Research and application of monitoring data processing method based on SVM-SMA
BAI Jiyuan
XIAO Hang
WU Zhigao
Abstract：To improve the interpretability and real-time response capability of slope monitoring data in open-pit mines,this article proposes a monitoring data processing framework based on the combination of support vector machine(SVM)and simple displacement averaging(SMA)methods.This method first uses an SVM model to remove outliers introduced by measurement errors,environmental disturbances,and other factors,in order to improve the credibility and robustness of the data.Then,SMA smoothing is used to process the data,replacing point by point displacement values and extracting overall trends,reducing the impact of a single abnormal displacement value on the overall curve.The processed data curve has significantly improved in both trend significance and conciseness compared to the original data,reflecting more clearly the actual trend of slope displacement changes.This method effectively enhances the sensitivity and trend recognition ability of open-pit mine slope monitoring,thereby helping to achieve timely warning and effective management of slope displacement.
Keywords：support vector machinesimple displacement averagingtrend itemrobustnessdata analysis
Publication Date：2025-06-15
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 13-17 )