F2010C180
Method for Model based Monitoring of Complex Mechatronic Systems
KEYWORDS: Test stand; simulation; condition monitoring; artificial neural networks;
When developing complex mechatronic systems, efficient and automated methods and processes play an important role in compensating the increasing time and cost pressure. High complexity leads, among other things, to a high level of possible error sources in development and operation. Consequently the demand to monitor such systems while operating on the one hand and in the validation phase on the test stand on the other has increased in order to detect and avoid possible system errors in advance. This allows an considerable reduction of test stand time and most notably the test bench costs. Damage to the test bench as well as unintended destruction of pre-series test items is not acceptable these days. Generating incorrect data due to unkown effects, especially in long-term test runs, bears an additional risk. This poses new challenges to test stand operators that cannot be solved with conventional tools of test stand monitoring. New tools, that recognize critical states in time and thereby reduce or even avoid the downtime of test stands and the number of damaged prototypes, have to be created. For this purpose advanced monitoring mechanisms must be developed and tested. A method for model based test stand monitoring is introduced in this abstract. This method combines conventional monitoring models with artificial neural networks in an innovative way. This approach solves the trade-off between flexibility in the day-to-day test stand operation and the traceability of the source of defect. In addition to preventing damage from test items and test stand, the presented method also guarantees the validation of measured data. The following examples affect the quality of measured data: - incorrect sensor signals - temperature influence - parasitic friction in the testing device o bearing friction e.g. in the engine when measuring the loading via motor current o bearing friction between torque test ports - slippage in connecting parts The control process has to recognize these causes and display them to the test stand operator. Moreover an offline anayisis of the cause of error, which allows access to collective expert knowledge, is being integrated in order to detect the sources of occurring errors. In collaboration with the Kröhnert Infotecs GmbH this concept is being translated into a monitoring system.The prototypical implementation takes place at IPEK's engine assembly test stand. With this example the whole workflow from system analysis and creation of the monitoring model all the way to the operation on a test stand is validated under real circumstances. This method also qualyfies for being transferred into the simulation, into hardware-in-the-loop environments as well as into the vehicle itself. Because of this continuity and modularity it is for example now possible to monitor the interaction of new functions in the controller with already existing hardware components in the validation process.
This abstract is supplemented by a PDF, which can be viewed here.