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Binary classification of items of interest in a repeatable process

United States Patent

January 6, 2015
View the Complete Patent at the US Patent & Trademark Office
A system includes host and learning machines. Each machine has a processor in electrical communication with at least one sensor. Instructions for predicting a binary quality status of an item of interest during a repeatable process are recorded in memory. The binary quality status includes passing and failing binary classes. The learning machine receives signals from the at least one sensor and identifies candidate features. Features are extracted from the candidate features, each more predictive of the binary quality status. The extracted features are mapped to a dimensional space having a number of dimensions proportional to the number of extracted features. The dimensional space includes most of the passing class and excludes at least 90 percent of the failing class. Received signals are compared to the boundaries of the recorded dimensional space to predict, in real time, the binary quality status of a subsequent item of interest.
Abell; Jeffrey A (Rochester Hills, MI), Spicer; John Patrick (Plymouth, MI), Wincek; Michael Anthony (Rochester, MI), Wang; Hui (Highland, MI), Chakraborty; Debejyo (Sterling Heights, MI)
GM Global Technology Operations LLC (Detroit, MI)
14/ 264,113
April 29, 2014
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT This invention was made with U.S. Government support under an Agreement/Project DE-EE0002217, Department of Energy Recovery and Reinvestment Act of 2009, Battery Pack Manufacturing B511. The U.S. government may have certain rights in this invention.