Solving the ADAPT Benchmark Problem - A Student Project Study



Erik Almqvist Daniel Eriksson Andreas Lundberg Emil Nilsson Niklas Wahlstro ̈m Erik Frisk Mattias Krysander


This paper describes a solution to the Advanced Diagnosis and Prognostics testbed (ADAPT) diagnosis benchmark problem. One main objective was to study and discuss how engineering students, with no diagnosis research background, would solve a challenging diagnosis problem. The study was performed within the framework of a final year project course for control engineering students. A main contribution of the work is the discussion on the development process used by the students.

The solution is based on physical models of components and includes common techniques from control theory, like observers and parameter estimators, together with established algorithms for consistency based fault isolation. The system is fully implemented in C++ and evaluated, using the DXC software platform, with good diagnosis performance.

How to Cite

Almqvist, E. ., Eriksson, D., Lundberg, A. ., Nilsson, E. ., Wahlstro ̈m N. ., Frisk, E., & Krysander, M. (2010). Solving the ADAPT Benchmark Problem - A Student Project Study. Annual Conference of the PHM Society, 2(2).
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diagnosis, residual generation, fault isolation, adapt benchmark

(Blanke et al., 2006) M. Blanke, M. Kinnaert, J. Lunze, and M. Staroswiecki. Diagnosis and Fault-Tolerant Control. Springer, 2006.
(de Kleer and Williams, 1987) J. de Kleer and B.C. Williams. Diagnosing multiple faults. Artificial Intelligence, 32(1):97–130, 1987.
(de Kleer et al., 1992) J. de Kleer, A. Mackworth, and R. Reiter. Characterizing diagnoses and systems. Arti- ficial Intelligence, 56, 1992.
(Gertler, 1998) J. Gertler. Fault Detection and Diagnosis in Engineering Systems. Marcel Dekker, Inc., 1998.
(KrysanderandFrisk,2008) MattiasKrysanderandErik Frisk. Sensor placement for fault diagnosis. IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, 38(6):1398–1410, 2008.
(Nyberg, 2006) Mattias Nyberg. A fault isolation algorithm for the case of multiple faults and multiple fault types. In Proceedings of IFAC Safeprocess’06, Bei- jing, China, 2006. Extended version to Appear in IEEE transaction on systems Man and Cybernetics - Part A.
(Pucel et al., 2009) X. Pucel, W. Mayer, and M. Stumpt- ner. Diagnosability analysis without fault models. In 20th International Workshop on Principles of Diagno- sis (DX-09), pages 67–74, Stockholm, Sweden, 2009.
(Reiter, 1987) R. Reiter. A theory of diagnosis from first principles. Artificial Intelligence, 32(1):57–95, 1987.
( ́`) ́` Trave-Massuyes et al., 2006 L. Trave-Massuyes, T. Es-
cobet, and X. Olive. Diagnosability analysis based on component supported analytical redundancy relations. IEEE Transactions on Systems Man and Cybernetics - Part A, 36(6), 2006.
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