Design and Implementation of Diaphragm Type Pressure Sensor in a ...

Ambarish G. Mohapatra / International Journal of Engineering Science and Technology (IJEST)

Design and Implementation of Diaphragm Type Pressure Sensor in a Direct Tire Pressure Monitoring System (TPMS) for Automotive Safety Applications Ambarish G. Mohapatra Dept. of Applied Electronics and Instrumentation Silicon Institute of Technology Bhubaneswar, India Email: [email protected]

Abstract: Correct tire pressure is a critical factor in the safe operation and performance of a motor vehicle. Over inflated tires often result in unnecessary tire wear, reduced gas mileage and less than optimal vehicle performance as well as vehicle safety. A tire pressure monitoring system (TPMS) monitors air pressure and temperature in the tires of a motor vehicle, and that generates a signal indicative of the tire pressure and temperature in each of the tires to increase the vehicle performance and safety. Present work is based on the design of tire pressure monitoring system which includes pressure sensor, an RF-communication unit, signal processing unit and display unit. To sense the changes in inflation pressure, a diaphragm based pressure sensor was designed to be used in pressure measurement of the tube. The inflation pressure was transmitted to the receiver side using ISM (Industrial, Scientific and Medical) band at 433.92MHz and ASK (Amplitude-Shift Keying) modulation scheme. The pressure sensor was tested at room temperature as well as at elevated temperature of 33°C - 70°C. Finally, the collected data was analyzed and different sensor characteristics were found out. Keywords: TPMS, Automotive safety, Pressure Sensor, Microcontroller, RF communication, ISM band, ASK. 1.

Introduction

Tire Pressure Monitoring System (TPMS) plays a vital role in automotive safety applications [2]. This system is based on direct method of tire pressure measurement. This system contains a direct tire pressure monitoring principle, RF communication link and a display unit for monitoring the pressure of the tire. The pressure sensor used here was a piezoresistive type pressure sensor. The sensor was a circular diaphragm type pressure sensor and a strain gauge was bonded on one face of the diaphragm which was taken as reference pressure (atmospheric pressure) and other side was connected to the input pressure valve. A strain gauge is based on piezoresistive principle so the resistance of the strain gauge will show a change. In a full bridge strain gauge configuration the output voltage of the bridge will change with the change in strain gauge resistance. A/D converter is used to get digital data and was then transmitted to a central receiver to display the inflation pressure.

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Fig. 1.

Basic block diagram of a Tire Pressure Monitoring System (TPMS)

In a tire pressure monitoring system the RF link plays a major role in sending data to the receiver unit near the driver side. The transmission of data is done by a suitable packet format containing pressure sensor data. Transmission and reception of sensor data: The sensor data was transmitted to a central receiver unit with a specific serial ID and displayed in an LCD driver. The transmission and reception of data was done over ISM band at a frequency of 433.92MHz [3]. The transmitted data was arranged in a header of preamble, sensor ID and pressure data. The display driver used was made by using a microchip PIC16F877A microcontroller and an LCD. The data encoding method used in this project is based on PWM format with TE (basic pulse element) time of 400 μs [Figure 2].

Fig. 2.

Data encoding format

The transmitter data header Preamble Sensor ID Sensor data Fig. 3.

Transmitter data header

Preamble: The preamble is a series of 31 logic ‘1’ bits followed by a single logic ‘0’ bit. The preamble allows the receiver to recognize the RF transmission as a valid transmitted message. The preamble also allows the receiver to synchronize to the RF message, thereby compensating for any oscillator inaccuracies within the transmitter. The transmitter preamble bits can be varied based on the system requirements. Longer preamble bit lengths may be appropriate where receiver quiescent current is an issue. Shorter preamble bit lengths may be appropriate where transmitter battery usage is a concern. In either case, it is purely a trade-off between receiver quiescent current and battery power consumed by the transmitter device. Sensor ID: The 32bit transmitter ID is used to uniquely identify each transmitter. A frame of 32 bits insures that there is a very low probability that any two transmitters will have the same ID. Sensor Data: The pressure in kg/cm2 was obtained putting the received unsigned value in the putting the received unsigned value in the equation found by calibrating the sensor using the tire with different input pressure levels.

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2.

System Configuration and Experimental Procedure

In the TPM system we have used following major component to monitors the internal pressure of an automobile's tire. a. b. c. d. e.

Pressure sensor Associated signal conditioning unit Transmitter Unit RF Receiver Unit Liquid Crystal Display driver circuit

2.1. Design of diaphragm type pressure sensor The sensor used in this work was made using a special purpose diaphragm strain gauge bonded on a circular diaphragm. The sensor was designed using the equation 1.

ΔE PR2 (1 −ν 2 ) = (0.82) V Et 2

(1)

In the above equation the output voltage per volt of excitation is generally chosen to be 2mV/V for almost all the strain gauge based transducers. Table 1. Assumed sensor design parameters.

Parameters

Values chosen

ΔE V

2 mV/V

E (Young’s modulus)AL P (Maximum pressure) ν (Poisson’s ratio) R (Radius of the diaphragm)

0.7E6 kg/cm2 2.5 kg/cm2 0.3 1.5 cm

By putting the above parameters, the thickness of the diaphragm obtained as: t = 0.54mm During design of the circular diaphragm pressure transducer two types of strain distributions were taken into consideration • Circumferential Strain • Radial Strain Radial strain

εR =

Circumferential strain

ε

T

=

3p(1 − ν 2 ) (R 2 − 3r 2 ) 0 8Et 2

2 3p(1 − ν ) 8Et

2

(R

2 0

2 −r )

According to the strain distribution profile in the diaphragm [Figure 4] below at any input pressure the circumferential strain ε T is always positive and maximum value at r=0. The radial strain ε R is positive in some regions but negative in others and maximum negative value at r=R0.

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Fig. 4.

Strain distribution profile in the circular diaphragm

Under the action of the pressure the diaphragm deflects and changes from a flat circular plate to a segment of a large radius shell. As a consequence, the strain in the diaphragm is nonlinear with respect to the applied pressure [15]. Acceptable linearity can be maintained by limiting the deflection of the diaphragm. The design consideration of diaphragm pressure transducer contains two major parameters. • •

Deflection of the diaphragm Natural frequency of the diaphragm (considered only for dynamic pressure measurement)

2.2. Deflection of the diaphragm: The center deflection

Wc of the diaphragm can be expressed as equation [2] Wc =

3PR 4 (1 − ν 2 ) 16Et 3

(2)

The sensor output will be linear if Wc < t/4 at maximum pressure. As a general rule, the deflection of the diaphragm at the center must not be greater than the diaphragm thickness for perfect linearity condition and the deflection should be limited to one quarter the diaphragm thickness. 2.3. Natural frequency of the diaphragm (for dynamic measurement): In order to faithfully respond to dynamic pressures, the resonant frequency of the diaphragm must be considerably higher than the highest applied frequency. Depending strongly upon the degree of damping in the diaphragm strain gauge assembly and in the fluid in contact with the diaphragm, the resonant frequency should be at least three to five times as high as the highest applied frequency [15]. The subject of proper design for accurate dynamic response is too complex and extensive to be included here. However, for transducers subject to high frequencies or to sharp pressure wave fronts involving high-frequency components, careful consideration must be given to frequency response, both in terms of amplitude and phase-shift. The undamped resonant frequency of a rigidly clamped diaphragm can be expressed using U.S. Customary Units as equation [3].

fn =

0.469t R0

2

gE γ (1−ν 2 )

In Hz

(3)

Where g = acceleration of gravity (386.4 in/sec2) γ =weight density (lbs/in3) The above equation [3] can be expressed as SI Unit as the equation [4] expressed below. fn =

Where

ρ = mass density (g/cm2)

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0.469t R0

2

E

ρ (1 − ν 2 )

In Hz

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(4)

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Ambarish G. Mohapatra / International Journal of Engineering Science and Technology (IJEST)

The sensor used here was designed and calibrated for 0 to 2.5 kg/cm2 static pressure variation. By applying the above equation for diaphragm deflection the deflection at the center of the diaphragm is 0.31346 cm, which is more than the maximum center deflection of a square diaphragm at 2.5 kg/cm2. 2.4. Modeling of circular diaphragm: The strain profile distribution of the diaphragm was also studied using finite element analysis (FEM) and partial derivative equation (PDE) method. Some of the analysis results are mentioned below.

Fig. 5.

Fig. 7.

Total displacement (in meter) of the circular diaphragm

Strain energy density J/m3 of the circular diaphragm

Fig. 6.

Fig. 8.

Mesh stucture of the circular diaphragm

Stress distribution profile of the circular diaphragm

Here a special-purpose diaphragm strain gauge was mounted on one side of the diaphragm which was exposed to atmospheric pressure as a reference pressure and other side is exposed to tire inflation tire pressure. The linear gauge configuration [Figure 9] functions in the same manner as the circular configuration with only minor differences in total gauge output. The main advantages of using a linear design are ease of installation (less surface area to bond) and generally lower gauge cost. The diaphragm pressure transducer is small, easy to fabricate, and inexpensive, and has a relatively high natural frequency. The diaphragm type pressure sensor designed in this project [Figure 10].

Fig. 9.

Stress distribution profile of the circular diaphragm

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Fig. 10.

Stress distribution profile of the circular diaphragm

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2.5. Calibration of pressure sensor: The designed pressure sensor was calibrated using a dead weight pressure gauge tester (which makes use of the relationship between pressure acting on the known area of a vertically free floating piston producing a force balanced by known dead weights) and the input-output relationship was also found out. 2.6. Design of associated signal conditioning circuit: The signal conditioning circuit was designed to amplify the sensor output voltage to match the resolution of the microcontroller and to nullify the offset voltage of the strain gauge bridge circuit. The signal conditioning circuit was made according to the specifications listed below. Table 2. Signal conditioning circuit parameters.

Input parameter Input pressure range 0 – 2.5 kg/cm2

Source signal Parameter: voltage Range: 14.4 mV – 26.6 mV

Signal conditioning Parameter: Voltage, linear Range: 0 – 1.5 V

The bridge output voltage was given to a high input impedance circuit to minimize the loading effect. The output voltage from the unity follower configuration was given to a differential amplifier to nullify the bridge offset voltage.

Fig. 11.

Fig. 13.

Fig. 15.

Diaphragm type pressure sensor.

Fig. 12.

Pressure sensor connected to a tire.

Signal conditioning unit and transmitter circuit connected to a tire.

Fig. 14.

Transmitter and receiver circuits used in this work.

Strain distribution profile in the circular diaphragm

Fig. 16.

Strain distribution profile in the circular diaphragm

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Fig. 17.

Receiver unit and display circuit ready for online measurement.

3.

Fig. 18.

Receiving data were monitored in a PC and stored for further analysis.

Results and Discussions

The system was designed to measure maximum tire pressure of 2.5kg/cm2 or 35.55psi. The system was configured to transmit the tire pressure value continuously to a central receiver. The transmitter was also tested with 54sec transmission delay to minimize the transmitter battery power dissipation. The output of the sensor was displayed in the central receiver using an LCD. Whenever the pressure will go above 2.5kg/cm2 and below 2.2kg/cm2, the warning LED was configured to blink with a warning sound using a buzzer. Different outputs of the sensor with different input tire pressure levels were taken at both room temperature (33°C) and also at an elevated temperature to find out different static characteristics of the sensor. Different sensor characteristics were also studied by analyzing the sensor outputs with respect to the input pressure levels. Table. 3. Input tire pressure levels (kg/cm2) Vs Sensor output voltage (volts) Pressure (kg/cm2)

Output1(volts)

Output2(volts)

Output3(volts)

Output4(volts)

Output5(volts)

Output6(volts)

Output7(volts)

0

0.006

0.006

0.006

0.006

0.006

0.006

0.006

0.2

0.066

0.060

0.066

0.067

0.068

0.066

0.066

0.4

0.180

0.178

0.182

0.178

0.180

0.179

0.180

0.6

0.300

0.297

0.300

0.296

0.300

0.297

0.300

0.8

0.416

0.416

0.420

0.416

0.420

0.416

0.416

1.0

0.530

0.530

0.531

0.530

0.530

0.531

0.530

1.2

0.657

0.658

0.658

0.659

0.658

0.658

0.659

1.4

0.749

0.748

0.749

0.747

0.749

0.750

0.749

1.6

0.859

0.859

0.859

0.859

0.859

0.859

0.859

1.8

0.959

0.959

0.959

0.959

0.959

0.959

0.959

2.0

1.060

1.060

1.060

1.061

1.060

1.060

1.062

2.2

1.165

1.165

1.165

1.165

1.165

1.165

1.166

2.5

1.355

1.355

1.355

1.355

1.355

1.355

1.355

Out put8(vo lts) 0.00 6 0.06 7 0.17 8 0.29 6 0.41 6 0.53 2 0.65 8 0.74 7 0.85 9 0.95 9 1.06 0 1.16 6 1.35 5

3.1. Sensor characteristics: From the input to the output, a sensor may have several conversion steps before it produces an electrical signal. For instance, pressure inflicted in the tire first results change in strain in the diaphragm, which, in turn, causes deflection, which, in turn, results in an overall change in resistance in the strain gauge bonded on the diaphragm. This change in resistance will cause unbalance in the strain gauge bridge circuit, which, in turn, results in output voltage change in the bridge circuit. From the input pressure and output voltage readings different sensor characteristics can be found out. The sensor characteristics studied in this project are listed [Table. 4].

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Ambarish G. Mohapatra / International Journal of Engineering Science and Technology (IJEST) Table.4 Sensor Characteristics

Transfer function Full-scale input Full-scale output Sensitivity Hysteresis

Repeatability Resolution Accuracy Calibration error Environmental factor (temperature)

3.2. Transfer function: An ideal or theoretical output stimulus relationship exists for every sensor. If the sensor is ideally designed and fabricated with ideal materials by ideal workers using ideal tools, the output of such a sensor would always represent the true value of the stimulus. The ideal function may be stated in the form of a table of values, a graph, or a mathematical equation. An ideal (theoretical) output–stimulus relationship is characterized by the socalled transfer function. This function establishes dependence between the electrical signal S produced by the sensor and the stimulus s: S =f (s). That function may be a simple linear connection or a nonlinear dependence, (e.g., logarithmic, exponential, or power function). In many cases, the relationship is one-dimensional (i.e., the output versus one input stimulus). A one-dimensional linear relationship is represented by the equation [5] S =a +bs [5] Where a is the intercept (i.e. the output signal at zero input signal) and b is the slope, which is sometimes called sensitivity. S is one of the characteristics of the output electric signal used by the data acquisition devices as the sensor’s output. It may be amplitude, frequency, or phase, depending on the sensor properties. Logarithmic function: S =a +b ln s [6] Exponential function: [7] S =aeks Power function: [8] S =a0 +a1sk Where k is a constant number. A sensor may have such a transfer function that none of the above approximations fits sufficiently well. In that case, a higher-order polynomial approximation is often employed. In this project by considering the input tire pressure levels and the corresponding output voltages, a linear transfer function was obtained as the equations (9 and 10) written below. The function established between the electrical signal S produced by the sensor and the stimulus‘s’ is given by: S=f(s) Theoretical calculation: S= 0.4524*s [9] Practical calculation: [From the graph as in Figure 19] S= 0.55*s - 0.021 [10]

Fig. 19.

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Graph between input pressure [kg/cm2] Vs S/C output voltage [V]

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3.3. Full-scale input: A dynamic range of stimuli which may be converted by a sensor is called a span or an input full-scale (FS). It represents the highest possible input value that can be applied to the sensor without causing an unacceptably large inaccuracy. For the sensors with a very broad and nonlinear response characteristic, a dynamic range of the input stimuli is often expressed in decibels, which is a logarithmic measure of ratios of either power or force (pressure). It should be emphasized that decibels do not measure absolute values, but a ratio of values only. A decibel scale represents signal magnitudes by much smaller numbers, which, in many cases, is far more convenient. By definition, decibels are equal to 10 times the log of the ratio of powers. P2 [11] 1dB = 10 log

P1

In a similar manner, decibels are equal to 20 times the log of the force, pressure, current, or voltage. S [12] 1dB = 20 log 2 S1

In this project the sensor was designed according to the sensor design equation (1) for the maximum input tire pressure level of 2.5kg/cm2. Means the sensor can sense a pressure range of 0 to 2.5kg/cm2. Hence the highest possible input value that can be applied to the designed sensor without causing an unacceptably large inaccuracy is 2.5kg/cm2. Full-scale input = 2.5kg/cm2 = 35.55psi 3.4. Full-scale output: Full-scale output (FSO) is the algebraic difference between the electrical output signals measured with maximum input stimulus and the lowest input stimulus applied. Full-scale output = 1.131 volts [Theoretical] = 1.355 volts [Practical] 3.5. Sensitivity: Sensitivity is a measure of the change in output of an instrument for a change in input. Generally speaking, high sensitivity is desirable in an instrument because a large change in output for a small change in output implies that a measurement may be taken easily. Sensitivity must be evaluated together with other parameters, such as linearity of output to input, range and accuracy. The value of the sensitivity is generally indicated by the transfer function. Thus, when a pressure transducer output 0.55V per kg/cm2, the sensitivity is 0.55V/kg/cm2. The sensitivity of the sensor was found out by plotting a graph between input tire pressure levels and output voltage readings from the sensor. Sensitivity = 0.45V/kg/cm2 [Theoretical] = 0.55V/kg/cm2 [Practical] 3.6. Hysteresis: Hysteresis error is a deviation of the sensor’s output at a specified point of the input signal when it is approached from the opposite directions (Figure. 16). For example, a displacement sensor when the object moves from left to right at a certain point produces a voltage which differs by 20 mV from that when the object moves from right to left. If the sensitivity of the sensor is 10 mV/mm, the hysteresis error in terms of displacement units is 2 mm.

Fig. 20.

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Measurement of Hysteresis error

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Fig. 21.

Hysteresis calculation

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In these work two sets of readings, both in forward and backward directions were plotted as in Figure 21 and the maximum deviation was found out as 0.02kg/cm2. Hysteresis = 0.02kg/cm2 [Theoretical] 3.7. Repeatability: A repeatability (reproducibility) error is expressed as the maximum difference between output readings as determined by two calibrating cycles [Figure.18), unless otherwise specified. It is usually represented as % of (Full-Scale) FS: [13] Δ δr = ×100% FS Possible sources of the repeatability error may be thermal noise, build-up charge, material plasticity, and so on.

Fig. 22.

Fig. 23.

Repeatability error

Repeatability error calculation

Therefore by taking two sets of readings (RUN1 and RUN2), the repeatability error was found out as the graph (Figure. 19). From the graph the deviation found out as ∆ = 0.02 from 1st and 2nd run. Repeatability error = (0.02/2.5)*100 = 0.8 %. 3.8. Resolution: The resolution (R) is the smallest increments of stimulus which can be sensed. Resolution (R) = 0.0355Kg/cm2 0.50509psi Where R is the smallest increments of stimulus which can be sensed

3.9. Accuracy: The deviation [Figure 24] can be described as a difference between the value which is computed from the output voltage and the actual input value. At 2.5kg/ cm2 output voltage = Pressure = = = Error = % Error = =

Fig. 24.

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1.355 V Full-scale output/Sensitivity (1.355/0.4524) 2.99 kg/cm2 2.99 – 2.5 = 0.495 kg/cm2 0.495 × 100 2 .5

19.80% [Inaccuracy]

Accuracy error calculation

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4.

Conclusion

The automobile Tire Pressure Monitoring System (TPMS) helps the driver to be conscious about the change in tire inflation pressure. The system was designed successfully and also tested with different tire pressure levels at different environmental conditions. The pressure sensor was designed using a self temperature compensated diaphragm type strain gauge, operating temperature range of -75°C to +95°C, tested at a temperature range of 33°C – 70°C. The pressure data was successfully transmitted with a new transmission scheme to minimize the power consumption and maximize the transmitter battery life. Acknowledgments The authors thank to Dr. R. N. Pal, retired Professor IIT Kharagpur, India and his team for their help in conducting experiments with tire pressure monitoring system (TPMS). We also thank Prof. A.K.Tripathy, Silicon Institute of Technology, Orissa for his assistance in the research work in the laboratory. References [1]. Jiaming Zhang; Quan Liu; Yi Zhong; “A Tire Pressure Monitoring System Based on Wireless Sensor Networks Technology”, International Conference on MultiMedia and Information Technology, 2008. MMIT '08, Page(s): 602 – 605. [2]. Yulan Zhou; Yongsheng Chai; Yantao Wang; “Tire Pressure Monitoring System for trucks”, Chinese Control and Decision Conference, 2008. CCDC 2008, Page(s): 1743 – 1745. [3]. Yu Shiming; Tang Jianbin; Qiu Hong; Cao Chengrong; “Wireless Communication Based Tire Pressure Monitoring System”, International Conference on Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007, Page(s): 2511 – 2514. [4]. Qi Zhang; Bo Liu; Guofu Liu; “Design of tire pressure monitoring system based on resonance frequency method”, IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2009. AIM 2009, Page(s): 781 – 785. [5]. Song, H.J.; Colburn, J.S.; Hsu, H.P.; Wiese, R.W.; “Development of Reduced Order Model for Modeling Performance of Tire Pressure Monitoring System”, IEEE 64th Vehicular Technology Conference, 2006. VTC-2006 Fall. 2006, Page(s): 1 – 5. [6]. Yulan Zhou; Yongsheng Chai; Yahong Lin; Kun Wang; “An application of multi-sensor information fusion in Tire Pressure Monitoring System”, International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2010, Page(s): 187 – 190. [7]. Kukshya, V.; Song, H.J.; Hsu, H.P.; Wiese, R.W.; “Impact of Inter-Vehicular Interference on the Performance of Tire Pressure Monitoring Systems”, IEEE 66th Vehicular Technology Conference, 2007. VTC-2007 Fall. 2007, Page(s): 778 – 781. [8]. Fleming, B.; “Tire pressure-monitoring systems rollout [Automotive Electronics]”, IEEE Vehicular Technology Magazine, Volume: 4, Issue: 3, Page(s): 6 – 10. [9]. Velupillai, S.; Guvenc, L.; “Tire Pressure Monitoring [Applications of Control]”, IEEE Control Systems 2007, Volume: 27 , Issue: 6, Page(s): 22 – 25. [10]. Nicolas persson, Fredrik Gustafsson, Department electrical engineering, Linkoping University, Markus drevo, Nira Dynamics AB, “Indirect tyre pressure monitoring using sensor fusion”, SAE paper, 2002-01-1250. [11]. Hyok J. Song, Hui P. Hsu, Richard Wiese, and Timothy Talty, HRL Laboratories, LLC, General Motors Corporation, MilfordNanen, MI USA, “Modeling Signal Strength Range of TPMS in Automobiles”, IEEE sensor J., vol. 4, pp. 3167-3170, 2004. [12]. Yanhong Zhang, Bingwu Liu, Litian Liu, Zhimin Tan, Zhaohua Zhang, Huiwang Lin and Tianling Ren Institute of Microelectronics, Tsinghua University, Beijing, “Design, Fabrication and Characterization of Novel Piezoresistive Pressure Microsensor for TPMS”, IEEE sensor J., vol. 1, pp. 443-446, 2006. [13]. Christian Kolle, Wolfgang Scherr, Dirk Hammerschmidt, Gerhard Pichler, Mario Motz, Bernhard Schaffer, Bernhard Forster, Udo Ausserlechner Infineon Technologies Austria AG, Villach, Austria1, “Ultra Low-Power Monolithically Integrated Capacitive Pressure Sensor for Tire Pressure Monitoring”, IEEE sensor J., vol. 4, pp. 244-247, 2004. [14]. K. Rajanna, S . Mohan, M. M. Nayak, N. Gunasekaran, and A. E. Muthunayagam, “Pressure Transducer with Au-Ni Thin-Film Strain Gauges”, IEEE Transactions On Electron Devices J., vol. 40. No. 3, 521-524, 03/1993. [15]. Matsuoka, Y.; Yamamoto, Y.; Tobita, T.; Shimada, S.; Yasukawa, A.; “Design method for sensing body of differential pressure transmitter using silicon diaphragm-type pressure sensor”, IEEE Transactions on Instrumentation and Measurement, Volume: 44 , Issue: 3, Page(s): 791 – 794.

About the author Ambarish G. Mohapatra received the M.Tech. degree in Sensor System Technology from Vellore Institute of Technology, VIT University, Vellore, India, in 2008 and the Bachelor in Electronics and Communication Engineering (ECE) from National Institute of Science and Technology (NIST), Berhampur, Inida, in 2004. He is currently pursuing the Doctor of Science in Technology degree and is working as Assistant Professor in Silicon Institute of Technology, Bhubaneswar, India. He has number of national and international papers in the field of sensing and control, where his interests are sensors and transducers, MEMS, wireless sensor network and Biomedical signal processing.

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