Passive Acoustic Leak Detection for Sodium Cooled Fast Reactors Using Hidden Markov Models

A. Riber Marklund (1) , S. Kishore (2) , V. Prakash (2) , K. K. Rajan (2) , F. Michel (3)

1 KTH Royal Institute of Technology - Department of Mathematics
2 Nuclear and Radioanalytical Chemistry, IGCAR, Kalpakkam-603102, Tamilnadu
3 CEA-DES (ex-DEN) - CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire)

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970s and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), the proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control.

Domains: Physics [physics]; Nuclear Experiment [nucl-ex]; Physics [physics]; Nuclear Theory [nucl-th]

A. Riber Marklund, S. Kishore, V. Prakash, K. K. Rajan, F. Michel. Passive Acoustic Leak Detection for Sodium Cooled Fast Reactors Using Hidden Markov Models. ANIMMA 2015 - 4th International Conference on Advancements in Nuclear Instrumentation Measurement Methods and their Applications, Apr 2015, Lisbon, Portugal. ⟨10.1109/ANIMMA.2015.7465560⟩. ⟨cea-02509266⟩