Online Condition Monitoring of Hydraulic Oils in the Steel Industry

The continuous availability of information on the condition of oil and in turn of lubricated equipment allows the fail-free operation of machines. Therefore an increasing demand for online oil condition monitoring exists. The choice of sensors and data processing have to be adapted to the monitored system for a proper detection of critical oil conditions. This demands comprehensive investigations, taking into account the knowledge on oil type, stresses in operation, and response of the sensors. In this work this selection procedure is demonstrated for ester-based hydraulic fluids. By using adjusted artificial alterations with integrated sensor systems, data for an algorithm was generated. In that way, the acidification can be determined independently of the alteration mechanism taking into consideration disturbing influences like varying temperature or moisture. The developed algorithm was verified using laboratory experiments. Furthermore, results from field tests showed the applicability under real operating conditions. © 2018, Springer-Verlag GmbH Austria, ein Teil von Springer Nature.