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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Asian Research Publishing Network (ARPN)
2016
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| 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 |
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| Summary: | 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. |
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