![]() If you plan to use a linear equation to predict the measurement uncertainty of a given measurement range, then you should include linearity into your uncertainty analysis. You should include linearity in your uncertainty analysis anytime you are estimating uncertainty for a continuous measurement range. When Should You Include Linearity Uncertainty At least consider whether or not it affects your measurement uncertainty. Nonetheless, linearity uncertainty is important. If you are unable to calculate linearity, try reading the manufacturer’s manuals and datasheets to see if they list it in the specifications. If the result is significant, then include the results in your uncertainty budget. However, I would still include it your uncertainty budget to prove you considered it. If the result is small or negligible, great! Now, you have objective evidence to support your opinion. I say, test it and let the results speak for themselves. I often hear people say that linearity is not important or doesn’t need to be included in an uncertainty budget. If you use an equation to estimate uncertainty across a measurement range, then you may need to consider evaluating linearity uncertainty. Linearity uncertainty is important because it allows you to consider the effects of non-linear behavior in a measurement function. No matter what type of equipment you are using, do not forget to consider linearity in your uncertainty analysis unless it is negligible or inappropriate to do so. ![]() mercury, spirit-filled, etc.),Īdditionally, many electrical devices can exhibit non-linear behavior too. Pressure Transducers (with strain gauges).For example, here is a list of devices that are commonly evaluated for linearity Non-linear behavior is most commonly observed for many mechanical devices and physical materials. Therefore, we must take linearity uncertainty into consideration. Still, prediction equations and coefficients do fully correct for their non-linear behavior. So, we try to correct them with coefficients and linear or polynomial equations to make their performance more predictable. The measurement functions of most devices are not actually linear. When you think about how measurement equipment functions, you probably assume that its measurement performance is linear across the measurement range. Therefore, linearity uncertainty would the uncertainty associated with non-linear behavior observed across the range of an assumed linear function. Non-linearity is the deviation from a straight line over a desired range. Linearity is the property of a mathematical relationship or function that can be graphically represented as a straight line. ![]() How to Calculate Linearity Uncertainty (Step By Step).Which Uncertainty Method You Should use.When Should You Include Linearity Uncertainty.In this guide, you are going to learn everything that you need to know about linearity uncertainty, including Therefore, I thought that it would be a great idea to develop a guide to show you how to estimate linearity uncertainty step by step using Microsoft Excel. If you have a test or measurement function that spans across a range of values, then you may need to include linearity in your uncertainty analysis. However, I do not see it included in uncertainty budgets as often as it should be. ![]() It is a common characteristic published in the manufacturer’s specifications for various types of measurement equipment. linearity error or non-linearity) is a source of uncertainty that should be included in most uncertainty budgets.
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