Fault detection and reporting in line monitoring systems

Abstract

In general, a system and method consistent with the present disclosure provides automated line monitoring using a machine learning fault classifier for determining whether a signature associated with the high loss loopback (HLLB) data matches a predetermined fault signature. The fault classifier may be applied to signatures generated in response to line monitoring signals of two different wavelengths. A fault may be reported only if the fault classifier indicates a fault in response to the signature for both wavelengths. A second fault classifier may also be used and a fault may be reported only if both the first and second fault classifiers indicate a fault in response to the signature for both wavelengths. A system consistent with the present disclosure may also, or alternatively, be configured to report the value of a pump degradation, span loss, or repeater failure fault, and may also, or alternatively, report the directionality of a span loss fault or the location of a fiber break fault.

Dependencies are inferred from the claim text.