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A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors

机译:一种改进的自适应随机共振检测传感器中的微弱信号

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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.
机译:在本文中,提出了一种通过随机共振(SR)检测传感器中具有强噪声的微弱信号的方法。我们采用功率谱作为SR的评估工具,可以通过快速傅里叶变换(FFT)获得。此外,我们介绍了自适应滤波方案以自动实现信号处理。该方案的关键是在有任何输入的情况下如何调整势垒高度以满足SR的最佳条件。对于给定的输入信号,我们提出了执行调整方案的可操作程序。给出了使用一个音频传感器从电源检测故障信息的示例。仿真结果表明,改进的随机共振方案可以有效地检测出具有较强噪声的故障信号。

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