LAPSE:2020.0053
Published Article
LAPSE:2020.0053
Evolutionary Observer Ensemble for Leak Diagnosis in Water Pipelines
January 7, 2020
This work deals with the Leak Detection and Isolation (LDI) problem in water pipelines based on some heuristic method and assuming only flow rate and pressure head measurements at both ends of the duct. By considering the single leak case at an interior node of the pipeline, it has been shown that observability is indeed satisfied in this case, which allows designing an observer for the unmeasurable state variables, i.e., the pressure head at leak position. Relying on the fact that the origin of the observation error is exponentially stable if all parameters (including the leak coefficients) are known and uniformly ultimately bounded otherwise, the authors propose a bank of observers as follows: taking into account that the physical pipeline parameters are well-known, and there is only uncertainty about leak coefficients (position and magnitude), a pair of such coefficients is taken from a search space and is assigned to an observer. Then, a Genetic Algorithm (GA) is exploited to minimize the integration of the square observation error. The minimum integral observation error will be reached in the observer where the estimated leak parameters match the real ones. Finally, some results are presented by using real-noisy databases coming from a test bed plant built at Cinvestav-Guadalajara, aiming to show the potentiality of this method.
Keywords
fault diagnosis, Genetic Algorithm, leak isolation, nonlinear observer
Suggested Citation
Navarro A, Delgado-Aguiñaga JA, Sánchez-Torres JD, Begovich O, Besançon G. Evolutionary Observer Ensemble for Leak Diagnosis in Water Pipelines. (2020). LAPSE:2020.0053
Author Affiliations
Navarro A: Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Av. General Ramón Corona 2514, Zapopan C.P. 45138, Jalisco, Mexico [ORCID]
Delgado-Aguiñaga JA: Centro de Investigación, Innovación y Desarrollo Tecnológico CIIDETEC-UVM, Universidad del Valle de México, Periférico Sur Manuel Gómez Morín 8077, Tlaquepaque C.P. 45601, Jalisco, Mexico [ORCID]
Sánchez-Torres JD: OPTIMA Lab, Departamento de Matemáticas y Física, ITESO, Periférico Sur Manuel Gómez Morín 8585, Tlaquepaque C.P. 45604, Jalisco, Mexico [ORCID]
Begovich O: CINVESTAV Guadalajara, Av. del Bosque 1145, Col. El Bajío, Zapopan C.P. 45019, Jalisco, Mexico [ORCID]
Besançon G: Université Grenoble Alpes, CNRS, Grenoble INP, Institute of Engineering Université Grenoble Alpes, GIPSA-lab, 38000 Grenoble, France [ORCID]
Journal Name
Processes
Volume
7
Issue
12
Article Number
E913
Year
2019
Publication Date
2019-12-03
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr7120913, Publication Type: Journal Article
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LAPSE:2020.0053
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doi:10.3390/pr7120913
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Jan 7, 2020
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CC BY 4.0
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[v1] (Original Submission)
Jan 7, 2020
 
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Jan 7, 2020
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Original Submitter
Calvin Tsay
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