Sparse generalized pencil of function and its application to system identification and structural health monitoring
ingularity expansion method (SEM) is a system identification approach with applications in solving inverse scattering problems, electromagnetic interaction problems, remote sensing, and radars. In this approach, the response of a system is represented in terms of its complex poles; therefore, this m...
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| Format: | Article |
| Language: | en_US |
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Society of Photo-Optical Instrumentation Engineers (SPIE)
2017
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| Online Access: | http://hdl.handle.net/1721.1/110239 https://orcid.org/0000-0002-7712-7478 https://orcid.org/0000-0001-7494-3050 |
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| author | Buyukozturk, Oral Mohammadi Ghazi Mahalleh, Reza |
| author2 | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Buyukozturk, Oral Mohammadi Ghazi Mahalleh, Reza |
| author_sort | Buyukozturk, Oral |
| collection | MIT |
| description | ingularity expansion method (SEM) is a system identification approach with applications in solving inverse scattering problems, electromagnetic interaction problems, remote sensing, and radars. In this approach, the response of a system is represented in terms of its complex poles; therefore, this method not only extracts the fundamental frequencies of the system from the signal, but also provides sufficient information about system's damping if its transient response is analyzed. There are various techniques in SEM among which the generalized pencil-of-function (GPOF) is the computationally most stable and the least sensitive one to noise. However, SEM methods, including GPOF, suffer from imposition of spurious poles on the expansion of signals due to the lack of apriori information about the number of true poles. In this study we address this problem by proposing sparse generalized pencil-of-function (SGPOF). The proposed method excludes the spurious poles through sparsity-based regularization with ℓ1-norm. This study is backed by numerical examples as well as an application example which employs the proposed technique for structural health monitoring (SHM) and compares the results with other signal processing methods. |
| first_indexed | 2024-09-23T14:27:15Z |
| format | Article |
| id | mit-1721.1/110239 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T14:27:15Z |
| publishDate | 2017 |
| publisher | Society of Photo-Optical Instrumentation Engineers (SPIE) |
| record_format | dspace |
| spelling | mit-1721.1/1102392022-09-29T09:32:47Z Sparse generalized pencil of function and its application to system identification and structural health monitoring Buyukozturk, Oral Mohammadi Ghazi Mahalleh, Reza Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Buyukozturk, Oral Mohammadi Ghazi Mahalleh, Reza ingularity expansion method (SEM) is a system identification approach with applications in solving inverse scattering problems, electromagnetic interaction problems, remote sensing, and radars. In this approach, the response of a system is represented in terms of its complex poles; therefore, this method not only extracts the fundamental frequencies of the system from the signal, but also provides sufficient information about system's damping if its transient response is analyzed. There are various techniques in SEM among which the generalized pencil-of-function (GPOF) is the computationally most stable and the least sensitive one to noise. However, SEM methods, including GPOF, suffer from imposition of spurious poles on the expansion of signals due to the lack of apriori information about the number of true poles. In this study we address this problem by proposing sparse generalized pencil-of-function (SGPOF). The proposed method excludes the spurious poles through sparsity-based regularization with ℓ1-norm. This study is backed by numerical examples as well as an application example which employs the proposed technique for structural health monitoring (SHM) and compares the results with other signal processing methods. 2017-06-23T20:45:50Z 2017-06-23T20:45:50Z 2016-04 2016-03 Article http://purl.org/eprint/type/ConferencePaper 9781510600461 http://hdl.handle.net/1721.1/110239 Mohammadi-Ghazi, Reza, and Oral Buyukozturk. “Sparse Generalized Pencil of Function and Its Application to System Identification and Structural Health Monitoring.” Proceedings of SPIE 9805, Health Monitoring of Structural and Biological Systems 2016, 20 March, Las Vegas, Nevada, SPIE, 2016. © 2016 SPIE https://orcid.org/0000-0002-7712-7478 https://orcid.org/0000-0001-7494-3050 en_US http://dx.doi.org/10.1117/12.2218893 Proceedings of SPIE 9805, Health Monitoring of Structural and Biological Systems 2016 Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Society of Photo-Optical Instrumentation Engineers (SPIE) SPIE |
| spellingShingle | Buyukozturk, Oral Mohammadi Ghazi Mahalleh, Reza Sparse generalized pencil of function and its application to system identification and structural health monitoring |
| title | Sparse generalized pencil of function and its application to system identification and structural health monitoring |
| title_full | Sparse generalized pencil of function and its application to system identification and structural health monitoring |
| title_fullStr | Sparse generalized pencil of function and its application to system identification and structural health monitoring |
| title_full_unstemmed | Sparse generalized pencil of function and its application to system identification and structural health monitoring |
| title_short | Sparse generalized pencil of function and its application to system identification and structural health monitoring |
| title_sort | sparse generalized pencil of function and its application to system identification and structural health monitoring |
| url | http://hdl.handle.net/1721.1/110239 https://orcid.org/0000-0002-7712-7478 https://orcid.org/0000-0001-7494-3050 |
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