PATENT CLAIM ANALYSIS

Application Number: 15916943
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["714", "026000"]

Abstract:
Systems and methods for detecting an anomaly in a power semiconductor device are disclosed. A system includes a server computing device and one or more local components communicatively coupled to the server computing device. Each local component includes sensors positioned adjacent to the power semiconductor device for sensing properties thereof Each local component receives data corresponding to one or more sensed properties of the power semiconductor device from the sensors and transmits the data to the server computing device. The server computing device utilizes the data, via a machine learning algorithm, to generate a set of eigenvalues and associated eigenvectors and select a selected set of eigenvalues and associated eigenvectors. Each local component conducts a statistical analysis of the selected set of eigenvalues and associated eigenvectors to determine that the data is indicative of the anomaly.

Claim (Index 17):
A method of detecting an anomaly in a power semiconductor device, the method comprising:\n receiving, by a processing device, sensed data from one or more sensors positioned adjacent to the power semiconductor device, wherein the sensed data corresponds to one or more sensed properties of the power semiconductor device; transmitting, by the processing device, the sensed data to a server computing device that is remotely located from the processing device; receiving, by the processing device, processed data from the server computing device, wherein the processed data comprises information generated as a result of an application of one or more of a machine learning algorithm, a fault diagnostic algorithm, and a fault prognostic algorithm to the sensed data; and statistically analyzing, by the processing device, the processed data to determine whether the sensed data is indicative of the anomaly.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 90.0
- Lexical Diversity: 2.2
- Patent Class: 714.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15408092', '15569222', '14537839', '14536477', '12577913']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2693229369011028
- 35 USC 102 Novelty (BERT): 0.469204650184257
- Combined Prediction Score: 0.2893111082294182
- Mean Citation Score: 143.56622199999995
- Max Citation Score: 149.083
- Similarity Product: 104.52649755275247

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