A novel scheme on multi-channel mechanical fault signal diagnosis based on augmented quaternion singular spectrum analysis

In this paper, a novel multi-channel mechanical failure signal classification method based on augmented quaternion singular spectrum analysis (AQSSA) is proposed. Quaternion is used to couple four channels signal, and the quaternion trajectory matrixes can be developed as augmented quaternion matrix by using the feature of the quaternion. The singular value sequence including characteristic information can be extracted by quaternion singular value decomposition (QSVD) of the augmented trajectory matrix using its covariance matrix. The method of traditional singular spectrum analysis (SSA) can only analyze the single channel signal, however, AQSSA can fully use the correlation of multi-channel and reduce the loss of the effective information. Additionally, the main singular values are defined by some methods such as difference spectrum aimed, which has the limitation that major singular values can't be obtained under the high background noise. Thus, a concept of partial mean of singular value sequence is proposed, and it can be set as the standard of evaluating the trend of singular value sequence. In order to testify the performance of the proposed method, the numerical simulation signal and the fault vibration signal of bearing are simultaneously adopted to verify its effectiveness. The results indicate that the effectiveness of mechanical fault classification by the proposed method is superior to the traditional SSA method and the method of permutation entropy.