TUD

Institut für Automatisierungstechnik

Morozov, Andrey; Dr.-Ing.

Dr.-Ing. Andrey Morozov

Telefon: +49 (0) 351 46 33 22 02

Fax: + 49 (0) 351 46 33 70 39

E-Mail:  andrey.morozov (at) tu-dresden.de

Besucheradresse:
Barkhausen-Bau, Raum E29
Georg-Schumann-Str. 11
01187 Dresden

Postanschrift (Briefe):
Technische Universität Dresden
Fakultät Elektrotechnik und Informationstechnik
Institut für Automatisierungstechnik
01062 Dresden

Postanschrift (Pakete u.ä.):
Technische Universität Dresden
Fakultät Elektrotechnik und Informationstechnik
Institut für Automatisierungstechnik
Helmholtzstraße 10
01069 Dresden

Kurzvorstellung des Promotionsthemas

Dual-graph Model for Error Propagation Analysis of Mechatronic Systems

Abstract:
Error propagation analysis is an important part of a system development process. This research addresses a model-based analysis of spreading of transient data errors through mechatronic systems. Error propagation models for such kind of systems must use a high abstraction level that allows the proper mapping of the mutual interaction of heterogeneous system elements such as software, hardware and physical parts. A number of appropriate approaches have been introduced in recent years. The majority of them are based only on a system data flow representation. This research shows that the system control flow has to be considered as well for a complete picture of error propagation. A core part of this work is a new probabilistic error propagation model based on two digraphs: a control flow graph and a data flow graph. The structures of these graphs can be derived systematically during a system development process. The knowledge about an operational profile and individual parameters of the system elements allows the definition of additional system properties. A discrete time Markov chains model is applied for simultaneous analysis of control flow and data flow of the system. This Markov chain can be generated automatically using the framework of the introduced dual-graph error propagation model. Specific computation of this Markov chain gives the distribution of the probabilities of different erroneous and error-free scenarios of system operation. It helps to perform a precise reliability evaluation, to speed up fault localization and error detection processes, and to develop an effective testing strategy.

Keywords:
Error propagation, Mechatronics, Control flow, Data flow, Discrete time Markov chain, Reliability, Fault localization, System testing

Stand: 29.07.2019 08:53
Autor: Webmaster IFA