In order to improve the repairing effect of vibration signal, Bayesian compressed sensing (BCS) theory is introduced, and a Bayesian compressed sensingbased repairing method with empirical mode decomposition (EMD) is proposed to solve the problem of continuously missing signal restoration. For the randomly missing signals, Bayesian compressed sensing algorithm is designed to repair them based on the principle of compressed sensingbased repairing. While for the continuously missing signals, empirical mode decomposition is firstly performed on them, and then all the basic mode components obtained by decomposition are repaired by multitask Bayesian compressed sensing algorithm. Finally, all the repaired mode components are accumulated to get the whole signal. Experiments on open bearing data from Case Western Reserve University show that the proposed method is superior to orthogonal matching pursuit and regularized orthogonal matching pursuit in timefrequency domain, error, signaltonoise ratio and peak signaltonoise ratio. From the perspective of repairing effect, it is found that this method successfully restores the fault feature frequency in the basic mode components of the outer ring fault signal, and achieves the purpose of repairing.