Thermoacoustic sensors
Ultrasound has a wide range of biomedical applications from imaging to promoting cell growth (Shaw 2008). For biological experiments, it is important to regulate the acoustic output to ensure the quality and consistency of each trial. If not monitored properly, the under-application of ultrasound in high intensity focused ultrasound (HIFU)-based kidney stone disintegration can lead to incomplete treatment, while the over-application of ultrasound in LIPUS applications can lead to cell death (Shaw 2008). Acoustic output parameters are typically evaluated using a hydrophone or a radiation force balance. Hydrophones are considered the universal instrument used to characterize acoustic field parameters, such as pressure waveforms or beam profiles. However, operation of a hydrophone can be technically difficult, time-consuming, and expensive (Wilkens 2010a, 2004). For determining ultrasound output power, the accepted technique is the use of a radiation force balance (Shaw 2008). A radiation force balance requires that the ultrasound beam must be transmitted into a chamber containing degassed water onto an absorbing or reflecting target, which must intercept the entire beam (Shaw 2008).
Although the radiation force balance is the gold standard for measuring ultrasound intensity, it is not possible for real-time monitoring in certain settings, for example bioreactors, or in clinic to measure ultrasound intensities during treatment. Foreseeing these needs, we have proposed a close-proximity thermoacoustic sensor.
In one embodiment, a thermoacoustic ultrasound sensor comprises a transducer and an ultrasound sensor directly acoustically coupled to the transducer and an electronic processing unit connected to process signals from the ultrasound sensor.
In various embodiments, acoustic coupling may be achieved by (1) placing a layer of material that conducts ultrasound such as gel, gel pad, or agar between matching surfaces of the transducer and the sensor and pressing the transducer and sensor together, (2) matching surfaces of the transducer and sensor glued together, and (3) matching surfaces of the transducer and sensor being pressed together with many points of solid contact, as for example by using a suitable material such as rubber on both transducer and sensor to achieve direct coupling. By having matching surfaces of the transducer and sensor directly or acoustically coupled more energy is transferred from the transducer into the sensor and this permits more accurate calibration. In various embodiments, matching of the contacting faces may comprise the contacting faces of the transducer and the sensor being flat, but both may for example have the same curvature but one inverted from the other, one for example being convex and the other concave. In various embodiments, the face of the sensor that contacts a face of the transducer is larger in area than the face of the transducer to ensure high coupling efficiency of energy into the sensor. In various embodiments, the sensor comprises a cylinder, and a temperature sensor is attached to the cylinder. Preferably, the cylinder, at the point of attachment to the temperature sensor, is made of a thermally conductive material such as a metal, for example copper, or a metal with greater thermal conductivity than copper. Thus for example, in the disclosed embodiment using a cylindrical housing for the sensor, the circular end wall furthest from the coupling with the transducer may be made of or partially made of copper. The ultrasound sensor and transducer may face each other across a medium that is confined between the ultrasound sensor and transducer and, in operation, ultrasound only approaches the ultrasound sensor on one side only of the ultrasound sensor.
Embodiments of a thermoacousting sensor will now be described, with reference to the drawings by way of example, in which:
Thermoacoustic sensors that measure the transformation of the incident ultrasonic energy into heat have the potential to be an alternative approach to determine ultrasound intensity. These sensors are based on the transformation of incident ultrasonic energy into heat inside a small cylindrical absorber, and the detection of the temperature rise on the rear side of the absorber (Wilkens 2010a). Previous thermoacoustic sensor operation has required the sensor and transducer to be placed in a large water tank, similar to hydrophone or radiation force balance measurements (Wilkens 2010a, 2010b, 2004, 2002; Fay 1994; Fay 1996b). To further simplify thermoacoustic sensor operation, we designed and tested a close-proximity thermoacoustic sensor that can determine radiated ultrasound intensities by directly coupling a transducer via a coupling medium. Compared to the previous thermoacoustic sensors that cannot take measurements without placing the senor and transducer in a large water tank, the close-proximity thermoacoustic sensor can take measurements in air without complicated set-up procedures.
In a manner of operation of the sensor, the sensor captures the beam, converts the ultrasound power into heat, and indirectly measures the spatial average time average ultrasound intensity (Isata) by dividing the calculated power by the beam-cross-section (or the nominal area of the transducers). In an embodiment of the design, used for testing, a thin copper sheet was adhered to the back face of the sensor to increase heat diffusivity 1000-fold, enabling a uniform temperature distribution across the back face. An embedded system design was implemented using an Atmel microcontroller programmed with a least squares algorithm to fit measured temperature vs. time data to a model describing the temperature rise averaged across the backside of the sensor in relation to the applied ultrasound intensity.
An advantage over the radiation force balance is its ability to make measurements in the field (i.e. during equipment service activities). Compared to thermoacoustic sensor designs outlined in literature and in patents, the design implemented in this paper also has several novel components. The implementation of a thin metal layer increases heat conduction at the back of the absorber. The metal layer also reduces the dependence of the ultrasound transducer's focal point. The results show that the copper layer can increase heat diffusion 1000 fold compared to plexiglass alone, and reduce the sensor's error. The setup is more convenient than previously demonstrated setups that require the sensor and transducer to be placed in a large water bath. Finally, an embedded system design utilizing a microcontroller running a least squares algorithm was implemented to process the data in real time.
Referring to
In the sensor shown in
Referring to
A thermistor is a type of resistor. The main property of a thermistor is its resistance varies significantly with its temperature. There are two types of thermistors: positive temperature coefficient (PTC) thermistors, and negative temperature coefficient (NTC) thermistors. These classifications depend on the sign of the temperature coefficient (kT) in the linear approximation equation that describes the operation of a thermistor,
ΔR=k−TΔT (1)
where ΔR is the change in resistance, and ΔT is change in temperature. In contrast, resistors are designed to have a temperature coefficient as close to zero as possible in order to not be effected by the surrounding temperature.
Thermistors differ from resistance temperature detectors (RTD) with regards to the materials used for construction, and performance. RTDs are generally constructed from pure metal, while thermistors are normally made from a ceramic or polymer. Thermistors typically achieve a higher precision within a limited temperature range, while RTDs have the ability to measure greater spans of temperatures.
The drawbacks of using a thermistor include its limited operational range, and self-heating effects. The linear approximation equation is only true over a small temperature range. Additionally, depending on the circuit designed, thermistors can suffer from self-heating effects. If a thermistor is used to calculate a change in temperature by measuring the voltage drop across itself, the current that must be run through the thermistor will generate heat that will raise the temperature of the thermistor above the actual ambient temperature. Low power circuit design is implemented to prevent this.
For the exemplary thermoacoustic sensor, a thermistor 22 was implemented to measure the changes in temperature due to absorbed ultrasonic energy. A Honeywell discrete thermistor was chosen. This glass bead thermistor has a rapid response time of 0.5 seconds in still air, is micro sized measuring only 0.36 mm in diameter, is sensitive to changes to temperature and has excellent long term stability. The thermistor was secured firmly to the back face of the thermoacoustic absorber 24 using a small piece of electrical tape and the leads were soldered onto longer wires that connected back into the thermoacoustic sensor printed circuit board. At room temperature, the thermistor measured 2000 Ohms.
An analog to digital converter (ADC) is used to convert input analog voltage to a digital number proportional to the magnitude of the voltage. The opposite device is a digital to analog converter (DAC), which performs the same function but in reverse. An ADC allows the analog information measured to be manipulated by digital equipment, such as a microcontroller. In this case, the ADC value is calculated using the following equation,
where b is the number of bits of resolution. In this design, the supply voltage (3.3 V) is inputted to the reference voltage pin (VREF), the voltage drop across the thermistor is the input voltage (VIN), and 14 bits of resolution (b) are calculated
An integrated circuit made by MAXIM is used to supply the current to measure the voltage drop across the thermistor. The MAX6682 28, a thermistor to digital converter, was implemented in the circuit. While the MAX6682 28 is capable of calculating the resistance to temperature relationship and communicate with a microcontroller using a serial peripheral interface (SPI), the precision, accuracy, and flexibility of the microcontroller's ADC was preferred. Using the ADC, resolution to the millionth decimal point could be reached, compared to thousandth obtainable using the MAX6682. However, the MAX6682 28 was still used to provide a minute current across the thermistor for the ADC to measure the voltage drop. The power management circuitry built into the MAX6682 reduced the average thermistor current, thus minimizing thermistor self-heating. A 220 μA current is issued across the thermistor during a reading, between conversions the supply current is reduced to 21 μA.
The directly-coupled thermoacoustic sensor disclosed here can be used in various embodiments to measure ultrasound output at any frequency or intensity, in pulsed or continuous modes.
In one embodiment, the system comprises a transducer and electronic processing components. The electronic processing components may be made of a variety of components, for example the ATmega324P, a high performance, low power Atmel AVR 8-bit microcontroller, or other microcontroller may form part of the electronic processing unit for the thermoacoustic sensor. Capable of twenty million instructions per second, with 32 kilobytes of in-system self-programmable flash memory, the ATmega324P 30 was able to carry out the computations required. The main features of the ATmega324P 30 include the real time counter, the analog to digital converter, the programmable serial universal asynchronous receiver/transmitter port, and the internal interrupts. The 44-pin TQFP package was chosen, and programming was carried out using an AVR JTAGICE mkII. The microcontroller was operated at 3.3 V and a processing speed of 12 MHz.
Communication was carried out using a MAX448 RS-485 transceiver (MAXIM). The MAX448 is a low-power, slew rate limited transceiver capable of RS-485 communication. This integrated circuit features a reduced slew rate driver that minimizes electromagnetic interference (EMI) and reduces reflections caused by improperly terminated cables. The MAX448 is capable of error free data transmission up to 250 kbps, and draws between 120 μA and 500 μA of supply current during operation. The RS-485 standard is a communication standard that specifies the electrical characteristics of the driver and receiver. It is used throughout the SonaCell™ system in a master-slave orientation.
As shown in
In various embodiments, the housing is cylindrical and has a circular end wall 42 furthest from the coupling with the transducer that is at least partially made of copper. Thus for example, in the disclosed embodiment using a cylindrical housing for the sensor, the circular end wall furthest from the coupling with the transducer may be made of or partially made of copper. In our setup, shown in
The transducer and ultrasound sensor are acoustically coupled by a layer of material that conducts ultrasound and that is placed between matching surfaces of the transducer and the sensor. The medium (degassed water for example, but other materials may be used) in
The ideal material for a thermoacoustic sensor combines perfect acoustic impedance matching with strong acoustic absorbance. Acoustic impedance (Z) is related to a material's density (ρ), and acoustic velocity (v), shown in equation (3) (Ensminger 2009). Ultrasound waves are reflected at boundaries where there is a difference in acoustic impedance on each side; this is referred to as an impedance mismatch. A larger impedance mismatch will result in a higher percentage of the incident intensity being reflected (Rw) at the boundary (4).
Z1 and Z2 correspond to the acoustic impedance of the two materials at the boundary (Ensminger 2009). Neglecting scattering effects, the portion of the ultrasound wave that is not reflected at the boundary is transmitted through the material.
Plexiglass has been successfully used in previous investigations, and is an available material that can be easily processed and quickly assembled in house (Wilkens 2010a, 2004, 2002; Fay 1996b). The inner absorbent cylinder in the sensor designed has a diameter of 20 mm, and an absorber length of 2 mm. Using the acoustic properties from Table 1 and equation (4), 13% of the incident ultrasound intensity will be reflected at the water-plexiglass interface. Ignoring scattering effects, 87% of the ultrasound wave will be transmitted into the plexiglass absorber. The low acoustic impedance of air, the insulating material, will cause 99% of the ultrasound wave to be reflected when it reaches the back of the sensor.
As it travels through the solid medium, the initial transmitted intensity is reduced due to acoustic attenuation. Acoustic attenuation is caused due to the absorption and scattering of the ultrasound wave and is generally dependent on two factors: (i) the material through which the wave is transmitted, and (ii) the frequency of the ultrasound (Ensminger 2009). The ultrasound intensity after being attenuated over a distance x can be calculated using the following equation, where I0 is the initial ultrasound intensity, and μ is the absorption coefficient:
I(x)=I0e−μs (5)
Myers and Herman investigated the transient temperature evaluation in a theoretical assessment (Myers 2002). They followed the single reflection theory and described a steady state solution and a transient solution to the temperature rise averaged over the absorber's cross-section. They suggested that temperature data collected over time could be fit to a curve with the form,
In equation (6), Tave(t) is the average temperature measured in the sensor in relationship to the temperature of the water bath, I0 is the incident ultrasound intensity, μ is the absorption coefficient, l is the length of the absorber, k is the thermal conductivity of the absorbing material, Cp is the heat capacity of the material, and ρ is the density of the material. Using this model, the ultrasound intensity can be inferred from the parameter Ca.
The thermal properties of the thermoacoustic sensor will dictate how the thermal energy propagates through the sensor. We are interested in the heat diffusivity on the back face, where the thermistor is located. The solution to (6) requires the temperature rise averaged across the back face. The goal of the sensor is to take accurate readings as quickly as possible; therefore, it is important for the temperature to rapidly spread across the back face. To investigate the diffusion of heat, equation (7) and the thermal properties outlined in Table 2 were used to calculate the thermal diffusivity of various materials. The thermal diffusivity (α) expresses the rate a material transfers heat from one point to another and is related to the thermal conductivity (k), density (ρ) and heat capacity (C) of the material.
Plexiglass has a thermal diffusivity of 1.09×10−7 m2/s. Copper, a material with a high thermal conductivity, has a thermal diffusivity of 1.18×10−4 m2/s, 3-orders of magnitude greater than plexiglass, allowing it to conduct heat at a much faster rate. A thin copper sheet (0.30 mm) was attached to the back face of the absorber using a thermal paste; this equally distributes the temperature across the whole surface faster than the plexiglass material. The temperature sensing thermistor was placed on top of the copper layer. Care was taken to ensure that the copper didn't short the thermistor leads.
Temperature readings are taken using an oversampled analog to digital converter (ADC). Oversampling the ADC increases the resolution and reduces the noise of each reading. The ATmega324P microcontroller's ADC has a 10-bit resolution. In order to measure the minute changes in temperature caused by the ultrasound beam, we increased the resolution by 4 bits using oversampling techniques.
A least squares equation is implemented to fit temperature vs. time data to the equation described in (2). The implemented least squares algorithm was programmed in C onto an Atmel ATmega324P microcontroller. Every 0.1 seconds a temperature and time reading are taken and fit to equation (6) and the coefficients are estimated. An iterative process with an experimentally determined R2 value of 0.00001 and step size of 0.001 is used.
After construction, the thermal response of the sensor was characterized. Thermal calibration was carried out by placing the sensor in a heated water bath and measuring the changes in the thermistor's electrical resistance with respect to changes in temperature. A thermocouple with an accuracy of 0.1° C. was attached to the sensor's thermistor and employed to record temperature changes relative to the thermistor's ADC readouts. In accordance with the operation of a negative temperature coefficient thermistor, the resistance decreased as the temperature increased. There was a linear correlation between the change in resistance and the temperature, with a coefficient of determination of 0.999 and a slope shown in equation (9). The slope of the graph was used to convert the change in the thermistor's resistance to a digital temperature value.
T=−0.01717X+78.79 (9)
Here X is the ADC readout. This relationship was programmed into the microcontroller operating the thermoacoustic sensor, allowing the sensor's temperature to be calculated.
Equation (10) shows the ratio of the power out of the transducer with respect to the power into the transducer, using the root mean squared voltage and current inputted into a piezoelectric transducer, and measuring the output power with a radiation force balance.
Approximately 55% of the input energy is lost during the conversion of electrical energy to mechanical energy; a portion of this is due to the internal friction of the transducer, which results in thermal energy. In a close-proximity setup model, the heat produced by the transducer will influence the temperature readings and the measurement accuracy. A thin layer of ultrasound gel was originally used, and the self-heating effect of the transducer made the sensor's calibration and measurement highly dependent on the construction of the ultrasound transducer, since a transducer made out of a different material would generate a different amount of heat. Due to the heat produced by the transducer, we used degassed water as an ultrasound medium. The heat generated by the transducer is dispersed throughout the water and will not affect the sensor's readings.
To evaluate the transient model with a thermoacoustic sensor implemented in a close proximity setup, measured data was collected and the least squares model was used to fit the curve, equation (11):
The value Tave is the measured temperature averaged across the absorber's back face; T0 is the starting temperature. The thermoacoustic sensor was coupled using degassed water in direct contact with the SonaCell™ ultrasound transducer. When the ultrasound generator was turned on, the thermoacoustic sensor began measuring the change in temperature at the absorber's back face. The temperature vs. time curve with incident ultrasound intensity of 80 mW/cm2, for example, is measured. Using the least squares method and MATLAB's curve fitting toolbox, the transient model was evaluated. The curve described in equation (11) was fit to the measured data with prediction bounds with 95% certainty (calculated using the MATLAB curve fitting toolbox), at an ambient temperature of 24° C. The coefficients of the transient model are displayed in Table 3.
The 95% confidence bound indicates that the model is 95% confident that the mean value will fall in between the upper and lower bounds. A smaller interval width is desirable because it indicates that in subsequent trials the calculated coefficient values will be near the mean value determined by this curve fitting session.
The accuracy of fit analysis calculated by the MATLAB curve fitting toolbox is outlined in Table 4.
The sum of squares of residuals (SSE) value measures the total deviation between the measured data (y) and the predicted data (ŷ) calculated by the fitted curve.
SSE=Σ
l=1
n
r
i
2=Σl=1n(yi−ŷi)2 (12)
The R-squared value is the square of the correlation between the measured data and the predicted value.
SST is the sum of squares about the mean, where (ŷ) is the overall mean. An R-squared value closer to 1 indicates that a great proportion of variance is accounted for by the model. Finally, the root mean squared error (RMSE) is an estimate of the standard deviation of the random component of the data. The RMSE calculation is shown in the equation below, where (n) is the number of terms.
An RMSE value closer to 0 indicates that the model is more useful for prediction. After using the MATLAB curve fitting toolbox to analyze the goodness of fit of equation (11) to the measured temperature vs. time data collected when a 80 mW/cm2 ultrasound intensity, for instance, was applied to the thermoacoustic sensor, we can conclude that the least squares method does fit the curve to the measured data.
Acoustic Calibration
Substitution calibration involves calibrating the ultrasound generator using a known calibration modality, in this case a radiation force balance, and then the calibrated ultrasound generator is employed to find a relationship between the thermoacoustic sensor's recorded temperature and the applied ultrasound. Four ultrasound transducers with surface area of 3.5 cm2 were operated at a 1.5 MHz frequency with a 20% duty cycle and 1 kHz pulse repetition frequency. The transducers, driven by a SonaCell ultrasound generator (IntelligentNano Inc., Edmonton, Alberta, Canada), were initially calibrated using a radiation force balance (Ohmic Instruments Co., Maryland) at 40, 60, 80, and 100mW/cm2, respectively.
The C coefficient (in ° C.) was calculated using the least squares method to fit the curve described in equation (11) to temperature data measured over time at different ultrasound intensities. A constant τ value, determined experimentally (τ=130 sec), was used, and the ambient temperature T0 was measured, and found to be 24° C., before readings were taken. There is a linear relationship between the calculated C coefficient and the applied ultrasound intensity, as suggested by equation (11). The linear relationship between the applied ultrasound intensity (I) and the calculated C coefficient is,
I=9.637×C+6.973 (15)
The R-squared value is 0.9962. This relationship is further analyzed and used to evaluate the thermoacoustic sensor's ability to relate applied ultrasound intensity to measure temperature after 20 seconds.
The thermoacoustic sensor's operation relies on measuring the temperature changes produced by absorbed ultrasound waves. However, the sensor's temperature changes depend not only on the ultrasound intensity, but also on ambient temperatures. Although the thermistor in the sensor is insulated with air to remove the influence of the outside room temperature, the front face of the sensor is still affected by the ambient temperature. The ambient temperature in our design is the temperature of ultrasound medium shown in
The difference between the C values at various starting temperatures indicates that a direct correlation between measured C coefficient values and starting ambient temperatures. A graph of the data outlined in Table 5 shows linearity between measured C coefficient values and starting ambient temperatures. The final version of the thermoacoustic sensor was calibrated using substitution calibration methods, which took the effect of ambient temperatures into consideration.
The second measurement was carried out using the designed thermoacoustic sensor. The sensor was coupled directly to the transducer through the ultrasound medium, as shown in
Using equation (14) to relate the ultrasound intensity to the calculated C coefficients determined from the measured temperature increases over time, the performance of the calibrated thermoacoustic sensor was evaluated. By comparing readings taken by a radiation force balance to readings taken using the calibrated thermoacoustic sensor, we examined the agreement between both techniques.
Six transducers were calibrated to nominal levels of 30, 40, 60, 80, 100, and 120 mW/cm2 using a radiation force balance. The output intensity of the same transducers was then measured using the thermoacoustic sensor. This process simulates a new user taking a fresh reading every time, making it a practical evaluation of the thermoacoustic sensor's operation. Table 6 outlines the measurements taken using the thermoacoustic sensor.
Table 7 compares the measurements made by the radiation force balance and our thermoacoustic sensor. The thermoacoustic sensor had an output with an average error of 5.46% across 18 measurements.
The result in
Since readings by the thermoacoustic sensor are based on the temperature across the back face of the sensor, a thin copper sheet (0.30 mm thick) was attached to the plexiglass material using a thermal paste to distribute heat quickly and uniformly such that the temperature measured at one location is assumed to be the average temperature across the entire back face. If there was not a uniform change in temperature, the goal would be to quickly distribute the heat from one location across the entire surface. Discrepancies between readings arise if the ultrasound energy heats an area away from the thermistor on a material with low thermal diffusivity.
As seen in Table 8, the average standard deviation when the transducer is placed in different locations on the copper backed sensor is 58.2% less than the average standard deviation of the sensor without the copper back. This is due to the higher thermal diffusivity of the copper compared to the plexiglass material allowing the temperature to dissipate across the back face more evenly.
The results shown in the lower half of Table 8 clearly illustrate why the sensor without copper backing cannot yield accurate results. At the same starting temperature, the calculated C coefficients must be close to the same value at every reading. This is especially important because substitution calibration methods are used. Once the sensor is calibrated, the same C coefficient that correlates to a specific ultrasound intensity should be generated every time that particular ultrasound intensity is applied. Conversely, the results shown in the upper half of table 8 show that the sensor with the copper backing can generate more consistent results. The algorithm implemented requires that measurements be taken using the average temperature across the absorber's back face. In order to record the average temperature, multiple sensors or a high conductivity surface must be used to rapidly distribute heat across the back face (Myers and Herman 2002).
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This application claims the benefit under 35 USC 119(e) of U.S. provisional application No. 61/621,543 filed Apr. 8, 2012. This provisional application is hereby incorporated by reference herein in its entirety.
Number | Date | Country | |
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61621543 | Apr 2012 | US |