US 12,216,147 B2
Non-invasive diagnostic systems and methods for using the same
Mark Scott, Oxford, OH (US); and Matt Boubin, Queens, NY (US)
Assigned to Miami University, Oxford, OH (US)
Filed by Miami University, Oxford, OH (US)
Filed on Jun. 8, 2023, as Appl. No. 18/331,585.
Application 18/331,585 is a continuation of application No. 16/879,734, filed on May 20, 2020, granted, now 11,714,114.
Claims priority of provisional application 62/850,203, filed on May 20, 2019.
Prior Publication US 2024/0159811 A1, May 16, 2024
Int. Cl. G01R 31/00 (2006.01); G01R 29/08 (2006.01); G06N 20/00 (2019.01)
CPC G01R 31/001 (2013.01) [G01R 29/0814 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method for determining whether a circuit fault exists in one or more components of a power electronic device comprising:
modeling a component of the power electronic device;
modeling one or more a plurality of failure modes for the component;
identifying an electromagnetic interference (EMI) characteristic of the component, wherein the EMI characteristic is indicative of each of the plurality of failure modes;
training a machine learning algorithm to detect each of the plurality of modeled failure modes based on the EMI characteristic;
monitoring the EMI of the component;
analyzing the monitored EMI via the machine learning algorithm to detect each of the plurality of modeled failure modes; and
providing feedback that no faults exist if none of the plurality of modeled failure modes are detected.