US 12,244,266 B2
Systems and methods for fault classification in photovoltaic arrays using graph signal processing
Jie Fan, Tempe, AZ (US); Sunil Rao, Tempe, AZ (US); Gowtham Muniraju, Tempe, AZ (US); Cihan Tepedelenlioglu, Tempe, AZ (US); and Andreas Spanias, Tempe, AZ (US)
Assigned to Arizona Board of Regents on Behalf of Arizona State University, Tempe, AZ (US)
Filed by Jie Fan, Tempe, AZ (US); Sunil Rao, Tempe, AZ (US); Gowtham Muniraju, Tempe, AZ (US); Cihan Tepedelenlioglu, Tempe, AZ (US); and Andreas Spanias, Tempe, AZ (US)
Filed on May 12, 2021, as Appl. No. 17/318,046.
Claims priority of provisional application 63/023,620, filed on May 12, 2020.
Prior Publication US 2021/0357703 A1, Nov. 18, 2021
Int. Cl. H02S 50/00 (2014.01); G06F 18/20 (2023.01); G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06F 18/241 (2023.01); G06N 20/00 (2019.01)
CPC H02S 50/00 (2013.01) [G06F 18/2155 (2023.01); G06F 18/22 (2023.01); G06F 18/241 (2023.01); G06F 18/29 (2023.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system for determining a classification of one or more nodes of a physical array, comprising:
a physical array including a plurality of nodes, wherein each node of the plurality of nodes includes a plurality of measurable features and wherein a plurality of labeled nodes are a subset of the plurality of nodes and are labeled according to a respective classification of each labeled node; and
a processor in communication with a memory module and being operable to execute stored instructions, the stored instructions, when executed, cause the processor to:
obtain a feature matrix including the plurality of measurable features associated with each respective node of the plurality of nodes;
generate a graph shift matrix based on the feature matrix, the graph shift matrix being representative of similarity between each node of the plurality of nodes;
generate a node target class matrix denoting labels for each node of the plurality of nodes, the node target class matrix including a plurality of rows associated with a respective plurality of classifications and wherein each node is represented within each row of the plurality of rows of the node target class matrix;
determine a set of optimized graph filter coefficients for a graph filter representative of a mapping between the plurality of features of each node of the plurality of nodes and a respective classification for each node of the plurality of nodes based on the graph shift matrix and the node target class matrix; and
determine a respective classification for each unlabeled node of the plurality of nodes using the graph filter with the set of optimized graph filter coefficients.