In order to improve the hidden fault detection rate of electromagnetic relay, a fault detection method based on super-path time measurement for electromagnetic relay is proposed in this paper. Firstly, the fuzzy threshold is optimized offline. Secondly, the superpath time data is predicted online using sliding window linear regression, and extended to predicted interval based on fitting error. Then, the relay super-path time measured data and predicted interval are converted into current fault evidence and predictive fault evidence using fuzzy threshold, and cumulative fault evidence is updated by iterative fusing cumulative, current and predictive fault evidence using interval evidence reasoning. Finally, the result of fault detection can be obtained from cumulative fault evidence according to fault criteria. The proposed method considers the slow-changing features of hidden relay fault and uncertainty in super-path time measurement process, so that the fault evidence is closer to the actual working condition of relay. The experimental results show that the proposed method has significant advantages in evidence accuracy and convergence speed, and can effectively improve the detection accuracy of electromagnetic relay hidden fault.