Title
Fault Diagnosis Strategies for SOFC-Based Power Generation Plants.
Abstract
The 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.
Year
DOI
Venue
2016
10.3390/s16081336
SENSORS
Keywords
Field
DocType
solid oxide fuel cell (SOFC),quantitative modelling,fault detection and isolation (FDI),model-based and data-driven strategies,pattern recognition,random forest (RF)
Signature matrix,Plant Components,Simulation,Fault detection and isolation,Fuel cells,Electronic engineering,Engineering,Quantitative model,Statistical classification,Random forest,Reliability engineering,Electricity generation
Journal
Volume
Issue
Citations 
16
8
1
PageRank 
References 
Authors
0.36
15
7
Name
Order
Citations
PageRank
Paola Costamagna110.36
Andrea De Giorgi241.76
Alberto Gotelli310.36
Loredana Magistri410.36
Gabriele Moser591976.92
Emanuele Sciaccaluga610.36
A Trucco7589.23