scholarly journals Measurement-Based Modelling of Material Moisture and Particle Classification for Control of Copper Ore Dry Grinding Process

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 667
Author(s):  
Oliwia Krauze ◽  
Dariusz Buchczik ◽  
Sebastian Budzan
Keyword(s):  
Particle Size ◽  
Measurement Errors ◽  
Fine Particles ◽  
Least Squares Method ◽  
Recursive Least Squares ◽  
Energetic Efficiency ◽  
Copper Ore ◽  
Input Material ◽  
Dry Grinding ◽  
Particle Classification

Moisture of bulk material has a significant impact on energetic efficiency of dry grinding, resultant particle size distribution and particle shape, and conditions of powder transport. As a consequence, moisture needs to be measured or estimated (modelled) in many points. This research investigates mutual relations between material moisture and particle classification process in a grinding installation. The experimental setup involves an inertial-impingement classifier and cyclone being part of dry grinding circuit with electromagnetic mill and recycle of coarse particles. The tested granular material is copper ore of particle size 0–1.25 mm and relative moisture content 0.5–5%, fed to the installation at various rates. Higher moisture of input material is found to change the operation of the classifier. Computed correlation coefficients show increased content of fine particles in lower product of classification. Additionally, drying of lower and upper classification products with respect to moisture of input material is modelled. Straight line models with and without saturation are estimated with recursive least squares method accounting for measurement errors in both predictor and response variables. These simple models are intended for use in automatic control system of the grinding installation.

The effect of Tin additionon on Structural and magnetic properties of the stannoferrite Li0.5+0.5XFe2.5-1.5XSnXO4

2016 ◽  
Vol 12 (3) ◽  
pp. 4307-4321 ◽  
Author(s):  
Ahmed Hassan Ibrahim ◽  
Yehia Abbas
Keyword(s):  
Particle Size ◽  
Fine Particles ◽  
Magnetic Moments ◽  
Lithium Ferrite ◽  
Tem Analysis ◽  
Weiss Temperature ◽  
X Ray ◽  
Two Phases ◽  
Nanocrystalline Ferrite ◽  
20 Nm

The physical properties of ferrites are verysensitive to microstructure, which in turn critically dependson the manufacturing process.Nanocrystalline Lithium Stannoferrite system Li0.5+0.5XFe2.5-1.5XSnXO4,X= (0, 0.2, 0.4, 0.6, 0.8 and 1.0) fine particles were successfully prepared by double sintering ceramic technique at pre-sintering temperature of 500oC for 3 h andthepre-sintered material was crushed and sintered finally in air at 1000oC.The structural and microstructural evolutions of the nanophase have been studied using X-ray powder diffraction (XRD) and the Rietveld method.The refinement results showed that the nanocrystalline ferrite has a two phases of ordered and disordered phases for polymorphous lithium Stannoferrite.The particle size of as obtained samples were found to be ~20 nm through TEM that increases up to ~ 85 nmand isdependent on the annealing temperature. TEM micrograph reveals that the grains of sample are spherical in shape. (TEM) analysis confirmed the X-ray results.The particle size of stannic substituted lithium ferrite fine particle obtained from the XRD using Scherrer equation.Magneticmeasurements obtained from lake shore’s vibrating sample magnetometer (VSM), saturation magnetization ofordered LiFe5O8 was found to be (57.829 emu/g) which was lower than disordered LiFe5O8(62.848 emu/g).Theinterplay between superexchange interactions of Fe3+ ions at A and B sublattices gives rise to ferrimagnetic ordering of magnetic moments,with a high Curie-Weiss temperature (TCW ~ 900 K).

scholarly journals Contribution of Fine Particles to Air Emission at Different Phases of Biomass Burning

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 278 ◽  
Author(s):  
Niloofar Ordou ◽  
Igor E. Agranovski
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Fine Particles ◽  
Combustion Process ◽  
Coarse Particles ◽  
Biomass Smoke ◽  
Smoke Particles ◽  
Air Emission ◽  
Entire Duration ◽  
Diffusion Properties

Particle size distribution in biomass smoke was observed for different burning phases, including flaming and smouldering, during the combustion of nine common Australian vegetation representatives. Smoke particles generated during the smouldering phase of combustions were found to be coarser as compared to flaming aerosols for all hard species. In contrast, for leafy species, this trend was inversed. In addition, the combustion process was investigated over the entire duration of burning by acquiring data with one second time resolution for all nine species. Particles were separately characterised in two categories: fine particles with dominating diffusion properties measurable with diffusion-based instruments (Dp < 200 nm), and coarse particles with dominating inertia (Dp > 200 nm). It was found that fine particles contribute to more than 90 percent of the total fresh smoke particles for all investigated species.

scholarly journals Experimental Analysis of the Mechanical Properties and Resistivity of Tectonic Coal Samples with Different Particle Sizes

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2303
Author(s):  
Congyu Zhong ◽  
Liwen Cao ◽  
Jishi Geng ◽  
Zhihao Jiang ◽  
Shuai Zhang
Keyword(s):  
Mechanical Properties ◽  
Particle Size ◽  
Compressive Strength ◽  
Elastic Modulus ◽  
Uniaxial Compressive Strength ◽  
Coalbed Methane ◽  
Coal Sample ◽  
Fine Particles ◽  
Particle Sizes ◽  
Tectonic Coal

Because of its weak cementation and abundant pores and cracks, it is difficult to obtain suitable samples of tectonic coal to test its mechanical properties. Therefore, the research and development of coalbed methane drilling and mining technology are restricted. In this study, tectonic coal samples are remodeled with different particle sizes to test the mechanical parameters and loading resistivity. The research results show that the particle size and gradation of tectonic coal significantly impact its uniaxial compressive strength and elastic modulus and affect changes in resistivity. As the converted particle size increases, the uniaxial compressive strength and elastic modulus decrease first and then tend to remain unchanged. The strength of the single-particle gradation coal sample decreases from 0.867 to 0.433 MPa and the elastic modulus decreases from 59.28 to 41.63 MPa with increasing particle size. The change in resistivity of the coal sample increases with increasing particle size, and the degree of resistivity variation decreases during the coal sample failure stage. In composite-particle gradation, the proportion of fine particles in the tectonic coal sample increases from 33% to 80%. Its strength and elastic modulus increase from 0.996 to 1.31 MPa and 83.96 to 125.4 MPa, respectively, and the resistivity change degree decreases. The proportion of medium particles or coarse particles increases, and the sample strength, elastic modulus, and resistivity changes all decrease.

Online parameter estimation and adaptive control with limited information in structures

2021 ◽  
pp. 107754632110191
Author(s):  
Fereidoun Amini ◽  
Elham Aghabarari
Keyword(s):  
Parameter Estimation ◽  
Adaptive Control ◽  
Least Squares ◽  
Control Algorithm ◽  
Least Squares Method ◽  
Recursive Least Squares ◽  
Limited Information ◽  
Online Identification ◽  
Recursive Least Squares Method ◽  
Adaptive Control Algorithm

An online parameter estimation is important along with the adaptive control, that is, a time-dependent plant. This study uses both online identification and the simple adaptive control algorithm with velocity feedback. The recursive least squares method was used to identify the stiffness and damping parameters of the structure’s stories. Identification was carried out online without initial estimation and only by measuring the structural responses. The limited information regarding sensor measurements, parameter convergence, and the effects of the covariance matrix is examined. The integration of the applied online identification, the appropriate reference model selection in simple adaptive control, and adopting the proportional integral filter was used to limit the structural control response error. Some numerical examples are simulated to verify the ability of the proposed approach. Despite the limited information, the results show that the simultaneous use of online identification with the recursive least squares method and simple adaptive control algorithm improved the overall structural performance.

Liquid antisolvent recrystallization and solid dispersion of flufenamic acid with polyvinylpyrrolidone K-30

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Rahul Kumar ◽  
Sanjay Kumar ◽  
Pranava Chaudhari ◽  
Amit K. Thakur
Keyword(s):  
Particle Size ◽  
Dissolution Rate ◽  
Solid Dispersion ◽  
Fine Particles ◽  
Xrd Analysis ◽  
Solution Concentration ◽  
Injection Rate ◽  
Size Reduction ◽  
Flufenamic Acid ◽  
Particle Size Reduction

Abstract Flufenamic acid (FFA) is a Biopharmaceutical Classification System- II (BCS-II) class drug with poor bioavailability and a lower dissolution rate. Particle size reduction is one of the conventional approaches to increase the dissolution rate and subsequently the bioavailability. The use of the liquid antisolvent method for particle size reduction of FFA was studied in this work. Ethanol and water were used as solvent and antisolvent, respectively. Experimental parameters such as solution concentration (10–40 mg/ml), flow rate (120–480 ml/h), temperature (298–328 K) and stirring speed (200–800 rpm) were investigated. Furthermore, the solid dispersion of FFA was prepared with polyvinylpyrrolidone K-30 (PVP K-30) with different weight ratios (1:1, 1:2, 1:3 and 1:4) and samples were characterized using SEM, FTIR and XRD techniques. The experimental investigation revealed that higher values of concentration, injection rate, stirring speed, along with lower temperature favored the formation of fine particles. SEM analysis revealed that the morphology of raw FFA changed from rock-like to rectangular-like after liquid antisolvent recrystallization. FTIR analysis validated the presence of hydrogen bonding between FFA and PVP in solid dispersion. XRD analysis showed no significant change in the crystallinity of the processed FFA.

Real-Time Diagnosis of the Exhaust Recirculation in Diesel Engines Using Least-Squares Parameter Estimation

2009 ◽  
Vol 132 (1) ◽  
Author(s):  
Javad Mohammadpour ◽  
Karolos Grigoriadis ◽  
Matthew Franchek ◽  
Benjamin J. Zwissler
Keyword(s):  
Diesel Engine ◽  
Least Squares ◽  
Real Time ◽  
Diesel Engines ◽  
Least Squares Method ◽  
Recursive Least Squares ◽  
Low Flow ◽  
Robust Version ◽  
Orifice Flow ◽  
Gas Recirculation

In this paper, we present a real-time parameter identification approach for diagnosing faults in the exhaust gas recirculation (EGR) system of Diesel engines. The proposed diagnostics method has the ability to detect and estimate the magnitude of a leak or a restriction in the EGR valve, which are common faults in the air handling system of a Diesel engine. Real-time diagnostics is achieved using a recursive-least-squares (RLS) method, as well as, a recursive formulation of a more robust version of the RLS method referred to as recursive total-least-squares method. The method is used to identify the coefficients in a static orifice flow model of the EGR valve. The proposed approach of fault detection is successfully applied to diagnose low-flow or high-flow faults in an engine and is validated using experimental data obtained from a Diesel engine test cell and a truck.

Maximum Adhesion Control of Railway Based on Sliding Mode Control System

2011 ◽  
Vol 383-390 ◽  
pp. 5242-5249 ◽  
Author(s):  
Yun Feng Li ◽  
Xiao Yun Feng ◽  
Rui Kuo Liu
Keyword(s):  
Least Squares Method ◽  
Sliding Mode ◽  
Reference Value ◽  
Variable Structure ◽  
Recursive Least Squares ◽  
Adhesion Coefficient ◽  
Reference Velocity ◽  
Torque Transmission ◽  
Vehicle Velocity ◽  
Recursive Least Squares Method

The wheels will idle when the relative slipping speed between the wheel and rail exceeds the reference slipping speed. In order to avoid this phenomenon, the simplified model of wheel-rail traction torque transmission was established. And the adhesion coefficient and vehicle velocity are got through the disturbance observer. Then the recursive least squares method was used to forecast the slope of the adhesion-slip curve. Sliding variable structure controller was used to control the error of wheel velocity and reference velocity. From the results of simulation, this method can be effective to maintain the adhesion coefficient around the maximum. And the slipping speed approached the reference value, so the damage for wheel and rail was effectively prevented which achieved the desired effect.

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