Clutch wear prediction via a deterministic-stochastic modeling approach

S. G. Kapoor

doi:10.1016/0043-1648(84)90068-1

Clutch wear prediction via a deterministic-stochastic modeling approach

Research output: Contribution to journal › Article › peer-review

Abstract

The front surface temperature of a clutch pressure plate is studied for clutch wear prediction. A combined deterministic plus stochastic modeling approach is proposed to fit the front surface temperature data. The underlying clutch engagement process is explained by a deterministic function, whereas the inherent dynamics are explained by the stochastic model. The results of the combined modeling approach indicate that the front surface temperature can be modeled accurately to within ± 4°F.

Original language	English (US)
Pages (from-to)	181-192
Number of pages	12
Journal	Wear
Volume	93
Issue number	2
DOIs	https://doi.org/10.1016/0043-1648(84)90068-1
State	Published - Jan 16 1984

ASJC Scopus subject areas

Condensed Matter Physics
Mechanics of Materials
Surfaces and Interfaces
Surfaces, Coatings and Films
Materials Chemistry

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10.1016/0043-1648(84)90068-1

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title = "Clutch wear prediction via a deterministic-stochastic modeling approach",

abstract = "The front surface temperature of a clutch pressure plate is studied for clutch wear prediction. A combined deterministic plus stochastic modeling approach is proposed to fit the front surface temperature data. The underlying clutch engagement process is explained by a deterministic function, whereas the inherent dynamics are explained by the stochastic model. The results of the combined modeling approach indicate that the front surface temperature can be modeled accurately to within ± 4°F.",

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N2 - The front surface temperature of a clutch pressure plate is studied for clutch wear prediction. A combined deterministic plus stochastic modeling approach is proposed to fit the front surface temperature data. The underlying clutch engagement process is explained by a deterministic function, whereas the inherent dynamics are explained by the stochastic model. The results of the combined modeling approach indicate that the front surface temperature can be modeled accurately to within ± 4°F.

AB - The front surface temperature of a clutch pressure plate is studied for clutch wear prediction. A combined deterministic plus stochastic modeling approach is proposed to fit the front surface temperature data. The underlying clutch engagement process is explained by a deterministic function, whereas the inherent dynamics are explained by the stochastic model. The results of the combined modeling approach indicate that the front surface temperature can be modeled accurately to within ± 4°F.

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Clutch wear prediction via a deterministic-stochastic modeling approach

Abstract

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