Abstract
The pre-treatment of ore particles by high voltage pulses (HVP) at low specific energy has a potential to reduce the energy consumption and operation costs. Nevertheless, the influencing factors and the behavior of HVP breakage of ore particles have not yet been fully understood. The overall objective of this thesis is to study the applications and modelling of HVP breakage by understanding the behaviour of ore particles subjected to pulse discharge. The three areas investigated are: 1) The effects of mineral properties on HVP selective breakage and the application of this selective breakage in ore pre-concentration. 2) The methods to evaluate and to characterize HVP breakage results. 3) Modelling ore particle behavior in HVP breakage. In this project, the selectivity of HVP breakage is studied using synthetic samples made of construction grout and pyrite grains. The result confirms that the breakage response of particles is dominated by the locality of electrical breakdown channel. The electrical breakdown channel locality is controlled by the grains of minerals with high conductivity/permittivity and their location in a particle. This understanding has led to the discovery of a novel technique for ore pre-concentration using high voltage electrical pulses. The technique utilises metalliferous grain-induced selective breakage, under a controlled pulse energy loading, and size-based screening to separate the feed ore into two products for splitting of ores by grade. To evaluate HVP breakage results, a t10-based model was developed to predict the degree of impact breakage, t10, of pulse-treated particles from that of untreated particles. This model incorporates only one parameter, CAb, which is equivalent to percentage change of A×b values. The t10-based model can be used to assess energy reduction due to the pre-weakening effect in the downstream mechanical comminution process. A Wide–size JKRBT characterisation method was created, initially for quick determination of breakage characteristics of the HVP product; ultimately for use as an express ore breakage characterisation method. In this method, particles in wide size range are tested as one size class in the JKRBT by single–particle breakage mode, significantly simplifying the feed particles preparing and product sizing procedures. A conceptual design of an on–line ore competence measuring system based on this principle is proposed. Both the t10-based model and the Wide-size JKRBT method utilise a size-dependent breakage model previously developed by the JKMRC. Behaviour of ore particles in HVP breakage was investigated with a pilot scale and a laboratory scale HVP breakage devices. The effects of specific energy, pulse voltage, cumulative discharges, feed particle size and ore particle breakage pattern (body breakage or surface breakage) were investigated. Based on the data, a model structure for HVP breakage was developed, which incorporates four sub-models using the similar structure to predict four HVP breakage indices: body breakage probability, body breakage product fineness, pre-weakening degree and metal recovery. A set of tn-family of curves were established to estimate the HVP product size distribution from the HVP model predicted breakage indices. In summary, this PhD study has delivered the following major outcomes: • A novel HVP ore pre-concentration method, which has a potential for the mining industry in making step-change improvements in energy efficiency, environment impact and operation costs. • A t10-based model to evaluate HVP breakage result. This method can also be applied for comparison of ore competence change, regardless of the breakage methods causing this competence change, as long as the benchmark ore breakage characteristic parameters are available. • A Wide-size JKRBT characterisation method, which significantly simplifies the traditional ore impact characterisation methods. • A set of HVP breakage models, which can be used for simulations of a hybrid circuit combining mechanical comminution and electrical comminution. • 13 papers generated during the course of this PhD study, being the first-named author for seven of them.
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