Abstract: In order to recognize chipping of square shoulder milling cutter effectively which machining the aerospace structural part of titanium alloy,an algorithm for chipping of square shoulder milling cutter is proposed. Firstly,by building a milling test platform for square shoulder milling cutter, a set of experimental protocol is designed. X,Z,Y-direction vibration data of intact and chipping conditions is acquired by performing the experimental protocol. Then, according to the amplitude interference of the idling vibration data, the Y-direction vibration data is selected for calculation of moving average of RMS per revolution. Three eigenvalues are selected as input to the SVM model, and the classification training of the SVM model is obtained by two eigenvalues. Finally, through the vibration data under the same working conditions as identification input, the reliability of the SVM model of square shoulder milling cutter which machining the aerospace structural part of titanium alloy is successfully verified, and its average prediction accuracy is over 97%.