Show simple item record

dc.contributor.authorLall, Pradeep
dc.contributor.authorLowe, Ryan
dc.date.accessioned2017-05-09T01:06:55Z
dc.date.available2017-05-09T01:06:55Z
dc.date.issued2014
dc.identifier.issn1528-9044
dc.identifier.otherep_136_04_041013.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl/handle/yetl/154507
dc.description.abstractThis paper compares three prognostic algorithms applied to the same data recorded during the failure of a solder joint in ball grid array component attached to a printed circuit board. The objective is to expand on the relative strengths and weaknesses of each proposed algorithm. Emphasis will be placed on highlighting differences in underlying assumptions required for each algorithm, details of remaining useful life calculations, and methods of uncertainty quantification. Metrics tailored specifically for prognostic health monitoring (PHM) are presented to characterize the performance of predictions. The relative merits of PHM algorithms based on a Kalman filter, extended Kalman filter, and a particle filter all demonstrated on the same data set will be discussed. The paper concludes by discussing which algorithm performs best given the information available about the system being monitored.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleComparison of Prognostic Health Management Algorithms for Assessment of Electronic Interconnect Reliability Under Vibration
dc.typeJournal Paper
dc.journal.volume136
dc.journal.issue4
dc.journal.titleJournal of Electronic Packaging
dc.identifier.doi10.1115/1.4028163
dc.journal.fristpage41013
dc.journal.lastpage41013
dc.identifier.eissn1043-7398
dc.treeJournal of Electronic Packaging:;2014:;volume( 136 ):;issue: 004
dc.contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record