A Fault Detection Method for Automatic Detection of Spawning in Oysters

Hafiz Ahmed; Rosane Ushirobira; Denis  Efimov; Damien  Tran; Mohamedou  Sow; Laura Payton; Jean-Charles  Massabuau

doi:10.1109/TCST.2015.2472999

A Fault Detection Method for Automatic Detection of Spawning in Oysters

Hafiz Ahmed, Rosane Ushirobira, Denis Efimov, Damien Tran, Mohamedou Sow, Laura Payton, Jean-Charles Massabuau

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

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Abstract

Using measurements of valve activity (i.e., the distance between the two valves) in populations of bivalves under 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 in this brief. Spawning observations are important in aquaculture and biological studies, and until now, such a detection is done through visual analysis by an expert. The algorithm is based 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 derivative of the valve distance. A summarized description of the methods used for the derivative estimation is provided, followed by the associated signal processing and decision-making algorithm to determine spawning from the velocity signal. A protection from false spawning detection is also considered by analyzing the simultaneity in spawning. Through this study, it is shown that spawning in a population of oysters living in their natural habitat (i.e., in the sea) can be automatically detected without any human expertise, saving time and resources. The fault detection method presented in this brief can also be used to detect complex oscillatory behavior which is of interest to control engineering community.

Original language	English
Pages (from-to)	1140-1147
Number of pages	8
Journal	IEEE Transactions on Control Systems Technology
Volume	24
Issue number	3
Early online date	9 Sept 2015
DOIs	https://doi.org/10.1109/TCST.2015.2472999
Publication status	Published - May 2016

Bibliographical note

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

Keywords

Valves
Sea measurements
Fault detection
Monitoring
Coils
Noise
Estimation
aquaculture
decision making
fault diagnosis
signal processing
fault detection
automatic detection
oysters spawning
valve movement activity measurements
bivalves
natural environmental conditions
Bay of Arcachon
France
biological studies
visual analysis
velocity estimation
valve distance
derivative estimation
decision-making algoritm
velocity signal
oscillatory behavior
filtering
spawning

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Cite this

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title = "A Fault Detection Method for Automatic Detection of Spawning in Oysters",

abstract = "Using measurements of valve activity (i.e., the distance between the two valves) in populations of bivalves under 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 in this brief. Spawning observations are important in aquaculture and biological studies, and until now, such a detection is done through visual analysis by an expert. The algorithm is based 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 derivative of the valve distance. A summarized description of the methods used for the derivative estimation is provided, followed by the associated signal processing and decision-making algorithm to determine spawning from the velocity signal. A protection from false spawning detection is also considered by analyzing the simultaneity in spawning. Through this study, it is shown that spawning in a population of oysters living in their natural habitat (i.e., in the sea) can be automatically detected without any human expertise, saving time and resources. The fault detection method presented in this brief can also be used to detect complex oscillatory behavior which is of interest to control engineering community.",

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author = "Hafiz Ahmed and Rosane Ushirobira and Denis Efimov and Damien Tran and Mohamedou Sow and Laura Payton and Jean-Charles Massabuau",

note = "{\textcopyright} 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Copyright {\textcopyright} and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders. ",

year = "2016",

month = may,

doi = "10.1109/TCST.2015.2472999",

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AU - Ahmed, Hafiz

AU - Ushirobira, Rosane

AU - Efimov, Denis

AU - Tran, Damien

AU - Sow, Mohamedou

AU - Payton, Laura

AU - Massabuau, Jean-Charles

N1 - © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

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N2 - Using measurements of valve activity (i.e., the distance between the two valves) in populations of bivalves under 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 in this brief. Spawning observations are important in aquaculture and biological studies, and until now, such a detection is done through visual analysis by an expert. The algorithm is based 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 derivative of the valve distance. A summarized description of the methods used for the derivative estimation is provided, followed by the associated signal processing and decision-making algorithm to determine spawning from the velocity signal. A protection from false spawning detection is also considered by analyzing the simultaneity in spawning. Through this study, it is shown that spawning in a population of oysters living in their natural habitat (i.e., in the sea) can be automatically detected without any human expertise, saving time and resources. The fault detection method presented in this brief can also be used to detect complex oscillatory behavior which is of interest to control engineering community.

AB - Using measurements of valve activity (i.e., the distance between the two valves) in populations of bivalves under 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 in this brief. Spawning observations are important in aquaculture and biological studies, and until now, such a detection is done through visual analysis by an expert. The algorithm is based 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 derivative of the valve distance. A summarized description of the methods used for the derivative estimation is provided, followed by the associated signal processing and decision-making algorithm to determine spawning from the velocity signal. A protection from false spawning detection is also considered by analyzing the simultaneity in spawning. Through this study, it is shown that spawning in a population of oysters living in their natural habitat (i.e., in the sea) can be automatically detected without any human expertise, saving time and resources. The fault detection method presented in this brief can also be used to detect complex oscillatory behavior which is of interest to control engineering community.

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KW - Noise

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KW - signal processing

KW - fault detection

KW - automatic detection

KW - oysters spawning

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KW - visual analysis

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KW - valve distance

KW - derivative estimation

KW - decision-making algoritm

KW - velocity signal

KW - oscillatory behavior

KW - filtering

KW - spawning

U2 - 10.1109/TCST.2015.2472999

DO - 10.1109/TCST.2015.2472999

M3 - Article

SN - 1063-6536

VL - 24

SP - 1140

EP - 1147

JO - IEEE Transactions on Control Systems Technology

JF - IEEE Transactions on Control Systems Technology

IS - 3

ER -

A Fault Detection Method for Automatic Detection of Spawning in Oysters

Abstract

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Keywords

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