Froth Image Morphological Characteristic Extraction Method And Its Application For Mineral Flotation

Mineral flotation is a kind of mineral processing methods.During the process, flotation reagents are added to the pulp and air is filled in the slot. Then they are mixed to bring a great deal of air bubbles.Finally ore grade is improved by retrieving froth containing minerals to meet smelting requirements.Usually, froth is large quantity, adherence, hybrid and irregular shape. Flotation process of nonferrous metal mines in China is usually operated by experienced workers through observing froth surface. As a result, it is hard to work in optimized running state and mineral recovery ratio is low. Consequently, researching the morphological characteristics extract method for froth images and applying them into practice are great significance for optimizing flotation process, maximum using resource, reducing resource consume and maintaining enterprise sustainable development.According the adhesion principle of air bubbles and mineral particles, relationship between froth morphological characteristics and flotation operating condition is researched in this paper based on flotation mechanism. Then froth image characteristics extraction scheme based on machine vision is proposed and applied in online monitoring system of mineral flotation process successfully. Main research work and innovative achievements are as follows:(1)Considering the limitation that manual selecting structural element in image segmentation, adaptive selection method for structural element was proposed in this paper based on geometric pattern spectra. Improved fuzzy C-means for image clustering and area reconstruction by open and close operation for de-noise were used to provide prior knowledge for image segmentation.To solve structure elements automatically, morphological geometric pattern spectrum was introduced for binary image. The non-increasing is proved on condition that arbitrary shape operator. In order to extend the characteristic to gray image, a max tree principle is utilized to prune the image. Thus, the proposed algorithm can compute the size and shape pattern spectra value efficiently. This method utilizes the bubble lighting spot information adequately, and provides image segmentation with the structural element. Consequently, it ensured the accuracy of image segmentation, and decreased manual experience to a great extent.(2) Aiming at the structural element optimization problem in morphological processing, a novel structural element optimization method based on particle swarm optimization(PSO) algorithm. On the basis of geometrical pattern spectra objection function, the global mixmization value is obtained by serially changing the size and shape of structural element, which not only avoid local optimum problem, but also ensure the real time property of the proposed algorithm.(3)Considering the problem of the asymmetrical size and irregular shape of bubbles in process of image segmentation, froth image adaptive segmentation based on hierarchical watershed algorithm was presented. On the basis of selection of optimal structure element, coarse segmentation was done by using watershed algorithm. Then texture features of the segmentation regions were extracted by fuzzy texture spectrum. Besides, fine-grained segmentation for under-segmentation vesicle regions was preceded through support vector machines for region recognition. At the same time, image region merging mechanism was introduced to merge the big bubble regions which were over-segmentation. Finally the result of segmentation was evaluated. The cooperation process mechanism combines image segmentation, feature extraction and image recognition. Thus, it enhanced the robustness of algorithm, and avoided the effection of all kinds of segmentation caused by hybrid bubble, and decreased under-segmentation and over-segmentation region.(4) A method for morphological characteristics extraction of froth image was presented. On the basis of image segmentation, pixels in bubble segmentation region were calibrated. At the meantime, concept of sample distribution statistics was introduced. Moreover, some statistical characteristics, such as the average size of bubbles, variance, skewness and abruptness were extracted. The bubble shapes were described from qualitative and quantitative view separately in order to extract bubble shape features. Morphological signature transformation and multi-structural elements were also used for extract bubble morphological characteristics.The feature extraction problem of complex shape is transform into extraction simple shape feature from several signature shapes, which simplify the shaple description method. The experimental results show that the morphological characteristics extracted in this paper have strong practicability.(5)For an acctural mineral flotation process, a hardware platform was designed to obtain froth images and mineral flotation froth video monitoring system was developed. On the basis of this, correlation analysis of froth morphological characteristics and production index was proposed. Sensitivity analysis of the extracted features was researched firstly. Then correlation analysis of forth morphological characteristics and rate of ore recovery was studied. As a result, prediction model of process indexes was established by using least square support vector machines.For the sake of real-timing of algorithm, the model is proceeded with sparse. Because of the using of this method for industrial flotation, real time monitoring of flotation process was realized. The system can give operating mode information and operation suggestion to the worker. Furthermore, labor productivity is increased and operation aimlessness is avoided, which provided the foundation for optimal control of flotation process.