Fiber optic bend sensor for in-process monitoring of polymeric composites

1997 ◽  
Vol 4 (3) ◽  
pp. 187-195 ◽  
Author(s):  
W. P. Wang ◽  
T. H. Hwang ◽  
E. Y. Shu ◽  
M. H. Vartanian ◽  
R. A. Ridilla
Keyword(s):  
Process Monitoring ◽  
Fiber Optic ◽  
Polymeric Composites ◽  
Bend Sensor

scholarly journals J044023 Molding process monitoring of FRP laminates by fiber-optic index sensors

2012 ◽  
Vol 2012 (0) ◽  
pp. _J044023-1-_J044023-5
Author(s):  
Tatsuro KOSAKA ◽  
Akihiro MATSUMOTO ◽  
Takuya KAJIKAWA ◽  
Atsushi KUTSUNA ◽  
Kazuhiro KUSUKAWA
Keyword(s):  
Process Monitoring ◽  
Fiber Optic ◽  
Molding Process

Near-infrared diffuse reflectance fiber optic spectroscopy for process monitoring applications

1999 ◽  
Author(s):  
Steven C. Switalski ◽  
Todd Colin ◽  
Neil Redden ◽  
Eric Stahlecker ◽  
Vijay Parthasarathy
Keyword(s):  
Process Monitoring ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Fiber Optic ◽  
Monitoring Applications

Simple Fiber-Optic-Based Sensors for Process Monitoring: An Application in Wine Quality Control Monitoring

2004 ◽  
Vol 58 (8) ◽  
pp. 1010-1019 ◽  
Author(s):  
Isabelle Noiseux ◽  
William Long ◽  
Alain Cournoyer ◽  
Marcia Vernon
Keyword(s):  
Quality Control ◽  
Process Monitoring ◽  
Fiber Optic ◽  
Wine Quality

Application of Improved BP Neural Networks Based on LM Algorithm in Characteristic Curve Fitting of Fiber-Optic Micro-Bend Sensor

2014 ◽  
Vol 889-890 ◽  
pp. 825-828 ◽  
Author(s):  
Shuo Ding ◽  
Xiao Heng Chang
Keyword(s):  
Fiber Optic ◽  
Characteristic Curve ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Testing System ◽  
Input And Output ◽  
Key Factor ◽  
Simulation Results ◽  
Lm Algorithm ◽  
Bend Sensor

As a key factor in a testing system, sensor nonlinearity has always been the study focus in the field of engineering and techniques. In order to accurately reflect the practical characteristics of a fiber-optic micro-bend sensor, Levenberg-Marguardt (LM) algorithm is used to optimize the correction of the weight values of standard back propagation neural network (BPNN). The learning process of improved BPNN based on LM algorithm (LM-BPNN) is also illustrated mathematically, and LM-BPNN is applied in fitting the input and output characteristic curve of a fiber-optic micro-bend sensor. The simulation results show that LM-BPNN is superior both in its convergence rate and fitting precision over standard BPNN.

High-power fiber optic cable with integrated active sensors for live process monitoring

2012 ◽  
Author(s):  
Ola Blomster ◽  
Mats Blomqvist ◽  
Hans Bergstrand ◽  
Magnus Pålsson
Keyword(s):  
Process Monitoring ◽  
High Power ◽  
Fiber Optic ◽  
Fiber Optic Cable ◽  
Active Sensors

Environmental considerations for fiber optic remote sensing systems in on-line process monitoring

1992 ◽  
Author(s):  
Richard D. Driver ◽  
James N. Downing ◽  
M. L. Brubaker ◽  
John D. Stark ◽  
Lubos J. B. Vacha ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Process Monitoring ◽  
Fiber Optic ◽  
Sensing Systems ◽  
On Line ◽  
Line Process ◽  
Remote Sensing Systems ◽  
Environmental Considerations
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