US 12,396,126 B2
Fan behavior anomaly detection using neural network
Eric Warner, Hudson, NH (US); Michael R. Salpukas, Lexington, MA (US); Arjang J. Noushin, Nashua, NH (US); Daniel J. Tipaldo, Arlington, MA (US); and Daniel D. Sheahan, Somerville, MA (US)
Assigned to Raytheon Company, Arlington, VA (US)
Filed by Raytheon Company, Arlington, VA (US)
Filed on Dec. 17, 2021, as Appl. No. 17/554,495.
Prior Publication US 2023/0196088 A1, Jun. 22, 2023
Int. Cl. H05K 7/20 (2006.01); G06N 3/08 (2023.01)
CPC H05K 7/20209 (2013.01) [G06N 3/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
providing, to a first neural network (NN) trained to model nominal behavior of a first fan and provide a value indicating a first amount of deviation from nominal as an output, first parameters of fan operation of the first fan;
receiving, from the first NN and responsive to the first parameters, first data indicating the first amount of deviation from nominal;
providing, to a second NN trained to model nominal behavior of a second fan and provide a value indicating a second amount of deviation from nominal as an output, second parameters of fan operation of the second fan;
receiving, from the second MN and responsive to the first parameters, second data indicating the second amount of deviation from nominal; and
estimating that the first or second fan has failed or will fail based on a comparison of the first and second data.