Research On Fault Detection And Identification Of Two Degrees Resilient Manipulator

Resilient robots can quickly and accurately detect the location and type of their own failure, and can spontaneously implement corresponding fault repair strategy to achieve the original function or continue an uncompleted given task. It has greatly improved the automatic and intelligent level of robots, and greatly extended the working life of the robot. Now, resilient robot has become a hot research field of robotics.Fault detection and identification technology is the basis of self-healing capabilities, accurate and timely fault diagnosis technology is the prerequisites of implementation of self-healing strategies. Fault detection and diagnosis technology is the basis of resilient function of robot. For fault detection of resilient robot, this paper presents a fault detection method based on multiple mathematic models and take two degrees of freedom manipulator as example performing simulation experiments to verify the feasibility and effectiveness of the proposed multi-model fault detection and diagnosis method.Based on Lagrange equation, this paper calculated the dynamics of an-DOF reconfigurable module robot, and a general application dynamic equations of reconfigurable module robot was given out. Based on the dynamic equations and unscented Kalman filter algorithm, a multi model fault detection and diagnosis algorithm was put forward to detect and identify the faults of reconfigurable robot. Many different unscented Kalman filters were used to track and estimate the true state of the robot system at the same second, then the generalized pseudo-Bayesian estimation was used to merge the information of multiple filters. Each filter corresponds to a different failure mode, according to the output of the filters, which mode the robot system is currently in is determined and complete the whole process of fault detection and diagnosis of the reconfigurable robot.In this paper, we took the basic two degrees robot as example, developed a comprehensive fault detection and diagnosis Simulink program on the Matlab simulation platform, performed a complete fault detection and diagnosis of simulation experiments, and effectively verified the feasibility and effectiveness of the proposed multi-model fault detection and diagnosis method.