RodrÃguez-MartÃn et al., 2020 - Google Patents
Predictive models for the characterization of internal defects in additive materials from active thermography sequences supported by machine learning methodsRodrÃguez-MartÃn et al., 2020
View HTML- Document ID
- 7537726183250783516
- Author
- RodrÃguez-MartÃn M
- Fueyo J
- Gonzalez-Aguilera D
- Madruga F
- GarcÃa-MartÃn R
- Muñóz Ã
- Pisonero J
- Publication year
- Publication venue
- Sensors
External Links
Snippet
The present article addresses a generation of predictive models that assesses the thickness and length of internal defects in additive manufacturing materials. These modes use data from the application of active transient thermography numerical simulation. In this manner …
- 239000000463 material 0 title abstract description 41
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- G06Q10/063—Operations research or analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06—COMPUTING; CALCULATING; COUNTING
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- G06Q10/00—Administration; Management
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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