Distributed Fiber Optic Sensing and Data Processing of Axial Loaded Precast Piles

The Pulse-Pre-Pump Brillouin Optical Time Domain Analysis (PPP-BOTDA) based distributed fiber optic sensing (DFOS) technique has a unique advantage of achieving full-distributed structural strain with cm-order spatial resolution, which is ideal for fine stress monitoring of the pile foundation. The high spatial resolution helped to detect local changes and defects while inevitably led to noisy data meanwhile, especially a certain part of anomalous sensing data. Therefore, a robust algorithm of random sampling consistency (RANSAC) was employed to extract and process the DFOS data. In a field static load test, the variation of strain along a precast pile was measured with PPP-BOTDA interrogator. The axial force and frictional resistance were calculated based on the RANSAC processed strain data. The pile-soil interface properties were estimated as well. It shows the feasibility and good performance of PPP-BOTDA in the measurement of precast piles stress test. The RANSAC proves to be an effective method for processing DFOS data with a certain number of outliers. This work presents a valuable reference for DFOS based pile stress test and data analysis which will promote its application in other related structural health monitoring purpose.

[1]  Mohammed Z. E. B. Elshafie,et al.  Distributed Fiber Optic Sensing of Axially Loaded Bored Piles , 2018 .

[2]  Hao Zhang,et al.  Performance Evaluation of PPP-BOTDA-Based Distributed Optical Fiber Sensors , 2012, Int. J. Distributed Sens. Networks.

[3]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[4]  Kenichi Soga,et al.  Distributed fiber optics sensors for civil engineering infrastructure sensing , 2018 .

[5]  Bin Shi,et al.  Interfacial characterization of soil-embedded optical fiber for ground deformation measurement , 2014 .

[6]  Luca Schenato,et al.  Distributed strain measurements in a CFA pile using high spatial resolution fibre optic sensors , 2018 .

[7]  Liang Chen,et al.  Recent Progress in Distributed Fiber Optic Sensors , 2012, Sensors.

[8]  Bin Shi,et al.  Characteristics and Application of BOTDR in Distributed Detection of Pile Foundation , 2010 .

[9]  K. Soga,et al.  Monitoring Twin Tunnel Interaction Using Distributed Optical Fiber Strain Measurements , 2012 .

[10]  Ping Wang,et al.  A new method for deformation monitoring on H-pile in SMW based on BOTDA , 2015 .

[11]  Dan Zhang,et al.  Data processing in BOTDR distributed strain measurement based on pattern recognition , 2010 .

[12]  Zhishen Wu,et al.  Distributed optic fiber sensing for a full-scale PC girder strengthened with prestressed PBO sheets , 2006 .

[13]  António Barrias,et al.  A Review of Distributed Optical Fiber Sensors for Civil Engineering Applications , 2016, Sensors.

[14]  Lei Gao,et al.  Experimental Study on Deformation Monitoring of Bored Pile Based on BOTDR , 2019, Applied Sciences.

[15]  K. Krebber,et al.  Fiber-optic sensor applications in civil and geotechnical engineering , 2011 .

[16]  Ke Li,et al.  Test on application of distributed fiber optic sensing technique into soil slope monitoring , 2009 .

[17]  Hisham Mohamad,et al.  Instrumented pile load testing with distributed optical fibre strain sensor , 2015 .

[18]  Farhad Ansari,et al.  Detection and monitoring of surface micro-cracks by PPP-BOTDA. , 2015, Applied optics.

[19]  Nicholas R. Gans,et al.  Predictive RANSAC: Effective model fitting and tracking approach under heavy noise and outliers , 2017, Comput. Vis. Image Underst..

[20]  Pj Bennett,et al.  Performance Monitoring of a Secant-Piled Wall Using Distributed Fiber Optic Strain Sensing , 2011 .

[21]  Bin Shi,et al.  Application of a distributed optical fiber sensing technique in monitoring the stress of precast piles , 2012 .

[22]  Guo-Wei Li,et al.  Recent progress of using Brillouin distributed fiber optic sensors for geotechnical health monitoring , 2017 .

[23]  Luca Schenato,et al.  A Review of Distributed Fibre Optic Sensors for Geo-Hydrological Applications , 2017 .

[24]  Andrew Zisserman,et al.  MLESAC: A New Robust Estimator with Application to Estimating Image Geometry , 2000, Comput. Vis. Image Underst..

[25]  Bo Liu,et al.  Mechanical behaviors of SD and CFA piles using BOTDA-based fiber optic sensor system: A comparative field test study , 2017 .

[26]  Genda Chen,et al.  Measurement accuracy improvement of Brillouin signal using wavelet denoising method , 2009, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[27]  Y. Bao Novel applications of pulse pre-pump Brillouin Optical Time Domain Analysis for behavior evaluation of structures under thermal and mechanical loading , 2017 .