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 8):
An optical communication system according to  claim 1 , wherein the fault is a span loss fault and the LME is configured to transmit an OTDR test signal on the optical transmission path and receive OTDR test signal data from the optical transmission path in response to the OTDR test signal, and\n wherein the processor is further configured to report a directionality of the span loss fault in response to a change in amplitude in the OTDR test signal data.

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): 0.7126568930040807
- 35 USC 102 Novelty (BERT): 0.5445969233131703
- Combined Prediction Score: 0.6958508960349896
- Mean Citation Score: 264.405218
- Max Citation Score: 347.2085
- Similarity Product: 258.6735212224722

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

Dataset: test