Helicopter rotor blades are prone to fatigue damage in flight. To solve the damage location problem, a damage monitoring and locating system was constructed. With the acoustic emission signals of the damage sources extracted by the kernel principal component analysis (KPCA), combining the support vector machine ( SVM) and its regression function, the damage sources of the rotor blades were located. The regional location accuracy after feature extraction is 100% and the average regression error is 7%, which are better than the original data location. Therefore, this method can effectively locate the damage source of the rotor blade, reduce the dimension of input data and the amount of calculation.