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Energies 2017, 10(12), 2125; doi:10.3390/en10122125

Boolean Network-Based Sensor Selection with Application to the Fault Diagnosis of a Nuclear Plant

Institute of Nuclear and New Energy Technology, Collaborative Innovation Centre of Advanced Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China
Received: 6 November 2017 / Revised: 5 December 2017 / Accepted: 11 December 2017 / Published: 13 December 2017
(This article belongs to the Special Issue 2017 Prognostics and System Health Management Conference)
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Fault diagnosis is crucial for the operation of energy systems such as nuclear plants, and heavily relies on various types of sensors for temperature, pressure, concentration, etc. Due to the redundancy of sensors in each energy system, the sensor selection scheme can deeply influence the diagnostic efficiency. In this paper, a Boolean network (BN) with its linear representation is proposed for describing the fault propagation among sensors. Both the sufficient condition of fault detectability and that of fault discriminability are given. Then, a sensor selection method for fault detection and discrimination is proposed. Finally, the theoretic result is applied to realize the diagnosis oriented sensor selection for a nuclear steam supply system based on a modular high temperature gas-cooled reactor (MHTGR). The computation and simulation results verify the correctness of the theoretical results. View Full-Text
Keywords: fault diagnosis; nuclear plant; sensor selection; semi-tensor product fault diagnosis; nuclear plant; sensor selection; semi-tensor product

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Dong, Z. Boolean Network-Based Sensor Selection with Application to the Fault Diagnosis of a Nuclear Plant. Energies 2017, 10, 2125.

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