Abstarct: In this thesis, fault detection and isolation (FDI) has been discussed for a cable-driven parallel robot. To do so, first the conventional algorithms have been reviewed for FDI and then to test their performance, they have been implemented on a two-Dof robotic manipulator. In the simulation, it is assumed that errors are originated from electrical motors. Therefore, the errors in electrical resistance, damping coefficient of the bearing and also stiffness of the output shaft are considered as the source of error. By defining residuals for each error, we can detect the error and also its source uniquely. By conducting different simulations, it can be proven. Since there is uncertainty in the values of some parameters such as the electrical resistance, to reach better results, the FDI algorithm has been developed by considering uncertainness then implemented on a manipulator. To develop this algorithm, bond graph modeling has been used and the residuals are obtained from this graph Finally, the bond-graph model of the cable-driven parallel robot is drawn and the proposed FDI algorithm is developed for this robot, in the simulations, only the electrical resistance and damping coefficient of the bearing errors are considered, here the independent residuals are calculated for each error. Obtained results show that the residuals can determine exactly which item is faulty. These errors affected the path of end effector. Also the results shows the effect of the electrical error on the end effector path is trivial in the comparison with other errors.