Ventilation systems depend on periodic preventive maintenance. Unfortunately, mission critical systems, exposed to varying levels of particulates and other contaminants, may require unpredictable and highly variable maintenance intervals. Direct sensing for pressure drops or other condition metrics can provide prognostic indicators, but at the expense of the installation and maintenance burden of the sensors themselves. Rotor slot harmonics from motors have been observed for decades to track motor speed. This paper presents hardware instrumentation and a signal processing algorithm that can nonintrusively track the rotor slot harmonics of multiple fan motors in an aggregate electrical stream. Combined with a physics-based model of the motors under observation, this nonintrusive data can be used to track the maintenance condition of multiple fan motors on a single electrical service, minimizing the costs of installation and data analysis and reducing the total number of sensors necessary to track fan health. Results are demonstrated with experiments on-board a US Coast Guard Cutter.
Bibliographical noteFunding Information:
Manuscript received May 14, 2021; revised June 17, 2021; accepted June 18, 2021. Date of publication June 24, 2021; date of current version August 31, 2021. This work was supported in part by The Grainger Foundation, in part by the Office of Naval Research NEPTUNE Program, and in part by MathWorks. The associate editor coordinating the review of this article and approving it for publication was Prof. Ruqiang Yan. (Corresponding author: Daisy H. Green.) Joseph W. O’Connell, Brian T. Mills, and Stephen Kidwell are with the United States Coast Guard, Washington, DC 20593 USA.
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- Condition monitoring
- fault detection
- nonintrusive monitoring
- rotor slot harmonic
- speed estimation