This project has joined hands with nine famous universities and enterprises to tackle the problems of fault diagnosis and health assessment of domestic industrial robots. Five areas of research were carried out: 1) multi-source information acquisition and transmission methods for the industrial robot monitoring and control; 2）research on the modelling and fault mechanisms of electromechanical-control-perceptual coupling system of Industrial robots; 3) fault feature extraction and intelligent transfer diagnosis methods for industrial robots; 4) health assessment and performance prognosis of industrial robots; and 5) development and application of online alarm and offline diagnosis systems. The achievements include one set of online/offline fault diagnosis and health assessment system for industrial robots, four national standards for online monitoring, fault diagnosis, health assessment and predictive maintenance of industrial robots, several testing equipment and software systems for key components of industrial robots, and a database of typical fault cases of industrial robots. A large number of field tests, laboratory tests and computer simulation data sets of industrial robots have been collected with self-developed equipment and systems. The simulation and test objects cover many key components of industrial robots such as harmonic reducers, RV reducers, servo motors, servo drives and controllers. The collected data sets are composed of current, angle, position, attitude, vibration, temperature, sound, acoustic emission, abrasive particles, etc. All data is stored and fully shared in Excel, CSV and BMP formats.
