Improving Event Classification Using Gammatone Filter For Distributed Acoustic Sensing
The phase optical time domain reflectometry (?-OTDR) system offers several advantages suitable for distributed acoustic sensing application. It has long sensing range, great anti-electromagnetic interference, and high sensitivity towards environmental vibrations. However, as a sensor system, the ?-O...
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Universiti Malaysia Perlis
2023
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| _version_ | 1833411632926031872 |
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| author | Faisal B. Yusri M.S. Ismail A. Saleh N.L. Ismail M.F. Nordin N.D. Sulaiman A.H. Abdullah F. Jamaludin M.Z. |
| author2 | 57209973264 |
| author_facet | 57209973264 Faisal B. Yusri M.S. Ismail A. Saleh N.L. Ismail M.F. Nordin N.D. Sulaiman A.H. Abdullah F. Jamaludin M.Z. |
| author_sort | Faisal B. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | The phase optical time domain reflectometry (?-OTDR) system offers several advantages suitable for distributed acoustic sensing application. It has long sensing range, great anti-electromagnetic interference, and high sensitivity towards environmental vibrations. However, as a sensor system, the ?-OTDR is limited to only collecting environmental vibrations without providing more useful information such as the location and types of events happening around the sensing region. Therefore, it requires an extensive data processing system to distinguish between different events happening within the sensing regions. In this paper, Simple Differential and Normalized Differential method were used to extract perturbation event prior to classification process comprising data organization, features extraction, and classification outcome were implemented. Gammatone Frequency Cepstral Cepstrum were used to handcraft features for classification and were obtained using Gammatone Filter processing. Classification scheme based on Support Vector Machine (SVM) is use as classifier where accuracy score 100%. � 2021, Universiti Malaysia Perlis. All rights reserved. |
| format | Note |
| id | my.uniten.dspace-25852 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Universiti Malaysia Perlis |
| record_format | dspace |
| spelling | my.uniten.dspace-258522023-05-29T17:05:17Z Improving Event Classification Using Gammatone Filter For Distributed Acoustic Sensing Faisal B. Yusri M.S. Ismail A. Saleh N.L. Ismail M.F. Nordin N.D. Sulaiman A.H. Abdullah F. Jamaludin M.Z. 57209973264 57480859600 36023817800 57198797134 57211721986 57217851042 36810678100 56613644500 57216839721 The phase optical time domain reflectometry (?-OTDR) system offers several advantages suitable for distributed acoustic sensing application. It has long sensing range, great anti-electromagnetic interference, and high sensitivity towards environmental vibrations. However, as a sensor system, the ?-OTDR is limited to only collecting environmental vibrations without providing more useful information such as the location and types of events happening around the sensing region. Therefore, it requires an extensive data processing system to distinguish between different events happening within the sensing regions. In this paper, Simple Differential and Normalized Differential method were used to extract perturbation event prior to classification process comprising data organization, features extraction, and classification outcome were implemented. Gammatone Frequency Cepstral Cepstrum were used to handcraft features for classification and were obtained using Gammatone Filter processing. Classification scheme based on Support Vector Machine (SVM) is use as classifier where accuracy score 100%. � 2021, Universiti Malaysia Perlis. All rights reserved. Final 2023-05-29T09:05:17Z 2023-05-29T09:05:17Z 2021 Note 2-s2.0-85126120319 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126120319&partnerID=40&md5=147a0815b2c4c465d85b105afa665bde https://irepository.uniten.edu.my/handle/123456789/25852 14 Special Issue InCAPE 325 332 Universiti Malaysia Perlis Scopus |
| spellingShingle | Faisal B. Yusri M.S. Ismail A. Saleh N.L. Ismail M.F. Nordin N.D. Sulaiman A.H. Abdullah F. Jamaludin M.Z. Improving Event Classification Using Gammatone Filter For Distributed Acoustic Sensing |
| title | Improving Event Classification Using Gammatone Filter For Distributed Acoustic Sensing |
| title_full | Improving Event Classification Using Gammatone Filter For Distributed Acoustic Sensing |
| title_fullStr | Improving Event Classification Using Gammatone Filter For Distributed Acoustic Sensing |
| title_full_unstemmed | Improving Event Classification Using Gammatone Filter For Distributed Acoustic Sensing |
| title_short | Improving Event Classification Using Gammatone Filter For Distributed Acoustic Sensing |
| title_sort | improving event classification using gammatone filter for distributed acoustic sensing |
| url_provider | http://dspace.uniten.edu.my/ |