In the case of small samples with unknown probability distribution

the fuzzy equivalence relation and bootstrap maximum entropy models were proposed

and the variation process of vibration performance of rolling bearing was analyzed by variation probability. The original data of rolling bearing vibration acceleration was grouped into the samples

and then the intrinsic sample was selected to calculate the fuzzy equivalent coefficients between the samples. The bootstrap maximum entropy model was used to establish the probability density function of each sample

and the variation probability of each sample relative to the intrinsic sample was calculated by the intersection method. The relation curve between the fuzzy equivalent coefficients and variation probabilities was established to realize the monitoring of the variation process. The feasibility and correctness of the proposed model were verified by simulation and experimental cases. Experimental investigation showed that the variation probability curve presented nonlinear upward trend like “deck chair” with the increase of wear diameter

which corresponded to the three stages of rolling bearing wear

namely the initial running stage

the normal performance degradation stage and the performance deterioration stage.