A novel method is proposed for rolling bearing performance degradation assessment.

Sensitive IMFs of improved EEMD are combined with SVD to extract time-frequency features.

Multi-domain feature vectors were constructed to characterize fault information more completely.

LLE effectively eliminates correlation and redundancy of vibration signal features.

As an assessment index the proposed relative compensation distance is more effective.