Fault detection of robot joint bolt loosening based on electrical current signal

YANG Jiasong1, LIU Xiaoqin1, XU Kai1, WANG Dongxiao1, WU Xing1,2

Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (6) : 248-254.

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Journal of Vibration and Shock ›› 2023, Vol. 42 ›› Issue (6) : 248-254.

Fault detection of robot joint bolt loosening based on electrical current signal

  • YANG Jiasong1, LIU Xiaoqin1, XU Kai1, WANG Dongxiao1, WU Xing1,2
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Abstract

Aiming at the problem of bolt loosening at the joints of industrial robots, an electromechanical coupling model was established according to the robot joint structure, and then the base loosening was introduced to establish the system dynamics model of bolt loosening. The current signal of the simulation model is analyzed, and the law between the current signal and the bolt loosening fault is obtained. The research shows that in the case of loosening, sidebands appear near the current frequency of the motor, pulse shocks appear in the time-domain waveform, and energy fluctuations appear on the time-frequency diagram. The analysis results of the proposed model are in good agreement with the experimental data, and the research results have important reference value for the modeling and diagnosis of industrial robot joint bolt loosening faults.

Key words

RV reducer swing arm test bench / bolt looseness / current signal;Kinetic modeling;Time-frequency analysis

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YANG Jiasong1, LIU Xiaoqin1, XU Kai1, WANG Dongxiao1, WU Xing1,2. Fault detection of robot joint bolt loosening based on electrical current signal[J]. Journal of Vibration and Shock, 2023, 42(6): 248-254

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