NDLI: Hybrid resampling scheme for particle filter-based inversion

Content Provider	IET Digital Library
Author	Zafar, Taimoor Mairaj, Tariq Alam, Anzar Rasheed, Haroon
Abstract	A novel online hybrid resampling (HR) scheme based on the combination of residual and multinomial resampling schemes is proposed. It can be implemented within the framework of the sequential Monte Carlo-based inversion algorithm, also known as particle filter (PF). Based upon the degeneracy of each particle, the choice of best resampling scheme among both candidates is made at each instant iteratively. Consequently, the inversion performance of PF improves by reducing the computational complexity of the resampling scheme. The proposed online HR scheme is incorporated here within the framework of the PF-based inversion scheme once applied on nuclear power plant steam generator non-destructive testing measurement data. The promising results showcase the efficacy of the technique.
Starting Page	396
Ending Page	406
Page Count	11
ISSN	17518822
Volume Number	14
e-ISSN	17518830
Issue Number	Issue 4, Jun (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-smt/14/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-smt.2018.5531
Journal	IET Science, Measurement & Technology
Publisher Date	2020-01-09
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Boilers Computational Complexity Interpolation And Function Approximation Iterative Method Monte Carlo Method Multinomial Resampling Scheme Nondestructive Testing Nondestructive Testing Measurement Nuclear Power Plant Nuclear Power Stations Nuclear Power Stations And Plant Numerical Analysis Online HR Scheme Online Hybrid Resampling Scheme Optimisation Technique Particle Filter Particle Filter-based Inversion PF-based Inversion Scheme Residual Resampling Scheme Sequential Monte Carlo-based Inversion Algorithm Steam Generator Thermal Power Stations And Plant
Content Type	Text
Resource Type	Article
Subject	Atomic and Molecular Physics, and Optics Electrical and Electronic Engineering

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