PATENT CLAIM ANALYSIS

Application Number: 15937241
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-08
Patent Classification: ["398", "021000"]

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.

Claim (Index 5):
An optical communication system according to  claim 1 , wherein the LME test signal is transmitted at a first wavelength, and wherein the LME is configured to transmit a second LME test signal on the optical transmission path at a second wavelength and receive a second LME loopback data from the optical transmission path in response to the second LME test signal,\n and wherein the processor is further configured to: compare the second LME loopback data to the baseline loopback data to obtain a second fault signature; analyze the second fault signature using the first fault classifier to indicate the fault if the second fault signature matches the predetermined fault signature; and report a fault in the system if the first fault classifier and the second fault classifier both indicate the fault.

Metadata:
- Claim Count in Document: 28.0
- Percentile: 90.0
- Lexical Diversity: 2.31579
- Patent Class: 398.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15870311', '13754344', '11829422', '15875734', '12140831']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7123697169372656
- 35 USC 102 Novelty (BERT): 0.5427410470929408
- Combined Prediction Score: 0.6954068499528331
- Mean Citation Score: 264.405218
- Max Citation Score: 347.2085
- Similarity Product: 292.50696763914823

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test