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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Main Authors: Chetan S. Kulkarni, Matthew J. Daigle, George Gorospe, Kai Goebel
Format: Article
Language:English
Published: The Prognostics and Health Management Society 2017-01-01
Series:International Journal of Prognostics and Health Management
Subjects:
Online Access:https://papers.phmsociety.org/index.php/ijphm/article/view/2590
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spelling doaj-7cbb8faba79441c5ae6c52beab1403012021-07-02T20:42:25ZengThe Prognostics and Health Management SocietyInternational Journal of Prognostics and Health Management2153-26482153-26482017-01-0181doi:10.36001/ijphm.2017.v8i1.2590Experimental Validation of Model-Based Prognostics for Pneumatic ValvesChetan S. Kulkarni0Matthew J. Daigle1George Gorospe2Kai Goebel3SGT, Inc., NASA Ames Research Center, Moffett Field, CA, 94035, USANASA Ames Research Center, Moffett Field, CA, 94035, USASGT, Inc., NASA Ames Research Center, Moffett Field, CA, 94035, USANASA Ames Research Center, Moffett Field, CA, 94035, USABecause 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.https://papers.phmsociety.org/index.php/ijphm/article/view/2590prognosticspneumatic valvesremaining useful lifedegradation modeling
collection DOAJ
language English
format Article
sources DOAJ
author Chetan S. Kulkarni
Matthew J. Daigle
George Gorospe
Kai Goebel
spellingShingle Chetan S. Kulkarni
Matthew J. Daigle
George Gorospe
Kai Goebel
Experimental Validation of Model-Based Prognostics for Pneumatic Valves
International Journal of Prognostics and Health Management
prognostics
pneumatic valves
remaining useful life
degradation modeling
author_facet Chetan S. Kulkarni
Matthew J. Daigle
George Gorospe
Kai Goebel
author_sort Chetan S. Kulkarni
title Experimental Validation of Model-Based Prognostics for Pneumatic Valves
title_short 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_sort experimental validation of model-based prognostics for pneumatic valves
publisher The Prognostics and Health Management Society
series International Journal of Prognostics and Health Management
issn 2153-2648
2153-2648
publishDate 2017-01-01
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.
topic prognostics
pneumatic valves
remaining useful life
degradation modeling
url https://papers.phmsociety.org/index.php/ijphm/article/view/2590
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