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In order to conquer the defects of the classic orthogonal matching algorithm obtaining the atom set having the much time consumption, a feature extraction method based on compressed sensing theory and Tabu Optimization Algorithm is proposed. Firstly, the compressed sensing theory is introduced and the fault diagnosis principle is described, the sparse signal solving method using the l1 norm as the goal and satisfying the RIP rule. Then a sparse signal reconstruction method based on orthogonal matching is defined, and using minimizing remain value as the goal, the improved tabu optimizing algorithm is used to find the optimizing atom set in the atom space. Finally, the fault signal extraction algorithm is given by combining sparse encoding and tabu optimizing. The simulation experiment of rolling bearing fault signal is simulated in the Matlab simulation environment, and the result shows the method in this paper can effectively realize the sparse reconstruction for fault signal with strong noise, the method in this paper not only has higher signal noise rate, and also has the less remain error and simulation, and compared with the other methods, it has big priority.