Fault Diagnosis Strategies for SOFC-Based Power Generation Plants
AbstractThe success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification) and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF) classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Costamagna, P.; De Giorgi, A.; Gotelli, A.; Magistri, L.; Moser, G.; Sciaccaluga, E.; Trucco, A. Fault Diagnosis Strategies for SOFC-Based Power Generation Plants. Sensors 2016, 16, 1336.
Costamagna P, De Giorgi A, Gotelli A, Magistri L, Moser G, Sciaccaluga E, Trucco A. Fault Diagnosis Strategies for SOFC-Based Power Generation Plants. Sensors. 2016; 16(8):1336.Chicago/Turabian Style
Costamagna, Paola; De Giorgi, Andrea; Gotelli, Alberto; Magistri, Loredana; Moser, Gabriele; Sciaccaluga, Emanuele; Trucco, Andrea. 2016. "Fault Diagnosis Strategies for SOFC-Based Power Generation Plants." Sensors 16, no. 8: 1336.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.