Monitoring for close proximity tunneling effects on an existing tunnel using principal component analysis technique with limited sensor data

•Validated principal component analysis method using a realistic field study of proximity tunneling.•Designed to analyze underdetermined systems due to insufficient sensor data.•Featured with visualization capability of spatio-temporal tunnel deformation.•Not limited to specific sensor types and does not rely on a priori physical information.•Wide applicability. 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.