Targeted testing and machine-learning systems for detecting and identifying machine behavior
Abstract:
Systems and methods are described for identifying a behavior of a machine. A computer system receives a signal indicative of operation of a field machine and applies a deep learning algorithm to identify a pattern in a collection of signals stored on a computer-readable memory. The collection of signals includes the received signal indicative of operation of the field machine and other signals. A series of targeted tests are performed using a test machine while monitoring a signal indicative of operation of the test machine. A behavior is identified during the series of targeted tests that produces a signal that matches the pattern identified by the deep learning algorithm. An occurrence of the behavior is then automatically identified in the field machine in response to detecting the pattern in the received signal indicative of operation of the field machine.
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