Multi Channel Sensor Linearization in Field Programmable Gate Array for Real Time Applications

In industrial applications multi-channel data acquisition and logging is of prime importance for process monitoring and control. In such situations linearization of the non-linear responses obtained from multichannel data acquisition systems is of prime importance for precise monitoring and control. Although various techniques have been developed for sensor linearization, real time multi channel linearization approaches are rare. This paper describes FPGA (Field Programmable Gate Array) implementation of different linearization techniques for multi-channel nonlinear sensor characteristics. The proposed multi-channel linearization techniques are implemented in real time using piecewise linearization (PWL), look up table (LUT) based linearization, linearization by interpolation (LI) and artificial neural network (ANN) based linearization methods. We have discussed the different aspects of these linearization techniques and the trade-off between accuracy and implementation area in FPGA. The comparative analysis was performed by using identical thermistors connected to 8 channels for linearization and the performance of each method was analyzed. The performance of different techniques of linearization is estimated on the basis of logic utilization, linearization accuracy, execution time, noise immunity and speed of operation. Fixed point arithmetic has been used for data representation in the FPGA implementation.Copyright © 2015 IFSA Publishing, S. L.