Sensing sheets based on large area electronics for structural health monitoring of bridges

2019 ◽  
Author(s):  
Vivek Kumar ◽  
Levent E. Aygun ◽  
Naveen Verma ◽  
James C. Sturm ◽  
Branko Glisic
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Large Area ◽  
Structural Health ◽  
Large Area Electronics

Strain Sensing Sheets for Structural Health Monitoring Based on Large-Area Electronics and Integrated Circuits

2016 ◽  
Vol 104 (8) ◽  
pp. 1513-1528 ◽  
Author(s):  
Branko Glisic ◽  
Yao Yao ◽  
Shue-Ting E. Tung ◽  
Sigurd Wagner ◽  
James C. Sturm ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Integrated Circuits ◽  
Health Monitoring ◽  
Strain Sensing ◽  
Large Area ◽  
Structural Health ◽  
Large Area Electronics

Large-Scale Sensing System Combining Large-Area Electronics and CMOS ICs for Structural-Health Monitoring

2014 ◽  
Vol 49 (2) ◽  
pp. 513-523 ◽  
Author(s):  
Yingzhe Hu ◽  
Warren S. A. Rieutort-Louis ◽  
Josue Sanz-Robinson ◽  
Liechao Huang ◽  
Branko Glisic ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Large Scale ◽  
Large Area ◽  
Structural Health ◽  
Sensing System ◽  
Large Area Electronics

scholarly journals Large-Area Resistive Strain Sensing Sheet for Structural Health Monitoring

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1386 ◽  
Author(s):  
Levent E. Aygun ◽  
Vivek Kumar ◽  
Campbell Weaver ◽  
Matthew Gerber ◽  
Sigurd Wagner ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Printed Circuit Board ◽  
Early Stage ◽  
Field Tests ◽  
Circuit Board ◽  
Gauge Factor ◽  
Peak Strain ◽  
Large Area ◽  
Structural Health

Damage significantly influences response of a strain sensor only if it occurs in the proximity of the sensor. Thus, two-dimensional (2D) sensing sheets covering large areas offer reliable early-stage damage detection for structural health monitoring (SHM) applications. This paper presents a scalable sensing sheet design consisting of a dense array of thin-film resistive strain sensors. The sensing sheet is fabricated using flexible printed circuit board (Flex-PCB) manufacturing process which enables low-cost and high-volume sensors that can cover large areas. The lab tests on an aluminum beam showed the sheet has a gauge factor of 2.1 and has a low drift of 1.5 μ ϵ / d a y . The field test on a pedestrian bridge showed the sheet is sensitive enough to track strain induced by the bridge’s temperature variations. The strain measured by the sheet had a root-mean-square (RMS) error of 7 μ ϵ r m s compared to a reference strain on the surface, extrapolated from fiber-optic sensors embedded within the bridge structure. The field tests on an existing crack showed that the sensing sheet can track the early-stage damage growth, where it sensed 600 μ ϵ peak strain, whereas the nearby sensors on a damage-free surface did not observe significant strain change.

scholarly journals Structural health monitoring: Closing the gap between research and industrial deployment

2018 ◽  
Vol 17 (5) ◽  
pp. 1225-1244 ◽  
Author(s):  
Peter Cawley
Keyword(s):  
Structural Health Monitoring ◽  
Condition Monitoring ◽  
Health Monitoring ◽  
Research Effort ◽  
Industrial Applications ◽  
Machine Condition ◽  
Large Area ◽  
Structural Health ◽  
Rotating Machine ◽  
Machine Condition Monitoring

There has been a large volume of research on structural health monitoring since the 1970s but this research effort has yielded relatively few routine industrial applications. Structural health monitoring can include applications on very different structures with very different requirements; this article splits the subject into four broad categories: rotating machine condition monitoring, global monitoring of large structures (structural identification), large area monitoring where the area covered is part of a larger structure, and local monitoring. The capabilities and potential applications of techniques in each category are discussed. Condition monitoring of rotating machine components is very different to the other categories since it is not strictly concerned with structural health. However, it is often linked with structural health monitoring and is a relatively mature field with many routine applications, so useful lessons can be read across to mainstream structural health monitoring where there are many fewer industrial applications. Reasons for the slow transfer from research to practical application of structural health monitoring include lack of attention to the business case for monitoring, insufficient attention to how the large data flows will be handled and the lack of performance validation on real structures in industrial environments. These issues are discussed and ways forward proposed; it is concluded that given better focused research and development considering the key factors identified here, structural health monitoring has the potential to follow the path of rotating machine condition monitoring and become a widely deployed technology.

Structural Health Monitoring Based on Electrical Impedance of a Carbon Nanotube Neuron

2006 ◽  
Vol 321-323 ◽  
pp. 140-145 ◽  
Author(s):  
In Pil Kang ◽  
Jong Won Lee ◽  
Gyeong Rak Choi ◽  
Joo Yung Jung ◽  
Sung Ho Hwang ◽  
...  
Keyword(s):  
Carbon Nanotube ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Electrochemical Impedance ◽  
Neural System ◽  
Large Area ◽  
Film Sensor ◽  
Structural Health ◽  
Structural Surface ◽  
The Cost

This paper introduces a new sensor design based on a carbon nanotube structural neuron for structural health monitoring applications. The carbon nanotube neuron is a thin and narrow polymer film sensor that is bonded or deposited onto a structure. The electrochemical impedance (resistance and capacitance) of the neuron changes due to deterioration of the structure where the neuron is located. A network of the long carbon nanotube neurons can form a structural neural system to provide large area coverage and an assurance of the operational health of a structure without the need for actuators and complex wave propagation analyses that are used with other SHM methods. The neural system can also reduce the cost of health monitoring by using biomimetic signal processing to minimize the number of channels of data acquisition needed to detect damage. The carbon nanotube neuron is lightweight and easily applied to the structural surface, and there is no stress concentration, no piezoelectrics, no amplifier, and no storage of high frequency waveforms. The carbon nanotube neuron is expected to find applications in detecting damage and corrosion in large complex structures including composite and metallic aircraft and rotorcraft, bridges, and almost any type of structure with almost no penalty to the structure.

scholarly journals Embedded Ultrasonics With Piezoelectric Wafer Active Sensors for Structural Health Monitoring of Thin-Wall Structures

Aerospace ◽  
2003 ◽  
Author(s):  
Victor Giurgiutiu
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Crack Detection ◽  
Thin Wall ◽  
Large Area ◽  
Active Sensors ◽  
Structural Health ◽  
Piezoelectric Wafer Active Sensors ◽  
Wall Structures ◽  
Pulse Echo

The capability of embedded piezoelectric water active sensors (PWAS) to perform in-situ ultrasonic nondestructive evaluation (NDE) is explored. Laboratory tests are used to prove that PWAS can satisfactorily perform Lamb wave transmission and reception. Subsequently, pulse-echo method for crack detection in an aircraft panel is illustrated. For large area scanning, a PWAS phased array is used to create the embedded ultrasonics structural radar (EUSR). In conclusion, opportunities for implementation into structural health monitoring applications and further research needs are discussed.

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