CN108573224A  A kind of Bridge Structural Damage localization method of mobile reconstruct principal component using singlesensor information  Google Patents
A kind of Bridge Structural Damage localization method of mobile reconstruct principal component using singlesensor information Download PDFInfo
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 CN108573224A CN108573224A CN201810293223.XA CN201810293223A CN108573224A CN 108573224 A CN108573224 A CN 108573224A CN 201810293223 A CN201810293223 A CN 201810293223A CN 108573224 A CN108573224 A CN 108573224A
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 G—PHYSICS
 G06—COMPUTING; CALCULATING; COUNTING
 G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
 G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
 G06K9/00496—Recognising patterns in signals and combinations thereof
 G06K9/00536—Classification; Matching
 G06K9/00543—Classification; Matching by matching peak patterns

 G—PHYSICS
 G06—COMPUTING; CALCULATING; 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
 G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, KarhunenLoeve, transforms
 G06F17/141—Discrete Fourier transforms

 G—PHYSICS
 G06—COMPUTING; CALCULATING; COUNTING
 G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
 G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
 G06K9/00496—Recognising patterns in signals and combinations thereof
 G06K9/00536—Classification; Matching
 G06K9/0055—Classification; Matching by matching signal segments

 G—PHYSICS
 G06—COMPUTING; CALCULATING; COUNTING
 G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
 G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
 G06K9/62—Methods or arrangements for recognition using electronic means
 G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
 G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
 G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
Abstract
The invention discloses a kind of Bridge Structural Damage localization methods of the mobile reconstruct principal component using singlesensor information, and steps are as follows：S1, one acceleration transducer is installed in beam bridge any position；S2, acceleration responsive of the vehicular load by beam bridge when is measured, the acceleration signal of measuring point where obtaining_{x(t)}；S3, traveling time window is defined；S4, to time series x in window_{i}(n) matrix A is reconstructed with time delay method_{i}；S5, to matrix A_{i}Principal component analysis calculates, and takes feature value vector V_{i}Element maximum value, be defined as RMPCA；S6, traveling time window obtain reconstructing mobile principal component damage criterion time series_{RMPCA(i)}；S7, pass through damage characteristic figureofmerit_{RMPCA}Layingout curve damages.This method need to only use single sensing data, and be not necessarily to intact bridge lossless data, and the damage position of bridge can be accurately positioned, reduce the quantity and cost of sensor, overcome current bridge lossless data it is incomplete in the case of can not detect the problem of damage.
Description
Technical field
The present invention relates to lossless structure detection technique fields, and in particular to a kind of mobile reconstruct using singlesensor information
The Bridge Structural Damage localization method of principal component.
Background technology
Civil engineering structure plays an important role in the development of national economy, is to have significant impact to national economy
Infrastructure.Civil engineering structure can lead to structural failure due to being corroded by environment, harmful substance.Bridge build and
During use, when the magnitude of traffic flow increases sharply, structure, which is in the military service of continuous excess load, may also lead to fatigue rupture.China
Medium and small span bridge, the overwhelming majority is beam type bridge, and as China's economy develops rapidly, quite a few this kind of bridge makes
It is on active service with serious overload in the process, bridge structure each section is caused just to generate different degrees of damage before reaching design period
And deterioration.Therefore, it is very necessary to carry out monitoring structural health conditions to bridge.In monitoring structural health conditions field, bridge in order to obtain
Girder construction responds, and various kinds of sensors is installed generally on bridge and carries out data acquisition, then based on different damage identification theories
Go out corresponding damage characteristic from different types of extracting data, achievees the purpose that the damage of bridge is diagnosed and positioned.
Traditional bridge structural health monitoring and nondestructive tests system needs the initial shape of a large amount of sensor and bridge
State complete data.Bridge structural health monitoring and nondestructive tests system both domestic and external installs hundreds and thousands of a sensors at present, no
It is only costly, it also causes " magnanimity junk data ".In addition, most of traditional power fingerprint methods are required for being based on original number
According to, i.e., structure nondestructive state or rear original state is built up, and actually this point also is difficult to accomplish in engineering, data are incomplete
It is relatively common engineering problem.
The exploitation of bridge structural health monitoring and damage identification technique is at present still in the basic exploratory stage, apart from work
Journey practice still has a certain distance, and wherein main problem is：The sensor of installation is excessive, costly, exists and is difficult to locate
The mass data of reason；And data are incomplete, many bridges have built up and have come into operation, and lack lossless data as benchmark shape
State data are compared.Based on abovementioned background, urgently propose that one kind can install a small number of sensors and be disobeyed on bridge at present
Dynamic response, analysis response signal, the Gernral Checkup for carrying out bridge and the damage reason location of bridge are measured by bridge lossless data
Method, to reduce the usage amount of sensor, the problems such as it is excessive to solve sensor, costly, and data are incomplete.
Invention content
The purpose of the present invention is to solve drawbacks described above in the prior art, provide a kind of using singlesensor information
The Bridge Structural Damage localization method of mobile reconstruct principal component.
The purpose of the present invention can be reached by adopting the following technical scheme that：
A method of carrying out beam type bridge structure damage reason location, institute using the mobile reconstruct principal component of singlesensor information
The method of stating includes:
S1, acceleration transducer a is installed in any one position on beam bridge, and installation direction is directly in bridge floor direction；
S2, acceleration responsive when vehicular load at the uniform velocity passes through beam bridge is measured, obtains the acceleration letter of acceleration transducer a
Number_{x(t)}；
S3, traveling time window is defined, intercepts measured individual signals and obtains signal x in window_{i}(n), n=1,
2 ..., L, L are moving window length, and i is the beansand bullets shooter of window movement, the computational methods such as formula (1) of L：
Wherein, f_{1}For beam bridge fundamental frequency, f_{s}For sample frequency.
S4, to time series x in window_{i}(n) matrix A is reconstructed with time delay method_{i}。
Q is reconstruct matrix column number in formula, and value is：
Wherein, f^{*}For bandwidth limit frequency, i.e., in the spectrogram of signal x (t), it is more than f^{*}There is no power is notable in frequency domain
Frequency range.
S5, eigenvalue matrix S is obtained to the matrix principal component analysis calculating (PCA) in formula (2)
PCA(A_{i})=[U_{i},S_{i},V_{i}] (4)
Wherein, U_{i}For main component matrix, S_{i}To correspond to matrix U_{i}Contribution rate vector, V_{i}To correspond to U_{i}Characteristic value to
Amount, V_{i}In element arrange from big to small.Take feature value vector V_{i}Maximum value, i.e. V_{i}First element is that damage is special in window
Sign amount, is defined as RMPCA：
RMPCA (i)=V_{i}(1) (5)
S6, traveling time window, moving step length are Δ t since the t=0 on the time shaft of measured signal, and Δ t is signal
Sampling time interval, obtain reconstructing mobile principal component damage criterion time series RMPCA (i), i=1,2 ..., NL；
S7, it is damaged by damage characteristic figureofmerit RMPCA layingout curves.
Further, the step S7, by damage characteristic figureofmerit RMPCA layingout curves damage process it is as follows：
S701, damage characteristic figureofmerit RMPCA curves are drawn according to the time series of damage characteristic figureofmerit RMPCA；
S702, upon displacement between window when being moved to vehicle just past beam bridge damage position, damage characteristic figureofmerit
There is peak value in RMPCA curves, determine vehicle by damage by the peakpeak position of damage characteristic figureofmerit RMPCA curves
At the time of position.
S703, multiplied at the time of vehicle passes through damage position with car speed, i.e., time shaft be converted into spatial position axis,
So that it is determined that damage position.
Further, the beam bridge fundamental frequency f_{1}With the bandwidth limit frequency f^{*}Pass through the acceleration signal x to measuring
(t) fft analysis acquisition is carried out.
The present invention has the following advantages and effects with respect to the prior art：
1) present invention only need to use single sensing data, can position beam bridge damage position, reduce the number of sensor
Amount and cost.
2) present invention is compared without the data of the nondestructive state of structure as benchmark, and the damage that can carry out bridge is fixed
Position, the problem of damage must could be detected according to lossless data by overcoming structure.
3) method proposed by the present invention, it is easy to operate, it calculates fast, Bridge Structural Damage locating effect is apparent.
Description of the drawings
Fig. 1 is the method flow diagram for carrying out beam type bridge structure damage reason location disclosed in the present invention using singlesensor；
Fig. 2 is beam type beam bridge model schematic diagram in the embodiment of the present invention；
Fig. 3 is the acceleration signal measured in the embodiment of the present invention and moving window schematic diagram；
Fig. 4 is the spectrogram of institute's acceleration signals in the embodiment of the present invention；
The curve graph of index RMPCA when Fig. 5 is beam bridge damage 10% in the embodiment of the present invention；
The curve graph of index RMPCA when Fig. 6 is beam bridge damage 30% in the embodiment of the present invention.
Specific implementation mode
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
The every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
Embodiment
As shown in FIG. 1, FIG. 1 is the process step figure of the single sensor, method of beam bridge damage reason location, used in embodiment
Truss bridge model schematic such as Fig. 2.Model beam length l is 20m, sample frequency 200Hz, is damaged at the 2/5 of beam length.It is specific real
It is as follows to apply process：
S1, acceleration transducer a is installed in any position on beam bridge, and installation direction is perpendicular to bridge floor direction, such as Fig. 2 institutes
Show in embodiment, sensor mounting location is at the 1/4 of beam length.
S2, its acceleration responsive when vehicular load passes through beam bridge is measured, obtains the measuring point acceleration letter of acceleration transducer a
Number x (t), is illustrated in figure 3 the signal measured by sensor, and signal length N is 4000.
S3, traveling time window is defined, intercepts measured individual signals x_{i}(n), n=1,2 ..., L, wherein L are to move
Dynamic length of window, the computational methods such as formula (1) of L：
Wherein, f_{1}For beam bridge fundamental frequency, f_{s}For sample frequency.
Fft analysis is carried out to the signal measured in S2 first, obtains beam bridge fundamental frequency f_{1}.After being illustrated in figure 4 fft analysis
Spectrogram can obtain fundamental frequency f from figure_{1}For 1.123Hz.Further according to sample frequency f_{s}, it is L=200/ that length of window, which is calculated,
1.123=178.09, rounding 178.
S4, to time series x in window_{i}(n) matrix A is reconstructed with time delay method_{i}。
Q is reconstruct matrix column number in formula, and value is：
Wherein,_{f*}For bandwidth limit frequency, i.e., in the spectrogram of signal x (t), it is more than f^{*}There is no power is notable in frequency domain
Frequency range.Bandwidth limit frequency f^{*}For 10.25Hz, further according to sample frequency f_{s}, it is q=200/10.25 that matrix columns, which is calculated,
=19.51, rounding 19.
S5, eigenvalue matrix S is obtained to the matrix principal component analysis calculating (PCA) in formula (2)
PCA(A_{i})=[U_{i},S_{i},V_{i}] (4)
Wherein, U_{i}For main component matrix, S_{i}To correspond to matrix U_{i}Contribution rate vector, V_{i}To correspond to U_{i}Characteristic value to
Amount, V_{i}In element arrange from big to small.Take feature value vector V_{i}Maximum value, i.e. first element is damage characteristic in window
Amount, is defined as RMPCA：
RMPCA (i)=V_{i}(1) (5)
S6, on the time shaft of measured signal since the t=0 traveling time window, as shown in figure 3, moving step length is Δ
T, Δ t are the sampling time interval of signal, obtain reconstructing mobile principal component damage criterion time series RMPCA (i), i=1,
2,...,3822；
S7, it is damaged by damage characteristic figureofmerit RMPCA layingout curves.
The step detailed process is as follows：
S701, damage characteristic figureofmerit RMPCA curves are drawn according to the time series of damage characteristic figureofmerit RMPCA；
S702, upon displacement between window when being moved to vehicle just past beam bridge damage position, damage characteristic figureofmerit
There is peak value in RMPCA curves, determine vehicle by damage by the peakpeak position of damage characteristic figureofmerit RMPCA curves
At the time of position.
S703, multiplied at the time of vehicle passes through damage position with car speed, i.e., time shaft be converted into spatial position axis,
So that it is determined that damage position.
Such as the RMPCA curves that Fig. 5 is beam bridge damage 10%, Fig. 6 is the RMPCA curves of beam bridge damage 30%, from Figures 5 and 6
Peak of curve judges that beam bridge damage position is 0.4, i.e., at the 2/5 of beam length, the damage of bridge has been accurately positioned.
In conclusion the method for beam type bridge structure damage reason location disclosed in the embodiment is only using mounted on mobile vehicle
The single sensor on beam type bridge under load action, and the data without nondestructive state compare, and just can be passed according to single
The reconstruct of sensor institute acceleration signals moves principal component analysis to diagnose and position bridge damnification.
The above embodiment is a preferred embodiment of the present invention, but embodiments of the present invention are not by abovedescribed embodiment
Limitation, it is other it is any without departing from the spirit and principles of the present invention made by changes, modifications, substitutions, combinations, simplifications,
Equivalent substitute mode is should be, is included within the scope of the present invention.
Claims (3)
1. a kind of Bridge Structural Damage localization method of mobile reconstruct principal component using singlesensor information, which is characterized in that
Steps are as follows for the Bridge Structural Damage localization method:
S1, acceleration transducer a is installed in any one position on beam bridge, and installation direction is directly in bridge floor direction；
S2, acceleration responsive when vehicular load at the uniform velocity passes through beam bridge is measured, obtains the acceleration signal x of acceleration transducer a
(t)；
S3, traveling time window is defined, intercepts measured individual signals and obtains signal x in window_{i}(n), n=1,2 ..., L,
Wherein, L is moving window length, and i is the beansand bullets shooter of window movement, the computational methods such as formula (1) of moving window length L：
Wherein, f_{1}For beam bridge fundamental frequency, f_{s}For sample frequency；
S4, to time series x in window_{i}(n) matrix A is reconstructed with time delay method_{i}：
Q is reconstruct matrix column number in formula, and value is：
Wherein, f^{*}For bandwidth limit frequency, i.e., it is more than f in the spectrogram of signal x (t)^{*}The significant frequency of power is not present in frequency domain
Section；
S5, eigenvalue matrix S is calculated to obtain to the matrix principal component analysis in formula (2)
PCA(A_{i})=[U_{i},S_{i},V_{i}] (4)
Wherein, U_{i}For main component matrix, S_{i}To correspond to principal component matrix U_{i}Contribution rate vector, V_{i}To correspond to principal component matrix
U_{i}Feature value vector, V_{i}Middle element takes feature value vector V according to arranging from big to small_{i}Maximum value, i.e. V_{i}First element
For signature of damage in window, it is defined as RMPCA：
RMPCA (i)=V_{i}(1) (5)；
S6, traveling time window, moving step length are Δ t since the t=0 on the time shaft of measured signal, and Δ t is adopting for signal
Sample time interval obtains reconstructing mobile principal component damage criterion time series RMPCA (i), i=1,2 ..., NL；
S7, it is damaged by damage characteristic figureofmerit RMPCA layingout curves.
2. a kind of mobile reconstruct principal component using singlesensor information according to claim 1 carries out beam type bridge structure
The method of damage reason location, which is characterized in that the step S7, pass through what damage characteristic figureofmerit RMPCA layingout curves damaged
Process is as follows：
S701, damage characteristic figureofmerit RMPCA curves are drawn according to the time series of damage characteristic figureofmerit RMPCA；
S702, upon displacement between window when being moved to vehicle just past beam bridge damage position, damage characteristic figureofmerit RMPCA is bent
There is peak value in line, determines vehicle by damage position by the peakpeak position of damage characteristic figureofmerit RMPCA curves
Moment；
S703, multiplied at the time of vehicle passes through damage position with car speed, i.e., time shaft is converted into spatial position axis, to
Determine damage position.
3. a kind of mobile reconstruct principal component using singlesensor information according to claim 1 carries out beam type bridge structure
The method of damage reason location, which is characterized in that
The beam bridge fundamental frequency f_{1}With the bandwidth limit frequency f^{*}By carrying out FFT points to the acceleration signal x (t) measured
Analysis obtains.
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Cited By (7)
Publication number  Priority date  Publication date  Assignee  Title 

CN109406076A (en) *  20181119  20190301  暨南大学  A method of beam bridge structure damage reason location is carried out using the mobile principal component of displacement sensor array output 
CN109406075A (en) *  20181119  20190301  暨南大学  A kind of beam bridge structure damage positioning method of the mobile first principal component using singlesensor information 
CN109443672A (en) *  20181119  20190308  暨南大学  A kind of beam bridge structure damage positioning method of the mobile the First Eigenvalue curvature using singlesensor information 
CN109684970A (en) *  20181218  20190426  暨南大学  A kind of length of window of the mobile principal component analysis of structural dynamic response determines method 
CN109839440A (en) *  20190320  20190604  合肥工业大学  A kind of bridge damnification localization method based on standing vehicle testing 
CN110657882A (en) *  20190923  20200107  暨南大学  Bridge realtime safety state monitoring method utilizing singlemeasuringpoint response 
CN110954154A (en) *  20191129  20200403  暨南大学  Bridge damage positioning method based on mobile sensing and filtering integrated system 
Citations (3)
Publication number  Priority date  Publication date  Assignee  Title 

CN103971018A (en) *  20140523  20140806  福州大学  Method for node rigidity prediction based on vibration measurement 
CN104331595A (en) *  20140904  20150204  天津大学  Moving principal component correlation analysis for early warning of damage of bridge 
US20170103507A1 (en) *  20151007  20170413  Fuchs Consulting, Inc.  Timelapse infrared thermography system and method for damage detection in largescale objects 

2018
 20180404 CN CN201810293223.XA patent/CN108573224B/en active Active
Patent Citations (3)
Publication number  Priority date  Publication date  Assignee  Title 

CN103971018A (en) *  20140523  20140806  福州大学  Method for node rigidity prediction based on vibration measurement 
CN104331595A (en) *  20140904  20150204  天津大学  Moving principal component correlation analysis for early warning of damage of bridge 
US20170103507A1 (en) *  20151007  20170413  Fuchs Consulting, Inc.  Timelapse infrared thermography system and method for damage detection in largescale objects 
Cited By (9)
Publication number  Priority date  Publication date  Assignee  Title 

CN109406076A (en) *  20181119  20190301  暨南大学  A method of beam bridge structure damage reason location is carried out using the mobile principal component of displacement sensor array output 
CN109406075A (en) *  20181119  20190301  暨南大学  A kind of beam bridge structure damage positioning method of the mobile first principal component using singlesensor information 
CN109443672A (en) *  20181119  20190308  暨南大学  A kind of beam bridge structure damage positioning method of the mobile the First Eigenvalue curvature using singlesensor information 
CN109684970A (en) *  20181218  20190426  暨南大学  A kind of length of window of the mobile principal component analysis of structural dynamic response determines method 
CN109839440A (en) *  20190320  20190604  合肥工业大学  A kind of bridge damnification localization method based on standing vehicle testing 
CN109839440B (en) *  20190320  20210330  合肥工业大学  Bridge damage positioning method based on static vehicle test 
CN110657882A (en) *  20190923  20200107  暨南大学  Bridge realtime safety state monitoring method utilizing singlemeasuringpoint response 
CN110657882B (en) *  20190923  20210727  暨南大学  Bridge realtime safety state monitoring method utilizing singlemeasuringpoint response 
CN110954154A (en) *  20191129  20200403  暨南大学  Bridge damage positioning method based on mobile sensing and filtering integrated system 
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