High-Frequency Sensor Signals from a One-Year Long Accelerated Wear Test of a KUKA KR16 Industrial Robotic Arm

<p dir="ltr">The data within this dataset was generated by a <b>KUKA KR16 L6</b> robot being monitored during an accelerated wear test (AWT) at the <b>Advanced Manufacturing Research Centre's</b> <b>(AMRC's) Integrated Manufacturing Group (IMG)</b> to help develop methods of wear and fault/anomaly detection. This includes data from retrofitted <b>accelerometers</b>, <b>current transducers</b> and <b>RTD</b> temperature sensors, stored in .zip files of <b>MATLAB structures</b>.</p><p dir="ltr">The AWT consisted of joint 3 of the robot rotated in isolation back and forth at 100% speed and acceleration 24/7 for 13 months with maximum payload on the end effector and the supplementary payload. During the AWT, the robot suffered from a naturally occurring oil leak and a controlled set of crashes.</p><p dir="ltr">Please see the '<i>README.txt'</i> file for further information on the dataset, and the '<i>Fingerprint routine.mp4'</i> file for an illustration of the routine undertaken by the robot.</p><p dir="ltr">The work behind creating this dataset was presented at the IEEE CASE 2024 conference, Bari, Italy:</p><p dir="ltr"><i>J. Moore and D. Sawyer, "Equipment Health Monitoring for Industrial Robotic Arms," 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), Bari, Italy, 2024, pp. 1853-1860, doi: 10.1109/CASE59546.2024.10711629.</i></p>