Bubble Velocity Measurement And Size Distribution Estimation For Mineral Flotation Process

Mineral flotation is a complex physical and chemical process involving three phases such as solid, liquid and air. It is a multivariate process influenced by many factors including physical variables like solid particles in macro level and chemical variables like reagent or dynamic fluid kinetic factors in micro level, and additional coupling effect among the variables can complicate the decisive reasons for flotation performance change. From the perspective of flotation mechanism, froth visual features can characterize the combining effect of multiple operating conditions on flotation, which is the indicator of flotation separation performance. The bottleneck of flotation optimization lies in guaranteeing accurate flotation froth features description, relation between image features and operational variables, flotation performances optimization based operation condition strategies. All these unsolved problems will be discussed and explored in this thesis.Based on froth flotation mechanism analysis and the relationship between froth visual features and operation conditions, surface bubble motion velocity measurement and bubble size distribution estimation algorithms are proposed. With the online feature data and operation conditions from the developed froth image feature monitoring system, relation on froth visual features, operational variables and flotation performances is established and applied on froth flotation industry. Main research work and innovative achievements are as follows:(1) To describe foam flow within a flotation cell which has inherent properties like opacity and invisibility, a Laplace base bubble motion model is established from kinetic analysis. With the assumption of incompressible and irrotational flow, boundary conditions are given for the established model. It can provide visual output of the bubble velocity distribution which is one of the important dynamic features in froth layer, and the trend of streamline within reveals flow pattern of adjacent bubbles which proves the bubble shape distorts with the density of streamline. The Laplace model based bubble motion velocity distribution can theoretically point out rational position in a flotation cell to measure the flow velocity of bubble in surface layer.(2) Considering the characteristics of complex surface bubble flow and its demand of real-time velocity feature extraction in flotation industry, a direction-oriented fast hexagon search based block matching velocity measurement algorithm is proposed. Since the traditional centroid tracking based algorithm fitting for 2D foam velocity measurement is no longer applicable in complex 3D industry froth images, the proposed algorithm suits the real-time extraction of velocity measurement with the approval of its accuracy from experimental results of two target blocks at same horizontal position but different height. Given the right position to measure the velocity and the froth depth over the lip, various experiments carried out shown that air recovery calculated from velocity feature appeared a peak with the increase of inlet gas velocity. When operating in condition of peak air recovery, the opportunity of optimal flotation performances increases consequently.(3) For froth images has an unpleasant property of no void background for conventional segmenting algorithms, two effective froth segmentation algorithms are explored based on the features of froth images to overcome the limitation of traditional methods such as segmenting instability of white spot effect, including improved morphological reconstruction watershed segmentation method and valley edge detection based segmentation method. The post-segmentation analysis has shown the fact that probability density distribution (PDF) of bubble size is non-Gaussian. Unlike traditional method applying singular feature such as mean or variance with the assumption that the distribution is normal, probability density distribution is suggested to accurately describe statistical feature of froth structure. The fact that the mathematical model of distribution is unknown makes nonparametric estimation method fitting to depict the unknown continuous process of froth flotation. Considering that the bubble size distribution is highly skewed with long tails, nonparametric descriptor is designed to reflect the variety of the curve.(4) In order to establish the relationship between bubble size distribution and reagents addition, a fault detection and diagnosis scheme using nonparametric estimation based dynamic weights model is proposed. The designed nonparametric estimation is applied so that the output PDF is formulated in terms of dynamic weights, by which a non-linear model with time delay is established. Effective fault detection and diagnosis is achieved by using linear matrix inequation method. The reagent fault is successfully detected and diagnosed on the industrial data of off-line froth images.(5) Taking certain alumina industry froth flotation as a research case, a froth visual feature extraction system is developed. Operational conditions with corresponding bubble velocity and size features based grade recovery model is proposed. By manipulating the cell operating condition such as chemical reagent addition or inlet air flowrate, the on-line monitoring of froth visual features can reflect the changes, and consequently the circuit performance can shift among the coordinates on the grade recovery curve to achieve optimal trade-off between grade and mineral recovery. The metallurgical results clearly indicate that changes in air rate or reagent addition result in the variation of flotation performance, which laid the foundation for implementation of real-time process optimization.