CN107014668A - A kind of fatigue crack integrated monitoring based on piezoelectricity and smart coat sensor - Google Patents
A kind of fatigue crack integrated monitoring based on piezoelectricity and smart coat sensor Download PDFInfo
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Abstract
The invention discloses a kind of based on the method for piezoelectricity and smart coat sensor to structural fatigue crackle comprehensive monitoring, this method obtains the damage quantitative model and real-time crack detection results between Lamb wave and damage according to the crack monitoring principle of piezoelectric transducer and smart coat sensor respectively, with reference to the data type of different sensors damage monitoring result, corresponding crackle detection probability model is set up.For piezoelectric transducer, according to the actual fatigue crack propagation test result of aluminium alloy plate structure, damage quantitative model is set up based on Lamb wave signal, uses Bayesian updating method correction model parameter to obtain more accurately damage quantitative model.Pass through the POD models and the POD models of smart coat Sensor monitoring result of comparative analysis piezoelectric transducer monitoring result, the monitoring capability of comprehensive descision piezoelectricity and smart coat the sensor fatigue crack under different length.
Description
Technical field
The invention belongs to structural health monitoring field, it is related to structure damage monitorings such as metal, composites, and in particular to
A kind of comprehensive monitoring determination methods for being used for piezoelectricity and smart coat sensor to aluminium alloy sheet crack Propagation situation.
Background technology
Structural health monitoring technology is obtained for extensive use, structural health in civil engineering and aeronautical engineering field
Monitoring technology is exactly to pass through smart sensor's network on-line real time monitoring structural health.At present, in structural health monitoring skill
The sensor main used in art will have piezoelectric transducer, fibre optical sensor, MEMS sensor, smart coat sensor etc..Wherein
Piezoelectric transducer is the piezo-electric effect by itself, excitation and reception guided wave signals, and is realized by signal processing technology to knot
Structure damage monitoring；Smart coat sensor is made up of driving layer, sensing layer and protective layer, and intelligence is expanded to by structural crack
Coating sensor cloth patch position causes the change of sensing layer resistance value, so as to realize the monitoring to structural crack.
There are some researches show, for the different sensors equipment of monitoring structural health conditions, because the monitoring principle of sensor is different,
The data type and processing mode of its signal are also not quite similar, each to damage monitoring advantageous.At present, according to different sensors pair
The signal of structure damage monitoring collection, its data type is broadly divided into Signal response data and Hit/miss data.
Signal response data refer to by the electric signal or vibration signal that detect (such as：Voltage, electric current, frequency, strain etc.)
Consecutive variations be used to characterize the change of structural damage (such as：Crack length, damaged area etc.).For discrete response signal,
The data of sensor collection can directly react its testing result (hit=1, miss=0), and 1 expression damage is detected, 0 table
Show that damage is not detected at.The ability of piezoelectricity and smart coat sensor to damage is compared by crackle detection probability.Crackle is examined
Go out probability, i.e. POD (Probability of Detection) model is a kind of characteristic manner of sensor detectability.POD
Model result is not only relevant with lesion size, also by material, physical dimension, damage type, the monitoring ring for being such as monitored structure
The influence of the uncertain factor such as border and monitoring personnel.
Found in pertinent literature and experiment, when monitoring crack Propagation missing inspection can occur for smart coat sensor
Situation, so-called missing inspection then refers to that sensor is not detected by when crackle has already passed through the monitored area of smart coat sensor
Phenomenon.
The content of the invention
The present invention fully takes into account the missing inspection problem of smart coat sensor to solve the above problems, and proposes a kind of base
In piezoelectricity and the fatigue crack integrated monitoring of smart coat sensor.The present invention is the damage monitoring by piezoelectric transducer
Principle, sets up structural crack quantitative model monitoring crack Propagation situation, with reference to the monitoring result of smart coat sensor, point
Corresponding POD models are not set up, draw POD curves.The present invention is the POD moulds set up by the monitoring result of two kinds of sensors
Type, Integrated comparative piezoelectricity and smart coat sensor are selected long in different fatigue crackle the detection probability of crack Propagation
More it is capable of the sensor type of the accurate measurements structural fatigue Crack Extensions under degree.
Comprehensive descision is carried out to crack Propagation monitoring result present invention employs two kinds of sensors, passes through fatigue test
Machine is loaded to testpieces, testpieces is produced crack Propagation, and two kinds of sensors are obtained by the analyzing and processing to monitoring information
Corresponding POD models are obtained, the comprehensive descision to crack Propagation of two kinds of sensors is realized, overcomes two kinds of sensors itself
Deficiency.
The present invention is the monitoring result for being based respectively on piezoelectricity and smart coat sensor to fatigue crack, it is proposed that information is melted
Conjunction method, realizes the comprehensive descision of On Crack Propagation.Using the fatigue crack propagation test of aluminium alloy sheet as platform, on thin plate
Arrange that smart coat and piezoelectric transducer are monitored to crack Propagation, specifically divide following steps simultaneously：
Step 1：Selection experiment part.
Step 2：Cloth pressing electric transducer and smart coat sensor on aluminium alloy sheet.
Step 3：Determine the pumping signal of piezoelectric transducer.
Step 4：The aluminium alloy sheet that smart coat and piezoelectric transducer are posted by more than is enterprising installed in fatigue tester
Row fatigue crack propagation test.Before fatigue tester loading, the initial signal of piezoelectricity and smart coat sensor is gathered respectively.
Step 5：The crack length under different circulation cycles is recorded in real time by light microscope, in average loading stress water
The flat Lamb wave signal for stopping collection piezoelectric transducer reception during CYCLIC LOADING.Meanwhile, in each smart coat sensor alarm
When, record the data of smart coat sensor and the Lamb wave signal of piezoelectric transducer.
Step 6：Complete after experiment, the signal that sensor is gathered is handled.Mainly analyze and process piezoelectric transducer
The Lamb wave signal of collection, is filtered to the signal, interception Lamb wave signal S0The time window of pattern.Because Lamb wave is being passed
Broadcast with Crack Extension in path, it is that amplitude reduces, propagation path changes i.e. phase place change etc. that decay, which occurs, for signal energy, is extracted
Damage characteristic normalization amplitude X, phase angle variations Y, set up crack lengthWith the function model f () of damaging diagnostic parameter.
Step 7：Repeat step 2-6, the Lamb wave signal gathered for piezoelectric transducer is analyzed and processed, and extracts damage
The function model set up in characteristic parameter, verification step 5, and model parameter is corrected, obtain revised model g
(·)。
Step 8：According to the piezoelectric transducer crack monitoring model and the history number of smart coat sensor determined in step 7
According to the corresponding POD models of selection draw POD curves, judge monitoring of two kinds of sensors to aluminium alloy structure crack Propagation
Ability.
The advantage of the invention is that：
Propose it is a kind of based on damage quantitative model of the piezoelectric transducer to crack Propagation, with reference to smart coat and pressure
The test data that electric transducer is monitored to aluminium alloy plate fatigue crack, obtains the POD models of respective sensor, judges two kinds of sensings
Monitoring capability of the device to different crack lengths.By comprehensive intelligent coating and the POD models of piezoelectric transducer, two kinds of sensings are judged
Monitoring capability of the device under different crack lengths.
Brief description of the drawings
Fig. 1 is testpieces specification schematic diagram；
Fig. 2 sensor arrangement schematic diagrames；
Fig. 3 piezoelectric transducer pumping signals；
The Lamb wave signal that Fig. 4 piezoelectric transducers are received；
Under Fig. 5 difference crack lengths, S0Modeling curve；
The POD curves of Fig. 6 smart coats and piezoelectric transducer crack monitoring.
Embodiment
Below in conjunction with drawings and examples, the present invention is described in further detail.
The invention reside in provide a kind of integrated monitoring of multisensor to crack Propagation.By smart coat and
Piezoelectric transducer is monitored to the crack Propagation of aluminium alloy sheet, research and application result, draws the POD of two kinds of sensors
Model curve.
Above-mentioned aluminium alloy sheet is as shown in figure 1, its specification:600*300*2(mm).In order to make knot during fatigue test
Structure can carry out crack Propagation along assigned direction quickly, and the circle of a diameter 10mm is provided with the center of aluminium alloy sheet
Hole, and the prefabricated long 3mm, wide 0.2mm crackle respectively in the both direction parallel to short side.
The aluminium alloy sheet (as shown in Figure 2) for being disposed with sensor is loaded into before fatigue tester is tested, it is necessary to
Piezoelectricity and smart coat sensor are debugged, and obtain initial signal.Wherein, the debugging of sensor includes test sensor
Whether the excitation and collection of signal are normal, and the pumping signal that piezoelectric transducer is selected in this method implementation process is that five crests are sinusoidal
Modulated signal, centre frequency 160KHz, as shown in Figure 3.In view of the Dispersion of Lamb wave, in the Lamb wave signal collected
In, it is T2 according to the flight time (ToF, Time-of-Flight) of distance and Lamb wave between the piezoelectric transducer of arrangement, such as
Shown in Fig. 4, Lamb wave S is calculated0Pattern group velocity, intercepts S under different crack lengths0Mode time window.Because Lamb wave is being propagated
During reflection and the scattering phenomenon of signal occur when running into damage, energy will dissipate.Lamb wave S is used in this method selection0
The change of the amplitude of pattern and phase characterizes the spread scenarios of fatigue crack.In the time window intercepted, extract sign and split
The normalization amplitude X of the line spread scenarios and change Y at phase angle, and set up corresponding function model.
The Crack Extension quantitative model set up by the historical data and piezoelectric transducer of smart coat sensor, builds respectively
Corresponding POD models are found, comparative analysis obtains monitoring effect of two kinds of sensors to different crack lengths.
A kind of fatigue crack integrated monitoring based on piezoelectricity and smart coat sensor of the present invention, including it is following several
Individual step：
Step 1：Selection experiment part.In checking this method, it is contemplated that the propagation characteristic of Lamb wave and the expansion of fatigue crack
Exhibition, selects aluminium alloy sheet, specification：600*300*2 (mm), is provided with Φ 10mm circular hole, simultaneously at the center of aluminium alloy sheet
Hole both sides perpendicular to each prefabricated 3mm length of long side direction, crackle wide 0.2mm.
Step 2：Cloth pressing electric transducer and smart coat sensor on thin plate, wherein smart coat sensor from along
The centre distance that the tip of precrack is risen between 16 sensors of arrangement, two piezoelectric ceramic pieces is 200mm, as shown in Figure 2.
Step 3：The pumping signal of piezoelectric transducer is determined, can according to the dispersion curve that Lamb wave is propagated in aluminium alloy plate
Know, the Lamb wave S when the thick product of frequency is smaller0Pattern group velocity is larger and stably, the periodicity one of each driving pulse of pumping signal
As select 3.5~13.5 cycles, periodicity can not be excessive, can not be very few.Because the periodicity of signal is more, it is different
Crosstalk will occur for the ripple bag of pattern, be unfavorable for the analysis of signal.The periodicity of pumping signal is very few, the energy entrained by signal
It is fewer, and bandwidth is wider, signal is easily disturbed.Here five cycle sinusoidal modulation wave signals, centre frequency 160KHz are selected.
Step 4：The aluminium alloy sheet that smart coat and piezoelectric transducer are posted by more than is enterprising installed in fatigue tester
Row fatigue crack propagation test.Before fatigue tester loading, the initial signal of piezoelectricity and smart coat sensor is gathered respectively.
Set the loading parameter of fatigue tester, including stress ratio, maximum stress, loading frequency, Loaded contact analysis etc..
Step 5：The crack length under different circulation cycles is recorded in real time by light microscope, in average loading stress water
It is flat to stop gathering the Lamb wave signal that piezoelectric transducer is received in the case of CYCLIC LOADING.Meanwhile, in each smart coat sensing
When device is alarmed, the data of smart coat sensor and the Lamb wave signal of piezoelectric transducer are recorded.
Step 6：After off-test, the collection signal of smart coat and piezoelectric transducer is handled.Passed for piezoelectricity
The Lamb wave signal that sensor is received carries out narrow-band filtering, and S is intercepted from filtered signal0The corresponding time window of ripple bag is (see figure
5) impairment parameter, and according to below equation is extracted from time window.A in formula 3iAnd A0I-th is represented in Fig. 5 dotted line frames respectively
The crest value and reference signal of curve are P in the crest value that crack length is zero, formula 4iAnd P0I-th curve is represented respectively
At the time of corresponding to crest value and the crest value of reference signal.Set up tired by the measured value and damaging diagnostic parameter of Crack Extension
The damage quantitative model of labor crackle.
Y (i)=Pi-P0 (4)
Wherein：X represents to normalize amplitude in above formula, and Y represents phase angle variations, αi(i=0,1,2,3) model ginseng is represented
Number,The crack length of model monitoring.
Step 7：Using the testpieces of same size, repeat step 2-6 six times, the function model set up in verification step 5,
And model parameter is modified using the MCMC methods of samplings in Bayes statistical method, obtain revised model.
Wherein：α ' in above formulai(i=0,1,2,3) it is model parameter after updating.
Step 8：According to model formation (7), (8) and (9), the POD models of piezoelectric transducer are set up, POD curves are drawn.
Wherein：Lna is the logarithmic form of actual crack length in formula (7),It is the logarithmic form of model monitoring result,
γ is that obedience average is zero, and standard deviation is σγError variance, α, β are model parameters.In formula (8)Crack monitoring threshold value.
The monitoring result of smart coat sensor in test of many times is handled, each smart coat Sensor monitoring
As a result as a Hit/miss data type, when Crack Extension is between two sensors, previous smart coat sensor
Alarm, then previous smart coat sensor detects crackle, and otherwise the sensor does not detect crackle.According to testing result,
Obtain the sample average and sample variance of smart coat sensor crack monitoring.Smart coat sensor is obtained by formula (10) to split
The POD models of line monitoring, wherein m is sample average, and σ is sample standard deviation.Finally, according to modeling rendering smart coat sensor
POD curves.
Wherein：M, σ are the sample average and standard deviation of smart coat Sensor monitoring result respectively in above formula.
According to the two of painted on top POD models, prison of two kinds of sensors to aluminium alloy structure crack Propagation is judged
Survey ability, as shown in Figure 6.
Claims (1)
1. a kind of fatigue crack integrated monitoring based on piezoelectricity and smart coat sensor, is split with the fatigue of aluminium alloy sheet
Line expanding test is platform, arranges that smart coat and piezoelectric transducer are monitored to crack Propagation simultaneously on thin plate,
Specifically include following steps：
Step 1：Selection experiment part；
Step 2：Cloth pressing electric transducer and smart coat sensor on aluminium alloy sheet；
Step 3：Determine the pumping signal of piezoelectric transducer；
Step 4：The aluminium alloy sheet for posting smart coat and piezoelectric transducer above is carried out on fatigue tester tired
Labor crack expansion test, before fatigue tester loading, gathers the initial signal of piezoelectricity and smart coat sensor respectively；
Step 5：Record the crack length under different circulation cycles in real time by light microscope, stop in average loading stress level
The Lamb wave signal that piezoelectric transducer is received only is gathered during CYCLIC LOADING；Meanwhile, in each smart coat sensor alarm, note
Record the data of smart coat sensor and the Lamb wave signal of piezoelectric transducer；
Step 6：Complete after experiment, the signal that sensor is gathered is handled, the Lamb wave signal gathered to piezoelectric transducer
It is filtered, interception Lamb wave signal S0The time window of pattern, extracts damage characteristic normalization amplitude X, phase angle variations Y, builds
Vertical crack length a and damaging diagnostic parameter function model f ()：
Step 7：Repeat step 2-6, the Lamb wave signal gathered for piezoelectric transducer is analyzed and processed, and extracts damage characteristic
The function model set up in parameter, verification step 6, and model parameter is corrected, obtain revised model g ()：
Step 8：According to the piezoelectric transducer crack monitoring model and the historical data of smart coat sensor determined in step 7,
Respectively according to the POD models (3) of the data type of piezoelectric transducer and smart coat Sensor monitoring result selection, (4), draw
POD curves, judge monitoring capability of two kinds of sensors to aluminium alloy structure crack Propagation；
In above formula (3)It is the logarithmic form of model monitoring result,Lna smart coats in crack monitoring threshold value, formula (4)
The logarithmic form of Sensor monitoring result, m, σ are the sample average and standard deviation of smart coat Sensor monitoring result respectively.
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Cited By (19)
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| CN107588788A (en) * | 2017-08-29 | 2018-01-16 | 北京航空航天大学 | Optical fiber and smart coat data fusion implementation method based on entropy weight step analysis |
| CN107607055A (en) * | 2017-09-08 | 2018-01-19 | 北京航空航天大学 | A kind of implementation method of the hardware system based on optical fiber and smart coat sensor |
| CN108318261A (en) * | 2018-01-08 | 2018-07-24 | 中车青岛四方机车车辆股份有限公司 | The monitoring method and device of vehicle structure |
| CN108645727A (en) * | 2018-05-10 | 2018-10-12 | 北京航空航天大学 | Crack Damage quantitative detecting method based on piezoelectric excitation-optical fiber grating sensing |
| CN109187857A (en) * | 2018-08-22 | 2019-01-11 | 中国飞机强度研究所 | A kind of crackle monitoring device and method based on silver powder coating sensor |
| CN109612806A (en) * | 2019-02-25 | 2019-04-12 | 北京航空航天大学 | A kind of efficient test material preparation and test method suitable for the test of surface crack defect detection probability |
| CN109632958A (en) * | 2018-12-24 | 2019-04-16 | 北京航空航天大学 | A kind of Lamb wave damage detecting method considering crackle orientation |
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| CN110390115A (en) * | 2018-04-17 | 2019-10-29 | 江苏必得科技股份有限公司 | Train part Crack Damage prediction technique and device |
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| CN107607055A (en) * | 2017-09-08 | 2018-01-19 | 北京航空航天大学 | A kind of implementation method of the hardware system based on optical fiber and smart coat sensor |
| CN108318261A (en) * | 2018-01-08 | 2018-07-24 | 中车青岛四方机车车辆股份有限公司 | The monitoring method and device of vehicle structure |
| CN110390115A (en) * | 2018-04-17 | 2019-10-29 | 江苏必得科技股份有限公司 | Train part Crack Damage prediction technique and device |
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