How Do You Calculate Sensor Non-Linearity from a Polynomial Equation?

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The discussion focuses on calculating sensor non-linearity from a polynomial output equation. The ideal straight line equation for the sensor is proposed as O = 1 + 2I, which is essential for determining non-linearity. Participants suggest plotting the output against the ideal line to visualize deviations and calculate non-linearity as a percentage of output span. There is uncertainty about the complexity of regression analysis and whether it aligns with course expectations. Overall, guidance emphasizes verifying the ideal line and using it to explore non-linearity through graphical representation and basic calculations.
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Homework Statement


The input range of a particular sensor is from 0-6 units and it's output is modeled by the equation O = ƒ(I) = 1+2I+0.005I^2-0.00833I^3

Ideally the output should be relate to the input by the straight line equation (ISL) if the form O=kI+a

A) give the law if the ideal straight line for the sensor
B) Plot a graph of the non linearity (N)I, against input I
C) from the graph, determine the maximum non linearity of the sensor, expressed as a percentage if output span
D) Attempt to determine the maximum percentage non linearity by mathematics.

Homework Equations


O = kI+a

The Attempt at a Solution


I not sure where to start here to be honest.
A) O = 1+ 2I + 0.0025I so ideal straight line equation is O= 2.0025I + 1?
B) I know once the above equation is right it's a case of inputting the input range into it to get the graph plot points so in put 0 would give output of 1 and so on but this is all based the correctness of the equation in A.
C) depends on A+B
D) depends on A+B

Any guidance on the above would be greatly appreciated.
 
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I am not familiar with "ideal straight line", but if I had to guess, you should plot the f(I) for 0<I<6, and do regression to find the best fitting line. I would also assume plotting nonlinearity vs input means plot the different between f(I) and the best fitting line at each value of I.

Did your teacher/book explain what is expected for this kind of thing?
I am just guessing here, so I would review what was covered in the course
 
I suggest that ilovescience85 should ask other students in the class how they are working this problem. Perhaps regression is beyond the course?

Meanwhile, solve the problem assuming the ideal linear characteristic is simply O=1+2I
and you can later speedily rework this if a better-fitting line is intended.
 
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