{"@type": "dcat:Dataset", "accessLevel": "public", "accrualPeriodicity": "irregular", "bureauCode": ["026:00"], "contactPoint": {"@type": "vcard:Contact", "fn": "Miryam Strautkalns", "hasEmail": "mailto:miryam.strautkalns@nasa.gov"}, "description": "This paper presents a novel set of uncertainty measures to quantify the impact of input uncertainty on nonlinear prognosis systems. A Particle Filtering-based method is also presented that uses this set of uncertainty measures to quantify, in real time, the impact of load, environmen- tal, and other stresses for long-term prediction. Further- more, this work shows how these measures can be used to implement a novel feedback correction loop aimed to suggest modifications, at a system input level, with the purpose of extending the remaining useful life of a faulty nonlinear, non-Gaussian system. The correction scheme is tested and illustrated using real vibration feature data from a fatigue-driven fault in a critical aircraft compo- nent.", "distribution": [{"@type": "dcat:Distribution", "description": "2010_PHM_Uncertainty.pdf", "downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/2010_PHM_Uncertainty.pdf", "format": "PDF", "mediaType": "application/pdf", "title": "2010_PHM_Uncertainty.pdf"}], "identifier": "DASHLINK_777", "issued": "2013-06-19", "keyword": ["ames", "dashlink", "nasa"], "landingPage": "https://c3.nasa.gov/dashlink/resources/777/", "modified": "2025-03-31", "programCode": ["026:029"], "publisher": {"@type": "org:Organization", "name": "Dashlink"}, "title": "Impact of Input Uncertainty on Failure Prognostic Algorithms: Extending the Remaining Useful Life of Nonlinear Systems"}