Perturbation incremental method of limit cycle for a nonlinear conveyor belt system

A conveyor belt system essentially consists of an endless belt of elastic material connected between two flat pulleys and driven by the rotation of one of the pulleys by a direct current motor. Usually, the material is fed to the belt near the other end of the pulley. The moving belt that carries the material to the drive pulley tends to sag between the two end pulleys due to its own weight. Rubber conveyor belts are commonly used to transport items with uneven bottom surfaces, small items that fall between rolls, or product bags that sag between rolls.

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Failure Rate Prediction of Belt Conveyor Systems using 2-parameter Weibull distribution

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2021.38570 ◽

2021 ◽

Vol 9 (10) ◽

pp. 1035-1039

Author(s):

Olutayo Opeyemi Ogunmilua

Keyword(s):

Failure Rate ◽

Scale Parameter ◽

Mining Industry ◽

Conveyor Belt ◽

Time To Failure ◽

Belt Conveyor ◽

System 2 ◽

Accuracy Of Results ◽

Component Failures ◽

Belt System

Abstract: The conveyor belt is one of the most operational critical equipment’s in the mining industry, they are mostly used in the transportation of crushed materials from the crushing station to where there’ll be further processed. Due to the increasing complexity of belt conveyor systems, managing their integrity has become even more difficult, as they are now used across various industries, environments and carry materials of different weight variations, leaving them susceptible to failures (1). This paper provides an industry specific knowledge on how Weibull analysis can be used to predict the failure rate of a conveyor belt system, using parameters such as the time to failure (TTF), installation and failure dates, as determinant parameters for the predictions. Several Weibull failure distributions and functions have been used to establish accuracy of results and to create comparisons on the different ways in which risk, unreliability and availability are quantified, using calculated values such as the Shape and scale parameter. The paper utilizes real world case studies in the area of mining, which sheds light on key component failures and their cut sets within the conveyor belt system (2) Keywords: TTF, TTR, Threshold parameter, Repair date, Shape parameter, B10, B15, B20, Scale parameter, ECA, CDF, PDF

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Truck-and-Loader Versus Conveyor Belt System: An Environmental and Economic Comparison

Proceedings of the 27th International Symposium on Mine Planning and Equipment Selection - MPES 2018 ◽

10.1007/978-3-319-99220-4_25 ◽

2019 ◽

pp. 307-318

Author(s):

C. M. de Almeida ◽

T. de Castro Neves ◽

C. Arroyo ◽

P. Campos

Keyword(s):

Conveyor Belt ◽

Economic Comparison ◽

Belt System

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A simulation analysis model of bucket wheel excavator-conveyor belt system for oil sand extraction and material handling

International Journal of Mining and Mineral Engineering ◽

10.1504/ijmme.2009.027257 ◽

2009 ◽

Vol 1 (3) ◽

pp. 278 ◽

Cited By ~ 1

Author(s):

Abhineet Sharma ◽

Jozef Szymanski ◽

Ajoy Anand

Keyword(s):

Material Handling ◽

Simulation Analysis ◽

Conveyor Belt ◽

Analysis Model ◽

Oil Sand ◽

Belt System ◽

Sand Extraction

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Building Intelligent Conveyor System using classification techniques in a logistics Industry

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.f8484.088619 ◽

2019 ◽

Vol 8 (6) ◽

pp. 2116-2121

Keyword(s):

Machine Learning ◽

Conveyor Belt ◽

Machine Learning Algorithms ◽

Machine Learning Techniques ◽

Test Results ◽

Logistics Industry ◽

Conveyor System ◽

Learning Techniques ◽

Operational Data ◽

Belt System

Machine learning techniques plays an important role in knowledge discovery and assists humans in decision making. They help to detect patterns and predict the actions/outcome. In a complex industrial environment mode of operations of a machine depends on various internal and external parameters which are often done using expert judgement method which is not accurate and results in machine breakdown thereby resulting in unplanned outage. In this paper, we discussed and demonstrated how machine learning algorithms can help to handle conveyor systems autonomously in an optimum way without any human intervention. A conveyor belt system operational data is used to select the appropriate classification technique for the selected dataset. The details of the dataset collected, algorithms used and the test results are discussed in this paper.

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Analysis of Transient Belt Stretch for Horizontal and Inclined Belt Conveyor System

International Journal of Mathematical Engineering and Management Sciences ◽

10.33889/ijmems.2019.4.5-092 ◽

2019 ◽

Vol 4 (5) ◽

pp. 1169-1179 ◽

Cited By ~ 1

Author(s):

Sanjay G. Sakharwade ◽

Shubharata Nagpal

Keyword(s):

Conveyor Belt ◽

Belt Conveyor ◽

Conveyor System ◽

Structure Damage ◽

Starting Condition ◽

Maximum Value ◽

Sudden Rise ◽

Static Calculation ◽

Standard Value ◽

Belt System

Belt is costliest part of belt conveyor system. Sudden rise in belt tension within transient starting condition, results in belt failure and structure damage. It is difficult to measure these stresses by static calculation method and hence their presence might go undetected. Belt elongation is an evident quantity for these stresses. Dynamic belt stretch is formulated in terms of displacement response of conjugative belt units with respect to time. This paper presents analysis of the event and propagation of dynamic belt stretch for straight horizontal and straight inclined belt conveyor system. Dynamic behavior of belt system is investigated for starting condition of fully stacked conveyor belt. Belt conveyor system is considered as series of vibrating mass and its unit is assumed to be a viscoelastic segment. Equation of motion of belt unit is developed by Lagrange’s approach. Observed transient parameters are more vibrant in inclined belt than the horizontal belt system. Maximum value of dynamic belt stretch for horizontal belt systems founds 1.13% of total belt length and for inclined belt conveyor system, it is 1.16% of belt length. Both values are within range of standard value specified for fabric belt system.

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Viscoelastic Indentation and Resistance to Motion of Conveyor Belts Using a Generalized Maxwell Model of the Backing Material

Rubber Chemistry and Technology ◽

10.5254/1.3547939 ◽

2006 ◽

Vol 79 (2) ◽

pp. 307-319 ◽

Cited By ~ 26

Author(s):

Thomas J. Rudolphi ◽

Allen V. Reicks

Keyword(s):

Viscoelastic Model ◽

Frictional Coefficient ◽

Maxwell Model ◽

Material Model ◽

Conveyor Belt ◽

Winkler Foundation ◽

System Parameters ◽

Backing Material ◽

Foundation Model ◽

Belt System

Abstract A one-dimensional Winkler foundation and a generalized viscoelastic Maxwell solid model of the belt backing material are used to determine the resistance to motion of a conveyor belt over idlers. The viscoelastic material model is a generalization of the three-parameter Maxwell model that has previously been used to predict the effective frictional coefficient of the rolling motion. Frequency, or loading rate, and temperature dependence of the material properties are incorporated with the time/temperature correspondence principle of linear viscoelastic materials. As a consequence of the Winkler foundation model, a normalized indentation resistance is independent of the primary belt system parameters - carrying weight per unit width, idler diameter and backing thickness - as is the case for a three-parameter viscoelastic model. Example results are provided for a typical rubber compound backing material and belt system parameters.

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