Wissenschaftliches

• C. C. Zhu, „An Advanced Data-driven Fault Diagnosis Framework based on Symmetric Positive-Definite Matrices for Industrial Processes,” 2026, Universität Duisburg-Essen.

• C. C. Zhu, K. Kasten, J. Birk. S. Ding, „Ein alternatives, datenbasiertes FDI-Framework basierend auf SPD-Matrizen,“ at – Automatisierungstechnik, Vol. 72, No. 4, p. 321-334, 2024, Walter de Gruyter GmbH.

• K. Kasten, C. C. Zhu, J. Birk, S. Ding, „An Integral Monitoring Concept for Data-Driven Detection and Localization of Incipient Leakages by Fusion of Process and Environment Data,” Journal of Advanced Manufacturing and Processing, 4(3), 2022, DOI:10.1002/amp2.10133.

• C. C. Zhu, L. Li, S. Ding, „Multiplicative fault detection and isolation in dynamic systems using data-driven k-Gap metric based kNN Algorithm," IFAC-PapersOnLine 55.6 (2022): 169-174. SAFEPROCESS conference 2022.

• K. Kasten und C.C. Zhu, „Die topologische Facette des digitalen Zwillings als Basis zur automatisierten Kontextualisierung von Prozessdaten,“ automation 2020: 21. Leitkongress der Mess- und Automatisierungstechnik, VDI-Berichte, Vol. 2375, 2020, VDI-Verlag Düsseldorf.

• F. Hesselmann, C. C. Zhu, B. Köppen-Seliger, S. Ding, „Model Predictive Control Based Energy Flow Control in the Smart Grid,“ In 15th European Workshop on Advanced Control and Diagnosis (pp. 657-677). Cham: Springer International Publishing.