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Hybrid Genetic-Fuzzy Systems for improved performance in Residual-Based Fault Detection.

, , , , , and . NaBIC, page 91-96. IEEE, (2014)

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Detecting cracks in reciprocating compressor valves using pattern recognition in the pV diagram., , , , , and . Pattern Anal. Appl., 18 (2): 461-472 (2015)Improved fault detection employing hybrid memetic fuzzy modeling and adaptive filters., , , , , , and . Appl. Soft Comput., (2017)Data based modeling for PEM fuel cell monitoring - a test bench application, Part I., , , and . CCA, page 262-267. IEEE, (2008)Fault detection in reciprocating compressor valves for steady-state load conditions., , , , and . ISSPIT, page 224-229. IEEE, (2011)Gradient-based fuzzy fault isolation in residual-based fault detection systems., , , , , and . FUZZ-IEEE, page 1428-1435. IEEE, (2014)Fault detection in multi-sensor networks based on multivariate time-series models and orthogonal transformations., , , , , and . Information Fusion, (2014)Data based modeling for PEM fuel cell monitoring - a test bench application, Part II., , and . CCA, page 256-261. IEEE, (2008)Reducing false positives for residual-based on-line fault detection by means of filters., , , , , and . SMC, page 2745-2750. IEEE, (2014)On the robustness of fault detection in reciprocating compressor valves., , , , , and . SMC, page 2733-2738. IEEE, (2014)Fuzzy fault isolation using gradient information and quality criteria from system identification models., , , , , and . Inf. Sci., (2015)