A Fault Detection Method for Automatic Detection of Spawning in Oysters


Using measurements of valve activity (i.e., the gap between the 2 valves) in populations of bivalves below natural environmental conditions (16 oysters in the Bay of Arcachon, France, in 2007, 2013, and 2014), an algorithm for an automatic detection of the spawning period of oysters is proposed during this temporary. Spawning observations are important in aquaculture and biological studies, and till now, such a detection is finished through visual analysis by an professional. The algorithm is predicated on the fault detection approach and it works through the estimation of velocity of valve movement activity, which can be obtained by calculating the time by-product of the valve distance. A summarized description of the methods used for the derivative estimation is provided, followed by the associated signal processing and call-creating algorithm to see spawning from the rate signal. A protection from false spawning detection is additionally thought of by analyzing the simultaneity in spawning. Through this study, it is shown that spawning in a very population of oysters living in their natural habitat (i.e., in the ocean) can be automatically detected while not any human experience, saving time and resources. The fault detection methodology presented in this transient will also be used to detect advanced oscillatory behavior which is of interest to regulate engineering community.

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