Motor Operated Valve (MOV) periodic performance verification system using Power Line Signal Analysis (PoLine) is suggested in this thesis. As supplement or alternative methods to replace the sensor based “at the valve test”, MCC based methods, such as motor power monitor (MPM) and $MC^2$ method have been introduced. MCC method has some merits such as cost saving, lower radiation exposure, and shortened overhaul outage. However, the accuracy of MCC is twice that of at-the valve test method. Accordingly, MOV Users Group (MUG) recommended that MOVs with less than 25% operating margin are not the candidates for MCC based testing without additional justification. This is due to the inability to decide the stem factor and valve factor correctly. By adoption of nonlinear correlation method for stem factor estimation using static and dynamic test data, the PoLine method has better robustness against the motor performance degradation, voltage variation, and aging effects of packing and lubricant. Moreover, the optimum valve factor is found at the maximum differential pressure and thrust point. So, the rule to verify the valve factor is established. The PoLine also allows calculation of valve actuator capacity and condition monitoring without having sensors. For MOV abnormality detection, Wigner-Ville Distribution (WVD) model and threshold method for feature extraction is applied. Through the error analysis, the uncertainty of MOV factor in proposed method is calculated using the experiment data that is taken from both torque simulator and MOV experiment facility. For validation of PoLine, the overall error is calculated. The error is classified into two categories, the biased error and the random error. The biased error consists of the mean of the relative error between measured and estimated torque, and the stem factor. The random error corresponds with the statistical analysis of the measured torque, stem factor and motor electric data. The experiment result shows tha...