Retrogressive Analysis of Industrial Robot Rotate Vector Reducer Using Acoustic Emission Techniques

Abstract

With the rapid development of robot technology, industrial robots have been widely used in mechanical manufacturing industry and integrated circuit manufacturing industry, maintenance developed into an important work with industrial robot service time growth. Rotate Vector (RV)reducer as the key component is the main fault source of industrial robot, most abrasion occurred in this component, but there are few researches focused on RV reducer fault diagnosis. In rotating mechanical fault diagnosis, there are many ways to get signals to analyze the working condition, such as using vibration and temperature signal, but abrasion signals of RV reducer are weak comparing with these signals. So, Acoustic emission (AE)is a new attempt in this domain recent years. However, there have been little or no researches in RV fault diagnosis by AE techniques. In this study, we designed an experiment platform and introduce AE into rotate vector (RV)reducer fault diagnosis. To the best of our knowledge, we are the first to design a series of quantitative experiments to do the qualitative analysis. By analyzing the time domain signals in two different channels, the AE signal source is recognized. And then the signal characteristics that related to the working load and rotation speed are analyzed in detail. Experimental results show that retrogressive analysis is able to accurately and effectively predict the degradation trend of RV reducer and also could work out the remain useful life of RV reducer.