SmartMetals: a new method for metal identification based on fuzzy logic
Abstract
This paper presents a method of searching, identifying and cross-referencing metal alloys based on their chemical composition and/or mechanical properties, typically obtained by analysis and tests. The method uses a general pattern similar to the approach of a human expert, and relies on a classification of metals based on metallurgical expertise and fuzzy logic for identifying metals and comparing their chemical and mechanical properties. The algorithm has been tested and deployed in real applications for fast metal identification and finding of unknown equivalents, by the leading companies in the field. The same principles can also be used in other domains for similar problems, such as organic and inorganic materials identification and generic drugs comparison. Copyright (C) 2009 John Wiley & Sons, Ltd.
Keywords:
metal identification / metal composition / metal properties / spectrometrySource:
Journal of Chemometrics, 2009, 23, 11-12, 555-561Publisher:
- John Wiley & Sons Ltd, Chichester
DOI: 10.1002/cem.1251
ISSN: 0886-9383
WoS: 000273586400001
Scopus: 2-s2.0-70450177947
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Institution/Community
FBTY - JOUR AU - Pocajt, Viktor AU - Ševarac, Zoran AU - Kovačević, Ana PY - 2009 UR - https://rhinosec.fb.bg.ac.rs/handle/123456789/38 AB - This paper presents a method of searching, identifying and cross-referencing metal alloys based on their chemical composition and/or mechanical properties, typically obtained by analysis and tests. The method uses a general pattern similar to the approach of a human expert, and relies on a classification of metals based on metallurgical expertise and fuzzy logic for identifying metals and comparing their chemical and mechanical properties. The algorithm has been tested and deployed in real applications for fast metal identification and finding of unknown equivalents, by the leading companies in the field. The same principles can also be used in other domains for similar problems, such as organic and inorganic materials identification and generic drugs comparison. Copyright (C) 2009 John Wiley & Sons, Ltd. PB - John Wiley & Sons Ltd, Chichester T2 - Journal of Chemometrics T1 - SmartMetals: a new method for metal identification based on fuzzy logic VL - 23 IS - 11-12 SP - 555 EP - 561 DO - 10.1002/cem.1251 UR - conv_392 ER -
@article{ author = "Pocajt, Viktor and Ševarac, Zoran and Kovačević, Ana", year = "2009", abstract = "This paper presents a method of searching, identifying and cross-referencing metal alloys based on their chemical composition and/or mechanical properties, typically obtained by analysis and tests. The method uses a general pattern similar to the approach of a human expert, and relies on a classification of metals based on metallurgical expertise and fuzzy logic for identifying metals and comparing their chemical and mechanical properties. The algorithm has been tested and deployed in real applications for fast metal identification and finding of unknown equivalents, by the leading companies in the field. The same principles can also be used in other domains for similar problems, such as organic and inorganic materials identification and generic drugs comparison. Copyright (C) 2009 John Wiley & Sons, Ltd.", publisher = "John Wiley & Sons Ltd, Chichester", journal = "Journal of Chemometrics", title = "SmartMetals: a new method for metal identification based on fuzzy logic", volume = "23", number = "11-12", pages = "555-561", doi = "10.1002/cem.1251", url = "conv_392" }
Pocajt, V., Ševarac, Z.,& Kovačević, A.. (2009). SmartMetals: a new method for metal identification based on fuzzy logic. in Journal of Chemometrics John Wiley & Sons Ltd, Chichester., 23(11-12), 555-561. https://doi.org/10.1002/cem.1251 conv_392
Pocajt V, Ševarac Z, Kovačević A. SmartMetals: a new method for metal identification based on fuzzy logic. in Journal of Chemometrics. 2009;23(11-12):555-561. doi:10.1002/cem.1251 conv_392 .
Pocajt, Viktor, Ševarac, Zoran, Kovačević, Ana, "SmartMetals: a new method for metal identification based on fuzzy logic" in Journal of Chemometrics, 23, no. 11-12 (2009):555-561, https://doi.org/10.1002/cem.1251 ., conv_392 .