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• W3049063313 endingPage "115642" @default.
• W3049063313 startingPage "115642" @default.
• W3049063313 abstract "Effective incipient fault detection requires a method that can separate fault signatures under constant and time-varying operating conditions. In this work, we focus on improving informative frequency band identification methods for applications under constant and time-varying operating conditions. Many automatic band selection techniques exist and have proven effective under constant speed and load conditions. However, it has been shown that these techniques occasionally identify frequency bands that contain non-damage related information, especially under fluctuating operating conditions and at low damage levels. With this research, a new methodology is proposed which makes use of popular informative frequency band selection techniques, such as the Fast Kurtogram, to effectively identify damage under constant and fluctuating speed and load conditions. A key step in this methodology, the NICogram, requires healthy historical data, which is used to identify frequency bands that contain novel information in unclassified signals. The methodology uses multiple signals to identify whether a component is damaged or not through a probabilistic approach. It is shown that the method performs much better than the conventional informative frequency band identification methods on synthetic and experimental data." @default.
• W3049063313 created "2020-08-21" @default.
• W3049063313 creator A5040167578 @default.
• W3049063313 creator A5059110516 @default.
• W3049063313 creator A5091276402 @default.
• W3049063313 date "2020-12-01" @default.
• W3049063313 modified "2023-10-01" @default.
• W3049063313 title "NIC Methodology: A probabilistic methodology for improved informative frequency band identification by utilizing the available healthy historical data under time-varying operating conditions" @default.
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• W3049063313 doi "https://doi.org/10.1016/j.jsv.2020.115642" @default.
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