Laboratory Study of ADCP Wave Measurements

Author(s):  
H. H. Shih ◽  
B. Strong

The National Ocean Service (NOS) collects real-time environmental data to support mission activities including navigation safety, coastal hazard mitigation, and coastal resource management. Near shore wave information is important for these activities and is of growing interest to marine user groups. Acoustic Doppler current profiler (ADCP) are a primary tool for NOS current measurement programs. Recent technology development has added wave measurement capability to these instruments and provided a convenient way for wave monitoring. However, only limited field comparative studies have been conducted. The need to further understand the performance of these instruments and their operation requirements exists. Tests under controlled laboratory conditions offer certain advantages over field intercomparisons including reduced measurement uncertainties, isolation of variables, and is generally cost effective. This paper describes the study of wave measurement performance of a RDI 1200 KHz ADCP in a wave basin with prescribed waves consist of regular, irregular, and multi-directional waves. The steepness and peak energy frequency for each type of waves, and the orientation of ADCP acoustic beams relative to incident waves were varied. A Linear Array of five ultrasonic sensors and a SonTek 5 MHZ ADVOcean instrument were used to provide reference for intercomparison. The ADCP shows good measurement resolutions and agrees well with the reference measurements.

2021 ◽  
Author(s):  
Morten Loell Vinther ◽  
Torbjørn Eide ◽  
Aurelia Paraschiv ◽  
Dickon Bonvik-Stone

Abstract High quality environmental data are critical for any offshore activity relying on data insights to form appropriate planning and risk mitigation routines under challenging weather conditions. Such data are the most significant driver of future footprint reduction in offshore industries, in terms of costs savings, as well as operational safety and efficiency, enabled through ease of data access for all relevant stakeholders. This paper describes recent advancements in methods used by a dual-footprint Pulse-Doppler radar to provide accurate and reliable ocean wave height measurements. Achieved improvements during low wind weather conditions are presented and compared to data collected from other sources such as buoys and acoustic doppler wave and current profiler (ADCP) or legacy. The study is based on comparisons of recently developed algorithms applied to different data sets recorded at various sites, mostly covering calm weather conditions.


2021 ◽  
Vol 944 (1) ◽  
pp. 012014
Author(s):  
A Dwinovantyo ◽  
S Solikin ◽  
H M Manik ◽  
T Prartono ◽  
Susilohadi

Abstract Characterization of each underwater object has its challenges, especially for small objects. The process of quantifying acoustic signals for these small objects can be done using high-frequency hydroacoustic instruments such as an acoustic Doppler current profiler (ADCP) combined with the artificial intelligence (AI) technique. This paper presents an artificial neural network (ANN) methodology for classifying an object from acoustic and environmental data in the water column. In particular, the methodology was tuned for the recognition of suspended sediments and zooplankton. Suspended sediment concentration and zooplankton abundance, which extracted from ADCP acoustic data, were used as input in the backpropagation method along with other environmental data such as effects of tides, currents, and vertical velocity. The classifier used an optimal number of neurons in the hidden layer and a feature selection based on a genetic algorithm. The ANN method was also used to estimate the suspended sediment concentration in the future. This study provided new implications for predicting and classifying suspended sediment and zooplankton using the ADCP instrument. The proposed methodology allowed us to identify the objects with an accuracy of more than 95%.


2008 ◽  
Author(s):  
Annett B. Sullivan ◽  
Michael L. Deas ◽  
Jessica Asbill ◽  
Julie D. Kirshtein ◽  
Kenna D. Butler ◽  
...  

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