ANN based sensor and actuator fault detection in nuclear reactors

Shohan Banerjee; Jiamei M. Deng; Chris Gorse; Vineet Vajpayee; Victor Becerra; S. R. Shimjith

doi:10.1109/ICCMA51325.2020.9301579

ANN based sensor and actuator fault detection in nuclear reactors

Shohan Banerjee, Jiamei M. Deng, Chris Gorse, Vineet Vajpayee, Victor Becerra, S. R. Shimjith

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

133 Downloads (Pure)

Abstract

In the nuclear power plants (NPPs), fault detection and diagnosis (FDD) methods are very important to improve the safety and reliability of plants. Researchers have established various FDD methods such as model-based methods, data driven methods, and signal-based methods. In practical applications, model based methods are very difficult to achieve. Thus, various data-driven methods and signal-based methods have been applied for monitoring key subsystems in NPPs. In this paper, a brief overview of the Artificial Neural Network (ANN) based FDD method is presented. Simulated data have been generated to train the ANNs as per requirement and to compare with the plant signal during a fault. A technique has been proposed analyzing two sensors data (power sensor and coolant sensor) to determine the sensor and actuator fault in a closed-loop in presence of robust (Proportional-Integral-Derivative) PID controller. Results are produced with credible MATLAB simulation.

Original language	English
Title of host publication	Proceedings of the 8th International Conference on Control, Mechatronics and Automation, (ICCMA 2020)
Place of Publication	978-1-7281-9211-6
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	88-94
Number of pages	7
ISBN (Electronic)	978-1-7281-9210-9, 978-1-7281-9209-3
DOIs	https://doi.org/10.1109/ICCMA51325.2020.9301579
Publication status	Published - 29 Dec 2020
Event	The 8th International Conference on Control, Mechatronics and Automation - Moscow, Russian Federation Duration: 6 Nov 2020 → 8 Nov 2020 http://www.iccma.org/

Conference

Conference	The 8th International Conference on Control, Mechatronics and Automation
Abbreviated title	ICCMA 2020
Country/Territory	Russian Federation
City	Moscow
Period	6/11/20 → 8/11/20
Internet address	http://www.iccma.org/

Keywords

RCUK
EPSRC
EP/R021961/1
EP/R022062/1
ANN
fault detection
NPP
PWR

Access to Document

10.1109/ICCMA51325.2020.9301579

ICCMA_20_SB
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Accepted author manuscript (Post-print), 1.18 MB

Fault Tolerant Control for Increased Safety and Security of Nuclear Power Plants
Becerra, V. & Bausch, N.
Engineering and Physical Sciences Research Council
1/12/18 → 28/02/22
Project: Research

Cite this

Banerjee, S., Deng, J. M., Gorse, C., Vajpayee, V., Becerra, V., & Shimjith, S. R. (2020). ANN based sensor and actuator fault detection in nuclear reactors. In Proceedings of the 8th International Conference on Control, Mechatronics and Automation, (ICCMA 2020) (pp. 88-94). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCMA51325.2020.9301579

@inproceedings{f1970ae0c2174f0d99d0c06e6fb1432f,

title = "ANN based sensor and actuator fault detection in nuclear reactors",

abstract = "In the nuclear power plants (NPPs), fault detection and diagnosis (FDD) methods are very important to improve the safety and reliability of plants. Researchers have established various FDD methods such as model-based methods, data driven methods, and signal-based methods. In practical applications, model based methods are very difficult to achieve. Thus, various data-driven methods and signal-based methods have been applied for monitoring key subsystems in NPPs. In this paper, a brief overview of the Artificial Neural Network (ANN) based FDD method is presented. Simulated data have been generated to train the ANNs as per requirement and to compare with the plant signal during a fault. A technique has been proposed analyzing two sensors data (power sensor and coolant sensor) to determine the sensor and actuator fault in a closed-loop in presence of robust (Proportional-Integral-Derivative) PID controller. Results are produced with credible MATLAB simulation.",

keywords = "RCUK, EPSRC, EP/R021961/1, EP/R022062/1, ANN, fault detection, NPP, PWR",

author = "Shohan Banerjee and Deng, {Jiamei M.} and Chris Gorse and Vineet Vajpayee and Victor Becerra and Shimjith, {S. R.}",

year = "2020",

month = dec,

day = "29",

doi = "10.1109/ICCMA51325.2020.9301579",

language = "English",

pages = "88--94",

booktitle = "Proceedings of the 8th International Conference on Control, Mechatronics and Automation, (ICCMA 2020)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Banerjee, S, Deng, JM, Gorse, C, Vajpayee, V, Becerra, V & Shimjith, SR 2020, ANN based sensor and actuator fault detection in nuclear reactors. in Proceedings of the 8th International Conference on Control, Mechatronics and Automation, (ICCMA 2020). Institute of Electrical and Electronics Engineers Inc., 978-1-7281-9211-6, pp. 88-94, The 8th International Conference on Control, Mechatronics and Automation, Moscow, Russian Federation, 6/11/20. https://doi.org/10.1109/ICCMA51325.2020.9301579

ANN based sensor and actuator fault detection in nuclear reactors. / Banerjee, Shohan; Deng, Jiamei M.; Gorse, Chris et al.
Proceedings of the 8th International Conference on Control, Mechatronics and Automation, (ICCMA 2020). 978-1-7281-9211-6: Institute of Electrical and Electronics Engineers Inc., 2020. p. 88-94.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - ANN based sensor and actuator fault detection in nuclear reactors

AU - Banerjee, Shohan

AU - Deng, Jiamei M.

AU - Gorse, Chris

AU - Vajpayee, Vineet

AU - Becerra, Victor

AU - Shimjith, S. R.

PY - 2020/12/29

Y1 - 2020/12/29

N2 - In the nuclear power plants (NPPs), fault detection and diagnosis (FDD) methods are very important to improve the safety and reliability of plants. Researchers have established various FDD methods such as model-based methods, data driven methods, and signal-based methods. In practical applications, model based methods are very difficult to achieve. Thus, various data-driven methods and signal-based methods have been applied for monitoring key subsystems in NPPs. In this paper, a brief overview of the Artificial Neural Network (ANN) based FDD method is presented. Simulated data have been generated to train the ANNs as per requirement and to compare with the plant signal during a fault. A technique has been proposed analyzing two sensors data (power sensor and coolant sensor) to determine the sensor and actuator fault in a closed-loop in presence of robust (Proportional-Integral-Derivative) PID controller. Results are produced with credible MATLAB simulation.

AB - In the nuclear power plants (NPPs), fault detection and diagnosis (FDD) methods are very important to improve the safety and reliability of plants. Researchers have established various FDD methods such as model-based methods, data driven methods, and signal-based methods. In practical applications, model based methods are very difficult to achieve. Thus, various data-driven methods and signal-based methods have been applied for monitoring key subsystems in NPPs. In this paper, a brief overview of the Artificial Neural Network (ANN) based FDD method is presented. Simulated data have been generated to train the ANNs as per requirement and to compare with the plant signal during a fault. A technique has been proposed analyzing two sensors data (power sensor and coolant sensor) to determine the sensor and actuator fault in a closed-loop in presence of robust (Proportional-Integral-Derivative) PID controller. Results are produced with credible MATLAB simulation.

KW - RCUK

KW - EPSRC

KW - EP/R021961/1

KW - EP/R022062/1

KW - ANN

KW - fault detection

KW - NPP

KW - PWR

U2 - 10.1109/ICCMA51325.2020.9301579

DO - 10.1109/ICCMA51325.2020.9301579

M3 - Conference contribution

SP - 88

EP - 94

BT - Proceedings of the 8th International Conference on Control, Mechatronics and Automation, (ICCMA 2020)

PB - Institute of Electrical and Electronics Engineers Inc.

CY - 978-1-7281-9211-6

T2 - The 8th International Conference on Control, Mechatronics and Automation

Y2 - 6 November 2020 through 8 November 2020

ER -

ANN based sensor and actuator fault detection in nuclear reactors

Abstract

Conference

Keywords

Access to Document

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Projects

Fault Tolerant Control for Increased Safety and Security of Nuclear Power Plants

Cite this