Comparison of Data Sources for Robot Gear Condition Monitoring

摘要

Industrial robot gear condition monitoring has the potential to increase the productivity of highly automated production lines. In order to implement an effective condition monitoring system, data must be collected which correlates with the robot gear’s state of health. The sensor choice and the characteristics of these sensors are crucial to the success of a condition monitoring system. Hence, we compare current and vibration sensor data from different accelerated robot gear wear tests in different frequency ranges to determine a suitable sensor setup. In the presented experiments, both data sources detect faults at a similar point in time and the variation of the frequency ranges has different effects on the data quality.