Gross Error Denoising Method for Slope Monitoring Data at Hydropower Station

There are mainly two types of errors existed in monitoring displacement of a rock slope: gross errors and random errors. Monitoring data is very important for the safety construction and operation of the Hydropower Station. The use of slope monitoring data for safety evaluation is influenced by the gross errors during the monitoring process. This paper presents a gross error denosing method for a nonlinear time series based on the three-standard-deviation rule (3-σ rule), and then reconstructing the time series by a first-order Lagrange interpolation method. The present method is applied to the gross error analysis of the slope displacement monitoring data collected at the Jinping I Hydropower Station. Computed results show that the first-order difference values of the gross errors can be above or below the upper or lower three-standard-deviation boundary, and the gross errors can be removed effectively.