Research On Fault Diagnosis For Industrial Robots Based On HMM And Expert System

The industrial robots have greatly improved the productivity of the industry by its automation and high efficiency.However,on the other hand,the industrial robots will degrade or even fail in the production process.Therefore,it is necessary to study the fault diagnosis of industrial robots,and to identify the fault,locate the fault,and ultimately reduce the loss,improve the efficiency of maintenance.At present,there is a little research on the fault diagnosis of industrial robot.In this paper,the system structure and fault mechanism of industrial robot are analyzed,and the fault diagnosis method for industrial robot is proposed,which is based on Hidden Markov model and expert system.In this paper,the fault diagnosis technology for industrial robots is studied systematically,and the following work is done:First,analyzing of the structure of industrial robot and summing up the various fault types of industrial robots,such as open loop fault,transmission congestion fault,transmission clearance fault and so on.Then,a fault diagnosis method based on Hidden Markov model is proposed.Different feature extraction methods are designed for different types of fault and then the fault diagnosis algorithms are realized and the reliability of the algorithms is verified.Finally,considering that the fault types and fault diagnosis algorithms are difficult to organize,a solution based on expert system is proposed,and Visual Prolog is used to implement the system.Based on the experimental verification and simulation analysis,it is found that the fault diagnosis algorithm proposed in this paper is very accurate,and the expert system used in the process of fault diagnosis works properly.It is concluded that the method can solve some problems of fault diagnosis for industrial robots,and the method is of high practical value.