CN109992834A - The distinguishing structural mode method of modified blind source separating - Google Patents
The distinguishing structural mode method of modified blind source separating Download PDFInfo
- Publication number
- CN109992834A CN109992834A CN201910162671.0A CN201910162671A CN109992834A CN 109992834 A CN109992834 A CN 109992834A CN 201910162671 A CN201910162671 A CN 201910162671A CN 109992834 A CN109992834 A CN 109992834A
- Authority
- CN
- China
- Prior art keywords
- modal
- mode
- identification
- matrix
- complex
- 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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Software Systems (AREA)
- Databases & Information Systems (AREA)
- Algebra (AREA)
- Computing Systems (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
Abstract
The invention discloses a kind of distinguishing structural mode methods of modified blind source separating.The present invention is primarily based on complex modal theory, increase virtual measuring point using Hilbert transformation, effective expansion rank is carried out to original signal and carrys out creation analysis signal, then whitening processing analyzes signal, asymmetric nonopiate joint approximate diagonalization is carried out to the second order covariance matrix of different delay, obtained hybrid matrix finally extracts modal frequency and damping ratio to single-degree-of-freedom modal response as Mode Shape, to realize the identification to modal parameters.Accuracy of identification of the present invention is higher than common SOBI algorithm and the SOBI algorithm based on orthogonal JAD, it is shown that good performance.
Description
Technical field
The present invention relates to fields, are to be related to the distinguishing structural mode method of modified blind source separating more specifically.
Background technique
Between source signal mutually it is independent or it is uncorrelated be to realize blind source separating (Blind Source Separation is referred to as
BSS basic assumption condition).The essence of model analysis is that the vibratory response in physical coordinates is converted in modal coordinate
Modal response, each coordinate because of modal response is mutually independently and without coupling.It can be seen that BSS is to be based on model analysis
Two kinds of analysis methods of " independence " or " irrelevance ", only BSS is derived from signal processing, and model analysis is derived from structural dynamic
It learns.It is inferred that there are certain corresponding relationships between BSS and model analysis, this is provided to carry out modal idenlification using BSS
Theoretical foundation.
Different from the BSS based on high-order statistic, the BSS based on second-order statistic considers the time structure of signal, will
Replacement of the auto-covariance as non-Gaussian system, reducing BSS and requiring source signal is the harsh conditions of non-Gaussian system, it can be separated
The signal for providing different auto-correlation functions (i.e. different capacity spectrum), is widely applied.Second-order blind identification algorithm
(Second-Order Blind Identification, SOBI) is typically based on second-order statistic BSS method, and joint is close
It is the core of SOBI like diagonalization (Joint Approximate Diagonalization of eigenmatrices, JAD).
JAD generally uses orthogonal joint approximate diagonalization, however the Orthonormality constraints of JAD destroy least square standard, orthogonalization rank
The error of section cannot be corrected in subsequent separation phase, finally affect the performance of Joint diagonalization.
Yeredor etc. proposes least square cost function and obtained a kind of non-orthogonal joint diagonalization algorithm: column are handed over
For update and diagonalization (Alternating Columns Diagonal Centers, ACDC), however the algorithm will alternately more
New two groups of undetermined parameters, therefore convergence rate is slower.It is derived from " Yeredor
A.Non-Orthogonal Joint Diagonalization in the Least-Squares Sense
With Application in Blind Source Separation [J] .IEEE Signal Processing.2002,50
(7): 1545-1553. " (Chinese translation: leaf mostly etc., non-orthogonal joint diagonalization under least square meaning and its in blind source point
Application [J] .IEEE signal processing 2002,50 (7) from: 1545-1553.).
In order to become the optimization of ACDC simply, China etc. proposes asymmetrical least square cost function, obtains
Better three iterative algorithm of performance (Triple iterative algorihm, TIA).Be derived from " Zhang Hua, Feng great Zheng, Nie Weike,
Equal Non-orthogonal joint diagonalization for blind source separation [J] Xian Electronics Science and Technology University journal .2008,35 (1): 27-31. ".
However as Li et al. is pointed out, which does not carry out any constraint to left and right diagonalizable matrix, and it is therefore possible to receive
Hold back singular solution.It is derived from " Li X L, Zhang X D.Nonorthogonal Joint Diagonalization Free of
Degenerate Solution [J] .Signal Processing, IEEE.2007,55 (5): 1803-1814. " (translate by Chinese
Text: Lee X L, X D, Non-orthogonal joint diagonalization [J] the .IEEE signal processing 2007,55 (5) of no degenerate solution: 1803-
1814.)。
In order to improve asymmetric Joint diagonalization convergence speed of the algorithm, and avoid algorithmic statement to singular solution, Zhang Weitao
Deng the non-orthogonal joint diagonalization cost function for proposing a belt restraining item, a kind of quickly asymmetric nonopiate joint pair is obtained
Angling (Nonsymmetric Nonorthogonal Joint Diagonalization, NNJD) algorithm.Be derived from " Zhang Weitao,
Building is followed the mandate of heaven, and asymmetric nonopiate fast joint diagonalization algorithm [J] of Zhang Yanliang automates journal .2010,36 (6): 829-
836.”。
Currently, BSS technology modal parameters identification in using a generally existing problem: can be only applied to reality
Mode situation, when system damping is general damping (complex mode situation), using being restricted.For above-mentioned limitation, have
Research compares AMUSE, SOBI and the ICA (Independent Component Analysis) based on high-order statistic exists
Respective advantage and deficiency in distinguishing structural mode, it is indicated that SOBI method has preferable noise immunity.Be derived from " Kerschen G,
Poncelet F, Golinval J C.Physical Interpretation of Independent Component
Analysis in Structural Dynamics[J].Mechanical Systems and Signal
Processing.2007,21 (4): 1561-1575. (Chinese translation: Peng Selie etc., independent component analysis in Structural Dynamics
Physical interpretation [J] mechanical system and signal processing 2007,21 (4): 1561-1575.).
Poncelet F, Kerschen G, Golinval J C, et al.Output-Only Modal Analysis
Using Blind Source Separation Techniques[J].Mechanical Systems and Signal
Processing.2007,21 (6): (Chinese translation: Peng Selie etc. is carried out pure defeated 2335-2358. using blind source separate technology
Model analysis [J] mechanical system and signal processing 2007,21 (6) out: 2335-2358.).
ZHOU W, Chelidze D.Blind Source Separation Based Vibration Mode
Identification [J] .Mechanical Systems and Signal Processing.2007,21 (8): 3072-
3087. " (Chinese translation: all W, etc., vibration mode identification [J] mechanical system and signal processing 2007 based on blind source separating,
21 (8): 3072-3087).
McNeill is based on SOBI algorithm, proposes blind modal identification (the Blind Modal that can identify complex mode system
Identification, BMID) algorithm, high building structure the experiment proves that BMID algorithm validity.It is derived from " McNeill
S I, Zimmerman D C.A Framework for Blind Modal Identification Using Joint
Approximate Diagonalization [J] .Mechanical Systems and Signal Processing.2008,
22 (7): 1526-1548. " (Chinese translation: McEnery S I, etc. the blind modal idenlification frame based on joint joint approximate diagonalization
[J] mechanical system and signal processing 2008,22 (7): 1526-1548.).
Pay that will is superfine that further steady type R-SOBI algorithm is introduced into distinguishing structural mode, spring-matter of four-degree-of-freedom
The simulation results show of amount system this method has stronger noise immunity.Be derived from " Fu Zhichao, Cheng Wei, Xu Cheng be based on R_
Modal parameters discrimination method [J] the vibration of SOBI and impact .2010,29 (1): 108-112. ".
The prior art has following defects that
1, poor to test environmental suitability.
2, it can be only applied to real mode situation, when system damping is general damping (complex mode situation), using being limited
System.
3, there are accumulated errors and common BSS cannot identify that complex mode is joined by the SOBI based on orthogonal joint approximate diagonalization
Number.
Summary of the invention
The present invention cannot identify the deficiency of Complex Modal Parameter Identification for common blind source separation algorithm, overcome and deposit in the prior art
Deficiency, a kind of distinguishing structural mode method of modified blind source separating is provided.
The distinguishing structural mode method of modified blind source separating of the present invention, is achieved, first by following technical proposals
Based on complex modal theory, increase virtual measuring point using Hilbert transformation, effective expansion rank is carried out to original signal and carrys out creation analysis
Signal, then whitening processing analyzes signal, and it is approximate to carry out asymmetric nonopiate joint to the second order covariance matrix of different delay
Diagonalization, obtained hybrid matrix finally extract modal frequency and damping to single-degree-of-freedom modal response as Mode Shape
Than to realize the identification to modal parameters；
Specific step is as follows:
Complex mode system simulation experiments are carried out, a Three Degree Of Freedom mass-spring system, mass matrix M, resistance are established
Buddhist nun's Matrix C, stiffness matrix K are as follows:
It is available:
Due to CM-1K is not symmetrical matrix, and damping matrix cannot be by natural mode of vibration diagonalization, therefore the system is multiple mould
State system.
In order to evaluate identification of Mode Shape as a result, a kind of broader modal assurance criterion can be defined:
φ in formulaj,The respectively jth rank Mode Shape vector of distinct methods identification,For φjComplex conjugate transposition,
0≤CMACj≤ 1, CMACjCloser to 1, illustrate that the vibration shape vector of two methods identification is closer.Obviously, formula (1) not only can be with
For evaluating real Mode Shape, and the complex mode vibration shape can be evaluated.
Consider free vibration response, is displaced primary condition x (0)=(0,0,0)T, speed primary conditionSample frequency is 10Hz, and preceding 150 seconds response signals that fetch bit moves finally are used as analysis object
ESOBI method carries out blind source separating to the complex mode system.
Compared with prior art, the beneficial effects of the present invention are:
1, accuracy of identification of the present invention is higher than common SOBI algorithm and the SOBI algorithm based on orthogonal JAD, it is shown that good
Performance.
2, the present invention has widened application range of the blind source separate technology in distinguishing structural mode.
Detailed description of the invention
The displacement time-history curves and its PSD of Fig. 1 complex mode system；
The separation signal and its PSD (complex mode) of Fig. 2 SOBI；
Fig. 3 BMID separates signal and its PSD (complex mode)；
The separation signal and its PSD (complex mode) of Fig. 4 ESOBI；
Fig. 5 steel-frame structure schematic diagram；
The lower six acceleration analysis signals of Fig. 6 pulse excitation and its PSD；
The lower six acceleration analysis signals of Fig. 7 arbitrary excitation and its PSD；
The modal response and its PSD that SOBI is identified under Fig. 8 pulse excitation；
The modal response and its PSD that BMID is identified under Fig. 9 pulse excitation；
The modal response and its PSD that ESOBI is identified under Figure 10 pulse excitation；
The modal response and its PSD that SOBI is identified under Figure 11 arbitrary excitation；
The modal response and its PSD that BMID is identified under Figure 12 arbitrary excitation；
The modal response and its PSD that ESOBI is identified under Figure 13 arbitrary excitation.
Specific embodiment
The present invention is described in further detail below in conjunction with the drawings and specific embodiments.It should be appreciated that described herein
Specific embodiment be only used to explain the present invention, be not intended to limit the present invention.
It is primarily based on complex modal theory, increases virtual measuring point using Hilbert transformation, original signal is effectively expanded
Rank carrys out creation analysis signal, and then whitening processing analyzes signal, carries out to the second order covariance matrix of different delay asymmetric non-
Orthogonal joint approximate diagonalization, obtained hybrid matrix finally extract mode to single-degree-of-freedom modal response as Mode Shape
Frequency and damping ratio, to realize the identification to modal parameters.
Complex mode system simulation experiments are carried out, a Three Degree Of Freedom mass-spring system, mass matrix M, resistance are established
Buddhist nun's Matrix C, stiffness matrix K are as follows:
It is available:
Due to CM-1K is not symmetrical matrix, and damping matrix cannot be by natural mode of vibration diagonalization, therefore the system is multiple mould
State system.
In order to evaluate identification of Mode Shape as a result, a kind of broader modal assurance criterion can be defined:
φ in formulaj,The respectively jth rank Mode Shape vector of distinct methods identification,For φjComplex conjugate transposition,
0≤CMACj≤ 1, CMACjCloser to 1, illustrate that the vibration shape vector of two methods identification is closer.Obviously, formula (1) not only can be with
For evaluating real Mode Shape, and the complex mode vibration shape can be evaluated.
Consider free vibration response, is displaced primary condition x (0)=(0,0,0)T, speed primary conditionSample frequency is 10Hz, and preceding 150 seconds response signals that fetch bit moves are as analysis object, three degree of freedom
Displacement time-histories and its corresponding power spectral density (PSD) it is as shown in Figure 1.
Blind source separating is carried out to the complex mode system using tri- kinds of methods of SOBI, BMID, ESOBI, separating resulting is respectively such as
Shown in Fig. 2~Fig. 4.From separating resulting as can be seen that SOBI method cannot accurately open each rank modal separation, especially third
Rank mode, and the ESOBI method that BMID method and this programme propose can be by each rank modal separation.
The results are shown in Table 1 for two methods of the Modal Parameter Identification of BMID and ESOBI, as can be seen from Table 1: BMID and
Two methods of the modal idenlification precision of ESOBI is all fine, but ESOBI is slightly better than BMID.
The Modal Parameter Identification result of table 1 BMID and ESOBI
Model test is carried out with a steel-frame structure, model is made of 3 girders, 8 secondary beams, 6 root posts, 6 root posts
It is mounted in ground, overall dimensions are 1500mm × 1150mm × 564mm, as shown in Figure 5.The secondary beam of the structure is T shaped steel,
Girder and column are i shaped steel, and Liang Yuzhu, girder and secondary beam are by being bolted.In order to maximize vertical direction (vertically
The direction in face) acceleration signal, reduce torsion mode influence, excitation point a position be selected near the 2nd point in Fig. 5.Six add
1~6 point in Fig. 5 of velocity sensor placement position, measures the acceleration signal of vertical direction, and sensor uses ICP
Acceleration transducer DH131E, vibration signal detecting and analysing system are DH5920N.
The present invention has done two groups of experiments: first group of experiment driving source is the pulse excitation of power hammer, sampling number 1024,
The measuring signal and its power spectral density function (PSD) of six acceleration transducers are as shown in Fig. 6；Second group of experiment driving source
For the gaussian random signal of vibration excitor, sampling number 8192, the measuring signal and its power spectrum of six acceleration transducers
Function (PSD) is spent as shown in fig. 7, the sample frequency of two groups of experiments is 1KHz.Mixed signal PSD can be with from Fig. 6 and Fig. 7
See, first three rank mode can be excited out, and the mode energy after three ranks is smaller, substantially with noise in same grade.
This programme respectively shakes to the structure under pulse excitation and arbitrary excitation using tri- kinds of methods of SOBI, BMID, ESOBI
Dynamic response has carried out modal idenlification.
Modal idenlification is carried out to the vibratory response under pulse excitation effect first.Fig. 8 is before being obtained using SOBI method
Three rank modal responses and its power spectral density function, the time-domain diagram on the left of Fig. 8 can see, and SOBI method can be known substantially
Not Chu system first three rank modal response, but can see from the PSD on the right side of Fig. 8 by there are more in isolated signal
Other frequency signals belong to multi-frequency mixed signal.Fig. 9 is first three the rank modal response obtained using BMID method and its function
Rate spectral density function, is better than the separating resulting of SOBI method by isolated modal response as seen from Figure 9, however still deposits
In more interference signal.Figure 10 is first three rank modal response and its power spectrum of the ESOBI method separation proposed using this chapter
Density function, in terms of the time-domain diagram and PSD of modal response, the interference signal of first three rank modal response has been lacked very much, recognition result
It is better than two methods of SOBI and BMID, it is contemplated that practical structures vibration signal can not completely remove noise, so this programme mentions
The vibratory response of complex mode system can be successfully separated out first three rank modal response by method out.Comparison diagram 8, Fig. 9 and figure
10, other than the amplitude of separation signal is not exactly the same, the modal idenlification precision of ESOBI method is better than SOBI and BMID two
Kind method.The reason of cannot identifying about the mode after three ranks is that these mode energies are lower, is substantially mingled in noise
Together, this point can be seen from Fig. 6.
The hybrid matrix that ESOBI method is calculated is then (right using single mode recognition methods as Mode Shape matrix
Separate signal extraction modal frequency and damping ratio.In order to be carried out to the mode result of tri- kinds of method identifications of SOBI, BMID, ESOBI
It further compares, this programme uses tag system to realize that method (ERA) has carried out modal idenlification, the mould of four kinds of methods simultaneously
State recognition result is as shown in table 2.Wherein CMAC is generalized Modal confidence criterion, CMAC12, CMAC13, CMAC23 in table 2 points
Not Biao Shi ERA and ESOBI, ERA and BMID, ESOBI and the BMID identification vibration shape modal assurance criterion, remaining mode confidence is quasi-
Then be worth and so on.
From table 2 it can be seen that at three aspect of modal frequency, damping ratio and the vibration shape, the recognition result ratio of ESOBI and BMID
SOBI is closer to the identification mode of ERA, and the recognition result of ESOBI method is slightly better than BMID method, illustrates in structural modal
Identification aspect, ESOBI method is best.
Modal idenlification finally is carried out to the vibratory response under arbitrary excitation effect, uses nature first before modal idenlification
Advocate approach (NExT) extracts free damping vibration signal to random response signal.Three kinds of methods (SOBI, BMID and ESOBI) are known
For first three other rank modal response respectively as shown in Figure 11~Figure 13, table 3 is the Modal Parameter Identification result of four kinds of methods.With arteries and veins
Identification conclusion under impulse is encouraged is identical: BMID modal idenlification precision is better than SOBI, and ESOBI accuracy of identification is better than BMID.
2 pulse excitation flowering structure Modal Parameter Identification result of table
3 arbitrary excitation flowering structure Modal Parameter Identification result of table
The above is only a preferred embodiment of the present invention, it is noted that for the common skill of the art
For art personnel, various improvements and modifications may be made without departing from the principle of the present invention, these are improved and profit
Decorations also should be regarded as protection scope of the present invention.
Claims (1)
1. a kind of distinguishing structural mode method of modified blind source separating, characterized in that be primarily based on complex modal theory, apply
Hilbert transformation increases virtual measuring point, carries out effective expansion rank to original signal and carrys out creation analysis signal, then whitening processing is analyzed
Signal carries out asymmetric nonopiate joint approximate diagonalization, obtained hybrid matrix to the second order covariance matrix of different delay
As Mode Shape, modal frequency and damping ratio finally are extracted to single-degree-of-freedom modal response, structural modal is joined to realize
Several identification,
Specific step is as follows:
Complex mode system simulation experiments are carried out, a Three Degree Of Freedom mass-spring system, mass matrix M, damping matrix are established
C, stiffness matrix K is as follows
It is available:
Due to CM-1K is not symmetrical matrix, and damping matrix cannot be by natural mode of vibration diagonalization, therefore the system is complex mode system
System,
In order to evaluate identification of Mode Shape as a result, a kind of broader modal assurance criterion can be defined:
φ in formulaj,The respectively jth rank Mode Shape vector of distinct methods identification,For φjComplex conjugate transposition, 0≤
CMACj≤ 1, CMACjCloser to 1, illustrate that the vibration shape vector of two methods identification is closer, it is clear that formula (1) can not only be used to
Real Mode Shape is evaluated, and the complex mode vibration shape can be evaluated,
Consider free vibration response, is displaced primary condition x (0)=(0,0,0)T, speed primary condition
Sample frequency is 10Hz, and preceding 150 seconds response signals that fetch bit moves finally are used as analysis object
ESOBI method carries out blind source separating to the complex mode system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910162671.0A CN109992834B (en) | 2019-03-05 | 2019-03-05 | Structural modal identification method for improved blind source separation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910162671.0A CN109992834B (en) | 2019-03-05 | 2019-03-05 | Structural modal identification method for improved blind source separation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109992834A true CN109992834A (en) | 2019-07-09 |
| CN109992834B CN109992834B (en) | 2022-09-30 |
Family
ID=67129480
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910162671.0A Active CN109992834B (en) | 2019-03-05 | 2019-03-05 | Structural modal identification method for improved blind source separation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109992834B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112749457A (en) * | 2021-01-22 | 2021-05-04 | 天津大学 | Intelligent damage identification method for jacket type ocean platform |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107357977A (en) * | 2017-06-27 | 2017-11-17 | 华侨大学 | The recognition methods of linear structure operational modal parameter and device based on second-order blind identification |
| CN107729592A (en) * | 2017-08-14 | 2018-02-23 | 西安理工大学 | Traced back the Time variable structure Modal Parameters Identification of track based on broad sense subspace |
| CN109238447A (en) * | 2018-09-12 | 2019-01-18 | 西北工业大学 | A kind of blind source separation method of tether vibration signal |
| CN109376330A (en) * | 2018-08-27 | 2019-02-22 | 大连理工大学 | A kind of non-proportional damping distinguishing structural mode method based on extension Sparse Component Analysis |
-
2019
- 2019-03-05 CN CN201910162671.0A patent/CN109992834B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107357977A (en) * | 2017-06-27 | 2017-11-17 | 华侨大学 | The recognition methods of linear structure operational modal parameter and device based on second-order blind identification |
| CN107729592A (en) * | 2017-08-14 | 2018-02-23 | 西安理工大学 | Traced back the Time variable structure Modal Parameters Identification of track based on broad sense subspace |
| CN109376330A (en) * | 2018-08-27 | 2019-02-22 | 大连理工大学 | A kind of non-proportional damping distinguishing structural mode method based on extension Sparse Component Analysis |
| CN109238447A (en) * | 2018-09-12 | 2019-01-18 | 西北工业大学 | A kind of blind source separation method of tether vibration signal |
Non-Patent Citations (2)
| Title |
|---|
| 刘晓伟等: "基于SONS的结构模态参数识别研究", 《中国机械工程》 * |
| 曹军宏等: "改进型盲源分离在结构模态识别中的应用", 《振动.测试与诊断》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112749457A (en) * | 2021-01-22 | 2021-05-04 | 天津大学 | Intelligent damage identification method for jacket type ocean platform |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109992834B (en) | 2022-09-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104076355B (en) | Tracking before Dim targets detection in strong clutter environment based on dynamic programming | |
| CN105589100B (en) | A kind of microseism hypocentral location and rate pattern Simultaneous Inversion method | |
| CN105759311B (en) | A kind of near real-time earthquake source location positioning method | |
| AU2019429806B2 (en) | Method for evaluating degree of complexity of regional geological structure | |
| CN107132575B (en) | Method based on shear wave polarographic analysis prediction fracture azimuth | |
| CN105138983B (en) | The pedestrian detection method divided based on weighting block model and selective search | |
| CN106646598A (en) | FAST-AIC-algorithm micro-seismic signal collecting method | |
| CN103235286B (en) | High-precision locating method for electric noise sources | |
| CN106250854A (en) | Body gait recognition methods based on micro-Doppler feature and support vector machine | |
| CN104215935A (en) | Weighted decision fusion based radar cannonball target recognition method | |
| CN104765064A (en) | Microseism interference imaging method | |
| CN108072906A (en) | A kind of distribution magnetic detection magnetic target identification method | |
| CN109992834A (en) | The distinguishing structural mode method of modified blind source separating | |
| Tee et al. | Numerical and experimental studies of a substructural identification strategy | |
| CN105632502A (en) | Weighted pairwise constraint metric learning algorithm-based speaker recognition method | |
| US20210350040A1 (en) | Method of physical mode extraction for engineering structure flexibility identification | |
| CN105954796A (en) | Method and apparatus for determining hypocenter position of micro earthquake | |
| CN105445699A (en) | Range measurement method and range measurement system based on non line-of-sight error elimination | |
| CN106353812A (en) | Method of extracting of shear wave velocity of dual-spaced full-wave train logging based on slowness-time | |
| CN103116740A (en) | Method and device for identifying underwater targets | |
| Mróz et al. | Parameter identification of materials and structures | |
| CN106168675A (en) | Borehole microseismic P/S ripple event recognition method and device | |
| CN105890738A (en) | Conflux vortex impact vibration identification method | |
| Ikeda et al. | Smart system identification of super high-rise buildings using limited vibration data during the 2011 Tohoku earthquake | |
| Helmberger et al. | Crustal complexity from regional waveform tomography: Aftershocks of the 1992 Landers earthquake, California |
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 |