Fractal Differentiation Between Wear and Contaminant Particles found in mining machinery lubrication systems

Abstract This paper describes preliminary work carried out on the applicability of fractal geometry for differentiating between wear and contaminant particles found in mining machinery lubrication systems. Coal dust, stone dust and roadstone dust from a granite quarry were used as the contaminant particles and the particles from two crushers, which had failed whilst in service, were used to provide the wear particles. Two differing populations appeared with the wear particles having higher boundary fractals than the contaminant, but tending to spread across a wide range of fractal numbers, whereas the contaminants were lower and fairly tightly grouped. The underfractal distributions of the two populations of particles, generate straight lines when plotted on Gaussian probability paper. This leads to the probability of being able to predict the distribution of particles, in fractal terms between wear and contaminant particles.