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using matlab to find steps 1-10

Calibration and sensing Consider a thermistor temperature sensor (Fig. 1) with a pull-up resistor R1 connected to a 10-bit anThe full model transfer function can be manipulated to yield an inverse transfer function that enables the processor to compunref 678 at Tref 303.15 K (30°C) nc 203 at T 363.15 K90°c). Solve the two unknown parameters, B and Rref, by substituting theSensing Now, let us see what involves using the linear piecewise approximation (3) (10 pts) Let us break up the transfer func

Calibration and sensing Consider a thermistor temperature sensor (Fig. 1) with a pull-up resistor R1 connected to a 10-bit analog-to-digital (ADC) converter (a full scale No-210-1=1023 counts corresponding to the reference voltage Vref). The thermistor is used to measure temperature in the total input span from -10°C to 110°C. knots n(t VO R1 A/D GND Temperature Fig. 1 The output count of the thermistor measurements circuit can be modeled by a nonlinear function of temperature, i.e., full model transfer function x ref ref where Tx is the measured temperature, Rref is the resistance of the thermistor at a reference temperature Tref, and β is the characteristic temperature. All temperatures and β are in degrees Kelvin. The full model transfer function can be manipulated to yield an inverse transfer function that enables the processor to compute the input temperature in Kelvin
The full model transfer function can be manipulated to yield an inverse transfer function that enables the processor to compute the input temperature in Kelvin: nx R Both equations contain two unknown parameters, β and Rref. The entire sensor circuit including ADC needs to be calibrated at the temperature Tref and another temperature Tc. In the circuit, we use a pull- up resistor R1 = 2 k Calibration For calibration, we select two calibrating temperatures in the operating range as Tref 303.15 K ( 30°C) and T 363.15 K (90°C), respectively. During calibration, the thermistor sequentially is immersed into a fluid bath at these two temperatures, and the ADC output counts are registered respectively as 1/2
nref 678 at Tref 303.15 K (30°C) nc 203 at T 363.15 K90°c). Solve the two unknown parameters, B and Rref, by substituting these pairs of calibration data to the nx and Tx in the inverse transfer function. This completes the calibration BK (5 pts) Rref (5 pts) Now, since all parameters in the full model transfer function are fully characterized, the inverse transfer function can be used for computing temperature from any ADC count in the operating range. We assume this is the most accurate way of computing true temperature.
Sensing Now, let us see what involves using the linear piecewise approximation (3) (10 pts) Let us break up the transfer function just into multiple sections (Fig. 1b) as shown in the look-up table and store it in a memory for processor to compute the sensing temperature. From calibration, we find the ADC outputs at these knot temperatures and have the count-temperature coordinate pairs plugged into a look-up table. Find the missing count numbers 3 and in the Table Knot Counts 1n Temp (C)10 4 3846 678 486 320203 90 10 30 50 70 110 (4) (30 pts) Consider some unknown temperatures the ADC outputs counts n 267,506, and 823. Compute the corresponding temperatures from the full model transfer function and the linear pricewise transfer function using the look-up table. Note that T in the transfer function has a unit in Kelvin degrees and Temp (°C) Temp (K) 273.15 Counts n Temp (C) Inverse tran. func. Temp (C) Linear piecewise 267 506 823 6 8 You may find some deviation between the results calculated by the full model transfer function and approximated transfer function. For a more demanding application, use more central knots to reduce errors
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