Abstract
The original Alternating Direction Method of Multipliers (ADMM) algorithm is suitable for solution of the convex function problem and is not suitable for nonlinear vibration characteristics. In the paper, the improved ADMM algorithm can be applied to sparse reconstruction of big data, sampled from rolling bearing vibration. On the basis of ADMM, ridge regression is applied to reduce the error of signal reconstruction. The improved ADMM uses a combinatorial optimization, which stores some initial decomposition and makes the subsequent iteration faster during the iteration process. Finally, the case of a rolling bearing vibration signal shows better reconstruction results.
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