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

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Discussion Overview

The discussion revolves around calculating sensor non-linearity from a polynomial equation representing the sensor's output. Participants explore the ideal straight line relationship, graphing non-linearity, and determining maximum non-linearity expressed as a percentage. The scope includes homework-related problem-solving and mathematical reasoning.

Discussion Character

  • Homework-related
  • Mathematical reasoning
  • Exploratory

Main Points Raised

  • Post 1 presents the polynomial equation for the sensor output and seeks guidance on deriving the ideal straight line equation, plotting non-linearity, and calculating maximum non-linearity.
  • Some participants suggest plotting the function f(I) and performing regression to find the best fitting line, questioning the definition of "ideal straight line."
  • One participant proposes simplifying the problem by assuming the ideal linear characteristic as O=1+2I for initial calculations.
  • Another participant provides a straight line of best fit calculated using WolframAlpha, suggesting that calculating a line of best fit may be more complex than expected.

Areas of Agreement / Disagreement

There is no consensus on the definition of the "ideal straight line" or the method to calculate non-linearity. Multiple approaches and interpretations are presented, indicating ongoing uncertainty and disagreement.

Contextual Notes

Participants express uncertainty about the expectations for the problem and the complexity of regression analysis. There are also questions regarding the correctness of the polynomial coefficients.

Who May Find This Useful

Students working on sensor output analysis, those interested in polynomial equations and regression methods, and individuals studying non-linearity in sensor measurements.

ilovescience85
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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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