Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28744
Title: Fault diagnosis of analog circuits using systematic tests based on data fusion
Authors: Peng, M
Tse, CK 
Shen, M
Xie, K
Keywords: Analog circuit
Data fusion
Fault detection
Fault estimation
Fault verification
Issue Date: 2013
Publisher: Birkhäuser
Source: Circuits, systems and signal processing, 2013, v. 32, no. 2, p. 525-539 How to cite?
Journal: Circuits, systems and signal processing 
Abstract: An analog fault diagnosis approach using a systematic step-by-step test is proposed for fault detection and location in analog circuits with component tolerance and limited accessible nodes. First, by considering soft faults and component tolerance, statistics-based fault detection criteria are established to determine whether a circuit is faulty by measuring accessible node voltages. For a faulty circuit, fuzzy fault verification is performed using the accessible node voltages. Furthermore, using an approximation technique, the most likely faulty elements are identified with a limited number of circuit gain measurements at selected frequencies. Finally, employing the D-S evidence theory, synthetic decision is made to locate faults according to the results of fault verification and estimation. Unlike other methods which use a single diagnosis method or a particular type of measurement information, the proposed approach makes use of the redundancy of different types of measurement information and the combined use of different diagnosis methods so as to improve diagnosis accuracy.
URI: http://hdl.handle.net/10397/28744
ISSN: 0278-081X
EISSN: 1531-5878
DOI: 10.1007/s00034-012-9487-x
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