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Binary classification of items of interest in a repeatable process

United States Patent

June 24, 2014
View the Complete Patent at the US Patent & Trademark Office
A system includes host and learning machines in electrical communication with sensors positioned with respect to an item of interest, e.g., a weld, and memory. The host executes instructions from memory to predict a binary quality status of the item. The learning machine receives signals from the sensor(s), identifies candidate features, and extracts features from the candidates that are more predictive of the binary quality status relative to other candidate features. The learning machine maps the extracted features to a dimensional space that includes most of the items from a passing binary class and excludes all or most of the items from a failing binary class. The host also compares the received signals for a subsequent item of interest to the dimensional space to thereby predict, in real time, the binary quality status of the 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)
13/ 632,670
October 1, 2012
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.