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The linear characteristics of temperature sensors are affected by material properties, aging, self-heating, lead resistance, and external interference. This study aims to improve sensor characteristics by overcoming power consumption and response time limitations. An evolutionary optimised log-ratiometric function is implemented for sensor linearisation using a translinear circuit. The differential evolution optimisation strategy is used to find the optimum values of the linearising parameters in the non-linear function. Further, these parameters are applied to the current mode circuit to linearise the selected sensors as an input current source. Due to higher fidelity, better comprehensive dynamic range, and improved linear areas, implementing the non-linear function using the BJT-based current mode circuit results in a better full-scale error reduction capability than MOSFET-based translinear implementation. Furthermore, the devices such as Gallium Arsenide Field-Effect Transistors (GaAsFET) and Modulation-Doped FET (MODFET) could be used in place of BJT in the future for additional error reduction due to rapid response speed, low power consumption, and reduced internal noise. Thus, the translinear implementation of the non-linear function can enhance the sensor characteristics in all aspects. [ABSTRACT FROM AUTHOR]

Linear response characteristics of sensors are affected by ageing and changes in material properties. However, existing methods for improving these characteristics are disadvantaged by recurrent full-scale errors and insufficient speed. Accordingly, this study aims to reduce temperature sensor non-linearity through implementation of evolutionary optimised non-linear functions via a translinear-based application-specific integrated circuit. Moreover, the translinear-based analogue computation method is compared to a proposed field programmable gate array (FPGA)-based digital computation methodology to develop an alternative method for linearisation at sensor nodes (edge computing). The optimal values of the linearisation parameters for selected thermocouples are determined using the covariance matrix adaptation evolutionary strategy. Specifically, these optimal values are input in order to realise the non-linear functions. Experimental results reveal that FPGA offers a lower full-scale error than that of the translinear-based computation, although the translinear method can accomplish the required linearisation with fewer components (e.g. Data Converters), less delay and less power. Further, analogue computation through the proposed single chip-based method can utilise the latest processes, e.g. gallium nitride or pseudomorphic high electron mobility, for an enhanced error reduction. The comparative result shows that the translinear method with recommended processes can correct the non-linearity of sensors in all aspects. [ABSTRACT FROM AUTHOR]