Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction
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- 作者：Baijie Qiaoa ; b ; qiao@stu.xjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Xingwu Zhanga ; b ; Jiawei Gaoa ; b ; Ruonan Liua ; b ; Xuefeng Chena ; b ; chenxf@mail.xjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author
- 关键词：Sparse deconvolution ; Impact force reconstruction ; l1-norm regularization ; Primal-dual interior point method ; Preconditioned conjugate gradients
- 刊名：Mechanical Systems and Signal Processing
- 出版年：2017
- 出版时间：15 January 2017
- 年：2017
- 卷：83
- 期：Complete
- 页码：93-115
- 全文大小：1744 K
文摘
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Sparse deconvolution is introduced to the field of impact force reconstruction.
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PDIPM based on l1-norm is proposed to solve large-scale deconvolution problem.
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The performance of l1-norm regularization method is verified by two experiments.
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Both single and consecutive impact forces are accurately reconstructed by PDIPM.
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Compared with l2-norm regularization, PDIPM is highly accurate and efficient.
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