EARLY DETECTION OF OPERATIONAL INSTABILITY IN COLLABORATIVE ROBOTS THROUGH JOINT-LEVEL THERMAL AND ELECTRICAL SIGNATURES
DOI:
https://doi.org/10.69980/e5fypj84Keywords:
Collaborative robots, Operational instability, Condition monitoring, Thermal signatures, Electrical signaturesAbstract
Operational instability in collaborative robots can interrupt production and reduce the reliability of human–robot manufacturing environments, creating a need for effective condition-monitoring approaches. This study investigated joint-level thermal and electrical signatures for identifying unstable cobot operation. A dataset comprising 7,409 observations from 240 operational cycles was analyzed, with 518 observations classified as unstable based on protective-stop or grip-loss events. Temperature, motor current, joint speed, and tool-current measurements were evaluated using statistical analysis and predictive modelling. Electrical signatures showed clearer differentiation between operating states than thermal measurements, with significant current differences observed in five of the six joints. J3 exhibited the strongest electrical change during instability. Current–temperature correlations were generally weak, indicating that thermal and electrical measurements represented complementary aspects of joint behavior. Predictive modelling showed stronger discrimination with Random Forest than Logistic Regression, while J3 current emerged as the most influential predictor. The findings demonstrate the potential of joint-specific multisensor analysis for recognizing operational instability and provide a basis for developing condition-monitoring strategies for collaborative robotic systems.
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