Direct numerical methods dedicated to second-order ordinary differential equations

Kostek, Robert

doi:10.1016/j.amc.2013.02.019

Cited by 7 publications

(2 citation statements)

References 11 publications

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“…4d). This was reported previously for simulation results (Kostek, 2013a;Kostek et al, 2015). In this case, application of filtration does not provide any more information.…”

Section: Analysis Of Experimental Resultssupporting

confidence: 87%

Arduino based diagnostics system dedicated to rolling bearings

2018

Engineering Mechanics

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This article presents: a test stand dedicated to testing rolling bearings; a low cost diagnostic system based on Arduino Mega and experimental results obtained with this system. Employed sensors were calibrated and described. Some attention was paid to measured errors. Next state indicators obtained from experimental results were presented. Provided information is useful for companies and researchers, who are focused on condition monitoring. The diagnostic system works properly and can be used in practice.

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“…4d). This was reported previously for simulation results (Kostek, 2013a;Kostek et al, 2015). In this case, application of filtration does not provide any more information.…”

Section: Analysis Of Experimental Resultssupporting

confidence: 87%

Arduino based diagnostics system dedicated to rolling bearings

2018

Engineering Mechanics

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“…And, the last forces are the rolling friction forces. This leads to non-linear secondorder differential equations, that are solved with a numerical method [24]. The rolling bearing vibrations are studied for various magnitudes of clearance.…”

Section: Nonlinear Modelingmentioning

confidence: 99%

Data processing of experimental and computational results in machinery diagnostics

Żółtowski

Kostek

2014

Int. J. Dynam. Control

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Dynamic properties of machines influence on generated noise and vibrations, moreover they influence on service life, precision and quality of products; hence condition monitoring is a key factor in machine maintenance. They are two main methods in machinery diagnostics. The first relays mostly on experimental results, whereas the second method relays on computational results. The first approach is called symptom diagnostics, whereas the second is called holistic diagnosis. The experimentally obtained failure modes (symptoms) are functions of measured parameters. They can be non-dimensional without a physical interpretation, but they should be sensitive to condition of machines, which is a key factor. Whereas in holistic diagnostics two kinds of models are used: linear and non-linear. Linear models are wide spread, because they are relatively simple to use. Non-linearity is neglected in these models, which introduces an error, but makes computation easier. In contrast to this, non-linear models are more accurate, but their application is far more difficult. It should be mentioned that, those non-linear models have an important advantage; they can explain phenomena like multi-stability, fluctuations of measured amplitudes and jumps of amplitudes. These phenomena do not take place in linear models. A few examples are presented, to illustrate linear and non-linear models in machinery diagnostics. Moreover practical approach to signal processing is presented.

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