Modulated Broadband Mode Decomposition for the Feature Extraction of Double Pulse Metal Inert Gas Welding

A lot of adaptive signal decomposition methods have been applied for nonstationary DPMIG electrical signals as they are always affected by noise. Recently, to solve the problems of former methods caused by the Gibbs phenomenon and the calculation of extremas when dealing with broadband electrical si...

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Autores principales: Yanfeng Peng, Zucheng Wang, Kuanfang He, Qingxian Li, Liangjiang Liu, Xianyu Zhu, Qinghua Lu, Yanfei Liu, Zhihua Peng
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Publicado: IEEE 2020
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spelling oai:doaj.org-article:efee175b57cc460fbe65551ca551e92c2021-11-20T00:00:39ZModulated Broadband Mode Decomposition for the Feature Extraction of Double Pulse Metal Inert Gas Welding2169-353610.1109/ACCESS.2020.3010806https://doaj.org/article/efee175b57cc460fbe65551ca551e92c2020-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9145553/https://doaj.org/toc/2169-3536A lot of adaptive signal decomposition methods have been applied for nonstationary DPMIG electrical signals as they are always affected by noise. Recently, to solve the problems of former methods caused by the Gibbs phenomenon and the calculation of extremas when dealing with broadband electrical signals such as square signals and sawtooth signals with “sharp corners”, broadband mode decomposition (BMD) method was proposed and the application of the algorithm showed a good performance. The main idea of BMD is searching in the associative dictionary contains both broadband and narrowband signals using a regulated differential operator as the optimal object. However, when applied to a broadband signal interfered by strong noise, as the relative bandwidth is not small enough, the BMD algorithm may treat the broadband signal to be several narrowband components. Therefore, modulated broadband mode decomposition (MBMD) is proposed in this paper to denoise broadband electrical signals based on modulated differential operator. By multiplying a high frequency mono-frequency signal, the relative bandwidth of the effective broadband signal is translated to be far less than 1, and the broadband signals are treated as approximate broadband signals to get more accurate decomposition results. For the further feature extraction of the electrical signals, locality preserving projection (LPP) is applied combined with MBMD. The effectiveness of the proposed method is testified by simulation and experimental signals, results show that it is effective when drawing broadband feature from noise, as well as is adaptive for the feature extraction of double pulse metal inert gas welding.Yanfeng PengZucheng WangKuanfang HeQingxian LiLiangjiang LiuXianyu ZhuQinghua LuYanfei LiuZhihua PengIEEEarticleModulated broadband mode decompositionmodulated differential operatorMIG weldinglocality preserving projectionfeature extractionElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 8, Pp 134031-134041 (2020)
institution DOAJ
collection DOAJ
language EN
topic Modulated broadband mode decomposition
modulated differential operator
MIG welding
locality preserving projection
feature extraction
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
spellingShingle Modulated broadband mode decomposition
modulated differential operator
MIG welding
locality preserving projection
feature extraction
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Yanfeng Peng
Zucheng Wang
Kuanfang He
Qingxian Li
Liangjiang Liu
Xianyu Zhu
Qinghua Lu
Yanfei Liu
Zhihua Peng
Modulated Broadband Mode Decomposition for the Feature Extraction of Double Pulse Metal Inert Gas Welding
description A lot of adaptive signal decomposition methods have been applied for nonstationary DPMIG electrical signals as they are always affected by noise. Recently, to solve the problems of former methods caused by the Gibbs phenomenon and the calculation of extremas when dealing with broadband electrical signals such as square signals and sawtooth signals with “sharp corners”, broadband mode decomposition (BMD) method was proposed and the application of the algorithm showed a good performance. The main idea of BMD is searching in the associative dictionary contains both broadband and narrowband signals using a regulated differential operator as the optimal object. However, when applied to a broadband signal interfered by strong noise, as the relative bandwidth is not small enough, the BMD algorithm may treat the broadband signal to be several narrowband components. Therefore, modulated broadband mode decomposition (MBMD) is proposed in this paper to denoise broadband electrical signals based on modulated differential operator. By multiplying a high frequency mono-frequency signal, the relative bandwidth of the effective broadband signal is translated to be far less than 1, and the broadband signals are treated as approximate broadband signals to get more accurate decomposition results. For the further feature extraction of the electrical signals, locality preserving projection (LPP) is applied combined with MBMD. The effectiveness of the proposed method is testified by simulation and experimental signals, results show that it is effective when drawing broadband feature from noise, as well as is adaptive for the feature extraction of double pulse metal inert gas welding.
format article
author Yanfeng Peng
Zucheng Wang
Kuanfang He
Qingxian Li
Liangjiang Liu
Xianyu Zhu
Qinghua Lu
Yanfei Liu
Zhihua Peng
author_facet Yanfeng Peng
Zucheng Wang
Kuanfang He
Qingxian Li
Liangjiang Liu
Xianyu Zhu
Qinghua Lu
Yanfei Liu
Zhihua Peng
author_sort Yanfeng Peng
title Modulated Broadband Mode Decomposition for the Feature Extraction of Double Pulse Metal Inert Gas Welding
title_short Modulated Broadband Mode Decomposition for the Feature Extraction of Double Pulse Metal Inert Gas Welding
title_full Modulated Broadband Mode Decomposition for the Feature Extraction of Double Pulse Metal Inert Gas Welding
title_fullStr Modulated Broadband Mode Decomposition for the Feature Extraction of Double Pulse Metal Inert Gas Welding
title_full_unstemmed Modulated Broadband Mode Decomposition for the Feature Extraction of Double Pulse Metal Inert Gas Welding
title_sort modulated broadband mode decomposition for the feature extraction of double pulse metal inert gas welding
publisher IEEE
publishDate 2020
url https://doaj.org/article/efee175b57cc460fbe65551ca551e92c
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