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Classification and fault detection methods for fuel cell monitoring and quality control

Lowery, N. L.H., Vahdati, M. M., Potthast, R. W.E. and Holderbaum, W. (2013) Classification and fault detection methods for fuel cell monitoring and quality control. Journal of Fuel Cell Science and Technology, 10 (2). 021002. ISSN 1550-624X

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To link to this item DOI: 10.1115/1.4023565


In this paper, various types of fault detection methods for fuel cells are compared. For example, those that use a model based approach or a data driven approach or a combination of the two. The potential advantages and drawbacks of each method are discussed and comparisons between methods are made. In particular, classification algorithms are investigated, which separate a data set into classes or clusters based on some prior knowledge or measure of similarity. In particular, the application of classification methods to vectors of reconstructed currents by magnetic tomography or to vectors of magnetic field measurements directly is explored. Bases are simulated using the finite integration technique (FIT) and regularization techniques are employed to overcome ill-posedness. Fisher's linear discriminant is used to illustrate these concepts. Numerical experiments show that the ill-posedness of the magnetic tomography problem is a part of the classification problem on magnetic field measurements as well. This is independent of the particular working mode of the cell but influenced by the type of faulty behavior that is studied. The numerical results demonstrate the ill-posedness by the exponential decay behavior of the singular values for three examples of fault classes.

Item Type:Article
Divisions:Life Sciences > School of Biological Sciences > Department of Bio-Engineering
Interdisciplinary centres and themes > Energy Research
Science > School of the Built Environment > Energy and Environmental Engineering group
ID Code:32321
Publisher Statement:The Journal of Fuel Cell Science and Technology publishes peer-reviewed archival scholarly articles, Research Papers, Technical Briefs, and feature articles on all aspects of the science, engineering, implementation, and manufacturing of fuel cells of all types. Papers describing fuel cell case studies involving examples of real-life systems are also accepted.

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