Integration of Condition Monitoring in Self-optimizing Function Modules Applied to the Active Railway Guidance Module (bibtex)
by Christoph Sondermann-Wölke, Walter Sextro
Abstract:
New mechatronic systems, called self-optimizing systems, are able to adapt their behavior according to environmental, user and system specific influences. Self-optimizing systems are complex and due to their non-deterministic behavior comprise hidden risks, which cannot be foreseen in the design phase of the system. Therefore, modifications of the ISO 17359 condition monitoring policy for being able to cope with this new kind of systems are presented. Besides avoiding critical situations evoked by self-optimization, the proposed concept uses self-optimization to increase the dependability of the system. This concept is applied to the active guidance module of an innovative rail-bound vehicle. First test drives provide information for the enhancement of the implementation of realtime switching to appropriate control strategies. The different control strategies are investigated in detail. It is illustrated that influences on the system like different track sections or the desired velocity of the RailCab effect the system and can lead to a higher amount of flange contacts, which indicate higher wear and thus a reduction of the availability of the system. Therefore, these influences should be minded within the condition monitoring policy. Consequently, this article presents the condition monitoring policy for self-optimizing function modules and its application to the active railway guidance module.
Reference:
Sondermann-Wölke, C.; Sextro, W.: Integration of Condition Monitoring in Self-optimizing Function Modules Applied to the Active Railway Guidance Module. International Journal On Advances in Intelligent Systems, volume 3, 2010.
Bibtex Entry:
@ARTICLE{Sondermann-Woelke2010,
  author = {Sondermann-W{\"o}lke, Christoph and Sextro, Walter},
  title = {Integration of Condition Monitoring in Self-optimizing Function Modules
	Applied to the Active Railway Guidance Module},
  journal = {International Journal On Advances in Intelligent Systems},
  year = {2010},
  volume = {3},
  pages = {65 - 74},
  number = {1 - 3},
  month = {September},
  abstract = {New mechatronic systems, called self-optimizing systems, are able
	to adapt their behavior according to environmental, user and system
	specific influences. Self-optimizing systems are complex and due
	to their non-deterministic behavior comprise hidden risks, which
	cannot be foreseen in the design phase of the system. Therefore,
	modifications of the ISO 17359 condition monitoring policy for being
	able to cope with this new kind of systems are presented. Besides
	avoiding critical situations evoked by self-optimization, the proposed
	concept uses self-optimization to increase the dependability of the
	system. This concept is applied to the active guidance module of
	an innovative rail-bound vehicle. First test drives provide information
	for the enhancement of the implementation of realtime switching to
	appropriate control strategies. The different control strategies
	are investigated in detail. It is illustrated that influences on
	the system like different track sections or the desired velocity
	of the RailCab effect the system and can lead to a higher amount
	of flange contacts, which indicate higher wear and thus a reduction
	of the availability of the system. Therefore, these influences should
	be minded within the condition monitoring policy. Consequently, this
	article presents the condition monitoring policy for self-optimizing
	function modules and its application to the active railway guidance
	module.},
  bdsk-url-1 = {http://www.thinkmind.org/index.php?view=article&articleid=intsys_v3_n12_2010_6},
  file = {:Sondermann-Woelke2010.pdf:PDF},
  keywords = {dependability; condition monitoring; selfoptimization; active railway
	guidance module},
  timestamp = {2011.02.21},
  url = {http://www.thinkmind.org/index.php?view=article&articleid=intsys_v3_n12_2010_6}
}