PATENT CLAIM ANALYSIS

Application Number: 15997612
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-10
Patent Classification: ["702", "050000"]

Abstract:
Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Claim (Index 19):
The non-transitory computer readable storage medium of  claim 18 , further comprising computer program instructions stored that, when executed by the processor, cause the processor to generate the machine learning model by performing operations comprising:\n determining spectral features for a subset of the plurality of spectral data sets for a respective subset of corresponding systems, wherein fluid conditions of the plurality of systems correspond to varying concentrations of a contaminant or impurity in motor oil; ranking spectral features using a linear model that characterizes spectral features in terms of dependence on concentration of the contaminant or impurity; selecting spectral features having stronger concentration dependence relative to unselected spectral features having weaker concentration dependence, based on the ranking of spectral features according to a predetermined threshold of concentration dependence; numerically representing spectral data for each spectral data set as a point in a multi-dimensional space, wherein peak intensity values of selected features serve as coordinates in the multi-dimensional space, and frequencies corresponding to the selected spectral features serve to define coordinate directions in the multi-dimensional space; and determining the machine learning model as a partitioning of the multi-dimensional space into two or more regions corresponding to two or more respective concentration ranges of the contaminant or impurity.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 94.0
- Lexical Diversity: 2.21212
- Patent Class: 702.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15139771', '11397927', '14631917', '13329597', '13630739']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1660862327969391
- 35 USC 102 Novelty (BERT): 0.5015077619516041
- Combined Prediction Score: 0.1996283857124056
- Mean Citation Score: 143.78900600000003
- Max Citation Score: 218.34229
- Similarity Product: 150.98335693535267

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

Dataset: test