Fault detection and diagnosis based on extensions of PCA

Zhang, Yu, Bingham, Chris and Gallimore, Michael (2013) Fault detection and diagnosis based on extensions of PCA. Advances in Military Technology, 8 (2). pp. 27-41. ISSN 1802-2308

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Item Type:Article
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The paper presents two approaches for fault detection and discrimination based on principal component analysis (PCA). The first approach proposes the concept of y-indices through a transposed formulation of the data matrices utilized in traditional PCA. Residual errors (REs) and faulty sensor identification indices (FSIIs) are introduced in the second approach, where REs are generated from the residual sub-space of PCA, and FSIIs are introduced to classify sensor- or component-faults. Through field data from gas turbines during commissioning, it is shown that in-operation sensor faults can be detected, and sensor- and component-faults can be discriminated through the proposed methods. The techniques are generic, and will find use in many military systems with complex, safety critical control and sensor arrangements.

Keywords:Fault detection, principal component analysis, y-index, residual error, faulty sensor identification index, bmjfind
Subjects:H Engineering > H661 Instrumentation Control
Divisions:College of Science > School of Engineering
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ID Code:12956
Deposited On:16 Jan 2014 09:20

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