Nilanjan Byabarta,Abir Chatterjee,Swarup Kumar Mitra,



Sensor,Linearization,curve fitting,non-linearity,Thermocouple,Python,


In this study, this paper presents a new method for linearizing thermocouple data using Python and compares the performance of higher-order polynomial models in achieving linearization. It involves fitting a non-linear model to the thermocouple data using the curve fit function from Python and then calculating the linearized temperature values using the optimized parameters. The paper also presents a comparative analysis of different polynomial models, ranging from 3rd to 12th order, and evaluates their performance in achieving linearization. The results show that higher-order polynomial models generally perform better than lower-order models in achieving linearization, but also have a higher risk of overfitting. The paper concludes that the presented method provides an effective way of linearizing thermocouple data using Python and that the choice of polynomial model should be carefully considered based on the data characteristics and the desired level of accuracy.


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