Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots

Industrial robots are widely used in modern factories. Robot faults and abnormal working state will lead to the shutdown of the production line inevitably. Robot condition monitoring can improve production capacity. However, due to the changes of robot in dynamic working state, this is a challenge. This paper presents a methodology of condition monitoring for industrial robots using vibration signals. The main purpose of this paper is to identify the occurrence of the fault and its different degrees. Experiments was performed on a 6-dof industrial robot (IR). Firstly, the Frequency Response Function of the IR was obtained by using the Experimental Modal Analysis method. And the characteristic frequency in each axis was found. Then, based on the Short-time Fourier Transform analysis method, the vibration data under normal conditions and different degrees of abnormal working conditions were analysed. In some characteristic frequency bands, the amplitude will increase with the increase of the binding force at the joint. Finally, this trend was further verified by the calculation of RMS value. The results show that the proposed frequency domain and model analysis method can monitor the operating condition of industrial robots.