for calculating 20*10*10 (cm) steel drum is Size:78.99 Decay:0.0247,
Symmetry:0.0109, Ratio 2.56.
Parameter is analyzed according to the above-mentioned result being calculated, Size 78.99, illustrates that target is a larger object
Body;Decay is 0.0247, illustrates that target decaying itself is very fast, conductivity is smaller;Symmetry is 0.0109, illustrates that target is
A axisymmetric body;Ratio is 2.56, illustrates that target is a shaped object.Thus, the present invention's is combined based on DE-LM
The buried target recognition methods of inverting can react the property of buried target itself well.
So far, attached drawing is had been combined the present embodiment is described in detail.According to above description, those skilled in the art
There should be clear understanding to the buried target recognition methods the present invention is based on joint inversion.In practical applications, the invention
As accurate inverting buried target information and it can judge the method for target signature.
It should be noted that in attached drawing or specification text, the realization method for not being painted or describing is affiliated technology
Form known to a person of ordinary skill in the art, is not described in detail in field.In addition, the above-mentioned definition to each element and method is simultaneously
It is not limited only to various concrete structures, shape or the mode mentioned in embodiment, those of ordinary skill in the art can carry out letter to it
It singly changes or replaces, such as:
Size can be replaced with target sizes or target size;Decay can be replaced with target attenuation rate;
Symmetry can be replaced with target symmetry;Ratio can be replaced with target axial ratio.
It should also be noted that, the demonstration of the parameter comprising particular value can be provided herein, but these parameters are without definite etc.
In corresponding value, but analog value can be similar in acceptable error margin or design constraint.The side mentioned in embodiment
Only it is the direction of refer to the attached drawing to term, such as "upper", "lower", "front", "rear", "left", "right" etc., is not used for limiting this
The protection domain of invention.In addition, unless specifically described or the step of must sequentially occur, the sequences of above-mentioned steps there is no restriction in
It is listed above, and can change or rearrange according to required design.And above-described embodiment can be based on design and reliability
Consider, the collocation that is mixed with each other is used using or with other embodiment mix and match, i.e., the technical characteristic in different embodiments can be with
Freely form more embodiments.
In conclusion the present invention provides a kind of buried target recognition methods based on joint inversion.The present invention can be
Accurate inversion result is obtained under the premise of not needing prior information, does not need the expression formula extraction of fit object dipole curve
Parameter, calculation amount is small, can promptly determine the property of buried target itself.
Algorithm and display be not inherently related to any certain computer, virtual system or miscellaneous equipment provided herein.
Various general-purpose systems can also be used together with teaching based on this.As described above, it constructs required by this kind of system
Structure be obvious.In addition, the present invention is not also directed to any certain programmed language.It should be understood that can utilize various
Programming language realizes the content of invention described herein, and the description done above to language-specific is to disclose this hair
Bright preferred forms.
Particular embodiments described above has carried out further in detail the purpose of the present invention, technical solution and advantageous effect
It describes in detail bright, it should be understood that the above is only a specific embodiment of the present invention, is not intended to restrict the invention, it is all
Within the spirit and principles in the present invention, any modification, equivalent substitution, improvement and etc. done should be included in the guarantor of the present invention
Within the scope of shield.
Claims (9)
1. a kind of buried target recognition methods based on joint inversion comprising following steps:
Step 1: establishing observation coordinate system near abnormal area, the coordinate of transmitting coil and receiving coil, one-point measurement are recorded
Obtain the survey area response of secondary field;
Step 2: parameter, observation coordinate and the observed responses of input electromagnetic survey system dispatch coil;
Step 3: carrying out first inverting using the first optimization algorithm, inversion result is obtained;
It is solved Step 4: the inversion result that step 3 obtains is input to the second optimization algorithm, obtains final inverting knot
Fruit;
Step 5: the final inversion result obtained according to step 4, object to be measured is identified into row information.
2. buried target recognition methods according to claim 1, wherein first optimization algorithm is:Improved difference
Evolution DE algorithms, genetic algorithm, simulated annealing, tabu search algorithm, particle cluster algorithm or ant group algorithm.
3. buried target recognition methods according to claim 2, wherein second optimization algorithm is:Levenberg-
MarquardtLM algorithms, Newton's algorithm or conjugate gradient algorithms.
4. buried target recognition methods according to claim 3, wherein the parameter of the dispatch coil includes:Emission lines
Enclose the position relationship of size, emission current size, receiving coil size, transmitting coil and receiving coil.
5. buried target recognition methods according to claim 3, wherein the crossover probability of improved differential evolution DE algorithms
Factor expression is:
Wherein, G is the current iteration number of differential evolution algorithm, and Gm is the maximum iteration of differential evolution algorithm.
6. buried target recognition methods according to claim 3, wherein the packet in the final inversion result
It includes:The three-dimensional coordinate of buried target, inclination angle, three-dimensional doublet intensity.
7. buried target recognition methods according to claim 6, wherein step 5 includes following sub-step:
S1, three-dimensional doublet intensity is subjected to parametric synthesis, obtains the characteristic information about buried target;
The characteristic information comprehensive descision buried target that S2, basis obtain.
8. buried target recognition methods according to claim 7, wherein the characteristic information includes:Size, attenuation rate,
Symmetry, axis ratio.
9. buried target recognition methods according to claim 8, wherein
The size of buried target is
t1Indicate the central instant of first time window;
The attenuation rate of buried target is
tnFor the central instant of late period sampling time window;
The symmetry of buried target is
s.t{p,q}∈{1,2,3};The number of window when n is.
The axis ratio of buried target is
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810150310.XA CN108802834B (en) | 2018-02-13 | 2018-02-13 | Underground target identification method based on joint inversion |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810150310.XA CN108802834B (en) | 2018-02-13 | 2018-02-13 | Underground target identification method based on joint inversion |
Publications (2)
Publication Number | Publication Date |
---|---|
CN108802834A true CN108802834A (en) | 2018-11-13 |
CN108802834B CN108802834B (en) | 2020-12-22 |
Family
ID=64094676
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810150310.XA Active CN108802834B (en) | 2018-02-13 | 2018-02-13 | Underground target identification method based on joint inversion |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN108802834B (en) |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110007357A (en) * | 2019-05-16 | 2019-07-12 | 核工业航测遥感中心 | A kind of aviation TEM and aviation MT joint inversion method |
CN110531429A (en) * | 2019-08-02 | 2019-12-03 | 中国科学院电子学研究所 | A kind of time-domain electromagnetic data object inversion method based on supervision descent method |
CN112130215A (en) * | 2019-06-24 | 2020-12-25 | 中国石油天然气集团有限公司 | Electromagnetic exploration data processing method and device |
CN112666612A (en) * | 2020-11-02 | 2021-04-16 | 中国铁路设计集团有限公司 | Magnetotelluric two-dimensional inversion method based on tabu search |
CN114859421A (en) * | 2021-02-03 | 2022-08-05 | 中国科学院声学研究所 | Underwater buried target identification method based on multi-parameter simultaneous inversion |
CN117270072A (en) * | 2023-09-19 | 2023-12-22 | 云南大学 | Gravity magnetic potential field imaging inversion method and system based on improved differential evolution algorithm |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2001071387A2 (en) * | 2000-03-22 | 2001-09-27 | The Johns Hopkins University | Electromagnetic target discriminator sensor system and method for detecting and identifying metal targets |
CN102426393A (en) * | 2011-11-16 | 2012-04-25 | 中国地质大学(北京) | Electric prospecting method and device |
CN104280782A (en) * | 2013-07-12 | 2015-01-14 | 中国石油天然气集团公司 | One-dimensional joint inversion method for time-frequency electromagnetic data and magnetotelluric data |
CN104375195A (en) * | 2013-08-15 | 2015-02-25 | 中国石油天然气集团公司 | Time-frequency electromagnetic multi-source multi-component three-dimensional joint inversion method |
CN105589108A (en) * | 2015-12-14 | 2016-05-18 | 中国科学院电子学研究所 | Rapid three-dimensional inversion method for transient electromagnetism based on different constraint conditions |
CN107305257A (en) * | 2016-04-21 | 2017-10-31 | 新疆维吾尔自治区煤炭科学研究所 | High Density Resistivity and transient electromagnetic method joint inversion technology |
-
2018
- 2018-02-13 CN CN201810150310.XA patent/CN108802834B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2001071387A2 (en) * | 2000-03-22 | 2001-09-27 | The Johns Hopkins University | Electromagnetic target discriminator sensor system and method for detecting and identifying metal targets |
CN102426393A (en) * | 2011-11-16 | 2012-04-25 | 中国地质大学(北京) | Electric prospecting method and device |
CN104280782A (en) * | 2013-07-12 | 2015-01-14 | 中国石油天然气集团公司 | One-dimensional joint inversion method for time-frequency electromagnetic data and magnetotelluric data |
CN104375195A (en) * | 2013-08-15 | 2015-02-25 | 中国石油天然气集团公司 | Time-frequency electromagnetic multi-source multi-component three-dimensional joint inversion method |
CN105589108A (en) * | 2015-12-14 | 2016-05-18 | 中国科学院电子学研究所 | Rapid three-dimensional inversion method for transient electromagnetism based on different constraint conditions |
CN107305257A (en) * | 2016-04-21 | 2017-10-31 | 新疆维吾尔自治区煤炭科学研究所 | High Density Resistivity and transient electromagnetic method joint inversion technology |
Non-Patent Citations (1)
Title |
---|
李雅德 等: "基于时间域电磁系统的近地表小目标识别", 《仪器仪表学报》 * |
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110007357A (en) * | 2019-05-16 | 2019-07-12 | 核工业航测遥感中心 | A kind of aviation TEM and aviation MT joint inversion method |
CN112130215A (en) * | 2019-06-24 | 2020-12-25 | 中国石油天然气集团有限公司 | Electromagnetic exploration data processing method and device |
CN112130215B (en) * | 2019-06-24 | 2024-05-28 | 中国石油天然气集团有限公司 | Electromagnetic prospecting data processing method and device |
CN110531429A (en) * | 2019-08-02 | 2019-12-03 | 中国科学院电子学研究所 | A kind of time-domain electromagnetic data object inversion method based on supervision descent method |
CN112666612A (en) * | 2020-11-02 | 2021-04-16 | 中国铁路设计集团有限公司 | Magnetotelluric two-dimensional inversion method based on tabu search |
CN114859421A (en) * | 2021-02-03 | 2022-08-05 | 中国科学院声学研究所 | Underwater buried target identification method based on multi-parameter simultaneous inversion |
CN114859421B (en) * | 2021-02-03 | 2024-05-31 | 中国科学院声学研究所 | Underwater buried target identification method based on multi-parameter simultaneous inversion |
CN117270072A (en) * | 2023-09-19 | 2023-12-22 | 云南大学 | Gravity magnetic potential field imaging inversion method and system based on improved differential evolution algorithm |
CN117270072B (en) * | 2023-09-19 | 2024-04-19 | 云南大学 | Gravity magnetic potential field imaging inversion method and system based on improved differential evolution algorithm |
Also Published As
Publication number | Publication date |
---|---|
CN108802834B (en) | 2020-12-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108802834A (en) | A kind of buried target recognition methods based on joint inversion | |
Kurth et al. | Electron densities inferred from plasma wave spectra obtained by the Waves instrument on Van Allen Probes | |
US20200326388A1 (en) | Method for Analyzing Magnetic Detection Blind Zone | |
US8633699B2 (en) | Techniques for determining physical properties of underground structures using lightning | |
CN106022339B (en) | A kind of extracting method of Reclaimed Land shallow embedding underground pipe depth | |
CN110007357B (en) | Aviation TEM and aviation MT joint inversion method | |
CN105759316B (en) | A kind of method and apparatus of rectangular loop source transient electromagnetic detecting | |
CN103561380A (en) | Location fingerprint positioning method and device | |
CN107085240A (en) | A kind of side slope magnetic fluid detection system and method | |
CN109541695A (en) | Artificial field source frequency domain electric-force gradient far-zone apparent resistivity fast imaging method | |
WO2021036780A1 (en) | Three-dimensional collection method and apparatus for magnetotelluric data, and terminal device | |
Deng et al. | Integrated detection of a complex underground water supply pipeline system in an old urban community in China | |
Wu et al. | Deep gold exploration with SQUID TEM in the Qingchengzi Orefield, eastern Liaoning, Northeast China | |
CN108761540B (en) | A kind of frequency domain natural electric field three-dimensional exploitation method | |
CN108415081B (en) | Method for transient electromagnetic detection of terrestrial Japanese heritage chemical warfare | |
CN109752762A (en) | Single-shot receives observation device transient electric field data more and moves bearing calibration and device | |
US8294466B2 (en) | Scaled plots of electromagnetic data | |
CN104793268B (en) | The blind depth measurement method and device of a kind of transient electromagnetic detecting | |
CN103376443A (en) | Ground penetrating radar terrestrial interference detecting and fast eliminating method | |
Saracco et al. | Multiscale tomography of buried magnetic structures: its use in the localization and characterization of archaeological structures | |
Du et al. | Magnetic field indoor positioning system based on automatic spatial-segmentation strategy | |
Goddard et al. | Detection and location of underground cables using magnetic field measurements | |
CN105550442B (en) | Data processing and D integral pin-fin tube method based on the transformation of transient electrical magnetic moment | |
CN110531429A (en) | A kind of time-domain electromagnetic data object inversion method based on supervision descent method | |
CN110109184A (en) | A kind of passive field source class three-dimensional electric field exploitation method based on more days heights |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |