Software-controlled signal converter for capacitive sensors

A software-controlled signal converter for capacitive sensors with integrated in-situ self-diagnostic functionality has been developed to detect instabilities during the measurement process. The proposed approach is based on the analysis of multi-cycle charge integration parameters in Switched Capacitor Circuits (SCC), implemented on a programmable system-on-chip (PSoC) of the 5LP series. To ensure high measurement accuracy, several software-controlled operating modes have been introduced: accumulation of integration cycle results for statistical evaluation of instabilities; analysis of integrator discharge phases for relaxation process assessment; and examination of the entire signal path without charge accumulation. These modes enable the identification of thermal noise, time drift, and parasitic influences from external objects on the capacitive structure. Results from SPICE modeling and experimental oscilloscope studies confirm the effectiveness of the proposed solution, support the verification of signal path models, and allow for the optimization of measurement parameters. The developed software tools provide flexible configuration of measurement modes, data acquisition, and graphical visualization of signal dynamics, which facilitates comprehensive analysis of external factors affecting sensor stability.

Institutions

Publication Details

Journal
InterConf
Published
2025-06-20
DOI
https://doi.org/10.51582/interconf.19-20.06.2025.026
Primary Topic
Neurogenesis and neuroplasticity mechanisms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Software-controlled signal converter for capacitive sensors

InterConf
Neurogenesis and neuroplasticity mechanisms
article

Software-controlled signal converter for capacitive sensors

article en

Abstract

A software-controlled signal converter for capacitive sensors with integrated in-situ self-diagnostic functionality has been developed to detect instabilities during the measurement process. The proposed approach is based on the analysis of multi-cycle charge integration parameters in Switched Capacitor Circuits (SCC), implemented on a programmable system-on-chip (PSoC) of the 5LP series. To ensure high measurement accuracy, several software-controlled operating modes have been introduced: accumulation of integration cycle results for statistical evaluation of instabilities; analysis of integrator discharge phases for relaxation process assessment; and examination of the entire signal path without charge accumulation. These modes enable the identification of thermal noise, time drift, and parasitic influences from external objects on the capacitive structure. Results from SPICE modeling and experimental oscilloscope studies confirm the effectiveness of the proposed solution, support the verification of signal path models, and allow for the optimization of measurement parameters. The developed software tools provide flexible configuration of measurement modes, data acquisition, and graphical visualization of signal dynamics, which facilitates comprehensive analysis of external factors affecting sensor stability.

InterConf(58(252))
Lviv Polytechnic National University (UA)
Openalex Percentile: Top 40%
Neurogenesis and neuroplasticity mechanisms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Software-controlled signal converter for capacitive sensors · InterConf (2025) | TGRS Research Map | TGRS