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Characterization and Compensation for a High
Performance SP82 Pressure Sensor
Sabin K.C, Yanni Chang, Ana Jessica daRocha, Hans Christian Nazareno, Huimian Lu
Abstract— The SP82 Pressure sensor manufactured by
MEMSCAP was investigated in terms of linearity, hysteresis
and offset. Melxesis microcontroller was then used to optimize
signal output.
Index Terms—
counteracts the cross-sectional giving a four-element linear
sensing setup[2]. The circuit diagram for the Wheatstone
bridge configuration is shown in figure 1.
Due to the high volume of demand the price of MEMS has
descended in recent prese1. This trend extends the marked
of applications for miniaturized sensor systems. Although
the marked is expanding, high precision and long term
stability is still an essential requirement.
Figure 1: Wheatstone configuration in pressure sensor
The pressure sensor is commonly used for altitude
monitoring for aerospace applications, but the purpose of
the sensor can vary from military defense to everyday
equipment as washing machines to increase the power
efficiency by monitoring the water level. To satisfy the
demands of the consumer a high sensitivity, linearity and
suitable calibration system to compensate for different
environmental parameters is essential .
In this research we discuss the system errors and nonlinearity and sensitivity. The measurements were analyzed
using LabVIEW, interfaced with a National Instruments
DAQ. For the compensation curve and sensitivity
amplification a pre-programmed Melxis microcontroller
will be connected to the DAQ and the sensor, the
performance will be investigated in range from
approximately 0 to 1 bar.
The piezoresistive working principle is being executed by
using an n-type silicon diaphragm and doping portions of
the needed areas to p-type material. The p-n junction
generates a resistivity which can be manipulated by
changing the geometry of the junction area. The resistivity
of the material is linearly depended on the surface area
implying that the strategy is useable in sensing applications.
The cross-sectional view of piezoresestive pressure sensor
is shown in figure 2.
The transducing of the mechanical pressure to the electrical
signal is achieved by piezoresistive effect induced by
mechanical strain being applied on the substrate diaphragm.
Four sensing elements arranged with two longitudinal and
two cross-sectional piezoresistors placed at the edges of the
diaphragm connected to a Wheatstone bridge setup. The
bridge is connected such as the longitudinal resistors
Figure 2: Cross-sectional view of Piezo-resestive sensor
We could vary the pressure value, starting from
environment pressure – 1 bar – to a value approaching zero
and for then to measure the reversibility. This process was
repeated in order to determine the system repeatability,
hysteresis and to present compact data from averaging
values. Observing the graph Fig. 5, we can verify that the
pressure sensor we were using obtained a highly linear
relation between the voltage and pressure, for both
increasing and decreasing pressure input.
Figure 3: Input/output specifications delivered by pressure sensor
producer MEMSCAP.
Pressure x Voltage
Voltage (V)
Fig. 3 gives specifications of input errors and resulting
output errors. To verify MEMSCAP calculations of output
errors, measurements and calculations with respect to 1 bar
absolute range, and disregarding all temperature variables
will be executed.
Pressure (bar)
The pressure sensor was placed in a vacuum compartment
and connected to a pump, where we could change the
values of pressure from environment pressure approaching
to zero.
Figure 5. Pressure and voltage relation
The system was uploaded to a DAQ (National Instruments),
which was connected to a computer in order to collect the
respected voltage values at an interface created on
LabVIEW (Fig. 4)
MLX90308 purchased from Melexis is a programmable
microcontroller which is used to perform signal
conditioning for sensors. The microcontroller was used for
regulating gain, offset and linearity, to fully utilize the
For the SP82 sensor, we used the Melexis
microcontroller to enhance the sensitivity and adjust the
offset. Due to the high linearity of the sensor 0.2%FSO, the
non-linearity compensation was not required, but to certify
the non-linearity compensation system we reversed the
procedure and made the response non-linear. The
microcontroller is interfaced with a computer software
produced by Melexis as shown in figure 9. The function
parameters are related to the signal manipulation for
calibration of the sensor.
Figure 4. LabVIEW interface
Melexis works in digital- and analog mode. Where the
analog mode provided the best accuracy for the gain and
offset calibration. For the non-linearity compensation,
digital mode was used, in digital mode the sample is held
while the data from the sensor is retrieved to the
microcontroller algorithms. The data flow follows the path
as shown in figure 6. where the data is sent from the
computer software to the EEPROM of the microcontroller.
For the reversed non-linearity compensation, we applied
suitable values to the offset and gain parameters
corresponding to the optimal values. Then Pi and PCi
parameters were changed for calculating the compensation.
Inside the microcontroller the signal is changed from
analogue to digital and again back to analogue value, from
which we could read out from the initial signal interface.
Vout = HG ∗ FG ∗ CG ∗ V in
where, HG=hardware gain fixed 20V/V
CG=coarse gain
FG=fixed gain
This is just used to calculate the range of the data that we
should obtain.
Afterwards in digital mode we can non-linearize the signal.
We use five different pressure points to observe the
characteristics of the melexis board, so in digital mode we
obtained the values for Pi and PC by using the steps
provided by datasheet (hit and trail method)[3].
Finally after obtaining the values for all the parameters we
then measured the output voltage for the respective pressure
points for increasing and decreasing pressure applied.
Figure 6: Block diagram of MLX90308
Circuit connection for voltage mode is given in figure
7.And how the objects are connected are showed on figure
8. And all the equipments we need are also listed in the
Table 1. It shows the main things in the figure 8 for details.
After characterizing the sensor we needed to connect the
signal conditning element (melexis) and observe the
corresponding characteristics.
First the sensor and data acquisition board were connected,
then the Melexis microcontroller was connected with the
power supply (+12v) and with serial cable (RS232
connector) to the computer. Sensor pins (VBP and VBN)
were connected accordingly.
The programmable “Edit Parameter” box was opened from
the software provided by the Melexis. Then in analog mode
optimal values of gain and offset were obtained. We choose
suitable value for the coarse offset (CO) and then searched
for the value of the fixed offset(FO) that cancels the offset.
We could not reach that condition until Vin=0. From
datasheet suitable value for gain can be obtained by using
datasheet as:
Figure 7: Voltage mode circuit diagram connection
line with decreasing pressure. Due to the high linearity of
the sensor the error range of the simplification will be
smaller. The hysteresis between the lines was calculated to
be 0.00423%.
Figure 8: Objects connection
Pressure Chamber
Pressure Sensor
Evaluation Kits
Power Supply
Number Anaylsis
Figure 9: Pressure vs Voltage curve obtained from sensor
Changing the pressure for
the Sensor
SP 82
Melexis DK90308 kits
+12 V DC
Read the voltages chaning
by the pressure
Excel & Matlab
Table 1: Equipments and User
Figure 10: Parameter values computed to Melexis demo software.
From the measurement of the sensor without any
microcontroller manipulation we calculated the regression
line to have a form of:
Y = 0.1129x – 0.0124
And from this figure, it is easy to read all the P and PC numbesr.
From our calculated regression line the full scale output
was calculated to be 100.5mV corresponding to
125mV±30%, likewise the offset value of 12.4mV suits
with the ±50mV(max) and the ±10mV(typical) value from
the specification sheet.
For the non-linearity %FSO the maximum value of the
difference from the measured line and the regression line
was calculated from a range starting from pressure above
0.1bar. After calculations the maximal non-linearity was
0.18% fsd.
For the hysteresis and repeatability measurements a
simplification by calculating the difference between the
regression line with increasing pressure and the regression
Figure: 11 Pressure/voltage response with max non-linearity 5% of fsd.
From the characterization measurements we can conclude
that the performance of the sensor linear and sensitive. The
Melexis microcontroller is practical tool for increasing
performance for different applications, increasing
sensitivity and tuning in the offset. The non-linearity
compensation is also a powerful tool enhancing the
precision of the sensor output.
In this report our measurements are compromised by our
measurements tools, where the accuracy of the reading
done for calculations suffers from leakage of pressure from
the pressure chamber. Due to this the specification
calculations will not be as reliable as if we had a better
pressure chamber giving higher stability. All though, the
results shows conclusively that the sensor performance of
the sensor is well defined and useable for practical
MEMSCAP, "SP 82 Pressure Sensor datasheet," ed, July 2006.
[2] J. P. Bentley, Principles of Measurement Systems: Pearson Prentice
Hall, 2005.
[3] Melexis, "MLX90308 Programmable Sensor Interface," 6th ed, April
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