
基于经验模态分解及小波变换的炸药NQR信号处理
Processing of explosive nuclear quadrupole resonance signals based on empirical mode decomposition and wavelet transform
Explosive nuclear quadrupole resonance (NQR) signals have nonlinear and non-stationary characteristics. In order to solve the NQR signal de-noising problem, a de-noising method based on empirical mode decomposition (EMD) and wavelet transform was proposed. The original NQR signals of RDX detected by experiment were used to analyze the de-noising performance. The results indicate that the proposed method can eliminate the noise effectively and preserve the effective information of the original signals well. Meanwhile, the method can overcome the shortcomings of wavelet threshold de-noising and direct EMD de-noising, and improve the signal-to-noise ratio. The method has excellent adaptability, and proved to be an effective de-noising way for NQR signals.
炸药探测 / 核四极矩共振 / 经验模态分解 / 小波阈值 / 信号去噪 {{custom_keyword}} /
explosive detection / nuclear quadrupole resonance (NQR) / empirical mode decomposition (EMD) / wavelet threshold / signal de-noising {{custom_keyword}} /
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