针对煤矿井下现场电磁干扰多,采用煤岩受载产生的电磁辐射(EME)预测煤岩动力灾害效果有待提高,提出一种新的结合自适应集合经验模态分解(AEEMD)和改进小波变换(IWT)的电磁辐射信号去噪算法,克服了模态混叠,弥补了对小波基存在选择性的不足。分别采用IWT、EMD—IWT及AEEMD—IWT对构造的带噪信号进行去噪仿真及试验测试研究,结果表明:AEEMD—IWT算法去噪性能优越,对高信噪比和低信噪比的电磁辐射信号均能有效去噪。
Aiming at coal mine field electromagnetic interference,non-contact electromagnetic emission( EME)produced by loading coal-rock is used to predict coal-rock dynamic disasters,but the effect remains to be improved. A new EME signal denoising algorithm combined with adaptive ensemble empirical mode decomposition( AEEMD) and improved wavelet transform( IWT) is put forward. Overcome the modal aliasing and make up for selectivity deficiency of wavelet base,the IWT,EMD—IWT and AEEMD IWT are used for denoising simulation and test research on tectonic of signal with noise. Results show that denoising performance of AEEMD—IWT algorithm is superior,denoising on high signal-to-noise ratio and low SNR of EME signals are effective.