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• W2591011293 abstract "In the real multisource signal analysis one of the main problems is the fact that true information is divided partially among the individual signals and/or measured signal is a mixture of different sources. This comes from the fact that input channels are typically related, and carry information about different processes occurring during the measurement. Those processes can be thought of as independent sources of vaguely understood “information”. In many cases separation and extraction of those sources can be crucial. In this paper we present the usage of Independent Component Analysis as a tool for information extraction from real-life multichannel temperature data measured on heavy duty gearboxes used in mining industry. Original signals, due to operational factors reveal cyclic variability and detection of damage was difficult. Thanks to proposed procedure, from four channels acquired from 4 gearboxes driving belt conveyor we have extracted one of 4 components, that is related to change of condition of a single gearbox. For new signal visibility of change is clear and simple automatic detection rule can be applied." @default.
• W2591011293 created "2017-03-03" @default.
• W2591011293 creator A5005212369 @default.
• W2591011293 creator A5077454176 @default.
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• W2591011293 date "2017-01-01" @default.
• W2591011293 modified "2023-09-27" @default.
• W2591011293 title "Application of Independent Component Analysis in Temperature Data Analysis for Gearbox Fault Detection" @default.
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• W2591011293 doi "https://doi.org/10.1007/978-3-319-51445-1_11" @default.
• W2591011293 hasPublicationYear "2017" @default.
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