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Experimental Validation of Model-Based Prognostics for Pneumatic ValvesBecause 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.
Document ID
20180001209
Acquisition Source
Ames Research Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Chetan S Kulkarni
(Wyle (United States) El Segundo, California, United States)
Matthew J Daigle
(Ames Research Center Mountain View, California, United States)
George Gorospe
(Wyle (United States) El Segundo, California, United States)
Kai Goebel
(Ames Research Center Mountain View, California, United States)
Date Acquired
February 15, 2018
Publication Date
November 16, 2020
Publication Information
Publication: International Journal of Prognostics and Health Management
Publisher: Prognostics and Health Management Society
Volume: 8
Issue: 1
Issue Publication Date: January 1, 2017
ISSN: 2153-2648
Subject Category
Ground Support Systems And Facilities (Space)
Report/Patent Number
ARC-E-DAA-TN51988
Funding Number(s)
CONTRACT_GRANT: NNA14AA60C
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
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