CN104165742B - A kind of operational modal analysis experimental technique based on mutual spectral function and device - Google Patents
A kind of operational modal analysis experimental technique based on mutual spectral function and device Download PDFInfo
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Abstract
A kind of operational modal analysis experimental technique based on mutual spectral function, comprises the following steps：1) with elastic threads, beam is hung, in the excitation point chosen, pulse excitation is implemented to beam using steel hammer；2) gather the response signal that reference point and response point produce after pulse excitation；3) bandpass filtering is carried out to collection signal；4) ask for the crosspower spectrum function between reference point and response point, and build the matrix equation that crosspower spectrum function difference sampling instant data is constituted；5) utilize matrix equation to solve coefficient matrix, obtain system pole；6) identification Mode Shape and modal participation factors matrix；7) carry out mode confidence criterion matrix value to calculate, when mode confidence criterion value is within default reasonable interval, obtain the modal parameter of beam.And a kind of operational modal analysis experimental provision based on mutual spectral function is provided.The present invention can reduce proof strength and time, and test efficiency and student learning effect are greatly improved.
Description
Technical field
The present invention relates to operational modal analysis technical field, especially a kind of operational modal analysis experimental technique and device.
Background technology
In the teaching process of the courses such as Engineering Testing Technique, Reformation of Mechanical Vibration, some model analyses are added to test, permissible
Motivate students' interest in learning, the learning initiative of mobilizing students and initiative, the innovation ability of training student, increase substantially
Teaching efficiency.Student can be made to obtain abundant perceptual knowledge by experiment, deepen student to modal parameter concept and its solution
The understanding of method, reduces the difficulty that self-learning process middle school student encounter problems.
Mould measurement is frequently utilized for the extraction of the modal model under actual operating conditions, condition monitoring and analysis, non-linear
The correctness of systematic study, accident analysis and checking FEM (finite element) model.Existing experimental modal analysis system is typically by three part groups
Become：1. excitation system：Make system vibration.2. measuring system：Measure the position on each main portions of experimental subject with sensor
Shifting, speed or acceleration vibration signal.3. analysis system：The pumping signal collecting and response signal are remembered through digital-to-analogue conversion
Record in computer, identify the modal parameter of vibrational system with software system.The basic step of experiment is as follows：1) determine experiment mould
Type, experimental configuration is supported；2) typically with exciting hammer hammering method using excitation experimental configuration, record encourages letter to mode experiment
Number and each measuring point response signal；3) digital processing is carried out to record data, obtain the transmission function of each measuring point, and form transmission
Jacobian matrix；4) enter line parameter identification using model analyses software；5) carry out animation to show.
The operational modal analysis method of modal parameter, the knot of identification is extracted from the vibration response signal of the in-service state of structure
Structure dynamic characteristic, becomes in recent years closer to the real kinetic behavior of structure under actual motion condition than test modal analysis
The active research direction of model analyses field development.Parameter identification method in operational modal analysis can be divided into time domain, frequency domain
With time-frequency domain discrimination method etc., mainly there are time series method, Modal Parameter by Random Decrement (random decrement, RD), environmental excitation
Method, Random Subspace Method, Empirical mode decomposition (empirical mode decomposition, EMD), peak picking method,
Frequency domain decomposition method and Continuous Wavelet Transform etc., existing analysis method many based on pumping signal for zero-mean white noise vacation
If, and every kind of method has certain limitation, the such as more difficult determination of model order of time series method；Natural excitation method method requires
Data sample length, average time are many；The determination of Random Subspace Method model order is more loaded down with trivial details, when measuring point is more, Hankel
Matrix order is very high, easily causes the problem of matrix morbid state；The disadvantage of frequency domain method is that requirement frequency resolution is high；Time-frequency Analysis profit
Response message is less, is a kind of local recognition methodss etc..In order to improve student learning effect, carry out operational modal and divide
Analysis experimental teaching is very necessary, but, have no such experimental provision at present, the operational modal analysis being therefore directed to teaching demand are real
Test method and device urgently to study.
Content of the invention
In order to improve learning effect during Students ' Learning modal analysis technique, the present invention provides one kind to be capable of quickly counting
Calculation, degree of accuracy height, the operational modal based on pulse excitation that there is preferable error control, proof strength and time can be reduced
Analysis experimental technique and device.
The technical solution adopted for the present invention to solve the technical problems is：
A kind of operational modal analysis experimental technique based on mutual spectral function, comprises the following steps：
1) with elastic threads, beam is hung, the end points selecting beam, as excitation point, implements pulse excitation using steel hammer to beam；
Selected distance excitation point is compared near and the larger response measuring point of response signal amplitude is as a reference point；
Each geometric model inserting knot response measuring point in described reference point and the reflection beam vibration shape；
2) gather the response signal that described reference point and response measuring point produce after pulse excitation；
3) bandpass filtering is carried out to collection signal, its passband is structural modal frequency scope interested, to all sound
Passage is answered to add Hanning window；
4) when asking for the crosspower spectrum function between reference point and response measuring point, and building the different sampling of crosspower spectrum function
Carve the matrix equation that data is constituted；
5) utilize described matrix equation to solve coefficient matrix, obtain system pole；
6) identification Mode Shape and modal participation factors matrix；
7) carry out mode confidence criterion matrix value to calculate, if mode confidence criterion matrix value is not in default reasonable interval
Interior, then choose different sampling instant values, return to step 4) rebuild Matrix division, until mode confidence criterion value is pre-
If within reasonable interval, obtain modal parameters.
Further, methods described is further comprising the steps of：8) mode animation is drawn：Show that the mode in each direction of each point is shaken
Type vector, corresponding with response point layout geometric model, just obtain describing the relative amplitude on each response measuring point x, y, z direction
Mode Shape animation.
Further, described step 4) in, respond the cross-correlation between measuring point j and reference point i according to formula (1) computation structure
Function：
In formula, Rij(τ) it is the cross-correlation function responding between measuring point j and reference point i, T is the testing time, xiT () is ginseng
The acceleration responsive signal of examination point, xjT () is the acceleration responsive signal of response measuring point, τ is time interval；
To the cross-correlation function R between structural response measuring point j and reference point iij(τ) sample according to sampling time interval Δ t,
And it is denoted as complex mode form：
C in formularijIt is the constant coefficient related to r order mode state；N is rank number of mode to be identified；Δ t is sampling time interval,
K represents the number of sampling；λrFor system pole；
By system pole λrIt is expressed asξ in formularFor r rank modal damping
Than；ωrFor r order mode state undamped natural frequency of a mechanical system
By Rij(k Δ t) makees periodic extension, and carries out discrete Fourier transform, meets with a response between measuring point j and reference point i
Monolateral cross-spectral density function：
TakeSet up crosspower spectrum Jacobian matrix equation in the value of different sampling start times：
A in formula0, a1... a2N is coefficient；Sij(t0), Sij(t1)…Sij(t4N) for responding between measuring point j and reference point i mutually
Power spectrum function is in t0, t1,…t4NThe value in moment, constitutes compression equation using the covariance matrix of equation group, is somebody's turn to do
The least square solution of compression equation, obtains coefficient a0, a1... a2NValue.
Further, described step 5) in, orderConstruction following equations：
A in formulakFor coefficient, the above formula left side is added by 2N item and forms, and therefore the number of equation group characteristic solution at least should be equal to
2N, therefore k=0,1,2 ... 2N, if above formula is set up, coefficient a0, a1... a2NMeeting following rational fraction orthogonal polynomial is
Poroney polynomial equation, and this multinomial withIt is characterized solution, take a2N=1, obtain：
By the coefficient matrix estimating a0, a1... a2NSubstitution formula (8), tries to achieve the limit of system.
Described step 6) in, crosspower spectrum Jacobian matrix is expressed as system each rank Mode Shape and modal participation factors square
The partial fraction sum of battle array, obtains
In formula, VrFor Mode Shape matrix, LrFor modal participation factors matrix, represent each order mode state in system response
Contribution amount,For the complex-conjugate matrix of Mode Shape matrix,For the complex-conjugate matrix of modal participation factors matrix,For system
The conjugate complex number of limit；
The system pole of identification is substituted into formula (9), tries to achieve by each rank Mode Shape vector ΨrThe Mode Shape matrix constituting
VrAnd its modal participation factors matrix Lr, obtain the overall situation estimation of system mode parameter.
Described step 7) in, mode confidence criterion matrix value is：
Wherein, ΨrFor r rank Mode Shape vector；ΨsFor s rank Mode Shape vector；Ψr *TFor r rank Mode Shape
The conjugate transpose of vector；Ψs *TConjugate transpose for s rank Mode Shape vector.
A kind of operational modal analysis experimental provision based on mutual spectral function, including fixed support, elastic threads, steel hammer, acceleration
Degree sensor, beam, suspension ring, coaxial cable, data acquisition front and operation module analysis center, described beam is hung by elastic threads,
Beam is made to be in free boundary condition, described elastic threads one end and fixed support connect, the other end of described elastic threads is with suspension ring even
Connect, described suspension ring and beam are threaded connection, the acceleration of vibration-time data of each measuring point tested by described acceleration transducer,
Each acceleration transducer is electrically connected with data acquisition front respectively by coaxial cable, data acquisition front with run module analysis
Center electrically connects, and after acceleration transducer collects the response signal under pulse excitation, its incoming data is gathered front end, then passes
To running module analysis center, the vibration response signal data being gathered is imported by data acquisition front and runs module analysis
Center is analyzed processing.
Beneficial effects of the present invention are mainly manifested in：1st, it is capable of quickly calculating, degree of accuracy is high, have preferable error
Control, proof strength and time can be reduced, test efficiency is greatly improved；2nd, breach existing experimental modal analysis techniques requirement
Extrinsic motivated response input and the defects that various pressures are assumed to excitation input, can achieve and quickly and easily enter action to girder construction
Step response is analyzed；3rd, do not need to measure external drive, only measurement response data, decreases device requirement, experimentation cost can be big
Big reduction, is that operational modal analysis experimental technique adds a kind of new method.
Brief description
Fig. 1 is a kind of schematic flow sheet of the operational modal analysis experimental technique based on mutual spectral function of the present invention.
Fig. 2 is operational modal analysis experimental provision composition schematic diagram.
Fig. 3 is girder construction point layout schematic diagram.
Fig. 4 is the time domain response oscillogram of reference point.
Fig. 5 is the crosspower spectrum functional arrangement between reference point and measuring point.
Fig. 6 is the Mode Shape figure of the beam of identification, and wherein, (a) is a first order mode, and (b) is second_mode, and (c) is three ranks
The vibration shape.
Specific embodiment
The invention will be further described below in conjunction with the accompanying drawings.
With reference to Fig. 1～Fig. 6, a kind of operational modal analysis experimental technique based on mutual spectral function, the method includes following step
Suddenly：
1) with elastic threads, beam is hung, the end points selecting beam, as excitation point, implements pulse excitation using steel hammer to beam；
Selected distance excitation point is compared near and the larger response measuring point of response signal amplitude is as a reference point；
Each geometric model inserting knot response measuring point in described reference point and the reflection beam vibration shape；
2) gather the response signal that described reference point and response measuring point produce after pulse excitation；
3) bandpass filtering is carried out to collection signal, its passband is structural modal frequency scope interested, to all sound
Passage is answered to add Hanning window；
4) when asking for the crosspower spectrum function between reference point and response measuring point, and building the different sampling of crosspower spectrum function
Carve the matrix equation that data is constituted；
5) utilize described matrix equation to solve coefficient matrix, obtain system pole；
6) identification Mode Shape and modal participation factors matrix；
7) carry out mode confidence criterion matrix value to calculate, if mode confidence criterion matrix value is not in default reasonable interval
Interior, then choose different sampling instant values, return to step 4) rebuild Matrix division, until mode confidence criterion value is pre-
If within reasonable interval, obtain modal parameters.
Further, methods described is further comprising the steps of：8) mode animation is drawn：Show that the mode in each direction of each point is shaken
Type vector, corresponding with point layout geometric model, just obtain describing the Mode Shape of the relative amplitude on each measuring point x, y, z direction
Animation.
Referring to Fig. 2, a kind of operational modal analysis experimental technique based on pulse excitation and device, including fixed support 1, bullet
Property rope 2, steel hammer 3, acceleration transducer 4, beam 5, suspension ring 6, coaxial cable 7, number adopt front end 8, run module analysis center 9 (can
To adopt notebook computer).Described beam 5 is hung by elastic threads 2, excludes the impact of extraneous vibration, and makes beam be in free boundary
Condition.Described elastic threads one end and fixed support 1 connect, and one end is connected with suspension ring 6, and described suspension ring 6 are threaded connection with beam,
Acceleration of vibration-the time data of each measuring point tested by described acceleration transducer 4, and each acceleration transducer 4 passes through coaxial cable 7
Electrically connect with data acquisition front 8 respectively, data acquisition front 8 electrically connects with running module analysis center 9.Acceleration sensing
After device 4 collects the response signal under pulse excitation, its incoming data is gathered front end 8, then pass to operation module analysis center
9, the vibration response signal data being gathered imports the operational modal analysis running module analysis center 9 by data acquisition front
Software module is analyzed processing, and identifies modal parameter.
A kind of operational modal analysis experimental technique based on mutual spectral function, concrete operation step is as follows：
1) select excitation point
In order to identify the modal parameter of unbonded beam, a wideband random excitation signal should be inputted as far as possible.Pulse excitation
Auto-power spectrum close with white noise signal, that is, its spectrum density, in lower frequency section close to straight, is comparatively ideal excitation letter
Number.Hence with steel hammer 3, pulse excitation is applied to beam, to excite each order mode state.
In technical solutions according to the invention, " pulse excitation " refers to choose excitation point on beam, is encouraged using steel hammer 3
Structure, improves the signal to noise ratio of collection signal.Referring to Fig. 3,9 measuring points are equally spaced on beam.Select beam No. 1 point of end points be
Excitation point.
2) select reference point and response measuring point, measure structural vibration response
In the present embodiment, on beam to be measured, No. 1 shop of selection is as a reference point, and remaining 8 measuring point is as response measuring point, same
When reference point and response measuring point on respectively fix acceleration transducer 4.Join by the excitation of acceleration transducer 4 acquisition pulse is lower
Examination point and the acceleration of vibration of response measuring point.The time domain plethysmographic signal of reference point is referring to Fig. 4.
3) ask for cross-correlation function, and be denoted as complex mode form
What cross-correlation function represented is that between two time serieses and at the same time sequence is not in any two in the same time
Value between degree of correlation, that is, cross-correlation function is description stochastic signal x (t), and y (t) is in any two not in the same time
Degree of correlation between value.Respond the cross-correlation function between measuring point j and reference point i according to formula (1) computation structure
In formula, Rij(τ) it is the cross-correlation function responding between measuring point j and reference point i, T is the testing time, xiT () is ginseng
The acceleration responsive signal of examination point, xjT () is the acceleration responsive signal of response measuring point, τ is time interval.
4) ask for response signal crosspower spectrum function, build the square being made up of the crosspower spectrum functional value of different sampling instants
Battle array equation.
By Rij(k Δ t) makees periodic extension, and carries out discrete Fourier transform (DFT), and meet with a response measuring point j and reference point i
Between monolateral cross-spectral density function：
No. 3 crosspower spectrum functions between measuring point and reference point are referring to Fig. 5.TakeIn different sampling start times
Value set up crosspower spectrum Jacobian matrix equation：
A in formula0, a1... a2NFor coefficient；Sij(t0), Sij(t1)…Sij(t4N) for responding between measuring point j and reference point i mutually
Power spectrum function is in t0, t1,…t4NThe value in moment.Constitute compression equation using the covariance matrix of equation group, be somebody's turn to do
The least square solution of compression equation, obtains coefficient a0, a1... a2NValue.
5) identifying system limit
For identifying system limit, makeConstruction following equations：
A in formulakFor coefficient, the above formula left side is added by 2N item and forms, and therefore the number of equation group characteristic solution at least should be equal to
2N, therefore k=0,1,2 ... 2N.If above formula is set up, coefficient a0, a1... a2NMeeting following rational fraction orthogonal polynomial is
Poroney polynomial equation, and this multinomial withIt is characterized solution.Take a2N=1, obtain：
By the coefficient matrix estimating a0, a1... a2NSubstitution formula (8), tries to achieve the limit of system.
6) identification Mode Shape and modal participation factors matrix
Crosspower spectrum Jacobian matrix is expressed as system each rank Mode Shape and the partial fraction of modal participation factors matrix
Sum, obtains
In formula, VrFor Mode Shape matrix, LrFor modal participation factors matrix, represent each order mode state in system response
Contribution amount,For the complex-conjugate matrix of Mode Shape matrix,For the complex-conjugate matrix of modal participation factors matrix,For system
The conjugate complex number of limit；
The system pole of identification is substituted into formula (9), tries to achieve by each rank Mode Shape vector ΨrThe Mode Shape matrix constituting
VrAnd its modal participation factors matrix Lr, obtain the overall situation estimation of system mode parameter.
In the present embodiment, each order mode state under different calculating orders is investigated using least square multifrequency domain method (LSFD method)
Corresponding natural frequency, the calculation error of damping when Mode Shape, obtain minimum mean-square error steady state picture, are chosen at all meters
Calculating mark " S " on order and putting the corresponding frequency of most N row is system mode frequency, and thus calculates damping when mode
The vibration shape.
7) mode checking and analysis：Mainly complete the verifying correctness of operational modal analysis result.Sentenced using mode confidence
According toJudge the accuracy of mode estimation.Wherein ΨrFor r rank Mode Shape vector；ΨsFor
S rank Mode Shape vector；Ψr *TConjugate transpose for r rank Mode Shape vector；Ψs *TFor s rank Mode Shape vector
Conjugate transpose.Can determine whether that modal parameter picks up the correctness of result by mode confidence criterion MAC matrix, thus judging that mode is estimated
The accuracy of meter.If there is linear relationship between two Mode Shape, its MAC value close to 1, if they are independently of each other
, then MAC value is close to zero.Judge the correctness of recognition result through mode confidence criterion matrix, if between each order mode state
MAC value is respectively less than 0.3, then each order mode state identifying is true mode, and recognition result accurately, terminates whole calculating process.If
The MAC value existing between certain two order mode state is more than 0.3, from the beginning of step (4), selects different sampling instant data to recalculate directly
To meeting the requirements.Have thus determined each order mode state parameter value, the operational modal analysis core calculations mistake based on pulse excitation
Journey terminates.
8) mode animation is drawn：Draw the Mode Shape vector in each direction of each point, corresponding with point layout geometric model,
Just obtain describing the Mode Shape animation of the relative amplitude on each measuring point x, y, z direction, thus completing whole service model analyses
Overall process.First three order mode state bending vibation mode picture of the beam of identification is referring to Fig. 6.
Described step 2) in reference point and response measuring point acceleration of vibration measured by acceleration transducer 4, adopted by data
Collection front end 8 completes the record of acceleration of vibration.
Described step 7) in, it is identified the verifying correctness of result using mode confidence criterion.
It is only the better embodiment of the present invention described in upper, therefore the construction described in all scopes according to present patent application, spy
Levy and equivalence changes that principle is done or modification, be all included in the range of present patent application.
The above is only the preferred embodiment of the present invention, and protection scope of the present invention is not limited to above-mentioned enforcement
Example, all technical schemes belonging under thinking of the present invention belong to protection scope of the present invention.It should be pointed out that for the art
Those of ordinary skill for, some improvements and modifications without departing from the principles of the present invention, these improvements and modifications
Should be regarded as protection scope of the present invention.
Claims (7)
1. a kind of operational modal analysis experimental technique based on mutual spectral function it is characterised in that：Comprise the following steps：
1) with elastic threads, beam is hung, the end points selecting beam, as excitation point, implements pulse excitation using steel hammer to beam；
Selected distance excitation point is compared near and the larger response measuring point of response signal amplitude is as a reference point；
Each geometric model inserting knot response measuring point in described reference point and the reflection beam vibration shape；
2) gather the response signal that described reference point and response measuring point produce after pulse excitation；
3) bandpass filtering is carried out to collection signal, its passband is structural modal frequency scope interested, logical to all responses
Road adds Hanning window；
4) ask for the crosspower spectrum function between reference point and response measuring point, and build crosspower spectrum function difference sampling instant number
According to the matrix equation constituting；
5) utilize described matrix equation to solve coefficient matrix, obtain system pole；
6) identification Mode Shape and modal participation factors matrix；
7) carry out mode confidence criterion matrix value to calculate, if mode confidence criterion matrix value is not in default reasonable interval,
Choose different sampling instant values, return to step 4) rebuild Matrix division, until mode confidence criterion matrix value is pre-
If within reasonable interval, obtain modal parameters.
2. the operational modal analysis experimental technique based on mutual spectral function as claimed in claim 1 it is characterised in that：Methods described
Further comprising the steps of：8) mode animation is drawn：Draw the Mode Shape vector in each direction of each point, several with response point layout
What model corresponds to, and just obtains describing the Mode Shape animation of the relative amplitude on each response measuring point x, y, z direction.
3. as claimed in claim 1 or 2 a kind of operational modal analysis experimental technique based on mutual spectral function it is characterised in that：
Described step 4) in, respond the cross-correlation function between measuring point j and reference point i according to formula (1) computation structure：
In formula, Rij(τ) it is the cross-correlation function responding between measuring point j and reference point i, T is the testing time, xiT () is reference point
Acceleration responsive signal, xjT () is the acceleration responsive signal of response measuring point, τ is time interval；
To the cross-correlation function R between structural response measuring point j and reference point iij(τ) sample according to sampling time interval Δ t, and will
It is expressed as complex mode form
C in formularijIt is the constant coefficient related to r order mode state；N is rank number of mode to be identified；Δ t is sampling time interval, k table
Show the number of sampling；λrFor system pole；
By system pole λrIt is expressed asξ in formularFor r rank damping ratios；ωr
For r order mode state undamped natural frequency of a mechanical system；
By Rij(k Δ t) makees periodic extension, and carries out discrete Fourier transform, meets with a response monolateral between measuring point j and reference point i
Cross-spectral density function：
TakeSet up crosspower spectrum Jacobian matrix equation in the value of different sampling start times：
A in formula0, a1... a2NFor coefficient；Sij(t0), Sij(t1)…Sij(4N) for responding crosspower spectrum between measuring point j and reference point i
Function is in t0, t1,…t4NThe value in moment, constitutes compression equation using the covariance matrix of equation group, obtains this compression side
The least square solution of journey, obtains coefficient a0, a1... a2NValue.
4. as claimed in claim 3 a kind of operational modal analysis experimental technique based on mutual spectral function it is characterised in that：Described
Step 5) in, orderConstruction following equations：
A in formulakFor coefficient, the above formula left side is added by 2N item and forms, and therefore the number of equation group characteristic solution at least should be equal to 2N, because
This k=0,1,2 ... 2N, if above formula is set up, coefficient a0, a1... a2NMeeting following rational fraction orthogonal polynomial is
Poroney polynomial equation, and this multinomial withIt is characterized solution, take a2N=1, obtain：
By the coefficient matrix estimating a0, a1... a2NSubstitution formula (8), tries to achieve the limit of system.
5. as claimed in claim 4 a kind of operational modal analysis experimental technique based on mutual spectral function it is characterised in that：Described
Step 6) in, crosspower spectrum Jacobian matrix is expressed as system each rank Mode Shape and the partial fraction of modal participation factors matrix
Sum, obtains
In formula, VrFor Mode Shape matrix, LrFor modal participation factors matrix, represent the contribution of each order mode state in system response
Amount,For the complex-conjugate matrix of Mode Shape matrix,For the complex-conjugate matrix of modal participation factors matrix,For system pole
Conjugate complex number；
The system pole of identification is substituted into formula (9), tries to achieve by each rank Mode Shape vector ΨrThe Mode Shape matrix V constitutingrAnd
Its modal participation factors matrix Lr, obtain the overall situation estimation of system mode parameter.
6. as claimed in claim 5 a kind of operational modal analysis experimental technique based on mutual spectral function it is characterised in that：Described
Step 7) in, mode confidence criterion matrix value is：
Wherein, ΨrFor r rank Mode Shape vector；ΨsFor s rank Mode Shape vector；Ψr *TFor r rank Mode Shape vector
Conjugate transpose；Ψs *TConjugate transpose for s rank Mode Shape vector.
7. the device that a kind of operational modal analysis experimental technique based on mutual spectral function as claimed in claim 1 is realized, it is special
Levy and be：Described device includes fixed support, elastic threads, steel hammer, acceleration transducer, beam, suspension ring, coaxial cable, data are adopted
Collection front end and operation module analysis center, described beam is hung by elastic threads, makes beam be in free boundary condition, described elastic threads one
End and fixed support connect, and the other end of described elastic threads is connected with suspension ring, and described suspension ring and beam are threaded connection, and described add
Velocity sensor test each measuring point acceleration of vibration-time data, each acceleration transducer pass through coaxial cable respectively with number
According to the electrical connection of collection front end, data acquisition front electrically connects with running module analysis center, and acceleration transducer collects pulse
After response signal under excitation, its incoming data is gathered front end, then pass to operation module analysis center, the vibration being gathered rings
Induction signal data imports operation module analysis center by data acquisition front and is analyzed processing.
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