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Spacecraft Micro-Vibration: A Survey of Problems, Experiences, Potential Solutions, and Some Lessons Learned

Show simple item record Dennehy, Cornelius Alvarez-Salazar, Oscar S. 2020-05-11T22:19:44Z 2020-05-11T22:19:44Z 2018-05-28
dc.identifier.citation European Conference on Spacecraft Structures, Materials and Environmental Testing (ECSSMET) 2018, Noordwijk, Netherlands, May 28 - June 1, 2018 en_US
dc.identifier.clearanceno 18-2645
dc.description.abstract Predicting, managing, controlling, and testing spacecraft micro-vibrations due to on-board internal disturbance sources is a formidable multi-disciplinary systems engineering challenge, especially for those observatories hosting extremely sensitive optical sensor payloads with stringent requirements on allowable Line-of-Sight (LOS) jitter. In this paper some specific spacecraft micro-vibration engineering challenges will be introduced and described. Technical background context is provided with the inclusion of several illustrative examples of NASA and ESA missions (both past and present) where dynamic interactions have to be addressed and which have demanding payload instrument LOS jitter requirements. A general modeling, analysis, simulation, and test approach to address and solve the overall problem of spacecraft micro-vibrations is outlined. Recommended rules of thumb are presented to provide guidance for analysts on where to initiate and how to approach a new spacecraft micro-vibration design problem. A set of experience based spacecraft micro-vibration lessons learned are also presented in the hope they can be leveraged on new system development projects to help overcome unfamiliarity with previously identified micro-vibration technical pitfalls and challenges. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2018 en_US
dc.title Spacecraft Micro-Vibration: A Survey of Problems, Experiences, Potential Solutions, and Some Lessons Learned en_US
dc.type Preprint en_US

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