External Load-Based Sensing of Electrical Current Degradation in Industrial Robots

Published

November 3, 2021

Author(s)

Vinh Nguyen, Jeremy Marvel

Abstract

Industrial robotic arms are used extensively in sectors including manufacturing, healthcare, and infrastructure. Electrical current sensors located in the joints of industrial robots are critical for maintaining safe and optimal performance. However, the current sensors are subject to inaccuracies resulting from performance degradation, which results in safety hazards and sub-optimal performance. Thus, this research describes, develops, and experimentally validates an external load-based sensing system and methodology to detect unacceptable drift of current sensors in industrial robots. The initial states of the current sensors are recorded using low-cost load cells mounted on each joint of a UR10 robot. Thus, subsequent current sensor measurements can be compared to the initial state to determine statistically significant current degradation. This paper demonstrates the load-based sensing system is subject to less variability compared to current sensor verification under free loading conditions, and further analysis shows the load cells can be selectively mounted onto specific joints. In addition, a case study shows that the external load-based system can robustly detect simulated current sensor degradation. Thus, this sensing system is an efficient, robust, and cost-effective method towards detecting electrical current degradation in industrial robots.

Proceedings Title

Proceedings of IEEE Sensors 2021

Conference Dates

October 31-November 3, 2021

Conference Location

Sydney, AU

Pub Type

Conferences

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Keywords

degradation, sensor systems, load cell, industrial robot systems, verification, monitoring and diagnostics

Citation

Nguyen, V. and Marvel, J. (2021), External Load-Based Sensing of Electrical Current Degradation in Industrial Robots, Proceedings of IEEE Sensors 2021, Sydney, AU, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=932347 (Accessed April 19, 2024)