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A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors

View Article: PubMed Central

ABSTRACT

In this paper, an approach is presented to detect faint signals with strong noises in sensors by stochastic resonance (SR). We adopt the power spectrum as the evaluation tool of SR, which can be obtained by the fast Fourier transform (FFT). Furthermore, we introduce the adaptive filtering scheme to realize signal processing automatically. The key of the scheme is how to adjust the barrier height to satisfy the optimal condition of SR in the presence of any input. For the given input signal, we present an operable procedure to execute the adjustment scheme. An example utilizing one audio sensor to detect the fault information from the power supply is given. Simulation results show that the modified stochastic resonance scheme can effectively detect fault signal with strong noise.

No MeSH data available.


Audio signal of intermediate frequency power supply.
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f4-sensors-07-00157: Audio signal of intermediate frequency power supply.

Mentions: Figure 4 shows the audio signal from a power supply with fault, which is collected and transformed into electrical signal by the audio sensor. Here we use a electret test microphone as the audio sensor. For this microphone, frequency response ranges from 10Hz to 5000Hz and standard sensitivity is 25mV/Pa. It can be used as noise monitor for measure of ambient noise machine noise, vehicle noise, electrical machinery noise, architecture acoustics and electroacoustics.


A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors
Audio signal of intermediate frequency power supply.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3756698&req=5

f4-sensors-07-00157: Audio signal of intermediate frequency power supply.
Mentions: Figure 4 shows the audio signal from a power supply with fault, which is collected and transformed into electrical signal by the audio sensor. Here we use a electret test microphone as the audio sensor. For this microphone, frequency response ranges from 10Hz to 5000Hz and standard sensitivity is 25mV/Pa. It can be used as noise monitor for measure of ambient noise machine noise, vehicle noise, electrical machinery noise, architecture acoustics and electroacoustics.

View Article: PubMed Central

ABSTRACT

In this paper, an approach is presented to detect faint signals with strong noises in sensors by stochastic resonance (SR). We adopt the power spectrum as the evaluation tool of SR, which can be obtained by the fast Fourier transform (FFT). Furthermore, we introduce the adaptive filtering scheme to realize signal processing automatically. The key of the scheme is how to adjust the barrier height to satisfy the optimal condition of SR in the presence of any input. For the given input signal, we present an operable procedure to execute the adjustment scheme. An example utilizing one audio sensor to detect the fault information from the power supply is given. Simulation results show that the modified stochastic resonance scheme can effectively detect fault signal with strong noise.

No MeSH data available.