14-02-2019 дата публикации
Номер: US20190049525A1
An optically detected power quality disturbance caused by a remote load is classified as belonging to a class of known classes of power quality disturbances. Features associated with different power quality disturbances that belong to a plurality of different known classes of power quality disturbances are learned. Cross-covariance is applied to the optically detected power quality disturbance and the different power quality disturbances that belong to the different known classes of power quality disturbances to recognize features of the optically detected power quality disturbance that at least partially match the learned features. The class of power quality disturbances among the plurality of classes of different known power quality disturbances to which the optically detected power quality disturbance belongs is determined based on the recognized features. 1. A method for classifying an optically detected power quality disturbance , comprising:a) learning features associated with different power quality disturbances that belong to a plurality of different known classes of power quality disturbances;b) applying cross-covariance to the optically detected power quality disturbance and the different power quality disturbances that belong to the plurality of different known classes of power quality disturbances to recognize features of the optically detected power quality disturbance that at least partially match the learned features associated with the different power quality disturbances, wherein the optically detected power quality disturbance is detected remotely from a load causing the optically detected power quality disturbance; andc) determining a class of power quality disturbances among the plurality of classes of different known power quality disturbances to which the optically detected power quality disturbance belongs based on the recognized features.2. The method of claim 1 , wherein the learned features associated with the power quality disturbances ...
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