CyPhEd - Sens
Cyber-physical, edge-based sensor network
Motivation
Condition monitoring of machine elements is of fundamental importance for the advancing digitalization in mechanical engineering. With the help of condition monitoring, critical operating states and incipient damage can ideally be detected immediately online. Through early detection and differentiation of incipient damage, machines can be maintained as needed, so that the planned maintenance intervals can be extended and costs can be saved. Plain bearings are a central machine element of rotating machines. The most important measured variables for determining lifetime-limiting conditions in plain bearings are bearing temperature, bearing load and lubrication gap height. Existing monitoring systems for lubrication gap height measurement are mounted subsequently on the plain bearings and can only be installed in multiple bearing systems with significant and thus economic effort. In contrast, the bearing load in the application can be determined from the operating parameters. However, this assumes an idealized power distribution between the bearings, so that in complex systems it is not possible to reliably determine individual bearing loads.
Research objectives
The primary goal of CyPhEd - Sens is to develop and apply cyber-physical edge-based sensor networks for early detection, prediction and differentiation of sliding bearing damage in rotating machinery. Sub-objectives of the project are:
- Development of innovative test procedures or training methodology of sensor networks on component and system level for differentiation of damage mechanisms
- Development of the required evaluation strategies for the model-based determination of maintenance requirements on the basis of the sensor data
- Definition and integration of validated, virtual sensors, for the monitoring of sliding bearings
- Development of an evaluation strategy for coupling the physical and virtual sensors
- Development of an edge-based evaluation unit with the property of interface-independent integration into higher-level control systems
Duration
01.07.2022 - 31.12.2024
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