土石坝监测数据的未确知滤波

 在分析粗差和异常值表征特性的基础上，结合未确知数学理论，提出了一种新的基于可信度概念的粗差探测方法——未确知滤波法（UF法），并深入研究了未确知滤波法阈值参数λ的取值方法，通过对该方法潜在问题的分析，提 出了相应的解决措施，即通过迭代滤波实现λ的优化，并运用列举法选择出最优的分段参数m，从而保证未确知滤波结果的正确性和可靠性。通过将未确知滤波法应用于土石坝监测数据的粗差探测和处理的实例，可以看出该方法克服了传统粗差处理方法存在的粗差互相污染、遮蔽、弃真以及难以区分粗差和异常值等问题。本方法还具有动态实时的特点尤其适合于处理观测周期长、测值跨度大的数据序列的粗差判别工作，是一种解决土石坝监测资料粗差判别及处理等问题的较为理想的方法。  

Unascertained Filtering Method for Monitoring Data of Earth Rock-fill Dams

In combination with unascertained mathematical theory, a unascertained filtering(UF) method is brought forward and the related parameters are investigated. Consequently, the latent problems are analyzed and some corresponding measures advanced. The value of λis optimized by alternative  calculation and the sectional parameter  m determined by enumeration, so the    validity and reliability of this method may be ensured. By using the UF method in the monitoring and experiment,  the problems on error hiding, normal data discarding and hard to differentiate errors from abnormality existing in traditional    methods for detecting errors are settled. The UF method possesses the characters    of dynamic and real -  time, and has the predominance in solving data error series with a long observation period and a wide span obtained from an ERD.  This new approach to process error is feasible and rather ideal.