broadband electrical impedance matching for broadband electrical impedance matching for...

IEEE TransacTIons on UlTrasonIcs, FErroElEcTrIcs, anD FrEqUEncy conTrol, vol. 58, no. 12, DEcEmbEr 2011 2699

0885–3010/$25.00 © 2011 IEEE

Broadband Electrical Impedance Matching for Piezoelectric Ultrasound Transducers

Haiying Huang, Member, IEEE, and Daniel Paramo

Abstract—This paper presents a systematic method for de-signing broadband electrical impedance matching networks for piezoelectric ultrasound transducers. The design process in-volves three steps: 1) determine the equivalent circuit of the unmatched piezoelectric transducer based on its measured admittance; 2) design a set of impedance matching networks using a computerized Smith chart; and 3) establish the simu-lation model of the matched transducer to evaluate the gain and bandwidth of the impedance matching networks. The ef-fectiveness of the presented approach is demonstrated through the design, implementation, and characterization of impedance matching networks for a broadband acoustic emission sensor. The impedance matching network improved the power of the acquired signal by 9 times.

I. Introduction

Piezoelectric transducers enjoy wide applications in areas such as nondestructive evaluation (nDE) [1],

structural health monitoring (sHm) [2], biomedical imag-ing [3], energy harvesting [4], [5], etc. Piezoelectric trans-ducers are inherently narrowband, i.e., they only display large response at the resonant frequencies. For many ap-plications (e.g., acoustic emission detection and medical imaging), however, broadband operation is highly desired. acoustic impedance matching (aIm) is a common prac-tice adopted to improve the otherwise narrowband opera-tion of the piezoelectric transducers [6]–[9]. by implement-ing multiple piezoelectric transducers and providing aIm, broadband ultrasound transducers can be realized. The electrical impedances of these broadband transducers, however, are usually rather high and are mainly capaci-tive. Therefore, there is an impedance mismatch between the transducer and the interface devices, such as the signal source or the data acquisition device, which usually have an impedance of 50 Ω. The development of wireless ultra-sound sensors also requires the impedance matching of the piezoelectric sensor and the wireless transponder, which usually has an input impedance of 50 Ω [10]. To maxi-mize the power transfer between the ultrasound transduc-er and these devices, an electrical impedance matching (EIm) network is needed. There are many publications on aIm design for ultrasound transducers, but EIm de-sign for piezoelectric ultrasound transducers has received little attention. most of the published work on EIm for ul-

trasound transducers only presented impedance matching (Im) at one resonant frequency using a simple network, such as an lc network or a shunt inductor/capacitor [11]–[15]. These simple networks, however, cannot achieve broadband EIm. Even though an FET-based preamplifier is commonly used for Im of piezoelectric ultrasound sen-sors, the passive Im circuit is more attractive for embed-ded sensor applications in which the power consumption of the sensor is of critical importance.

Unlike an lc network, whose components can be uniquely determined once the network topology is cho-sen, a broadband EIm network can have multiple different choices for the component values. In addition, the band-width of the impedance-matched transducer can only be determined after the design of the Im network is finished. Given these considerations, a simulation model of the impedance-matched transducer is needed for iterative de-sign and for the selection of the optimal Im network [16], [17]. To establish such a simulation model, however, the equivalent circuit of the unmatched ultrasound transducer must be determined first. There are three popular equiva-lent circuits for a piezoelectric ultrasound transducer: the Klm model [18], [19], the network model [15], [20], and the butterworth-Van Dyke (bVD) model [21]. The Klm model requires the knowledge of the transducer’s physical parameters (e.g., size and thickness) as well as the proper-ties of the bonding layer. Therefore, it is more suitable for the mechanical design of the transducer. The mechanical impedance at the opposite side of the crystal also has a significant effect on sensor performance which is difficult to model. both the network model and the bVD model can be determined from the measured impedance or ad-mittance of the transducer without knowing the physical details. For simulation purposes, however, the bVD model is more straightforward because it is represented with lumped-element components. moreover, parameter identi-fication algorithms have been developed to determine the component values at one resonance of the piezoelectric transducers [21], [22]. although Kim et al. [23] presented an easy model that represents an ultrasound transducer with multiple resonances, they identified the component values by visual inspection instead of through a computer-ized parameter identification process.

In this paper, we extend the single-frequency bVD model to account for the multiple resonances of a broad-band ultrasound transducer. a parameter identification procedure was developed to determine the component values of the extended bVD model using the nonlinear regression fitting of the measured admittance over a wide frequency range. This extended bVD model is combined

manuscript received July 28, 2011; accepted september 26, 2011. This work was supported by the Texas nHarP program.

The authors are with the mechanical and aerospace Engineering De-partment, The University of Texas at arlington, arlington, TX (e-mail: [email protected]).

Digital object Identifier 10.1109/TUFFc.2011.2132

IEEE TransacTIons on UlTrasonIcs, FErroElEcTrIcs, anD FrEqUEncy conTrol, vol. 58, no. 12, DEcEmbEr 20112700

with the broadband Im networks synthesized using a com-puterized smith chart to establish the equivalent circuit of the matched transducer, from which the gain and the bandwidth of different Im networks can be simulated. a 5-component Im network and a T-network were designed for a broadband acoustic emission (aE) sensor and fab-ricated using commercially available components. The performance of the impedance-matched aE sensor was characterized using an ultrasound pitch-catch system and pencil-lead break tests. both the simulation and experi-ment results indicated that the 5-component Im network has a wide bandwidth and is less sensitive to component and transducer variability. by implementing the Im net-work, the power received by the aE sensor is increased by 9 times.

II. Design Process

an overview of the design process is shown in Fig. 1. after the admittance of an unmatched ultrasound trans-ducer is measured, a two-step nonlinear regression proce-dure is first applied to determine the component values of the equivalent circuit for the unmatched transducer. In addition, the center frequency and the corresponding transducer admittance are determined from the measured admittance, based on which the Im networks are designed. next, the equivalent circuit and the Im network are com-bined to establish the equivalent circuit of the matched transducer. computer simulations can then be carried out to evaluate the gain, the bandwidth, and the sensitivity of the Im networks. based on these simulations, the design of the Im network can be finalized. The admittance of an ultrasound transducer can be measured using commer-cially available equipment, such as an impedance analyzer or a vector network analyzer (Vna), or time-domain mea-surements [24], [25]. We will not discuss the admittance measurement here. The rest of the design process is dis-cussed in the following subsections.

A. Equivalent Circuit Parameter Identification

The single-frequency bVD model, as shown in Fig. 2(a), has four lumped-element components: a resistor R, a capacitor C, an inductor L, and a clamping capacitor C0. The equivalent circuit of the piezoelectric ultrasound transducer with multiple resonances can be established by connecting multiple single-frequency bVD circuits in parallel, with each bVD circuit corresponding to a specific resonance, as shown in Fig. 2(b). as a result, the admit-tance of the extended bVD model is calculated as

Y Y R L C Cii N

i i i iext = ( )=∑ , , , ,0 (1)

where Yi(Ri, Li, Ci, C0i) are the admittances of the single-frequency bVD circuits. To determine the component values (Ri, Li, Ci, C0i), a two-step parameter identification

process was developed. First, the component values of the single-frequency bVD circuits must be determined. The admittance of a single-frequency bVD circuit can be cal-culated as

Yj C RC C LC C

R C j LCii i i i i i i

i i i i=

− − ++ −

ω ω ω ωω ω

20 0

2

21

1( )( )

( ), (2)

where ω = 2πf is the angular frequency. as shown in Fig. 3, the admittance of a single-frequency bVD circuit dis-plays two resonances. at the series resonance, the magni-tude of the admittance is the largest. Therefore, the series angular frequency can be found by setting the imaginary part of the denominator of (2) to zero, i.e.,

ωsii iL C

=⋅

1, (3)

where ωsi = 2πfsi is the angular frequency at the series resonance frequency fsi. at ω = ωsi, (2) is reduced to

Y R j Ci ii

i i( ) .ω ωs s= +1

0 (4)

Therefore, Ri can be calculated from the real part of Yi(ωsi), i.e., the conductance:

RYii i

=ℜ

1[ ( )]

.ωs

(5)

Fig. 1. overview of the impedance matching network design process.

Fig. 2. butterworth-Van Dyke model of piezoelectric ultrasound trans-ducer to account for (a) a single resonant frequency and (b) multiple resonant frequencies.

huang and paramo: broadband electrical impedance matching 2701

similarly, C0i is calculated from the imaginary part of Yi(ωsi), i.e., the susceptance:

CY

ii i

i0 =

ℑ[ ( )].

ωω

s

s (6)

at the parallel resonance, the magnitude of the admit-tance is the smallest. Therefore, setting the real part of the numerator of (2) to zero results in

C C LC Ci i i i i ii

i= − = −

0

20

2

21 1( ) .ωωωp

p

s (7)

Finally, the inductor Li is calculated from (3) as

LCii i

=12ωs

. (8)

because the four components are determined from the admittances at the series and parallel resonant frequen-cies only, the admittances of the bVD circuit calculated from these four values may not match with the actual admittances at the other frequencies. To fine-tune the es-timated component values, a nonlinear regression process is adopted to minimize the errors between the admittance calculated from (2) and the measured admittance, using the component values calculated from (5)–(8) as the ini-tial guess. This nonlinear regression can only be carried out over a frequency range that contains one resonance peak. To determine the components for an admittance curve containing multiple resonances, the measured ad-mittance must be divided into multiple sub-sections, with each subsection containing a single resonance peak. The component values determined from the sub-sections are then used as the initial guesses for a second nonlinear regression fitting process for the entire frequency range, which determines the component values for the extended bVD model.

B. Impedance Matching Circuit Design

according to the impedance matching theory, maxi-mum power is delivered from a source to a load if the load

impedance is a complex conjugate of the source imped-ance. If the load impedance does not meet this criterion (i.e., the load and the source are unmatched), a two-port Im network, with its input impedance at port #1 conju-gate matched to the source impedance and its output im-pedance at port #2 conjugate matched to the load imped-ance, is needed to maximize the power transfer from the source to the load (see Fig. 4). a smith chart is a powerful tool to synthesize such an Im network (smith V3.10, avail-able: http://www.fritz.dellsperger.net/downloads.htm). In the case of matching an ultrasound transducer, the source impedance is the impedance of the ultrasound transducer, which is likely to be found at the far right end of the smith chart (see Fig. 5). The load impedance is usually 50 Ω, which is located at the center of the smith chart. The purpose of the Im network is, therefore, to move the source impedance to the 50 Ω impedance point by adding capacitors/inductors in series or in parallel. an inductor in parallel moves the impedance point along the constant resistance curves, whereas a capacitor in series moves the impedance point along the constant conductance curves. The path connecting the original impedance point and the new impedance point depends on the component value for a given frequency. To control the bandwidth of the Im network, the inductances/capacitances should be kept under certain values so that the paths connecting the transducer impedance and the 50 Ω impedance point are confined within a given quality factor, Q. The lower the Q value is, the larger the bandwidth will be. on the

Fig. 3. admittance of a butterworth-Van Dyke circuit with a single resonant frequency.

Fig. 4. Two-port complex electrical impedance matching.

Fig. 5. Design impedance matching network using a smith chart.


other hand, a lower Q value mandates short paths and thus requires adding more components to reach the 50 Ω impedance point. Therefore, the selection of Q is a trade-off between the desired bandwidth and the complexity of the Im network. Under a given Q, there are multiple Im networks of different topologies that can meet the design criterion. These Im networks, however, are likely to have different bandwidths. as a result, the final selection of the appropriate Im networks must rely on the computer simulations. For more detailed discussions of smith charts and EIm, the readers should consult [26].

C. Computer Simulation of Matched Ultrasound Transducer

The final design step involves combining the extended bVD model with a particular Im network to establish the equivalent circuit for the matched ultrasound transducer. once the equivalent circuit is established, circuit simula-tion software with ac simulation capability, such as the open-source quite Universal circuit simulator (qUcs, available: http://qucs.sourceforge.net/) or Pspice (ca-dence Design systems, san Jose, ca), can be utilized to calculate the frequency response of the matched transduc-er. The gain of the Im network can then be calculated as the ratio between the frequency response of the matched transducer and that of the unmatched transducer, from which the bandwidth of the Im network can be deter-mined. In addition, the sensitivity of the Im networks to parameter variations, such as deviations in the component values and the source impedance, can also be investigated.

III. Design results and Discussions

The complex admittances of a broadband aE sen-sor with a specified operating frequency range of 150 to 400 kHz (r50α, Physical acoustics corp., marcus Hook, Pa), bonded on an aluminum channel using super Glue (super Glue corp., rancho cucamonga, ca), were mea-sured with the help of a Vna with a port impedance of 50 Ω (Zl3, rohde & schwarz International, munich, Ger-many). The measurements were averaged over 20 sweeps and smoothed with a 1% aperture. as shown in Fig. 6(a), the admittance displayed three resonance peaks. The one at 150 kHz has a relatively high admittance whereas the other two, at around 320 and 525 kHz, have similar admit-tance magnitudes. Fig. 6(b) shows the frequency spectrum of an aE signal, generated by breaking a 0.5-mm H2 pen-cil lead at a distance of 0.05 m from the aE sensor and acquired using an oscilloscope with a 50 Ω coupling. The

frequency spectrum of the aE signal displays a large peak at around 320 kHz and a small peak at around 150 kHz which match well with the two resonant frequencies identi-fied from the measured admittance. The signal strength at 320 kHz is about twice as high as that at 150 kHz. In ad-dition, the majority of the signal is concentrated between 200 and 600 kHz. considering the large impedance mis-match and the large sensor response around 320 kHz, the center frequency of the Im network was therefore chosen to be 320 kHz to maximize the benefit of the Im network. at 320 kHz, the complex admittance of the aE sensor is 0.6 + j0.63 ms or 791 − j840 Ω in impedance.

a maTlab program (The mathWorks, natick, ma) was developed to extract the component values of the ex-tended bVD model from the measured admittance. Three frequency ranges, i.e., 100 to 200 kHz, 260 to 400 kHz, and 400 to 600 kHz, were selected for the parameter identifica-tion of the single-frequency bVD circuits. The component values of the single-frequency bVD model calculated from (5)–(8) and those determined using the maTlab non-linear regression function, nlinfit, are shown in Table I. The component values of the extended bVD model, again determined using the maTlab nonlinear regression func-tion nlinfit, are also shown in Table I. notice that L3 and C3 determined by the equations and the single-frequency bVD model are negative. This is due to the selection of frequency range of 400 to 600 kHz, which resulted in a lower parallel frequency than the series frequency. chang-ing the frequency range, e.g., to 500 to 700 kHz, will cor-rect this mistake. nonetheless, these negative values did not cause a problem for the second nonlinear regression process, which produced positive L3 and C3 values. The conductance and susceptance of the unmatched transduc-er, calculated from the single-frequency and the extended bVD models, are compared with their measured coun-terparts in Fig. 7. Even though the nonlinear regression was performed on the magnitude of the admittance only, both the conductance and susceptance calculated from the

Fig. 6. Unmatched acoustic emission (aE) sensor: (a) measured admit-tance and (b) frequency spectrum of measured aE signal generated us-ing pencil-lead break.

TablE I. component Values of Equivalent circuit of Unmatched acoustic Emission sensor.

(R1, L1, C1, C01) (R2, L2, C2, C02) (R3, L3, C3, C03)

From (5)–(8) 336 Ω, 1.4 mH, 0.8 nF, 0.13 nF 1684 Ω, 2.5 mH, 97 pF, 0.38 nF 2859 Ω, −1 mH, −94 pF, 0.24 nFsingle resonance 298 Ω, 5.4 mH, 0.2 nF, 0.3 nF 1684 Ω, 8.8 mH, 26 pF, 0.24 nF 2849 Ω, −1.3 mH, −0.16 pF, 0.13 nFmultiple resonances 298 Ω, 5.4 mH, 0.2 nF, 0.13 nF 1684 Ω, 5.8 mH, 44 pF, 87 pF 2849 Ω, 4.0 mH, 23 pF, 18 pF


extended bVD model matched well with the measured values. This indicates that the equivalent circuit is a rea-sonable representation of the ultrasound transducer.

because the admittance of the unmatched transducer at 320 kHz has a Q value of 1.06, the Im network was designed with the constraint of Q = 2, which led to an estimated bandwidth of 225 to 375 kHz. In addition, a maximum number of five components was imposed by the open-source software, smith v3.10. Under these con-straints, two 5-component Im networks, i.e., networks a [Fig. 8(a)] and b [Fig. 8(b)], were realized. For compari-son, a 4-component network-c [Fig. 8(c)], a T-network [Fig. 8(d)] with a constraint of Q = 5, and an l-network with no constraint of Q [Fig. 8(e)], were also designed. The topologies and component values of these Im networks are shown in Fig. 8. The simulation model for the unmatched aE sensor is shown in Fig. 9(a). The clamping capacitors C0i were combined to form a single clamping capacitor C0 because they are connected in parallel. To calculate the frequency response of the unmatched aE sensor, an ideal ac source with a normalized amplitude of 1 V are specified. The frequency response was measured across the 50 Ω load by sweeping the frequency of the ac source over a frequency range of 100 to 750 kHz with 5001 fre-quency points. The frequency response of the unmatched transducer, as shown in Fig. 9(b), displays three resonant peaks that match well with those of the measured admit-tance. The simulation model for the matched aE sensor was established by simply inserting the Im network be-tween the equivalent circuit of the unmatched transducer and the 50 Ω load.

The gains of the Im networks, defined as the ratio be-tween the frequency responses of the matched and the

unmatched transducers, are compared in Fig. 10. network a [the 5-component network shown in Fig. 8(a)] has the highest gain over the widest frequency range. The maxi-mum gain was not obtained at the center frequency, i.e., 320 kHz. rather, the gains are higher at the frequencies near the center frequency, at which the ultrasound trans-ducer has smaller admittance. because the impedance mismatches between the transducer and the 50 Ω load at these frequencies are larger, the Im network increased the power transfer the most. The T-network has a similar gain as network a around 300 kHz but has a much nar-rower bandwidth. The simple l-network displayed a much lower gain than the more complicated Im networks. These simulation results confirm the importance of selecting the proper Q constraint for broadband Im network design.

IV. Hardware Implementation and characterization

For comparison purpose, both network a and the T-network were implemented using surface mount induc-tors and through-hole capacitors. These components are soldered on a surface mount prototype board with sma connectors for both ports. To characterize the Im net-works, an ultrasound pitch-catch system with a second aE sensor bonded at a distance of 0.1 m from the first aE sensor, was implemented. Five different configura-tions were tested (see Table II). The first configuration,

Fig. 7. nonlinear regression fitting results of measured (a) conductance and (b) susceptance.

Fig. 8. Different impedance matching networks designed with Q con-straint: (a) network a, (b) network b, (c) network c, (d) T-network, and (e) l-network.

Fig. 9. (a) lumped-element model of the unmatched acoustic emission (aE) sensor and (b) the simulated frequency response showing three resonant frequencies.

Fig. 10. simulated voltage gains of an impedance-matched transducer compared with an unmatched transducer.


with both the actuator and the sensor unmatched, serves as the baseline configuration that the other configura-tions can be compared with. For configurations 2, 3, and 4, either the actuator or the sensor was impedance matched and the matched transducer was tested with both network a and the T-network. For the last configu-ration, as shown in Fig. 11, the actuator aE#2 was con-nected to the signal generator (DG1022 rigol Technolo-gies Inc., oakwood Village, oH) through the T-network while the sensor aE#1 was connected to the oscilloscope (WavePro 760Zi, lecroy corp., chestnut ridge, ny) through network a. both the signal generator and the oscilloscope were configured to have an internal imped-ance of 50 Ω. The excitation signal was a 6-cycle burst with a peak-to-peak amplitude of 5 V and a burst period of 10 ms. The received ultrasound signal was acquired without any averaging.

The measured admittance of aE#2 is slightly differ-ent from that of aE#1. because the Im networks were designed based on the measured admittance of aE#1, characterizing the Im networks with aE#2 allowed us to evaluate the robustness of the Im networks in response to the impedance variations of the aE sensors, which could be induced by temperature fluctuations or changing bond-ing conditions.

V. measurement results and Discussions

because of the availability of the commercial compo-nents, the actual component values used for assembling the Im networks may be slightly different from the design

values. In addition, an actual inductor must be treated as an ideal inductor in series with a resistor. The assem-bled components as well as their equivalent series resistor (Esr) were measured using an lcr meter. The actual component values, their Esrs, and the designed values are compared in Table III. The Esrs of the actual induc-tors are shown in the parentheses following the compo-nent values. The Esrs of the capacitors are negligible. The frequency responses of the actual Im networks were again simulated and compared with the ideal networks. as shown in Fig. 12, the effect of the component variations on the frequency responses is similar for network a and the T-network for frequencies below 250 kHz. between 250 and 400 kHz, the frequency response of network a is less affected by the component variations than that of the T-network. This effect is reversed between 400 and 600 kHz. beyond 600 kHz, the frequency response of net-work a is drastically altered by the component variations whereas the frequency response of the T-network remains unchanged. because the response of the aE sensor is con-centrated between 200 and 600 kHz, we estimated that the non-ideal components reduce the gain of the Im net-works by about 10 to 15%.

To characterize the assembled Im networks, the input and output admittances of the Im networks were mea-sured by connecting the corresponding ports to the aE sensor or to a 50 Ω load. The input admittances of the two networks, with port #2 connected to a 50 Ω load, are compared with the admittance of aE#1 in Figs. 13(a) and 13(b). as expected, the admittances of these networks around 320 kHz are the conjugates of the admittance of aE#1. Even through the conductance of the Im networks are different from that of aE#1 at other frequencies, the susceptance of the Im networks are close to the opposite of the aE#1 susceptance over a large frequency range. as a result, the susceptance of aE#1 is almost cancelled by the susceptance of the Im networks, which improves the power transfer. similarly, the output conductance of the Im networks, with their port #1connected to aE#1, is about 20 ms (50 Ω) at 320 kHz whereas the output susceptance is close to zero [see Fig. 13(c) and 13(d)]. The deviation of the measured impedances from the ideal conjugate matching is due to the non-ideal components.

TablE II. configurations of the Ultrasound Pitch-catch system.

configuration #1 #2 #3 #4 #5

actuator Unmatched Unmatched aE#2 Unmatched aE#1 matched aE#2 T-matched aE#2sensor Unmatched matched aE#1 matched aE#2 Unmatched aE#1 a-matched aE#1

Fig. 11. Ultrasound pitch-catch system test bed: aE#1 is impedance matched using network a and aE#2 is impedance matched using the T-network.

TablE III. Ideal and actual component Values for network a and the T-network.

components L1 (μH) L2 (μH) L3 (μH) C1 (nF) C2 (nF)

network a ideal 405 160 38.6 1.2 4.5network a actual 425 (14.2 Ω) 164 (8.1 Ω) 41 (7.8 Ω) 1.2 4.5T-network ideal 431 96 n/a 2.44 n/aT-network actual 426 (16.5 Ω) 95 (15.2 Ω) n/a 2.49 n/a

resistances given in parentheses are the equivalent series resistor for the assembled components.


nonetheless, these measurements validate the design and implementation of the Im networks.

The Im networks were characterized using the ultra-sound pitch-catch system first. Fig. 14 shows the volt-age gain of the Im networks for different pitch-catch con-figurations, using configuration #1 as the baseline (see Table II). The voltage gain is defined as the ratio between the amplitude of the signals acquired using a respective configuration and that acquired using configuration #1. When the unmatched aE#2 serves as the actuator and the matched aE#1 serves as the sensor, network a real-ized a voltage gain of about 3 over a frequency range of 250 to 500 kHz, whereas the T-network displayed a large voltage gain of 5 over a much narrower frequency range [see Fig. 14(a)]. These measured voltage gains are con-sistent with the simulation results shown in Fig. 10. The discrepancies between the measured and simulated volt-age gains are likely contributed to by the circuit board and the connecting traces, which were not accounted for in the simulation model. In addition, the equivalent circuit does not represent the transducer completely, as indicated by the small differences between the measured admittance

and the admittance predicted by the equivalent circuit (see Fig. 7). The voltage gain of the Im networks for con-figuration #3, i.e., the matched aE#2 serving as the sen-sor and the unmatched aE#1 serving as the actuator, is shown in Fig. 14(b). Even though the Im networks were designed based on the measured admittance of aE#1, network a achieved a similar performance for aE#2 as well. The T-network, however, displayed a much lower voltage gain at around 300 kHz for aE#2 but achieved a broader bandwidth. These experiment results indicate that network a is less sensitive to the source impedance variations whereas network-T is more sensitive. Using the matched aE#2 as the actuator and the unmatched aE#1 as the sensor produced similar voltage gains [see Fig. 14(c)], confirming that the Im networks were recipro-cal. When both the actuator and the sensor were matched, i.e., the actuator is the T-matched aE#2 and the sensor is aE#1 matched with network a, a voltage gain of 6 to 9 was realized between 250 and 500 kHz [see Fig. 14(d)]. The voltage gain could be further improved if both aE sensors were matched with network a.

The frequency spectra of the aE signals, generated by pencil lead breaks and acquired using an oscilloscope with a 50-Ω coupling are shown in Fig. 15 to compare the broadband responses of the unmatched and matched aE sensor. because it was difficult to produce repeatable aE signals using pencil lead breaks, the pencil lead was bro-ken at equal distances from both aE sensors so that one of the aE sensors could serve as the reference. First, the aE signals were acquired using the unmatched aE sen-sors. as shown in Fig. 15(a), the signal strength acquired by aE#1 is about 80% of that acquired by aE#2. Figs. 15(b) and 15(c) compare the aE signal acquired using aE sensors matched with network a, i.e., a-matched, with their unmatched counterpart. similar to the ultrasound pitch-catch experiment, the amplitudes of the aE signals

Fig. 12. comparison of frequency responses of impedance matching net-works with actual and ideal components.

Fig. 13. measured input and output admittance of impedance matching networks. (a) and (b): comparison of input admittance of 50-Ω loaded Im networks with the admittance of aE#1; (c) and (d): output admit-tance of network a and the T-network with port #1 connected to aE#1.

Fig. 14. measured voltage gains of impedance matching networks for ultrasound pitch-catch configuration: (a) #2, (b) #3, (c) #4, and (d) #5 using configuration #1 as the baseline (see Table II).


acquired using the matched aE sensor are about 3 times larger than those acquired using the unmatched aE sen-sors. In addition, the broadband characteristics of the aE sensors are not affected by the implementation of network a. The T-network, however, appears to reduce the band-width of the aE signal slightly, as shown in Fig. 15(d).

VI. conclusions

We have developed a systematic approach to design broadband Im networks for piezoelectric ultrasound transducers. Two Im networks for a broadband aE sen-sor were designed and implemented. The performances of the impedance-matched aE sensors were characterized us-ing both an ultrasound pitch-catch system and pencil-lead break tests. both experiments confirmed that the signal strength received by the matched aE sensors increased by more than 3 times in amplitude, which is equivalent to 9 times in power. Iterative design process can be applied to further fine-tune the design of the Im networks.

references

[1] a. Grandt, Fundamentals of Structural Integrity. Hoboken, nJ: Wi-ley, 2003.

[2] V. Giurgiutiu, Structural Health Monitoring with Piezoelectric Wafer Active Sensors. new york, ny: academic, 2007.

[3] r. s. c. cobbold, Foundations of Biomedical Ultrasound. new york, ny: oxford University Press, 2007.

[4] s. roundy, P. Wright, and J. rabaey, Energy Scavenging for Wire-less Sensor Networks with Special Focus on Vibrations. norwell, ma: Kluwer academic, 2004.

[5] K. cook-chennault, n. Thambi, and a.m. sastry, “Powering mEms portable devices—a review of non-regenerative and regen-

erative power supply systems with special emphasis on piezoelectric energy harvesting systems,” Smart Mater. Struct., vol. 17, no. 4, art. no. 043001, 2008.

[6] c. s. Desilets, J. D. Fraser, and G. s. Kino, “The design of efficient broad-band piezoelectric transducers,” IEEE Trans. Sonics Ultra-son., vol. sU-25, no. 3, pp. 115–125, may 1978.

[7] y. chen and s. Wu, “multiple acoustical matching layer design of ultrasonic transducer for medical application,” Jpn. J. Appl. Phys., vol. 41, no. 10, pp. 6098–6107, oct. 2002.

[8] T. Inoue, m. ohta, and s. Takahashi, “Design of ultrasonic trans-ducers with multiple acoustic matching layers for medical applica-tion,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 34, no. 1, pp. 8–16, 1987.

[9] D. callens, c. bruneel, and J. assaad, “matching ultrasonic trans-ducer using two matching layers where one of them is glue,” NDT & E Int., vol. 37, issue 8, pp. 591–596, Dec. 2004.

[10] H. Huang, D. Paramo, and s. Deshmukh, “Unpowered wireless transmission of ultrasound signals,” Smart Mater. Struct., vol. 20, p. 015017 2011.

[11] m. Garcia-rodriguez, J. Garcia-alvarez, y. yanez, m. Garcia-Her-nandez, J. salazar, a. Turo, and J. a. chavez, “low cost matching network for ultrasonic transducers,” Phys. Proc., vol. 3, no. 1, pp. 1025–1031, Jan. 2010.

[12] J. l. san Emeterio, a. ramos, P. T. sanz, and a. ruiz, “Evaluation of impedance matching schemes for pulse-echo ultrasonic piezoelec-tric transducers,” Ferroelectrics, vol. 273, no. 1, pp. 297–302, 2002.

[13] V. y. molchanov and o. y. makarov, “Phenomenological method for broadband electrical matching of acousto-optical device piezo-transducers,” Opt. Eng., vol. 38, no. 7, pp. 1127–1135, 1999.

[14] J. brufau-Penella and m. Puig-Vidal, “Piezoelectric energy harvest-ing improvement with complex conjugate impedance matching,” J. Intell. Mater. Syst. Struct., vol. 20, no. 5, pp. 597–608, nov. 2008.

[15] T. J. lawry, K. r. Wilt, s. roa-Prada, J. D. ashdown, G. J. saul-nier, H. a. scarton, P. K. Das, and J. D. Pinezich, “Electrical opti-mization of power delivery through thick steel barriers using piezo-electric transducers,” Proc. SPIE, vol. 7683, art. no. 768314, apr. 2010.

[16] b. Henning, J. rautenberg, c. Unverzagt, a. schroder, and s. olf-ert, “computer-assisted design of transducers for ultrasonic sensor systems,” Meas. Sci. Technol., vol. 20, no. 12, art. no. 124012, Dec. 2009.

[17] s.n. ramadas and G. Hayward, “Knowledge based approach for design optimization of ultrasonic transducers and arrays,” in Proc. IEEE Int. Ultrasonics Symp., sep. 2005, pp. 2247–2250.

[18] l. Wu and y. chen, “PsPIcE approach for designing the ultrasonic piezoelectric transducer for medical diagnostic applications,” Sens. Actuators A, vol. 75, no. 2, pp. 186–198, may. 1999.

[19] m. castillo, P. acevedo, and E. moreno, “Klm model for lossy piezoelectric transducers,” Ultrasonics, vol. 41, no. 8, pp. 671–679, nov. 2003.

[20] G. r. lockwood and F. s. Foster, “modeling and optimization of high-frequency ultrasound transducers,” IEEE Trans. Ultrason. Fer-roelectr. Freq. Control, vol. 41, no. 2, pp. 225–230, mar. 1994.

[21] l. svilainis, V. Dumbrava, and G. motiejunas, “optimization of the ultrasonic excitation stage,” in 30th Int. Conf. Information Technol-ogy Interfaces, Dubrovnik, croatia, Jun. 2008, pp. 791–796.

[22] y. chen, l. Hung, s. chaol, and T. chien, “Pc-base impedance measurement system for piezoelectric transducers and its imple-mentation on elements values extraction of lump circuit model,” WSEAS Trans. Syst., vol. 7, no. 5, pp. 521–526, may 2008.

[23] J. Kim, b. l. Grisso, J. K. Kim, D. s. Ha, and D. J. Inman, “Elec-trical modeling of piezoelectric ceramics for analysis and evaluation of sensory systems,” in IEEE Sensors Applications Symp., atlanta, Ga, Feb. 2008, pp. 122–127.

[24] G. K. lewis Jr., G. K. lewis sr., and W. olbricht, “cost-effective broad-band electrical impedance spectroscopy measurement circuit and signal analysis for piezo-materials and ultrasound transducers,” Meas. Sci. Technol., vol. 19, no. 10, p. 105102, oct. 2008.

[25] D. m. Peairs, G. Park, and D. J. Inman, “Improving accessibility of the impedance-based structural health monitoring method,” J. Intell. Mater. Syst. Struct., vol. 15, no. 2, pp. 129–140, Feb. 2004.

[26] G. Gonzalez, Microwave Transistor Amplifiers: Analysis and Design, 2nd ed., Upper saddle river, nJ; Prentice Hall, 1997.

Fig. 15. aE signals acquired using unmatched and matched aE sensors: (a) both aE sensors are unmatched; (b) aE#1 is matched using network a, whereas aE#2 is not matched; (c) aE#1 is not matched, whereas aE#2 is matched using network a; (d) aE#1 is matched using network T, whereas aE#2 is not matched.


Haiying Huang (m’98) received the b.s. degree in aircraft propulsion from the beijing University of aeronautics and astronautics (bUaa) in 1987. she received the m.s. degree in electrical engi-neering and the Ph.D. degree in aerospace engi-neering from the Georgia Institute of Technology in 1997 and 1998, respectively. Dr. Huang worked as a member of staff at lucent Technologies/bell labs before becoming an assistant professor at Purdue University in 2004. In 2006, she joined the University of Texas at arlington as an assistant

professor and was promoted to an associate professor in 2010. Her cur-rent research interests are focused on developing wireless, microwave, ultrasonic, and optical fiber sensors for structural health monitoring. Prof. Huang has been an IEEE member since 1998.

Daniel Paramo was born in Ecuador in 1989. He came to the United states to study aerospace en-gineering at the University of Texas at arlington (UTa) in 2008. since 2009, he has been working as an undergraduate research assistant at the ad-vanced sensor Technology lab at UTa. His re-search interests include wireless ultrasound sen-sors, acoustic emission detection, and mechanical testing of engineering materials.

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