Crack Detection and Monitoring Using Passive Wireless Sensor

2009 ◽  
Author(s):  
Srikar Deshmukh ◽  
Irshad Mohammad ◽  
Manos Tentzeris ◽  
Terence Wu ◽  
Haiying Huang
Keyword(s):  
Spatial Resolution ◽  
Power Supply ◽  
Data Transmission ◽  
Crack Detection ◽  
High Spatial Resolution ◽  
Wireless Sensor ◽  
Large Area ◽  
Sensor Fabrication ◽  
Interrogation Technique ◽  
Characterization Procedure

This paper presents an antenna sensor that can detect and monitor crack remotely and passively. Since this antenna sensor does not need electric wires for power supply and data transmission, it has great potential to be implemented as large area sensor skin with high spatial resolution, simple configuration and remote-interrogation capability. The sensor fabrication, the sensor characterization procedure and the non-contact interrogation technique are presented. The experimental results demonstrated that the antenna sensor is sensitive to crack growth and can be interrogated remotely.

Design and Characterization of a Real Time, Large Area, High Spatial Resolution Particle Tracker Based on Scintillating Fibers

2013 ◽  
pp. 159-174 ◽  
Author(s):  
D. Lo Presti ◽  
D. L. Bonanno ◽  
F. Longhitano ◽  
C. Pugliatti ◽  
S. Aiello ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Large Area ◽  
Scintillating Fibers

Eddy current technique for testing large-area, high Tc superconducting films with high spatial resolution

Cryogenics ◽  
1995 ◽  
Vol 35 (3) ◽  
pp. 155-160 ◽  
Author(s):  
K. Wegendt ◽  
R.P. Huebener ◽  
R. Gross ◽  
Th. Träuble ◽  
W. Geweke ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Eddy Current ◽  
High Spatial Resolution ◽  
Superconducting Films ◽  
Large Area ◽  
High Tc ◽  
Current Technique

scholarly journals Fast large area reflectivity scans of wafers and solar cells with high spatial resolution

2017 ◽  
Vol 124 ◽  
pp. 166-173 ◽  
Author(s):  
Andreas Schütt ◽  
Stefanie Wahl ◽  
Sylke Meyer ◽  
Jens Hirsch ◽  
Dominik Lausch
Keyword(s):  
Solar Cells ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Large Area

scholarly journals Crack Detection Using Fiber Optic Distributed Sensor with High Spatial Resolution

2003 ◽  
Vol 41 (7) ◽  
pp. 29-33
Author(s):  
H. Kumagai ◽  
H. Iwaki ◽  
Sean Soon Leng Ong ◽  
K. Hotate
Keyword(s):  
Spatial Resolution ◽  
Crack Detection ◽  
Fiber Optic ◽  
High Spatial Resolution ◽  
Distributed Sensor

scholarly journals Large-Area, High Spatial Resolution Land Cover Mapping Using Random Forests, GEOBIA, and NAIP Orthophotography: Findings and Recommendations

2019 ◽  
Vol 11 (12) ◽  
pp. 1409 ◽  
Author(s):  
Aaron E. Maxwell ◽  
Michael P. Strager ◽  
Timothy A. Warner ◽  
Christopher A. Ramezan ◽  
Alice N. Morgan ◽  
...  
Keyword(s):  
Land Cover ◽  
Spatial Resolution ◽  
Classification Accuracy ◽  
High Spatial Resolution ◽  
Kappa Statistic ◽  
Data Availability ◽  
Computational Time ◽  
Land Cover Mapping ◽  
Large Area ◽  
Ancillary Data

Despite the need for quality land cover information, large-area, high spatial resolution land cover mapping has proven to be a difficult task for a variety of reasons including large data volumes, complexity of developing training and validation datasets, data availability, and heterogeneity in data and landscape conditions. We investigate the use of geographic object-based image analysis (GEOBIA), random forest (RF) machine learning, and National Agriculture Imagery Program (NAIP) orthophotography for mapping general land cover across the entire state of West Virginia, USA, an area of roughly 62,000 km2. We obtained an overall accuracy of 96.7% and a Kappa statistic of 0.886 using a combination of NAIP orthophotography and ancillary data. Despite the high overall classification accuracy, some classes were difficult to differentiate, as highlight by the low user’s and producer’s accuracies for the barren, impervious, and mixed developed classes. In contrast, forest, low vegetation, and water were generally mapped with accuracy. The inclusion of ancillary data and first- and second-order textural measures generally improved classification accuracy whereas band indices and object geometric measures were less valuable. Including super-object attributes improved the classification slightly; however, this increased the computational time and complexity. From the findings of this research and previous studies, recommendations are provided for mapping large spatial extents.

High-Spatial-Resolution Diffusion Length Measurements in Polycrystalline GaAs

1981 ◽  
Vol 5 ◽  
Author(s):  
Robert M. Fletcher ◽  
D. Ken Wagner ◽  
G. W. Wicks ◽  
J. M. Ballantyne
Keyword(s):  
Nondestructive Evaluation ◽  
Spatial Resolution ◽  
Minority Carrier ◽  
Diffusion Length ◽  
High Spatial Resolution ◽  
Small Step ◽  
Large Area ◽  
Minority Carrier Diffusion Length ◽  
Length Measurements

ABSTRACTA technique for making rapidly-scanned, high-spatial resolution measurements of minority-carrier diffusion length is applied to the characterization of polycrystalline GaAs. Measurements on a large-grained n-type epitaxial layer show gradual variations of hole diffusion length from 0.1µm to l.lµm across the wafer as well as occasional small step changes at grain boundaries. By trading resolution for speed, the technique would be well suited to the nondestructive evaluation of large-area epitaxial layers.

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