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# A microcontroller based wall shear stress measurement

Mourad Laghouche, David Meunier, Jumana Boussey-Said, Sedat F. Tardu, A. Adane

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Mourad Laghouche, David Meunier, Jumana Boussey-Said, Sedat F. Tardu, A. Adane. A microcontroller based wall shear stress measurement. IEEE International Symposium on Industrial Electronics, May 2004, Ajaccio, France. 10.1109/ISIE.2004.1571793. [hal-00262264]

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Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
A Microcontroller Based Wall Shear Stress Measurement

M. Laghouche¹,³, D. Meunier¹, J. Boussey¹, S. Tardu² and A. Adane³

¹Institute of Microelectronics, Electromagnetism and Photonics
IMEP, ENSERG, 23 rue des Martyrs, 38016 Grenoble Cédex 1, France
²Laboratoire des Ecoulements Géophysiques et Industriels, LEGI, INPG-UJF-CNRS
B.P. 53 X, 38402 Grenoble Cédex-France
³Mouloud Mammeri University, Department of Electronics,
Faculty of Engineering, PO Box 17 RP 15000, Tizi Ouzou, Algeria
email: laghouc@enserg.fr http://www.imep.enserg.fr

**Abstract**— A new type of hot wire anemometer was developed by using surface micro machining techniques. The reduction of the microprobes section and the development of a thermal isolation cavity below the hot polycrystalline silicon wire reduced considerably indirect thermal exchanges between the hot wire and its substrate. As a consequence, the response time of the sensor is considerably improved allowing the detection of fast fluctuations and turbulent phenomena in fluid mechanics. In this paper we briefly describe the realisation technology of the developed sensors, its operation principles and the data acquisition circuit especially conceived and realised to perform turbulent flow detection in a low speed wind tunnel.

**Index Terms**—MEMS, sensor data acquisition, wall shear stress sensor.

I. INTRODUCTION

The control of turbulence in fluid mechanics is a very
important issue which may has strong impact in several in-
dustrial fields. The more important one is the civil and
military aviation where the reduction of air friction on the
delta wings still a big economics stake. Since the early 90's,
several research teams have been working on this applica-
tion developing either integrated sensors or microactuators
that have to be implemented in a specific critical points on
the aeroplane. The work presented in this paper is related to
a specific type of those sensors. i.e., hot wire anemometers
which are usually dedicated for flow speed measurement. In
aerodynamics applications, it has been established that hot
wire anemometers can be used to detect turbulent mecha-
nisms inside boundary layers, under the only condition to
be mounted tangential to the aeroplane surface. The turbu-
lent phenomena induce swirling structures which are a few
hundred of microns width and a few millimetres length [1,
2] and have a very short life span (on the order of the milli-
second). Classical anemometer (with Platinum wire of
10µm diameter and 400 µm length, inserted inside macro-
scopic tubes) [3] were reported to have very good dynamic
performance (time response of few milliseconds) but still
are incompatible with the need to obtain an array of identi-
cal, and ultra-miniaturised, sensors The spatial and tempo-
ral sensing of the swirling structures (responsible for parie-
tal friction) is a big issue and is made progressively possible
thanks to the use of integrated sensors. We will show in the
presented work how the use of adapted microtechnologies
allowed us to obtain highly miniaturised hot wire ane-

mometers. Several microsensors of various geometries were
produced by surface micro machining, using thermally sen-
sitive materials like polycrystalline silicon [4, 5]. The re-
sponse time was also optimised via a suitable thermal iso-
lation architecture. Finally, electrical and functional (in
wind tunnel) characterisations were performed and the
firstly obtained results are presented.

II. REALIZATION OF A SHEAR STRESS SENSOR

Fig. 1 shows top and cross section scheme of the adopted technology. PECVD (Plasma Enhanced Chemical Vapor Deposition) silicon nitride was first deposited on p type 4" wafers to a thickness of 0.3 µm. Then the silicon nitride film was patterned and wet thermal oxidation of silicon was made through the nitride window. Oxidation time was adjusted with technological step simulation for achieving a flat surface. A 0.3 µm depth silica cavity was obtained. A 0.5 µm-thick polycrystalline silicon film was then deposited inside a LPCVD (Low Pressure Chemical Vapor deposition) furnace and doped by boron ions implantation at appropriate parameters (energy and dose of ion implantation were chosen to optimise the thermal sensibility of the so-obtained semiconductor. After the thermal annealing, polycrystalline silicon was patterned into to obtain variable section and length of wires.

<figure><img src="image_3.png" /><figcaption>Fig.1 Technological realization of the hot-wire probe suspended on a mi-
cro-cavity.</figcaption></figure>

Electrical contacts were finally taken with chromium
pads. The whole wafer was then diced into individual chips
and releasing of the polysilicon wire was performed by wet-
etching of the silica cavity performed on each sample. The
presence of the cavity underneath the wire ensures the more efficient thermal isolation between the hot wire and its substrate. The depth of cavity is only of 0.5 µm which prevents the formation of parasitic turbulence inside the cavity [2].

### III. ELECTRIC SENSITIVITY OF THE SENSORS

The sensors were firstly characterized under 2 points prober, in order to determine their static electrical properties (current-bias characteristics) and their behavior with temperature. Two types of parameters were deduced for each type of sensors:

the resistance variation as a function of the temperature for determining the TCR (Temperature Coefficient Resistance = $\frac{1}{R_0} \frac{\partial R}{\partial T}$ where R₀ is the extrapolated resistance taken at the temperature of 0°C). It was found out that the TCR values are independent of the hot wire geometry and relatively uniform on all the surface of the wafer. An average value of -0.5.10⁻⁴/°C was measured for samples doped at 10¹⁶cm⁻² (80 keV) of boron.

The current value to be injected inside the polysilicon wire in order to elevate its temperature. This overheating polarisation current was deduced from TCR value and current-voltage characteristics of each sensor. As an example, for the 0.5 x 2 x 50 µm³ having the above mentioned TCR value, a current of 235µA was used to increase the wire temperature of 70°C.

#### A. Dynamic and Electric Time Response

Although static measurement is founded on a simple principle, it is now accepted that the frequency response of such sensors is in general complex because of convective and conductive heat exchanges. This can be illustrated by the significant difference between the electrical time response and the thermal time response. The electrical time response defined as being the response time of the conductor when it is biased with a perfect square signal (pulse). The electrical time response of the sensor is 3µs (Fig 2).

<figure><img src="image_4.png" /><figcaption>Fig. 2 Electrical time response</figcaption></figure>

An electric circuit based on the internal heating method was designed and carried out for the dynamic response time determination of the sensors (Fig.3)

<figure><img src="image_5.png" /><figcaption>Fig. 3 Time response measurement circuit.</figcaption></figure>

The circuit makes possible to simulate. at the sensor level. the fluctuations of temperature by carrying out an internal modulation of the wire heating created by a D.C. current (rated current of the probe). An alternative current. AC. with a frequency of 1 MHz modulated by a square signal with a frequency of 1 kHz is superimposed.

Fig. 4 shows the time response of a 60x2x0.5µm³ hot wire. which is about 150µs. The bandwidth sensor lies between 0 and 1KHz. This bandwidth is not large enough for detecting all turbulence phenomena associated with airflow over aircraft's.

<figure><img src="image_6.png" /><figcaption>Fig. 4 Time response measurement of a 50x2x0.5µm³ wall shear stress sensor.</figcaption></figure>

#### B. Data Acquisition System

The Data Acquisition System is composed of two main subsystems: the programmable digital data acquisition system and the sensors with their associated circuits [6]. The requirement of data acquisition system, in terms of speed and amount, dictated the use of a microcontroller. In our case the Motorola 68HC11 CMOS microcontroller integrated circuit was chosen for this purpose thanks to its low power consumption, small size and built-in analog to digital (A/D) converter with 8 input multiplexer.

The A/D converter of the microcontroller converts simple signals into digital values and transfers them to a personal computer with RF circuit via an RS 232 serial port.

The RF module transmits the data through the Amplitude Modulation of 464 MHz frequency, so the consumed power of transmission is 13mW.
<figure><img src="image_7.png" /><figcaption>Fig. 5 Block diagrams of the microcontroller data acquisition</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 6 Schematic diagram of the data receiver in the laboratory</figcaption></figure>

### C. Conditioning circuit

As shown in Fig. 7, the associated analogue circuit is divided into 3 stages: a Wheatstone bridge circuit, a Constant Temperature Anemometer (CTA) feedback circuit with a power stage and a differential amplifier circuit with an offset compensation network.

The Wheatstone circuit is formed with two precision resistors of 0.01% accuracy and a tuneable resistor to control the initial voltage reference. In the fourth branch we place the sensor near the resistors and the conditioned circuit in order to minimise the noise and any external perturbations.

The AD620 circuit component, is a low cost, high accuracy instrumentation amplifier which requires only one external resistor to set main gains from 1 to 1000. This latter is working as preamplifier due to its low voltage noise.

In order to reduce the circuit size, we have pasted the sensor and the Wheatstone bridge on the ceramic support. The conditioning circuit is realized with a very small circuit under the ceramic holder in which the Surface Mounted Circuits (CMS) technology is used.

<figure><img src="image_9.png" /><figcaption>Fig. 7 Schematic diagram of hot wire anemometer mounted in Constant Temperature Mode.</figcaption></figure>

The hot wire anemometer is mounted in a Wheatstone bridge: This is a self-balancing bridge which maintains the resistance $R_T$ of the sensor at a constant value R. An increase in fluid velocity causes a decrease of the temperature T as well as of the $R_T$ values inducing an unbalancing of the bridge. This causes the amplifier output current and current through the sensor to increase thereby restoring T and $R_T$ to their required values.

The advantage of such CTM circuit [7] is to minimise thermal inertia of the sensors, which was leading to rather bad time response.

## IV. STATIC SPEED CALIBRATION

The sensor was also characterised in a wind tunnel in order to calibrate it for static speed variation.

Experimentally, the hot wire anemometer is mounted at the wall surface of the wind tunnel. A Pitot tube measures the pressure in the centre of the tunnel. This pressure is then transformed in order to know the macroscopic speed. This calibration was performed for velocity ranging from 7m/s up to 15m/s.

With this constant temperature configuration, we can find the various parameters $\alpha$, $\beta$ and $n$ of the electrical calibration of the sensor described by a law as:
$$E^2 = \alpha \cdot (\overline{u_t})^{2n} + \beta \quad [8]$$
where E is the output voltage and $\overline{u_t} \approx u_\infty / 22$ is the friction speed.

In measuring the output voltage variations, we can determine the other coefficients. In Fig. 8, one can see that the above mentioned law fits perfectly the experimental values when $n$ is taken equal to 1/3. This is in very good agreement with the Levêque solution which states that $n$ coefficient has to be close to 1/3.
[1] S. Tardu; Near wall turbulence control for local periodical blowing. Experimental thermal and fluid science. Vol 16 n°1-2, pp.41-53.1998.
[2] D. Meunier, D.Tsamados, J.Bousse, S.Tardu; Simulation of wall shear stress integrated sensors. Therminics,02. Madrid (Spain). Oct 02.
[3] P.C. Stainback, K. A Nagabushana, Review of hot wire Anemometry techniques and the range of their applicability for various flows. Electronic Journal of Fluids Engeering.
[4] D. Meunier, D.Tsamados, J.Bousse, S.Tardu; Thermo-fluidic FEM simulation of ultra-minaturised wall shear sensors. Eurosime 03, Aix en provence (France). April 03.
[5] L. Löfdahl: The influence of temperature on the measurements of Reynolds Stresses in shear free turbulence near a wall. Experiments in Fluids 25 (1998) 160-164.
[6] S.Ameur, M. Laghouche and A.Adane "Monitoring a greenhouse using a microcontroller-based meteorological data acquisition" re-newabe energy, vol 24,(2001),19-30.
[7] B.C. Gale: An Elementary Introduction to Hot Wire and Hot Film Anemometry, DISA Technical Publication.
[8] L.V. King; On the convection of heat from small cylinders in a stream of fluid. Philosophical Transactions of Royal Society, Series A. vol. 214, 1914.
[9] F.Jiang, Silicon Micromachined Flow Sensors. Thesis, California Institute of Technology. 1998.

<figure><img src="image_10.png" /><figcaption>Fig. 8 Static speed calibration in wind tunnel: $E^2$ in function of $(u_r)^{2/3}$.</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>Fig. 9 Schematic diagram of the wind tunnel and the shear stress sensor mounting with data acquisition</figcaption></figure>

V. CONCLUSION

Hot wire integrated anemometers obtained with polysili-
con material were fabricated and characterised. Very tiny
wires suspended upon cavity were on-wafer tested and
demonstrated to have a good temperature sensitivity. The
TCR value was found on the order of - 0.5×10⁻⁴ /°C and
proven to be constant on the whole wafer. Time response
with constant current model (CCM) and Constant tempera-
ture model (CTM) was measured. The latter gives a value
of 150µs which is compatible with the required perform-
ance and in good agreement with our previous results ob-
tained by simulation [4, 5, 9].