Control System of Electromagnetic Mill Load

Ogonowski, Szymon; Ogonowski, Zbigniew; Swierzy, Markus; Pawełczyk, Marek

doi:10.1109/icseng.2017.23

Cited by 7 publications

(9 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During research in that area several ideas were tested, including active power of the EM field inductor or transport air pressure changes measurements among others. Finally, indirect measurement based on acoustic signal generated by the working chamber was applied [27]. A measurement microphone with cardioid polar pattern is installed on the top of the mill's working chamber on the opposite side to the fresh feed inlet (see Fig.…”

Section: Indirect Measurement Of the Mill's Load Levelmentioning

confidence: 99%

Archives of Control Sciences

Ogonowski,

Bismor,

Ogonowski

2020

View full text Add to dashboard Cite

Control of complex dynamic nonlinear loading process for electromagnetic mill SZYMON OGONOWSKI, DARIUSZ BISMOR and ZBIGNIEW OGONOWSKI Electromagnetic mill installation for dry grinding represents a complex dynamical system that requires specially designed control system. The paper presents model-based predictive control which locates closed loop poles in arbitrary places. The controller performs as gain scheduling prototype where nonlinear model -artificial recurrent neural network, is parameterized with additional measurements and serves as a basis for local linear approximation. Application of such a concept to control electromagnetic mill load allows for stable performance of the installation and assures fulfilment of the product quality as well as the optimization of the energy consumption.

show abstract

Section: Indirect Measurement Of the Mill's Load Levelmentioning

confidence: 99%

Archives of Control Sciences

Ogonowski,

Bismor,

Ogonowski

2020

View full text Add to dashboard Cite

show abstract

“…Such a system for dry grinding process was developed [14] and patented [15] by the consortium of Polish universities and companies: Silesian University of Technology, AGH University of Science and Technology, ELTRAF Company (EMM producer, Lubliniec, Poland) and AMEplus Company (integrator of automation systems, Gliwice, Poland). Modelling of the air transport paths was carefully studied [16][17][18], classification capabilities were examined [19,20], and control problems were discussed [21][22][23]. Section 2.2 describes the idea of the entire system and describes differences between wet and dry grinding circuits.…”

Section: Device Descriptionmentioning

confidence: 99%

Comparison of Wet and Dry Grinding in Electromagnetic Mill

et al. 2018

Self Cite

View full text Add to dashboard Cite

Abstract:Comparison of dry and wet grinding process in an electromagnetic mill is presented in this paper. The research was conducted in a batch copper ore grinding. Batch mode allows for precise parametrization and constant repetitive conditions of the experiments. The following key aspects were tested: processing time, feed size, size of the grinding media, mass of the material and graining media, and density of the pulp. The particles size distribution of the product samples was analyzed in the laboratory after each experiment. The paper discusses the experimental results as well as the concept of dry and wet grinding and classification circuits for the electromagnetic mill. The main points of the discussion are the size reduction effectiveness and power consumption of the entire system.

show abstract

“…Grinding is invaluable in carbon steel microstructures [1], metal ore milling [2], cement production [3], minerals [4], powder technology for the food industry [5], and the pharmaceutical industry [6], among others. Based on final particle size, time consumption, parameters of the grinding process, grinding media, assumed particle size, and type of material used, we identify various types of mills that have described in recent literature—the ball [7], vertical roller [8], electromagnetic [9,10], pin mill [11], Buhrstone [12], and others.…”

Section: Introductionmentioning

confidence: 99%

Combining Segmentation and Edge Detection for Efficient Ore Grain Detection in an Electromagnetic Mill Classification System

Budzan

Buchczik

Pawełczyk

et al. 2019

Sensors

View full text Add to dashboard Cite

This paper presents a machine vision method for detection and classification of copper ore grains. We proposed a new method that combines both seeded regions growing segmentation and edge detection, where region growing is limited only to grain boundaries. First, a 2D Fast Fourier Transform (2DFFT) and Gray-Level Co-occurrence Matrix (GLCM) are calculated to improve the detection results and processing time by eliminating poor quality samples. Next, detection of copper ore grains is performed, based on region growing, improved by the first and second derivatives with a modified Niblack’s theory and a threshold selection method. Finally, all the detected grains are characterized by a set of shape features, which are used to classify the grains into separate fractions. The efficiency of the algorithm was evaluated with real copper ore samples of known granularity. The proposed method generates information on different granularity fractions at a time with a number of grain shape features.

show abstract

Control System of Electromagnetic Mill Load

Cited by 7 publications

References 8 publications

Archives of Control Sciences

Archives of Control Sciences

Comparison of Wet and Dry Grinding in Electromagnetic Mill

Combining Segmentation and Edge Detection for Efficient Ore Grain Detection in an Electromagnetic Mill Classification System

Contact Info

Product

Resources

About