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

Abstract

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.