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Title: Binary classification of items of interest in a repeatable process

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.
Authors:
; ; ; ;
Publication Date:
OSTI Identifier:
1136396
Report Number(s):
8,757,469
13/632,670
DOE Contract Number:
EE0002217
Resource Type:
Patent
Research Org:
NETL (National Energy Technology Laboratory, Pittsburgh, PA, and Morgantown, WV (United States))
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING