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Research on Weak Signal Feature Extraction Method Based on Double Coupled Duffing Oscillator Stochastic Resonance

机译:基于双耦合Duffing振子随机共振的弱信号特征提取方法研究

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A weak signal feature extraction method is proposed based on double coupled Duffing oscillator stochastic resonance (SR). In this method, the doubly coupled stochastic resonance system consists of two Duffing oscillators. Stochastic resonance is generated in the coupled stochastic resonance system by the synergy of input weak signal and noise, so that signal to noise ratio (SNR) of output signal is enhanced. The influences of different parameters on SR are researched by SNR. The scale transformation method is used to realize the detection of large frequency signals. At first, the large frequency is compressed into a small frequency to satisfy the stochastic resonance through the twice sampling frequency. Finally, the feature extraction of weak fault signal is realized through the scale recovery. The analysis results of simulation signal and example signal of rolling element bearing show that this method can effectively extract the fault feature information of weak signal. The experimental results show that this method is more effective for weak signal detection than the Duffing oscillator detection.
机译:提出了一种基于双耦合Duffing振子随机共振(SR)的弱信号特征提取方法。在这种方法中,双耦合随机共振系统由两个Duffing振荡器组成。输入弱信号与噪声的协同作用在耦合随机共振系统中产生随机共振,从而提高了输出信号的信噪比(SNR)。通过SNR研究了不同参数对SR的影响。标度变换方法用于实现大频率信号的检测。首先,将大频率压缩为小频率,以通过两次采样频率来满足随机共振。最后,通过尺度恢复实现了微弱故障信号的特征提取。仿真信号和滚动轴承实例信号的分析结果表明,该方法可以有效地提取弱信号的故障特征信息。实验结果表明,该方法对弱信号的检测比Duffing振荡器的检测更为有效。

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