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- W1532382306 abstract "Dynamic is another critical behaviour of the process data, which has also caught much attention in process monitoring. Based on the previous works on dynamic process monitoring in the past years, this chapter introduces two different methods. These approaches rely on (i) recent work on independent component analysis and support vector data description that is applied to a dynamic data structure and (ii) the incorporation of the statistical local approach into a dynamic data representation. The analysis of experimental data from a gearbox system confirms (i) significant auto- and cross-correlation within and among these signals and (ii) that they cannot be assumed to follow Gaussian distributions. The application of both approaches showed that they are more sensitive to incipient faults than conventional multivariate statistical methods." @default.
- W1532382306 created "2016-06-24" @default.
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- W1532382306 date "2012-11-21" @default.
- W1532382306 modified "2023-09-23" @default.
- W1532382306 title "Dynamic Process Monitoring" @default.
- W1532382306 doi "https://doi.org/10.1007/978-1-4471-4513-4_10" @default.
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