Self-powered autonomous wireless sensor system with multivariable sensing capability

Here we demonstrate a triboelectric nanogenerator (TENG) based fully self-powered multi-parameter wireless sensing system. By integrating the TENG with multiple mutually coupled RLC resonators, the energy harvested by the TENG is directly converted into a decaying oscillating signal containing multiple frequency components with encoded sensing information. The oscillating signals can be transmitted and received by the near-field antennas using inductive coupling and the wireless sensing distance is up to 2 m. A theoretical analysis method based on characteristic parameters is proposed firstly, which is used to obtain the functional expressions between the attenuation coefficients alpha, eigen frequencies omega and characteristic parameters. Fast Fourier transform (FFT) spectral analysis is used to extract multi-parameters, shows that the theoretical analysis agrees very well with the experimental results. A self-powered wireless strain distribution sensing system based on LabVIEW was developed to demonstrate the feasibility of the proposed multi-parameter sensing technology, the results show that the system can monitor strains and its distribution along a cantilever-like structure precisely, demonstrating its great application potential.