Abstract
Condition monitoring of industrial robots has the potential to decrease downtimes in highly automated production systems. In this context, we propose a new method to evaluate health indicators for this application and suggest a new health indicator (HI) based on vibration data measurements, Short-time Fourier transform and Z-scores. By executing the method, we find that the proposed health indicator can detect varying faults better, has lower temperature sensitivity and works better in instationary velocity regimes compared to several state-of-the-art HIs. A discussion of the validity of the results concludes our contribution.
Highlights
We propose a method to evaluate the suitability of health indicator (HI) for the task of robot gear condition monitoring
6600 experiment and less noisy behavior in the ABB IRB 7600 experiment, we suggest the use of the Z-score-HI for the condition monitoring of robot gears
We chose window lengths that lead to a good compromise between time and frequency resolution by inspecting spectrograms created with different window lengths
Summary
This section is divided in two parts. First, the newly developed HI is presented.Afterwards, the methodologies to evaluate the HI’s performance and data sets used in this context are explained.2.1. This section is divided in two parts. Afterwards, the methodologies to evaluate the HI’s performance and data sets used in this context are explained. The concept of the newly designed HI is based on two cornerstones. To deal with instationary velocity regimes, which are found in robot applications due to the typical movement patterns of a robot, the HI is based on time–frequency-domain data. The HI must take into account a certain variance of this data due to environmental changes such as temperature fluctuations. This is realized by the concept of Z-scores, a common similarity measure from statistics [34].
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