Fitting temperature sensor data using (Linear, polynomial, and boltzmans' models) in excel. also, how to handle the relative humidity (compensation)
Budget: $30 – $250 USD
The attached Excel sheet contains characterization data for a temperature sensor. It includes the sensor’s output voltage versus ambient temperature for three different values of relative humidity (RH).
1) Fit the data to the following models (specify what will you do about the sensor’s output dependency on RH) , and specify which model is the best and why:
a. A Linear model (specify the linearity as % of FS)
b. A polynomial model (3rd degree)
c. A Boltzman equation model
2) Using the three models in part (1) and whatever RH compensation method you devised in part (2), specify the errors for the following readings of the sensor’s output: [20 points]
RH value Sensor’s output voltage Error (% of FS)
35% 0.55 V
45% 1.00 V
55% 1.50 V
1) Fit the data to the following models (specify what will you do about the sensor’s output dependency on RH) , and specify which model is the best and why:
a. A Linear model (specify the linearity as % of FS)
b. A polynomial model (3rd degree)
c. A Boltzman equation model
2) Using the three models in part (1) and whatever RH compensation method you devised in part (2), specify the errors for the following readings of the sensor’s output: [20 points]
RH value Sensor’s output voltage Error (% of FS)
35% 0.55 V
45% 1.00 V
55% 1.50 V