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

为解决炸药NQR信号去噪问题,针对NQR信号非线性与非平稳性特点,提出基于经验模态分解及小波变换联合的信号去噪方法。据实验测试的黑索金NQR信号对所提方法进行去噪性能分析。结果表明该方法在保留信号有用信息的前提下可有效去除噪声,从而提高信噪比、克服小波阈值去噪与直接EMD去噪缺陷,自适应性良好,为有效的炸药NQR信号去噪方法。

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 well preserve the effective information of original signals. 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 was proved to be an effective de-noising way for NQR signals.