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Journal
2015 | 60 | 3 | 633-636
Article title

Industrial diagnostics system using gamma radiation

Content
Title variants
Languages of publication
EN
Abstracts
EN
During the operation of large industrial installations, a very important task is to maintain the proper technical state. In the event of an emergency, it is vital to locate the place of occurrence as soon as possible. In solving this type of problem, it often helps to apply the methods of measurement associated with ionizing radiation. One of these methods is the gamma scanning. The purpose of this type of measurement is the detection and localization of disturbance of technological processes which may result in incorrect decomposition the fl owing medium and workpiece (sediments, congestion) as well as damage to the internal constructions. A particularly: (i) preventive diagnosis - early detection of installation failure; (ii) rationalization of repairs and renovations - to determine the need to take or not to take remedial action; (iii) quick and precise installation inspections - to gain knowledge of the technical condition and technological installations; (iv) indication of worn parts and posing a threat - diagnostics of the technical condition installation; (v) forecasting the useful lifetime of equipment.
Publisher
Journal
Year
Volume
60
Issue
3
Pages
633-636
Physical description
Dates
published
1 - 9 - 2015
accepted
20 - 5 - 2015
online
25 - 9 - 2015
received
29 - 9 - 2014
References
  • 1. Mihułek, M. (Ed.). (2003). Charakterystyka technologiczna rafi nerii ropy i gazu w Unii Europejskiej. Warsaw: Ministerstwo Środowiska.
  • 2. Rada do Spraw Atomistyki. (2006). Strategia rozwoju atomistyki w Polsce. Warsaw: Państwowa Agencja Atomistyki.
  • 3. Machaj, B., Jakowiuk, A., Świstowski, E., & Palige, J. (2011). Operation manual of Gamma Scanner. Warsaw: Institute of Nuclear Chemistry and Technology.
  • 4. Krzanowski, W. J. (2000). Principles of multivariate analysis: A user’s perspective. Oxford University Press.
  • 5. Rencher, A. C. (1997). Multivariate statistical inference and applications. Department of Statistics, Brigham Young University.
  • 6. Kak, A. C., & Slaney, M. (1988). Principles of computerized tomographic imaging. New York: The Institute of Electrical and Electronics Engineers, Inc.
Document Type
Publication order reference
YADDA identifier
bwmeta1.element.-psjd-doi-10_1515_nuka-2015-0094
Identifiers
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