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

Kumar, Vivek; Acot, Bianca; Aygün, Levent E.; Wagner, S.; Verma, Naveen; Sturm, James C.; Glišić, Branko

doi:10.1007/s13349-021-00498-5

Cited by 9 publications

(6 citation statements)

References 51 publications

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“…Strain field mapping provides a comprehensive distribution of strain across an entire structure, thus opens up numerous opportunities that cannot be achieved by conventional discrete strain sensors. It validates the outcomes of finite element analysis (FEA) simulations and enhances confidence in results 1 , 2 , It enables timely detection of structural anomalies in structural health monitoring 3 , 4 , and aids in health condition assessment by identifying heterogeneous deformations in human body 5 . Currently, optical methods are predominantly used for full-field strain mapping due to their high spatial resolution 6 .…”

Section: Introductionmentioning

confidence: 58%

High-density, highly sensitive sensor array of spiky carbon nanospheres for strain field mapping

Mei,

Yi,

Zhao

et al. 2024

Nat Commun

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While accurate mapping of strain distribution is crucial for assessing stress concentration and estimating fatigue life in engineering applications, conventional strain sensor arrays face a great challenge in balancing sensitivity and sensing density for effective strain mapping. In this study, we present a Fowler-Nordheim tunneling effect of monodispersed spiky carbon nanosphere array on polydimethylsiloxane as strain sensor arrays to achieve a sensitivity up to 70,000, a sensing density of 100 pixel cm−2, and logarithmic linearity over 99% within a wide strain range of 0% to 60%. The highly ordered assembly of spiky carbon nanospheres in each unit also ensures high inter-unit consistency (standard deviation ≤3.82%). Furthermore, this sensor array can conformally cover diverse surfaces, enabling accurate acquisition of strain distributions. The sensing array offers a convenient approach for mapping strain fields in various applications such as flexible electronics, soft robotics, biomechanics, and structure health monitoring.

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Section: Introductionmentioning

confidence: 58%

High-density, highly sensitive sensor array of spiky carbon nanospheres for strain field mapping

Mei,

Yi,

Zhao

et al. 2024

Nat Commun

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“…Figure S18c (Supporting Information) shows the change in the relative resistance response, which can be explained by the low viscosity after treatment which affects the low area of contact in the 45° direction, resulting in change surface area, compared to the hydrogel before treatment. [ 49,50 ] Figure S18d (Supporting Information) further highlights the increased responsiveness of the GSH‐treated M‐Hydrogel, as it can detect a drop of water falling on it compared to the untreated hydrogel. [ 45,51 ] The higher responsiveness demonstrated by the M‐Hydrogel after GSH treatment was attributed to the release of cPDA, which contributes toward a higher conductivity.…”

Section: Resultsmentioning

confidence: 99%

A Self‐Reporting Mineralized Conductive Hydrogel Sensor with Cancer‐Selective Viscosity, Adhesiveness, and Stretchability

Roy

Lee

Ryplida

et al. 2023

Adv Funct Materials

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A cancer‐selective self‐reporting sensor based on a redox‐responsive mineralized conductive hydrogel (M‐Hydrogel) is proposed with cancer‐specific viscosity, adhesive strength, stretchability, tunable conductivity, and fluorescence. The redox‐triggered release of carbonized polydopamine (cPDA) from the loaded disulfide‐crosslinked polymer dots (PD@cPDA) in the hydrogel matrix modulates the macroporous structure responsible for self‐recognizable cancer sensing and photothermal activity for cancer therapy. The self‐reporting nature of the M‐Hydrogel sensor is highlighted when in vicinity of a high glutathione (GSH) level owing to the controllable pore size and H‐bonding by cPDA, as confirmed by experiments on cancer cells (HeLa, PC3, B16‐F10‐GFP, and SNU‐C2A) and normal cells (CHO‐K1). The lower viscosity during syringe test along with the exceptional adhesiveness and stretchability with various cancer cells, combined with a high wireless pressure‐sensing response absent in normal conditions, confirms the dependence of self‐recognizable behavior on the cancer microenvironment. The M‐Hydrogel demonstrates excellent ex situ sensing with tumor ablation, after implantation in mice xenografted with HeLa cells, with the wireless sensing system, enabling real‐time analysis coupled with the upregulation of pro‐apoptotic markers P53 and BAX in the tumor. Therefore, this self‐reporting sensor may facilitate a strategy for innovative and convenient cancer diagnostics.

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“…When a fatigue crack occurs, strain measurements can be effective for crack detection and monitoring because of the sensitivity of strain change to the opening and closing of the crack, especially when the strain sensors are installed close to the crack [ 18 ]. However, the point and distributed one-dimensional sensors may not provide adequate information for fatigue crack monitoring since their small sizes hinder their ability to cover an adequate surface of fatigue crack prone areas [ 18 , 19 , 20 , 21 ]. Moreover, the limited ductility of those sensors causes them to fail under the extreme strain demand due to crack formation, and using a dense array of them to cover large areas to provide adequate surface coverage may be impractical and expensive [ 18 , 19 , 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, the point and distributed one-dimensional sensors may not provide adequate information for fatigue crack monitoring since their small sizes hinder their ability to cover an adequate surface of fatigue crack prone areas [ 18 , 19 , 20 , 21 ]. Moreover, the limited ductility of those sensors causes them to fail under the extreme strain demand due to crack formation, and using a dense array of them to cover large areas to provide adequate surface coverage may be impractical and expensive [ 18 , 19 , 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

“…To address the above issues, various large-area sensors were proposed to measure strain over a large area. For instance, strain sensing sheets which can cover large areas were proposed for damage and crack detections [ 19 , 22 , 23 ], in which laboratory experiments and a pedestrian bridge were used to validate the proposed sensors for damage and crack detections. An antenna sensor was developed for monitoring fatigue crack growth and opening in a compact tension (C(T)) specimen under fatigue loading [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Structural Health Monitoring of Fatigue Cracks for Steel Bridges with Wireless Large-Area Strain Sensors

Taher

Jeong

et al. 2022

Sensors

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This paper presents a field implementation of the structural health monitoring (SHM) of fatigue cracks for steel bridge structures. Steel bridges experience fatigue cracks under repetitive traffic loading, which pose great threats to their structural integrity and can lead to catastrophic failures. Currently, accurate and reliable fatigue crack monitoring for the safety assessment of bridges is still a difficult task. On the other hand, wireless smart sensors have achieved great success in global SHM by enabling long-term modal identifications of civil structures. However, long-term field monitoring of localized damage such as fatigue cracks has been limited due to the lack of effective sensors and the associated algorithms specifically designed for fatigue crack monitoring. To fill this gap, this paper proposes a wireless large-area strain sensor (WLASS) to measure large-area strain fatigue cracks and develops an effective algorithm to process the measured large-area strain data into actionable information. The proposed WLASS consists of a soft elastomeric capacitor (SEC) used to measure large-area structural surface strain, a capacitive sensor board to convert the signal from SEC to a measurable change in voltage, and a commercial wireless smart sensor platform for triggered-based wireless data acquisition, remote data retrieval, and cloud storage. Meanwhile, the developed algorithm for fatigue crack monitoring processes the data obtained from the WLASS under traffic loading through three automated steps, including (1) traffic event detection, (2) time-frequency analysis using a generalized Morse wavelet (GM-CWT) and peak identification, and (3) a modified crack growth index (CGI) that tracks potential fatigue crack growth. The developed WLASS and the algorithm present a complete system for long-term fatigue crack monitoring in the field. The effectiveness of the proposed time-frequency analysis algorithm based on GM-CWT to reliably extract the impulsive traffic events is validated using a numerical investigation. Subsequently, the developed WLASS and algorithm are validated through a field deployment on a steel highway bridge in Kansas City, KS, USA.

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

Cited by 9 publications

References 51 publications

High-density, highly sensitive sensor array of spiky carbon nanospheres for strain field mapping

High-density, highly sensitive sensor array of spiky carbon nanospheres for strain field mapping

A Self‐Reporting Mineralized Conductive Hydrogel Sensor with Cancer‐Selective Viscosity, Adhesiveness, and Stretchability

Structural Health Monitoring of Fatigue Cracks for Steel Bridges with Wireless Large-Area Strain Sensors

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