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Fault detection in multi-sensor networks based on multivariate time-series models and orthogonal transformations.

, , , , , and . Inf. Fusion, (2014)

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Residual-based fault detection using soft computing techniques for condition monitoring at rolling mills., , , , and . Inf. Sci., (2014)Fuzzy fault isolation using gradient information and quality criteria from system identification models., , , , , and . Inf. Sci., (2015)Filtering of dynamic measurements in intelligent sensors for fault detection based on data-driven models., , , and . CDC, page 463-468. IEEE, (2003)Gradient-based fuzzy fault isolation in residual-based fault detection systems., , , , , and . FUZZ-IEEE, page 1428-1435. IEEE, (2014)Online modelling based on Genetic Programming, , , , and . International Journal of Intelligent Systems Technologies and Applications, 2 (2/3): 255--270 (19 February 2007)On-Line Modelling Based on Genetic Programming., , , , and . ALaRT, page 119-130. University Siegen, Germany, (2005)Improved fault detection employing hybrid memetic fuzzy modeling and adaptive filters., , , , , , and . Appl. Soft Comput., (2017)Hybrid Genetic-Fuzzy Systems for improved performance in Residual-Based Fault Detection., , , , , and . NaBIC, page 91-96. IEEE, (2014)Condition Monitoring at Rolling Mills with Data-Driven Residual-Based Fault Detection., , , , and . MIM, page 1530-1535. International Federation of Automatic Control, (2013)Online modelling based on Genetic Programming., , , , and . Int. J. Intell. Syst. Technol. Appl., 2 (2/3): 255-270 (2007)