Mesoscale Numerical Modeling for Predicting Wear Debris Generation
Sign Up to like & getrecommendations! Published in 2019 at "Tribology Letters"
DOI: 10.1007/s11249-019-1150-2
Abstract: With the development of debris detection techniques, wear debris has become a powerful indicator for wear conditions monitoring of engineering machines. However, there is still a lack of effective method for predicting the generation of… read more here.
Keywords: modeling predicting; wear debris; generation; numerical modeling ... See more keywords
Probability of Formation of Wear Debris during Initial Running-In Period of Sliding Wear of Al-Si (LM13)-10 wt.% Fly Ash Composites
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DOI: 10.1007/s11665-020-05211-z
Abstract: In this paper, the effect of sliding distance on dry sliding wear behavior of LM 13 alloy reinforced with 10 wt.% fine fly ash particles was studied with special reference to the probability of formation… read more here.
Keywords: formation wear; wear debris; formation; sliding wear ... See more keywords
Characterization of airborne wear debris produced by brake pads pressed against HVOF-coated discs
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DOI: 10.1007/s40544-019-0284-4
Abstract: A significant fraction of the non-exhaust particulate matter emissions from vehicular traffic comprises fine particles from the wear debris of brake pads and discs. Recent studies have shown that these emissions can be consistently reduced… read more here.
Keywords: characterization airborne; airborne wear; brake pads; wear debris ... See more keywords
Physical, tribological and viscoelastic behavior of machining wear debris powder reinforced epoxy composites
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Cleaner Production"
DOI: 10.1016/j.jclepro.2020.122786
Abstract: Abstract In the field of construction and building materials, many researchers have demonstrated the utilization of fly ash in polymer composites. In a similar way, the present study also focuses on the utilization of machining… read more here.
Keywords: physical tribological; wear debris; epoxy composites; wedm wear ... See more keywords
Size distribution analysis of wear debris generated in HEMM engine oil for reliability assessment: A statistical approach
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DOI: 10.1016/j.measurement.2018.09.012
Abstract: Abstract Wear debris size distribution in lubricated system closely related to lubricant condition and wear process. In this work, a model has been developed to predict the wear severity with operation time. The used oil… read more here.
Keywords: time; wear debris; size distribution; distribution ... See more keywords
Prediction of wear trend of engines via on-line wear debris monitoring
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DOI: 10.1016/j.triboint.2018.01.015
Abstract: Abstract On-line wear debris monitoring is a useful technology for real-time machine wear condition monitoring but needs further development. This study, based on previous developments of an on-line visual ferrograph (OLVF), focused on (i) data… read more here.
Keywords: line; wear debris; line wear; debris monitoring ... See more keywords
Influence of tribo-magnetization on wear debris trapping processes of textured dimples
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DOI: 10.1016/j.triboint.2018.01.046
Abstract: Abstract The mechanism of attachment of wear debris to textured dimples was investigated experimentally. Textured dimples were fabricated on the surface of medium carbon steel specimen with drilling method. Reciprocating ball on disc sliding wear… read more here.
Keywords: textured dimples; magnetization wear; tribo magnetization; wear debris ... See more keywords
Effect of debris size on the reciprocating sliding wear of aluminium
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DOI: 10.1016/j.wear.2016.10.025
Abstract: Abstract The literature is controversial in relation to the influence of wear debris on tribological behaviour. Some works have shown that the presence of debris is fundamental to the formation of a protective tribolayer, thus… read more here.
Keywords: presence; friction; reciprocating sliding; wear debris ... See more keywords
Integrated model of BP neural network and CNN algorithm for automatic wear debris classification
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DOI: 10.1016/j.wear.2018.12.087
Abstract: Abstract Mechanism-based wear debris classification (WDC) is important for root cause analysis and prediction of wear related faults. Compared to manual classifications, automatic WDC is more efficient and often more reliable for a wide range… read more here.
Keywords: debris classification; neural network; network cnn; wear debris ... See more keywords
Spur gear wear analysis as applied for tribological based predictive maintenance diagnostics
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DOI: 10.1016/j.wear.2018.12.088
Abstract: Abstract This paper describes an experimental investigation on a pair of spur gears in which wear and pitting were intentionally allowed to occur, namely, moisture corrosion pitting, acid-induced corrosion pitting, hard contaminant-related pitting and mechanical… read more here.
Keywords: pitting wear; wear analysis; spur gear; wear debris ... See more keywords
Wear debris of friction materials for linear standing-wave ultrasonic motors: Theory and experiments
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DOI: 10.1016/j.wear.2020.203216
Abstract: Abstract This study focuses on the wear debris of different friction materials for linear standing-wave ultrasonic motors (SWUMs). Wear debris with different morphology and sizes derive from wear mechanisms and has a critical influence on… read more here.
Keywords: linear standing; standing wave; friction; wear debris ... See more keywords