Title:
Automated Piecewise Linear Regression for Analyzing Structural Health Monitoring Data
Author(s):
Harshita Garg, Kai Yang, Anthony G. Cohn, Duncan Borman, Sreejith V. Nanukuttan, P.A. Muhammed Basheer
Publication:
Materials Journal
Volume:
121
Issue:
2
Appears on pages(s):
93-104
Keywords:
artificial intelligence (AI); automated clustering-based piecewise linear regression (ACPLR); diffusion coefficient; electrical resistance; in-service performance; structural health monitoring (SHM)
DOI:
10.14359/51740370
Date:
4/1/2024
Abstract:
The recent increased interest in structural health monitoring (SHM)
related to material performance has necessitated the application
of advanced data analysis techniques for interpreting the realtime
data in decision-making. Currently, an accurate and efficient
approach for the timely analyses of large volumes of uncertain
sensor data is not well-established. This paper proposes an automated
clustering-based piecewise linear regression (ACPLR)-SHM
methodology for handling, smoothing, and processing large data
sets. It comprises two main stages, where the gaussian weighted
moving average (GWMA) filter is used to smooth noisy data
obtained from electrical resistance sensors, and piecewise linear
regression (PLR) predicts material properties for assessing the
performance of concrete in service. The obtained values of stabilized
resistance and derived values of diffusion coefficients using
this methodology have clearly demonstrated the benefit of applying
ACPLR to the sensor data, thereby classifying the performance of
different types of concrete in service environments.
Related References:
ACI Committee 201, 2016, “Guide to Durable Concrete (201.2R-16),” American Concrete Institute, Farmington Hills, MI, 84 pp.
ACI Committee 444, 2021, “Structural Health Monitoring Technologies for Concrete Structures—Report (ACI PRC-444.2-21),” American Concrete Institute, Farmington Hills, MI, 110 pp.
Ahmed, Z.; Ali, J. S. M.; Rafeeq, M.; and Hrairi, M., 2019, “Application of Machine Learning with Impedance Based Techniques for Structural Health Monitoring of Civil Infrastructure,” International Journal of Innovative Technology and Exploring Engineering (IJITEE), V. 8, No. 6S4, pp. 1139-1148.
Aydin, K., and Kisi, O., 2015, “Damage Diagnosis in Beam-Like Structures by Artificial Neural Networks,” Journal of Civil Engineering and Management, V. 21, No. 5, pp. 591-604. doi: 10.3846/13923730.2014.890663
Azarsa, P., and Gupta, R., 2017, “Electrical Resistivity of Concrete for Durability Evaluation: A Review,” Advances in Materials Science and Engineering, pp. 1-30. doi: 10.1155/2017/8453095
Ballo, F.; Gobbi, M.; Mastinu, G.; and Previati, G., 2014, “Advances in Force and Moments Measurements by an Innovative Six-Axis Load Cell,” Experimental Mechanics, V. 54, No. 4, pp. 571-592. doi: 10.1007/s11340-013-9824-4
Basheer, P. A. M.; Gilleece, P. R. V.; Long, A. E.; and Mc Carter, W. J., 2002, “Monitoring Electrical Resistance of Concretes Containing Alternative Cementitious Materials to Assess Their Resistance to Chloride Penetration,” Cement and Concrete Composites, V. 24, No. 5, pp. 437-449. doi: 10.1016/S0958-9465(01)00075-0
Basheer, P. A. M.; Grattan, K. T.; Sun, T.; Long, A. E.; McPolin, D.; and Xie, W., 2004, “Fiber Optic Chemical Sensor Systems for Monitoring pH changes in Concrete,” Advanced Environmental, Chemical, and Biological Sensing Technologies II, International Society for Optics and Photonics, Bellingham, WA, pp.144-153.
Basnayake, K.; Mazumder, A. F.; Attanayake, U.; and Berke, N. S., 2020, “Assessment of Concrete Curing Duration using Bulk Electrical Conductivity and Porosity,” Transportation Research Record: Journal of the Transportation Research Board, V. 2674, No. 10, pp. 261-268. doi: 10.1177/0361198120935114
Berke, N. S., 1988, “Microsilica and Concrete Durability,” Transportation Research Record: Journal of the Transportation Research Board, V. 1204, pp. 21-26.
Bjegović, D.; Krstić, V.; Mikulić, D.; and Ukrainczyk, V., 1995, “C-D-c-t Diagrams for Practical Design of Concrete Durability Parameters,” Cement and Concrete Research, V. 25, No. 1, pp. 187-196. doi: 10.1016/0008-8846(94)00126-J
Brownjohn, J. M. W.; de Stefano, A.; Xu, Y. L.; Wenzel, H.; and Aktan, A. E., 2011, “Vibration-Based Monitoring of Civil Infrastructure: Challenges and Successes,” Journal of Civil Structural Health Monitoring, V. 1, No. 3-4, pp. 79-95.
Bungey, J. H.; Millard, S. G.; and Grantham, M. G., 2006, Testing of Concrete in Structures, fourth edition, Taylor & Francis, New York, 352 pp.
Chandrasekaran, S., 2019, “Structural Health Monitoring: An Overview,” Structural Health Monitoring with Application to Offshore Structures, World Scientific, pp. 1-50.
Cosoli, G.; Mobili, A.; Tittarelli, F.; Revel, G. M.; and Chiariotti, P., 2020, “Electrical Resistivity and Electrical Impedance Measurement in Mortar and Concrete Elements: A Systematic Review,” Applied Sciences, Basel, Switzerland, V. 10, No. 24, pp. 1-42. doi: 10.3390/app10249152
Demircilioğlu, E.; Teomete, E.; Schlangen, E.; and Baeza, F. J., 2019, “Temperature and Moisture Effects on Electrical Resistance and Strain Sensitivity of Smart Concrete,” Construction and Building Materials, V. 224, No. 11, pp. 420-427. doi: 10.1016/j.conbuildmat.2019.07.091
Diez, A.; Khoa, N. L. D.; Makki Alamdari, M.; Wang, Y.; Chen, F.; and Runcie, P., 2016, “A Clustering Approach for Structural Health Monitoring on Bridges,” Journal of Civil Structural Health Monitoring, V. 6, No. 3, pp. 429-445. doi: 10.1007/s13349-016-0160-0
Dong, C. Z., and Catbas, F. N., 2021, “A Review of Computer Vision-Based Structural Health Monitoring at Local and Global Levels,” Structural Health Monitoring, V. 20, No. 2, pp. 692-743. doi: 10.1177/1475921720935585
Fabo, P.; Sedivy, S.; Kuba, M.; Buchholcerova, A.; Dudak, J.; and Gaspar, G., 2020, “PLC Based Weather Station for Experimental Measurements,” 19th International Conference on Mechatronics – Mechatronika (ME), Prague, Czech Republic, pp. 1-4.
Farrar, C. R., and Worden, K., 2012, Structural Health Monitoring: A Machine Learning Perspective, first edition, John Wiley & Sons, Ltd, Chichester, UK, 631 pp.
Ferrari-Trecate, G., and Muselli, M., 2002, “A New Learning Method for Piecewise Linear Regression,” J. R. Dorronsoro, ed., Artificial Neural Networks – ICANN 2002, International Conference, Springer Verlag, Madrid, Spain, pp. 444-449.
Flah, M.; Nunez, I.; Ben Chaabene, W.; and Nehdi, M. L., 2021, “Machine Learning Algorithms in Civil Structural Health Monitoring: A Systematic Review,” Archives of Computational Methods in Engineering, V. 28, No. 4, pp. 2621-2643. doi: 10.1007/s11831-020-09471-9
Frangopol, D. M., and Kim, S., 2014, “Prognosis and Life-Cycle Assessment Based on SHM Information,” Sensor Technologies for Civil Infrastructures. Volume 2 - Applications in Structural Health Monitoring, M. L. Wang, J. P. Lynch, and H. Sohn, eds., Woodhead Publishing, Netherlands, pp. 145-171.
Garboczi, E. J., and Bentz, D. P., 1992, “Computer Simulation of the Diffusivity of Cement-Based Materials,” Journal of Materials Science, V. 27, No. 8, pp. 2083-2092. doi: 10.1007/BF01117921
Glišić, B., and Simon, N., 2000, “Monitoring of Concrete at Very Early Age Using Stiff SOFO Sensor,” Cement and Concrete Composites, V. 22, No. 2, pp. 115-119. doi: 10.1016/S0958-9465(99)00037-2
Hearty, J., 2016, Advanced Machine Learning with Python, first edition, Packt Publishing, Birmingham, UK, 278 pp.
Hernandez, W., 2006, “Improving the Response of a Load Cell by Using Optimal Filtering,” Sensors (Basel), V. 6, No. 7, pp. 697-711. doi: 10.3390/s6070697
Hossain, K. M. A., and Lachemi, M., 2004, “Corrosion Resistance and Chloride Diffusivity of Volcanic Ash Blended Cement Mortar,” Cement and Concrete Research, V. 34, No. 4, pp. 695-702. doi: 10.1016/j.cemconres.2003.10.021
Jansen, D.; Goetz-Neunhoeffer, F.; Lothenbach, B.; and Neubauer, J., 2012, “The Early Hydration of Ordinary Portland Cement (OPC): An Approach Comparing Measured Heat Flow with Calculated Heat Flow from QXRD,” Cement and Concrete Research, V. 42, No. 1, pp. 134-138. doi: 10.1016/j.cemconres.2011.09.001
Kalkani, E. C., 1992, “Ambient Temperature Effect in Concrete Dam Foundation Seepage,” Journal of Geotechnical Engineering, ASCE, V. 118, No. 1, pp. 1-11. doi: 10.1061/(ASCE)0733-9410(1992)118:1(1)
Karbassi, A.; Mohebi, B.; Rezaee, S.; and Lestuzzi, P., 2014, “Damage Prediction for Regular Reinforced Concrete Buildings using the Decision Tree Algorithm,” Computers and Structures, V. 130, pp. 46-56. doi: 10.1016/j.compstruc.2013.10.006
McCarter, W. J.; Chrisp, T. M.; Starrs, G.; Adamson, A.; Owens, E.; Basheer, P. A. M.; Nanukuttan, S. V.; Srinivasan, S.; and Holmes, N., 2012, “Developments in Performance Monitoring of Concrete Exposed to Extreme Environments,” Journal of Infrastructure Systems, ASCE, V. 18, No. 3, pp. 167-175. doi: 10.1061/(ASCE)IS.1943-555X.0000089
McCarter, W. J.; Chrisp, T. M.; Starrs, G., Basheer, P. A. M.; and Blewett, J., 2005, “Field Monitoring of Electrical Conductivity of Cover-Zone Concrete,” Cement and Concrete Composites, V. 27, No. 7-8, pp. 809-817.
Montemor, M. F.; Alves, J. H.; Simões, A. M.; Fernandes, J. C. S.; Lourenço, Z.; Costa, A. J. S.; Appleton, A. J.; and Ferreira, M. G. S., 2006, “Multiprobe Chloride Sensor for In-Situ Monitoring of Reinforced Concrete Structures,” Cement and Concrete Composites, V. 28, No. 3, pp. 233-236. doi: 10.1016/j.cemconcomp.2006.01.005
Muhammad, Y., S.; Afgan, N.; Iqbal, M.; and Hussain, I., 2014, “Modeling Non-linear Behavior of Independent Variables,” International Journal of Business and Social Science, V. 5, No. 13, pp. 192-200.
Nanukuttan, S. V.; Basheer, P. A. M.; McCarter, W. J.; Tang, L.; Holmes, N.; Chrisp, T. M.; Starrs, G.; and Magee, B., 2015, “The Performance of Concrete Exposed to Marine Environments: Predictive Modelling and Use of Laboratory/On-Site Test Methods,” Construction and Building Materials, V. 93, pp. 831-840. doi: 10.1016/j.conbuildmat.2015.05.083
Nanukuttan, S. V.; Campbell, N.; Mccarter, J.; Basheer, M.; Mcrobert, J.; and McBurney, P., 2017a, “State of Health Assessment of Concrete Repair using Electrical Sensors,” 2nd International RILEM/COST Conference on Early Age Cracking and Serviceability in Cement-Based Materials and Structures, S. Staquet, and D. Aggelis, eds., RILEM Publications SARL, Brussels, pp. 149-154.
Nanukuttan, S. V.; Yang, K.; McCarter, J.; and Basheer, P. A. M., 2017b, “Methods of Assessing the Durability and Service Life of Concrete Structures,” Annual Technical Symposium of the Institute of Concrete Technology (ICT), Leeds, UK, pp. 1-14.
Nehdi, M. L., and Soliman, A. M., 2011, “Early-Age Properties of Concrete: Overview of Fundamental Concepts and State-of-the-Art Research,” Construction Materials, V. 164, No. 2, pp. 57-77.
Neville, A. M., 2011, Properties of Concrete, fifth edition, Pearson Education Limited, London, UK, 846 pp.
Nokken, M. R., and Hooton, R. D., 2007, “Using Pore Parameters to Estimate Permeability or Conductivity of Concrete,” Materials and Structures, V. 41, No. 1, pp. 1-16. doi: 10.1617/s11527-006-9212-y
Oslakovic, I. S.; Serdar, M.; Bjegovic, D.; and Mikulic, D., 2008, “Modeling of Time Depended Changes of Chloride Diffusion Coefficient,” 11DBMC International Conference on Durability of Building Materials and Components, Istanbul, Turkey, pp. 203-2112.
Pan, Y., and Zhang, L., 2021, “Roles of Artificial Intelligence in Construction Engineering and Management: A Critical Review and Future Trends,” Automation in Construction, V. 122, No. 2, pp. 1-21. doi: 10.1016/j.autcon.2020.103517
Perveen, K.; Bridges, G. E.; Bhadra, S.; and Thomson, D. J., 2014, “Corrosion Potential Sensor for Remote Monitoring of Civil Structure based on Printed Circuit Board Sensor,” IEEE Transactions on Instrumentation and Measurement, V. 63, No. 10, pp. 2422-2431. doi: 10.1109/TIM.2014.2310092
Rai, V. K., 2007, “Temperature Sensors and Optical Sensors,” Applied Physics B: Lasers and Optics, V. 88, No. 2, pp. 297-303. doi: 10.1007/s00340-007-2717-4
Safiuddin, M.; Raman, S. N.; and Zain, M. F. M., 2007, “Effect of Different Curing Methods on the Properties of Microsilica Concrete,” Australian Journal of Basic and Applied Sciences, V. 1, No. 2, pp. 87-95.
Schöler, A.; Lothenbach, B.; Winnefeld, F.; Haha, M. B.; Zajac, M.; and Ludwig, H.-M., 2017, “Early Hydration of SCM-Blended Portland Cements: A Pore Solution and Isothermal Calorimetry Study,” Cement and Concrete Research, V. 93, pp. 71-82. doi: 10.1016/j.cemconres.2016.11.013
Scrivener, K. L., and Nonat, A., 2011, “Hydration of Cementitious Materials, Present and Future,” Cement and Concrete Research, V. 41, No. 7, pp. 651-665. doi: 10.1016/j.cemconres.2011.03.026
Sellevold, E. J., and Radjy, F. F., 1983, Condensed Silica fume (Microsilica) in Concrete: Water Demand and Strength Development, Symposium Paper, V. 79, pp. 677-694.
Smarsly, K.; Dragos, K.; and Wiggenbrock, J., 2016, “Machine Learning Techniques for Structural Health Monitoring,” 8th European Workshop on Structural Health Monitoring (EWSHM), Bilbao, Spain, pp. 1522-1531.
Steinhart, J. S., and Hart, S. R., 1968, “Calibration Curves for Thermistors,” Deep-Sea Research and Oceanographic Abstracts, V. 15, No. 4, pp. 497-503. doi: 10.1016/0011-7471(68)90057-0
Takatoi, G.; Sugawara, T.; Sakiyama, K.; and Li, Y., 2020, “Simple Electromagnetic Analysis against Activation Functions of Deep Neural Networks,” J. Zhou, ed., International Conference on Applied Cryptography and Network Security, Springer, Cham, pp.181-197.
Tanner, B. D., 1990, “Automated Weather Stations,” Remote Sensing Reviews, V. 5, No. 1, pp. 73-98. doi: 10.1080/02757259009532123
Yang, K.; Basheer, P. A. M.; Bai, Y.; Magee, B. J.; and Long, A. E., 2014, “Development of a New In-Situ Test Method to Measure the Air Permeability of High-Performance Concretes,” NDT & E International, V. 64, pp. 30-40. doi: 10.1016/j.ndteint.2014.02.005
Yang, K.; Nanukuttan, S. V.; McCarter, W. J.; Long, A.; and Basheer, P. A. M., 2018, “Challenges and Opportunities for Assessing Transport Properties of High-performance Concrete,” Revista ALCONPAT, V. 8, No. 3, pp. 246-263. doi: 10.21041/ra.v8i3.301
Yang, L.; Liu, S.; Tsoka, S.; and Papageorgiou, L. G., 2016, “Mathematical Programming for Piecewise Linear Regression analysis,” Expert Systems with Applications, V. 44, pp. 156-167. doi: 10.1016/j.eswa.2015.08.034
Yavuz, K., and Safak, E., 2019, “Structural Health Monitoring: Real-Time Data Analysis and Damage Detection,” Seismic Structural Health Monitoring, M. P. Limongelli and M. Çelebi, eds., Springer, Cham, pp. 171-197.
Yu, C.; Wang, J.; Tan, L.; and Tu, X., 2011, “A Bridge Structural Health Data Analysis Model Based on Semi-supervised Learning,” IEEE International Conference on Automation and Logistics (ICAL), Chongqing, China, IEEE, pp. 30-34.
Zelić, J.; Rušić, D.; Veža, D.; and Krstulović, R., 2000, “Role of Silica Fume in the Kinetics and Mechanisms During the Early Stage of Cement Hydration,” Cement and Concrete Research, V. 30, No. 10, pp. 1655-1662. doi: 10.1016/S0008-8846(00)00374-4
Zhang, C.; Zhang, W.; Webb, D. J.; and Peng, G. D., 2010, “Optical Fibre Temperature and Humidity Sensor,” Electronics Letters, V. 46, No. 9, pp. 643-644. doi: 10.1049/el.2010.0879