7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access
7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access
https://doi.org/10.36001/phmconf.2014.v6i1.2508
Copy DOIJournal: Annual Conference of the PHM Society | Publication Date: Sep 29, 2014 |
License type: cc-by |
System state determination with incomplete sensory information set proved to be a technically challenging problem. In this paper, authors tackle a problem of this type associated with vehicle fuel storage systems and proposed a novel feature extraction method. Federal and state regulations require fuel storage leak detection mechanism to be conducted periodically and regulate its execution rate and performance to ensure effective emission controls. Being able to robustly determine a fuel storage system’s state in terms of its effectiveness of fuel containment is therefore of great importance to all vehicle original equipment manufacturers (OEM). Prevailing practice in the industry utilizes a method relevant to natural vacuum phenomenon and is loosely associated with ideal gas law. Commonly referred to as “Entry Conditions” in in-vehicle monitoring design literature, major noise factors go through stringent pre-monitoring evaluations before monitoring program execution to ensure ideal test conditions. Differences in ambient conditions compounded with varying customer drive cycle patterns present great challenge to existing monitor designs for the purpose of leak detection. In addition, prevailing practices of evaluation in-tank fuel pressure and temperature information are generally conducted with surrogate or estmiated temperature information due to the absence of in-tank temperature sensor. All this calls for an alternative feature calculation and detection method that are less sensitive to known noise factors, can operate with incomplete sensory information yet being able provide similar or improved detection capability. In this paper, we put the main focus on the derivation of a novel method of feature calculation for the purpose of detecting presence of a leak in a fuel storage tank.
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.