Neuromorphic alternating current sensing using piezoelectric resonators and physical reservoir computing

Non-contact current sensors are valuable because they can safely measure alternating current without interrupting the circuit. However, current sensors utilizing Hall elements or coils are only available for single wires, and piezoelectric resonator-based sensors have difficulty achieving both high sensitivity and linearity. To address this issue, we propose a novel approach, that is, the use of piezoelectric current sensors as nodes for physical reservoir computing (physical RC), allowing us to utilize nonlinear regions. To improve the sensitivity and short-term memory required by physical RC, a piezoelectric resonator with a quality factor of 75 was realized by employing a tuning fork structure. Nonlinearities were also introduced by analog circuits. The results of the benchmark tests indicate that the device worked as a physical RC and that it successfully predicted unknown current values from the results of training at three levels of current.