【摘要】：提出了基于集合經(jīng)驗模態(tài)分解(EEMD)和奇異值(SVD)相結合的微弱信號提取方法和高低頻部分的判別準則:采用EEMD把信號分解成幾部分,將IMF分為高頻段與低頻段2部分,對2部分分別進行奇異值處理,疊加得到降噪信號,做出其頻譜圖,得到所需要的有用信號。此方法可以在未知原信號的情況下提取,并且可以提取信噪比為-15 dB的信號。仿真結果和對比分析表明,此方法能更好地提取微弱特征信號。
[Abstract]:A weak signal extraction method based on ensemble empirical mode decomposition (EEMD) and singular value (SVD) and a criterion for distinguishing high and low frequency components are presented. The signal is decomposed into several parts by using EEMD, and the IMF is divided into high frequency band and low frequency section 2, and the two parts are respectively subjected to singular value processing. The noise reduction signal is superposed to obtain the noise reduction signal, and the spectrum diagram thereof is made to obtain the required useful signal. The method can be extracted in the case of an unknown original signal, and a signal with a signal-to-noise ratio of -15dB can be extracted. The simulation results and the comparative analysis show that the method can better extract the weak characteristic signal.
【作者單位】： 西安建筑科技大學機電工程學院;
【基金】：國家自然科學基金青年科學基金項目(51105292) 教育部博士點基金項目(20126120110009) 陜西省科技攻關項目(2013K07-09) 陜西省教育廳專項基金項目(2013JK1032)
【分類號】：TH17

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