Evolutionary optimised nonlinear function for linearisation of constant temperature anemometer

A simple software method to derive linearised output for constant temperature anemometer (CTA) is presented. The method uses a nonlinear ratiometric-logarithmic function, which consists of two parameters whose optimal values are determined by minimising the objective function (mean square error) to improve the linearity of CTA signal. Covariance matrix adopted evolutionary strategy algorithm, which generates optimal values consistently, is employed to determine the optimal values of linearisation parameters. The proposed linearisation algorithm was implemented using LabVIEW 7.1 Professional Development System in a personal computer that provides the facility to interface with the National Instruments data acquisition module PCMCIA-NI DAQCard-6024E. Experimental studies have been carried out using practical air-flow velocity measurement data obtained form Dantec Dynamics practical guide. The performance measures such as full-scale error and root mean square error are considered to compare the performance of the proposed method with the methods reported for linearisation of transducers. Experimental results reveal that the proposed evolutionary optimised nonlinear function-based software lineariser works well for CTA, and it can be suitable for computer-based flow measurement/control systems.