Intelligent Bearings for Engine Development and Validation

Authors

DipI.-Ing. Dr. R. Aufischer, Dr. B. Esmael, Dipl.-Ing. G. Hager, Dipl.-Ing. K. Hamdard, Dipl.-Ing. S. Schallmeiner, Miba Bearing Group, Miba Gleitlager Austria GmbH, Laakirchen;
Dipl.-Ing. T. Breiteneder, Graz University of Technology;
Dipl.-Ing. (FH) Dr. G. Taucher, Dipl.-Ing. J. Vystejn, Ao. Univ.-Prof. Dipl.-Ing. Dr. A. Wimmer, LEC GmbH, Graz

Year

2019

Print Info

Fortschritt-Berichte VDI, Reihe 12, Nr. 811

Summary

In order to improve and optimize engines further in terms of emission regulations and costs, further developments are required to the crank train and the plain bearings. Although state-of-the-art simulation systems consider friction reduction, reliability and costs, new and more sophisticated approaches are needed in order to incorporate real-world data. The use of highly sophisticated simulation systems in combination with adequate validation and feedback systems from operations is required, especially considering the need to coordinate short development times with the meeting of environmental targets. Condition monitoring, also of the engine, is already being undertaken in many large engine applications, but as yet the feedback from crank train/bearing values is not fully integrated.
To improve the validation process for crank train bearings, as well as to gather empirical values from engine operation, a system combining

• bearing sensors close to operational surface,
• wireless transmission and
• big data analysis to identify system errors and bearing operational risk

is set up to reduce validation time and to gain empirical values for operation of the crank shaft/bearing.
The article includes a basic description of the sensors, the wireless transmission, as well as data analysis as a first step, based on test rig sensor data for validation and for operational risk evaluation. The next steps for integration into monitoring systems are set out.