In this paper we generalize to soft constraints the approximation techniques usually used for local consistency in classical constraint satisfaction and programming. The theoretical results show that this is indeed possible without loosing the fundamental properties of such techniques, and the experimental results (on partial arc-consistency) show that this work can help develop more efficient implementations for logic-based languages working with soft constraints.