Applicability of Context-Aware Health Monitoring to Hydraulic Circuits

Monitoring is an important aspect of operation and maintenance in virtually every industrial system. However, the extent and methods of monitoring vastly vary in different systems, from fully automated to fully manual. One of the challenges of automated monitoring is the tediousness of, and the extent of engineering time and effort required to develop necessary models or machine learning algorithms for the units to be monitored. Model-free monitoring, on the other hand, can save resources and efforts substantially. However, more often than not they have a very limited scope and application. Such a system is needed, for example, to monitor entire Heating, Ventilation and Air Conditioning (HVAC) systems, consisting of different types of sensors such as temperature, pressure, humidity or flow sensors. Recently, we proposed the Context-Aware Health Monitoring (CAH) system for model-free monitoring of any injective-function black-box, and it was tested successfully on an AC motor. In this paper, we evaluate the CAH system for an entirely different industrial use-case, that is, a hydraulic circuit. The results show the potential for considerable benefits in monitoring HVAC systems. Moreover, in the light of applying CAH to different use-cases which may potentially need a different setup of parameters, we performed a sensitivity analysis on the values of different parameters in the system. The results show the robustness of CAH with regard to the values of these parameters.