Analysis of the Acoustic Emission Spectra of Particle Breakage in a Laboratory Cone Crusher

Crushing and grinding ore consumes so much energy that it represents a major component of total processing costs. While it has been estimated that only about 0.6% of the total energy expended in grinding is actually used to create new surfaces, accurate measurement of this quantity is difficult. If energy expended in crushing and grinding could be more directly measured, alternatives for increasing efficiency of the processes could be evaluated more effectively. Since the energy intensity associated with rock fracture is related to fracture sonority, it should be possible to use this sound (acoustic emission) to measure the actual energy expended. However, it is difficult to apply this approach because the mill environment is so noisy. To make the approach practical, a method for differentiating acoustic emissions caused by rock fracture from those caused by extraneous noises must be found. Pattern recognition analysis may provide such a method. This paper presents the results of pattern recognition analysis to make two types of differentiations: acoustic emissions caused by crushing two types of minerals (quartz and chrysocolla) and those caused by two extraneous noise sources, and acoustic emissions produced by each mineral.