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Detecting, localizing, and quantifying damage using two-dimensional sensing sheet: lab test and field application

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Abstract

Damage to structures in the form of cracks could reduce safety and induce high maintenance cost. Structural health monitoring (SHM) is increasingly employed to detect damage in the structure and inform the stakeholders in a timely manner to allow rehabilitation actions. Reliable crack detection, localization, and quantification are, hence, extremely important. To achieve this goal, a dense network of sensors is often required. Damages even a meter away from sensors are often unable to be detected reliably by a sensing system. Creating a dense network of sensors using the commonly used point sensors (e.g., strain gages) or distributed one-dimensional sensors (e.g., fiber-optic sensors) is expensive and often practically impossible. Sensing sheet is a distributed two-dimensional thin-film sensor comprising of a dense array of resistive strain gage units developed at Princeton University. Based on the principles of large-area electronics (LAE), this thin-film sensor provides an affordable solution to reliably detect and localize damage. This paper derives analytical models for damage detection, localization, and quantification based on sensing sheet. Laboratory experiments are performed by creating artificial damage to verify these models and highlight their uses. Further, the damage quantification algorithm is used to estimate the crack opening in a shrinkage crack on the foundation of the pedestrian bridge at Princeton University. Finally, the results and future research directions are discussed.

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The experimental and field data can be made available upon request.

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The code used for data analysis can be made available upon request.

References

  1. Jang JH, Yeo I, Shin S, Chang SP (2002) Experimental investigation of system-identification-based damage assessment on structures. J Struct Eng 128(5):673–682

    Article  Google Scholar 

  2. Yao Y, Glisic B (2012) Reliable damage detection and localization using direct strain sensing. In: 6th international conference on bridge maintenance, safety and management, IABMAS 2012, Taylor and Francis-Balkema, pp 714–721

  3. Yao Y, Tung STE, Glisic B (2014) Crack detection and characterization techniques - an overview. Struct Control Health Monit 21(12):1387–1413

    Article  Google Scholar 

  4. Glisic B, Inaudi D (2012) Development of method for in-service crack detection based on distributed fiber optic sensors. Struct Health Monit 11(2):161–171

    Article  Google Scholar 

  5. Roach D (2009) Real time crack detection using mountable comparative vacuum monitoring sensors. Smart Struct Syst 5(4):317–328

    Article  Google Scholar 

  6. Rodŕıguez G, Casas JR, Villaba S (2015) Cracking assessment in concrete structures by distributed optical fiber. Smart Mater Struct 24(3):035005

    Article  Google Scholar 

  7. Ramos T, Braga DF, Eslami S, Tavares PJ, Moreira P (2015) Comparison between finite element method simulation, digital image correlation and strain gauges measurements in a 3-point bending flexural test. Procedia Eng 114:232–239

    Article  Google Scholar 

  8. dos Reis J, Oliveira Costa C, Sá da Costa J (2018) Strain gauges debonding fault detection for structural health monitoring. Struct Control Health Monit 25(12):e2264

    Article  Google Scholar 

  9. Bao Y, Beck JL, Li H (2011) Compressive sampling for accelerometer signals in structural health monitoring. Struct Health Monit 10(3):235–246

    Article  Google Scholar 

  10. Park HS, Lee HY, Choi SW, Kim Y (2013) A practical monitoring system for the structural safety of mega-trusses using wireless vibrating wire strain gauges. Sensors 13(12):17346–17361

    Article  Google Scholar 

  11. Feng X, Zhou J, Sun C, Zhang X, Ansari F (2013) Theoretical and experimental investigations into crack detection with BOTDR-distributed fiber optic sensors. J Eng Mech 139(12):1797–1807

    Article  Google Scholar 

  12. Glisic B, Inaudi D (2008) Fibre optic methods for structural health monitoring. John Wiley & Sons

    Google Scholar 

  13. Ramakrishnan M, Rajan G, Semenova Y, Farrell G (2016) Overview of fiber optic sensor technologies for strain/temperature sensing applications in composite materials. Sensors 16(1):99

    Article  Google Scholar 

  14. Glišić B, Yao Y, Tung STE, Wagner S, Sturm JC, Verma N (2016) Strain sensing sheets for structural health monitoring based on large-area electronics and integrated circuits. Proc IEEE 104(8):1513–1528

    Article  Google Scholar 

  15. Xiong Z, Glisic B (2020) An inverse elastic method of crack identification based on sparse strain sensing sheet. Struct Health Monit 20(2):532–545

    Article  Google Scholar 

  16. Kaya Y, Safak E (2015) Real-time analysis and interpretation of continuous data from structural health monitoring (SHM) systems. Bull Earth-quake Eng 13(3):917–934

    Article  Google Scholar 

  17. Han Q, Ma Q, Xu J, Liu M (2020) Structural health monitoring research under varying temperature condition: a review. J Civ Struct Health Monit 11:149–173

    Article  Google Scholar 

  18. Reilly J, Glisic B (2018) Identifying time periods of minimal thermal gradient for temperature-driven structural health monitoring. Sensors 18(3):734

    Article  Google Scholar 

  19. Yao Y, Glisic B (2015) Sensing sheets: optimal arrangement of dense array of sensors for an improved probability of damage detection. Struct Health Monit 14(5):513–531

    Article  Google Scholar 

  20. Yao Y, Glisic B (2015) Detection of steel fatigue cracks with strain sensing sheets based on large area electronics. Sensors 15(4):8088–8108

    Article  Google Scholar 

  21. Lin M, Chang FK (2002) The manufacture of composite structures with a built-in network of piezoceramics. Compos Sci Technol 62(7–8):919–939

    Article  Google Scholar 

  22. Lin M, Qing X, Kumar A, Beard SJ (2001) Smart layer and smart suitcase for structural health monitoring applications. Smart Struct Mater 4332:98–106

    Google Scholar 

  23. Qing XP, Beard SJ, Kumar A, Li I, Lin M, Chang FK (2009) Stanford multiactuator–receiver transduction (SMART) layer technology and its applications. Encyclopedia of structural health monitoring

  24. Downey A, Laflamme S, Ubertini F (2016) Reconstruction of in-plane strain maps using hybrid dense sensor network composed of sensing skin. Meas Sci Technol 27(12):124016

    Article  Google Scholar 

  25. Downey A, D’Alessandro A, Baquera M, Garćıa-Maćıas E, Rolfes D, Ubertini F, Laflamme S, Castro-Triguero R (2017) Damage detection, localization and quantification in conductive smart concrete structures using a resistor mesh model. Eng Struct 148:924–935

    Article  Google Scholar 

  26. Downey A, Laflamme S, Ubertini F (2017) Experimental wind tunnel study of a smart sensing skin for condition evaluation of a wind turbine blade. Smart Mater Struct 26(12):125005

    Article  Google Scholar 

  27. Kharroub S, Laflamme S, Madbouly S, Ubertini F (2015) Bio-based soft elastomeric capacitor for structural health monitoring applications. Struct Health Monit 14(2):158–167

    Article  Google Scholar 

  28. Kharroub S, Laflamme S, Song C, Qiao D, Phares B, Li J (2015) Smart sensing skin for detection and localization of fatigue cracks. Smart Mater Struct 24(6):065004

    Article  Google Scholar 

  29. Kong X, Li J, Collins W, Bennett C, Laflamme S, Jo H (2017) A large-area strain sensing technology for monitoring fatigue cracks in steel bridges. Smart Mater Struct 26(8):085024

    Article  Google Scholar 

  30. Kong X, Li J, Bennett C, Collins W, Laflamme S, Jo H (2019) Thin-film sensor for fatigue crack sensing and monitoring in steel bridges under varying crack propagation rates and random traffic loads. J Aerosp Eng 32(1):04018116

    Article  Google Scholar 

  31. Laflamme S, KolloscheConnor MJJ, Kofod G (2012) Soft capacitive sensor for structural health monitoring of large-scale systems. Struct Control Health Monit 19(1):70–81

    Article  Google Scholar 

  32. Laflamme S, Kollosche M, Connor JJ, Kofod G (2013) Robust flexible capacitive surface sensor for structural health monitoring applications. J Eng Mech 139(7):879–885

    Article  Google Scholar 

  33. Dharap P, Li Z, Nagarajaiah S, Barrera E (2004) Nanotube film based on single-wall carbon nanotubes for strain sensing. Nanotechnology 15(3):379

    Article  Google Scholar 

  34. Hallaji M, Seppänen A, Pour-Ghaz M (2014) Electrical impedance tomography-based sensing skin for quantitative imaging of damage in concrete. Smart Mater Struct 23(8):085001

    Article  Google Scholar 

  35. Hou TC, Loh KJ, Lynch JP (2007) Spatial conductivity mapping of carbon nanotube composite thin films by electrical impedance tomography for sensing applications. Nanotechnology 18(31):315501

    Article  Google Scholar 

  36. Lee BM, Loh KJ (2017) Carbon nanotube thin film strain sensors: comparison between experimental tests and numerical simulations. Nanotechnology 28(15):155502

    Article  Google Scholar 

  37. Loh KJ, Azhari F (2012) Recent advances in skin-inspired sensors enabled by nanotechnology. JOM 64(7):793–801

    Article  Google Scholar 

  38. Loh KJ, Kim J, Lynch JP, Kam NWS, Kotov NA (2007) Multifunctional layer-by-layer carbon nanotube–polyelectrolyte thin films for strain and corrosion sensing. Smart Mater Struct 16(2):429

    Article  Google Scholar 

  39. Loh KJ, Hou TC, Lynch JP, Kotov NA (2009) Carbon nanotube sensing skins for spatial strain and impact damage identification. J Nondestr Eval 28(1):9–25

    Article  Google Scholar 

  40. Bae SH, Lee Y, Sharma BK, Lee HJ, Kim JH, Ahn JH (2013) Graphene-based transparent strain sensor. Carbon 51:236–242

    Article  Google Scholar 

  41. Chen X, Zheng X, Kim JK, Li X, Lee DW (2011) Investigation of graphene piezoresistors for use as strain gauge sensors. J Vacuum Sci Technol B Nanotechnol Microelectron Mater Process Meas Phenom 29(6):06FE01

    Google Scholar 

  42. Gupta S, Vella G, Yu IN, Loh CH, Chiang WH, Loh KJ (2020) Graphene sensing meshes for densely distributed strain field monitoring. Struct Health Monit 19(5):1323–1339

    Article  Google Scholar 

  43. Nagarajaiah S, Weisman RB, Sun P, Bachilo SM, Yang Y (2016) Strain-sensing smart skin: A non-contact optical strain sensor using single-walled carbon nanotubes. Innovative Developments of Advanced Multifunctional Nanocomposites in Civil and Structural Engineering. Elsevier, pp 353–375

    Chapter  Google Scholar 

  44. Withey PA, Vemuru VSM, Bachilo SM, Nagarajaiah S, Weisman RB (2012) Strain paint: non-contact strain measurement using single-walled carbon nanotube composite coatings. Nano Lett 12(7):3497–3500

    Article  Google Scholar 

  45. Zonta D, Chiappini A, Chiasera A, Ferrari M, Pozzi M, Battisti L, Benedetti M (2009) Photonic crystals for monitoring fatigue phenomena in steel structures. Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, vol 7292. International Society for Optics and Photonics, p 729215

    Google Scholar 

  46. Han B, Yu X, Ou J (2014) Self-sensing concrete in smart structures. Butterworth-Heinemann

    Google Scholar 

  47. Hu Y, Rieutort-Louis W, Sanz-Robinson J, Song K, Sturm JC, Wagner S, Verma N (2012) High-resolution sensing sheet for structural-health monitoring via scalable interfacing of flexible electronics with high-performance ICs. In: 2012 symposium on VLSI circuits (VLSIC). IEEE, pp 120–121

  48. Hu Y, Rieutort-Louis WS, Sanz-Robinson J, Huang L, Glišić B, Sturm JC, Wagner S, Verma N (2014) Large-scale sensing system combining large-area electronics and CMOSICs for structural-health monitoring. IEEE J Solid-State Circuits 49(2):513–523

    Article  Google Scholar 

  49. Tung S, Glisic B (2016) Sensing sheet: the response of full-bridge strain sensors to thermal variations for detecting and characterizing cracks. Meas Sci Technol 27(12):124010

    Article  Google Scholar 

  50. Tung S, Yao Y, Glisic B (2014) Sensing sheet: the sensitivity of thin-film full-bridge strain sensors for crack detection and characterization. Meas Sci Technol 25(7):075602. https://doi.org/10.1088/0957-0233/25/7/075602

    Article  Google Scholar 

  51. Aygun LE, Kumar V, Weaver C, Gerber M, Wagner S, Verma N, Glisic B, Sturm JC (2020) Large-area resistive strain sensing sheet for structural health monitoring. Sensors 20(5):1386

    Article  Google Scholar 

  52. Kumar V, Aygun LE, Verma N, Sturm JC, Glisic B (2019) Sensing sheets based on large area electronics for structural health monitoring of bridges. Sensors and Smart Structures Technologies for Civil Mechanical and Aerospace Systems, vol 10970. International Society for Optics and Photonics, p 109702G

    Google Scholar 

  53. Ozatay M, Aygun L, Jia H, Kumar P, Mehlman Y, Wu C, Wagner S, Sturm JC, Verma N (2018) Artificial intelligence meets large-scale sensing: Using large-area electronics (LAE) to enable intelligent spaces. In: 2018 IEEE Custom Integrated Circuits Conference (CICC), IEEE 1–8

  54. Sturm J, Mehlman Y, Aygun LE, Wu C, Zheng Z, Kumar P, Wagner S, Verma N (2019) (keynote) Machine learning and high-speed circuitry in thin film transistors for sensor interfacing in hybrid large-area electronic systems. ECS Trans 92(4):121

    Article  Google Scholar 

  55. Gerber M, Weaver C, Aygun LE, Verma N, Sturm JC, Glišić B (2018) Strain transfer for optimal performance of sensing sheet. Sensors 18(6):1907

    Article  Google Scholar 

  56. Li Y, Wang Z, Xiao C, Zhao Y, Zhu Y, Zhou Z (2018) Strain transfer characteristics of resistance strain-type transducer using elastic-mechanical shear lag theory. Sensors 18(8):2420

    Article  Google Scholar 

  57. Zhang XX, Rena CY, Ruiz G, Tarifa M, Camara MA (2010) Effect of loading rate on crack velocities in HSC. Int J Impact Eng 37(4):359–370

    Article  Google Scholar 

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Acknowledgements

The authors would like to acknowledge the work of Campbell Weaver and Matthew Gerber in the initial prototyping of the sensing sheet and study to establish the right adhesives. The authors would like to acknowledge the help of Joseph Vocaturo in making the micrometer gage for laboratory experiments and providing logistical support for the field experiments.

Funding

This research was, in part, supported by the USDOT OST-R UTC Program, grant no. 69A3551847102, enabled through the Center for Advanced Infrastructure and Transportation (CAIT) at the Rutgers University (subcontract agreement no. 0615).

Author information

Authors and Affiliations

Authors

Contributions

V.K.: Developed the idea for the paper, derived the analytical results, designed, and performed both laboratory and field experiments, performed data analysis, wrote, and edited the manuscript. He is the lead author of the paper. B.A.: Performed laboratory experiments. L.A.: Performed the field experiments, performed data analysis on field experiment, developed the software interface for sensing sheet. N.V., J.S., and S.W.: Created the concept of sensing sheet. B.G: Created the concept of sensing sheet, developed the idea for the paper, designed the experiments, edited the draft of the paper.

Corresponding author

Correspondence to Vivek Kumar.

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The authors declare that they have no conflict of interest.

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Appendices

Appendix A

In this section step-by-step derivation of the change in voltage ratio \(\Delta V_{r}\), strain measured by the sensing sheet \(\varepsilon\) and the strain ratio \(\omega\) for the four cases are detailed.

1.1 Preliminary

Consider the case of a single resistor \(R_{3}\) through which a crack passes as shown in Fig. 

Fig. 20
figure 20

A preliminary case where the crack only passes through resistor \(R_{3}\)

20. Let the number of serpentines intersected by the crack \({\mathcal{C}}\) be \(n_{{\mathcal{C}}}\). Let \(\alpha_{{\mathcal{C}}}\) denote the ratio of serpentines intersected by the crack to the total number of serpentines \(n\). Let the crack opening be denoted by \(w_{{\mathcal{C}}}\) and the ratio \(\frac{{w_{{\mathcal{C}}} }}{{l_{r} }} = \psi\).

The total length of the serpentine after crack opening is given by equation A1.

$$l_{f} = (n(1 - \alpha_{c} ) + 1)l_{r} + n\alpha_{c} (l_{r} + w_{{\mathcal{C}}} ) = (n + 1)l_{r} + n\alpha_{c} w_{{\mathcal{C}}}$$
(A1)

The final resistance can then be calculated as

$$R_{3,f} = \rho \frac{{l_{f} }}{{A_{f} }} = \rho \frac{{\left( {(n + 1)l_{r} + n\alpha_{c} w_{{\mathcal{C}}} } \right)}}{{A\left( {1 - \nu \frac{{n\alpha_{c} w_{{\mathcal{C}}} }}{{\left( {n + 1} \right)l_{r} }}} \right)^{2} }}$$
(A2)

On rearranging the terms, we obtain the equation A3.

$$R_{3,f} = \rho \frac{{l_{f} }}{{A_{f} }} = R\frac{{\left( {1 + \frac{{n\alpha_{c} \psi }}{{\left( {n + 1} \right)}}} \right)}}{{\left( {1 - \nu \frac{{n\alpha_{c} \psi }}{{\left( {n + 1} \right)}}} \right)^{2} }} = R\frac{{\left( {1 + \alpha_{c} \psi - \frac{{\alpha_{c} \psi }}{{\left( {n + 1} \right)}}} \right)}}{{\left( {1 - 2\nu \alpha_{c} \psi + \frac{{\nu \alpha_{c} \psi }}{{\left( {n + 1} \right)}} + \nu^{2} \frac{{n^{2} \alpha_{c}^{2} \psi^{2} }}{{\left( {n^{2} + 1} \right)}}} \right)}},$$
(A3)

where \(R\) is the initial resistance of the resistor \(R_{3}\) and \(\psi\) was defined before. Noting that \(w_{{\mathcal{C}}} < < l_{r}\), hence \(\psi \ll 1\), and \(n \ge 50\) we can drop terms such as \(\frac{{\alpha_{c} \psi }}{{\left( {n + 1} \right)}}\) and \(\nu^{2} \frac{{n^{2} \alpha_{c}^{2} \psi^{2} }}{{\left( {n^{2} + 1} \right)}}\). Further using the binomial expansion for \(\frac{1}{1 - x}\) for \(x \ll 1\) we get the final resistance in terms of crack opening and proportion of resistor under the influence of crack as given in equation A4.

$$R_{3,f} = R\frac{{\left( {1 + \alpha_{c} \psi } \right)}}{{\left( {1 - 2\nu \alpha_{c} \psi } \right)}} = R\left( {1 + \alpha_{c} \psi } \right)\left( {1 + 2\nu \alpha_{c} \psi } \right)$$
(A4)

Subtracting the original strain from the final strain gives the change in resistance due to the crack opening \(w_{{\mathcal{C}}}\).

$$\Delta R_{3} = R_{3} \left( {\left( {1 + \alpha_{c} \psi } \right)\left( {1 + 2\nu \alpha_{c} \psi } \right) - 1} \right)$$
(A5)

Rearranging the terms gives change in resistance with respect to the original resistance of the unit resistor as shown in equation A6.

$$\frac{{\Delta R_{3} }}{{R_{3} }} = \left( {1 + \alpha_{c} \psi } \right)\left( {1 + 2\nu \alpha_{c} \psi } \right) - 1$$
(A6)

This change in resistance results to a voltage drop which is governed by the Eq. 3 in Sect. 2.1. As stated before, the change in resistance in the remaining resistors,\(R_{1} ,\;R_{2} ,\;R_{4}\), would be negligible compared to this and hence those changes are approximately 0.

Hence the change in voltage drop for the preliminary scenario would be given by equation A5.

$$\Delta V_{r} = \frac{1}{2} - \frac{{\left( {1 + \alpha_{c} \psi } \right)\left( {1 + 2\nu \alpha_{c} \psi } \right)}}{{1 + \left( {1 + \alpha_{c} \psi } \right)\left( {1 + 2\nu \alpha_{c} \psi } \right)}}$$
(A7)

This change in voltage drop is related to the strain measured by the sensing sheet through equation A6 (For complete derivation, refer [51]).

$$\varepsilon = - \frac{{2\Delta V_{r} }}{{{\text{GF}}\left[ {(1 + \nu ) + \Delta V_{r} \left( {1 - \nu } \right)} \right]}}$$
(A8)

On substituting the drop in voltage in equation A6 we obtain the strain:

$$\varepsilon = - \frac{{2\left( {1 - \left( {1 + \alpha_{c} \psi } \right)\left( {1 + 2\nu \alpha_{c} \psi } \right)} \right)}}{{{\text{GF}}\left[ {(3 + \nu ) + \left( {1 + \alpha_{c} \psi } \right)\left( {1 + 2\nu \alpha_{c} \psi } \right)\left( {3\nu + 1} \right)} \right]}}.$$
(A9)

In the above equation for a given value of \(\varepsilon\) and \(\alpha_{c}\), \(w_{{\mathcal{C}}}\) can be computed by solving the above equations. Finally, using the baseline strain measurement from Eq. 9 in Sect. 2.3 to obtain the voltage ratio.

$$\omega = \frac{{2\left( {1 - \left( {1 + \alpha_{c} \psi } \right)\left( {1 + 2\nu \alpha_{c} \psi } \right)} \right)\left[ {1 + \nu \left( {1 + \psi } \right)\left( {1 + 2\nu \psi } \right)} \right]}}{{\psi \left( {2\nu \left( {\psi + 1} \right) + 1} \right)\left[ {(3 + \nu ) + \left( {1 + \alpha_{c} \psi } \right)\left( {1 + 2\nu \alpha_{c} \psi } \right)\left( {3\nu + 1} \right)} \right]}}$$
(A10)

The above approach holds for the cases where a combination of resistors is intersected by a crack as the change in resistance of individual resistor can be calculated as before and substituted in Eq. 3 of Sect. 2.1 to obtain the change in voltage resistance and compute the strain and strain ratios for various cases in Sect. 2.3.

1.1.1 Case 1: the crack intersects resistors R 2 and R 3 only

The case 1 is shown in Fig. 5c. Based on the preliminary calculations shown, the ratio of change of resistances in \(R_{2}\) if the proportion of crack being affected in \(\alpha_{2}\) is given by:

$$\frac{{\Delta R_{2} }}{{R_{2} }} = \left( {1 + \alpha_{2} \psi } \right)\left( {1 + 2\nu \alpha_{2} \psi } \right) - 1.$$
(A11)

While the values of ratio for \(R_{3}\) for a proportion of resistor being affected by crack given by \(\alpha_{3}\) is shown in equation A12.

$$\frac{{\Delta R_{3} }}{{R_{3} }} = \left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right) - 1$$
(A12)

Substituting the values of these relative change in resistances in Eq. 3 to obtain the voltage drop measured by the sensing system for case 1.

$$\Delta V_{r} = \frac{1}{{1 + \left( {1 + \alpha_{2} \psi } \right)\left( {1 + 2\nu \alpha_{2} \psi } \right)}} - \frac{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right)}}{{1 + \left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right)}}$$
(A13)

One can substitute this value in equation A8 to obtain the strain recorded by the sensing system:

$$\varepsilon = - \frac{{2\left( {\frac{1}{{\left( {1 + \alpha_{2} \psi } \right)\left( {1 + 2\nu \alpha_{2} \psi } \right) + 1}} - \frac{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right)}}{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right) + 1}}} \right)}}{{{\text{GF}}\left( {\left( {1 + \nu } \right) + \left( {1 - \nu } \right)\left( {\frac{1}{{\left( {1 + \alpha_{2} \psi } \right)\left( {1 + 2\nu \alpha_{2} \psi } \right) + 1}} - \frac{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right)}}{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right) + 1}}} \right)} \right)}}.$$
(A14)

1.1.2 Case 2: The crack intersects resistors R 4 and R 1 only

The case 2 along with the notation used in shown in Fig. 5d. The ratio of change of resistances in \(R_{1}\) if the proportion of crack being affected in \(\alpha_{1}\) is given by:

$$\frac{{\Delta R_{1} }}{{R_{1} }} = \left( {1 + \alpha_{1} \psi } \right)\left( {1 + 2\nu \alpha_{1} \psi } \right) - 1.$$
(A15)

The ratios of change of resistances in \(R_{4}\) if the proportion of crack being affected in \(\alpha_{4}\) is given by:

$$\frac{{\Delta R_{4} }}{{R_{4} }} = \left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right) - 1.$$
(A16)

Substituting the values in Eq. 3 to obtain the change in voltage ratio for case 2 in equation A17.

$$\Delta V_{r} = \frac{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}}{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right) + 1}} - \frac{1}{{\left( {1 + \alpha_{1} \psi } \right)\left( {1 + 2\nu \alpha_{1} \psi } \right) + 1}}$$
(A17)

The strain is obtained by substituting the value of \(\Delta V_{r}\) in equation A8 and shown in equation A18.

$$\varepsilon = - \frac{{2\left( {\frac{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}}{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right) + 1}} - \frac{1}{{\left( {1 + \alpha_{1} \psi } \right)\left( {1 + 2\nu \alpha_{1} \psi } \right) + 1}}} \right)}}{{{\text{GF}}\left( {\left( {1 + \nu } \right) + \left( {1 - \nu } \right)\left( {\frac{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}}{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right) + 1}} - \frac{1}{{\left( {1 + \alpha_{1} \psi } \right)\left( {1 + 2\nu \alpha_{1} \psi } \right) + 1}}} \right)} \right)}}$$
(A18)

1.1.3 Case 3: The crack intersects resistors R 3 and R 4 only

The case 3 along with notation is shown in Fig. 5e. The ratio of change of resistances in \(R_{3}\) if the proportion of resistor being affected by crack is \(\alpha_{3}\) is given by equation A2 and the ratio of change of resistance for \(R_{4}\) when the proportion of resistor being affected by crack is \(\alpha_{4}\) is given equation A16. The change in voltage ratio for the present case is given by equation A19.

$$\Delta V_{r} = \frac{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}}{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right) + 1}} - \frac{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right)}}{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right) + 1}}$$
(A19)

We can rearrange the terms to simplify the above expressions, given in equation A20.

$$\Delta V_{r} = \frac{1}{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right) + 1}} - \frac{1}{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right) + 1}}$$
(A20)

The measured strain in this case is given by equation A21.

$$\varepsilon = - \frac{{2\left( {\frac{1}{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right) + 1}} - \frac{1}{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right) + 1}}} \right)}}{{{\text{GF}}\left( {\left( {1 + \nu } \right) + \left( {1 - \nu } \right)\left( {\frac{1}{{\left( {1 + \alpha_{3} \psi } \right)\left( {1 + 2\nu \alpha_{3} \psi } \right) + 1}} - \frac{1}{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right) + 1}}} \right)} \right)}}$$
(A21)

The strain ratio can be calculated by dividing this term by baseline strain in Eq. 9.

1.1.4 Case 4: the crack intersects resistors R 2 and R 4 only

The case 4 along with notation is shown in Fig. 5f. The ratio of change of resistances in \(R_{2}\) if the proportion of resistor being affected by crack is \(\alpha_{2}\) is given by equation A11 and the ratio of change of resistance for \(R_{4}\) when the proportion of resistor being affected by crack is \(\alpha_{4}\) is given by equation A16. The change in voltage ratio for the present case is given by equation A22.

$$\Delta V_{r} = \frac{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}}{{\left( {1 + \alpha_{2} \psi } \right)\left( {1 + 2\nu \alpha_{2} \psi } \right) + \left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}} - \frac{1}{2}$$
(A22)

For the cases where \(\alpha_{2} = \alpha_{4}\), \(\Delta V_{r} = 0\). This would result in the strain and hence the strain ratio to be zero. For other cases, the strain is given by equation A23.

$$\varepsilon = - \frac{{2\left( {\frac{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}}{{\left( {1 + \alpha_{2} \psi } \right)\left( {1 + 2\nu \alpha_{2} \psi } \right) + \left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}} - \frac{1}{2}} \right)}}{{{\text{GF}}\left( {\left( {1 + \nu } \right) + \left( {1 - \nu } \right)\left( {\frac{{\left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}}{{\left( {1 + \alpha_{2} \psi } \right)\left( {1 + 2\nu \alpha_{2} \psi } \right) + \left( {1 + \alpha_{4} \psi } \right)\left( {1 + 2\nu \alpha_{4} \psi } \right)}} - \frac{1}{2}} \right)} \right)}}$$
(A23)

Upon dividing the equation A23 with the equation of baseline strain, we can obtain the strain ratio.

Appendix B

Following steps were performed to establish the equation of the estimated crack path (shown in red dashed line in Fig. 25).

  1. i.

    The red solid line in Fig. 17a is used the initial guess for crack orientation obtained by fitting the best line to the centers of the sensors 1, 7, and 8. These sensors were localized using the algorithm presented in Box 2. Let the equation of the line be given by \(y = m_{0} x + c_{0}\). Both \(m_{0}\) and \(c_{0}\) are known.

  2. ii.

    Using this initial estimate of the crack path, the initial estimate on the \(\omega\) was obtained which is provided in Table 8.

  3. iii.

    Using the initial slope value, estimate the values of \(\omega\) for various values of \(c\) the intercept subject to the constraint that the line must intersect the sensors 1, 7, 8 and compute the \(\ell_{1}\)-norm between the strain ratio from the estimated line and the experimental strain ratios.

  4. iv.

    For each orientation that have \(\ell_{1}\)-norm better than the initial guess change (increase/decrease) the value of slope at a step size of 0.1 upto 0.5. This corresponds to ~ \(5.7^{^\circ } - 22.8^{^\circ }\). This is also subject to the constraint that the line must intersect sensors 1, 7, and 8 and compute the \(\ell_{1}\)-norm of the difference between the strain ratio from the estimated line and the experimental strain ratios.

  5. v.

    The line which has the minimum \(\ell_{1}\)-norm between the experimental and estimated strain ratios is chosen the crack path.

  6. vi.

    That final line is shown in Fig. 17b.

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Kumar, V., Acot, B., Aygun, L.E. et al. Detecting, localizing, and quantifying damage using two-dimensional sensing sheet: lab test and field application. J Civil Struct Health Monit 11, 1055–1075 (2021). https://doi.org/10.1007/s13349-021-00498-5

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