Application of fault detection and identification (FDI) techniques in power regulating systems of nuclear reactors

Roy, Kallol; Banavar, Ravi N.; Thangasamy, S.

doi:10.1109/23.736198

Cited by 22 publications

(10 citation statements)

References 27 publications

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“…Lemma 1 [24]: For an arbitrary given nonlinear system taking the form as (1), if there exists a Hamiltonian function such that (4) then system (1) has the following generalized Hamiltonian realization (5) where is a skew-symmetric matrix, and are all symmetric semi-positive, and the three matrices satisfy…”

Section: A Generalized Hamiltonian Realization (Ghr)mentioning

confidence: 99%

“…The most widely used state observation strategies in practical engineering are Kalman filter (KF) and the extended Kalman filter (EKF) [1]. Kalman filter has been widely used in the areas of monitoring and fault detection and isolation (FDI) for nuclear reactors [2]- [5]. Particle filter (PF) is another promising state-observation strategy, and PF has been applied to observe the state-vector of nuclear reactors successfully [6], [7].…”

Section: Introductionmentioning

confidence: 99%

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Dissipation-Based High Gain Filter for Monitoring Nuclear Reactors

Dong

Feng

Huang

et al. 2010

IEEE Trans. Nucl. Sci.

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Growing electricity requirement and the serious pollution caused by burning petroleum and coal give the current rebirth of nuclear energy industry. State observation is one of the key and basic technologies of system monitoring which is very necessary to the safe and effective operation of today's nuclear reactors. Since nuclear reactors are complex and nonlinear systems, it is quite necessary to design a nonlinear state-observer with high-performance for nuclear reactors. A dissipation-based high gain filter (DHGF) is presented for nonlinear systems in this paper, and robustness analysis is also given. The DHGF is then applied to the state-observation for a nuclear heating reactor (NHR), and simulation results show the feasibility of the DHGF.

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Section: A Generalized Hamiltonian Realization (Ghr)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dissipation-Based High Gain Filter for Monitoring Nuclear Reactors

Dong

Feng

Huang

et al. 2010

IEEE Trans. Nucl. Sci.

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“…In the 1990s, an alternative to the KF, the risk sensitive filter (RSF) was proposed, 7,8,29 which is based on exponential cost criteria. 30 The RSF uses a parameter, called the risk factor in the exponential cost function of squared estimation error, for shaping the estimation probability density function.…”

Section: Introductionmentioning

confidence: 99%

“…Since the 1960s, a large number of nonlinear filtering approaches based on the Kalman filter (KF), 4 risk sensitive, 7,8,[22][23][24] sigma-points, 15,25,26 point-mass, 27 and sequential Monte Carlo (SMC) simulation 5,28 have been proposed for nonlinear estimation problems. However, the sigma points, point mass, and SMC are usually computationally too 0091-3286/2011/$25.00 C 2011 SPIE demanding to be applied in practical applications and, therefore, these approaches are not focused on in the present work.…”

Section: Introductionmentioning

confidence: 99%

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Bearings-only tracking with iterated extended risk sensitive filter

Munisamy¹

2011

Opt. Eng

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This paper concerns the application of an iterated extended risk sensitive filter (IERSF) to target tracking problems. The relative merits of IERSF vis-à-vis the extended risk sensitive filter (ERSF) for a bearingsonly tracking problem using root mean square error (RMSE) and robustness with uncertainty in initial condition are explored. An ERSF weakness, specifically an accumulation error in the computation of innovation steps due to approximating nonlinear functions at a recently available prior estimate, is presented. By using the IERSF with proper tuning of risk factor and local iteration, the filtering divergence may be overcome, and a stable, robust, and unbiased estimation is satisfactorily obtained. With numerical simulation results, the tracking performance of IERSF is compared with the performance of ERSF and extended Kalman filter. The IERSF results in reduced estimation error without much of an increase in burden of the associated computational algorithm. C 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).

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Adapting plant measurement data to improve hardware fault detection performance in pressurised water reactors

Cilliers¹,

Mulder²

2012

Annals of Nuclear Energy

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Application of fault detection and identification (FDI) techniques in power regulating systems of nuclear reactors

Cited by 22 publications

References 27 publications

Dissipation-Based High Gain Filter for Monitoring Nuclear Reactors

Dissipation-Based High Gain Filter for Monitoring Nuclear Reactors

Bearings-only tracking with iterated extended risk sensitive filter

Adapting plant measurement data to improve hardware fault detection performance in pressurised water reactors

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