2026-09-19T11:19:13Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1445422022-08-30T03:02:14Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Leeb, Steven B.
Krause, Thomas C.
Quinn, Devin Wayne
Massachusetts Institute of Technology. Department of Mechanical Engineering
2022-08-29T15:54:40Z
2022-08-29T15:54:40Z
2022-05
2022-06-23T14:10:28.756Z
https://hdl.handle.net/1721.1/144542
https://orcid.org/0000-0001-5704-1477
Vibration analysis can measure and track machine health. Computational advances in signal processing that leverage spectral coherence to identify subtle shifts in cyclostationary behavior provide new opportunities in vibration-based monitoring. The acquisition of vibration measurements must overcome significant practical challenges for successful vibration analysis. This work demonstrates vibration analysis for shipboard fault detection. Custom instrumentation and measurement techniques are applied to compressors, pumps, fans, and other shipboard electric machines.
S.M.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
Shipboard Fault Detection Methods for Condition-based Maintenance
Thesis
application/pdf
Master
Master of Science in Mechanical Engineering
Publication
unknown
unknown
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<Abstract>Vibration analysis can measure and track machine health. Computational advances in signal processing that leverage spectral coherence to identify subtle shifts in cyclostationary behavior provide new opportunities in vibration-based monitoring. The acquisition of vibration measurements must overcome significant practical challenges for successful vibration analysis. This work demonstrates vibration analysis for shipboard fault detection. Custom instrumentation and measurement techniques are applied to compressors, pumps, fans, and other shipboard electric machines.</Abstract>
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