US 12,488,265 B2
Optimizing a prognostic-surveillance system to achieve a user-selectable functional objective
Menglin Liu, San Mateo, CA (US); Richard P. Sonderegger, Dorchester, MA (US); Kenneth P. Baclawski, Waltham, MA (US); Dieter Gawlick, Palo Alto, CA (US); Anna Chystiakova, Palo Alto, CA (US); Guang C. Wang, San Diego, CA (US); Zhen Hua Liu, San Mateo, CA (US); Hariharan Balasubramanian, Redmond, WA (US); and Kenny C. Gross, Escondido, CA (US)
Assigned to Oracle International Corporation, Redwood City, CA (US)
Filed by Oracle International Corporation, Redwood Shores, CA (US)
Filed on Jul. 28, 2021, as Appl. No. 17/386,965.
Prior Publication US 2023/0035541 A1, Feb. 2, 2023
Int. Cl. G06N 7/06 (2006.01); G06F 18/21 (2023.01); G06F 18/2132 (2023.01); G06N 5/04 (2023.01); G06F 18/214 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01)
CPC G06N 7/06 (2013.01) [G06F 18/21326 (2023.01); G06F 18/2193 (2023.01); G06N 5/04 (2013.01); G06F 18/214 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method for optimizing a prognostic-surveillance system to achieve a user-selectable functional objective, comprising:
receiving a selection of a functional objective to be optimized, wherein the functional objective to be optimized is selected from a set of functional objectives configured for the prognostic-surveillance system, wherein the functional objective comprises a quality of information objective; and
optimizing the selected functional objective, wherein the optimizing the selected functional objective comprises:
performing Monte Carlo simulations using a synthetic data pump,
wherein the synthetic data pump generates time-series signals that vary operational parameters for the prognostic-surveillance system in response to defects in a monitored asset,
wherein the Monte Carlo simulations vary the operational parameters for the prognostic-surveillance system while the prognostic-surveillance system operates on synthesized signals;
determining optimal values for the operational parameters that optimize the selected functional objective; and
determining, based on the Monte Carlo simulations, a quality of sensors, and based on the quality of the sensors, adjusting a sampling rate.