scholarly journals Determination of surface moisture and particle size distribution of coal using online image processing

2020 ◽  
Vol 56 (1) ◽  
pp. 37-46
Author(s):  
P. Choudhary ◽  
T. Maloo ◽  
H. Parida ◽  
P. Khatri ◽  
B. Deo ◽  
...  

Production of sponge iron requires iron ore, coal, and dolomite. The quality of sponge iron is affected by particle size variation and moisture content of the feed materials. In the present work, image processing was used to detect both particle size and moisture variation of the feed materials on an online basis. Noise and signal irregularities in images were removed by image analysis through MATLAB. Continuous (online, every 30 minutes) images were taken over a coal bed which was moving on a conveyor belt. It was a challenge to determine the particle size distribution and surface moisture of coal online. The distribution of reflectivity of coal in the image varied according to the moisture content and particle size. It affected the intensity information of the image which was then used to predict the surface moisture content of the coal. The method is now being used successfully in a processing plant.

2015 ◽  
Vol 770 ◽  
pp. 512-517 ◽  
Author(s):  
O.V. Tailakov ◽  
M.P. Makeev ◽  
A.N. Kormin ◽  
A.I. Smyslov

Therein algorithms of application of digital models for evaluation of porosity and fractional composition of coals based on analysis of their optical images are offered. The models allow allocating significant informational objects and estimation of structural and filtration properties of coals. The results of algorithms application on recognition of the optical images of coals are presented, the particle size distribution of coal charge and porosity of coal is defined.


2021 ◽  
Author(s):  
Alexandra Escobar ◽  
Jorge Relvas ◽  
Alvaro Pinto ◽  
Mafalda Oliveira

<p>Neves Corvo is an underground high-grade Cu-(Sn)-Zn mine, currently producing copper, zinc and lead concentrates. Copper production started in 1989, followed by tin production, between 1990 and 2001, and zinc / lead production started in 2006. The operation is owned by SOMINCOR, a subsidiary of Lundin Mining, with a maximum capacity of 2.6Mtpy for the copper processing plant and 1.0Mtpy (ongoing expansion to 5.6Mtpy) for the zinc processing plant.</p><p>The Neves Corvo VMS deposit is located in the Portuguese part of the world-class Iberian Pyrite Belt (IPB) and is composed of seven orebodies. The Neves, Corvo, Zambujal and Lombador orebodies are currently in production, whereas the Semblana and Monte Branco orebodies are relatively recent discoveries still under development and evaluation, and the Graça orebody has been already fully mined.</p><p>From 2010 till end of 2019, the mine has accumulated 7.3Mt of waste rock and 17Mt of thickened tailings. These mining residues are stored in Cerro do Lobo Tailings Management Facility (Cerro do Lobo TMF), which completes a volume of 47Mt since the beginning of the operation in 1989 (30Mt are slurry tailings).</p><p>The deposition method changed in 2010 from slurry subaquatic deposition to sub-aerial thickened tailings stack (vertical expansion) in co-deposition with potentially acid-generating (PAG) waste rock. The thickened tailings have an average of 63% solids. X-ray fluorescence analysis have shown copper and zinc grades variation in the waste rock between 0.3 and 0.9%, and 0.4% and 1.1%, respectively, and concentrations up to 0.3% and 0.4% of copper and zinc, respectively, in the tailings.</p><p>Mineralogically, the tailings consist mainly in pyrite, sphalerite, chalcopyrite, +/- arsenopyrite, +/- tetrahedrite-tennantite, gangue minerals such as quartz, phyllosilicates, carbonates and some oxides, and have a non-uniform particle size distribution ranging between 1 and 100 µm. The waste rock fraction is millimetric to centimetric in size, and is formed by the local host rocks, which include acid volcanic rocks, schists and graywackes, all of them containing variably significant disseminated sulfides, largely dominated by pyrite.</p><p>On-going research is being undertaken aiming to build a geometallurgical model for the Neves Corvo mine, ground on a huge database on the chemical and mineralogical composition, and particle size distribution of the mine tailings, coupled with (and calibrated by) new analytical and automated data acquired in a large set of carefully selected representative samples, in order to assess the potential recovery of base metals and their by-products out of these potentially valuable mine residues. The model construction and consequent resource estimation will be based on the daily monitoring of the tailings deposition at the disposal units, over the past 10 years (i.e., since the subaerial deposition has started at Neves Corvo), in terms of volume/tonnage, chemical and mineralogical compositions and physical characterization of the material.</p><p>This study is part of the work package 1 (WP1) of ETN–SULTAN project (H2020) - European Training Network for the remediation and reprocessing of sulfidic mining waste sites. Publication supported by FCT- Project UID/GEO/50019/2019 - Instituto Dom Luiz.</p>


2020 ◽  
Vol 80 (1) ◽  
pp. 611-625 ◽  
Author(s):  
Zhengyang Sun ◽  
Zhiyong Yang ◽  
Yusheng Jiang ◽  
Hongji Gao ◽  
Kuanda Fang ◽  
...  

2013 ◽  
Vol 788 ◽  
pp. 627-630
Author(s):  
Jian Shu Hou

The particle size distribution of soil is very importantto its physical and mechanical property. The ordinary method of the particlesize distribution analysis is based on shaking the soil through a set of sieves.But it will be difficult to use the method while there have particles largerthan the biggest aperture of the size sieves. Then the digital image processingwas used to solve the problem here. The processing technologies, such as imageanalysis and enhancement, deblurring, edge detection were studied to analyzethe image of soil particles. Then the image processing method was used to getthe particle size distribution accurately. Though some promotions need to becarried out in the further study, it is can be found that the image processingmethod is more efficiently than the traditional method.


Author(s):  
I. L. Whyte

AbstractThe origins and development of the U100 (U4) thick-walled open-drive sampler are reviewed. The requirements of CP 2001 and BS 5930 are examined in relation to sample quality, and these are shown to be too favourable. Causes of sample disturbance are considered, particularly those due to volume changes, and shown to depend on moisture content, plasticity and particle size distribution. Quality classes possible with conventional U100 samples are suggested, and Classes 3 or 4 are to be generally expected. Class 1 samples are improbable. It is recommended that a general purpose sampler such as the U100 should have a maximum inside clearance of 1% and not ‘about 1%’ as recommended in BS 5930.


1994 ◽  
Vol 74 (2) ◽  
pp. 383-385 ◽  
Author(s):  
R. Soofi-Siawash ◽  
G. W. Mathison

Two studies were conducted to assess the possibility of using particle size distribution following grinding as a routine procedure of forage evaluation. It was concluded that although differences in particle size distribution could be detected when different feeds were ground, it would be difficult to standardize the technique since particle size distributions were influenced by type of mill used for grinding, particle size of forage before grinding, and moisture content of the forage. Key words: Forages, grinding, particle size, moisture, mill


2015 ◽  
Vol 25 (6) ◽  
pp. 774-784 ◽  
Author(s):  
Nikolaos Ntoulas ◽  
Panayiotis A. Nektarios ◽  
Thomais-Evelina Kapsali ◽  
Maria-Pinelopi Kaltsidi ◽  
Liebao Han ◽  
...  

Several locally available materials were tested to create an optimized growth substrate for arid and semiarid Mediterranean extensive green roofs. The study involved a four-step screening procedure. At the first step, 10 different materials were tested including pumice (Pum), crushed tiles grade 1–2 mm (T1–2), 2–4 mm (T2–4), 5–8 mm (T5–8), 5–16 mm (T5–16), and 4–22 mm (T4–22); crushed bricks of either 2–4 mm (B2–4) or 2–8 mm (B2–8); a thermally treated clay (TC); and zeolite (Zeo). All materials were tested for their particle size distribution, pH, and electrical conductivity (EC). The results were compared for compliance with existing guidelines for extensive green roof construction. From the first step, the most promising materials were shown to include Pum, Zeo, T5–8, T5–16, and TC, which were then used at the second stage to develop mixtures between them. Tests at the second stage included particle size distribution and moisture potential curves. Pumice mixed with TC provided the best compliance with existing guidelines in relation to particle size distribution, and it significantly increased moisture content compared with the mixes of Pum with T5–8 and T5–16. As a result, from the second screening step, the best performing substrate was Pum mixed with TC and Zeo. The third stage involved the selection of the most appropriate organic amendment of the growing substrate. Three composts having different composition and sphagnum peat were analyzed for their chemical and physical characteristics. The composts were a) garden waste compost (GWC), b) olive (Olea europaea L.) mill waste compost (OMWC), and c) grape (Vitis vinifera L.) marc compost (GMC). It was found that the peat-amended substrate retained increased moisture content compared with the compost-amended substrates. The fourth and final stage involved the evaluation of the environmental impact of the final mix with the four different organic amendments based on their first flush nitrate nitrogen (NO3−-N) leaching potential. It was found that GWC and OMWC exhibited increased NO3−-N leaching that initially reached 160 and 92 mg·L−1 of NO3−-N for OMWC and GWC, respectively. By contrast, peat and GMC exhibited minimal NO3−-N leaching that was slightly above the maximum contaminant level of 10 mg·L−1 of NO3−-N (17.3 and 14.6 mg·L−1 of NO3−N for peat and GMC, respectively). The latter was very brief and lasted only for the first 100 and 50 mL of effluent volume for peat and GMC, respectively.


2014 ◽  
Vol 40 (4) ◽  
pp. 299-305 ◽  
Author(s):  
Kenichi Arima ◽  
Isao Torii ◽  
Ryuhei Takashima ◽  
Tetsuya Sawatsubashi ◽  
Masaaki Kinoshita ◽  
...  

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