Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks

Drabik, J.; Trzos, M.

doi:10.1007/s10973-011-2176-3

Cited by 7 publications

(4 citation statements)

References 14 publications

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“…In the presented paper all calculations were performed with Statistica Neural Networks program and MLP networks were used as they are stable, simplified and very often used to resolve real problems [15,16,18].…”

Section: Neural Network Creationmentioning

confidence: 99%

“…Few researches predict a relationship between oil parameters, as in [16] modelling relation between oxidation resistance and tribological properties of nontoxic lubricants or predicting remaining useful life with use of ANN [17], basing on the critical values of oil parameters such as viscosity, flash point, water content, insoluble rating. Oil FTIR spectrum data are very seldom used with ANN [18].…”

Section: Introduction *mentioning

confidence: 99%

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Neural Networks as a Tool to Characterise Oil State After Porous Bearings Prolonged Tests

Król

Gocman

Giemza³

2015

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The paper presents the results of research of durability tests of porous sleeves under differed conditions (600, 1000 and 1400 rpm, duration of the tests: 100, 200 and 1000 hours, temperature 60, 80 and 130 °C) of one oil. During the tests a temperature of the bearing and a friction torque were measured. After each durability test oil samples were extracted from the bearings and some chosen properties were carried out (FTIR spectrums and total acid number). In the second stage the neural networks were used to describe achieved tribological characteristics. The data collected during the tests were used as an input to different neural networks models and as an output the investigative results of oil parameters were used. Different models of neural networks were checked to achieve the smallest training error and the best correlation between output from the network and the target.

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Section: Neural Network Creationmentioning

confidence: 99%

Section: Introduction *mentioning

confidence: 99%

Neural Networks as a Tool to Characterise Oil State After Porous Bearings Prolonged Tests

Król

Gocman

Giemza³

2015

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“…Proper design of lubricant is crucial to ensure the resistance to wear of the friction elements in industrial equipment. Lubricants have to meet many demands concerning the process parameters such as load, temperature, velocity, 1,2 and environmental requirements with the elimination or considerable reduction of toxic chemical compounds and the use of vegetable oils 3‐5 . The friction and wear properties of materials and lubricants are investigated in many aspects to meet the needed functionalities.…”

Section: Introductionmentioning

confidence: 99%

Polymer‐silica additive as a modifier of tribological properties of ecological grease, improvement of fatigue resistance

Drabik

Trzos

2020

Lubrication Science

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The influence of polymer additive (polytetrafluoroethylene) in grease based on paraffin oil on the resistance to fatigue wear (pitting) was investigated of rolling contact. The research results revealed that grease containing a polymer caused an increase in resistance to fatigue. It was examined whether the additive affects the properties of the grease, including rheological (investigated with the use of rheometer operated in the cone/plate configuration) and thermal (determined using the Differential Scanning Calorimetry) to check their relationship with a resistance to fatigue. A scanning electron microscope equipped with an energy dispersive spectrometer was used to determine if a polymer was present on wear trace. Then the sources of chemical elements were analysed with the use of X‐ray photoelectron spectroscopy to explain the improvement of resistance to fatigue. The relation between rheological properties and resistance to fatigue was shown, and the presence of polymer in friction contact was observed.

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“…Physical and chemical monitoring is the most basic evaluation method to check whether the physical and chemical indexes of oil-film bearing oil can meet the standard or not, the commonly used analytical methods are spectral analysis [4,5], differential scanning calorimetry [6], and the chemical approach [7]. However, these methods can hardly reflect the lubrication status of bearing friction pairs.…”

Section: Introductionmentioning

confidence: 99%

Experimental Evaluation of Lubrication Characteristics of a New Type Oil-Film Bearing Oil Using Multi-Sensor System

et al. 2016

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Abstract:In order to evaluate the operating performance of a new type oil-film bearing oil S220, a new test bearing was designed based on oil-film bearing test rig. The operating temperature of S220 was tested through the thermocouples installed on a test bearing; the operating oil-film pressure was tested through pressure transducers; and the operating oil-film thickness was tested through displacement transducers. Meanwhile, M220 was also tested as a comparison, and both oils are based on mineral oil. The results showed that all property indexes of the test rig can meet the specified requirements and can guarantee the performance test of oil-film bearing oil; the operating temperature of S220 is generally equal to that of M220, and both have the same operating stability. The temperature property conforms to Formula (1) and the operating temperature under different load cases can be predicted. Although oil-film pressure of M220 is a little more stable, the oil-film pressure of S220 is similar to that of M220. Moreover, both have the similar oil-film thickness, and the oil-film thickness of S220 is slightly smaller than that of M220, especially at the beginning of operation. Ultimately, oil S220 is evaluated to be suitable for actual engineering application.

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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks

Cited by 7 publications

References 14 publications

Neural Networks as a Tool to Characterise Oil State After Porous Bearings Prolonged Tests

Neural Networks as a Tool to Characterise Oil State After Porous Bearings Prolonged Tests

Polymer‐silica additive as a modifier of tribological properties of ecological grease, improvement of fatigue resistance

Experimental Evaluation of Lubrication Characteristics of a New Type Oil-Film Bearing Oil Using Multi-Sensor System

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