Time-series fault detection, fault classification, and transition analysis using a K-nearest-neighbor and logistic regression approach
Abstract:
Methods and systems for time-series transient analysis of data are disclosed herein. A method includes receiving time-series data, generating a training data set including randomized data points, generating randomized data point combinations using a set of the randomized data points that are within a time window, computing distance values based on the randomized data point combinations, generating a classifier based on a plurality of computed distance values, and determining, using the classifier, a probability that new time-series data generated during a new execution of the process matches the time-series data. A system for performing the method is also disclosed.
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