Don C. Opada, Elmer S. Maravillas, Chris Jordan G. Aliac, Vol. 2, No. 1, pp. 17-22, Mar. 2020
10.22662/IJASC.2020.2.1.017, Full Text:
Keywords: Digital Signal Processing; Frequency Clustering; Noise Classification; Sound Analytics; Sound to Energy

Abstract

Background/Objectives: A resonator plays a significant part in harnessing sound waves. An idea to use a resonator that only resonates on a specific frequency is hypothesized to harness sound efficiently. The primary objective of this study is to investigate the noise present in the boat engine room and be able to classify its resonant frequency and to know which of these frequencies occur most often. Methods/Statistical analysis: By using a sound recorder and a sound pressure level meter, the sound recorded from the idle state of the boat to disembarking and upon reaching the destination. Findings: Fast Fourier transform is applied to extract the frequencies of the recorded sound. Then the frequencies are evaluated using the Davies-Bouldin index to estimate the number of clusters and K-means clustering to classify the frequencies. Improvements/Applications: There are 2 clusters found and that Cluster 1 frequencies are from 17 Hz to 3295 Hz. Cluster 2 frequencies are from 6291 Hz to 8279 Hz. Among the available frequencies, 47 Hz, 155 Hz, and 186 Hz out weight all of the frequencies in terms of their occurrence, and among the three frequencies, 186 Hz has the highest amplitude.

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