Improving event classification using Gammatone Filter for distributed acoustic sensing
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Date
2021-12Author
B., Faisal
M. S., Yusri
A., Ismail
N. L., Saleh
M. F., Ismail
N. D., Nordin
A. H., Sulaiman
F., Abdullah
M. Z., Jamaludin
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Show full item recordAbstract
The phase optical time domain reflectometry (Φ-OTDR) system offers several advantages
suitable for distributed acoustic sensing application. It has long sensing range, great antielectromagnetic
interference, and high sensitivity towards environmental vibrations.
However, as a sensor system, the Φ-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%.