Mechanical fingertips can better perceive information about the motion state of an object, which is essential to achieve a stable grip similar to that of a human hand. In order to provide better perception of slip information of objects at the end of fingertips, this paper proposes a tactile slip signal recognition method based on discrete wavelet transform. Firstly, the information from the 25 contacts of the tactile sensor is fused using the correlation coefficient method; then the obtained information is wavelet transformed to observe the difference between the tangential force signal and the normal force signal in the frequency domain components. Finally, the discrete wavelet algorithm is used to differentiate between tangential and normal forces by setting appropriate wavelet coefficients and performing eigenvalue extraction through several trials. The experimental results show that the same wavelet coefficient threshold of 0.018 can still distinguish the pressure and slip signals well under the action of normal force of 3 N size, which is applied to three objects with different contours of spiky ball, smooth ball and bumpy ball to cause sliding respectively. The results of this paper can provide the basis and technical support for the robot to achieve stable grasping.