Irregularity detection in artificial signal using time-frequency analysis
A typical time signal contain overwhelming amounts of data and some of the signal components represent for irregularity such as crack and leak which greatly important to be identified precisely instead of using traditional method. The strategy can be done using signal processing method through h...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
Asian Research Publishing Network (ARPN)
2016
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/20742/1/Irregularity%20detection%20in%20artificial%20signal%20using%20time-fkm-2016.pdf http://umpir.ump.edu.my/id/eprint/20742/ http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0316_3850.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1831525431771136000 |
|---|---|
| author | Hamat, A. Malik M. F., Ghazali Amin, Makeen Fatihah, Adnan |
| author_facet | Hamat, A. Malik M. F., Ghazali Amin, Makeen Fatihah, Adnan |
| author_sort | Hamat, A. Malik |
| building | UMPSA Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | A typical time signal contain overwhelming amounts of data and some of the signal components represent for irregularity such as crack and leak which greatly important to be identified precisely instead of using traditional method. The strategy can be done using signal processing method through high-quality time-frequency representation (TFR) for analysing such time dependent signals to accurately discover these superposition signal components. A few popular TFR methods such as wavelet transform analysis and relatively new, synchrosqueezed wavelet transform were applied in current study using artificial signal. From the result, both methods successfully discover an irregularity in the signal with different degree of accuracy and it is shown that synchrosqueezed wavelet transform provide the best and detailed time-frequency representation. |
| format | Article |
| id | my.ump.umpir.20742 |
| institution | Universiti Malaysia Pahang |
| language | en |
| publishDate | 2016 |
| publisher | Asian Research Publishing Network (ARPN) |
| record_format | eprints |
| spelling | my.ump.umpir.207422018-08-06T04:51:50Z http://umpir.ump.edu.my/id/eprint/20742/ Irregularity detection in artificial signal using time-frequency analysis Hamat, A. Malik M. F., Ghazali Amin, Makeen Fatihah, Adnan TJ Mechanical engineering and machinery A typical time signal contain overwhelming amounts of data and some of the signal components represent for irregularity such as crack and leak which greatly important to be identified precisely instead of using traditional method. The strategy can be done using signal processing method through high-quality time-frequency representation (TFR) for analysing such time dependent signals to accurately discover these superposition signal components. A few popular TFR methods such as wavelet transform analysis and relatively new, synchrosqueezed wavelet transform were applied in current study using artificial signal. From the result, both methods successfully discover an irregularity in the signal with different degree of accuracy and it is shown that synchrosqueezed wavelet transform provide the best and detailed time-frequency representation. Asian Research Publishing Network (ARPN) 2016 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/20742/1/Irregularity%20detection%20in%20artificial%20signal%20using%20time-fkm-2016.pdf Hamat, A. Malik and M. F., Ghazali and Amin, Makeen and Fatihah, Adnan (2016) Irregularity detection in artificial signal using time-frequency analysis. ARPN Journal of Engineering and Applied Sciences, 11 (6). pp. 3593-3597. ISSN 1819-6608. (Published) http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0316_3850.pdf |
| spellingShingle | TJ Mechanical engineering and machinery Hamat, A. Malik M. F., Ghazali Amin, Makeen Fatihah, Adnan Irregularity detection in artificial signal using time-frequency analysis |
| title | Irregularity detection in artificial signal using time-frequency analysis |
| title_full | Irregularity detection in artificial signal using time-frequency analysis |
| title_fullStr | Irregularity detection in artificial signal using time-frequency analysis |
| title_full_unstemmed | Irregularity detection in artificial signal using time-frequency analysis |
| title_short | Irregularity detection in artificial signal using time-frequency analysis |
| title_sort | irregularity detection in artificial signal using time-frequency analysis |
| topic | TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/20742/1/Irregularity%20detection%20in%20artificial%20signal%20using%20time-fkm-2016.pdf http://umpir.ump.edu.my/id/eprint/20742/ http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0316_3850.pdf |
| url_provider | http://umpir.ump.edu.my/ |