Ship-bridge collision monitoring system based on flexible quantum tunneling composite with cushioning capability

Zheng, Qiaofeng; Han, Baoguo; Ou, Jinping

doi:10.1088/1361-665x/aac362

Cited by 3 publications

(4 citation statements)

References 17 publications

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“…Because of the quality gap of the homemade sensors, the sensor output showed a lack of consistency due to impact energy level, but it was apparent that the sensors showed fairly linear impact responses to changes in both impact energy and distance. We compared the impact sensing properties of nano carbon composite sensors with another piezoresistive impact sensor made of nickel powder composites [52]. The nickel powder composite impact sensor also showed fairly good impact responses with consistency but the sensitivity could not be compared due to lack of information on the study.…”

Section: Impact Sensing Resultsmentioning

confidence: 99%

Impact paint sensor based on polymer/multi-dimension carbon nano isotopes composites

Kim

Choi

Baek

et al. 2019

Smart Mater. Struct.

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We presented a novel impact paint sensor made of piezoresistive nano-carbon composites and studied its characteristics. The paint sensors were fabricated with multi-walled carbon nanotube (MWCNT), exfoliated graphite nano-platelets (xGnP), and a hybrid type of the two nano-carbon fillers and were sprayed onto a carbon fiber-reinforced plastic panel for lab testing. In ball drop impact test, the MWCNT-xGnP-based hybrid sensor showed the best characteristics in impact energy sensing within the range 0.07-1.0 J. We also studied the piezoresistive mechanism due to dimensional variations of nano carbon isotopes for sensor design. Piezorestivity of nano-carbon sensor was significantly dominated the electrical contact variation of the electrical fillers in a matrix. This study is expected to provide a feasibility test for designing impact paint sensors with optimized sensitivity for a composite structural health monitoring.

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Section: Impact Sensing Resultsmentioning

confidence: 99%

Impact paint sensor based on polymer/multi-dimension carbon nano isotopes composites

Kim

Choi

Baek

et al. 2019

Smart Mater. Struct.

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“…A composite is produced from two or more constituent materials to achieve better performance than individual components [ 1 ]. They are classified into four categories based on the matrix constituent, such as (a) polymer matrix composites, (b) metal matrix composites, (c) ceramic matrix composites, and (d) quantum tunneling composites [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. Quantum tunneling composites (QTCs) are combinations of polymer composites having both dielectric elastomer and conductive metal particles.…”

Section: Introductionmentioning

confidence: 99%

“…Within the finished structure of QTC, the individual elements remain separate and unique, distinguishing composites from mixtures and solid solutions. QTCs are demonstrated to use different applications, such as smart textiles, foot wears, touch pads, display devices, NASA’s Robonaut, mp3 players, sporting materials, automotive, and life science applications, such as measuring blood pressure, making safe batteries, and extreme weather conditions [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. The QTC pills for such applications were generally made using primarily silicone as a non-conductive elastomer and Nickel as one of the conductive materials.…”

Section: Introductionmentioning

confidence: 99%

Smart Quantum Tunneling Composite Sensors to Monitor FKM and FFKM Seals

Periyasamy

Quartapella

Piacente

et al. 2023

Sensors

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Operators of industrial machinery relentlessly pursue improving safety, increasing productivity, and minimizing unplanned downtime. Elastomer seals are ubiquitous components of this machinery. In general, static seals are designed to be compressed at a fixed level of compression, taking gland geometry, loading condition, temperature range of operation, fluid media exposure, and other factors into account to ensure the safe operation of equipment. Over time, seals experience compression set, chemical-induced swelling, erosion, and other phenomena which can compromise the compressive force generated by the seal and cause leaking. This is particularly important in critical applications, where high pressure, high temperature, and aggressive media are present, and fluorinated elastomers are common materials for seals. Further, changes in operating conditions at manufacturing plants, either intentional or through regular process variation, create unknown operating conditions for seals. This unknown and variable application environment makes seal performance hard to predict. Therefore, machinery utilizing seals is, at best, serviced preventatively at certain intervals, where seals are removed, and the remaining useful life of the seal is unknown. This leads to unnecessary machinery downtime and increases consumable costs for manufacturers. In the worst case, the seal is run to failure, creating machinery and plant safety concerns. Both scenarios are undesirable for manufacturers using industrial machinery. This paper reports on the development of “smart” intrinsic self-sensing seals, which enable performance monitoring of the compression behavior of seals while in use. In addition, this paper examines quantum tunneling elastomeric composites (QTC) to demonstrate a method of component performance monitoring by modifying the underlying elastomeric material itself. This paper studies QTC sensor-based fluorinated (FKM) and per-fluorinated (FFKM) compositions, which are modified to incorporate varying levels of carbon nanostructure (CNS) material. The resulting seal’s resistive properties are shown to be a function of the level of compression, the first time this phenomenon has been demonstrated in high-performing FKM and FFKM seal materials.

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“…An enhanced structural health monitoring system using stream processing and artificial neural network techniques (SPANNeT) is developed by Khemapech et al [ 12 ] for wireless sensor networks to enable real-time data streaming and proper damage detection under impacts, which, however, does not address the constraints of battery power limits for long-term deployment. Zheng et al [ 13 ] proposed a flexible quantum tunneling composite with cushioning capability for ship-bridge collision monitoring, and simple rule-based conditions are used for damage warning. A wireless transmission system is planned for future study but has not been reported so far.…”

Section: Introductionmentioning

confidence: 99%

xImpact: Intelligent Wireless System for Cost-Effective Rapid Condition Assessment of Bridges under Impacts

Zhu

Hoang

et al. 2022

Sensors

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Bridge strikes by over-height vehicles or ships are critical sudden events. Due to their unpredictable nature, many events go unnoticed or unreported, but they can induce structural failures or hidden damage that accelerates the bridge’s long-term degradation. Therefore, always-on monitoring is essential for deployed systems to enhance bridge safety through the reliable detection of such events and the rapid assessment of bridge conditions. Traditional bridge monitoring systems using wired sensors are too expensive for widespread implementation, mainly due to their significant installation cost. In this paper, an intelligent wireless monitoring system is developed as a cost-effective solution. It employs ultralow-power, event-triggered wireless sensor prototypes, which enables on-demand, high-fidelity sensing without missing unpredictable impact events. Furthermore, the proposed system adopts a smart artificial intelligence (AI)-based framework for rapid bridge assessment by utilizing artificial neural networks. Specifically, it can identify the impact location and estimate the peak force and impulse of impacts. The obtained impact information is used to provide early estimation of bridge conditions, allowing the bridge engineers to prioritize resource allocation for the timely inspection of the more severe impacts. The performance of the proposed monitoring system is demonstrated through a full-scale field test. The test results show that the developed system can capture the onset of bridge impacts, provide high-quality synchronized data, and offer a rapid damage assessment of bridges under impact events, achieving the error of around 2 m in impact localization, 1 kN for peak force estimation, and 0.01 kN·s for impulse estimation. Long-term deployment is planned in the future to demonstrate its reliability for real-life impact events.

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Ship-bridge collision monitoring system based on flexible quantum tunneling composite with cushioning capability

Cited by 3 publications

References 17 publications

Impact paint sensor based on polymer/multi-dimension carbon nano isotopes composites

Impact paint sensor based on polymer/multi-dimension carbon nano isotopes composites

Smart Quantum Tunneling Composite Sensors to Monitor FKM and FFKM Seals

xImpact: Intelligent Wireless System for Cost-Effective Rapid Condition Assessment of Bridges under Impacts

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