From Individual Graphite Assignment to an Improved Digital Image Analysis of Ductile Iron

被引:8
|
作者
Friess, J. [1 ]
Buehrig-Polaczek, A. [1 ]
Sonntag, U. [2 ]
Steller, I [3 ]
机构
[1] Rhein Westfal TH Aachen, Foundry Inst, Aachen, Germany
[2] GFaI Soc Adv Appl Comp Sci, Berlin, Germany
[3] BDG German Foundry Assoc, Dusseldorf, Germany
关键词
graphite morphology; graphite classification; nodularity; image analysis; ductile iron; spheroidal graphite cast iron; CAST-IRON;
D O I
10.1007/s40962-020-00416-3
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
Since graphite classification by visual analysis exhibits large variations, a more integrative concept of graphite shape classification is required to evaluate the correlations of process, microstructure and properties, and to fulfill customers' requirements. The automatic digital image analysis is partly based on visual analysis, but it is not thoroughly defined for graphite shape classification. For example, nodules and thereby nodularity are only defined by the shape parameter roundness, although several studies suggest more sophisticated approaches. Within the first of three successive round robin tests, visual assignment for a variety of graphite particles was performed to obtain a universal digital data set of classified graphite particles. For this, the classification approach from standard EN ISO 945-1 was used and extended with degenerated graphite. The assigned particles were evaluated concerning different shape parameters showing that roundness and the assigned minimum limit value of 0.6 are not sufficient to distinguish nodules from less ideal graphite particle shapes. Furthermore, the current classification approach does not represent the full spectrum of graphite morphologies and needs to be extended. The development of a universal hierarchical classification method for nodules and other graphite shapes has been initiated, and the results will contribute to an improved image analysis standard for ductile iron, particularly ISO 945-4.
引用
收藏
页码:1090 / 1104
页数:15
相关论文
共 50 条
  • [41] A Digital Image Analysis Technique for Improved Strain Measurement in Geosynthetic Tensile Testing
    Poggiogalle, Tyler M.
    Meehan, Christopher L.
    Clarke-Sather, Abigail R.
    Talebi, Majid
    GEOTECHNICAL TESTING JOURNAL, 2022, 45 (03): : 513 - 529
  • [42] Improved automated digital retinal image analysis for detection of diabetic retinopathy through image quality restoration
    Soliz, P
    Raman, B
    Nemeth, S
    Barriga, S
    Zamora, G
    Bursell, E
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2005, 46
  • [43] Correction: Statistical Comparisons & Correlations of Thermal Analysis, Ultrasonic Velocity and Image Analysis Metallography Methods for Quantification of Ductile Iron Microstructure
    James Cree
    Adam Hoover
    International Journal of Metalcasting, 2023, 17 : 3167 - 3167
  • [44] Generation of Conspicuity-improved Synthetic Image from Digital Breast Tomosynthesis
    Kim, Seong Tae
    Kim, Dae Hoe
    Ro, Yong Man
    2014 19TH INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2014, : 395 - 399
  • [45] Computer simulation of electrical conductivity of graphite-based polypropylene composites based on digital image analysis
    Dweiri, Radwan
    Sahari, Jaafar
    JOURNAL OF MATERIALS SCIENCE, 2007, 42 (24) : 10098 - 10102
  • [46] Speciation analysis based on digital image colorimetry: Iron (II/III) in white wine
    Santos Neto, Joao H.
    Porto, Icaro S. A.
    Schneider, Mateus P.
    dos Santos, Ana M. P.
    Gomes, Adriano A.
    Ferreira, Sergio L. C.
    TALANTA, 2019, 194 : 86 - 89
  • [47] Computer simulation of electrical conductivity of graphite-based polypropylene composites based on digital image analysis
    Radwan Dweiri
    Jaafar Sahari
    Journal of Materials Science, 2007, 42 : 10098 - 10102
  • [48] Thermal Parameter Optimization for Enhanced Graphite Nodular Properties in Ductile Cast Iron: A Comprehensive Analysis of Cooling Rates and Its Effect on Microstructure
    Kumar, Prabhakar
    Gosvami, Nitya Nand
    Jain, Jayant
    Vikrant, K. S. N.
    METALLOGRAPHY MICROSTRUCTURE AND ANALYSIS, 2024, 13 (05) : 832 - 838
  • [49] An improved panoramic digital image correlation method for vascular strain analysis and material characterization
    Genovese, K.
    Lee, Y-U.
    Lee, A. Y.
    Humphrey, J. D.
    JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS, 2013, 27 : 132 - 142
  • [50] Individual participant data from digital sources informed and improved precision in the evaluation of predictive biomarkers in Bayesian network meta-analysis
    Umemneku-Chikere, Chinyereugo M.
    Wheaton, Lorna
    Poad, Heather
    Ray, Devleena
    Andrade, Ilse Cuevas
    Khan, Sam
    Tappenden, Paul
    Abrams, Keith R.
    Owen, Rhiannon K.
    Bujkiewicz, Sylwia
    JOURNAL OF CLINICAL EPIDEMIOLOGY, 2023, 164 : 96 - 103