Piezoelectric Transducer Self-Diagnosis Under Changing

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2017IEEE TransacTIons on UlTrasonIcs, FErroElEcTrIcs, and FrEqUEncy conTrol, vol. 57, no. 9, sEpTEmbEr 2010

Abstract—Surface-mountable wafer-type piezoelectric trans-ducers using lead zirconate titanate (PZT) are widely used to generate and sense guided waves for nondestructive evaluation and structural health monitoring applications. However, little attention has been paid to monitoring PZT transducer integ-rity, despite possibly being the weakest link in the entire moni-toring system. In this study, PZT transducer self-diagnostic techniques, which enable a single PZT transducer to exam-ine its own integrity, are developed based on a time-reversal process; the effects of temperature and structural condition variations are explicitly considered. Two PZT self-diagnosis indices are proposed which allow debonded and cracked PZT conditions to be identified and distinguished from changing environmental and structural conditions. First, the proposed self-diagnosis schemes are theoretically formulated, and then the feasibility of the proposed schemes is validated through simulations and experimental tests under varying temperature and structural conditions.

I. Introduction

Guided waves such as lamb waves have been widely used for structural damage detection [1]–[3]. one of

main advantages of guided wave-based structural health monitoring (sHm) or non-destructive testing (ndT) techniques is that guided waves generally travel a rela-tively long distance with little attenuation. active sens-ing devices using piezoelectric materials such as lead zirconate titanate (pZT) are among the most commonly used for lamb wave excitation and sensing, because of their compactness, low power consumption and cost, and light weight [4]. despite these advantages, deployment of pZT transducers for sHm applications could be limited because pZT materials are brittle, and their ruggedness under various external loadings and harsh environmental conditions are unproven.

There are two major pZT failure modes of concern: pZT debonding and cracking. It is often assumed that these transducers are perfectly bonded to a structure and their performance does not change. However, in field ap-plications, a pZT’s bonding condition deteriorates over time and the transducer is vulnerable to cracking because of its brittleness and external loading. Here, the primary concern is that pZT deterioration can directly compro-mise measured mechanical responses and misguide a sHm system to produce false alarms. Therefore, it is necessary to develop a reliable pZT transducer self-diagnosis tech-nique for current pZT-based sHm systems.

There have been several studies on pZT transducer di-agnosis. saint-pierre et al. [5] and Giurgiutiu et al. [6] show that pZT debonding causes the resonant frequency of a pZT transducer to shift, as measured from its imped-ance. In other studies, park et al. [7] and Eckstein et al. [8] tried to detect pZT defects by estimating the pZT’s capacitance from the measured pZT admittance, because a pZT’s capacitance increases or decreases as the pZT transducer is debonded or cracked, respectively. However, the pZT capacitance can be also influenced by tempera-ture variation. In our previous study [9], we have extracted features that are sensitive to pZT defects but insensitive to temperature variation.

In this study, the following contributions are made: 1) advancement of the previously proposed features to mini-mize sensitivity to structural condition changes and struc-tural damage as well as temperature variation; 2) actual development of pZT damage classifiers for autonomous decision making; and 3) Experimental verification to show that these features are indeed insensitive to both tempera-ture and structural condition changes, which consequently can minimize false alarms of pZT malfunction.

This paper is organized as follows. First, the theoreti-cal background for pZT transducer self-sensing and self-diagnosis is provided; corresponding classifiers and some numerical simulation studies are presented. Then, experi-mental studies are conducted to validate the feasibility of the proposed self-diagnosis schemes under changing tem-perature and structural conditions. Finally, conclusions with a brief summary are given.

II. Theoretical background

This section describes the theoretical framework of the proposed pZT transducer self-diagnosis schemes for de-

Piezoelectric Transducer Self-Diagnosis Under Changing Environmental and Structural

Conditionssang Jun lee and Hoon sohn

manuscript received January 14, 2010; accepted may 10, 2010. This work was supported by the radiation Technology program (m20703000015-07n0300-01510) and the nuclear research & develop-ment program (2009-0083489) of national research Foundation (nrF) of Korea funded by the ministry of Education, science & Technology (mEsT) and by the agency for defense development (Uc080019Jd). any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies.

s. J. lee is with the school of Electrical and computer Engineering, Georgia Institute of Technology, atlanta, Ga.

H. sohn is with the department of civil and Environmental Engi-neering, Korea advanced Institute of science and Technology, daejeon, Korea (e-mail: [email protected]).

digital object Identifier 10.1109/TUFFc.2010.1649

tecting pZT defects. Fig. 1 outlines two steps of the pro-posed self-diagnosis schemes: 1) calculation and monitor-ing of a self-diagnosis index, named the symmetric (sym) index for pZT debonding detection; and 2) calculation and monitoring of another index, called the mechanical response power (mrp) index for pZT cracking detection. at each stage, the abnormality of the pZT transducer will be examined using the developed classifiers.

First, the sym index, which will be defined later, is cal-culated at each driving frequency and plotted with respect to the driving frequency to identify pZT debonding. This index has the unique characteristic of depending only on pZT debonding: it is not affected by temperature, varying structural conditions, or pZT cracking. second, the mrp index is calculated by sweeping the driving frequency; it is plotted against the driving frequency and used to detect pZT cracking. In this study, it will be shown that although the mrp index plot shifts horizontally when the pZT is cracked, temperature or structural condition variation causes only a vertical shift of the mrp index plot, making it possible to differentiate pZT cracking from changing temperature and structural conditions. Finally, the pZT condition is classified into either debonded, cracked, or no defect conditions based on the proposed pZT self-diagno-sis indices obtained from these two steps.

This section is organized as follows: First, the scaling factor (sF) index is defined and the pZT transducer self-sensing scheme necessary for the pZT transducer self-di-agnosis is briefly introduced. Then, the sym and mpr indices are provided with the corresponding classifiers.

A. PZT Transducer Self-Sensing

For completeness, a pZT self-sensing circuit from our previous work [9] is briefly described. Here, the term self-sensing means that a single pZT transducer is used for simultaneous excitation and sensing. a simple voltage di-vider composed of a conventional capacitor is employed

to construct a self-sensing circuit as shown in Fig. 2. The self-sensing scheme consists of two steps: 1) estimation of the sF index by applying a probing waveform, and 2) extraction of a mechanical response corresponding to an arbitrary input waveform.

When the pZT transducer is mounted on one surface of the host structure, the output voltage [vo(t)] of the pro-posed self-sensing circuit depends only on the input volt-age [vi(t)] and the mechanical response [vp(t)] of the host structure. Here, the sF index of the proposed self-sensing circuit is defined as

SF p

p r

o

i p

o

i=

+=

+@

CC C

v tv t v t

v tv t

( )( ) ( )

( )( )

,

(1)

2018 IEEE TransacTIons on UlTrasonIcs, FErroElEcTrIcs, and FrEqUEncy conTrol, vol. 57, no. 9, sEpTEmbEr 2010

Fig. 1. an overview of the proposed pZT transducer self-diagnosis schemes.

Fig. 2. a schematic of the proposed self-sensing circuit based on a volt-age divider, which enables extraction of the mechanical response from the host structure.

where Cp and Cr are the pZT capacitance and the refer-ence capacitance of the self-sensing circuit, respectively. Using the defined sF index, the mechanical response can be estimated as

v tv t

v tpo

iSF( )

( )( ).= - (2)

B. SYM Index for PZT Debonding Identification

a pZT transducer self-diagnosis index, which is only sensitive to pZT debonding under changing environmen-tal and structural conditions, is developed here using the time-reversal process (Trp). according to time reversal acoustics (Tra) between two pZT transducers [10], an input signal can be reconstructed at an excitation point through the following steps: 1) measurement of an out-put signal at a sensing point; 2) reversal of the measured output signal in the time domain and emission of this reversed signal back to the measurement point; and 3) measurement of the corresponding response at the original input point, called the reconstructed signal. In this study, the concept of the Tra is extended so that the Trp can be still accomplished using a single pZT transducer for which the exciting and sensing points are identical, as shown in Fig. 3. park et al. [11] show that the shape and size of the pZT transducer does not affect the Trp, implying that the Trp is not affected by the cracked pZT condition.

Fig. 3 shows a schematic of the time reversal-based pZT debonding detection. The Trp consists of four steps: 1) application of a symmetric narrowband toneburst in-put signal [vtb(t)] to the pZT transducer [Fig. 3(a)]; 2) measurement of the corresponding mechanical response

of the structure [vrs(t)] from the same pZT transducer using the previously described self-sensing circuit [Fig. 3(b)]; 3) reversal of the mechanical response, scaled in the time domain, which is then reemitted [vre(t)] [Fig. 3(c)]; and 4) measurement of the reconstructed signal [vrc(t)], which is the mechanical response of the structure from the reemitted input, which is finally compared with the original input signal [Fig. 3(d)]. although the am-plitude of the reconstructed signal is smaller than that of the original input signal because of attenuation, and although there are several side bands because of the dis-persive nature of lamb waves, the shape of the main mode of the reconstructed signal, where most of lamb wave energy is contained, remains identical to the origi-nal input signal. The reconstructed signal is scaled so that the shape of the main mode in the reconstructed signal can be quantitatively compared with that of the original input signal. note that the reconstructed signal is symmetric with respect to the main peak as long as a symmetric input is applied, regardless of the symmetry of the host structure.

The proposed debonding detection technique is based on the premise that, if the pZT transducer were partially or fully debonded from the host structure, the time revers-ibility and symmetry of the reconstructed signal’s main mode would break down, because free vibration of the debonded pZT region appears during the initial excitation [step 1 in Fig. 3(a)] and reemission [step 3 in Fig. 3(c)] steps. Therefore, the pZT debonding can be identified by examining the deviation of the reconstructed signal’s main mode from the original input signal as shown in Fig. 3(d). The theoretical analysis done by Tong et al. [12] also sub-stantiates our finding that the vibration of the pZT trans-ducer at the debonded region is not coupled with that of the host structure.

2019lee and sohn: piezoelectric transducer self-diagnosis

Fig. 3. a schematic of the time reversal-based pZT transducer debonding detection, which consists of four steps: (a) excitation, (b) measurement of the mechanical response, (c) reemission of the time-reversed and scaling of the mechanical response, and (d) measurement of the reconstructed signal.

To quantify the deviation of the reconstructed signal’s main mode from the original input waveform, the sym index is used here [13]. Here, the sym index is defined at each driving frequency as (3), see above, where l[k] and r[k] denote the discrete version of the left-hand and right-hand sides of the reconstructed signal’s main mode with respect to the center of the main mode as shown in Fig. 4. M0 is the center time point of the main mode, and Ml and Mr represent the starting and ending time points of this time interval, respectively. If the shape of the recon-structed signal’s main mode is perfectly symmetric, the sym index becomes zero. note that the determination of the driving frequency is important but can be difficult in real applications. Therefore, the sym index values are computed for a range of driving frequencies from 100 to 200 kHz rather than at a single driving frequency for the experimental results presented later. The main advantage of this sym index is that this index is defined using only the current data set; it does not rely on direct comparison with previously obtained baseline data. consequently, it is less sensitive to external temperature variation and struc-tural condition changes. our previous numerical study [9]

showed that the pZT debonding disturbs the Trp, as shown in Fig. 5.

next, an outlier analysis is performed on the sym in-dex to automate the pZT debonding identification process. because the sym index can have a value only between 0 and 1, a β distribution is used to model the statistical distribution of the sym index [14].

ca b

a bSYM = -- -1

11 1

B( , )( ) ,x x (4)

where b(∙), x, α, and β are the β function, the confidence level, and two positive shape parameters of the β distribu-tion, respectively. note that α and β are estimated from the sym index values obtained from the intact pZT at room temperature. Using this model, a threshold value (χsym) corresponding to a one-sided 99.9% confidence in-terval at the upper tail of the distribution is computed. When the sym index value exceeds the threshold value, the pZT transducer associated with the sym index is classified as debonded.

C. MRP Index for PZT Crack Identification

In this subsection, another pZT transducer self-diagno-sis index for pZT cracking detection is proposed. The pre-vious work on lamb wave tuning curves [15], [16] shows that the amplitude plot of lamb wave modes with respect to the driving frequency moves horizontally as the pZT size changes. because pZT cracking essentially results in pZT size variation, the lamb wave tuning curves are expected to change accordingly. From this concept, it is conceived to use the power of the generated lamb wave signal for crack detection. To compute the power of the lamb wave signal, the output signal measured in the sec-ond step of the Trp [Fig. 3(b)] is first divided into two parts in the time domain as shown in Fig. 6: 1) the input


SYM [ ] [ ] [ ]= - × -ìíïïï

îïïï

üýïïï

þïïï

( )= =å1 2 0

22

0 0

L R LL L

k M k kk M

M

k M

M

åå å× ( )ìíïïï

îïïï

üýïïï

þïïï=

RR

[ ]kk M

M2

0

(3)

Fig. 4. definition of main mode, sidebands, l[k], r[k], Ml, M0, and Mr.

Fig. 5. comparison of the input and reconstructed signals obtained from the numerical simulations of three different pZT transducer conditions: (a) intact condition, (b) debonded condition, and (c) cracked condition.

signal and the direct response of the pZT when the in-put voltage is applied to the pZT, and 2) the reflections from the boundaries. The power of the second part of the output signal, which is the scaled mechanical response (sF∙vp[k]), is normalized by the maximum value of the squared input voltage in the output signal (sF∙vi[k]). The corresponding mrp index for the pZT cracking detection is described as

MRPmax

SF

max SF

o

o

p

i

S

E

S

E

( , )[ ]

[ ]

[ ]w A

v k

v k

v k

v

k MM

k MM

={ }

=×

×

= =å å2

2

2

[[ ]

[ ]

[ ],

k

v k

v k

k MM

2

2

2

{ }

={ }

=å p

i

S

E

max

(5)

where Ms and ME represent the starting and ending time points of the measured mechanical response in the output signal (i.e., the second part of the output signal), respec-tively.

Temperature variation and changing structural condi-tions such as structural damage mainly affect the over-all response power level, moving the corresponding mrp index plot vertically. on the other hand, pZT cracking shifts the mrp index plot horizontally as shown in Fig.

7(a). Therefore, a pZT crack can be readily distinguished from temperature and structural condition variations.

To identify the pZT cracking automatically, a mrp index-based classifier is developed here. To remove the vertical shift caused by changing temperature and struc-tural conditions, the mrp index plot is first normalized with respect to its own maximum value so that the nor-malized mrp (nmrp) index value becomes between 0 and 1. Then, the absolute differences between the nmrp index values obtained from the current data and the base-line data are computed, summed, and compared with a pre-determined threshold value as shown in Fig. 7(b). To compute the threshold value, nmrp index values are first computed using the data sets numerically obtained from the intact pZT at 24°c and the 20% cracked pZT under three different temperature conditions. Then, a β distri-bution is fitted to the nmrp values similar to the sym index classifier [14]. Here, 20% pZT cracking was used to establish the threshold value with the assumption that 20% pZT cracking is the minimum pZT defect with which users are concerned.

III. Experiment

In this section, two separate experiments were per-formed to validate the proposed pZT self-diagnosis tech-niques under varying temperature and changing structural conditions, respectively.

A. Experiments Under Varying Temperature

an aluminum plate of 455 × 254 × 3 mm was selected because it could fit into the temperature chambers avail-able. a single pZT transducer was attached in the middle of the plate using permabond 820 cyanoacrylate adhesive from permabond llc (pottstown, pa). The operating temperature of this adhesive is from −60°c to 200°c.

Fig. 8 shows three different pZT transducer conditions investigated in the experimental studies. Fig. 8(a) shows the intact pZT transducer (20 × 20 × 0.508 mm). In


Fig. 6. a schematic of the mrp index calculation used for the pZT crack detection.

Fig. 7. pZT crack detection using the mrp index plot obtained from numerical simulations: (a) the mrp index plots obtained from intact and cracked pZTs at three different temperature conditions and (b) the sum of the normalized mrp (nmrp) index differences between the current and baseline data. note that the baseline mrp index plot was obtained from the intact pZT at 24°c. The threshold was computed from the sum of nmrp index differences between the intact pZT at 24°c and the 20% cracked pZT under three different temperature conditions.

Fig. 8(b), a 4 × 20 mm commercial Teflon tape was par-tially inserted between the pZT transducer and the plate to simulate a 20% debonded pZT condition. after the bonding layer was cured for 24 h, the inserted tape was removed. Fig. 8(c) shows the pZT transducer cracked by a razor blade. note that, to minimize other variations in the experiments, only a single pZT transducer was used to realize all three pZT conditions. First, the experiments with the debonded pZT transducer were performed. next, the debonded area of the pZT transducer was filled in with the adhesive to create the intact condition. Finally, the pZT size was reduced to 16 × 16 mm to replicate a 36% cracked pZT condition. For each pZT condition, experiments were conducted at three different tempera-ture values by inserting the specimen into the temper-ature chambers. To minimize test-to-test variation, the same experiment was also repeated three times under each temperature condition. For each temperature experiment, data were collected after waiting two hours to stabilize the temperature of the specimen.

Waveforms applied to the pZT transducer were gener-ated by an arbitrary waveform generator (aWG) which had 16-bit resolution and 100 ms/s sampling rate. Then, the self-sensing circuit was built on a bread-board with a commercial capacitor. Finally, the input and output signals were measured by a signal digitizer (dIG) that supported 14-bit resolution and 100 ms/s sampling rate. The operation of the aWG and the dIG was controlled by commercial software, labVIEW (national Instruments corp., austin, TX). Fig. 9(a) shows the experimental set-up used in this study. Without using any additional low-pass filter or power amplifier, the same excitation signal

was applied 10 times, and the corresponding signals were averaged in the time domain to improve the signal-to-noise ratio. a time interval of about 5 s was taken between two subsequent input excitations to minimize vibration interference among multiple excitations. a commercial refrigerator and an isotemperature oven from Fisher sci-entific (Waltham, ma) were used to simulate −5°c and 53°c temperature conditions as shown in Fig. 9(b) and (c), respectively.

Fig. 10(a) illustrates that the frequency-swept sym index plot can be effective to detect debonding of the pZT under varying temperature. a threshold value was determined using 11 sym index values obtained from the intact pZT at 24°c. Then, outlier analysis using the sym index is performed in Fig. 10(b). no temperature variation produced false-positive alarms of pZT debond-ing.

next, the mrp index was applied to experimental data to indentify pZT cracking. Fig. 11(a) shows that the mrp index moves vertically with respect to temperature and shifts horizontally because of the pZT transducer size change. particularly, pZT cracking results in pZT size decrease and subsequently moves the mrp index to the right. Therefore, pTZ cracking can be successfully identi-fied by observing the horizontal shift of the mrp index. note that the output responses were processed with a con-tinuous wavelet transform (cWT) [1], [17] for noise reduc-tion before computing the mrp index plot.

Finally, the pZT crack damage classifier is applied to the experimental data. Each mrp index plot was nor-malized with respect to its own maximum value. Then, the absolute differences between the nmrp index values


Fig. 8. Three different pZT conditions investigated in the experimental studies: (a) intact condition, (b) debonded condition, and (c) cracked condi-tion.

Fig. 9. Experimental setup and the temperature chambers used for temperature experiments: (a) experimental setup, (b) a refrigerator for the −5°c condition, and (c) an oven for the 53°c condition.

obtained from the current data and baseline data were computed, summed and plotted as shown in Fig. 11(b). note that the baseline nmrp index plot was experimen-tally obtained from the intact pZT condition at 24°c. Fig. 11(b) shows that the proposed classifier successfully identifies the cracked pZT under varying temperature us-ing the pre-determined threshold value obtained from the numerical simulations.

B. Experiments Under Changing Structural Conditions

Two aluminum beams of 915 × 102 × 3 mm were con-nected with six bolts and nuts as shown in Fig. 12. a

single pZT transducer was attached to the bottom beam using the same adhesive previously used in the tempera-ture tests. The rest of test setup remained the same as the previous temperature experiments unless mentioned otherwise.

as shown in Fig. 8, three different pZT transducer con-ditions were prepared in the same manner as before, this time with increased severity of 50% debonding and 50% cracking. First, the experiment with the 50% debonded pZT transducer was performed, and then the debonded area of the pZT transducer was filled with the adhesive to create the intact condition. next, the pZT size was reduced to 10 × 20 mm to replicate the 50% cracked pZT


Fig. 12. The experimental setup for measuring the sym and mrp indices under changing structural conditions: (a) the configuration and dimension of the two-layered beams including the surface-bonded pZT and (b) the bolted joint and the implemented pZT.

Fig. 10. (a) sym index plots experimentally obtained under varying temperatures: The debonded pZT under varying temperature was clearly identi-fied. (b) an outlier analysis of the sym index plots. The baseline data were experimentally obtained from the intact pZT at 24°c. note that intact and cracked conditions did not produce any outliers under any temperature condition investigated.

Fig. 11. (a) mrp index plots experimentally obtained under varying temperature: The cracked pZT was clearly indicated by the horizontal shift of the mrp index peak. (b) The sum of the nmrp index differences between current and baseline data. The threshold value was predetermined from numerical simulations. note that the nmrp index plot experimentally obtained from the intact pZT condition at 24°c was used as the baseline data.

condition. For each pZT condition, experiments were con-ducted under four different structural conditions: 1) with-out a notch or a lubricant; 2) without a notch, but with a lubricant; 3) With a 1-mm-thick notch, but without a lubricant; and 4) with a 2-mm-thick notch, but without a lubricant. at each structural condition, the number of loosened bolts was varied between 0 and 6, for a total of 28 different structural conditions that were investigated. similar to the temperature test, the same experiment was also repeated three times under each structural condi-tion.

The same Trp experiments were repeated for a total of 84 different test cases (3 pZT conditions × 28 struc-tural conditions), covering various changing structural conditions. note that only 36 representative cases were presented here for simplicity. Fig. 13 shows that various changing structural conditions had only a small effect on the sym index values. similar to the previous tempera-ture test, the reconstructed signal from the debonded pZT significantly deviated from the original input signal and the corresponding sym index values were much larger than those of the intact and cracked pZT conditions. note that changing structural conditions and the cracked pZT condition did not affect the symmetry of the reconstructed signal’s main mode obtained from the Trp. once again, the outlier analysis was performed, and the baseline data

were obtained from the intact pZT and initial structural conditions without any loosened bolts, notches, or lu-bricant. Fig. 14 shows that no false-alarms were flagged from the intact pZT condition regardless of the changing structural conditions; however, some outliers associated with the cracked pZT were observed. It is speculated that these outliers are associated with occasional unintended debonding of the pZT.


Fig. 14. an outlier analysis of sym index plots shown in Fig. 13. The baseline data was obtained from the intact pZT and initial structural condition without any loosened bolts, notch, or lubricant.

Fig. 13. sym index plots experimentally obtained under changing structural conditions: the debonded pZT was clearly identified from the sym index plots under changing structural conditions. (a) Without a notch and a lubricant, (b) without a notch and with a lubricant, (c) with a 1-mm-thick notch and without a lubricant, and (d) with a 2-mm-thick notch and without a lubricant.

Fig. 15 shows that the mrp index moves vertically according to changing structural conditions and shifts horizontally because of the pZT transducer size change. Therefore, the pZT cracking can be successfully identified by observing the horizontal shift of the mrp index under changing structural conditions.

similar to Fig. 11(b), Fig. 16 shows that the pro-posed classifier for pZT cracking detection is also ef-fective under changing structural conditions. note that the nmrp index plot experimentally obtained from the intact pZT condition without a notch and a lubricant was used as the baseline data and the same thresh-old value obtained from the numerical simulations was again applied.

note that the sensitivity of the proposed self-diagnosis technique to pZT crack and debonding size was experi-mentally and numerically examined in [9]. However, it may be difficult to generalize these findings to different structures because each experiment is unique.

IV. conclusion

In this study, pZT transducer self-diagnosis schemes were developed to detect defects, especially debonding and cracking, in wafer-type pZT transducers commonly

used for guided wave-based sHm and ndT applications. Two pZT transducer self-diagnosis indices, which are ef-fective under changing temperature and structural condi-tions, were proposed and examined. pZT debonding and cracking conditions were detected successfully using the sym and mrp indices with the corresponding classifiers, respectively. The uniqueness of this study is that pZT de-fects can be differentiated from temperature and structur-al variations, and the experimental studies show that the proposed pZT self-diagnosis techniques can minimize false alarms which can be generated by changing temperature and structural conditions. Furthermore, ongoing effort is underway to determine an appropriate threshold value without use of numerical simulations, and additionally to validate the feasibility of the proposed pZT self-diagnosis under changing temperature and structural conditions si-multaneously.

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Sang Jun Lee received his b.s. and m. s. de-grees in mechanical and aerospace engineering from seoul national University, seoul, Korea, and his ph.d degree in civil and environmental engi-neering from carnegie mellon University, pitts-burgh, pa, in 2002, 2004, and 2009, respectively.

currently, he is a postdoctoral fellow in school of Electrical and computer Engineering at Geor-gia Institute of Technology working on developing ultrasonic structural health monitoring systems.


Fig. 16. The sum of the nmrp index differences between current and baseline data. The threshold value was determined from numerical simulations. note that the nmrp index plot experimentally obtained from the intact pZT and the initial structural condition was used as the baseline data. (a) Without a notch and a lubricant, (b) without a notch and with a lubricant, (c) with a 1-mm-thick notch and without a lubricant, and (d) with a 2-mm-thick notch and without a lubricant.

Hoon Sohn received the b.s. and m.s. degrees from seoul national University, seoul, Korea, and the ph.d. degree from stanford University, stan-ford, ca, in 1992, 1994, and 1999, respectively, all in civil engineering.

He joined los alamos national laboratory (lanl) as a director-funded postdoctoral fellow (1999–2001), and he was a technical staff mem-ber from 2001 to 2004. He joined the faculty of the civil and Environmental Engineering (cEE) department, carnegie mellon University, pitts-

burgh, pa, in august 2004. currently, he is with the department of cEE at Korea advanced Institute of science and Technology (KaIsT) as an associate professor. For the last fifteen years, his research interest

has been in the area of structural health monitoring and sensing tech-nologies. He has published more than 65 refereed journal articles, 180 conference proceedings, and three book chapters. He and his colleagues have been offering a three-day short course entitled “structural Health monitoring Using statistical pattern recognition” for the last five years at various locations.

dr. sohn won the best paper award at the 2003 spIE annual In-ternational symposium on non-destructive Evaluation for Health moni-toring and diagnostics conference for his paper entitled “Utilizing the sequential probability ratio Test for building Joint monitoring.” He received the young scientists award from Korean ministry of science and Technology with the presidential citation and the Incentive re-search Grant in 2008.


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Piezoelectric Transducer Self-Diagnosis Under Changing