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Experimental Validation of Model-Based Prognostics for Pneumatic Valves

Because valves control many critical operations, they are prime candidates for deployment of prognostic algorithms. But, similar to the situation with most other components, examples of failures experienced in the field are hard to come by. This lack of data impacts the ability to test and validate...

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Detalles Bibliográficos
Autores principales: Kulkarni, Chetan S., Daigle, Matthew J., Gorospe, George, Goebel, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7398137/
https://www.ncbi.nlm.nih.gov/pubmed/32747869
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author Kulkarni, Chetan S.
Daigle, Matthew J.
Gorospe, George
Goebel, Kai
author_facet Kulkarni, Chetan S.
Daigle, Matthew J.
Gorospe, George
Goebel, Kai
author_sort Kulkarni, Chetan S.
collection PubMed
description Because valves control many critical operations, they are prime candidates for deployment of prognostic algorithms. But, similar to the situation with most other components, examples of failures experienced in the field are hard to come by. This lack of data impacts the ability to test and validate prognostic algorithms. A solution sometimes employed to overcome this shortcoming is to perform run-to-failure experiments in a lab. However, the mean time to failure of valves is typically very high (possibly lasting decades), preventing evaluation within a reasonable time frame. Therefore, a mechanism to observe development of fault signatures considerably faster is sought. Described here is a testbed that addresses these issues by allowing the physical injection of leakage faults (which are the most common fault mode) into pneumatic valves. What makes this testbed stand out is the ability to modulate the magnitude of the fault almost arbitrarily fast. With that, the performance of end-of-life estimation algorithms can be tested. Further, the testbed is mobile and can be connected to valves in the field. This mobility helps to bring the overall process of prognostic algorithm development for this valve a step closer to validation. The paper illustrates the development of a model-based prognostic approach that uses data from the testbed for partial validation.
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spelling pubmed-73981372020-08-03 Experimental Validation of Model-Based Prognostics for Pneumatic Valves Kulkarni, Chetan S. Daigle, Matthew J. Gorospe, George Goebel, Kai Int J Progn Health Manag Article Because valves control many critical operations, they are prime candidates for deployment of prognostic algorithms. But, similar to the situation with most other components, examples of failures experienced in the field are hard to come by. This lack of data impacts the ability to test and validate prognostic algorithms. A solution sometimes employed to overcome this shortcoming is to perform run-to-failure experiments in a lab. However, the mean time to failure of valves is typically very high (possibly lasting decades), preventing evaluation within a reasonable time frame. Therefore, a mechanism to observe development of fault signatures considerably faster is sought. Described here is a testbed that addresses these issues by allowing the physical injection of leakage faults (which are the most common fault mode) into pneumatic valves. What makes this testbed stand out is the ability to modulate the magnitude of the fault almost arbitrarily fast. With that, the performance of end-of-life estimation algorithms can be tested. Further, the testbed is mobile and can be connected to valves in the field. This mobility helps to bring the overall process of prognostic algorithm development for this valve a step closer to validation. The paper illustrates the development of a model-based prognostic approach that uses data from the testbed for partial validation. 2017 2018-01-19 /pmc/articles/PMC7398137/ /pubmed/32747869 Text en https://creativecommons.org/licenses/by/3.0/Chetan S. Kulkarni et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Article
Kulkarni, Chetan S.
Daigle, Matthew J.
Gorospe, George
Goebel, Kai
Experimental Validation of Model-Based Prognostics for Pneumatic Valves
title Experimental Validation of Model-Based Prognostics for Pneumatic Valves
title_full Experimental Validation of Model-Based Prognostics for Pneumatic Valves
title_fullStr Experimental Validation of Model-Based Prognostics for Pneumatic Valves
title_full_unstemmed Experimental Validation of Model-Based Prognostics for Pneumatic Valves
title_short Experimental Validation of Model-Based Prognostics for Pneumatic Valves
title_sort experimental validation of model-based prognostics for pneumatic valves
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7398137/
https://www.ncbi.nlm.nih.gov/pubmed/32747869
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