6533b826fe1ef96bd128471f

RESEARCH PRODUCT

Evaluating creep in metals by grain boundary extraction using directional wavelets and mathematical morphology

Michel PaindavoinePierre GoutonS. JournauxG. Thauvin

subject

EngineeringMeasure (data warehouse)Materials sciencebusiness.industryMetallurgyMetals and AlloysPattern recognitionFilter (signal processing)Mathematical morphologyCondensed Matter PhysicsIndustrial and Manufacturing EngineeringComputer Science ApplicationsImage (mathematics)WaveletCreepModeling and SimulationMaterials ChemistryCeramics and CompositesGrain boundaryComputer visionExtraction (military)Artificial intelligencePhysical and Theoretical ChemistrybusinessAlgorithm

description

Abstract It is economically important for manufacturers of high-temperature machines to be able to measure creep so that they can predict residual service life more accurately. This paper describes and refines an image analysis method for evaluating creep in laboratory test pieces. It is a preliminary study of how to extract relevant information for creep measurement by cavities counting. Sample preparation for quantification by image analysis is an important step determining the further development of the image analysis technique. Grain boundary extraction, which is directional information, is the major question to be overcome before measurement can be automated. The search for a crest-line extraction filter by the Canny’s method has led to the development of a directional wavelet transform filter. The results of this innovative filtering method are applied here.

https://doi.org/10.1016/s0924-0136(01)01057-3