A Non-linear Tent Map-Based ADC Design for Sensitive Condition Monitoring Measurement Systems

Condition monitoring systems generally require data acquisition (DAQ) systems. These in turn necessitate high-precision analogue-to-digital converters (ADCs) to sample and convert analogue signals from sensors into digital data, for establishing the condition of the monitored equipment. There is generally a need for high-accuracy measurement of minimally changing parameters in condition monitoring applications, indicating small changes in performance of system components. This requires DAQ systems containing high-resolution and precision ADCs, which increases the overall cost of the measurement system. This research employs chaos-based, non-linear Tent Map (TM) circuitry to perform analogue-to-digital conversion. As previous research has demonstrated TM-based ADCs, developed using low-cost components, can detect small changes in an input voltage signal over a relatively large voltage range and be incorporated with FPGAs for signal conditioning. This work investigates the potential of a TM ADC for detecting voltage differences of 100 µV over a range of 0–1.8 V. The analysis involved simulating the ADC and assessing behavior when noise was induced in the system and gains of its TM circuits altered. Results showed the ADC could detect 100 µV changes in a low frequency voltage signal, providing the TM circuits had an ideal gain of 2 and no noise was present in the system. Reducing the gain of the TM circuits and noise affected the accuracy and precision of the ADC. For this reason, this work will aim to develop an algorithm for self-calibration, to run in real-time on an FPGA, enabling a precision ADC to be realized.