Abstract
Analog hardware used for signal envelope extraction in low-power interfaces for acoustic event detection, owing to its low complexity and power consumption, suffers from low sensitivity and performs poorly under low signal to noise ratios (SNR) found in undersea environments. To overcome those problems, in this paper, we propose a novel passive electromechanical solution for the signal feature extraction in low frequency acoustic range (200–1000 Hz), in the form of a piezoelectric vibration transducer, and a rectifier with a mechanically switched inductor. A simulation study of the novel solution is presented, and a proof-of-concept device is developed and experimentally characterized. We demonstrate its applicability and show the advantages of the passive electromechanical device in comparison to the active electrical solution in terms of operation with lower input signals (<20 mV compared to 40 mV), and higher robustness in low SNR conditions (output voltage loss for −10 dB ≤ SNR < 40 dB of 1 mV, compared to 10 mV). In addition to the signal processing performance improvements, compared to our previous work, the utilization of the presented novel passive feature extractor would also decrease power consumption of a detector’s channel by over 76%, enabling life-time extension and/or increased quality of detection with larger number of channels. To the best of our knowledge, this is the first solution presented in the literature that demonstrates the possibility of using a passive electromechanical feature extractor in a low-power analog wake-up event detector interface.
Highlights
The recognition of infrequent events is of interest in many fields
In order to evaluate the use of the passive electromechanical feature extractor (PEM FE) in a set frequency band, an analytical model has been implemented and simulated in MathWorks’ MATLAB®
Peak.The results show that the PEM FE is far more resistant to noise than active electrical feature extractor (AE FE), as for the input results alsofrom show that with the PEM
Summary
The recognition of infrequent events is of interest in many fields (environmental monitoring [1,2,3,4,5], safety and security [6,7,8,9,10,11,12,13], communication [14,15,16], agriculture, health monitoring [17]) It requires continuous operation of an electronic system comprising sensing, detection and recognition functions, which are power-hungry tasks [7,18]. Many acoustic events can be recognized based on their time-frequency pattern [5], which can be approximated by an ordered sequence of discrete time-frequency states (Figure 1a) The extraction of these patterns in wake-up systems is usually performed by processing in the time domain utilizing a low-power multichannel analog detector [21]. The event detector consists of multiple channels to allow for simultaneous analog frequency decomposition, with each channel requiring a feature extractor to Sensors 2020, 20, 5445; doi:10.3390/s20185445 www.mdpi.com/journal/sensors
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.