Review of vibrating screen development trends: Linking the past and the future in mining machinery industries

Makinde, Olasumbo; Ramatsetse, Boitumelo; Mpofu, Khumbulani

doi:10.1016/j.minpro.2015.11.001

Cited by 86 publications

(38 citation statements)

References 6 publications

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“…Vibrating screens are critical machines prone to successive failures that can result in huge economic losses [5] and must be constantly improved in order to meet the requirements of the mining industry [6]. Proper operation of this machine has important benefits for the whole mineral process [7], and for this reason, many studies have been conducted to investigate the behavior and operational parameters for successful operation.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Modeling of a Vibrating Screen Considering the Ore Inertia and Force of the Ore over the Screen Calculated with Discrete Element Method

Moncada

Rodríguez

2018

Shock and Vibration

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Vibrating screens are critical machines used for size classification in mineral processing. Their proper operation, including accurate vibration movement and slope angle, can provide the benefits of energy savings and cost reductions in the screening process and the whole mining process. Dynamic models of the vibrating screen movement available in the literature do not simulate ore motion or its interaction with screen decks. The discrete element method (DEM) allows for the calculation of the dynamic of the ore. In this paper, two 2D three-degrees-of-freedom dynamic models for a vibrating screen are tested, using linear and nonlinear approaches for angular displacement. These models consider the inertia of the ore and the ore force calculated with DEM. A double-deck linear motion vibrating screen is simulated using the DEM software LIGGGTHS. DEM is used to obtain the ore parameters in the steady state and the force on the screen decks. Two cases are compared: Case 1 considers the ore as moving together with the vibrating screen, and Case 2 considers the ore force on the screen deck as calculated by DEM. Simulations are carried out with data for an industrial vibrating screen used in copper mining. The force over the screen is significantly different between the cases. Case 1 produces a force that is unrealistic because the ore cannot produce a high-amplitude adhesion force over the screen decks. In Case 2, no adhesion force acts between the ore and deck. It is concluded that the linear dynamic model used in Case 2 is adequate to evaluate the influence of the ore on the movement of the vibrating screen. The linear dynamic model considering the force as in Case 1 can be used to simulate a vibrating screen, as long as a correct calibration parameter is included to obtain an accurate motion amplitude.

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Section: Introductionmentioning

confidence: 99%

Dynamic Modeling of a Vibrating Screen Considering the Ore Inertia and Force of the Ore over the Screen Calculated with Discrete Element Method

Moncada

Rodríguez

2018

Shock and Vibration

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“…One of the most popular methods used in the industry to classify grains are screening machines, called also sieves machines [4]. Generally, it is based on the screening material through screens with different hole size using vibrations which make material falling through next screening panels with different mesh size.…”

Section: Related Workmentioning

confidence: 99%

Grain size determination and classification using adaptive image segmentation with shape information for milling quality evaluation

Budzan

Pawełczyk

2018

Diagnostyka

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In this paper, authors described methods of material granularity evaluation and a novel method for grain size determination with inline electromagnetic mill device diagnostics. The milling process quality evaluation can be carried out with vibration measurements, analysis of the milling material images or well-known screening machines. The method proposed in this paper is developed to the online examination of the milled product during the milling process using real-time digital images. In this paper, authors concentrated their work on copper ore milling process. Determination of the total number of the grain, the size of each grain, also the classification of the grains are the main goal of the developed method. In the proposed method the vision camera with lightning mounted at two assumed angles has been used. The detection of the grains has been based on an adaptive segmentation algorithm, improved with distance transform to enhance grains detection. The information about particles shape and context is used to optimize the grain classification process in the next step. The final classification is based on the rule-based method with defined particle shape and size parameters.

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“…Additionally, each elastic support is composed of several metal helical springs. These springs are critical components in a mining vibrating screen's elastic supports, which directly affect the working performance of the mining vibrating screen [6,7]. However, long-term alternating loads are highly likely to lead to spring failure through spring stiffness decrease [8], causing a negative influence on the mining vibrating screen.…”

Section: Introductionmentioning

confidence: 99%

A Theoretical Rigid Body Model of Vibrating Screen for Spring Failure Diagnosis

et al. 2019

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Springs are critical components in mining vibrating screen elastic supports. However, long-term alternating loads are likely to lead to spring failures, likely resulting in structural damages to the vibrating screen and resulting in a lower separation efficiency. Proper dynamic models provide a basis for spring failure diagnosis. In this paper, a six-degree-of-freedom theoretical rigid body model of a mining vibrating screen is proposed, and a dynamic equation is established in order to explore the dynamic characteristics. Numerical simulations, based on the Newmark-β algorithm, are carried out, and the results indicate that the model proposed is suitable for revealing the dynamic characteristics of the mining vibrating screen. Meanwhile, the mining vibrating screen amplitudes change with the spring failures. Therefore, six types of spring failure are selected for simulations, and the results indicate that the spring failures lead to an amplitude change for the four elastic support points in the x, y, and z directions, where the changes depend on certain spring failures. Hence, the key to spring failure diagnosis lies in obtaining the amplitude change rules, which can reveal particular spring failures. The conclusions provide a theoretical basis for further study and experiments in spring failure diagnosis for a mining vibrating screen.

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Review of vibrating screen development trends: Linking the past and the future in mining machinery industries

Cited by 86 publications

References 6 publications

Dynamic Modeling of a Vibrating Screen Considering the Ore Inertia and Force of the Ore over the Screen Calculated with Discrete Element Method

Dynamic Modeling of a Vibrating Screen Considering the Ore Inertia and Force of the Ore over the Screen Calculated with Discrete Element Method

Grain size determination and classification using adaptive image segmentation with shape information for milling quality evaluation

A Theoretical Rigid Body Model of Vibrating Screen for Spring Failure Diagnosis

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