Sustainable model for high signal to noise ratio to measure underwater acoustic signal using Acoustic Doppler Velocimeter. (May 2018)

• Record Type: Journal Article
• Authors: Arumbu, P.; Srinivasalu, S.
• Is Part Of: Computers & electrical engineering. Volume 68(2018)
• Page Start: 262
• Page End: 270
• Publication Date: 2018-05
• Subjects: Sustainable model -- Response surface methodology (RSM) -- Signal to Noise Ratio (SNR) Measurement -- Acoustic Doppler Velocimeter (ADV) -- Central Composite Design (CCD) -- Underwater acoustic signal; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.03.034
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: The objective of this research is to identify the optimum region in the underwater of flume, an artificial channel setup, to measure the acoustic signal. Acquiring the signal with high Signal to Noise Ratio is essential. Utilizing the Response Surface Methodology (RSM) with three factors Central Composite Design (CCD), this paper demonstrates the sustainable model of characterizing the Signal to Noise Ratio (SNR) through second order quadratic model in measuring the acoustic signal through Acoustic Doppler Velocimeter (ADV). Over all model fitness test of the suggested Design is justified by Degrees of freedom (DF). Highly Influenceable parameters of Signal to Noise Ratio are recognized using Analysis of Variance (ANOVA). The design for optimum region to investigate and acquire the signal for processing is acknowledged through F -Statistics. The multicolinearity of parameters is studied by Variance Inflation Factor, brought uncontrolled parameter such as Signal to Noise Ratio and Velocity of the measured signal to under control.