Computer Vision for Wave Flume Experiments

Abstract

During the past several decades, a number of attempts have been made to contain oil slicks (or any surface contaminants) in the open sea by means of a floating barrier. Many of those attempts were not very successful especially in the presence of waves and currents. The relative capabilities of these booms have not been properly quantified for lack of standard analysis or testing procedure (Hudon, 1992). In this regard, more analysis and experimental programs to identify important boom effectiveness parameters are needed. To achieve the desirable performance of floating booms in the open sea, it is necessary to investigate the static and dynamic responses of individual boom sections under the action of waves; this kind of test is usually carried out in a wave flume, where open sea conditions can be reproduced at a scale. Traditional methods use capacitance or conductivity gauges (Hughes, 1993) to measure the waves. One of these gauges only provides the measurement at one point; further, it isn’t able to detect the interphase between two or more fluids, such as water and a hydrocarbon. An additional drawback of conventional wave gauges is their cost. Other experiments such as velocity measurements, sand concentration measurements, bed level measurements, breakwater’s behaviour, etc... and the set of traditional methods or instruments used in those experiments which goes from EMF, ADV for velocity measurements to pressure sensors, capacity wires, acoustic sensors, echo soundings for measuring wave height and sand concentration, are common used in wave flume experiments. All instruments have an associate error (Van Rijn, Grasmeijer & Ruessink, 2000), and an associate cost (most of them are too expensive for a lot of laboratories that can not afford pay those amount of money), certain limitations and some of them need a large term of calibration. This paper presents another possibility for wave flume experiments, computer vision, which used a cheap and affordable technology (common video cameras and pc’s), it is calibrated automatically (once we have developed the calibration task), is a non-intrusive technology and its potential uses could takes up all kind experiments developed in wave flumes. Are artificial vision’s programmers who can give computer vision systems all possibilities inside the visual field of a video camera. Most experiments conducted in wave flumes and new ones can be carried out programming computer vision systems. In fact, in this paper, a new kind of wave flume experiment is presented, a kind of experiment that without artificial vision technology it couldn’t be done.