In model-based diagnosis, the candidate diagnostic results are generally characterized by all minimal hitting sets for the collection of all conflict sets. In this paper, a new method is proposed to judge a hitting set by the number of conflict sets corresponding to components, and the computing procedure is formalized by combining revised SE-tree (set enumeration tree) with closed nodes to generate all minimal hitting sets. Results show that because closed nodes are added into SE-tree, the search efficiency is highly improved. Furthermore, the proposed method is easy to be understood and implemented. Compared with other effective algorithms with completeness in some experimental tests, the diagnosis efficiency of our proposed method is higher, particularly for single- and double-fault diagnosis. In this model, the candidate diagnostic results are generally characterized by all minimal hitting sets for the collection of all conflict sets. In this paper, a new method is proposed to judge a hitting set by the number of conflict sets corresponding to components, and the computing procedure is formalized by combining revised SE-tree (set enumeration tree) with closed nodes to generate all minimal hitting sets. Compared with other effective algorithms with completeness in some experimental tests, the diagnosis efficiency of our proposed method is higher, particularly for single- and double-fault diagnosis.