Patent ID: 11868906
Assignee: UTOPUS INSIGHTS, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. A system comprising:
at least one processor; and
memory containing instructions, the instructions being executable by the at least one processor to:
receive historical sensor data of a first time period, the historical sensor data including sensor data from one or more sensors of a renewable energy asset;
extract features from the historical sensor data;
perform a unsupervised anomaly detection technique on the historical sensor data to generate a first set of labels associated with the historical sensor data, the performing comprises;
generate an anomaly score based on an output of the unsupervised anomaly detection technique;
compare the anomaly score to a threshold; and
generate a label of the first set of labels based on the comparison;

perform at least one dimensionality reduction technique to generate a second set of labels associated with the historical sensor data, the dimensionality reduction technique reducing a second number of dimensions of the extracted features when compared to a first number of dimensions of the extracted features analyzed using the unsupervised anomaly detection;
combine at least the label of the first set of labels and one or more labels of the second set of labels to generate combined labels;
generate one or more models based on supervised machine learning and the combined labels;
receive current sensor data of a second time period, the current sensor data including sensor data from at least a subset of the one or more sensors of the renewable energy asset;
extract features from the current sensor data;
apply the one or more models to the extracted features of the current sensor data to create a prediction of a future fault in the renewable energy asset;
compare the prediction of the future fault against one or more criteria to determine significance of the future fault, the one or more criteria including a number of failures in close proximity to each other, a total number of failures, significance of risk to the renewable energy asset as a whole, impact to other assets, impact to an electrical network, or impact the future fault has to important service; and
generating an alert based on the comparison, the alert including the prediction of the future fault in the renewable energy asset.