Compact power units - Smart through sensor technol

Friday, April 28, 2017

Compact power units - Smart through sensor technology

Within the concept "Predictive Maintenance", built-in sensors and the intelligent evaluation of the collected data monitor the state of the hydraulic system permanently during operation. IO-Link-capable sensors can also be installed within the HAWE Hydraulik compact power units resulting in a particularly space-saving and intelligent solution for industrial applications.

Hydraulic power units are regarded as reliable subsystems within machine tools and manufacturing plants. Regular maintenance prevents unplanned failures and reduces downtime. Today the essential functions are already pre-warned monitored by switches. Thus, e.g. a required exchange of the oil filter can be scheduled in a planned maintenance period.

In the "Predictive Maintenance" concept, built-in sensors continuously monitor the system status. If these sensors are IO-Link-capable, the recorded data can be transferred and stored to an evaluation unit. This data can then be forwarded to a higher-level system via a fieldbus.

However, the real know-how is to evaluate the recorded sensor data in appropriate algorithms. Some short examples give a first impression. Thus, a change in the differential pressure on the filter can be used to predict a specific time window for a required exchange.  A test cycle for monitoring the preload pressure in the hydraulic accumulator can evaluate this information and point at the correct time to the refilling. Continuous filling level monitoring can detect external leakages and initiate appropriate measures. The continuous temperature tracking can prematurely indicate standstill due to overheating. Many other evaluations are possible, like monitoring of the pump wear and the assessment of the oil state. HAWE Hydraulik will present a study on the basis of a speed-controlled compact unit of the HKF series in which the corresponding sensor system is installed at the Hanover Fair 2017 in Hall 21 G30. First possibilities for data evaluation are implemented, further algorithms will follow.

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