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Health Monitoring of Strain Wave Gear on Industrial Robots

Heqing Sun, Jiafan Zhang

Year
2019
Citations
8

Abstract

Industrial robots play important parts in modern industries, and the low performance or even sudden breakdown of robots will cause losses due to poor product quality and plant down time. Robot condition monitoring technologies draw much attention from both academia and industry to study how to discover abnormality of robot as early as possible to minimize damages. Strain wave gear has been widely applied in industrial robot because of its desirable and attractive properties, such as small backlash and high compactness. This paper focuses on health monitoring solution of strain wave gear on industrial robots, mainly including sensor type selection and feature extraction. The proposed solution is verified on strain wave gear from Harmonic Drive and on thousands of ABB industrial robots in the factories.

Keywords

RobotStrain (injury)Computer scienceAcousticsPhysicsArtificial intelligenceMedicine

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