SOFTWARE-CONTROLLED MEASUREMENT CONVERTER FOR CAPACITIVE SENSORS

Abstract

This study focuses on the development and implementation of a software-controlled measurement converter for capacitive sensors. The system addresses critical challenges in modern sensor technology, particularly the temporal and temperature instability of capacitive measurements and the significant influence of external factors on measurement results. This is especially crucial in chemical and biochemical analysis applications, where the measured changes in capacitive parameters can be extremely small (10^-15...10^-13 F), making them highly susceptible to interference from external objects (10^-12...10^-11 F).

The developed converter is based on the PSoC (Programmable System-on-Chip) architecture, implementing the SCC (Switched Capacitor Circuits) approach for coulometric measurement conversion. The system features programmable control modes that generate multiple signal families, enabling built-in in-situ self-diagnostics. This functionality allows for the detection and analysis of parasitic influences from external factors on measurement results. The design incorporates comprehensive SPICE modeling methods to optimize signal path parameters and enhance measurement stability.

The research presents practical implementation results using the PSoC 5LP platform, demonstrating the system's capability to perform multi-stage integration and signal processing. The converter includes features such as programmable gain amplification, high-resolution analog-to-digital conversion (both SAR and Delta-Sigma types), and active shielding capabilities. Experimental results validate the effectiveness of the proposed approach in improving measurement accuracy and reliability in capacitive sensor applications. This work contributes to advancing sensor technology by providing a robust, programmable solution for precise capacitive measurements in challenging environments.