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Monitoring for close proximity tunneling effects on an existing tunnel using principal component analysis technique with limited sensor data |
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| Affiliation: | 1. Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, USA;2. Korea Infrastructure Safety Technology Corporation, GoYang-Si, GyeongGi-Do, Republic of Korea;3. Dean of University of Graduate School, Florida International University, Miami, USA;1. Department of Civil, Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123 Trento, Italy;2. Department of Civil Engineering and Information Engineering, University of Rome TorVergata, Via Politecnico 1, 00133 Rome, Italy;3. Accademia Nazionale dei Lincei, Via della Lungara, 10, 00165 Rome, Italy;4. Department of Mathematics, University of Rome TorVergata, via della Ricerca Scientifica 1, 00133 Rome, Italy;1. Department of Mathematics, University of Ljubljana, and Institute for Mathematics, Physics and Mechanics, Jadranska 19, Ljubljana, Slovenia;2. Department of Mathematical Sciences, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa |
| Abstract: | A realistic field monitoring application to evaluate close proximity tunneling effects of a new tunnel on an existing tunnel is presented. A Principal Component Analysis (PCA)-based monitoring framework was developed using sensor data collected from the existing tunnel while the new tunnel was excavated. The developed monitoring framework is particularly useful to analyze underdetermined systems due to insufficient sensor data for explicit relations between force and deformation as the system input and output, respectively. The analysis results show that the eigen-parameters obtained from the correlation matrix of raw sensor data can be used as excellent indicators to assess the tunnel structural behaviors during the excavation with powerful visualization capability of tunnel lining deformation. Since the presented methodology is data-driven and not limited to a specific sensor type, it can be employed in various proximity excavation monitoring applications. |
| Keywords: | Close proximity tunneling Structural health monitoring Observational method Blind source separation Principal component analysis Underdetermined system Field monitoring |
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