Abstract
Wear particle characterization plays a important role in condition monitoring of machine as most of the breakdown occurs due to wear particle saturation in the lubricating oil. Traditional methods for wear debris analysis depend on human expertise to conclude the results, which are subjective in nature, time consuming, and costly. The objective of this paper is to categorize different techniques of fractal analysis to study the wear particle morphology and calculate fractal dimension of wear particles. Fractal analysis is used to give information about different features of wear particles like fractal dimension, shape, size, color, boundary representation, and surface/texture analysis. This data can be used to detect the fault and decide prognostic maintenance period.
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References
Kumar M (2013) Advancement and current status of wear debris analysis for machine condition monitoring: a review. Ind Lubr Tribol 65:3–11
Stachowiak GW (1998) Numerical characterization of wear particles morphology and angularity of particles and surfaces. Tribol Int 31:139–157
Kumar C Kumar M (2016) Wear debris analysis using ferrography. Int J Recent Trends Eng Res 2(8):398–404
Podsiadlo P, Podsiadlo GW (2000) Scale-invariant analysis of wear particle surface morphology: II. Fractal Dimension Wear 242:180–188
Raadnui S (2005) Wear particle analysis—utilization of quantitative computer image analysis: a review. Tribol Int 38(10):871–878
Kirk TB, Panzera D, Anamalay RV, Xu ZL (1995) Computer image analysis of wear debris for machine condition monitoring and fault diagnosis. Wear 181:717–722
Ghosh S, Sarkar B (2005) Wear characterization by fractal mathematics for quality improvement of machine. J Q Maintenance Eng 11(4):318–332
Lopes R, Betrouni N (2009) Fractal and multifractal analysis: a review. Med Image Anal 13:634–649
Debnath L (2006) A brief historical introduction to fractals and fractal geometry. Int J Math Educ Sci Technol 37:29–50
Kang MC, Kim JS, Kim KH (2005) Fractal dimension analysis of machined surface depending on coated tool wear. Surf Coat Technol 193(1–3):259–265
Shah H, Hirani H (2014) Online condition monitoring of spur gears. Int J Condition Monit 4:1–8
Kirk TB, Stachowiak GW, Batchelor AW (1991) Fractal Parameters and computer image analysis applied to wear particles isolated by ferrography. Wear 145:347–365
Stachowiak GW, Kirk TB, Stachowiak GB (1991) Ferrography and fractal analysis of contamination particles in unused lubricating oils. Tribol Int 6:329–334
So GB, So HR, Jin GG (2017) Enhancement of the box-counting algorithm for fractal dimension estimation. Pattern Recognit Lett 98:53–58
Li J, Du Q, Sun C (2009) An improved box-counting method for image fractal dimension estimation. Pattern Recogn 42(11):2460–2469
Gonzato G, Mulargia F, Marzocchi W (1998) Practical application of fractal analysis: problems and solutions. The Charlesworth Group 132:275–282
Hong-tao L, Shi-rong G (2009) Fishbone graph fractal description to UHMWPE wear debris boundary. Tribol Int 42(11–12):1624–1628
Shirong G, Guoan C, Xiaoyun Z (2001) Fractal characterization of wear particle accumulation in the wear process. Wear 251(1–12):1227–1233
Klinkenberg B (1994) A review of methods used to determine the fractal dimension of linear features. Math Geol 26(1):23–46
Karperien A (2004) FracLac advanced user manual. Charles Sturt University, Australia
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More, P.P., Jaybhaye, M.D. (2021). Wear Particle Analysis Using Fractal Techniques. In: Kalamkar, V., Monkova, K. (eds) Advances in Mechanical Engineering. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-3639-7_21
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DOI: https://doi.org/10.1007/978-981-15-3639-7_21
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