本文選題：經驗小波變換　切入點：固有模態(tài)　出處：《焊接學報》2017年06期 　論文類型：期刊論文

【摘要】：針對磁控埋弧焊跟蹤信號非線性,不平穩(wěn)及常用濾波方法難以濾除其相近低頻干擾信號的缺點,提出一種基于經驗小波變換(EWT)的磁控埋弧焊焊縫跟蹤信號分析方法.該方法繼承了EMD分解與小波變換各自的優(yōu)點,分解出電弧跟蹤信號的固有模態(tài),在頻域自適應地構造帶通濾波器組從而構造正交小波函數(shù),提取具有緊支撐傅立葉頻譜的調幅-調頻(AM-FM)成分.將此方法用于埋弧焊磁控電弧傳感器焊縫跟蹤平臺信號分析中,提取出了更精確的焊縫跟蹤信號,并通過試驗驗證了此方法的有效性及精確性.同時分析了相近低頻噪聲的信息,為進一步的信號處理及跟蹤系統(tǒng)的優(yōu)化提供了理論依據(jù).
[Abstract]:Aiming at the nonlinearity, nonstationarity of tracking signals of magnetically controlled submerged arc welding (MAW), and the disadvantages of common filtering methods, it is difficult to filter the similar low-frequency interference signals. A method for analyzing the tracking signals of magnetically controlled submerged arc welding seam based on empirical wavelet transform (EWT) is proposed. This method inherits the advantages of EMD decomposition and wavelet transform, and decomposes the inherent modes of arc tracking signals. The band pass filter bank is constructed adaptively in frequency domain to construct orthogonal wavelet function, and the amplitude modulation-frequency modulation (AM FM) component with compact support Fourier spectrum is extracted. The method is applied to the signal analysis of weld seam tracking platform of submerged arc welding (SAW) magnetron arc sensor. More accurate seam tracking signals are extracted, and the validity and accuracy of this method are verified by experiments. The information of similar low frequency noise is analyzed, which provides a theoretical basis for further signal processing and optimization of tracking system.
【作者單位】： 湘潭大學機械工程學院;
【基金】：國家自然科學基金資助項目(50975243)
【分類號】：TG409

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本文編號：1610118