MULTIFUNCTIONAL SIGNAL CONVERTER FOR CAPACITIVE SENSORS - BARYLO, HRYHORII; HOLIAKA, ROMAN; ADAMIAK, OLEH; SAVYTSKYI, ANDRII; SHKRIBYNETS, VITALII (Herald of Khmelnytskyi National University. Technical sciences, 2024)
This paper presents the results of research on signal converters for capacitive sensors, focusing on the analysis of additional parameters that directly influence measurement outcomes. The study addresses the problem of limited functionality in traditional signal converters, which often leads to reduced accuracy and reliability in measurements. To overcome this limitation, a new multifunctional operating mode is proposed, enabling the formation of additional signal families. These signal families not only allow for measurements but also perform self-diagnostics and detect parasitic interactions, significantly improving the reliability of the measurement results. A thorough review of existing research on capacitive sensors and their signal converters is provided, highlighting key advancements in impedance measurement systems and the impact of various materials on sensor performance. The development of specialized signal conversion circuits, aiming to expand the functionality and enhance the accuracy of capacitive sensor measurements, is emphasized. The core of the proposed solution lies in the use of switched capacitor circuits (SCC), which implement a coulometric measurement method. The basic circuit structure includes a measured capacitor, an integrating capacitor, a set of analog switches, and a reference voltage source. The signal conversion process involves the periodic charging and discharging of the measured capacitor, followed by the transfer of charge to the integrating capacitor. The system operates in multiple phases, controlled by corresponding switch signals, enabling accurate measurement of the output voltage. The multifunctional nature of the signal converter is realized through specific control algorithms, which modulate the switching process to introduce additional measurement modes. These modes include various signal processing techniques that detect destabilizing factors, such as parasitic capacitances and external object influences, which can affect the sensor’s accuracy. By employing extended SPICE models of the sensor’s capacitive structure, the system accounts for the complex reactive components and parasitic effects within both the sensor and its signal pathways. The research demonstrates the practical implementation of the multifunctional signal converter using a Programmable System-on-Chip (PSoC) architecture. The experimental studies validate the proposed approach, showing high linearity in the output signal under ideal conditions and effective compensation for destabilizing influences in non-ideal environments. The developed signal converter also supports several diagnostic modes, allowing for the detection of noise and DC offset in the measurement circuit, which further enhances the measurement accuracy.