Optimized Algorithm for Industrial Process Instrumentation Calibration based on Nonlinear Function Approximation

Calibration is an all important operation in the instrumentation industry for determining the relationship between the output(s) (or response) of a measuring instrument and the value of the input(s). Common industrial practice is to use a finite number of calibration points covering the entire calibration range. The common calibration method is to select the equidistant (over the calibration range) operating (calibration) points and performing linear interpolation operation between them. Although this ensures uniformity, but it does not guarantee effective and optimal composite modeling of the linearity and the non-linearity involved. In this paper, we propose a nonlinear function approximation-based optimized calibration technique which takes into account the composite effect of the underlying linear and nonlinear behavior of the process. Application examples are cited to substantiate the improved accuracy of the proposed algorithm over the common calibration practice.