NDLI: Automated classification of heat resistant steel structures based on neural networks

Content Provider	IEEE Xplore Digital Library
Author	Topalova, I. Mihailov, A. Tzokev, A.
Copyright Year	2008
Description	Author affiliation: Tech. Univ.-Sofia, Sofia, Bulgaria (Topalova, I.; Mihailov, A.; Tzokev, A.)
Abstract	Gathering enough reliable information for the moment state of metal structures is needed to measure the rest life time and to assure usage without failures for devices in thermo-electric power plants. This information can be obtained by microstructure analysis of metal specimens by using plastic replicas and structural analysis. During the in-service process (high pressure and temperature) the structural and the phase composition of the steel are changed bringing different damages which can lead to complete breakdown. It is appropriate to develop methods for automated classification of steel structures aiming high recognition accuracy, reliability and lack of any subjective evaluation. The goal of the represented research is to propose a new method for automated classification of heat resistant steel structures aiming higher accuracy in comparison to other existing methods. The proposed method is based on recognition of microscope images for representative steel structures having different aging stage. In the preprocessing stage the histograms of the images are extracted and a set of reduced numbers of the cover curve values are given to the input neurons of a MLP type neural network. The achieved 100% accuracy is a good preposition to implement the method for automated calculation of the remaining capacity of the steel avoiding the subjective evaluation factor and implementing it in a real time working system.
Starting Page	437
Ending Page	440
File Size	1018368
Page Count	4
File Format	PDF
ISBN	9781424424818
DOI	10.1109/EEEI.2008.4736565
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-03
Publisher Place	Israel
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Steel Neural networks Information analysis Power measurement Time measurement Power generation Microstructure Plastics Temperature Electric breakdown supervised learning automated classification texture analysis MLP neural networks
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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