(90 Min.) Case Study: Auto Adapting Vibration Monitoring Based on Process Conditions

Marcell Suranyi, PhD student, TU Graz Christian Reinbrecht, Product Manager, iba AG

Description

With more and more process and vibration data getting recorded for monitoring various industrial applications, we need smart solutions to automatically detect the interesting spots for analyzing. Especially for applications with changing process conditions, classical alarming methods are no longer sufficient.
The Institute of Machine Components and Methods of Development of the Graz University of Technology, AVL List GmbH and iba AG will present a case study on auto adapting vibration monitoring techniques. The project is a cooperation on improving Condition Monitoring Systems for automotive-test benches. We will show a spectrum analysis tool with self-learning reference spectrums for multiple operation points used for a gear monitoring system. With this method we could achieve that alarming is based on the process conditions and individual references for alarming are automatically learned by the system. This reduces the configuration effort and improves the reliability of the system. Furthermore, we will explain how this technique can be generally applied to other vibration monitoring challenges.

Takeaways

  1. Techniques for vibration monitoring based on process conditions.
  2. How tools with self-learning reference spectrums are working.
  3. What other applications these techniques can be applied to.

Bio - Marcell Suranyi

Marcell Suranyi received his B.S. degree at the Technical University of Budapest and graduated in 2014 at the RWTH Aachen University in automotive engineering and transport (M.S.). After his studies he worked as an analysis engineer in the engine simulation at AVL List GmbH. In 2017 he started at the Technical University Graz as a PhD student. His task is the development of condition monitoring methods for powertrain testbeds. His research is supported by the AVL List GmbH.

Bio - Christian Reinbrecht

Christian graduated from the Friedrich Alexander University of Erlangen with Master of Science in Mechatronic Engineering. During his studies he worked for a power plant manufacturer optimizing mathematical models for simulating Fluid Structure Interaction in vibrating pipes. For iba AG he is working as product manager for Condition Monitoring tools, including the whole spectrum from online vibration monitoring systems to expert vibration analysis tools. As product manager he is also offering support and training to customers on basics of vibration monitoring and how to use the iba-tools.