Automatic systems diagnosis without behavioral models

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Shekhar Gupta (Author) Other; Rui Abreu (Author) FEUP; Johan de Kleer (Author) Other; Arjan J C van Gemund (Author) Other

Conference proceedings International

Title: 2014 IEEE AEROSPACE CONFERENCE

Pages: 1-8

IEEE Aerospace Conference

Big Sky, MT, MAR 01-08, 2014

Indexing

ISI Web of Knowledge - 0 Citations

ISI Web of Science

Scopus - 1 Citation

INSPEC

Scientific classification

FOS: Engineering and technology > Mechanical engineering

CORDIS: Technological sciences

Other information

Authenticus ID: P-009-NY7

DOI: 10.1109/aero.2014.6836252

Abstract (EN): Recent feedback obtained while applying Model-based diagnosis (MBD) in industry suggests that the costs involved in behavioral modeling (both expertise and labor) can outweigh the benefits of MBD as a high-performance diagnosis approach. In this paper, we propose an automatic approach, called ANTARES, that completely avoids behavioral modeling. Decreasing modeling sacrifices diagnostic accuracy, as the size of the ambiguity group (i.e., components which cannot be discriminated because of the lack of information) increases, which in turn increases misdiagnosis penalty. ANTARES further breaks the ambiguity group size by considering the component's false negative rate (FNR), which is estimated using an analytical expression. Furthermore, we study the performance of ANTARES for a number of logic circuits taken from the 74XXX/ISCAS benchmark suite. Our results clearly indicate that sacrificing modeling information degrades the diagnosis quality. However, considering FNR information improves the quality, attaining the diagnostic performance of an MBD approach.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8