A new microprocessor-based protection algorithm is presented. The sampling signals are decomposed to smooth signals and detail signals by multi-scale wavelet transform. Utilizing modulus maximum method for detail signals to determine whether or not an exception occurs and when it occurs. Entering the fault handler once the exception generates and activating the Kalman filter. The smooth signals are adopted to update the observations of the filter to reduce the interference of fault signals’ transient noise, which can improve the convergence speed of the filter algorithm. Detail signals are adopted to calculate the measurement noise variance in real-time to improve the convergence precision of the filter algorithm. Wavelet analysis method can detect and judge the fault for the first time, while the estimated fundamental frequency component of fault signals combined with relay protection principle are adopted to judge the fault again, which can improve the reliability of the protection algorithm. The Matlab/Simulink simulation system is built and the results show the feasibility and effectiveness of the algorithm.