reference-free crack detection under varying...

KSCE Journal of Civil Engineering (2011) 15(8):1395-1404DOI 10.1007/s12205-011-1271-0

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www.springer.com/12205

Structural Engineering

Reference-Free Crack Detection under Varying Temperature

Hoon Sohn*

Received July 16, 2010/Revised November 26, 2010/Accepted February 22, 2011

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Abstract

A new paradigm for damage diagnosis is proposed by developing a damage detection technique that eliminates the need forinitially collected baseline data. Traditional techniques often identify damage by comparing the current data set with the referencedata collected from the pristine condition of the structure being monitored. However, this conventional pattern comparison approachis shown to be vulnerable to other changes such as temperature variation that may not be relevant to defects of interest. One ofpotential advantages of the proposed reference-free approach is that false-alarm due to these undesirable variations could beminimized particularly for field applications where varying structural and environmental conditions impose significant challenges fordamage diagnosis. In this paper, the effect of varying temperature on the previously developed reference-free crack detectiontechnique is investigated using an aluminum plate with an increasing crack depth.Keywords: Structural Health Monitoring (SHM), Piezoelectric Transducer (PZT), reference-free damage detection, lamb wave,temperature effect

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1. Introduction

Recently, international attention is garnered highlighting theneeds for adopting Structural Health Monitroing (SHM) and Non-Destructive Testing (NDT) technoigies to continuous monitoringof aging aircraft, civil infrastructure and mechanical systems.There is a large volume of literature that offers an excellentoverview of recent developments in SHM and NDT (Adams,2007; Blitz et al., 1996; Chang et al., 2003a, 2003b; Ciolko et al.,1999; Doherty, 1987; Hellier, 2001; Montalvao et al., 2006,Popovics, 2004; Sohn et al., 2004; Staszewski et al., 2004; Su etal., 2004, 2006; Van der Auweraer et al., 2003). Guided waves isone of the NDT techniques that have received a great deal ofattention because they can propagate over considerable distanceswith little attenuation. Many of guided wave studies have focusedon schemes where baseline signals are measured so that changesfrom the baseline data can be detected and related to defects.However, there are significant technical challenges to performthis pattern comparison. For instance, structural defects typicallytake place long after the initial baseline data are collected, andother operational and environmental variations of the system canproduce significant changes in the measured responses, maskingany potential signal changes due to structural defects (Adama,2007). On the other hand, it can be claimed that other NDT tech-niques such as X-ray, magnetic particle, infrared imaging tech-niques also do not rely on past baseline data. However, the inter-pretation of these data should be performed by expriecenced

engineers, and these technique may not be eaisly automated forcontinuous monitoring of in-service structures where operationaland enviromental changes play a major role.

As a potential alternative that can overcome the drawbacks ofthe conventional NDT methods, a new concept of NDT tech-nique, which does not rely on previously obtained baseline dataand can be easily automated, is proposed for crack detection in aplate-like structure with a uniform thickness (Kim and Sohn,2007a). In the first step, a damage-sensitive feature that can iso-late the mode conversion is developed using the polarizationcharacterisitcs of piezoelectric materials such as Lead ZirconateTitanate (PZT). Then, automated damage identificaiton is achievedby comparing the extracted feature with a threshold obtainedinstantaneously from the current data set. By removing the depend-ency on the prior baseline data, the proposed damage detectionsystem becomes less vulnerable to operational and environ-mental variations that might occur throughtout the life span ofthe structures being monitored. In this study, the effect of tem-perature variation on the prevously deveoped reference-free crackdetection technique is theoretically and experimentally investi-gated. Other refernece-free techniques are being investigted byother researchers (Fasel et al., 2010; Kim et al., 2007b; Sohn etal., 2007a, 2007b).

This paper is organized as follows. In section TheoreticalDevelopment, a damage-sensitive feature for crack detection isextracted using two pairs of collocated PZTs. Then, thresholdingtechniques are proposed to determine the existence of crack

*Member, Chaired Professor, Dept. of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon 305-701, Korea(E-mail: [email protected])

Hoon Sohn

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damage even at the presence of variations in PZT sizes, bondingconditions and alignments without using predetermined decisionboundaries. Experimental setups are explained in section 3, andthe effectiveness and robustness of the proposed technique undervarying temperatures are experimentally investigated in section4. Finally, the paper concludes with a brief summary and dis-cussions in section 5.

2. Theoretical Development

2.1 The Effect of PZT Polarization Direction on LambWave Propagation

Piezoelectric materials are natural or artificially polarized ce-ramics which have piezoelectricity (Sohn et al., 2007b). Thepiezoelectric materials develop an electrical charge or voltagewhen a mechanical pressure is applied. Conversely, they producedeformation (strain) when exposed to an applied electric field.Due to this unique nature of the piezoelectric materials, they arecommonly used for sensing and control applications. The pie-zoelectric material’s behavior in terms of sensing and actuation isgoverned by the polarization (or poling) direction of the material(Buchanan, 2004).

First, it is investigated how the phase of a Lamb wave modechanges depending on (1) the poling directions of exciting andsensing PZT wafer transducers and (2) whether a wafer trans-ducer is attached either on the top or bottom surface of a plate. InFig. 1(a), it is assumed that four identical PZT wafer transducers,labeled as “A”, “B”, “C”, and “D”, are attached to a plate. Thearrows indicate positive poling directions of each PZT trans-ducers. PZTs A and D are placed exactly at the same position buton the other side of the plate. PZTs B and C are positioned in asimilar fashion. Furthermore, it is assumed that a narrowband

toneburst signal is applied as an input, and the driving frequencyis chosen such that only the fundamental symmetric (S0) andanti-symmetric (A0) modes are generated. In this paper, the termof “positive bending” is used when the positively polarized sideof the PZT is subjected to tensile strain.

When PZT A is excited, the S0 and A0 modes are generated andmeasured at PZTs B and C (Giurgiutiu et al., 2000; Viktorov,1967). In an ideal condition, the amplitudes and arrival times ofthe S0 mode measured at PZTs B and C should be identical. Inaddition, both PZTs B and C would be subjected to positivebending because of the symmetric nature of the S0 mode (See thefigure on the left hand side of Fig. 1(b)). Because both PZTs Band C are subject to the positive bending, the phases as well asthe amplitudes and arrival times of the S0 mode measured atthese PZTs should be identical as shown in Fig. 2(a). Here, signalAB denotes the response measured at PZT B when the excitationis applied at PZT A. Signals AC, DB and DC are defined in asimilar manner. As far as the A0 mode is concerned, PZT C issubjected to the negative bending when PZT B undergoes thepositive bending (See the figure on the right side of Fig. 1(b)).Therefore, the A0 modes measured at PZTs B and C are out-of-phase as shown in Fig. 2(a). A similar concept can be applied toexcitation. When the collocated PZTs A and D are subjected tothe same positive bending, they generate in-phase S0 modes andout-of-phase A0 modes as depicted in Fig. 2(b). In Fig. 3(a), thisconcept is extended to signals AB, AC, DB, and DC.

This idea of using the PZT poling directionality in Lamb wavepropagation is not a completely new idea. However, the majorityof the past work has focused on selective generation of S0 and A0

modes (Giurgiutiu, 2005; Su et al., 2004; Wilcox et al., 2001;Yamanaka et al., 1991). For instance, by exciting PZTs A and Dshown in Fig. 1(a) in-phase, only the S0 mode can be excited. Inthis study, the polarization characteristic of the PZT is utilizednot only for selective generations of Lamb wave modes but alsofor selective measurements. Also, it should be noted that thepresented selected mode excitation and sensing are possible atany arbitrary temperature as long as the collocated PZTs aresubjected to the same temperature. In the following subsection,this idea of using PZT poling directionality is further advancedso that the mode conversion due to crack formation can be

Fig. 1. The PZT Transducer Configuration of the Proposed Tech-nique and the Effect of the S0 and A0 Modes on the PZTBending: (a) Configuration of Double Sides PZTs (PZTs Aand D are Collocated with the Opposite Poling Directions,and PZTs B and C are Placed in the same manner), (b) TheS0 mode produces the same bending for PZTs B and Cwhile the A0 mode results in the opposite bending

Fig. 2. Comparison of the Relative Phases of the S0 and A0 ModesObtained from the Collocated Sensing and Exciting PZTs:AB (a solid line) and AC (a dash line) Denote the ResponseSignals Measured at PZTs B and C when a Tone Burst Inputis Applied at PZT A. DB is Defined in a Similar Manner: (a)The Sensing Effect of Collocated PZTs B and C: the S0

Mode In-phase and the A0 Mode Out-of-phase, (b) TheExcitation Effect of Collocated PZTs A and D: the S0 ModeIn-phase and the A0 Mode Out-of-phase


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extracted from the measured Lamb wave signals.

2.2 Extraction of Crack Induced Mode Conversion WithoutBaseline Data

In this subsection, the PZT polarization characteristic is furtheradvanced so that the mode conversion due to crack formationcan be detected without direct comparison with prior baselinedata. If Lamb waves propagating along a specimen with a uniformthickness encounter a discontinuity such as a sudden thicknesschange of the plate, some portion of the waves are reflected atthe discontinuity point and others are transmitted through it.When a S0 mode arrives at the discontinuity as shown on the topfigure of Fig. 3(b), the transmitted wave is separated into S0 andA0 modes (denoted as S0 and A0/S0, respectively). In a similarmanner, an A0 mode is also divided into S0 and A0 modes (S0/A0,and A0). Similarly, the reflected waves are split into S0 and A0

modes. This phenomenon is called mode conversion (Cho,2000).

Based on the description in section , the relative phases amongsignals AB, AC, DB and DC are revisited in Fig. 3(b) whenmode conversion occurs. On the other hand, the signs of newlygenerated modes (A0/S0 and S0/A0) will be altered depending onthe characteristics of the discontinuity that the launching Lambmodes are passing through. Although the signs of these convertedmodes cannot be determined without knowing the detailed char-acteristics of the discontinuity, it can be shown that the phases ofthe A0/S0 mode in signal AB and the S0/A0 mode in signal BAshould be always identical. This is based on the reciprocity ofsignals AB and BA (Park et al., 2009). Comparing signals ABand AC, the symmetric S0 and S0/A0 modes are in-phase and theanti-symmetric A0 and A0/S0 modes are out-of-phase. On theother hand, the collocated PZTs A and D generate in-phase S0

and A0/S0 modes and out-of-phase A0 and S0/A0 modes betweensignals AB and DB. After examining Fig. 3, several observationscould be made:

1. At the absence of mode conversion, signals AB and DC areidentical. When the S0/A0 and A0/S0 modes appear in these twosignals due to crack, these converted modes become fully out-of-phase.

2. Similarly, signals AC and DB are initially identical, and theconverted modes in these two signals grow to be out-of-phaseat the presence of the crack.

3. Although all signals change due to temperature variations asdemonstrated in later experiments, the initial matchingbetween signals AB and DC (or signals AC and DB) is validfor any temperature, loading, boundary and support conditionsas long as there is no thickness change of the specimen.

4. Furthermore, signals AB and DC (or signals AC and DB)remain identical regardless of the symmetry of the specimen,temperature and the PZT placement. However, it is assumedthat all PZTs are identical in terms of size and bonding condi-tions.

5. Signals AB and BA (or any pair of reciprocal signals such assignals AC and CA) are always identical at any temperaturewith and without crack.

Therefore, the mode conversion due to crack formation cansimply be extracted by subtracting signals AB from DC or signalsAC from DB. Note that the extraction of the mode conversion isaccomplished based solely on the signals obtained from the cur-rent state of the system. Furthermore, the crack does not neces-sarily have to be in the direct wave propagation path betweenPZTs A and B. As long as mode conversions reflected or refractedfrom the crack are measured by one of the PZTs, the associatedcrack should be detectable. Because this approach relies only oncomparison between two signals instantaneously obtained at thecurrent state of the system rather than comparison with previouslyrecorded reference data, it is expected that this approach reducefalse-positive alarms due to changing operational and environ-mental conditions of the system.

2.3 Decomposition of Individual Lamb Modes from Mea-sured Time Signals

From Fig. 3(b), it can be seen that signal AB is a simplesuperposition of signals S0, MC1, MC2 and A0. Here, signal S0

indicates a time signal that contains only the S0 mode, but itslength is identical to that of signal AB. Signals MC1, MC2 and A0

are defined in a similar fashion. MC1 and MC2 represent the firstand second arrivals of the Lamb wave modes created by modeconversion, respectively. Note that MC1 and MC2 could be eitherS0/A0 or A0/S0 modes depending on the relative position of thecrack with respect to the actuating and sensing PZTs used.

Similar to signal AB, signals AC, DB, and DC can be alsoexpressed as combinations of individual Lamb wave signals withspecial attention to the phases. For instance, the A0 and MC2

modes in signal AC are out-of-phase compared to these modes insignal AB. Therefore, signal AC can be obtained by flippingsignals A0 and MC2 and summing up signals S0, MC1, MC2 andA0 all together. Based on these observations, the relationship

Fig. 3. Comparison of Relative Phases of the S0 and A0 ModesAmong Signals AB, AC, DB and DC (The solid line indi-cates that the phase of a mode is in-phase with the cor-responding mode in signal AB, and the dash line denotesthat its phase is out-of-phase with respect to the associatedmode in signal AB): (a) Signals without a Notch, (b) Signalswith a Notch

Hoon Sohn


between the time signals that can be measured (signals AB, AC,DB and DC) and the individual Lamb mode signals (signals S0,MC1, MC2 and A0) can be obtained as follows:

(1)

Because of measurement errors and variations in PZT sizes,alignments and bonding conditions, error terms are incorporatedin Eq. (1). Here, eAB is an error signal in the measured signal ABthat is superimposed to the exact signal AB, and eAC, eBD, and eCD

are defined similarly. eS0, eMC1, eMC2 and eA0 represent error signalsin each decomposed Lamb mode signals. By taking the inverseof Eqs. (1) and (2) below shows how each individual Lambmode signals can be extracted from the measured signals AB,AC, BD and CD.

(2)

Note that only signals MC1 and MC2 are supposed to containLamb modes relevant to damage (MC1 and MC2, respectively),and Eqs. (1) and (2) are valid at any temperature. Ideally, signalsMC1 and MC2 should be zeros at the absence of damage. Inpractice, however, due to eMC1 and eMC2 that are superimposed tothe exact signals MC1 and MC2, the estimated signals MC1 andMC2 may not be zeros even without damage. Since eMC1 and eMC2

cannot be separated from signals MC1 and MC2 only using Eq.(2), it is challenging to determine whether additional modes inthese signals are due to mode conversion or initial errors. To tacklethis issue, a new damage classifier is developed in the followingsection to determine if the non-zero responses in signals MC1

and MC2 are due to the mode conversion or simply due to theinitial errors. Finally, when a total of 8 signals (signals, AB, AC,DB, DC, BA, CA, BD and CD) are available, Eq. (2) can bemodified to incorporate all these available signals:

(3)

2.4 Damage Classification using Instantaneously Mea-sured Lamb Wave Signals

The imperfections in PZTs may generate initial differences

between signals AB and DC and consequently the initial errorsin the extracted signals MC1 and MC2 even at the absence of acrack. Here, the challenge is to discern the amplitude increaseswithin signals MC1 and MC2 due to the crack from those causedby the initial errors. To tackle this issue, two damage detectionschemes are developed so that a crack, which produces largeramplitudes in signals MC1 and MC2 than those of the initialerrors, can be detected. The uniqueness of the proposed damageclassification schemes is that the threshold value for damageclassification is determined only using signals instantaneouslymeasured from the current state of the system without relying ona predetermined threshold value.

Two techniques for thresholding are investigated. In the firsttechnique (Technique 1), signals S0, MC1, MC2 and A0 are firstcomputed using Eq. (2). Then, the arrival times of the first S0 andA0 modes, tS and tA, are computed. Next, the maximum absoluteamplitude of the potential MC1 mode, max(|MC1|), is foundbetween tS and (tS + tA)/2, and the maximum absolute amplitudeof the errors, emax1, is found between (tS + tA)/2 and tA. In theory,signal MC1 between (tS + tA)/2 and tA should remain zero all thetime regardless of the damage state, because the MC1 modealways arrives before (tS + tA)/2. In practice, there are, however,some initial errors in this time region due to the imperfections inPZTs. This level of the initial errors is estimated from emax1. Asimilar procedure is repeated for signal MC2. Finally, the thresh-old for damage classification is set to be max(|emax1|, |emax2|) andcompared with max(|MC1|) and max(|MC2|). When both ofmax(|MC1|) and max(|MC2|) are larger than max(|emax1|, |emax2|), itis concluded that there is a crack between PZTs A and B. Notethat Technique 1 produces the same threshold value for bothMC1 and MC2 modes, and applicable only when the crack is notclose to the middle point between PZTs A and B. Although theamplitudes of max(|emax1|, |emax2|), max(|MC1|) and max(|MC2|)are all temperature dependent, the following classifier is valid forany temperature.

If max(|MC1|) and max(|MC2|) > max(|emax1|, |emax2|), a crack exists (4)

The second technique (Technique 2) starts by decomposingmeasured signals AB, AC, DB and DC into signals S0, MC1,MC2 and A0 again. Then, the standard deviation of signal MC1,σ MC1, is computed. If there is no defect, the variance of signalMC1 is mainly attributed to the initial errors. Assuming that theinitial errors have a normal distribution of zero mean and σMC1

standard deviation, 99.7% of the data points in signal MC1

should be within the range of -3σ MC1 to 3σ MC1. Once actual modeconversion appears within signal MC1, the maximum absoluteamplitude of the actual MC1 mode could go outside this range asthe crack progressed. Therefore, the existence of a crack can beidentified when max(|MC1|) becomes larger than 3σMC1 at anytemperature. The performances of these two thresholding techn-iques are experimentally examined in section 4.

If max(|MC1|) > 3σ MC1 and max(|MC2|) > 3σMC2|, a crack exists (5)

Signal AB eAB+Signal AC eAC+Signal DB eDB+Signal DC eDC+

1 1 1 11 1 1– 1–1 1– 1 1–1 1– 1– 1

Signal S0 eS0+Signal MC1 eMC1+Signal MC2 eMC2+

Signal A0 eA0+

=


Signal A0 eA0+

14---

1 1 1 11 1 1– 1–1 1– 1 1–1 1– 1– 1


=


Signal A0 eA0+

18---

1 1 1 11 1 1– 1–1 1– 1 1–1 1– 1– 1


=

18---

1 1 1 11 1 1– 1–1 1– 1 1–1 1– 1– 1

Signal BA eBA+Signal CA eCA+Signal BD eBD+Signal CD eCD+

+


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3. Experimental Setup

For this study, an aluminum plate of 455 mm×254 mm×3 mmwas used as shown in Fig. 4. The size of the plate was mainlylimited by the available space of the climate chamber used forsubsequent temperature experiments. The Young’s modulus ofthis T6 aluminum plate was 310 MPa, and the specimen wassupported by two rubber blocks placed at the ends of thespecimen.

Circular PZTs (6.35 mm in diameter and 0.25 mm in thickness)were purchased from American Piezo Ltd. They had a Curietemperature of 360oC and the maximum operational temperatureof 180oC. The d33 piezoelectric charge constant, the capacitancevalue and the Young’s Modulus were 4×10-10 m/V, 1.50 nF,6×1010 N/m2, respectively. PZTs A and D were collocated andattached on the other side of the plate, and PZTs B and C weremounted in a similar fashion. The PZTs were attached so thattheir poling directions were identical to the configuration shownin Fig. 4 (In the figure, the positive poling direction of individualPZT is shown with an arrow). PZTs A and B (or PZTs C and D)were 215 mm apart each other.

For the attachment of PZTs to the specimen, M-bond 200cyanoacrylate adhesive from Vishay measurements group wasused. Based on the manufacturer’s specification, this M-bondadhesives could be used for a one-cycle proof test over 90oC or-185oC. But, the normal operating temperature range was -30oCto 65oC. To secure the wires to the specimen, high temperatureTeflon tapes from 3M Corporation (3M Scotch Brand 5412)were used. In addition, high temperature wires were used.

The data acquisition system was composed of a laptop compu-ter, an Arbitrary Waveform Generator (AWG), a high-speedsignal digitizer (DIG), a Low Noise Preamplifier (LNP) and amultiplexer. Using the 14-bit AWG, a tone burst signal with a±10 peak-to-peak voltage and a driving frequency of 280 kHzwas generated and applied. In order to improve the signal-to-noise ratio, the forwarding signals were measured ten times andaveraged in the time domain. After the forwarding signals fromPZT A to PZT B (signal AB) were measured, the same processwas repeated by measuring signals AC, DB, DC, BA, CA, BDand CD. The length and width of the crack was 31 mm and 1mm, respectively, and the crack depth was gradually increasedfrom 0 mm to 0.5 mm, 1.0 mm and 2.0 mm. All examineddamage cases are summarized in Table 1.

As shown in Fig. 4, two thermocouples T1 and T2 were in-strumented in the middle and quadrant points of the specimen.As part of temperature experiments, an infrared heater fromProtherm Heater (model #12014) shown in Fig. 5(a) was used tosimulate partial head-up of the specimen. The infrared heaterwas controlled by a thermostatic temperature controller using T1thermocouple on the test article as the feedback control temper-ature. The infrared heater was placed near the center of thespecimen, and the temperature reading from thermocouple T1was used as the set point for the controller. For the experimentalresults provided in section 4, the reading from thermocouple T2was reported. Note that there was a large temperature gradientbetween T1 and T2 readings. For instance, when the readingfrom T2 was 50oC, the one from T1 was close to 100oC.

Another temperature experiment was conducted using a Micro-Climate temperature/humidity chamber. This chamber is a pre-engineered chamber designed to provide an environment withspecific temperature (humidity) conditions. In this study, onlythe temperature value was controlled. In this case, the tempera-ture gradient between thermocouples T1 and T2 was less than3oC, and the T2 value was reported in section 4. It took about 2-3minutes before the temperature was stabilized. Unlike the tem-perature experiment with the infrared heater, the temperaturechamber experiment allowed the specimen to be tested below theroom temperature.

4. Test Results

4.1 Preliminary Data AnalysisFirst, the experimental tuning curves for the first arrivals of the

S0 and A0 modes were obtained for a range of 100 kHz to 400kHz to determine the optimal driving frequency of the input toneburst signal (see Fig. 6) (The extraction process of the S0 and A0modes from the measured time signals AB, AC, DB, DC, BA,

Fig. 4. Dimension and Configuration of the Aluminum Test Speci-men with a Uniform Thickness: The Arrows Denote the Po-sitive Polarization Directions of Each PZTs

Table 1. Summary of Data Collected with an Increasing Crack Depth

Crack depth Data collection date Temperature0.0 mm 08/01/07 22oC0.5 mm 08/03/07 22oC1.0 mm 08/06/07 23oC2.0 mm 08/10/07 22oC

Fig. 5. Two Experimental Setups for Temperature Variation Experi-ments: (a) A Inferred Heater for Temperature Gradient Tests,(b) A Temperature Chamber for Uniform Temperature Tests

Hoon Sohn


CA, BD and CD are described later). Based on Fig. 6., thedriving frequency of the subsequent experiments is fixed to be280 kHz so that the amplitudes of the S0 and A0 modes arerelatively equal and other higher modes do not appear. Thecorresponding theoretical dispersion curves are shown in Fig. 7.The group velocities of the S0 and A0 modes were estimated to be5.13 m/ms and 3.04 m/ms, respectively.

From the intact condition of the specimen, a total of 8 timesignals (signals AB, AC, DB, DC, BA, CA, BD and CD) werecollected. A subset of the collected time signals was displayed inFig. 8. First, the linear reciprocity between signals AB and BAwas demonstrated in Fig. 8(a). It was shown that these twosignals were almost identical regardless of the existence of acrack. A similar observation was made between signals DB andBD in Fig. 8(b) or any other reciprocal pairs of signals. Next,based on the PZT polarization directions shown in Fig. 4, the S0

modes in signals AB and AC should be in-phase while the A0

modes should be out-of-phase (Fig. 8c). It was readily shownthat the first arrival of the S0 mode was in-phase, but it wasdifficult to distinguish S0 and A0 modes for the rest of the signalsbecause multiple S0 and A0 modes overlapped. Similar observa-tion was made for signals BA and BD shown in Fig. 8(d). Thetheoretical development in section suggested that signals ABand DC or signals AC and DB should be identical when there isno mode conversion in the specimen. This was experimentallydemonstrated in Fig. 8(e) and (f). It should be noted that, due tovariations in PZTs themselves, bonding and alignment conditions,small discrepancies between signals AB and DC (or signals ACand DB) were observed even at the absence of a crack.

Individual S0, A0, MC1 and MC2 modes were decomposed from

the measured time signals using Eq. (2) and shown in Fig. 9.When the S0 modes were decoupled in Fig. 9(a), the first arrivaland reflections from the side and end boundaries were clearlyidentified. Similarly, the arrivals of the first A0 mode and subse-quent reflections were discerned in Fig. 9(b). Note that becausethe S0 mode reflected from the side boundaries and the first A0

mode arrived almost concurrently, the identification of the firstA0 mode was difficulty in the measured raw time signals such as

Fig. 6. Experimental Tuning Curves of S0 and A0 Modes for a 3mm Thick Aluminum Plate

Fig. 7. Group Velocities of S0 and A0 Modes for a 3 mm ThickAluminum Plate

Fig. 8. Comparison of Measured Time Signals without Notch: (a)Reciprocity between Signals AB and BA, (b) Reciprocitybetween Signals DB and BD, (c) Comparison of Signals ABand AC (S0 modes in-phase and A0 modes out-of-phase),(d) Comparison of Signals BA and BD (S0 modes in-phaseand A0 modes out-of-phase), (e) Comparison of Signals ABand CD (S0 and A0 modes in-phase), (f) Comparison of Sig-nals AC and BD (S0 and A0 modes in-phase)

Fig. 9. Individual S0, A0, MC1 & MC2 Modes Decomposed fromMeasured Time Signals (without notch): (a) Decomposed S0

Signal, (b) Decomposed A0 Signal, (c) Decomposed MC1

Signal, (d) Decomposed MC2 Signal


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signals AB and AC in Fig. 8(c) and (d). The tuning curves in Fig.6. were obtained using these decoupled S0 and A0 modes. Fur-thermore, the mode conversion did not occur at this stage sincethere was no sudden thickness change in the pristine test article.Fig. 9(c) and (d) substantiated the theoretical expectation becausethe magnitudes of supposedly converted modes were negligiblecompared to those of the S0 and A0 modes.

4.2 Crack Detection at Room TemperatureTo investigate the effectiveness of the proposed reference-free

crack detection method, a crack with an increasing crack depthwas introduced in the specimen. As shown in Fig. 4, the crackwas introduced between PZTs A and B (about 54 mm from PZTA). The crack depth was increased from 0 mm to 0.5 mm, 1.0mm and 2 mm, respectively. Because the MC1 and MC2 modeswere expected to arrive between the first arrival S0 and A0

modes, all the signals hereafter were shown between the firstarrival S0 and A0 modes.

In Fig. 10(a) and (b), the measured time signals AB and BDobtained from the test article with the varying crack depth wereshown. Although changes of signals AB and BD were observed,it was inconclusive whether these variations were mainly due tocrack formation. Next, the decoupled signals S0 and A0 weresubsequently shown in Fig. 10(c) and (d). When the individualS0 and A0 modes were decomposed from a total of 8 measuredsignals, the arrivals of the first S0 and A0 modes and the secondS0 mode reflected from the side boundaries were clearly identifi-

ed. As the crack depth increased, the amplitudes of the firstarrival S0 and A0 modes decreased while the amplitude of theMC1 and MC2 modes were amplified. The attenuations of thefirst arrival S0 and A0 modes were mainly attributed to modeconversion. Finally, the converted MC1 and MC2 modes wereshown in Fig. 10(e) and (f). In this particular experiment, the S0

mode converted from the A0 mode (S0/A0) arrived before theother converted mode (A0/S0) because the crack was closer toPZT A than PZT B. In both converted modes, their amplitudesincreased proportionally to the deepening of the crack.

It was demonstrated that, by decomposing the measuredsignals into the individual Lamb mode signals, the appearance ofthe mode conversion due to the crack formation were qualitati-vely identified. However, the identification of the mode conver-sion still relied on the comparison of the subsequently obtainedtime signals with the baseline signals. Without this pattern com-parison with the baseline signals, it was difficult to decide whetherthe amplitudes of the converted modes were larger than the initialnoise levels and whether they actually resulted from the crackformation. Therefore, to complete the reference-free damagediagnosis scheme, this decision making process should be alsoconducted without explicit dependency on the baseline data. Thisissue of reference-free damage classification is addressed in thefollowing section.

4.3 Instantaneous Damage ClassificationIn this subsection, two damage classification techniques de-

scribed in section were applied to the data sets presented in theprevious subsection. First, the adaptive threshold values for eachdamage cases were determined using Eqs. (4) and (5) andreported in Table 2. For technique 1, the threshold values for

Fig. 10. Variations of Measured Time Signals and DecomposedModes with the Increasing Crack Depth ( 0 mm,

0.5 mm, 1.00 mm, 2.0 mm): (a) Mea-sured Signal AB, (b) Measured Signal BC, (c) DecoupledSignal S0, (d) Decoupled Signal A0, (e) Decoupled SignalMC1 (S0/A0), (f) Decoupled Signal MC2 (A0/S0)

Fig. 11. Instantaneous Damage Classification with Varying DecisionBoundaries without using Prior Baseline Data (h1, h2, h3and h4 are the Thresholds Corresponding to 0 mm, 0.5mm, 1.0 mm & 2.0 mm ( 0 mm, 0.5 mm, 1.00 mm, 2.0 mm): (a) Decoupled Signal MC1 (S0/A0)with Technique 1, (b) Decoupled Signal MC2 (A0/S0) withTechnique 1, (c) Decoupled Signal MC1 (S0/A0) with Tech-nique 2, (d) Decoupled Signal MC2 (A0/S0) with Technique2

Hoon Sohn


MC1 (S0/A0) and MC2 (A0/S0) modes were identical while thesevalues were different in technique 2. The threshold values fromtechnique 1 remained relatively unchanged, but the ones fromtechnique 2 increased as the damage progressed. The results ofdamage classification are qualitatively shown in Fig. 11, and thenumbers of the outliers outside each threshold values are re-ported in Table 3. In Fig. 11, signals MC1 and MC2 were zoomedin for 0.1 ms to 0.5 ms to highlight MC1 (S0/A0) and MC2 (A0/S0).When the crack depth was equal to or less than 0.5 mm, noindications of cracks were provided using both techniques 1 and2. As the crack depth increased to 1.0 mm and 2.0 mm, the num-bers of outliers increased significantly. Because 0.5 mm deepcrack was not detected, the result corresponding to the 0.5 mmcrack depth was not reported hereafter.

4.4 Crack Detection at Varying TemperaturesThe next step was to examine if the proposed damage classi-

fiers would be robust even under changing temperature condi-tions. The variations of representative measured time signals anddecoupled Lamb modes with respect to temperature were illus-trated in Fig. 12. These signals were obtained when the specimenwith 2 mm deep crack was placed inside the temperaturechamber. The amplitude increase and phase delay of the signalswere observed as the temperature increased from -30oC to 70oC.The Young’s modulus of Aluminum decreased with increasingtemperature (Department of Defense Handbook, 2003), and as aresult, the group velocities of the propagating wave packetsdeclined. Therefore, a delay of the arrival time was observed forthe signals propagated at higher temperatures (Andrews et al.,2008). It should be noted that because the temperature variationitself caused significant changes in the measured signal’samplitude and phase as shown in Fig. 12, it would be challengingto perform pattern comparison with the baseline signals for the

purpose of damage diagnosis.All damage diagnosis results from varying temperature condi-

tions were summarized in Table 4. In the first 4 rows (cases 1-4),false-positive studies were conducted using the intact specimen.For all cases examined, there were no indications of false alarms.For cases 1 to 4, the temperature was controlled using the in-frared heater from 22oC to 55oC. Note that the temperaturereported here was obtained from thermocouple T2 shown in Fig.4, and thermocouple T1 was used as the set point for the tem-perature controller. A broader spectrum of temperature variationswas not examined using the intact specimen to avoid anypotential damage to the PZT transducers before performingsubsequent damage cases. For cases 5 to 16 in Table 4, the speci-men with 1 mm crack was subjected to temperature increase from5oC to 60oC using either the infrared heater or the temperaturechamber. For all cases investigated, the maximum absoluteamplitudes of the MC1 and MC2 modes exceeded the thresholdvalues obtained from techniques 1 and 2. Furthermore, the num-bers of outliers outside each threshold values remained reasonablyconsistent. For the remaining cases, (cases 17-27), the specimenwith 2 mm-deep crack was subjected a broader temperaturevariation of -30oC to 70oC using the temperature chamber. Com-pared to cases 5 to 16, larger numbers of outliers were observedfor cases 17 to 27. The increase of the outlier numbers was muchhigher when technique 1 was used compared to technique 2. Thiswas attributed to the fact that the threshold values also increasedwith the deepening crack for technique 2.

Table 2. Adaptive Threshold Values for Instantaneous DamageClassification

Threshold

Crack

Technique 1 Technique 2

S0/A0 A0/S0 S0/A0 A0/S0

0.0 mm 0.0058 0.0058 0.0053 0.00610.5 mm 0.0053 0.0053 0.0036 0.00631.0 mm 0.0052 0.0052 0.0067 0.01142.0 mm 0.0063 0.0063 0.0133 0.0179

Table 3. Number of Outliers beyond the Decision Boundaries (Atroom temperature)

Threshold

Crack

Technique 1 Technique 2S0/A0 A0/S0 S0/A0 A0/S0

0.0 mm 0 0 0 00.5 mm 0 0 0 01.0 mm 78 131 43 302.0 mm 140 180 48 46

Fig. 12. Variations of Measured Time Signals and DecomposedModes with Respect to Temperature (with 2 mm deepcrack: -30oC, 0oC, 22oC, 70oC): (a)Measured Signal AB, (b) Measured Signal BC, (c) Decou-pled Signal S0, (d) Decoupled Signal A0, (e) DecoupledSignal MC1 (S0/A0), (f) Decoupled Signal MC2 (A0/S0)


Vol. 15, No. 8 / November 2011 − 1403 −

It was concluded that a crack deeper than 1 mm was detectablewhen the 3 mm specimen was investigated in the temperaturerange of -30oC to 70oC as long as there was no degradation of thePZTs’ piezoelectricity and bonding conditions. The applicabilityof the proposed technique was demonstrated under the limitedconditions: The consistent bonding of the PZTs and the precisealignments of the collocated PZTs were critical to the success ofthe proposed technique. In addition, the current technique is onlyapplicable to a structure with a uniform thickness. As long as themode conversion reflected or refracted from a crack could bemeasured by one of the PZTs, the crack does not necessarilyhave to be along the direct wave propagation path between PZTsA and B. However, the effects of the crack location and orienta-tion were not fully investigated in this study. Ongoing research isunderway to address these issues.

5. Conclusions

In this study, a new damage detection technique is presented sothat a crack within a specimen with a uniform thickness can bedetected without direct comparison with baseline data obtained

from the pristine condition of the structure being monitored. Theproposed reference-free approach is two-folds. First, a featuresensitive to crack formation is extracted using two pairs of col-located PZTs placed on the both sides of the specimen. Second,an instantaneous damage classifier is developed by instantaneouslyestablishing the decision boundaries without pre-determined thresh-olds. In particular, the robustness of the proposed technique totemperature variations is experimentally investigated in the tem-perature range of -30oC to 70oC. For the 3 mm thick specimeninvestigated, a crack deeper than 1 mm was successfully detectedunder all the temperature range examined. The success of theproposed technique heavily depended on the consistent place-ment of the PZTs and the precise alignment of the collocated PZTs.Ongoing research is underway to address these instrumentationissues and to investigate the effects of the crack location andorientation on the proposed crack detection technique.

Acknowledgements

The experiment was conducted at the Wright Patterson AirForce Base (WPAFB) in Dayton, Ohio, while the author parti-

Table 4. Number of Outliers Outside the Threshold Values (Under changing temperatures)

Crack depth # T2 (oC)*Technique 1 Technique 2 Temp.

ControlDate

(mm/dd/yy)S0/A0 A0/S0 S0/A0 A0/S0

0 mm

1 22 0 0 0 0

InfraredHeater

08/01/072 39 0 0 0 0 08/01/073 40 0 0 0 0 08/01/074 55 0 0 0 0 08/01/07

1 mm

5 23 82 134 47 31

InfraredHeater

08/07/076 30 77 135 44 39 08/07/077 40 69 135 44 39 08/07/078 51 56 132 44 39 08/07/079 05 84 131 43 32

Temp.chamber

08/07/0710 10 74 130 45 28 08/08/0711 15 84 130 44 31 08/08/0712 21 81 132 45 31 08/09/0713 23 80 133 44 31 08/08/0714 41 65 132 45 37 08/09/0715 50 52 123 42 36 08/09/0716 60 56 135 42 40 08/09/07

2 mm

17 -30 137 177 43 41 08/13/0718 -20 163 188 46 43 08/13/0719 -10 157 183 45 41 08/13/0720 -5 144 177 49 49

Temp.chamber

08/13/0721 0 141 173 47 39 08/13/0722 11 137 173 48 43 08/13/0723 17 143 185 47 41 08/13/0724 22 137 181 46 46 08/13/0725 50 123 172 47 47 08/13/0726 60 141 184 51 55 08/13/0727 70 138 172 50 51 08/13/07

*The temperature reported here was obtained from thermocouple T2 shown in Fig. 4.

Hoon Sohn


cipated in the Air Force Summer Fellowship Program at the AirForce Research Laboratory/Air Vehicles Directorate (AFRL/VA)in 2007. Additional supports were provided by the NuclearResearch & Development Program (2010-0020423) and theNational Research Laboratory Program (2010-0017456) ofNational Research Foundation of Korea (NRF). The author alsolikes to acknowledge Dr. Mark Derriso and the SHM team atWPAFB for providing this opportunity and Mr. Todd Bussey forhelping the instrumentation of the test specimen.

References

Adams, D. (2007). Health Monitoring of Structural Materials andComponents: Methods with Applications John Wiley and Sons.

Andrews, J. P., Palazotto, A. N., DeSimio, M. P., and Olson, S. E. (2008).“Lamb wave propagation in varying isothermal environments.” Int.Journal of Structural Health Monitoring, Vol. 7, No. 3, pp. 265-270.

Blitz, J. and Simpson, G. (1996). Ultrasonic methods of non-destructivetesting, Chapman & Hall.

Buchanan, R. C. (2004). Ceramic materials for electronics, New York:Marcel Dekker.

Chang, P. C. and Liu, S. C. (2003b). “Recent research in nondestructiveevaluation of civil infrastructures,” Journal of Materials in CivilEngineering, Vol. 15, No. 3, pp. 298-304.

Chang, P. C., Flatau, A., and Liu, S. C. (2003a). “Review paper: Healthmonitoring of civil infrastructure.” An International Journal ofStructural Health Monitoring, Vol. 2, No. 3, pp. 257-267.

Cho, Y. (2000). “Estimation of ultrasonic guided wave mode conversionin a plate with thickness variation.” IEEE transactions on ultraso-nics, ferroelectrics, and frequency control, Vol. 47, No. 10, pp. 591-603.

Ciolko, A. T. and Tabatabai, H. (1999). “Nondestructive methods forcondition evaluation of prestressing steel strands in concrete bridges.Final report phase I: Technology review.” NCHRP Project 10-53.

Department of Defense Handbook. (2003). Metallic materials andelements for aerospace vehicle structures, MIL-HDBK-5J.

Doherty, J. E. (1987). Nondestructive evaluation chapter 12 in Hand-book on experimental mechanics, Kobayashi, A. S. (ed), Society forExperimental Mechanics, Inc.

Fasel, T. and Todd, M. (2010). “An adhesive bond state classificationmethod for a composite skin-to-spar joint using chaotic insonification.”Journal of Sound and Vibration, Vol. 329, No. 15, pp. 3218-3232

Fraden, J. (2001). Handbook of modern sensors, American Institute ofPhysics, New York.

Giurgiutiu, V. (2005). “Tuned lamb wave excitation and detection withpiezoelectric wafer active sensors for structural health monitoring.”Journal of Intelligent Material Systems and Structures, Vol. 16, No.4, pp. 291-305.

Giurgiutiu, V. and Zagrai, A. N. (2000). “Characterization of piezoelec-tric wafer active sensors.” Journal of Intelligent Material Systemsand Structures,Vol. 11, No. 12, pp. 959-976.

Hellier, C. J. (2001). Handbook of non-destructive evaluation, McGraw-Hill, New York.

Kim, S. B. and Sohn, H. (2007a). “Instantaneous reference-free crack

detection based on polarization characteristics of piezoelectricmaterials.” Smart Materials and Structures, Vol. 16, pp. 2375-2387

Kim, S. D., In, C. W., Cronin, K. E., Sohn, H., and Harries, K. (2007b).“A reference-free NDT technique for debonding detection in CFRPstrengthened RC structures.” ASCE, Journal of Structural Engi-neering, Vol. 133, No. 8, pp. 1080-1091.

Montalvao, D., Maia, N. M. M., and Ribeiro, A. M. R. (2006). “Areview of vibration-based structural health monitoring with specialemphasis on composite materials.” The Shock and Vibration Digest,Vol. 38, No. 4, pp. 295-324.

Park, H. W., Kim, S. B., and Sohn, H. (2009). “Understanding a timereversal process in lamb wave propagations.” Wave Motion, Vol. 46,No. 7, pp. 451-467.

Popovics, J. (2004). “Non-destructive evaluation for civil engineeringstructures and materials.” Quantitative Nondestructive StructureEvaluation, Vol. 700, pp. 32-42.

Sohn, H. (2007). “Effects of environmental and operational variabilityon structural health monitoring.” A Special Issue of PhilosophicalTransactions of the Royal Society A on Structural Health MonitoringVol. 365, pp. 539-560.

Sohn, H., Farrar, C., Hemez, F. M., Czarnecki, J. J., Shunk, D. D.,Stinemates, D. W., and Nadler, B. R. (2004). A review of structuralhealth monitoring literature: 1996-2001, Los Alamos NationalLaboratory Report, LA-13976-MS.

Sohn, H., Park, H. W., Law, K. H., and Farrar, C. R. (2007a). “Combi-nation of a time reversal process and a consecutive outlier analysisfor baseline-free damage diagnosis.” Journal of Intelligent MaterialSystems and Structures, Vol. 18, No. 4, pp. 335-346.

Sohn, H., Park, H. W., Law, K. H., and Farrar, C. R. (2007b). “Damagedetection in composite plates by using an enhanced time reversalmethod.” ASCE Journal of Aerospace Engineering, Vol. 20, No. 3,pp. 141-151.

Staszewski, W., Boller, C., and Tomlinson, G. (2004). Health monitoringof aerospace structures, John Wiley and Sons.

Su, Z. and Ye, L. (2004). “Selective generation of lamb wave modes andtheir propagation characteristics in defective composite laminates.”Proceedings of the Institution of Mechanical Engineers, Part L:Journal of Materials: Design and Applications, Vol. 218, No. 2, pp.95-110.

Su, Z., Ye, L., and Lu, Y. (2006). “Guided lamb waves for identificationof damage in composite structures: A review,” Journal of Sound andVibration, Vol. 295, pp. 753-780.

Van der Auweraer, H., and Peeters, B. (2003). “International researchprojects on structural health monitoring: An overview,” An Inter-national Journal of Structural Health Monitoring, Vol. 2, No. 4, pp.341-358.

Viktorov, I. (1967). Rayleigh and lamb waves, New York: Plenum Press.Wilcox, P. D., Lowe, M. J. S., and Cawley, P. (2001). “Mode and

transducer selection for long range lamb wave inspection.” Journalof Intelligent Material Systems and Structures, Vol. 12, No. 8, pp.553-565.

Yamanaka, K., Nagata, Y., and Koda, T. (1991). “Selective excitation ofsingle-mode acoustic waves by phase velocity scanning of a laserbeam.” Applied Physics Letters, Vol. 58, No. 15, pp. 1591-1593.

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