Autarkic sensory foil bearing

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Air bearings are used for very high speed shafts (>100,000 rpm) due to the low lubrication gap friction and the pollutant series lubrication. This makes them particularly interesting for air compressors and in medical applications. Even though air bearings are almost frictionless in operation, the lower speed range is characterized by high level of mixed friction. Due to the low speed and the low viscosity of the air, a sufficiently load-bearing lubricant film cannot be formed. Frequent cycling or long dwell times in this range lead to significantly increased wear and thus to a reduction in the remaining service life. Overload, severe imbalance or camber can also damage the air bearing. This effect is intensified by manufacturing deviations, the effects of which are difficult to predict. The aim of the project is to achieve on-line condition monitoring of film air bearings by sensor integration. On-line monitoring allows a clean identification of unfavorable operating points and a more accurate remaining life estimation, thus contributing to greater reliability and early detection of failures. Relevant bearing parameters are the minimum lubrication gap height, the lubrication gap temperature, or current film shape and film temperature in film bearings, the trajectory curve or orbit of the shaft center point and the wear in the bearing. The challenge is therefore to integrate suitable sensors for recording the relevant measured variables in the aerodynamic bearing. This implies high demands on the integrability and reliability of these sensors, which must also function reliably in the range of high speeds or with high-frequency excitation and possibly at high bearing temperatures.This condition monitoring is achieved by the complete integration of a complex condition monitoring system. Power supply, data acquisition, preparation, processing and evaluation are performed in the bearing. After processing, the bearing status is forwarded by wireless data transmission. To evaluate the operating condition, the temperature, air gap, unbalance, speed, temperature of the bearing, film elongation and shaft tilting are monitored. The evaluation is carried out by an artificial neural network which is implemented in a microcontroller located in the bearing. The operating points, energy generation, data acquisition and processing of the sensor-integrated bearing are being investigated and further developed with the aid of an initial prototype in two test rigs. The monitoring of the start-up and lift-off behavior up to 30,000 rpm and the operating behavior up to 120,000 rpm are being tested. The data obtained here will be used to further refine the network and improve the prototype.