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A Digital Image Processing Tool for size and number density distribution of precipitates in creep exposed material

IR@NML: CSIR-National Metallurgical Laboratory, Jamshedpur

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Title A Digital Image Processing Tool for size and number density distribution of precipitates in creep exposed material
 
Creator Sahu, Minati Kumari
Dutta, Chandan
Ghosh, Arpita
Palit Sagar, S
 
Subject Materials Charcterization
 
Description Present paper deals with developing an advanced digital image processing tool for determination of size and number density of precipitates present in creep exposed P92 steel. The image processing tool box in MATLAB is usually employed for noise detection and removal, edge detection, cropping, histogram of region of interest as well as size wise distribution of the desired objects from the micrograph. This tool helps in fast and accurate acquisition of information. In this investigation, creep testing has been carried out on two P92 steel specimens at temperature of 650C and stress of 120MPa till rupture. Scanning electron microscopy was used to capture images of the specimen in as-tempered condition and in the near rupture gage region after creep rupture. The developed software has been used to analyze the micrographs for quantification of precipitates in terms of area fraction, size and number density. The use of edge detection technique in the developed software helps in avoiding human intervention during image thresholding thereby increasing accuracy in precipitate sizing. Findings from this investigation have been used to evaluate the role of precipitation morphology for specimen failure due to creep especially in precipitate strengthened steel like P92 steel.
 
Publisher Springer
 
Date 2019
 
Type Book or NML Publication
PeerReviewed
 
Format application/pdf
 
Identifier http://eprints.nmlindia.org/7882/1/sahu2018.pdf
Sahu, Minati Kumari and Dutta, Chandan and Ghosh, Arpita and Palit Sagar, S (2019) A Digital Image Processing Tool for size and number density distribution of precipitates in creep exposed material. In: Soft computing for problem solving. Springer, 2019, pp. 653-659. ISBN 978-981-13-1592-3
 
Relation https://link.springer.com/chapter/10.1007/978-981-13-1592-3_51
http://eprints.nmlindia.org/7882/