Online sensors and wavelet-based filter approach for tsunami case study

被引：0
|
作者：
Umadevi, Manickam [1 ,2 ]
Srinivasulu, Seshachalam [1 ]
机构：
[1] Anna Univ, Coll Engn, Dept Geol, Chennai 600025, Tamil Nadu, India
[2] Ganadipathy Tulsis Jain Engn Coll, Vellore 632102, Tamil Nadu, India
来源：
JOURNAL OF APPLIED REMOTE SENSING | 2013年 / 7卷
关键词：
tsunami; wavelet transform; conjugate quadrature filter; noise removal filter; downsampling; DESIGN;
D O I：
10.1117/1.JRS.7.073517
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
The Tsunami classification model with real-time sensors placed at different locations and at different depths is proposed. To exclude the artifact effects in the sensor values, a wavelet-based denoising scheme is integrated in the model. In addition, a downsampling approach has been proposed to achieve maximum flat delay response, and the present results are compared with the Pc McClellan method. Various parameters such as conductivity, salinity, pressure, temperature, and dissolved oxygen are measured and sensed using multisensor grid architecture. Our results show that by sensing the above parameters and subject them online, it is possible to clearly distinguish the pre- and post-tsunami behaviors. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)
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页数：14
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