Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/40359
Title: Infrasound signal processing
Authors: Yap, Kai En.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2010
Abstract: Infrasound is a low frequency acoustic phenomenon typically in the frequency range of 0.01 to 20 Hz. It has been used to monitor various man-made and natural events due to its inherent ability to propagate long distances. The detection and study of infrasound would greatly benefit society in a wide range of non-trivial applications. The purpose of this infrasound signal processing project is to establish a data acquisition system to capture and classify infrasound data. A detailed description of the equipment setup clarifies the methodology on how infrasound data is recorded. In addition, issues with the data collection process were identified and relevant measures were taken to overcome the problems. The infrasound data is preprocessed using techniques similar to speech processing, such as Mel-scale Frequency Cepstrum Coefficients (MFCC), to obtain a set of feature vectors which will be used to train and test the neural network. The benefit of this technique is that it is not affected by the record length, sampling frequency or the signal amplitude. A parallel neural network classifier bank is developed to classify infrasound events from six different classes of signals, where each module in the classification bank is a backpropagation neural network responsible for classifying one of the six events. For the six different infrasound events, the correct classification rate achieved is 92%.
URI: http://hdl.handle.net/10356/40359
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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