The use of PCA and signal processing techniques for processing time-based construction settlement data of road embankments

Faisal Siddiqui, Paul Sargent, Gary Montague

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Instrumentation is beneficial in civil engineering for monitoring structures during their construction and operation.The data collected can be used to observe real-time response and develop data-driven models for predicting future behaviour. However, a limited number of sensors are usually used for on-site civil engineering construction due to cost restrictions and practicalities. This results in relatively small raw datasets, which often contain errors and anomalies. Interpreting and making judicious use of the available dataset for developingreliable predictive model represents a significant challenge. Therefore, it is essential to pre-process and clean the data for improving their quality. To date, little investigation has been performed in the application of such data cleaning methods to geotechnical engineering datasets collected from full-scale sites. The purpose of this study is to apply simple and effective data pre-processing techniques to site-data collected from a highway embankment constructed on a sequence of soil layers of different physical make-up and non-linear consolidation characteristics.Various cleaning methods were applied to magnetic extensometer data collected for monitoring settlement within foundation soils beneath the embankment. PCA was used to explore raw data, identify and remove outliers. Numerous filtering and smoothing methods were used to clean noise in the data and their results were further compared using RMSE and NMSE. The methods adopted for data pre-processing and cleaning proved very effective for capturing the raw settlement behaviour on site. The findings from this study would be useful to site engineers regarding complex decision-making relating to ground response due to embankment construction. This also has positive prospects for developing dynamic prediction models for embankment settlement.
Original languageEnglish
Article number101181
Pages (from-to)1-14
Number of pages14
JournalAdvanced Engineering Informatics
Early online date1 Oct 2020
Publication statusPublished (in print/issue) - 1 Oct 2020

Bibliographical note

Funding Information: Thanks go to Teesside University for funding this research. In addition, the authors would like to thank Northumberland County Council and AECOM Environment and Ground Engineering (Newcastle upon Tyne, UK) for providing all of the monitoring data from the Morpeth Northern Bypass. Publisher Copyright: © 2020 Elsevier Ltd Copyright: Copyright 2020 Elsevier B.V., All rights reserved.


  • Embankment construction
  • Soil settlement
  • Data pre-processing
  • Principal component analysis
  • Signal processing
  • Data cleaning


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