PATENT CLAIM ANALYSIS

Application Number: 16076860
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-03
Patent Classification: ["073", "570000"]

Abstract:
The invention relates to a method for monitoring the vibrational state of a wind turbine comprising detecting a plurality of acceleration values that represent accelerations which a component of the wind turbine is subject to at different respective points in time within a specified time interval, storing the acceleration values in an acceleration data set; generating a sum frequency distribution on the basis of the acceleration data set, comparing a first sum frequency value of the sum frequency distribution with a second sum frequency value of a threshold sum frequency distribution for at least one acceleration value, and outputting a warning signal if the second sum frequency value is greater than the first sum frequency value.

Claim (Index 7):
The method of  claim 1 , further comprising:\n determining a blade angle of rotor blades of the wind turbine; selecting a limiting cumulative frequency distribution from a plurality of different limiting cumulative frequency distributions which are each associated with different blade angles, wherein the limiting cumulative frequency distribution is selected as a function of the blade angle which the rotor blades have; comparing a first cumulative frequency value of the cumulative frequency distribution to a second cumulative frequency value of the limiting cumulative frequency distribution for at least one acceleration value; and outputting a warning signal if the second cumulative frequency value is greater than the first cumulative frequency value.

Metadata:
- Claim Count in Document: 12.0
- Percentile: 96.0
- Lexical Diversity: 1.92063
- Patent Class: 73.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['13306059', '14266315', '13687679', '12350357', '13125488']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6993105115957109
- 35 USC 102 Novelty (BERT): 0.4740817795127174
- Combined Prediction Score: 0.6767876383874115
- Mean Citation Score: 197.764328
- Max Citation Score: 209.32085
- Similarity Product: 169.45106268289092

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

Dataset: test