State estimation problem for the detection of valve closure in gas pipelines. Issue 12 (2nd December 2021)

• Record Type: Journal Article
• Authors: Madeira, Italo M.; Lucumi, Mabel A. R.; Orlande, Helcio R. B.
• Is Part Of: Inverse problems in science and engineering. Volume 29:Issue 12(2021)
• Page Start: 2186
• Page End: 2206
• Publication Date: 2021-12-02
• Subjects: Particle filter -- shutdown valves -- Bayesian framework of statistics -- WAF-TVD scheme -- state estimation problem; Engineering mathematics -- Periodicals; Inverse problems (Differential equations) -- Periodicals; 620.001515357
• DOI: 10.1080/17415977.2021.1910682
• Languages: English
• ISSNs: 1741-5977

Abstract

Abstract : The undesired and unexpected closure of valves in pipelines is the most frequent failure that causes interruptions in the transport of natural gas. This work aims at the detection of valve closures by solving a state estimation problem with the Particle Filter method. The gas flow problem in the duct is solved with a Weighted Average Flux – Total Variation Diminishing scheme, while state variables are estimated with simulated measurements of pressure, velocity and temperature at different points along the pipeline. Two versions of the particle filter method are implemented in this work for the solution of the state estimation problem, namely, the Sampling Importance Resampling (SIR) and the Auxiliary Sampling Importance Resampling (ASIR) algorithms. Accurate estimations were obtained with both algorithms for configurations involving pipelines with one or three valves. On the other hand, the SIR algorithm required a larger number of particles than the ASIR algorithm for the same solution accuracy.