Binary classification of items of interest in a repeatable process
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.
- Research Organization:
- GM Global Technology Operations LLC, Detroit, MI (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- EE0002217
- Assignee:
- GM Global Technology Operations LLC (Detroit, MI)
- Patent Number(s):
- 8,925,791
- Application Number:
- 14/264,113
- OSTI ID:
- 1167030
- Resource Relation:
- Patent File Date: 2014 Apr 29
- Country of Publication:
- United States
- Language:
- English
Method And System For Online Quality Monitoring And Control Of A Vibration Welding Process
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patent-application | May 2011 |
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